Economics and Law of Artificial Intelligence: Finance, Economic Impacts, Risk Management and Governance 3030642534, 9783030642532

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Georgios I. Zekos

Economics and Law of Artificial Intelligence Finance, Economic Impacts, Risk Management and Governance

Economics and Law of Artificial Intelligence

Georgios I. Zekos

Economics and Law of Artificial Intelligence Finance, Economic Impacts, Risk Management and Governance

Georgios I. Zekos International Hellenic University Serres, Greece

ISBN 978-3-030-64253-2 ISBN 978-3-030-64254-9 https://doi.org/10.1007/978-3-030-64254-9

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© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG. The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

To my lovely wife ΣΟΦIΑ ΠPΟΔPΟMΟΥ ΓPΗΓΟPIΑΔΟΥ & to my son IΩΑΝΝΗΣ-MΑPIΝΟΣ ΖΕKΟΣ

Contents

Part I

Economics of Artificial Intelligence

1

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

3

2

E-Globalization and Digital Economy . . . . . . . . . . . . . . . . . . . . . . . 2.1 Cyberspace Settings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Cyberspace Governance . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Digital Economy Background . . . . . . . . . . . . . . . . . . . . . . . . 2.4 Digital Economy Developments . . . . . . . . . . . . . . . . . . . . . . . 2.5 Finance and Globalization . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.6 From Conventional Globalization to E-Globalization . . . . . . . . 2.7 Fintech . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.8 Globalization, AI, and Accounting . . . . . . . . . . . . . . . . . . . . . 2.9 Logistics and E-Commerce . . . . . . . . . . . . . . . . . . . . . . . . . . 2.10 Networks and Logistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

13 13 19 22 23 26 27 33 41 43 61 65

3

Management and Corporate Governance . . . . . . . . . . . . . . . . . . . . 3.1 Digital Governance and Digital Platforms . . . . . . . . . . . . . . . . 3.2 DLT, Crypto-Asset Holders, and Digital Governance . . . . . . . . 3.3 Blockchain and Fiduciary Duties . . . . . . . . . . . . . . . . . . . . . . 3.4 Corporate Governance Theories . . . . . . . . . . . . . . . . . . . . . . . 3.5 Governance Structures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.6 Corporate Governance Externalities . . . . . . . . . . . . . . . . . . . . 3.7 The Governance Features of Venture Capital . . . . . . . . . . . . . 3.8 Characteristics of Blockchain Governance . . . . . . . . . . . . . . . . 3.9 Expectations and Performance Management . . . . . . . . . . . . . . 3.10 Behavioral Portfolio Management . . . . . . . . . . . . . . . . . . . . . 3.11 Management of Financial Enterprises . . . . . . . . . . . . . . . . . . . 3.12 Operational Line Management . . . . . . . . . . . . . . . . . . . . . . . . 3.13 Supply Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

67 67 70 78 83 86 93 93 105 110 111 112 113 115 115 vii

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Contents

4

Artificial Intelligence Governance . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Artificial Intelligence Governance . . . . . . . . . . . . . . . . . . . . . 4.2 AI and Corporate Governance . . . . . . . . . . . . . . . . . . . . . . . . 4.3 Machine Learning and Management . . . . . . . . . . . . . . . . . . . . 4.4 AI and Corporate Management . . . . . . . . . . . . . . . . . . . . . . . 4.5 AI’s Managerial Involvement . . . . . . . . . . . . . . . . . . . . . . . . . 4.6 AI and Vehicles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

117 117 119 132 135 139 144 145

5

Risk Management Developments . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1 Risk, GDPR, and AML . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2 Defining Risk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3 Managing Risks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.4 Risk Factors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.5 Risk Management and Governance . . . . . . . . . . . . . . . . . . . . . 5.6 Internal–External Governance Mechanisms . . . . . . . . . . . . . . . 5.7 Strengthening Internal Governance Mechanisms . . . . . . . . . . . 5.8 Risk Management and Corporate Governance in EU . . . . . . . . 5.9 Defining Risk Management . . . . . . . . . . . . . . . . . . . . . . . . . . 5.10 The Limits of Risk Management . . . . . . . . . . . . . . . . . . . . . . 5.11 Big Data: Risk Management . . . . . . . . . . . . . . . . . . . . . . . . . 5.12 Risk Management Implications and Finance . . . . . . . . . . . . . . 5.13 Corporate Governance and Finance Tools . . . . . . . . . . . . . . . . 5.14 Enterprise Risk Management . . . . . . . . . . . . . . . . . . . . . . . . . 5.15 Operational Risk Management . . . . . . . . . . . . . . . . . . . . . . . . 5.16 Financial Risk Management . . . . . . . . . . . . . . . . . . . . . . . . . . 5.17 Banks Risk Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.18 CSR as Risk Management . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.19 Risk Management and Compliance . . . . . . . . . . . . . . . . . . . . . 5.20 Pandemic Risk Management . . . . . . . . . . . . . . . . . . . . . . . . . 5.21 COVID-19 and Risk Management . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

147 147 154 158 158 163 167 173 174 180 184 189 190 196 199 207 210 216 220 220 223 227 231

6

AI Risk Management . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.1 AI Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2 The Globalization of Information and Its Consequences . . . . . . 6.3 AI Networks Vs. Human Networks . . . . . . . . . . . . . . . . . . . . 6.4 Automated Decision-Making . . . . . . . . . . . . . . . . . . . . . . . . . 6.5 AI and Risks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.6 Transforming Governance . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.7 AI and Governance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.8 AI in Banks’ Governance . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.9 AI in Audit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.10 Chief Legal Officer and AI Management . . . . . . . . . . . . . . . . 6.11 AI and Healthcare Industry . . . . . . . . . . . . . . . . . . . . . . . . . .

233 233 237 238 239 248 253 255 260 263 266 269

Contents

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6.12 Unregulated Artificial Intelligence . . . . . . . . . . . . . . . . . . . . . 6.13 AI and EU Trade . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.14 AI and Labor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6.15 AI in Finance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Part II

272 273 275 282 288

Law of Artificial Intelligence

Econometric Analysis on AI Economy . . . . . . . . . . . . . . . . . . . . . . . 7.1 Econometric Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.2 AI and IPRs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.3 Econometric Outcomes Zekeuipr Index . . . . . . . . . . . . . . . . . 7.3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.3.2 A Linear Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.3.3 Empirical Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.3.4 Linear Results Regarding GDP Growth and Trade . . . . 7.3.5 Nonlinear Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.3.6 Linear Results Regarding Trade in EU . . . . . . . . . . . . . 7.3.7 Linear Results Regarding GDP Growth in Relation to FDI Inflows Merchandise and Services/Tertiary Sector OLS Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7.3.8 Empirical Results for Zekipr6 . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

339 342 346

8

Electronic Technology and the Law . . . . . . . . . . . . . . . . . . . . . . . . 8.1 AI History . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.2 Blockchain and the Law . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8.3 Legalizing Machine Learning . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

349 349 351 357 359

9

Legalizing Artificial Intelligence . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.1 Characteristics of AI Vs. Humans . . . . . . . . . . . . . . . . . . . . . . 9.2 The Worthiness of AI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.3 AI Legal Personality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.4 From Traditional Legal Personhood to AI Legal Personhood . . 9.5 AI Entities Accountability . . . . . . . . . . . . . . . . . . . . . . . . . . . 9.6 E-Persons and Liability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

361 361 365 366 369 381 391 399

10

AI and Legal Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.1 Legal Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.2 AI and the Rule of Law . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.3 From the Rule of Law to the AI Rule of Law . . . . . . . . . . . . . 10.4 Al and Administration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.5 Al and Common Law . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.6 Al and Companies Responsibility . . . . . . . . . . . . . . . . . . . . . .

401 401 403 411 423 429 431

7

291 291 296 303 303 305 307 321 322 336

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Contents

10.7 AI and Security Rights . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.8 AI and Criminal Law . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.9 Al and Discrimination Law . . . . . . . . . . . . . . . . . . . . . . . . . . 10.10 Regulating Bias and Digital Platforms . . . . . . . . . . . . . . . . . . 10.11 AI, Computation, and Digital Justice . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

436 438 444 448 452 459

11

AI and IPRs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.1 IPRs for Data-Centric Technologies . . . . . . . . . . . . . . . . . . . . 11.2 Al and Patents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.3 AI and Copyright . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.4 AI and Fair Use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.5 Software and Law . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

461 461 471 479 485 487 489

12

AI and International Law . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.1 Legal Outline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.2 Al in Weaponry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.3 AI and International Law . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12.4 AAI Rule of Law and AAI International Law . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

491 491 500 507 512 527

13

Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 529

Part I

Economics of Artificial Intelligence

Chapter 1

Introduction

Artificial intelligence is becoming global and so, it is encompassing various industries and transforming commerce, which means that AI is having tremendous economic consequences akin to transformational technologies of the past, such as electrification, manufacturing, and information technology. It could be said that artificial intelligence (AI) encompasses the development of computers able to engage in human-like thought processes such as learning, reasoning, and selfcorrection.1 It is worth noting that the term “artificial intelligence” suggests equivalence with human intelligence. In other words, AI can be seen as the replacement of human brain and activity by machines’ thinking and activity, which is currently human made, and we have not arrived to the point where machines can generate their own intelligence. Machine learning is a subset of AI that utilizes statistical, databased methods to progressively expand the performance of computers on a given task, without humans reprogramming the computer system to achieve enhanced performance. First of all, AI can reproduce physical human processes through machines, making routine tasks more competent, such as attaching the front bumper of a car in an assembly line. Moreover, AI can also make possible “large-scale automation of entire groups of tasks, including repetitive intellectual tasks previously performed by human beings” and so, it seems that more than just mimicking

1 Phillipe Aghion et al., Artificial Intelligence and Economic Growth (Nat’l Bureau of Econ. Research, Working Paper No. 23928, 2017) (defining artificial intelligence as “the capability of a machine to imitate intelligent human behavior [or] an agent’s ability to achieve goals in a wide range of environments.”; Sean Semmler & Zeeve Rose, Comment, Artificial Intelligence: Application Today and Implications Tomorrow, 16 Duke L. & Tech. Rev. 85, 86 (2017–2018) (defining artificial intelligence as “the process of simulating human intelligence through machine processes”); The Petrie-Flom Center for Health Law Policy, Biotechnology, and Bioethics at Harvard Law School, Black-Box Medicine: Legal and Ethical Issues: A Health Policy and Bioethics Consortium (February 8, 2019) (describing the “black-box” of artificial intelligence algorithms as opaque computational models to make decisions).

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 G. I. Zekos, Economics and Law of Artificial Intelligence, https://doi.org/10.1007/978-3-030-64254-9_1

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the physical aspects of humans, AI simulates and exceeds human mental processes.2 Drones, robots, genetic engineering, self-driving, autonomous vehicles, and renewable energy are technological advancements the globe has seen lately. AI has transformed the human population in terms of technology, leading to the rise of new devices and tools that are vital in doing business, education, and communication such as machine learning, deep learning, biometrics identification, speech recognition, and natural language generation (NLG). All these technologies advance human interaction with machines to facilitate most operations such as biometric identification uses many devices to improve the security of data. It has to be taken into account that the right of freedom of expression and the right of freedom of science cannot be restricted. It is worth noting that algorithmic decisions influence everyone, often without their knowledge. Algorithmic decision-making presents multiple benefits to society and so, algorithms surpass human abilities, and the set of those tasks is escalating. The algorithm engages in its own feature selection, adding layers of features that are used to map real-world data to a specific outcome and so, amending the weight given to each neuron and type of information, which means that deep learning does not entail a data scientist to interfere where its predictions are insufficient and so, the neural network will make decisions. It seems that presently algorithms are never entirely autonomous and so, any decision-making algorithm necessitates a human to decide the desired output under a conditional probability. It has to be taken into consideration that algorithmic development happens more swiftly than past innovation cycles to some extent for the reason that the software on which AI runs is developed, erased, and reconstructed with rather fewer investments in physical infrastructure and resources. Are there cons concerning AI technology? It is worth noting that a defective algorithm results in the failure to the accomplishment of aims and ending up being positively destructive. Moreover, AI assembles information from cyberspace that reproduces bogus data and since the information is contaminated, the algorithm will be unable to distinguish among “good” and “bad” information. Furthermore, AI is a software can be hacked, pirated, or get corrupted. Additionally, AI has an opacity problem, and an increase in complexity makes the AI opaque named as a “black box,” indicating the inability of human beings to understand what the machines are doing when they are teaching themselves that is improvising itself without any human interference. AI and machine learning focused on the generation of mechanisms not only for the management and integrity of data but also for its marketization. It has to be taken into account that the purpose of AI is to filter the noise, find meaning, and act upon it, 2

Michael Copeland, What’s the Difference Between Artificial Intelligence, Machine Learning, and Deep Learning?, NVIDIA BLOG (July 29, 2016), https://blogs.nvidia.com/blog/2016/07/29/whatsdifference-artificial-intelligence-machine-learningdeep-learning-ai; Yann Ménière & Ilja Rudyk, The Fourth Industrial Revolution from the European Patent Office Perspective, in Intellectual Property And Digital Trade In The Age Of Artificial Intelligence And Big Data 31, 31 (Xavier Seuba, Christophe Geiger, & Julien Penin eds, June 2018), https://www.ictsd.org/sites/default/files/ research/ceipi-ictsd_issue_5_final_0.pdf.

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finally with greater precision and better outcomes than humans reach on their own. The evolving intelligence of machines is a powerful tool to solve problems and to generate new ones and so, improvements in AI herald not just a new age in computing, but also present new threats to social values and constitutional rights. It is worth noting that AI-based technologies gradually penetrate areas such as transportation, health, education, justice, news and entertainment, and commerce underlining the significance of the context for which AI systems are developed and in which they are embedded. Maybe the central attribute of many AI systems is the changeable degrees to which they influence human autonomy and shift it away from human beings toward machines, with actually deep effects also for concepts such as the profession and professionalism. It is worth mentioning here that AI implementation demands both the ability to adapt public infrastructure to fit AI innovations and a private sector commercializing AI into viable goods. Blockchain technology is transformative for every human practice that utilizes recordkeeping. If blockchain technology accomplishes even a small part of its anticipated prospective, then soon it will replace many critical infrastructures within societies, from property records to payment and voting systems. Moreover, if blockchain technology ends up enabling our most fundamental social infrastructures, then the governance processes for generating, upholding, and changing the technology must be examined carefully as they will influence the resilience of the technology, along with any infrastructure that comes to rely on it.3 Furthermore, when it comes to technological revolution, governments have historically been wary and so, China at first resisted technological transformation owing to its prospective to activate social change. Afterwards the state utilized technology to its advantage and so, China has become a key actor in technology generally and AI specifically.4 It has to be taken into account that AI in the wrong hands is very dangerous and the UK and US governments have not involved in shaping or controlling AI for the democratic public good, instead leaving it to be molded and controlled by a small group of tech company controllers, in their own

3 Angela Walch, ‘The Bitcoin Blockchain as Financial Market Infrastructure: A Consideration of Operational Risk’[2015]18 NYU J Legislation and Public Policy837 (considering the operational risks created by informal governance processes in Bitcoin and their implications for its suitability as financial market infrastructure); Angela Walch, ‘Open-Source Operational Risk: Should Public Blockchains Serve as Financial Market Infrastructures?’ in David LEE Kuo Chuen and Robert D Deng (eds), Handbook of Blockchain, Digital Finance, and Inclusion Vol. 2 (Elsevier Academic Press 2017) (exploring the operational risks raised by use of grassroots open source software development practices in the use of public blockchains as financial market infrastructures). 4 R. Veugelers (2017) The challenge of China’s rise as a science and technology powerhouse, Bruegel Policy Contribution, Issue n ̊19, July http://bruegel.org/wp-content/uploads/2017/07/PC19-2017.pdf; K-F. Lee (2017) The Real Threat of Artificial Intelligence, The New York Times, 24 June, https://www.nytimes.com/2017/06/24/opinion/sunday/artificial-intelligence-economicinequality.html.

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interests. Furthermore, it seems that autocratic models of governance stemming from the US and China dominate the advancement of AI globally.5 Due to their superior performance in data gathering and processing, big data analytics, AI, and machine learning are supposed to influence all operational, as well as internal control matters, from strategy setting to risk management and compliance. It has to be taken into account that while humans have core data at their disposal and dynamically use only these data for decisions, technology take into account not only core but also apparently unrelated data. Technology is said to be unbiased, notwithstanding in the limited sense that technology does not follow its own agenda and is not itself subject to humans’ cognitive biases. It could be said that machines neutralize the “groupthink” and the strong social pressure against the expression of dissent in boardrooms. Hence, it is worth noting the likelihood of imposing the risks linked with blockchain’s service on the platform operator. Taking into account that only the blockchain platform operator is able to translate risk into cost, there is a need for a blockchain platform operator to be insured, which means that if blockchain transactions or smart contracts are destined to grow in the future, the greatness of the risk will proportionately augment.6 It is argued that shareholders will no longer need boards to make sure that managers do not deviate from the strategies and policies that maximize shareholder value, for the reason that shareholders will be able to do the supervising themselves and so, there will be no essential for boards to mediate between the corporation and its management on the one hand, and shareholders on the other. Are people prepared for the challenges presented by tech developments? Will people be replaced, partially or fully, by AI? It has to be taken into account that the technologies of the Fourth Industrial Revolution confront international governance and cooperation due to the fact that there is no institutional focal point for technology governance in the international system, just as there is not an integrated focal point for such policy in national governments. In addition, corporate governance is about management decisionmaking, and so, it is inevitable that social norms, national culture, and structures play a central role, which varies from nation to nation. While the world economy is global, law, regulation, politics, and society are still largely national, only gradually emerging from bounds forced by the modern international or Westphalian states system. Moreover, globalization and the revolution in information technology have altered the economic and political meaning of space and so, borders are “transcended” rather than crossed, relations become

5

A. Perkins (2018) Government to review law before self-driving cars arrive on UK roads, The Guardian, 6 March, https://www.theguardian.com/technology/2018/mar/06/self-driving-cars-inuk-riding-on-legalreview. 6 Matthew Dyson and Sandy Steel, ‘Risk and English Tort Law’ in Dyson (ed), Regulating Risk through Private Law (Intersentia 2018) 23. Rene Demogue, ‘Fault, risk, and apportionment of loss in responsibility’ (1918) 13 Ill L Rev 308.

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Introduction

7

progressively “supraterritorial” as distance, borders, and geographic space itself lose economic and political importance. The term governance designates all regulations intended for organization and centralization of human societies on a global scale. Moreover, governance conveys formal political institutions coordinating and controlling independent social relations having the capacity to enforce, by force, their decisions. Which the capacity of enforcement is and by whom global economic governance is imposed in economic globalization? Globalization is requesting for new kinds of governance such as governance without government, at least without state governments in their traditional capacities as new institutions are formed or strengthened. The new kinds of governance often raise critical questions of legitimacy. Globalization creates a larger space that of global space challenging the current capacity of the legal formations such as international law, courts, and arbitration. One consequence of globalization is that on an international level, nation-states have gradually more to function through the mode of horizontal power. The corporate governance focuses on the internal structure, rules, and procedures of the board of directors. Good governance implies that the corporation is functioning for the optimal benefit of the stakeholders involved and so, adoption of better corporate governance practices offers the long-term stability and growth to the corporation, which means that it facilitates in building the confidence among the stakeholders along with prospective stakeholders. Investors are paying higher price to the corporations whom adhere the international governance norms. Moreover, effective corporate governance lessens the perceived risks, therefore reducing the capital cost and aids the Board of Directors to take quick and better decisions. The application of principles of corporate governance increases engagement and longterm relations of the stakeholders avoiding mismanagement and refining the method of capital use giving support in diminishing the level of risk in the organization through nonstop involvement in creative practices. Enterprise risk management (ERM) is decisive for firms functioning in the global industry in order to accomplish their highest long-run expected values. ERM manages the risk across all parts of the organization so that, at any given time, it gains just the optimal risk taking in order to engage in strategic objectives.7 The management of corporations organizes the efforts of individuals in order to achieve aims and objectives using available resources resourcefully and efficiently.8 Management is not merely the handling of a mechanism. Moreover, management has as its leading purpose the satisfaction of a range of stakeholders. In most models of management and governance, shareholders vote for the board of directors, and the board then employs senior management. Asset pricing, portfolio maximization, and risk management have always been the central focuses in the banks, insurance firms, and personal investment. Risk

7

Frasier J. & Simkins B. Enterprise Risk Management: Today’s Leading Research and Best Practices for Tomorrow’s Executives. Wiley, 2010. 8 “Management”. Business Dictionary.

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management is the processes via which management identifies, analyzes, and reacts properly to risks affecting the organization’s business objectives. The answer to risks typically depends on their perceived gravity and implicates controlling, avoiding, accepting, or transferring them to a third party. However, organizations manage a wide range of risks such as technological risks, commercial/financial risks, information security risks, etc. Furthermore, risk management is the identification, assessment, and prioritization of risks followed by corresponding and efficient use of resources to diminish, supervise, and control the likelihood and/or influence of adverse events or to exploit the upcoming chances.9 Moreover, risk management is a two-step course: firstly, uncovering what risks exist in an investment and secondly dealing with those risks in a way best-suited to a corporation’s investment objectives. It is worth mentioning that while the twentieth century is considered the epoch of management, the twentyfirst century is expected to be more focused on governance and e-governance. Moreover, both terms tackle control of enterprises but governance includes always an assessment of underlying rationale and legality. Globalization brought new global governance mechanisms to which civil society and private actors, along with governments, contribute knowledge and capital. The global governance mechanisms consist of networks of private and public actors relying on voluntary action and having only weak enforcement measures.10 Corporate governance is, to a great extent, a set of means through which outside investors protect themselves against expropriation by the insiders. Information problems and managerial incentives naturally restrict the efficiency of corporate governance in public corporations.11 Effective corporate governance restricts managerial selfinterest and protects shareholder interests managing the interests of multiple stakeholders and so, settling the conflicts of interest between shareholders and noninvesting stakeholders. MNEs are driving the globalization process and the largest and the most powerful belong to the most advanced industrialized countries. The sustainability of corporate growth requires a national government support, ever declining trade barriers, free flow of capital, a viable and favorable legal, economic, financial and technological environment, and host governments friendlier to market-driven economies. Moreover, the leaders of MNEs are antagonizing to get a clear view on their future expansion and to build their potential world market domination and so, often they avoid and/or exceed the economic, legal, and political traditional structures, which means that they consider themselves as the eventual agent of revolution and the 9 Hubbard, Douglas (2009). The Failure of Risk Management: Why It’s Broken and How to Fix It. John Wiley & Sons. p. 46. ISO/DIS 31000 (2009). Risk management — Principles and guidelines on implementation. International Organization for Standardization. 10 Braithwaite, J., and P. Drahos. 2000. Global Business Regulation. Cambridge, UK: Cambridge University Press. 11 Miller, M.: 2005, ‘Is American corporate governance fatally flawed?’, in D. Chew and S. Gillan (eds.), Corporate Governance at the Crossroads: A Book of Readings (Irwin Mcgraw-Hill, Boston, MA).

1

Introduction

9

ultimate driver of the global economy. In addition, the leaders believe that government policy should be regarded as a way for achieving their eventual economic interest. Do market forces determine which technology will be used? Is it the technology that is used which dictates that the market must be molded to fit technology’s requirements? Nowadays, companies can transfer advanced technology to countries with low labor costs, and concurrently exploit the advantages of cheap capital in capital-rich countries. As a consequence of enhanced global mobility, a new capitalist world economy has emerged, and key feature is a massive migration of capital from the industrialized countries to low-cost production sites in the third world. The cause of the globalization of production is market forces and property rights. The advent of mass production technology brings with it the desire and the need to manage the market and to stabilize demand.12 Multinational enterprises play vital role in promoting and shaping the patterns of economic development, and this responsibility is affected by means of their foreign direct investment decisions. MNEs are required to assess the requests of international integration of production within the enterprise, with that of the need to respond to local surroundings. Moreover, MNEs operate to capitalize on the production of income and access to the capital markets. Will AI replace MNEs or MNEs will utilize AI in order to impose its terms globally without any control? It is characteristic that markets no longer need to be defined in terms of geographic proximity and, in some contexts, the location of transactions and organizations has become indeterminate. It seems that technology repairs imperfections, augments effectiveness, diminishes costs, increases predictability, and offers celerity. It has to be taken into account that from a legal viewpoint, AI has already begun to question fundamental notions underlying how and why we incentivize creation and innovation.13 AI and its usage have significant impact on human lives and society as a whole. Moreover, AI and its nature resemble the well-known field of software engineering and software as itself and so, AI technology entails the implementation of software to be functional, which means that AI has to be copyrighted or patented as software based on its character.14 Moreover, AI is creating machines that can think and work like the human brain. Engineers are crafting robots that help in the manufacturing,

Lester Thurow, The Future of Capitalism. New York: W. Morrow, 1996. p. 115. “The ‘globalization’ topic arises from a cluster of empirical data which show how in many branches and areas of activity, there is a small number of relevant firms operating and there are no national boundaries to competition. So in sectors like finances, telecommunications, aerospace, semiconductors etc. there exists real world-wide competition among a reduced number of firms.” 13 PricewaterhouseCoopers, Global Artificial Intelligence Study: Exploiting the AI Revolution 4 (2017), https://www.pwc.com/gx/en/issues/analytics/assets/pwc-ai-analysis-sizing-theprizereport.pdf; Jonathan Bastable, Is artificial intelligence set to become art’s next medium?, Christie’s (Aug. 20, 2018), https://www.christies.com/features/A-collaboration-between-two-artists-onehuman-one-amachine-9332-1.aspx. 14 Oracle, Am. Inc. v. Google Inc., 2014; case BSA v. Ministerstvo kultury ČR, C-393/09, 2010; case SAS Institute Inc. v. World Programming Ltd, C-406/10, 2012. 12

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Introduction

assembling, and commercial industries. The robots offer information and work by assembling products using AI and programming has a significant application in artificial intelligence since these machines use computer programs to deliver information and do different actions. AI has disadvantages affecting the globe. Has AI become useful to the human community? Will AI affect the future human society? Can law deal with AI disruptive technologies? Will AI replace the law by technology? How humans and AI work together? Under what circumstances the human or the AI should have formal decision-making authority? Which is the impact of AI upon society? Does the emergence of Advanced Artificial Intelligence (AAI) by creating AI persons alter the whole of the conventional world? Will the earth be inhabited by AAI creatures? In return for their persistent pursuit for profits, the corporate leaders assure to make noteworthy investments in host countries that would result in dissemination of technology and job creation, outcomes that are widely believed to lead to the enhancement of the overall economic and social surroundings of the host countries. Nonetheless, the chase of this endless corporate growth is not without cost; it has generated asymmetrical economic and technological results not only between developed and developing economies but also between developing and the least developing economies. Given that technology is the engine of economic growth, is the globalization helping or hindering its dissemination in developing countries? There is fierce global competition concerning AI and so, a solid European approach is required building on the European strategy for AI15 addressing the opportunities and challenges of AI. Thus, the Commission backs a regulatory and investment-oriented approach with the twin objective of promoting the uptake of AI and of addressing the risks linked with certain uses of this new technology. To that extent, AI involves a number of potential risks, such as opaque decision-making, gender-based or other kinds of discrimination, intrusion in private lives, or being used for criminal purposes. Aim of the present work is a deep analysis of the alterations and problems caused by new technologies in all fields of the global digital economy and society. The uniqueness of the current project is the overall investigation of the impact of AI upon not only of the law but also upon economics encompassing corporate governance, management, and risk management followed by a quantitative analysis by utilizing econometric regressions stipulating the scale of the impact. Furthermore, the project is divided in two parts, and the first part deals with the impact of AI upon economics followed by the second part concerning the impact of AI upon the Law. The analysis starts with a profound investigation of the characteristic of cyberspace, which is the original basis upon which new technologies build up. Moreover, there is special reference to advancements of globalization and digital economy due to new technologies with a presentation of Fintech. Additionally, the investigation enters the part of the economic analysis by examining the developments regarding

AI for Europe, COM/2018/237 final https://ec.europa.eu/commission/sites/beta-political/files/ political-guidelines-next-commission_en.pdf.

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management, governance, corporate governance, and risk management followed by a specific reference and deep analysis of the influence of AI upon them. As a real terms outcome being the clue after a theoretical analysis of the alterations caused by AI is the results of the econometric analysis. Moreover, the analysis moves on to the legal area by investigating the blockchain environment and the law. AI regulation and legal problems are analyzed for the reason that technology moves faster than law and so, highlighting the legal laps in regulation and proposing solutions for the spotted legal problems. The analysis brings forward answers concerning the legal problems such as AI personhood, etc. and also proposals concerning corporate governance, management, and risk management via AI models. It is worth mentioning here the analysis of the reaction of management and risk management in the COVID-19 period and the role of AI. The work closes with the presentation of the conclusions drawn from the authors’ examination.

Chapter 2

E-Globalization and Digital Economy

2.1

Cyberspace Settings

The new era of information technologies is referring to the globalization of communication. The quick decrease of the communication costs enhanced the dealings among countries and is a vital foundation for the structure of a stronger universal civil society. The global communication services have the supremacy to move visible and invisible things from one part of the globe to another. Global communication services influence not only the economic exchanges but also the ideas by way of increasingly widespread communication networks generating political groups and alignments. The supraterritorial cyberspace domain, notwithstanding distances, turns out to be likely via the communication globalization. In today’s technology-driven world, industry standardization, device interoperability, and product compatibility have turned out to be vital to advancing innovation and competition. Interoperability-centric challenges seem to continue to influence a variety of regulatory topics. Moreover, interoperability is one of the huge challenges of the convergence that occurs as a multilevel compatibility problem, purposely at the network, service, content, and terminal equipment levels.1 To attain interoperability and administer convergence-based complexities, the use of common standards and protocols or the use of a conversion function to map between diverse services would be needed. Furthermore, the notion of interoperability, resting at the center of network industries, is broader than merely a cyberspace entrée debate, as it influences innovation in software. The essential relationships among the components of the network, complementarity and compatibility, are present in many nonnetwork industries, including financial intermediation and the exchange of financial instruments and assets. Complementarity requires compatibility and coordination.

Damian Tambini, Danilo Leonardi, and Chris Marsden, Codifying Cyberspace: Communications Self-Regulation in the Age of Internet Convergence, Routledge, 2008.

1

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 G. I. Zekos, Economics and Law of Artificial Intelligence, https://doi.org/10.1007/978-3-030-64254-9_2

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This author2 considers that cyberspace is an electronic place that conforms to our understanding of the real world, with private spaces such as websites, e-mail servers, and fileservers, connected by the public thoroughfares of the network connections. Moreover, cyberspace is the virtual space and place created by operation of the Internet,3 a network of computers that share information with each other, and any other electronic networking resulted by different electronic devices such as satellites and cellar phones that can be interconnected and producing a global virtual reality network accessible by different electronic devices currently from earth but why not from people out of space or virtual entities outside our space or of another dimension livelihood within our space without currently being tracked by humans. It has to be taken into consideration that virtual events can be understood by human beings by the use of electronic devices transforming electronic signals into words and pictures viewed and comprehended by human beings and not virtual ones. It is argued that what cyberspace “is” remains highly contested, making agreement on its boundaries nearly unmanageable. Moreover, it could be said that outlining what cyber operations “are” has caused equally intractable questions as to which sets of international law rules apply and how they do so. Besides, where theoretical disputes do not exist, the functions boundaries are open to contest as an affair of (a) accuracy, (b) effectiveness, and (c) completeness. A law’s functions may be conditional on, or derivative of, a satisfactory theory for why the law exists which does not mean that theoretical variances preclude agreement on such functions completely. Sometimes, agreement is achievable even without agreement on why this is the case which means that in a global domain of diverse interests “incompletely theorized agreements” are anticipated.4 To that extent, relying on

2

G Zekos, Internet or Electronic Technology: A Threat to State Sovereignty, JILT 1999 (3) https:// warwick.ac.uk/fac/soc/law/elj/jilt/1999_3/zekos/ “The Internet cannot have a main control center nor can any single entity monopolize the abundant variety of information freely accessible on the Internet which does not mean a thread to sovereignty. Besides, in general, advanced electronic technology can be used in order to paralyze an inferior technology of a state and therefore threatening practically its sovereignty. In other words, the Internet does not simply erode sovereignty, but its effect will depend on the nature of the actions involved and thus the Internet may strengthen democratic practice. A democratic and open character of the Internet limits the possibilities of authoritarian and monopoly control. Besides, the global market has the power to discipline national governments. The commercialization of the Internet might end up as concentrated power. At present, there is no purely digital economy. The Globalization together with the digitalization of financial markets has made these markets a powerful presence. Private digital networks rather than the Internet have the power to neutralize sovereignty. Hence, a shift of some components of the state's sovereignty over to other entities carries the potential to limit sovereignty but may not be the elimination rather than a partial relocation to supra national institutions. In the end, it could be argued that the inapplicability of the theory of absolute territorial sovereignty could be supported rather than the death of the state.” 3 Voyeur Dorm v. City of Tampa, 265 F.3d 1232. 4 CR Sunstein, “Incompletely Theorized Agreements in Constitutional Law” (2007) 74 Social Research 1 (noting consensus on valuing religious liberty without agreement on why it deserves value: “Some people may stress what they see as the need for social peace; others may think that religious liberty reflects a principle of equality and a recognition of human dignity; others may

2.1

Cyberspace Settings

15

law-by-analogy to define explicit IHL thresholds can engender erroneous lines if they do not adjust nonanalogous characteristics of cyberspace and cyber operations. To that extent, it is worth noting that the question is not where law’s boundary lines go, but whether boundaries can work at all. To that extent, a boundary’s effectiveness depends on definite criteria such as a degree of determinacy and constraint being difficult to warrant given cyberspace’s predominant conditions such as anonymity. Additionally, the confining reason of borders causes an imperfect regulatory response to cyber operations, not just owing to incorrect or ineffective line drawing but also for failing to underline law’s other competences such as authorizing behavior. Furthermore, predominant difficulties on whether, where, and why borders are required in cyberspace imply that there is a need for re-appraising the existing landscape.5 “Sovereignty” is an adaptable perception. The term “sovereignty” has a range of meanings, and in its widespread modern treatment, sovereignty is the term for the “totality of international rights and duties recognized by international law”6 as residing in an autonomous territorial unit – the State. Sovereignty is an in-house perception, related only to the basis of legitimate authority within a state. Henkin7 argues that universal human values have superseded state values at the foundation of international law. In addition, Krasner8 views sovereignty as a supposed limitation on states’ power to interfere in each other’s affairs. Sovereign nation state is an entity whose sovereignty jointly derives from the sole jurisdiction to make laws for its people and its freedom from the coercive authority of any other state.9 Moreover, the state lies upon the foundation of sovereignty, which expresses internally in the supremacy of the governmental institutions and externally as the supremacy of the state as a legal person.10 The courts derive its power to adjudicate a matter from the state. Therefore, the concept of jurisdiction is based on the concept of state. The jurisdictional bases are the following: first territoriality; under the principle of territoriality, jurisdiction is based on acts that have been executed within the territory of the State in question. An alternative of this is the “objective territoriality principle,” purporting that the function in question was begun abroad but concluded within the territory of the State or that a constitutive part of the conduct happened within the territory.11 Second personality: under the principle of personality, jurisdiction is invoke utilitarian considerations; still others may think that religious liberty is itself a theological command”). 5 M Schmitt, “Military Necessity and Humanity in International Humanitarian Law: Preserving the Delicate Balance” (2010) 50 Va J Intl L 795. 6 James Crawford, The creation of states in international law 26-27 (1979). 7 Louis Henkin, The Mythology of Sovereignty, AM. SOC’Y INT’L L. NEWSL., Mar. 1993, at 1. 8 Stephen D. Krasner, Sovereignty: Organized Hypocrisy (1999). 9 Gilson, Bernard, The Conceptual System of Sovereign Equality. Leuven: Peeters, 1984. 10 Masilamani, N., & Anup Kurvilla John, “The Future of State Sovereignty: Emerging Concerns in the Internet Era” (The student Advocate, Volume 13, 2001). 11 Ralf Michaels, “Territorial jurisdiction after territoriality” in: Piet Jan Slot and Mielle Bulterman (eds.), Globalisation and Jurisdiction (2004 Kluwer Law International) 105, 106.

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upheld by the State of nationality of the perpetrator (active personality principle) or of the victim (passive personality principle).12 A number of countries confine passive personality jurisdiction to the cruellest of crimes, such as terrorist hijackings and crimes against humanity. Third effects doctrine: the “effects doctrine” jurisdiction is established on the fact that conduct outside a State has effects within the State but it is open ended, given that in a globalized economy, everything has a consequence on everything.13 All countries have a connection to all websites by virtue of their accessibility. Should the “effects doctrine” a fortiori be rejected completely on cyberspace? The divergence between the objective territoriality principle and the effects doctrine is vanishing because of cyberspace, given that the act of letting a message or information be seen in another territory and the effect caused by it are tricky to differentiate.14 Fourth protective principle: The protective principle is considered to protect a State from acts performed abroad that put at risk its sovereignty. The territorial jurisdiction of states and the jurisdictional limits of the municipal courts are established on the territorial theory. Personal jurisdiction depends on some quality attaching to the person involved in a particular legal situation which justifies a state or states in exercising jurisdiction in regard to him/her. Moreover, personal jurisdiction may be exercised on the basis of one or other of the following principles: (a) active nationality principle: Under this principle, jurisdiction is assumed by the state of which the person, against whom the proceedings are taken, is a national, and (b) passive nationality principle: Jurisdiction is assumed by the state of which the person suffering injury or a civil damage is a national. It has to be taken into account that it has not been established an effective or recognized customary international law that controls personal jurisdiction.15 Is the present emphasis on drawing law from boundaries and boundaries from law an adequate or effective way to regulate cyberspace and its conflicts? It is worth noting that cyberspace lacks a uniform foundation for why it needs boundaries, since cyberspace is endless, there is no possible to enclose cyber actions in a state sovereignty but the effects of cyber actions can be felt in states’ boundaries. It is worth noting here that even though the belief that law is dependent on the “materialities of place” has long been challenged, nonetheless the Westphalian origins of sovereignty today remain “very much alive, even if their current-day manifestations

Eric Cafritz and Omer Tene, “Article 113-7 of the French Penal Code: The Passive Personality Principle” (2002–2003) 41 Columbia Journal of Transnational Law 585, 588. 13 Thomas Schultz, “Carving Up the Internet: Jurisdiction, Legal Orders, and the Private/Public International Law Interface’ (2008) 19 European Journal of International Law 799, 815. 14 Mika Hayashi, “The Information Revolution and the Rules of Jurisdiction in Public International Law” in Myriam Dunn, Sai Felicia Krishna-Hensel, and Victor Mauer (eds), The Resurgence of the State 59, 74–75 (Ashgate 2007). 15 Jack L. Goldsmith, Against Cyberanarchy, 65 U. Chi. L. Rev. 1199 (1998). 12

2.1

Cyberspace Settings

17

are constantly transforming.”16 The developments on cyberspace and artificial intelligence have brought forward doubts about the essence of sovereignty, but regardless of the contemporary decline of state sovereignty, the enduring and expansive spatial reach of state power to counter threats to sovereign territorial control is taking place. Paul Linden-Retek17 deems that “in confronting the new ‘spaces’ of international entanglement, judges must redeem the idea that citizens might yet reclaim those entanglements as a ‘common world’, not just a space in which they are brought together, unfreely, under the mantle of state coordination and coercion.” The technologies and virtual places that represent cyberspace have been assimilated into the lives of people who accept the Internet as a tool for pursuing their common, real-world needs. The information circulated in cyberspace is produced by real people. People can use cyberspace framework only for their online dealings.18 Other people can use cyberspace setting for free circulation of ideas or having the impression of traveling virtually in many other places.19 Even why not if it is made possible, in the distant future, to achieve interconnection with digital networks of other civilizations living out there in space. Courts are using the metaphor of cyberspace as a “place” to justify application of traditional laws governing real property to this new medium.20 It should be taken into account that the Internet is not “just like” the physical world. Not every website is necessarily a purposeful availment of the benefits of every forum state.21 Furthermore, the courts showed significant keenness to treat Internet and paper transactions as equals – comparable results should be reached if not there is a reason to treat them in a different way.22 For instance, a contract cannot be denied enforcement solely because it is in electronic from or signed electronically.23 On the Internet, problems of physical infrastructure and overcrowding are less apparent because it is a different dimension,24 but it has to be taken into account that electronic infrastructure used to accommodate the operability of cyberspace causes very often many problems due to its material feature. Moreover, information is saved in electronic devices and is not

16 Ran Hirschl and Ayelet Shachar Spatial Statism, 17(2) Int’l J. Const. L. 387, 391 (2019). Anna Jurkevics, Hannah Arendt Reads Carl Schmitt’s Nomos of the Earth, 16(30) Eur. J. Pol. Theory 345, 349 (2017). 17 Paul Linden-Retek, The subjects of spatial statism: Reclaiming politics and law in international entanglement https://ssrn.com/abstract¼3450966 p1. 18 Caroline Bradley & A. Michael Froomkin, Virtual Worlds, Real Rules, 49 N.Y.L. Sch. L. Rev. 103, 139–46 (2004). 19 Edward Castronova, The Right to Play, 49 N.Y.L. Sch. L. Rev. 185, 185, 200–05 (2004). 20 eBay, Inc. v. Bidder’s Edge, Inc., 100 F. Supp. 2d 1058. 21 Jessica Litman, Breakfast with Batman: The Public Interest in the Advertising Age, 108 Yale L.J. 1717, 1725 (1999). 22 CSX Transportation, Inc. v. Recovery Express, Inc. 415 F. Supp. 2d 6. 23 ((“UETA”), 7A U.L.A.§701, (“E-Sign”), 15 U.S.C. §§7001–7031). 24 Intel Corp. v. Hamidi, 114 Cal. Rptr. 2d 244.

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freely circulated on earth like sound, wind, or oxygen and so, controlled by the owners of the electronic devices. Cyberspace allows the implementation of different activities such as online gaming, online banking, fan fiction, and comparison shopping. In fact, cyberspace brings forward a question of allocation of rights and responsibilities in virtual space. What occurs in cyberspace is related with what occurs in real space. People are using cyberspace and circulate information or contact electronic transactions. Information access and control in cyberspace have consequences that reflect into real space because it is people in real space who require information residing in different jurisdictions.25 Thus, lives and concerns of people using cyberspace are inextricably rooted in real space. Space encompasses geographic/mapped places representing both totality and infinity. To that extent, cyberspace as a virtual space encompasses virtual places with a virtual totality and infinity and the countless amount of virtual places constitutes the cyber place of cyberspace. Hence, cyberspace includes many cyber places. Moreover, cyberspace is a separate space in a virtual dimension viewed and operated by electronic agents programmed by humans. It is necessary to be made the distinction between cyberspace as the place and space where different type of virtual activities can take place that have an effect on humans and cyberspace as a virtual place and space where virtual functions can take place which are only virtual without affecting humans. Cyberspace as a virtual space and place can be used by virtual entities and electronic beings, but presently human being do not have this ability to be transformed from human being into electronic beings and vice versa. The future use of cyberspace – not merely Internet – by virtual entities and electronic beings to inflict the real world cannot be overruled in advance which will cause different problems giving a different dimension into the phenomenon of cyberspace needing a state’s intervention. The production of electronic beings that will function only electronically on behalf of human beings cannot be rejected for the distant future. It is open to research if cyberspace in its current form or a new more advanced cyberspace based on wireless communication can be connected with unknown electronic/digital systems own by civilizations out of our planet but within the endless cyberspace. Cyberspace is not a real place and so, users can adopt a new electronic identity with which travel in cyberspace. The electronic user always will correspond to a real person who can adopt many different electronic identities as technical identities allowing him/her to use cyberspace not mentioning purely electronic agents that can be used in electronic transactions. Which is the liability of electronic agents? Electronic agents will continue to remain electronic agents created by humans to act as electronic agents having no liability. On the other hand, humans even as

25 Reno v. ACLU, 521 U.S. 844, Mark A. Lemley, Place and Cyberspace, 91 Cal. L. Rev. 521 (2003).

2.2

Cyberspace Governance

19

electronic users have finally liability for any misgivings caused by their electronic transactions.26

2.2

Cyberspace Governance

Conventionally governance has been related with “governing,” denoting formal political institutions aiming to organize and control interdependent social relations possessing the capability to enforce decisions. Moreover, governance denotes the regulation of interdependent relations in the absence of overarching political authority, such as in the global system. As a general rule, governance is the set of tasks and practices exercised by those in charge for an enterprise with the objective of providing strategic direction, guaranteeing that objectives are accomplished, making certain that risks are administered properly and verifying that the company’s means are utilized responsibly. Increasing computer interconnectivity – particularly growth in the use of the Internet/cyberspace – has transformed the way that governments, states, and much of the world communicate and perform business. The numerous networks that make up the Internet/cyberspace embrace the national backbone and regional networks which networks run by individual businesses or “enterprise” networks. The global interconnectivity provided by the Internet/cyberspace permits cyber-attackers such as criminal groups, hackers, and terrorists to with no trouble cross national borders, contact great numbers of victims at the same time, and effortlessly preserve anonymity. E-government is an innovation in the public sector making public services less expensive and more open27 and so, offering the equipment for innovative interactions between a government and its citizens and intelligent ways to supply public services.28 E-government brings the government closer to citizens, defeating the barriers of bureaucracy, reducing corruption, and making decision-makers more reactive to people’s needs, which means that e-services of e-government are characterized by greater efficiency and transparency.29 Moreover, the functional

26

Georgios I Zekos, Globalisation and States’ Cyber-Territory, http://www.bailii.org/uk/other/ journals/WebJCLI/2011/issue5/zekos5.html. 27 OECD (2009). Rethinking e-Government Services: User-Centred Approaches. OECD Publishing, 2009. 28 Yigitcanlar T., Baum S. B. (2006). E-Government and the digital divide. In: Encyclopedia of e-commerce, e-government, and mobile commerce. Khosrow-Pour M. (Ed.), pp. 353–358. USA, Pennsylvania, Hershey: Idea Group Reference (IGI Global), 2006. Wauters P., Lörincz B. (2008). User satisfaction and administrative simplification within the perspective of eGovernment impact: Two faces of the same coin?” European Journal of ePractice, no. 4, August 2008, www. epracticejournal.eu. 29 OECD (2009). Rethinking e-Government Services: User-Centred Approaches. OECD Publishing, 2009.

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components of e-government, such as e-infrastructure, e-services, and access to public information, have a raison d’être upon anticorruption effect by enhancing the transparency of procurements system, making public services more easily reached and clear, and making certain a global citizens’ access to information. Furthermore, e-access to government information is a vital good governance tool in making certain the execution of state obligations and raising the accountability to citizens.30 Governance of the cyberspace is carried out by so-called multistakeholder (MSH) organizations such as the Internet Society and the World Wide Web Consortium which entities have principally established the norms and standards for the global Internet/cyberspace. Cyberspace governance implies the capacity to enforce mandates limited in the framework of Internet governance as performed by MSH processes varying from the “soft” power of rough consensus to the “hard” power of international law and binding treaties. For the reason that the Internet/cyberspace works around and beyond political boundaries, efforts to censor Internet/cyberspace speech have proven complex and ineffective. Waz and Weiser31 say that “it will be important to establish an understanding as to whether, when, and how sovereign governments should defer to MSH processes, should themselves be recognized as stakeholders in such processes, and should empower or backstop such processes.” Cyber-security governance verifies how generally accepted management controls such as risk assessment controls are adapted, supplemented, and utilized in the face of the advanced persistent threat and mirroring the total enterprise risk management strategy and enterprise risk governance structure.32 In addition, cyber-security33 governance refers to the element of corporate governance that tackles the enterprise’s dependence on cyberspace in the presence of opponent and so, covering information systems security governance. Moreover, cyber-security governance is the section of corporate governance regarding organizational dependence on cyberspace in the presence of adversaries as a domain of enterprise risk management. Deb Bodeau et al.34 specify that “Cyber Prep provides a framework for assessing, and identifying gaps or possible areas of evolution in, an organization’s cyber-security governance structures and practices. Achieving cyber-security governance consistent with its target Cyber Prep level enables an organization to make consistent and understandable decisions about investing in security measures; aligning cyber-security risk

30

Belanger F., Carter L. (2006). The impact of the digital divide on e-government use. In: Proceeding HICSS ‘06 Proceedings of the 39th Annual Hawaii International Conference on System Sciences, 2006, No. 04. 31 Joe Waz and Phil Weiser, Internet Governance: The Role of Multistakeholder Organizations, 2012 J. ON Telecomm. & High Tech. L. Vol. 10 331 p 348. 32 International Standards Organization (ISO), Corporate governance of information technology, ISO/IEC 38500:2008, 2008. 33 GAO, Cyberspace: United States Faces Challenges in Addressing Global Cybersecurity and Governance, GAO-10-606, July 2010, http://www.gao.gov/new.items/d10606.pdf. 34 Deb Bodeau, Steve Boyle, Jenn Fabius-Greene, Rich Graubart, Cyber Security Governance, MTR100308 MITRE Technical Report ©2010 The MITRE Corporation.

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Cyberspace Governance

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management with other aspects of enterprise risk management; and managing the organization’s cyber-security posture.” The growth of cyberspace has been portrayed by an emphasis on interoperability, effectiveness, and freedom but our increasing reliance has not been matched by efforts to keep it secure reflecting the original rationale of the web, which was to exchange scientific data, rather than to assist an entire global economy. The upsurge of use and functionality of cyberspace has outpaced efforts to restructure and secure the original cyberspace’s infrastructure. Cyber security includes borderless challenges, while responses remain overpoweringly national in scope and even these are unsatisfactory. Moreover, cyber security characterizes an increasing challenge to democratic governance, as public and private efforts to secure cyberspace. IT networks supervise the traffic that they carry has to be balanced with human security anxiety and, above all, with human rights to privacy and to freedom of expression and association. Benjamin S. Buckland, Fred Schreier, and Theodor H. Winkler35 argue that “democratic governance concerns – particularly regarding control, oversight and transparency – have been almost entirely absent from the debate. These concerns are exacerbated by the enormous role played by private actors (both alone and in cooperation with governments) in online security of all types. Given the pace at which states and private companies are reinforcing online security and preparing for cyber war, addressing democratic governance concerns has never been more pressing.” The G7/8 addressed the problems of coordinating policies regarding the governance of cyberspace dealing with governance issues, including, among others, the formation of norms, principles, and rules concerning the interconnection of computer networks via networks of networks such as the Internet/cyberspace, rights of access to those networks, pricing of access, observing of network-mediated economic transactions, intellectual property protection, taxation of goods and services delivered via cyberspace, matters of privacy, security, and a range of other subjects thought to influence the trust of cyberspace’ users.36 According to Jeffrey A. Hart,37 “in areas, such as Internet governance, where private actors are needed both to provide accurate informational inputs to form and implement new norms, rules, and procedures, a properly configured multistakeholder approach is both necessary and desirable.”

35

Benjamin S. Buckland, Fred Schreier, Theodor H. Winkler, Democratic governance challenges of cyber security, DCAF Horizon 2015 Working Paper No. 1. 36 Skantze, Pernilla (2003). “European Cyber Security.” OECD Global Forum on Information Systems and Network Security: Towards a Global Culture of Security. . 37 Jeffrey A. Hart, The G8 and the Governance of Cyberspace, Chapter 9, In New Perspectives on Global Order: Why America Needs the G8.

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Digital Economy Background

FDI is central to understand both financial and real economic links between economies, but the presence of offshore financial centers and SPEs conceal ultimate bilateral linkages. However, FDI is not only regionally clustered, but investments are also spread out between many economies with direct FDI links. It is worth noting that global FDI network is a new synergy within which AI is implemented and so, the comparison of global FDI networks is based on different FDI measures. In fact, the United States, the Netherlands, and Luxembourg rule the FDI network based on the CDIS, and so, the network discloses a very high degree of connectedness where most economies have FDI links vis-à-vis each other. Moreover, it is worth mentioning here that the new global FDI network advances several insights and formal facts that provide a different picture of long-term relations between economies and final investment patterns than traditional FDI data.38 It is characteristic that “traditional” key economies become more dominant in the adjusted global FDI network, but financial centers remain vital for FDI even after removing SPEs which means that entities located in financial centers also take an active role in managing FDI rather than only acting as passive holding corporations. FDI has become more responsive to taxation over time and MNEs optimize taxes through SPEs, and so, tax optimization often encompasses shifting profits to a low-tax jurisdiction through debt allocation, transfer pricing, or corporate inversions. To that extent, MNEs allocate most of their debt to a high-tax economy to take advantage of high interest deductions while shifting profits to low-tax jurisdictions. Additionally, MNEs use unrecognizable transfer pricing to shift profits to low-tax jurisdictions through sales of goods and services between affiliates and so, influencing FDI through profits and retained earnings.39 It is worth noting that the European Commission has ruled that the tax authorities in Ireland, Luxembourg, and the Netherlands have allowed Apple, Fiat, and Starbucks to use transfer prices that do not echo underlying economic prices and so, violating EU state aid rules.40 It seems that international corporate structures are used to shift profits away from high-tax jurisdictions.41 The link between FDI and real economic activity is growing as corporate structures, and financing mechanisms become more global. While FDI measures financial investments, it is traditionally used as a proxy for real economic activity caused by foreign-owned corporations and long-term relations between economies. Nonetheless, with gradually multifaceted and flexible MNE structures and

38 Jannick Damgaard, Thomas Elkjaer, and Marco Espinosa-Vega, The Global FDI Network: Searching for Ultimate Investors IMF Working Paper WP/17/258. 39 Lanz, Rainer, and Sébastien Miroudot (2011), “Intra-Firm Trade: Patterns, Determinants and Policy Implications,” OECD Trade Policy Working Paper No. 114. 40 OECD (2016), “Are the Irish 26.3% better off?” OECD Insights. 41 Lane, Philip, and Gian-Maria Milesi-Ferretti (2017), “International Financial Integration in the Aftermath of the Global Financial Crisis,” IMF Working Paper WP/17/115.

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Digital Economy Developments

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widespread use of SPEs, the strong SPE presence in certain economies is an imperative cause for the decoupling between FDI and real economic activity due to the fact that the SPEs break the direct link between the receiving economy and the ultimate owner. Subsequently, SPEs make it difficult to separate real financial integration and diversification from financial engineering. It is argued that FDI financing through SPEs is often only transitory and so, a high positive correlation between quarterly FDI inflows and outflows in several economies means that FDI inflows are often just passing through an economy on the way to their final destination.42 Furthermore, it seems that FDI positions have continued to expand in the consequences of the financial crisis emerging from FDI positions vis-à-vis financial centers attributed to the growing complexity of the corporate structures of large MNEs.

2.4

Digital Economy Developments

All sectors of the economy have adopted ICT to increase productivity, enlarge market reach, and diminish operational costs. Moreover, this adoption of ICT is demonstrated by the spread of broadband connectivity in businesses, which in almost all nations of the Organisation for Economic Co-operation and Development (OECD) is complete for large enterprises and reaches 90% or more even in smaller businesses. To that extent, the extensive adoption of ICT, along with the rapid decline in price and surge in performance of these technologies, has added to the occurrence of new activities in both the private and public sectors. In addition, these technologies have multiplied market reach and lowered costs, and they have enabled the advance of new products and services and so, altering the ways in which such products and services are manufactured and delivered, as well as the business models used in firms ranging from MNEs to start-ups. It is worth mentioning here that the advent of cyberspace brought key alterations first to the entertainment, news, advertising, and retail industries. Are there central characteristics of the digital economy? There are a number of characteristics that are increasingly noticeable in the digital economy and which are possibly relevant from a tax perspective. While these features are not all present at the same time in any particular business, they increasingly portray the digital economy encompassing mobility, reliance, networking, and volatility. In fact, mobility refers to (1) the intangibles on which the digital economy depends on heavily, (2) users, and (3) business functions as a result of the declined requirement for local personnel to accomplish particular functions along with the flexibility in many cases to select the location of servers and other resources. Moreover, reliance refers to dependence on data and so, encompassing the use of so-called big data as

Blanchard, Olivier, and Julien Acalin (2016), “What Does Measured FDI Actually Measure?” PIIE Policy Brief 16-17, Peterson Institute for International Economics.

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well. In addition, network effects indicate reference to user participation, integration, and synergies which means that utilization of multisided business models in which the two sides of the market are in different jurisdictions. There is a tendency toward monopoly or oligopoly in particular business models relying heavily on network effects, and so, it has generated volatility owing to low barriers to entry and rapidly advancing technology. The digital economy offers consumers access to information formerly inconceivable in any traditional marketplace. Yet that information and more is also available to retailers who are able to use pricing software to maximize profits. In the past, anticompetitive conduct entailed proof of a meeting of the minds to collude on prices or abuse market dominance, but the speed with which prices are adjusted today means that tacit collusion may take place without any intent on the part of market actors or even without any formal coordination between their computer programs. Due to the mobility of intangibles, the advancement and utilization of intangibles is a crucial element of the digital economy, and so, investment in and development of intangibles are a principal contributor to value formation and economic growth for firms in the digital economy. Hence, digital firms rely on software and so, expend extensive resources on research and development to advance existing software or to develop new software products. In addition, mobility of users means that progresses in ICT and the enhanced connectivity that portrays the digital economy indicate that users are progressively able to continue commercial activities remotely while traveling across borders. Nevertheless, mobility of business functions shown by enhanced telecommunications, information management software, and personal computing has diminished the cost of organizing and co-ordinating complex activities over long distances which means that businesses are able to accomplish their global operations on an integrated basis from a central location that may be removed geographically from both the locations in which the operations are carried out and the locations in which their suppliers or customers are located. It is worth noting that the capacity to manage business centrally while keeping substantial flexibility over the location of business functions has amplified the capacity of businesses to spread functions and assets among multiple different states. In fact, while globalization of business among larger organizations is not a new incident, the spread of the digital economy, linked with the growing significance of the service component, along with reductions in trade costs owing to trade and investment liberalization and regulatory amendments, has removed logistical barriers expanding the speed at which such globalization is achievable. Technological advances have also allowed greater integration of global businesses, which has augmented the flexibility of corporations to spread their actions among several locations globally, even if those locations are distant from each other and from the physical location of their final customers. Moreover, in the digital economy, reliance on data is common and so, corporations collect data about their customers, suppliers, and operations.

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Digital Economy Developments

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In reality, network effects refer to the fact that decisions of users have a direct influence on the benefit received by other users which means that these network outcomes are an imperative feature of many companies in the digital economy. Network effects are seen whenever compatibility with other users is vital, even where the primary reason of a specific technology may not be to co-operate with others. It has to be taken into account that the digital economy includes two categories of multisided business models. First, a business can operate several applications that offer complementary services by generating two types of synergy: on the one hand, the numerous activities combine their resources such as executable code, content, or user data; on the other hand, the activities may be put into a package that is more attractive for users. Second, vertical platform models are exploited to make resources available for third-party developers in an attempt to attract their creativity as part of open innovation strategies. Moreover, a platform is the consequence of the largescale development of an application that gets commoditized. A firm can build up a social networking service, using internally created applications to attract customers and funding operations via the sale of advertising. In addition, the firm can also choose to open an application programming interface (API) which permits developers to easily employ applications using the platform and so, access to the API diminishes the developers’ initial investment and assists their access to the market of customers that use the platform. Sequentially the participation of the developers augments the user experience, thereby further strengthening the firm’s position in the marketplace. It is worth noting that in some markets, predominantly where a firm is the first actor to gain traction on an immature market, network results joined with low incremental costs allow the firm to get a dominant position in a very short time and so, this capacity to gain traction is boosted where a patent or other intellectual property right grants one competitor the exclusive power to utilize a specific innovation in a certain market. Likewise, it has to be taken into consideration that technological progress has led to progress in miniaturization and a drop in the cost of computing power and so, neither a cyberspace user nor the service provider is required to pay a marginal price for using the network, which means that these elements, linked with increased performance and capital expenditure, have markedly reduced barriers to entry for new cyberspace-based businesses. Moreover, these factors have joined to promote innovation and the constant development of new business models and so, in short term, firms that control a considerable part of the market and enjoyed a dominant position for a short period of time have found themselves rapidly losing market share to challengers that built their businesses on more powerful technology, a more attractive value proposal, or a more sustainable business model. Hence, as a result of the fast pace of innovation, the few firms that have achieved long-term success normally have done so by investing extensive capitals in research and development and in acquiring start-ups with innovative ideas, launching new features and new

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goods, and repeatedly evaluating and adjusting business models so as to leverage their market position and uphold dominance in the market.43

2.5

Finance and Globalization

Finance has become one of the most globalized and digitized sectors of the economy. Moreover, globalization, digitization, and money are boosting AI in finance forward at an ever-increasing pace. In line, Zetzsche44 et al. argue that “the use of AI in finance comes with three regulatory challenges: (1) AI increases information asymmetries regarding the capabilities and effects of algorithms between users, developers, regulators and consumers; (2) AI enhances data dependencies as different day’s data sources may alter operations, effects and impact; and (3) AI enhances interdependency, in that systems can interact with unexpected consequences, enhancing or diminishing effectiveness, impact and explainability. These issues are often summarized as the ‘black box’ problem: no one understands how some AI operates or why it has done what it has done, rendering accountability impossible.” It could be said that bolstering cyberspace governance of regulated financial market participants through external regulation is the way forward in AI era. In other words, the most effective course forward implicates regulatory approaches which bring the human into the loop, augmenting internal governance through external regulation. Thus, the application of the principles of governance in an AI environment is an answer. In the context of finance, the post-Crisis concentration on personal and managerial responsibility systems offer a central external framework to augment internal accountability in the context of AI which means that AI-tailored manager responsibility frameworks, augmented in some cases by independent AI review committees, as developments to the conventional three lines of defense is the most effective way for dealing with AI-related matters not only in finance concerning “black box” problems then again possibly in any regulated business.

OECD (2014), “The digital economy, new business models and key features,” in Addressing the Tax Challenges of the Digital Economy, OECD Publishing, Paris. DOI: https://doi.org/10.1787/ 9789264218789-7-en. 44 Dirk A. Zetzsche, Douglas Arner, Ross Buckley, Brian W. Tang Artificial Intelligence in Finance: Putting the Human in the Loop, https://ssrn.com/abstract¼3531711 P3. 43

2.6

2.6

From Conventional Globalization to E-Globalization

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From Conventional Globalization to E-Globalization45

It is worth noting that major alterations in technology, geopolitics, environment, and society push forward a new phase of globalization. It is worth noting that the convergence of globalization and digitization denotes that business leaders and policy-makers will need to reassess their strategies. Thus, it has to be taken into account that digital platform enterprises are an essential part of the global economy. Taking into account that the web of global economic connections is growing deeper, broader, and more complex, nowadays digital form of globalization is shifting who is participating, how business is done across borders, how quickly competition moves, and where the economic benefits are flowing. It is worth mentioning here that while advanced economies continue to be the leaders in most flows, the road has opened to more countries, to small firms and start-ups, and to billions of people. FDI is a crucial link in global economic interconnectedness and is widely used to analyze globalization of production, attractiveness of an economy, long-term relationships between economies, technology transfer, and real economic activity produced by MNEs. In today’s unpredictable and hypercompetitive global markets, achieving and sustaining competitive advantage necessitate not only the creation of superior customer value but also the continuous pursuit of operational effectiveness. Synergy46 is supposed to lead to a competitive advantage as two or more units of a company share know-how or resources, coordinate strategies, and pool negotiation power. Thus, capturing cross-business synergies is an essential part of corporate strategy. As competition is growing more intense, firms look for synergies in their overall global purchasing effort across business units. Synergy initiatives often fall short of management’s expectations and might even distract managerial attention.47

45

Georgios I. Zekos, MNEs, globalisation and digital economy: legal and economic aspects, https:// www.emerald.com/insight/content/doi/10.1108/03090550310770875/full/html. 46 Global purchasing synergies can be divided into three categories • Economies of information and learning: sharing all available purchasing knowledge on suppliers, new technologies, markets, internal users, applications, the prevention of mutually incompatible negotiating strategies, the prevention of affiliates from depriving one another of the limited available resources in times of scarcity, etc. • Economies of process: establishing a common way of working thereby showing worldwide one line of con-duct to suppliers, benchmarking procedures and results, and joint training and development • Economies of scale: pooling volumes to enforce purchasing power, reducing the number of global suppliers, standardization, and synchronizing requirements. 47 Goold, M., and Campbell, A.: Desperately Seeking Synergy. Harvard Business Review 76 (5),131–143 (1998). Quelch, J.A., and Hoff, E.J.: Customizing Global Marketing, in Transnational Management, C. Bartlett, and S. Ghoshal eds., Irwin, Chicago, IL, 1995, pp 638–649. Quelch and Hoff suggest five approaches ranging from very low to extreme centralization. They are (1) information sharing among local executives (stimulating word-of-mouth); (2) friendly persuasion by headquarters; (3) global coordination, whereby headquarters has a structured role in both decisionmaking and performance evaluation (often using a matrix or team approach); (4) “stamped and approved” (i.e., a properly managed approval system); and (5) directing or “doing it the headquarter’s way.”

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Hayes48 argues that a “coordinated global sourcing for competitive advantage” is a logical extension of respectively domestic and foreign sourcing. Cultural differences and local market conditions might further prevent companies from realizing global efficiencies. Can globalization be achieved without the expansion of MNEs and their activities? Mobility of labor and capital, transfer of technology and innovation, advanced technology, and evolvement of cyberspace have been achieved by the development and expansion of MNEs and their role in international trade. Application of advanced technology in production and management of MNEs led to the evolvement of e-commerce and consequently to digital economy. Does globalization associate with progress, prosperity, and peace? Globalization necessitates the creation of a new paradigm of social and political enquiry and is associated with technological revolutions in transport, communications, and the data processing deriving to centrality of manufacturing industry in a global economy deriving to a digital economy. It has to be taken into consideration that sources of FDI as actors in a society are acting differently conditional to the institutional structure of the host society. Moreover, institutions are central economic growth factors due to the fact that institutions offer a framework for interaction with foreign investors. Thus, FDI can be beneficial to growth depending on the institutional quality of the host country and so, weak governance performance is linked with government ineffectiveness, ineffective rule of law, political instability, and poor accountability among other governance factors.49 FDI-financed firms are highly sensitive to the governance framework of the host country and so, institutional quality does not only attract FDI but also strengthens the growth results of FDI in the continent.50 M. Ngundu, N. Ngepah51 argue that “the impact of EU and US is unique from that of Asia in two ways. First, their impact on growth in Africa is divided upon weak and strong governance performing countries. Second, their impact of weak governance performing countries is non-significant. . . US and the EU investments are channelled towards African countries with relatively effective rule of law although the former is more sensitive than the latter. Whereas China do investment both in weak and strong governance countries.” A strengthened framework of global cooperation is required to speed up progress on shared challenges and lessen tensions among and within states. Technological

48 Hayes, H.M., Jenster, P.V., and Aaby, N.E.: Business Marketing: A Global Perspective. Irwin, Chicago, 1996, pp 88–89. 49 Jude, C. & Levieuge, G., 2015. Growth Effects of FDI in Developing Economies: The Role of Institutional Quality. Banque De France Eurosysteme, (559). 50 Peres, M., Ameer, W. & Xu, H., 2018. The impact of institutional quality on foreign direct investment inflows: evidence for developed and developing countries. Economic ResearchEkonomska Istraživanja, 31(1), pp.626–644. https://www.tandfonline.com/doi/full/10.1080/ 1331677X.2018.1438906. 51 Marvellous Ngundu, Nicholas Ngepah, Growth Effects of Foreign Direct Investment (FDI) from China and Other Sources in Africa: The Role of Institutional Quality. The Asian Institute of Research Journal of Economics and Business Vol.2, No.3, 2019: 1026–1038 p1037.

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From Conventional Globalization to E-Globalization

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transformation is altering the way economies and societies organize themselves in national policy helping societies maximize the benefits and mitigate the risk of these advances, which are fueling the wholesale disruption and recombination of industries; the dematerialization of value creation; a move in the nature of competition in domestic product, capital, and labor markets along with countries’ international trade and investment strategies. Thus, e-globalization will be shaped by a combination of governance decisions and technological developments transforming the systems of health, transportation, communication, production, distribution, and energy. It is worth noting that the rapid growth of “fintech,” the provision of credit and other financial services through electronic platforms embracing those that make possible peer lending, signifies a prospective new challenge for the global financial architecture due to the fact that such activity is growing rapidly, posing opportunities along with risks for the financial system. There is the need to close gaps in fields where international cooperation involving all stakeholders, including fintech actors, are both strikingly absent and urgently required. It could be said that price volatility of traded crypto assets, rapid growth of fintech corporations with unprecedented scale of operations and network effects, and the influence of fintech innovations on volatile cross-border savings and transactions cause new tasks to systemic risk surveillance through the need to identify, monitor, and assess modifications to the nature, magnitude, and structure of resulting capital flows. Thus, fintech services intensify financial interconnectedness and cross-border spillovers. Blockchain upend current models of data ownership, giving users greater control over their data, enabling micropayments for data usage. Also, the digital representation of real-world assets on a blockchain, along with the appearance of new categories of crypto assets, presents new financial opportunities for stakeholders which means that new economic models augment privacy, security, inclusion, and individual rights, possibly lifting control of user data from shareholders to consumers while offering access to new funding flows. To that extent, digital platforms alter the economics of doing business across borders, bringing down the cost of international interactions and transactions by generating markets and user communities with global scale, offering businesses with a huge base of prospective customers and effective ways to reach them. The European Commission52 describes an online platform as “an undertaking operating in two (or multi)-sided markets, which uses the Internet to enable interactions between two or more distinct but interdependent groups of users so as to generate value for at least one of the groups.” On one hand, DLT upend entire systems. On the other hand, it faces important policy and cooperation encounters, embracing absence of interoperability, security threats, and prospective environmental and financial system impacts. While in the long run autonomously piloted systems will revolutionize how people and goods are transported and drones will transform business models and

52 European Commission, “Public consultation on the regulatory environment for platforms, online intermediaries, data and cloud computing and the collaborative economy,” Sept. 24, 2015, p. 5.

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tackle societal challenges around the world, governments are trying to find ways to inspire innovation while keeping public safety and confidence. Thus, large corporations, along with a growing start-up environment, are deterred in their capacity to invest and expand. To that extent, making possible millions of manned and unmanned aircraft to fly simultaneously will entail new types of airspace management, physical infrastructure, and privacy and data ownership policies. As more people employ digital systems more intensively, the amount of data in digital form generated, processed, and communicated will rise exponentially. The Fourth Industrial Revolution will fail completely without cyber security. Presently, the current cyber risk is keeping privacy and confidentiality, and the Marriott breach shows the reputational, legal, and business risks of leaking large amounts of customer information.53 The increased speed of information technology is an indispensable part of the AI systems that are at the vanguard of what has been called a fourth industrial revolution. Yet there are indications that the rate of increase is slowing, ever more efficient machines mean that the marginal costs of data storage and computing power are trending toward zero and so, the rising involvedness of those systems means that, even though general AI remains science fiction for the time being, existing applications of narrow AI have already moved considerably beyond human cognitive capacities. In other words, the effacement of distance by the speed with which data flow around the globe is noticeable of the character of the new technological revolution leading to a virtual world. Cyber and Internet law are now subdisciplines in their own right, introducing multifaceted jurisdictional and practical issues in regulating online behavior.54 It seems that algorithms executing trades are subject to the same regulations as the human brokers that set them in motion and so, the possibility of disruption or manipulation owing to the speed at which those algorithms run has led bourses to explore ways of slowing them down. Moreover, computer-based trading has altered not only the culture but also the very nature of the market. Technological revolution influences the political stability and economic viability, limiting the corporation’s own prospects for value creation and growth which means that a new aspect of corporate governance needs attention from boards owing to the identification of new just-transition risks linked to automation, restructuring, climate change abatement, or other plans in order to make certain that management has adequate policies and practices for mitigating them.

53 https://krebsonsecurity.com/2018/12/what-the-marriott-breach-says-about-security https://www. schneier.com/ (a hacker altering a patient’s blood type in a hospital context could pose a far greater individual danger than the loss of that patient’s data) www.weforum.org/centre-for-cybersecurity (the World Economic Forum Centre for Cybersecurity is established in 2018). 54 G Zekos, Cyber Versus Conventional Personal Jurisdiction, 2015 Journal of Internet Law, Volume 18 Number 10, April 2015 3-35 Wolters Kluwer. www.wrightsmedia.com https://lrus. wolterskluwer.com/store/product/journal-of-internet-law/ G Zekos, Demolishing State’s sole power over Sovereignty & Territory via Electronic Technology & Cyberspace, 2013 Journal of Internet Law, Volume 17, Number 5, November 2013 27-41 Aspen Publications-Wolters Kluwer.

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It has to be taken into consideration that government tax bases have come under further pressure, as digitization, deregulation, trade liberalization, and global value chains have improved the economies of scale and geographical fragmentation of production along with the corporate sector’s share of national income in many states. Corporations have not only a legal obligation to pay taxes but also a broader fiduciary responsibility stemming from their long-term value-creation mandate to make certain that they pay their fair share. Boards have a responsibility to guarantee that their companies are acting not only legally but also in keeping with the trust society has placed in them to provide fairly and responsibly to the long-term viability of the economy in which they function. Concerning geopolitical and geo-economic cooperation presently, global power has been swinging, creating new risks confronting international relations as outlined in greater detail in the Forum’s Global Risks Report 2019–2020. Anyway, the biggest benefits of trade flows go to countries at the center of the global network, but countries at the periphery of the network of data and capital flows get even more than those at the center.55 Digital technologies can overcome complexity and generate leaner models for going global which means that firms have to alter their organizational structures, products, assets, and competitors. Moreover, states cannot shut themselves off from global flows or narrow export strategies because they miss the real value of globalization which encloses the flow of ideas, talent, and inputs that spur innovation and productivity. On the other hand, e-globalization makes policy selections even more multifaceted and so, value chains are transferring, new hubs are emerging, and economic activity is being renovated, but this changeover generates new openings for states to build profitable roles in the global economy. Likewise, e-globalization opportunities will favor locations that build the infrastructure, institutions, and business environments that corporations and citizens have to participate fully. Moreover, digitization modifies the economics of globalization in many ways and so, as digital platforms become global in scope, they are driving down the cost of cross-border communications and transactions, permitting businesses to connect with customers and suppliers in any state. While globalization was once for MNEs, platforms diminish the minimum scale required to go global, enabling small business and entrepreneurs around the globe to join which means that new kinds of competitors appear quickly and so, escalating pressure on industry incumbents. Hence, states and firms cannot ignore the opportunities beyond their own borders. While advanced economies are still the most globally connected, developing economies are strengthening their participation and so. they are narrowing the gap with the leading advanced economies, which means that accelerating catch-up growth is a key prospect for the developing world. It is worth mentioning that data flows offer stronger economic benefits to economies on the periphery of the world’s digital networks, but e-globalization

55 Kinsey Global Institute, Digital globalization: The new era of global flows, February 2016 | Report.

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poses challenges, which means that while firms can enter new markets, they are exposed to pricing pressures, aggressive global competitors, and disruptive digital business models. Modern globalization is more complex and fast-paced, but connectedness is a way to growth. It could be said that a new era of digital globalization has begun and the world has never been more deeply connected by commerce, communication, and travel than it is today. Moreover, the model of globalization is shifting and so, while trade was once dominated by tangible goods and was largely confined to advanced economies and MNEs, current global data flows are surging, and digital platforms permit more states and companies to participate which means that present model has far-reaching implications. Hence, globalization has entered a new epoch characterized by data flows that transmit information, ideas, and innovation and so, digital platforms generate more effective and transparent global markets in which far-flung buyers and sellers find each other with a few clicks. To that extent, the near-zero marginal costs of digital communications and transactions release new options for conducting business across borders on an immense level.56 A. Ouandlous and A. Narsing57 argue “that MNCs are not only moving toward globalization of markets and globalization of production, but toward a unified global market economic system. And the only potential bargaining power left to developing countries is to form an alliance among them to protect their interest against the most powerful multinational corporations. This potential alliance cannot survive for too long given the fragmentation and the divergence of interests that exist among these countries. The emergence and increasing number of multinational corporations from developing countries, as shown in this paper, are making this alliance even more fragile.” The OECD Guidelines for MNEs do not shift responsibilities from governments to enterprises, but they state that obeying domestic laws in the jurisdictions in which the enterprise operates and/or where they are domiciled is the first obligation of enterprises. Moreover, the nature and extent of due diligence are affected by factors, such as the size of the enterprise, the context of its operations, its business model, its position in supply chains, and the nature of its products or services.58 Large enterprises global value chains (GVCs) have augmented the prospective for individuals and nations to benefit from globalization.59 Moreover, the rise of information technology and transportation innovations has globalized production, which has been fragmented along so-called global value chains: workers across different nations that contribute to the design, production, marketing, and sales of the same David Smick, “Could globalization crack up?” International Economy, fall 2012; Joshua Cooper Ramo, “Globalism goes backward,” Fortune, November 20, 2012; Jeffrey Rothfeder, “The great unraveling of globalization,” Washington Post, April 24, 2015. 57 Arav Ouandlous, Anthony Narsing, Multinational Corporations and Economic/Digital Technological Divide: An Analytical Approach to Global Economic Integration. Volume 2, Number 12, International Business & Economics Research Journal 27 p 36. 58 OECD (2018), OECD Due Diligence Guidance for Responsible Business Conduct. 59 OECD (2017), OECD Skills Outlook 2017: Skills and Global Value Chains, OECD Publishing, Paris. https://doi.org/10.1787/9789264273351-en. 56

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product. Thus, GVCs give companies the option of entering production processes they might be unable to develop alone but offshoring enables companies to reorganize and achieve productivity gains leading to job creation. Furthermore, GVCs offer companies and nations opportunities to increase their productivity by specializing in tasks in which they perform better and so, increasing competition among companies accelerates the adoption of new ways of organizing work and production.60 COVID-19 is currently changing our understanding of the globe challenging ideologies from capitalism to neoliberalism and from globalization to nationalization. Was COVID-19 pandemic an inevitable result of globalization? The answer is no but merely the spread of the virus assisted by individuals’ travel because globalization has not created the virus. On the other hand, the pandemic has seriously influenced the world’s globalization. Moreover, the pandemic’s adverse consequences on globalization are temporary generating more international cooperation among nations on the long run. The pros of digitization have emerged during pandemic adding to a faster development of the e-globalization. It is supposed that the globe has realized that humanity as a whole share a common fate despite all the nationalistic differences leading to more co-operation than gearing toward nationalization. The temporary closing of borders to maintain public health cannot be considered as a big step toward nationalization but merely a medical measure for fighting the specific virus.

2.7

Fintech

The rise of new technologies has altered the operation, regulation, and supervision of financial markets and so, new technologies revolutionize the world of traditional finance. Hence, the concept of “fintech” refers to the use of technology in the financial world, encompassing the use of technologies to stimulate new or innovative financial products and services.61 Technology enhances financial services through its effect on cost reduction, improved decision-making or execution, and broadened access. For instance, reductions in computing, storage, and device cost expedite the analysis and affordability of massive volume of data and the accessibility of financial services. Hence, fintech includes financial services and products adopting technology for improved service delivery such as e-banking and AI-based banking. Moreover, the revolution path of fintech involves the technology firms that reinvent the business model of finance through disruptions in the design and delivery of financial Baldwin, J. and B. Yan (2014), “Global value chains and the productivity of Canadian manufacturing firms,” Economic Analysis Research Paper Series, No. 090, Statistics Canada, Analytical Studies Branch. 61 Douglas W. Arner, Janos Nathan Barberis & Ross P. Buckley, “The Evolution of Fintech: A New Post-Crisis Paradigm?” (2015) University of Hong Kong Faculty Law Research Paper NO. 2015/ 047, https://papers.ssrn.com/sol3/papers.cfm?abstract_id¼2676553. Chris Brummer, Fintech Law in a Nutshell (Minnesota, USA: West Academic Publishing, 2019). 60

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services such as fast payments, marketplace lending, and decentralized systems such as blockchains.62 Data mining systems across the board are reproducing the biases produced by human decisions taking place for the reason that the data inputted into the computer have been simplified to teach the computer to learn by example, oftentimes a flawed example.63 Hence, developers have generated predictive algorithms that mine personal information to make guesses about individuals’ actions and risks and so, credit-scoring mechanisms embrace factors that do not just assess the risk features of the borrower; they also reflect the riskiness of the environment in which a consumer is utilizing credit, along with the riskiness of the products a consumer uses. On July 31, 2018, the OCC announced its decision to resolve the regulatory uncertainties regarding the application of banking regulations to fintech companies and to allow these newly minted nondepository entities to apply for national bank charters in the Fintech Charter Decision.64 Presently, trading systems use algorithms for trading – algorithm determines the time, price, quantity, and routing of orders. The algorithm also monitors orders and market conditions, among other elements of the negotiation process, of a security altering the market dynamics and the contests regulators face to protect consumers and investors and so, preserving the stability of financial systems. However, new technologies or new ways to use already existent technologies generated new financial services and products and so, alongside with the emergence of new actors, it has inspired a technological revolution in the financial industry, instigating regulatory opportunities and challenges. Fintech consists of a set of recently developed digital computing technologies that have been applied or will likely be applied in the future to financial services formulating a broad typology of fintech comprising seven categories, namely, cyber security, mobile transactions, data analytics, blockchain, peer-to-peer (P2P), robo-advising, and the IoT.65 Furthermore, algorithmic trading (AT) is described as the use of computer algorithms to automatically make certain trading decisions, submit orders, and manage those orders after submission. It is worth noting that 62 Haitian LU Bingzhong, WANG Qing, WU Jing YE, Fintech and the Future of Financial Service: A Literature Review and Research Agenda, at: https://ssrn.com/abstract¼3600627. 63 Martin Stumpe & Craig Mermel, Applying Deep Learning to Metastatic Breast Cancer Detection, GOOGLE AI BLOG (Oct. 12, 2018), http://ai.googleblog.com/2018/10/applying-deep-learning-tometastatic.html. 64 The Office of the Comptroller of the Currency (OCC) charters, regulates, and supervises national banks and federal savings associations and licenses, regulates, and supervises the federal branches and agencies of foreign banking organizations. The OCC supervises these banks to ensure that they operate in a safe and sound manner, provide fair access to financial services, treat customers fairly, and comply with applicable laws and regulations. Roberto Mangabeira Unger, The Knowledge Economy 3 (2019). Press Release, Office of the Comptroller of the Currency, OCC Begins Accepting National Bank Charter Applications from Financial Technology Companies (July 31, 2018), https://www.occ.gov/news-issuances/news-releases/2018/nr-occ-2018-74.html. 65 Chen, M., Q. Wu, and B. Yang. 2019. How valuable is Fintech innovation? The Review of Financial Studies, 32:2062–2106.

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compared with human beings, algorithmic investment strategies have the capacity to create superior returns because of their informational advantage and trading speed. In addition, their informational advantage comes from the larger capability of algorithms than humans to receive and process information which means that their speed advantage, often through high-frequency trading (HFT), empowers the algorithm to pick the most favorable deals in the market ahead of human investors. On one hand, AT fastens price discovery, improves price informativeness, and advances market quality. On the other hand, AT presents adverse selection costs to slow traders and AT contributes to market efficiency concerning public information as long as such information is disclosed by other sources taking place at the expense of discouraging the acquisition of new information. E-currencies might bring forward e-banks, but the main problem is the matter of their acceptability as money and the control of monetary policy because there is a great danger to overproduce e-money with not a link to economic value of goods and services in an e-market which not to be forgotten are utilized by human beings and not machines. Furthermore, with the arrival of the fourth industrial revolution, regulators have faced the challenges posed by the use of new technologies along with the appearance of new players in the provision of financial services embracing neo-banks, fintech firms, and traditional entities focused on digital transformation processes. Neo-banks are entities that usually have a traditional bank behind them, even with physical branches, but have adjusted their tools and user interaction to mobile platforms which means that they offer retail banking services primarily through smartphone applications and Internet-based platforms.66 In 2018, banks globally invested more than $9.7 billion to augment their digital banking competences only when it comes to customer service not taking into account middle and back office innovation processes such as risk management, compliance, operations compliance, and accounting.67 Furthermore, the fourth industrial revolution has also brought forceful competition for technological innovation not only fueling business strategies for participants in financial markets but also competition among countries raising their profile as fintech centers or fintech hubs.68

Basel Committee on Banking Supervision, “Sound Practices. Implications of fintech developments for banks and bank supervisors” (2018) Bank for International Settlements Publication, available at https://www.bis.org/bcbs/publ/d431.pdf. 67 Val Srinivas & Angus Ross, “Accelerating digital transformation in banking. Findings from the global consumer survey on digital banking” (2018), https://www2.deloitte.com/insights/us/en/ industry/financial-services/digital-transformation-in-bankingglobal-customer-survey.html. 68 Ross P. Buckley, Douglas W. Arner, Robin Veidt & Dirk A. Zetzsche, Building FinTech Ecosystems: Regulatory Sandboxes, Innovation Hubs and Beyond, University of Hong Kong Faculty of Law Research Paper No. 2019/100, https://papers.ssrn.com/sol3/papers.cfm?abstract_ id¼3455872. 66

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In fact, regulators are called in the fintech era69 to position themselves within the ecosystem of financial innovation, finding the right balance between protecting the stability of the system and promoting innovation.70 It is worth noting that financial regulators worldwide are accepting various strategies to fintech and so, regulators have departed from conventional regulatory strategies finding a suitable balance between the benefits and risks of technological innovation in the financial industry.71 Hence, via new regulatory approaches, regulators advance innovation without compromising the protection of consumers and investors, in addition to the confidence and stability of the financial system. Moreover, regulatory responses depend on the type of fintech development, including crypto assets, digital payments, and the use of artificial intelligence in the banking, insurance, and capital markets industries.72 Taking into account that technology progresses faster than regulatory processes, for certain fintech issues, some regulators have prohibited certain activities or operations while evaluating the effects and possible risks that innovation epitomize for the financial system.73 It is worth noting that the growth and rapid expansion of crypto currency mining have given China an imperative impact on the development of blockchain, and China has recognized its advantages and potential and so, considering blockchain technology a tool permitting them to advance their regional interests in commerce.74 However, in February 2018, China imposed a de facto ban on Initial Coin Offerings by adding international crypto currency exchanges to its

69 Johannes Ehrentraud, Denise Garcia Ocampo, Lorena Garzoni & Mateo Piccolo, Policy responses to fintech: a cross-country, FSI Insights On Policy Implementation No 23 (2020), https://www.bis. org/fsi/publ/insights23.pdf. 70 “The race to become Islamic banking’s fintech hub. Financial centers in the Middle East scramble to join the fintech wave” (2017) The Economist, https://www.economist.com/finance-andeconomics/2017/06/01/the-race-to-become-islamic-bankingsfintech-hub; Jamie Lee, Singapore, London in race to be top global fintech hub (2016) The Business Times, available at: https:// www.businesstimes.com.sg/banking-finance/singapore-london-in-race-to-be-topglobal-fintechhub; Yanin Alfaro, “México se convertirá en el hub de fintech en América Latina. Una vez que entre en vigor la Ley Fintech habrá una explosión en la inversión de tecnologías financieras” (2017) Entrepreneur, https://www.entrepreneur.com/article/306044. 71 Basel Committee on Banking Supervision, “Sound Practices. Implications of fintech developments for banks and bank supervisors” (2018) Bank for International Settlements Publication, https://www.bis.org/bcbs/publ/d431.pdf. 72 Aurelio Gurrea-Martínez & Nydia Remolina, The Law and Finance of Initial Coin Offerings, in Chris Brummer (ed.), Cryptoassets: Legal, Regulatory and Monetary Perspectives (Oxford University Press, 2019) Nydia Remolina, “Contextualizing Regulatory Sandboxes in Latin America” (2019), available at https://fintechpolicy.org/2019/01/20/contextualizing-regulatory-sandboxes-inlatin-america/. 73 Lin, “Managing the Risks of Equity Crowdfunding: Lessons from China” (2017) JCLS 327 74 Wharton, University of Pennsylvania, “China’s Blockchain Dominance: Can the U.S. Catch Up?” (2019), https://knowledge.wharton.upenn.edu/article/can-u-s-catch-chinas-blockchain-dominance/.

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“Great Firewall.”75 Furthermore, in early 2019, the Chinese cyber security and Internet regulator, the Cyberspace Administration of China, published a prohibitive regulation of anonymity, so hindering many public blockchain use cases.76 The Great Firewall of China is officially called the Golden Shield Project and involves Internet censorship and surveillance by the Chinese Ministry of Public Security (MPS). The regulation is applicable to firms that have websites or mobile applications offering information and technical support to the public using blockchain and so, these firms register their names, domains, and server addresses in the registry that for this purpose will be carried by the Internet and cyber-security authority. Moreover, the rule affirms that firms that work with blockchain permit authorities to access the data stored in the distributed database and that they introduce registration procedures demanding their users to have an identification card or mobile phone number. Furthermore, firms will be required to monitor content and censor information that is prohibited by current Chinese law.77 South Korea’s legalization of crypto currencies generated crypto investments in Asia, and has positioned South Korea as the world’s third-largest crypto market.78 However, when observing the high costs of crypto currency exchanges in the country, the excessive speculation in crypto assets, and their fall in prices worldwide in 2018, along with the hacks that happened in several South Korean crypto currency exchanges, the government accepted more restrictive measures such as banning initial coin offerings.79 It could be said that regulators prohibiting certain fintech industries do so with the reason of waiting while they get a better understanding of the risks and challenges of these technological innovations so as to then implement an adequate regulatory strategy. Additionally, albeit a state approves a prohibitive model, these prohibitions are limited not applying consistently across the all fintech industry and so, regulators limit specific kinds of fintech subindustries, such as crypto currencies, but they endorse others such as digital payments under the established monetary system, which indicates that the uncontrolled offer of any kind of tokens used as money is causing problems on the quantity of money circulating in an economy igniting problems of stability of prices and values in order for an economy to function

Harsch Taneja & Angela Xiao Wu, “Integrating Access Blockage with Cultural Factors to Explain Web User Behavior: The Case of China’s Great Firewall” (2014)The Information Society 297, https://www.tandfonline.com/doi/abs/10.1080/01972243.2014.944728. 76 http://www.cac.gov.cn/. Robert Schwertner, “Does China ban Cryptocurrencies?” (2019), https:// cryptorobby.blog/2019/01/11/does-china-bancryptocurrencies/. 77 Hui Huang, “Online P2P Lending and Regulatory Responses in China: Opportunities and Challenges” (2018) 19 EBOR 63. 78 Carlos A. Arango-Arango, María M. Barrera-Rego, Joaquín F. Bernal-Ramírez & Alberto BoadaOrtiz, “Criptoactivos” (2018) Banco de la República de Colombia Documentos Técnicos o de Trabajo, http://www.banrep.gov.co/es/publicaciones/documento-tecnico-criptoactivos. 79 Yogita Khatri, South Korea Will Maintain ICO Ban After Finding Token Projects Broke Rules (2019) CoinDesk, https://www.coindesk.com/south-korea-will-maintain-ico-ban-after-findingtokenprojects-broke-rules. 75

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according the classical principles of economy. Moreover, in the area of crypto assets, the UK regulator has proposed to ban the purchase and sale of this product to retail consumers excused by the greater risks and information asymmetries faced by these actors, particularly in the context of these complex and volatile products.80 Similarly, the Financial Superintendence of Colombia prohibited financial entities from guarding, investing, intermediating, and operating with crypto currencies which are justified on the fact that crypto currencies are used for money laundering and financing of terrorism.81 Finally, another regulatory strategy to advocate financial innovation consists of the enactment of new legislation for fintech firms such as new licensing regime for neo-banks, new legislation for blockchain and virtual assets, and Fintech Acts.82 Germany’s government has passed a new strategy via a law outlining the ways the leading EU state is utilizing blockchains.83 In reality, technological developments promote competition in the financial service industry and so, reducing transaction costs which indicates financial inclusion and companies’ access to finance.84 On the other hand, the use of technologies in the financial sector generates problems because the use of algorithms for credit scoring causes discrimination and financial exclusion, which means that the increasing use of cyberspace has exposed people and companies to more cyberattacks and so, if these risks are not tackled, the use of technology will end up damaging the most fundamental pillar of a financial system which is trust.85

80 Financial Conduct Authority, Restricting the sale to retail clients of investment products that reference cryptoassets (2019), https://www.fca.org.uk/publications/consultation-papers/cp19-22restricting-sale-retail-clients-investment-products-reference-cryptoassets. 81 Superintendencia Financiera de Colombia, “Criptoactivos” (2018), https://www.superfinanciera. gov.co/inicio/criptoactivos-10090492 Superintendencia Financiera de Colombia, “Operaciones con ‘monedas virtuales’ NO se encuentran amparadas por ningún tipo de garantía privada o estatal” (2017), https://www.superfinanciera.gov.co/jsp/Publicaciones/publicaciones/ loadContenidoPublicacion/id/10089 581/dPrint/1/c/00. 82 Hong Kong Monetary Authority, Virtual Banks, https://www.hkma.gov.hk/eng/keyfunctions/ banking/banking-regulatory-and-supervisory-regime/virtual-banks/ Malta Virtual Financial Assets Act (2018), http://www.justiceservices.gov.mt/DownloadDocument.aspx?app¼lom& itemid¼12872&l¼1 Office of the Comptroller of the Currency, Exploring Special Purpose National Bank Charters for Fintech Companies (2020), https://www.occ.gov/publications-andresources/ publications/banker-education/files/exploring-special-purpose-nat-bank-chartersfintechcompanies.html Ley para regular las instituciones de tecnología financiera (2018), http:// www.diputados.gob.mx/LeyesBiblio/pdf/LRITF_090318.pdf. 83 Anna Baydakova, Germany Passes National Policy to Explore Blockchain But Limit Stablecoins, COINDESK (2020), https://www.coindesk.com/germany-passes-nationalpolicy-to-exploreblockchain-but-limit-stablecoins; Federal Ministry of Economic Affairs and Energy, Blockchain Strategy of the Federal Government (2020), https://www.blockchainstrategie.de/BC/Navigation/ DE/Home/home.html. 84 World Bank, “Fintech and Financial Inclusion,” http://pubdocs.worldbank.org/en/ 877721478111918039/breakout-DigiFinance-McConaghy-Fintech.pdf. 85 Robert Bartlett, Adair Morse, Richard Stanton, & Nancy Wallace, Consumer-Lending Discrimination in the FinTech Era (2019), https://faculty.haas.berkeley.edu/morse/research/papers/discrim. pdf.

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It could be said that “fintech era” brings differentiating elements such as using a massive amount of data collected via the use of social networks and websites serving as precious tools of information to understand patters and behaviors of financial consumers. Moreover, there is an increasing automatization of financial services introducing new challenges when financial services are not directly provided from the interaction between firms and consumers. Furthermore, new actors have emerged, embracing fintech firms and big tech companies bringing forward new challenges, not only from the perspective of the risks and challenges that financial regulation has to tackle but also in terms of the costs of the regulatory agenda.86 Besides, the interaction between old and new actors generates a fragmentation in the financial services supply chain and so, notwithstanding the advantages such as competition, innovation, and financial inclusion caused by the existence of new actors, regulators must be aware of the new risks potentially generated.87 It is worth noting that a regulatory agenda for fintech should tackle properly riskbased supervision, principle-based regulation, and an activity-based regulation because risk-based supervision has become the predominant approach to the regulation and supervision of financial markets around the globe. Risk-based supervision is focusing on assessing the level of risk created by certain actors and activities and applying regulatory strategies to tackle those risks in an inclusive way which means that not only addresses individual risks but also addresses the risks for the whole financial system. Fintech is distinguished by rapid changes and technological developments needing permanent monitoring activity by the regulator.88 Secondly, principle-based regulation meets regulatory outcomes due to the fact that AI entities pursue goals such as protecting the interest of the consumers, rather the following procedures differing from the rule-based approach being vital for the fintech era because of the inability of the regulator to catch up with the market.89 Finally, activity-based regulation is suitable in this new era of financial technologies because an institution-based approach encompasses the imposition of different rules for different entities albeit they perform similar functions or they generate similar risks by leaving aside other issues such as fairness and antitrust issues which means that regulatory arbitrage and shadow banking are emerging being inadequate

World Economic Forum, “Beyond fintech: a pragmatic assessment of disruptive potential in financial services” (2017); Dong He et al., “Fintech and Financial Services: Initial Considerations” (2017) International Monetary Fund. Héctor Vázquez, “Big Data, la Revolución de los Datos Masivos” (2019), https://www.michaelpage.es/advice/empresas/desarrollo-profesional/big-data-larevoluci%C3%B3nde-los-datos-masivos. 87 Christopher Brummer & Yesha Yadav, “Fintech and the Innovation Trilemma” (2019) Geo.L.J., https://georgetownlawjournal.org/articles/298/fintech-and-the-innovation-trilemma/pdf. 88 Christopher Brummer & Yesha Yadav, “Fintech and the Innovation Trilemma” (2019) Geo.L.J., available at https://georgetownlawjournal.org/articles/298/fintech-and-the-innovation-trilemma/ pdf. 89 Douglas W. Arner, Janos Nathan Barberis & Ross P. Buckley, “The Evolution of Fintech: A New Post-Crisis Paradigm?” (2015) University of Hong Kong Faculty Law Research Paper No. 2015/ 047. 86

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to tackle individual and systemic risks produced in the financial system.90 Overall, it could be argued that fintech regulation has to be both activity based and risk based. Moreover, it has to be taken into account that fintech hub is interesting for a country for a variety of reasons such as promoting financial innovation, which means enhancing the attractiveness and competition of financial sectors and so, leading to more financial inclusion and better financial services. Also, lifting a country’s profile as a fintech hub is a profitable business for a country generating revenues for several industries and becoming a leader in the fintech space is advantageous not only for the financial service industry but also for other sectors in the real economy.91 Furthermore, it has to be taken into account that the use of technologies for financial supervision, known as “suptech,” is being used by more and more supervisors relying more on artificial intelligence, machine learning, and blockchain for the implementation of their supervisory strategies. Additionally, the use of big data increases the capability of supervisors by extracting useful information from large volumes of unstructured data supporting risk assessments of financial institutions, monitoring or examination exercises, or improvements in regulatory guidance. To that extent, markets and reporting systems based on blockchain or distributed registries permit supervisors to supervise the exposures and transactions of market participants in real time as network nodes, which along with artificial intelligence competences advance supervisory functions.92 It has to be taken into consideration that CEOs play a key role in overall firm management, involving corporate risk, profits, and business strategies. Brocas93 et al. argue that people’s risk-taking stances augment after they earn profits. Nevertheless, during crises, investors prefer firms managed by CEOs with stable risk management capacity. To that extent, since FCEOs have risk management capacity, firms operated by FCEOs have greater survival probabilities than other companies. Moreover, Albuquerque et al.94 advocate that corporate social responsibility (CSR) diminishes risk by augmenting firm value via firms’ long-term profitability and

Marc Lebonte & Baird Webel, “Activities-Based Regulation and Systemic Risk” (2019) CRS Insight, https://fas.org/sgp/crs/misc/IN10997.pdf https://www.cfainstitute.org/research/foundation/ 2017/fintech-and-regtech-in-a-nutshell-and-thefuture-in-a-sandbox; https://www.bis.org/publ/ arpdf/ar2019e3.htm. 91 Nydia Remolina, “Contextualizing Regulatory Sandboxes in Latin America” (2019) Fintech Policy, https://fintechpolicy.org/2019/01/20/contextualizing-regulatory-sandboxes-inlatin-america/ . Bank of International Settlements, New BIS Innovation Hub Centre in Singapore (2019), https:// www.bis.org/press/p191113.htm. 92 Nydia Remolina, “Open Banking: Regulatory Challenges for a New Form of Financial Intermediation in a Data-Driven World” (2019) SMU Centre for AI & Data Governance Research Paper No. 2019/05, https://papers.ssrn.com/sol3/papers.cfm?abstract_id¼3475019. 93 Brocas, I., Carrillo, J.D., Giga, A., & Fernando, Z. (2019). Risk aversion in a dynamic asset allocation experiment. Journal of Financial and Quantitative Analysis, 54(5), 2209–2232. 94 Albuquerque, R., Koskinen, Y., & Zhang, C. (2019). Corporate social responsibility and firm risk: Theory and empirical evidence. Management Science, 65(10), 4451–4469. 90

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Globalization, AI, and Accounting

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sustainability. In addition, Kang and Ryu95 argue that “the relationship between investors’ valuations (Tobin’s Q) and FCEOs shifts from negative to positive as company risk increases. . . . that FCEOs contribute to company value in the stock market through their risk management ability. Notably, we suggest that associating the tendency to avoid risk with risk management ability could be a logical error caused by prejudice against women’s tendencies to avoid risk.” There is a need for efficacy of consensus of increased information distribution and so, increased information distribution lessens information asymmetry but inducing increased collusion. Consequently, a trade-off exists between decentralized consensus and information distribution on the blockchain. Moreover, economic issues are surfacing in fintech. On one hand, technology-enabled alternative data source, coupled with fast computing power, advances financial decisions. On the other hand, technology increases the possibility of fraud and fraud detection at the same time.

2.8

Globalization, AI, and Accounting

Globalization and the activities of MNEs present an increasing challenge for macroeconomic measures predominantly those intended to reflect national economies. Furthermore, in a globalized world with limited to no trade barriers, MNEs will function across multiple national economies, often under a single management or control structure. Besides, one of the problems that MNEs pose for macroeconomic measurement is the issue of assigning economic ownership of Intellectual Property to the different fractions of a global value chain and to national economies. In recent years, the second issue on R&D concerning MNEs and globalization has received increasing attention and so, one of the key contests of economic globalization is clarifying how capital services of intellectual property enter the globally organized production chains. First of all, the international fragmentation of production chains, inside or outside MNE structures, denotes that business functions such as R&D and software development are being separated and disconnected from the process of physical transformation. Secondly, production chain fragmentation also enters the stages of physical transformation such as those found in the automobile or aircraft industry. R&D capitalization implies that intellectual products are accounted for like any other fixed asset in the National Accounts. Taking into account that many developments are complicating the globalization puzzle, an extra complicating factor is that IP, or intangible assets more broadly, becomes a medium for tax planning. Moreover, MNEs locate their IP and report related IP revenues in low-tax jurisdictions and afterward charge affiliated firms, which report substantive shares of the MNEs

95

Sungchang Kang, Doojin Ryu, Investors’ valuations of female CEOs: Risk management performance and information asymmetry, at: https://ssrn.com/abstract¼3557015 p14, 16.

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turnover, for the use of the IP and so, such tax planning arrangements implicate a variety of special purpose entities (SPEs) located in a series of states. Thus, a national accountant is able to observe only fragments of the tax planning arrangement and is easily misled by the information being obtained at the level of individual SPEs, or other entities in a tax planning arrangement. Moreover, it has to be taken into account that judgments on substance or discrepancies in legal vis-à-vis economic ownership are difficult.96 Corporations have been directed toward the adoption of AI in their activities, particularly in accounting and auditing fields. Even though the adoption of AI in corporations augments their efficiency, they have to monitor the costs and updates needed for intelligent systems to circumvent any risk and uncertainty. Nevertheless, the present AI adaptation process differs across countries and even between corporations in the same country.97 Which is the usefulness of AI? There are doubts about the usefulness of AI technology permitting firms to have concerns about whether adopting AI is worth it or not. On the other hand, it could be said that the existence of AI itself may alter the workload of accountants and auditors and augment their efficiency and effectiveness.98 Inspector general and internal auditors must have the technical capability and additional legal authority to critically review testing and validation procedures and the institutions that carry them out and to move forward with enforcement or other corrective measures. Anyway, there are positive relationships between AI, productivity, auditing process, and accounting information systems and so, the adoption of AI increases work efficiency which permits better decisions, diminishing the time required to perform accounting tasks, creating new jobs, and permitting employees to focus on a higher level and more important tasks. Additionally, AI has enhanced the accounting information systems to some extent, but current AI technology is not enough to enhance and develop accounting information systems in the future. Managers in the private and public sectors utilize AI to improve the speed and quality of work requiring specific planning and organizing of AI adoption to circumvent unsatisfactory results. Moreover, managers have to integrate AI systems in order to improve firm performance and reduce the threat of misusing AI systems. Solaimani99 et al. argue that “Empirical results show a significant positive impact of AI on firm performance, the auditing process and accounting information systems.

96 Mark de Haan & Joseph Haynes R&D capitalisation: where did we go wrong. Conference on Research in Income and Wealth. The Challenges of Globalisation in the Measurement of National Accounts March 9-10 2018, Washington DC. 97 Gotthardt, M., Koivulaakso, D., Paksoy, O., Saramo, C., Martikainen, M., & Lehner, O. M. (Eds.). (2019). Current state and challenges in the implementation of robotic process automation and artificial intelligence in accounting and auditing. ACRN Oxford Journal of Finance & Risk Perspectives, 8, 31-46. http://www.acrn-journals.eu/resources/SI08_2019c.pdf. 98 Nickerson, M. A. (2019). AI: New risks and rewards. https://sfmagazine.com/post-entry/ april2019-ai-new-risks-and-rewards. 99 Reem Solaimani, Fatima Rashed, Shahad Mohammed, Walaa Wahid ElKelish, The Impact of Artificial Intelligence on Corporate Control at: https://ssrn.com/abstract¼3576777 p171.

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More specifically, AI intervention increases firm productivity, creates new jobs and speeds up work processes. However, current AI technology is less likely to redefine auditing roles and still insufficient for developing accounting information systems. Human integration with AI systems will lead to more efficient results.”

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Logistics was defined as a function that was minimizing total distribution costs and logistic costs or maximizing profits, while achieving desired levels of service performance. Jules Dupuit100 firstly introduced the concept of logistics and compared road transport with transport over water in order to identify the most optimal way of transporting goods from origin to destination. Modern logistics incorporates information technology, generating the definition that “modern logistics is the movement and storage of goods, together with associated information flows, from the beginning to the end of the supply chain.”101 To that extent, logistics is directing toward maximizing local flexibility inside the company and customer service issues. In other words, logistics has been implemented as a part of the strategic level decision-making process. Horizontal logistics concern relations between parties within a group of companies at the same level in a supply chain, while vertical logistics concern relations between companies at different levels in the supply chain. Also, logistics is the science dealing with the planning, organization, control, and automation of the material and information flow. So, the logistics combine machines, information technology, and factory organization and economy. Furthermore, logistic management is the forward and reverse movement of outputs within a corporation and with its external environment and so, coordinating, enhancing, and integrating all logistic actions with other functional areas of a business entity links with performance. Likewise, management of manufacturing companies has to expand outbound activities they accomplish encompassing drivers, such as information technology to advance performance, along with seeing outsourcing outbound activities.102 What is e-logistics? E-logistics are designed to fit into the new, electronic economy and the cyberspace transactions. Globalization is one of the most important forces driving the restructuring of the world economy.103 New trends in investment, See Dupuit Jules (1952) “On the measurement of the utility of public work” reprinted in International Economic Papers No 2 translated from French by Barback R, Macmillan Press London. 101 Cooper, Brown, Peters “European Logistics: Markets, Management and Strategy” 1994 Blackwell Publishers. 102 Ahmad, A. A. (2017). Factors affecting the organizational performance of manufacturing firms. International Journal of Engineering Business Management, 9, 1–9. doi:10.1177/ 1847979017712628. 103 Globalisation of Industry: Overview and Sector Reports, OECD, 1996. 100

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trade, and collaboration between firms have immensely changed the scope of world business and extended the role of foreign companies in national economies. Globalization, in economic terms, can be thought of as a process in which business decisions, production processes, and markets gradually come to exhibit more “global” characteristics and less “national” ones. Globalization is characterized by structural reforms – especially trade and investment liberalization – and increased trade and international investment flows. International trade and investment promote growth, alter the composition and geographical distribution of economic activities, stimulate competition, and facilitate the international diffusion of technologies. P. Hirst and G. Thompson104 identify that globalization is “large and growing flows of trade and capital investment between countries.” Globalization also refers to the rapidly improved communications systems (information and transportation), which have served to reduce distances between different countries and regions, bringing not only a greater exchange of goods and services but also more exchanges between people and information from different countries. The essential task of logistics is to create a flexible and coherent production system that spans the globally dispersed set of production resources, and logistics is not merely a set of shipping and delivery transaction that can be made paperless. Only by linking all logistic activities directly to the organization’s strategic plan can logistics manager work effectively to support their organization’s strategy for achieving competitive advantage. The cost of information was one of the few business costs to reduce during the 1980s. The revolution in information technology provides the opportunity for logistics to utilize transaction-based and decision support systems as a source of competitive differentiation and increased market share. Management of inbound raw materials utilizing electronic data interchange (EDI) between the organization and key suppliers can provide substantial cost savings. Due to the complexity of logistics, it is nowadays almost inconceivable to manage the logistics operation without the support of computers and management information systems. Computer hardware and software provide a solid basis for computer systems to be used in logistics. Electronic data interchange is currently one of the most important subjects in the area of computer applications in logistics. The use of EDI in logistics applications mainly concerns the electronic interchange of trading documents, such as purchase orders, acknowledgments, letters of credit, bills of lading, and invoices.105 The advantages of EDI are identified at the operational level (increased productivity, cost reductions), the technical level (improved customer service), and the strategic level (using JIT suppliers, repositioning on the market). EDI has significant implications regarding the firm’s behavior and its organizational

104 P Hirst, G Thompson “Globalisation: Ten frequently asked questions” 1996 Soundings Vol 4, 47–66, p48. 105 Georgios I Zekos, The Use of Electronic Technology in Maritime Transport: the Economic Necessity and the Legal Framework in European Union Law, http://www.bailii.org/uk/other/ journals/WebJCLI/1998/issue3/zekos3.html.

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structure. It has achieved internal efficiency of the firm and its competitive position by speeding up its response to customer service. There are some problems related to the interconnectivity of EDI systems of different companies. The differences are related to data structure, operating system, transmission services, organization of data, and organizational differences between companies. Thus, there is a need to agree upon all that issues. The system provider defines the message format, and all participants have to apply the same message format. The same rule applies if the data have to be sent according to legal regulations. There is a time gap between the production of the goods and their consumption. The time gap between consumer and producer arises when goods are not produced at the same time, as the consumer requires them. The warehousing process bridges this gap. The second is the geographical gap, which is covered by transportation. Most companies are not able to give a clear insight into their logistical costs. Logistical costs are generated in several departments of the company and are allocated to other cost components in corporate accounting. According to measures, 2.3% and 3% of the companies’ total turnover are, respectively, warehousing costs and transportation costs.106 Can we isolate transport as an independent activity from the logistical system? Transport is part of the logistical system, which makes it complex to separate transport as an independent activity. The logistical structure determines the points in space and the patterns of trading links, which pairs of points in space are connected and in which direction. Decisions on product design affect transport through the complexity of the product and packaging of goods. Concepts of logistic organization including distance, speed, frequency, and point in time do not translate purely into consequences for transport logistical chain. Transport is a required precondition of economic growth and of extended logistical reach, and transport is inevitable consequence of the development.107 Significant advances in operations and logistics software tools, along with the growth of third-party logistics services, have enabled MNEs to more efficiently segment their production globally, while at the same time reducing inventory and shipping times and so, reducing governance costs. With reliable single sources for nearly all out-bound logistics services, MNEs have achieved both cost and time savings.108 Management of inbound raw materials utilizing EDI between the organization and key suppliers can provide substantial cost savings. Logistics manage the interrelationship of all the factors, which affect the flow of both information and goods necessary to fill orders. Strategic planning forces management to reconcile two contradictory tasks: long-term planning with short-term responsiveness to

A T Kearny “Value Added Logistics” 1993 Amsterdam. Lise Drewes Nielsen, Per Homann Jespersen, Tina Petersen, Leif Gjesing Hansen, Freight transport growth ––a theoretical and methodological framework, European Journal of Operational Research 144 (2003) 295–305 www.elsevier.com/locate/dsw. 108 S Feinberg, M Keane, Accounting for growth of MNC-based trade using a structural model of US MNCs, 2003 SSRN-ID3741103. 106 107

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customers. The principles of logistics excellence are the following: (1) Link logistics to corporate strategy. (2) Organize comprehensively. (3) Use the power of information. Successful logistics departments take full advantage of information and information processing technology. Electronic data interchange links with customers. Creative use of computer-based models can yield cost service improvements, which bolster competitive advantage. (4) Emphasize human resources. (5) Form strategic alliances. (6) Focus on financial performance. (7) Target optimum service levels. (8) Manage the details. (9) Leveraging logistics volumes. (10) Measure the react to performance. Customer order satisfaction and product processes increasingly often take place not within a single company, but cross company borders with the result that the enterprise executing the engineering processes is virtual. Suitable methodologies of product modeling, engineering data management, and project management must be identified and combined as a unified whole. Moreover, the central element of the global logistic design and controlling system is the assessment of what kind of logistic tasks has to be solved in autonomic way by virtual co-operating companies and what kind of tasks belongs to the capability of the virtual logistic center. Efficient software tools must be used in order to follow the internal and external material flow. The development of just-in-time (JIT) concept has been set by the automotive industry. Logistics is the integrating element of the globalized production, especially of the virtual factories. The production can be fully automated, but other areas might demand a lower grade of automation. L. Cser et al.109 specify that “Virtual factory is a product of globalization in production as well as a new type of task sharing among the manufacturers, and between the manufacturer and customer.” Production networks perform as one factory, independent of borders and geographic distances, and logistics play an important role in the production of a virtual factory. IT of production networks of virtual factories is much higher than those in the traditional one-site factories. At present logistics has been expanding increasingly from the traditional material flow toward the chain connecting the network of production, sales, and maintenance and recycling. Computer and information systems technologies have brought forward the use of Internet, e-commerce, and virtual reality/manufacturing.110 Computers and information systems have become so much a part of every business’s core that other areas of the business are now designed around it. Developments and growth in IT have impacted manufacturing activities concerning their capacity utilization, inventory turnover and quality, price reduction, market share, and return on assets together with the use of computer-integrated manufacturing and virtual manufacturing. The early twentieth century was an era of global integration, marked by extraordinary 109

L. Cser, J. Cselenyi, M. Geiger, M. Mantyla, A.S. Korhonen, Logistics from IMS towards virtual factory, Journal of Materials Processing Technology 103 (2000) 6–13. 110 O. Felix Offodile, Layek L. Abdel-Malek, The virtual manufacturing paradigm: The impact of IT/IS outsourcing on manufacturing strategy, Int. J. Production Economics 75 (2002)147–159. Fujita, M., Krugman, P., Venables, A.J., 1999. The Spatial Economy. MIT Press, Cambridge, London.

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flows of goods, capital, and people. When economies generate rising returns in one sector within a state, that state is ready for “industrial clustering,” which would increase its productivity and wages. Specialization and the speed of relocation of factors depend on the costs of relocating factors, on comparative advantages, and on market rigidities, and comparative advantages contribute to lock a country in its existing specialization pattern slowing relocation of factors.111 Mobility of the highly skilled may necessitate harmonization or coordination between the countries’ policies. What is the relationship between the regional and global economy and the urban social and physical environment? The globalization of communication by satellite is inevitable and is the result of the spread of medium-power telecommunication satellites as support for international television broadcasting. In economic terms, globalization of communication represents high stakes since it is well known that an investment in the global audio-visual market or its content has become a rare and in demand resource. Satellite television without frontiers can be of tremendous use for governmental communication, so much so that the satellite has become a privileged instrument of international state politics. Globalization is likely to manifest itself in the dynamics of financial indices of stock markets in different countries.112 Not only does globalization increasingly impact the social stability of cities, however, it is also important to environmental conditions.113 Globalization not only drives contemporary development114 but also is a long-term process that can be shaped by its own internal contradictions along with a host of other factors.115 The increasing globalization of computer hardware and software production coupled with active government encouragement of inward investment within the context of the single European Market. If technological convergence is a strong factor in determining sectoral ownership patterns, then one may conclude that acquisition and setting up of subsidiaries are a part of a wider search for technology on the part of large international firms. The main difference between national and international firms may well be in the degree of global integration they offer, and industrial policy may trade-off increased market power for a few firms in exchange

Baldwin, R., 2001. The core-periphery model with forward-looking expectations. Regional Science and Urban Economics 31 (1), 21–49. Ottaviano, G.I.P., 1999. Integration, geography and the burden of history. Regional Science and Urban Economics 29, 245–256. 112 Sergei Maslov, Measures of globalization based on cross-correlations of world financial indices, Physica A 301 (2001)397–406. 113 McGranahan, G., Songsore, J., & Kjellen, M. (1999). Sustainability, Poverty and urban environmental transitions. In D. Satterthwaite (Ed.), Sustainable cities (pp. 107–130). London: Earthscan. Douglass, M., & Ooi, G.-L. (1999). Industrializing cities and the environment in Pacific Asia: Towards a policy framework and agenda for action. At http://www.usaep.org/policy/ framing1.html. 114 Held, D., McGrew, A., Goldblatt, D., & Perraton, J. (1999). Global transformations, politics, economics and culture. Stanford: Stanford University Press. 115 Peter J. Marcotullio, Asian urban sustainability in the era of globalization, Habitat International 25 (2001)577–598. 111

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for wider global integration. Technological convergence is defined as the process by which two hitherto different industrial sectors come to share a common knowledge and technological base. Hence, technological convergence is a concept that is used to link industrial sectors that may seem unrelated in consumption terms, because of the cohesion in their technological bases. In order to establish an international information system to facilitate transfer of data across borders, MNEs must take into consideration that they are operating within and among different sovereignties; under different social, economic, cultural, and legal climates; with people of different value systems; and in national markets varying in structure, population, and area. Transborder data flow (TDF) restrictions significantly increase IS costs and influence MIS decisions overseas.116 Has technological convergence meant a convergence of product markets? Digitalization is gradually replacing earlier mechanical technologies and involves the hardware sector more than the software sector, since a lot of it involves using the microprocessor. With multimedia revolution, all forms of media are now accessible to the computer user, such as graphics, newspapers, audio information, or complex combinations of these. Technological convergence has implied rapid redefinition of industry boundaries. In order to utilize the full range of implications that technological changes may have for firm growth, firms must possess a wider range of competencies in generic technologies than that which their production requires. Convergence has created problems of technological access and of market access. Companies may overcome the shortcomings in their internal competencies by entering into alliances of various kinds such as joint ventures and technology collaborations, mergers, and acquisitions with other firms having a complementary range of competencies. Acquiring subsidiary companies or setting up independent subsidiaries may be another mechanism to overcome the shortcomings in the internal competencies of companies. A firm must find a kind of coherence between its own activities and the activities of the acquired/merged firm. Companies that retained a stronger focus on particular product markets appear to perform better.117 Product market access has various costs not all of which are technological. Has collaborative behavior between companies changed the existing technology structures of the collaborating firms very much? High-technology companies are less likely to enter into equity-based relationships for purposes of access to technology.118 What is the impact of technological change, technological convergence, and consequently increased competition on the processes of globalization? It is obvious that the degree of multinationality is notably associated with a company’s increase of its technological advantages from foreign sources. Globalization processes have been Vincent S. Lai, Steven Floyd, The impact of transborder data flow restrictions on international information systems management, Decision Support Systems 22 1998 121–134. 117 Gamberdella, A., Torrisi, S., 1996. Does technological convergence imply a convergence in product markets? Mimeo. IEFE, Bocconi University, Milan. 118 Hagedoorn, J., 1993. Understanding the rationale of strategic technology partnering: interorganizational modes of cooperation and sectoral differences. Strategic Management Journal 14, 371–385. 116

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investigated under the purview of processes of internationalization of capital and foreign direct investment. MNEs enhance systems of innovation through selective specialization. Firms internationalize in order to gain market share and develop control over major foreign markets. Choice of national location within the EU also reflects such factors as government policies and financial incentives to locate in less-developed or industrially declining regions.119 According to Cantwell120 technology, leaders are pacesetters in the globalization of technology, through “. . . the development of international intra-firm networks to exploit the locationally differentiated potential of foreign centers of excellence.” Production inter-nationalization is associated with the maturity stage of innovation development, in which standardization of production and increasing price competition forces relocation to low production cost countries.121 Location decisions have frequently been a function not of labor costs alone but also of the quality of infrastructure and of agglomeration economies.122 According123 to S. Athreye and D. Keeble, long-term problems of finance for computer sector firms, together with market access and profitability considerations for parent firms, may explain the large presence of subsidiary firms in this sector. The global information society brought the development of telecommunications so that not only can data from large knowledge bases be exchanged rapidly but also complex systems can be run remotely. It has to be taken into consideration that one of the most innovative and high-stakes fields of science and practice is medicine.124 The explosive growth of the Internet has enabled complex telemedicine applications, including remote in vivo diagnostic analysis as well as teleconsultation.125 As mentioned above, the firm-specific knowledge is a part of the fixed costs, and the transfer of the knowledge to other plants implies that the production is subject to

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Stone, I., Peck, F., 1996. The foreign-owned manufacturing sector in the UK peripheral regions, 1978–1993: restructuring and comparative performance. Regional Studies 30 (1), 55–68. 120 Cantwell, J., 1995. The globalisation of technology: what remains of the product cycle model? Cambridge Journal of Economics 19, 155–174. p. 157. 121 Frobel, F., Heinrichs, J., Kreye, O., 1979. The New International Division of Labour. Cambridge University Press, Cambridge. 122 O’Connor, D., 1985. Global trends in electronics: implications for developing countries. Mimeo. World Bank, Washington, DC. 123 Suma Athreye, David Keeble, Technological convergence, globalisation and ownership in the UK computer industry, Technovation 20 (2000) 227–245. 124 Puaschunder, J.M. (2019). Artificial Intelligence market disruption. Proceedings of the International RAIS Conference on Social Sciences and Humanities organized by Research Association for Interdisciplinary Studies (RAIS) at Johns Hopkins University, Montgomery County Campus, pp. 1–8, Rockville, MD, United States, June 10–11. Puaschunder, J.M. (2019). On Artificial Intelligence’s razor’s edge: On the future of democracy and society in the artificial age. Journal of Economics and Business, 2, 1, 100–119. Puaschunder, J.M. (2019). On Artificial Intelligence’s razor’s edge: On the future of democracy and society in the artificial age. Scientia Moralitas: International Journal of Multidisciplinary Research, 4, 1, 51–72. 125 Michael Rigby, The management and policy challenges of the globalisation effect of informatics and telemedicine, Health Policy 46 (1999) 97–103.

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increasing returns to scale. Strength, broaden product diversification by expanding product lines or achieving scale economies, high costs of research and development, capital or equipment can be shared with other firms, therefore, the risk will be reduced and the cost burden of a firm is lowered are factors that allow the firms to prefer joint ventures. FDI, either establishing wholly owned subsidiaries or joint ventures, allows a firm to cut cost of production, and then, an MNE is able to earn more from foreign expansion. In the process of globalization, the ability of MNEs to develop integrated technological networks, to coordinate geographically diversified activities, has become the rule. The product cycle model126 shows the international technology flows, which are seen as running from creation in one location, through transfer to a firm or affiliate in another location, to diffusion to a wider variety of firms in the host country. MNEs will have a valuable source of competitive advantage by locating in the technological centers of excellence to get hold of access to differentiated streams of new knowledge. The “new” technologies are complex because of the complex nature of contemporary technological interdependencies. A company is obliged to broaden its technological activity through an international strategy if it wants to improve technological development even in its own immediate primary field of interest. The technological specialization of each company within its field is intimately related to the pattern of its corporate technological competence. Which are the conditions under which firm-specific knowledge and plant-specific knowledge will persuade a MNE to integrate horizontally into a foreign country through both wholly owned subsidiaries and joint ventures? Cultural considerations may be central in an MNE’s choice between acquiring a wholly owned subsidiary and entering into a joint venture with an established domestic firm, in the partnering process. Either way, the foreign partner brings with it plant-specific knowledge. Establishing a joint venture is a choice as long as the cooperation cost can be covered by the gain of joint contribution from the parent firms. Leung127 thinks that the learning and growth matters are important in the decision-making of an MNE. An MNE operates both joint ventures and wholly owned enterprises in a foreign country if the technology advantage over the native competitors is larger and the local firms’ plant-specific knowledge is further valuable.128 A company may choose to concentrate its efforts on each area of activity in particular international locations rather than others. Globalization tends to increase

126 Vernon, R., 1966. International investment and international trade in the product cycle. Quarterly Journal of Economics 80, 190–207. Vernon, R., 1979. The product cycle hypothesis in the new international environment. Oxford Bulletin of Economics and Statistics 41, 255–267. 127 W.-F. Leung, A model of coexistence of international joint ventures and foreign wholly-owned subsidiaries, Japan and the World Economy 10 (1998) 233–252. 128 Horstmann, I.J., Markusen, J.R., 1987. Strategic investments and the development of multinationals, International Economic Review 28, 109–121. Horstmann, I.J., Markusen, J.R., 1987. Licensing versus direct investment: A model of internalization by the multinational enterprise, Canadian Journal of Economics 3, 464–481. Horstmann, I.J., Markusen, J.R., 1989. Firm-specific assets and the gains from direct foreign investment. Economica, 56, 41–48.

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national differentiation and technological specialization. Have countries tended to narrow their technological specialization and become focused on areas of chronological competitive advantage? Globalization makes the understanding of locational specificity further significant, and the nation state remains a potent force in the competitive advantage of nations. According129 to J. Cantwell and O. Janne, “leading multinational firms from the major European centers in their industry tend to carry out technological activity abroad which is relatively differentiated from their domestic technological strengths.” European firms are stirring toward international strategies for technological development to engender geographically dispersed but complementary streams of innovation through the construction of international research networks in Europe.130 Shorter product life cycles, fragmented markets, more demanding customers, consolidation, and mergers of companies together with rapid advances in technology’ processes always presenting a dynamic competitive situation are other factors which further deter the global competitiveness of a company. Manufacturing and operations excellence are essential factors for profitability, and globalization is a critical component of the firm’s competitive strategy.131 Electronic commerce is one of several marketing channels, including the use of the Internet to support interorganizational processes such as marketing, ordering, and related service activities.132 Finally, globalization means moving production facilities around to benefit from the skilled executives or the cheapest labor to position a firm competitively against its competition. Global e-commerce sector is experiencing a growth, and one of the key drivers of such a growth is the upsurge in the size youth customer segment having high cyberspace usage and better social media presence. Amazon, eBay, Alibaba, etc. are expanding their business globally anticipating further growth and so, e-commerce penetration has extended beyond cities, and considerable growth is visible with reference to deliveries outside city limits. E-commerce handles both types of products, and challenges in last-mile logistic efficiency are more in the case products with unpredictable demand. Even in the case of functional products, demand varies across develops challenges to LML efficiency. Last -mile logistics

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John Cantwell, Odile Janne, Technological globalisation and innovative centres: the role of corporate technological leadership and locational hierarchy, Research Policy 28 1999 119–144. Patel, P., 1995. Localised production of technology for global markets. Cambridge Journal of Economics 19, 141–153. 130 Freeman, C., 1995. The ‘national system of innovation’ in historical perspective. Cambridge Journal of Economics 19, 5–24. Zander, I., 1995. Technological Diversification in the Multinational Corporation—Historical Evolution and Future Prospects. In: Schiattarella, R. Ed., New Challenges for Europe and International Business. Confindustria, Rome. 131 S. Nahmias, Production and Operations Analysis, 3rd ed., Irwin, Homewood, IL, 1997. J.T. Harvey, S.F. Quinn, Expectations and rational expectations in the foreign exchange market, Journal of Economic Issues 31 (2) (1997) 615–622. 132 European Commission, 1998. An Introduction to Electronic Commerce. http://europa.eu.int/ ISPO/ecommerce.

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(LML) is the last part of the delivery process, and normally, it takes place minimum distance from the last transit point in the supply chain and so, it is more complex and problematic being the touch point to the customer in the whole purchase process. Hence, the last-mile effectiveness lies in how fast the ordered item is supplied to logistic partner delivering it to the customer. It has to be taken into account that locating the product and the customer is critical issues for the last-mile logistics and so, better effectiveness is to minimize the distances between the logistics company, warehouse, and the customer which means that ecommerce companies must develop an extensive network of existing stores as local distribution centers. Thus, ineffective last-mile delivery leads to slow response rate, low customer satisfaction, ineffective service, and low retention levels influencing the overall profitability.133 The logistics effectiveness leads to competitive advantage through enhanced customer loyalty and so, higher earnings. It is worth noting that the last-mile logistics is the most complex phase in the whole e-supply chain and has a dominant role in safeguarding customer trust and satisfaction. Does e-commerce represent nothing new for how goods are being handled and moved in economy and society? Is e-commerce more than just a tool for optimizing goods flows? E-commerce is an essential element of a lately emerging “sphere of circulation,” the system of information, finance, and goods flows that is both a fundament and an outcome of the network economy.134 What is the typical empirical pattern by which commercial firms translate Internet technology into private value and, more broadly, into sustained economic growth? Doing business electronically over the cyberspace has increased exposure to unfair market practices, insecure means of payment, loss of privacy, and lack of enforceable remedies. E-commerce is defined as any actions undertaken by business, which requires a commercial transaction to be carried out over a network such as the Internet. E-presence starts with one-way information about the enterprise, its products, and services. Furthermore, E-commerce offers benefits to both seller and buyer. The seller can create a global presence and therefore reducing costs, increasing competition, and allowing the ability to customize products. E-commerce has the ability to eliminate the time span between ordering, delivery, invoicing, and payment by using the World Wide Web.135 The new developments of economy forced logistics to respond to changing customer requirements and deal with freedom of choice, discontinuity, flexibility, and economies of scope. The advent of digital economy has triggered the emergence of e-logistics to deal with speed, flexibility, connectivity, interactivity, and electronic products. The competitive advantage is embedded in knowledge and competence, and a company must improve and adapt physical flows according customer’s

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Lim, S. F. W., Jin, X., & Srai, J. S. (2018). Consumer-driven ecommerce: A literature review, design framework, and research agenda on last-mile logistics models. International Journal of Physical Distribution & Logistics Management, 48(3), 308–332. 134 Castells M. The rise of the network society. In: The Information Age: Economy, Society, and Culture, vol.1. Oxford, UK: Blackwell, 1996. 135 G Zekos “Legal Problems in Cyberspace” 2002 Managerial Law 45, Number 5.

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demands. Hence, traditional logistics must be combined with process management and use of cyberspace. Process management requires understanding and acceptance of what has to be done, why, and how. Every company competes in two markets: the marketplace, in which resources and products exist physically, and the market space, which is a virtual world of electronic commerce in which the main object of transaction is information. The market space involves the company, its partners, and its customers and provides the opportunities for developing communication interactions, including customer surveys and information exchange on such things as product warranty and service capabilities. Moreover, it has to be taken into consideration that maintaining customer loyalty is complicated in e-commerce because of difficulty in developing trust in the absence of face to face contacts. Thus, customer service differentiation through customization increases trust and loyalty to every e-commerce company. Nonetheless companies try their level best to make certain uniform quality of service through technology interventions, misgivings still exist in specific domains of customer service, and the logistic is one such function that has an unimpeded role in ensuring unmatched customer experience in e-commerce. To that extent, the effectiveness of the e-supply chain adds to overall customer satisfaction and so, logistics becomes an integral function having the prospective to act as a differentiator in generating better customer experience in e-commerce. Hence, logistic effectiveness of e-commerce sector allows companies to devise strategies to transform logistic function as a crucial differentiator for competitive advantage. Many factors linked to logistic performance such as convenience, availability of the product, delivery, and returns policy add to the better customer satisfaction. Likewise, many logistic matters such as late arrival or nonarrival of the ordered product, the discrepancy in the order specifications, and damages in transit trigger customer dissatisfaction. The accuracy in delivery time and perfect product condition are considered as indicators of logistic effectiveness and so, inadequate logistic effectiveness to the expectations of the customer has instigated failure of many e-commerce companies. It is worth mentioning here that a typical e-supply chain has five key components, such as first-mile delivery, fulfilment, processing, line haul, and the last-mile delivery. First-mile distribution handles all activities concerned in collection of goods from the sellers, which are transported to the fulfilment center or directly to mother warehouse. In the fulfilment center, the packing of goods as per the order placed on the e-commerce website occurs, which means that in the processing stage, sorting of the products is done as per the final delivery location and so, linking the central supply center with the key demand center, via land or air. In addition, the last-mile delivery is the most critical phase of the logistics cycle; where the product is delivered to the end customers which means that the “last-mile” consigns to the last phase in the supply chain dealing with final delivery of products to customers as per their expectations and satisfaction. Furthermore, last-mile delivery experience is essential to the e-commerce, since this stage only has a face-to-face interaction between customer and company. In addition, efficiency management in last mile is central point to key stakeholders in e-commerce. Online customers expect to receive

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ordered goods at the earliest, and so, poor delivery experience creates a key reason for customer complaints, which means that e-commerce companies outsource distribution function, customers blame them for inconveniences and share an inferior image of the e-tailer in the social media avoiding such e-commerce companies for future purchases. To that extent, e-commerce giant Amazon addresses issue of complexity in triadic relationship by developing competency in last-mile delivery and so, the cost of transporting individualized shipments to distinct and unreliable destinations is a key issue in the last-mile inefficiency of economies. Furthermore, the arrival of the global economy and intensified competition have led many companies to be aware of the importance of managing their supply chains for fast product introduction and service innovations to the markets, and in order to improve competitiveness, many of them have embraced supply chain management (SCM) to enhance organizational effectiveness and achieve such organizational goals as improved customer value, better utilization of resources, and increased profitability.136 SCM is concerned with managing the upstream and downstream relationships with suppliers and customers to deliver superior customer value at the least cost to the chain as a whole and implementing SCM requires both “interfunctional” and “partnership” perspectives avoiding inward-looking and selffocused attitudes in the management approach.137 The management of a supply chain encompasses customer values and costs to customers that together emphasize the significance of getting goods/services to customers at the right time, in the right place, in the right quantities, under the right conditions, and at the lowest possible costs. Low cost is reflected in the costs of the product/service to the customers achieving a competitive advantage by striving for excellence in both service and cost leadership.138 In the context of SCM, the focus of performance measurement should be not only on process operations within the organizational boundaries of a company but also requires an understanding of the performance prospect of other member companies in the supply chain, backward from the suppliers and forward to the customers being the key to its effective implementation.139 It is important to measure performance for the effective management of a supply chain, and to that extent, Harrington140 refers that “If you cannot measure it, you cannot control it. If you cannot control it, you cannot manage it. If you cannot manage it, you cannot improve it.” Besides, companies involved in various parts of the supply chain are likely to

Lee, H.L., 2000. Creating value through supply chain integration. Supply Chain Management Review 4 (4), 30–36. Lee, H.L., Billington, C., 1992. Managing supply chain inventory: pitfalls and opportunities. Sloan Management Review 33 (3), 65–73. 137 Holmberg, S., 2000. A systems perspective on supply chain measurements. International Journal of Physical Distribution and Logistics Management 30 (10), 847–868. 138 Dreyer, D.E., 2000. Performance measurement: a practitioner’s perspective. Supply Chain Management Review 4 (4), 30–36. 139 Frohlich, M.T., Westbrook, R., 2001. Arcs of integration: an international study of supply chain strategies. Journal of Operations Management 19 (2), 185–200. 140 Harrington, H.J., 1991. Business process improvement: the breakthrough strategy for total quality, productivity, and competitiveness. McGraw-Hill, New York. 136

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work to improve performance in those areas within their interest, but they need a complete overview of their supply chain activities and full appreciation of the impact of their performance on other member companies in the supply chain. There is a need of integrating the internal functions within a company and effectively linking them with the external operations of member companies in the chain, and a correct performance measurement is contributing to successful SCM implementation. Moreover, Mentzer and Konrad141 argue that performance measurement is the effectiveness and efficiency in accomplishing a given task in relation to how well a goal is met meaning the extent to which goals are accomplished and they may include leadtime, stock-out probability, fill rate, inventory costs, and operating costs. The goal of a transport logistics service provider is to satisfy the customers (both upstream and downstream) in the chain with greater effectiveness and efficiency than the competitors. Moreover, SCP in transport logistics should encompass not only operations efficiency parameters but also measures of service effectiveness to meet the goals of all shipper, service provider, and consignee and not be centered only on individual functional areas, but rather on the various parties involved in the transport logistics processes and the overall SCP. Lai, Ngai, and Cheng142 present practitioners with a 26-item measurement instrument for evaluating SCP in transport logistics, suggesting that all 26 measurement items are critical attributes of SCP in transport logistics. Thus, e-logistics deliver solutions that are built on virtual integration and information and communication technology enabling the optimization of customer’s value. Furthermore, SCM assembles competencies and resources inherent to companies and their partners in supply channels for delivering an unmatched customer experience in delivery of products by coordinating the flow of products, services, and information generating better customer value. Hence, SCM incorporates the imperative business processes in delivering products and services along with relevant information. Consequently, an effective SCM makes certain a constant flow of information and materials across the supply chain. Logistics is an integral part of the SCM that supervises the storage of goods and services, its forward and reverse flow, and related information sharing from production stage to consumption stage. Thus, the inbound logistics, materials management, physical distribution, and information management are vital in logistics. The inward movement of raw materials from suppliers materializes the inbound logistics; the flow of materials within a production house comes under purview of materials management, and the delivery of goods to customers refers to the physical distribution. Moreover, distribution logistics process encompasses activities in delivering the finial products to the end customers. Hence, last-mile logistics is the last stretch in the delivery process including transit of goods from last transit point to the end-customer location.

141

Mentzer, J.T., Konrad, B.P., 1991. An efficiency/effectiveness approach to logistics performance analysis. Journal of Business Logistics 12 (1), 33–62. 142 Kee-hung Lai, E.W.T. Ngai, T.C.E. Cheng, Measures for evaluating supply chain performance in transport logistics, Transportation Research Part E 38 (2002) 439–456.

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The supply chain model suggests that the demand characteristics of numerous products decide supply chains’ strategic response, and consequently, innovative products have variations in supply and demand, whereas functional products have uniform demand patterns. So, cost advantage in logistics is possible for functional products having uniform demand patterns. Instead, novel and innovative products have unpredictable demand signifying the demand for a responsive supply chain strategy for logistic efficiency. It has to be taken into account that there is shortening of product life cycles, and customer trends are rapidly evolving with a limited capacity of manufacturers to respond to market alterations on an on-going basis, making integration in terms of harmonization with the customer a delicate exercise. Because of competitive cost and competitive demands, corporations are embracing internationalization strategies, making supply chains more complex, more extensive, and leaner to market risks, as production capability and logistics infrastructure are very vulnerable and so, risk refers to any threat such as cultural, energy, and terrorism having devastating consequences on supply chains which means that the tsunami of 11 March 2011, the nuclear crisis in Japan, the wars and terrorist acts in Libya, Syria, and Iraq along with the political crises with the exit of the United Kingdom from the European Union interrupt the global trade implicating the operations of the supply chain. Hence, any financial, physical, and information risk have not only disruptions in terms of share price and loss of long-term reputation but also a loss of capacity of nonresilient supply chain. Moreover, logistics performance counts on effectiveness and efficacy in carrying out logistics activities in a business context and so, effectiveness corresponds to the respect of the wants of the clientele, while the efficiency corresponds to the control of the resources. There is a need for the evaluation of the extent and impact of supply chain risks on logistics performance echoing a substantial part of overall performance with a noteworthy influence on marketing and financial performance.143 Are reverse logistics systems useful in emergency logistics management? The number and influence of both natural and human-related catastrophes have been increasing lately, and so among numerous types of disasters, epidemic disease outbreaks pose treats for human beings. It is worth mentioning here that the outbreak of an epidemic disease causes noteworthy regard to human beings leading to a global crisis and so, with the purpose of controlling the spread of an epidemic, the utilization of logistics via the effective management of rapidly increased medical waste through establishing a temporary reverse logistics system is of vital significance.144 From a general perspective, the epidemic logistics problem belongs to Tang, O., and S. N. Musa. 2011. “Identifying risk issues and research advancements in supply chain risk management.” International Journal of Production Economics 133: 25–34. Li Zhao Baofeng Huo Linyan Sun Xiande Zhao, (2013), “The impact of supply chain risk on supply chain integration and company performance: a global investigation”, Supply Chain Management: An International Journal, Vol. 18 Iss 2 pp. 115–131. 144 Boonmee, C.; Arimura, M.; Asada, T. Facility location optimization model for emergency humanitarian logistics. Int. J. Disaster Risk Reduct. 2017, 24, 485–498. Büyüktahtakın, I.E.; 143

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emergency or disaster logistics management concentrating on four consecutive decision-makings linked with risk mitigation, preparation, response activities, and postdisaster recovery. Moreover, epidemic outbreak leads to a sharp upsurge on the infections within a very short time, which drives a dramatically increased demand of various resources such as medical staff, medical supplies, and healthcare facilities, so as to offer a timely and sufficient medical service, control the disease spread, and diminish the economic influence which means that the establishment of an effective and responsive logistics network to cope with this temporarily and drastically augmented demand is of indispensable value. Since January 2020, the number of COVID-19 infections has increased significantly and a global emergency has been declared by the WHO on January 31st.145 There is a need for the establishment of a reverse logistics system for effective management of medical waste.146 One of the most significant logistics challenges is to set up temporary healthcare facilities so as to cope with the rapid increase of infections, which means that logistics must balance the trade-off among the risk at sources, the risk of transportation and treatment of medical waste, and the total cost. The model (SCOR)147 developed by the Supply Chain Council provides a useful framework viewing activities in the supply chain as a series of interlocking interorganizational processes with each individual organization comprising four components: plan, source, make, and deliver. Moreover, the SCOR model provides an indication as to how effective a company uses resources in creating customer value. Furthermore, SCOR not only identifies both the effectiveness and efficiency aspects of performance but also recognizes that there can be internal as well as customerrelated reasons for performance measurement. The physical distribution (PD) sector comprises the entire system of goods handling and goods movement. Is PD influenced by e-commerce? Would the electronic transfer of information through a logistics system lead to more competent transport operations by cutting out “unnecessary” transactions, by avoiding redundant traffic flows, and by eliminating underutilized infrastructure? An optimized logistics system would lead to more efficient transport operations,148 and electronic des-Bordes, E.; Kıbı¸s, E.Y. A new epidemics–logistics model: Insights into controlling the Ebola virus disease in West Africa. Eur. J. Oper. Res. 2018, 265, 1046–1063. Dasaklis, T.K.; Pappis, C. P.; Rachaniotis, N.P. Epidemics control and logistics operations: A review. Int. J. Prod. Econ. 2012, 139, 393–410. 145 World Health Organization. Situation Report-11 Novel Coronavirus (2019-ncov) 31 January 2020. https://www.who.int/docs/default-source/coronaviruse/situation-reports/20200131-sitrep-11ncov.pdf?sfvrsn¼de7c0f7_4. 146 Liu, M.; Cao, J.; Liang, J.; Chen, M. Epidemic-Logistics Modeling: A New Perspective on Operations Research; Springer: Singapore, 2020. 147 Stewart, G., 1995. Supply chain performance benchmarking study reveals keys to supply chain excellence. Logistics Information Management 8 (2), 38–44. 148 Meyer MD. Delivering the Future: E-Freight. Provided by the Foundation for Intermodal Research and Education, Greenbelt, MD 20770, USA (on the web: http://intermodal.org/FIRE/ meyerpaper.html).

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exchange would make the logistics market transparent allowing for optimal organization149 and allocation of transport services. The goods distribution system in industrialized countries has been undergoing profound changes over the last two decades, and the introduction of supply chain management and its integrated approach to corporate re-organization has vitally changed the entire system of goods processing. A PD comprises all functions of movement and handling of goods, above all transportation services (trucking, freight rail, air freight, inland water ways, marine shipping, and pipelines), logistics, and warehousing service such as consignment, storage, inventory management, packaging, wholesale, and mainly retail as well. PD gets the right assortment of raw materials and finished products to the right location in a proficient manner timely to marketing and manufacturing requirements. One of the primary changes associated with electronic commerce in terms of logistics is the process of disintermediation, leading to a reduced number of members in the distribution channel, compared with traditional supply chains. Features like electronic data interchange (EDI), the automatization of product flow in dedicated warehouses and distribution centers (DCs), or the recent computerbased tracking-and-tracing systems (which offer online insight into the status of your shipment via the web) are primary sources of enormous productivity gains over the last two decades. Global Positioning Systems (GPSs) allow for identification and both well-organized and flexible routing of vehicles in a way that was not known before. The material foundation for the contemporary “network economy” is based on both modern logistics and traditional asphalt and concrete. Cyberspace functions as a main platform for information exchanges, transforming them into market transactions. Business customers can speed up the entire ordering process, can receive delivery faster, and are able to follow the status of their order online. Companies experience greater market transparency (offers, prices) and are able to increase their purchasing power, in order to achieve overall cost reduction. Does online retail mean that a product is being delivered directly either from the manufacturer or distributed out of a dedicated DC to the final consumer? It is unclear how many agents are financially involved in the transactions, nor how many operate within the physical transfer.150 It should be taken into account that electronic commerce is certainly not only a matter of virtual information flows but also has a material goods movement dimension. Competition drives service level and time requirements, and in order to fulfil these needs, a certain transport and environmental expense is generated. Due to integrated data transfer and information management, flexible distribution and e-commerce would permit the processing and shipping only those materials that have been ordered. Air transport is critical for the sustainability of the entire transport system, and e-commerce as a major customer of airfreight is also expected to increase (even indirectly) the pressure on airports for further growth and further

149

Song J, Regan A. Transition or transformation? Emerging freight transportation intermediaries. Transportation Research Record 2001;1763:1–5. 150 Reynolds J. E-commerce - a critical review. International Journal of Retail and Distribution Management 2000; 28(10):417–44.

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expansion. E-commerce by airfreight will be associated with future air traffic growth and related problems. Moreover, e-commerce is the increasing need for transshipment points, such as warehouses and DCs operated in order to control the more complex, mass-customized freight flows without increased logistics costs. Furthermore, the new technology enables continual movements of products in the supply chain, which means that traditional storage space must start housing activities that involve more horizontal movement rather than vertical stacking. New economy by modernizing production and distribution facilities more and more will cluster around major airfreight hubs and logistics drive distribution facilities to strategic locations, often closer to customers151 and so, the new DCs, designed for rapid material flow, are more and more being established at strategic, time- and space-sensitive locations. New warehouses, DCs, and logistics facilities are moving at the edge of the agglomeration, and the demand for developed land for distribution purposes is likely to increase. Taking into account that not all goods can be electronic, the economic success and logistics efficiency of e-commerce are challenged by the costly frictions of physical space. According to Markus Hesse,152 “Possible contributions of e-commerce to a more efficient and sustainable distribution system very much depend on particular regional circumstances, such as consumer habits, certain delivery modes and the important question of population density.” As mentioned earlier, logistics is referred to as a nonhomogenous part of the supply chain that involves several participants at different levels.153 A logistics platform is a homogenous and controlled part of a logistics system by one actor in the supply chain affected by marketing channel strategy and should as such support the strategy across and within business units. MNEs outsource the operation of logistics to transport and logistics providers taking over a large variety of services such as transportation, warehousing, warehousing services, pick and pack, packing, statistics, and many other value-added services. Recently, companies prefer to use a third-party logistic provider in order to manage different parts of their strategic plan of development or even a part of their logistic schedule. A third-party logistics provider (TPL) is defined as the services offered by a middleman in the logistics channel that has specialized in providing, by contract, for a given period, all or a substantial number of the logistics activities for other companies. A logistics partnership is defined as a long-term formal or informal relationship between shippers and logistics providers to render all or an extensive amount of logistics activities for the shipper. It should be taken into account that the way the logistics firms manage to organize and choose their customers as well as combine their different logistics solutions is vital not only for their own but often also their customers and sometimes 151

Kirschbraun T, Bomba T. The New Economy. Effects on corporate real estate strategies. In: Jones Lang LaSalle: Property Futures. Occupier Strategies in the New Economy: Chicago, London 16, 2000. 152 Markus Hesse, Shipping news: the implications of electronic commerce for logistics and freight transport, Resources, Conservation and Recycling 36 (2002) 211–240, at 234. 153 Lambert, D., Cooper, M., 2000. Issues in supply chain management. Industrial Marketing Management 29, 65–83.

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even for their customers’ customer survival. There is economic, physical, technological, and legal knowledge exchange between firms, but also a social exchange where trust and communication are vital for the use of TPL. Awareness, formation, closer cooperation, extension, and maintenance and then finally looser cooperation and dissolution are stages of a professional relation between a customer and a TPL which means that changes of increasing integration and commitment seem to take place in logistics alliances154 between the TPL and its customers.155 The logistics strategy and marketing of the customers will be of importance for what type of demands the customer set on TPL.156 An important aspect of logistics in general, and therefore of the logistics platform, is the need for flexibility157 in order to support the marketing strategy in the longand short-term perspective. Hence, logistics need to be flexible in the short term to offer operational opportunities and flexible in the long term to apply to new marketing channel positions. Examples of logistics flexibility types needed in the short and long term are volume flexibility, time-based flexibility, and flexibility in products and services. There is an interaction between marketing and logistics, horizontally and vertically in the supply chain. The possibility of adapting to changes in the environment concerns the possibility of choosing different lines of action in terms of disintermediation, multiple marketing channels, composite supply chain channels and/or multiple logistics channels, ordering channels, or distribution flows.158 The distinctive feature of an electronic marketplace is that it brings multiple buyers and sellers together (in a “virtual” sense) in one central market space enabling them to buy and sell from each other at a dynamic price, which is determined in accordance with the rules of the exchange. Co-operative supply chains aim to reduce the number of suppliers and form long-term strategic alliances that lock in suppliers and lockout competition, while EMs promote competition and permit buyers to search for appropriate suppliers and support “transaction-based” partnering. Supply chain management needs to manage the organizational complexity of adopting a dynamic mix and emphasis between content, context, and infrastructure. Internet Kyle, P., H. Singh & H. Perlmutter (2000) “Learning and protection of proprietary assets in strategic alliances: building relational capital.” Strategic Management Journal, 21: 217–237. 155 Bagchi, P.K. & H. Virum (1998) “Logistical alliances: trends and prospects in integrated Europe.” Journal of Business Logistics, Vol 19 No 1 (pp 191–213). 156 Hertz, S., (1996). “The Dynamics of International Strategic Alliances – A Study of Freight Transport Companies.” In: International Studies of Management and Organisation, Vol. 26, No 2, pp. 104–130; Lieb, R.C. & H.L. Randall, 1996. “A comparison of the Use of Third Party Logistics Services by Large American Manufacturers, 1991, 1994 and 1995.” In: Business Logistics Vol 17, No 1. 157 Upton, D.M., 1994. The Management of Manufacturing Flexibility. California Management Review, Winter, pp. 72–89. Flexibility is here defined as “the ability to change or react with little penalty in time, effort, cost or performance.” 158 Niklas Aldin, Fredrik Stahre, Electronic commerce, marketing channels and logistics platforms ––a wholesaler perspective, European Journal of Operational Research 144 (2003) 270–279 www.elsevier.com/locate/dsw. 154

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commerce does not eliminate the need of physical logistics systems; in fact, it even increases their importance. The flow of information between the supply chain partners can be efficiently managed over cyberspace, reducing the costs and increasing the speed and the quality of data transfer. On the other hand, the EM should organize a complementary physical logistics system in order to distribute material products to its clients. Hence, the EM159 must decide to create its own physical assets in order to provide a consistent quality of product delivery. Finally, different electronic marketplaces require supply chain management.160

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Globalization conveys entirely new forms of global competition that are expected to mold markets, societies, regions, and their surroundings in an underlying manner. Global integration contributes to deep changes generating a multiplicity of responses. Evaluations of globalization fluctuate drastically from exceptionally positive (“hyper globalist”/liberalism) to negative (“skepticism”/state interventionism) views. There is an emerging understanding that globalization is best comprehended as an underlying transformation consisting of a mixture of processes and effects.161 Globalization is not space-less and so being related with a dissolution of material space into the virtual world of information transfer and that there is not an underlying connection between a by some means structural demand for facilities and local places that have to accomplish such imperative.162 Furthermore, globalization with both its universal importance on one hand and its broad multiplicity of probable consequences on the other hand is unquestionably one of the most demanding matters for geography and urban or regional policy in particular. There is a height of mobility of raw materials, parts, and finished goods in a scenery which is somewhat regulated with hurdles such as tariffs, quotas, and restrictions to foreign ownership. The mobility of features of production, explicitly capital, turned out to be feasible, predominantly from the 1980s. The legal and physical setting in which international trade was conducted turned into less burdensome, leading to a better realization of the relative advantages of particular locations.

159

Martin Grieger, Electronic marketplaces: A literature review and a call for supply chain management research, European Journal of Operational Research 144 (2003) 280–294 www. elsevier.com/locate/dsw. 160 Christopher, M. (1998) Logistics and Supply Chain Management – Strategies for Reducing Cost and Improving Services. London, UK. Financial Times/Pitman Pbl. 161 Held, D., McGrew, A., Goldblatt, D. and J. Perraton. 1999. Global Transformations. Politics, Economics and Culture. Stanford: Stanford University Press. 162 Coe, N., Hess, M., Yeung, H., Dicken, P. and J. Henderson. 2004. Globalizing regional development: a global production networks perspective. Transactions of the Institute of British Geographers 29 (4): 468–484.

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To that extent, multifaceted networks concerning flows of information, commodities, parts, and finished commodities have been laid down, which consecutively demands a high point of command of logistics and freight distribution. In such surroundings, dominant players have appeared which are not directly concerned the purpose of production and retailing, but largely taking the accountability of managing the web of flows. The global economic system is differentiated by an upward point of integrated services, finance, retail, manufacturing, and nevertheless distribution. A good example of these influential players is given by Wal-Mart, the largest company in the globe, which has turned into the “template” for late-modern capitalism.163 Especially, the appearance of global production networks and their enduring spatial over and above organizational demarcation have led to the escalating significance of the transportation and logistics industries, even if the component of physical distribution still keeps on highly underdeveloped. Moreover, globalization has an essential relation with transportation and logistics, even if the importance of distribution has been ignored. Nevertheless, the major conceptualizations of globalization either overlook entirely any reference to transportation or make only implied linkages.164 Risk management is significantly vital for the endurance of firms in service in all areas of today’s competitive marketplace. All prospective risks should be administered properly and investments should be suitably assigned with the purpose of reaching long-term sustainable expansion and beneficial. Successful risk management strategies are being built-up all around the globe for compound risks caused by new technologies in the global markets, price uncertainties, compliance issues, privatization, mergers, political fluctuations, and globalization. As a result, the role of transportation is regarded as more than a simple assistance to the mobility of freight within global commodity chains, but a fundamental ingredient of the value generation procedure. Although economic geography has paid much attention to the producers of goods and services and the international flows of capital, ideas, and people encroaching on production networks, the companies and locations convoluted in really moving the materials and products are less broadly investigated.165 International transportation risk is portrayed primarily in two categories which are internal and external risks. External risks occur from external factors that firm cannot effortlessly get around it. Being in global trade is more complex than the national trade, and firms confronting with this type of risks commonly in global trade. In addition, external risks are varying according to geographical position, forecasting complexity, exchange rates, the probability of terrorism, and government regulations. Internal risks are resulting from internal corporations’ function processes,

Lichtenstein, N. ed. 2006. Wal-Mart. The Face of Twenty-First-Century Capitalism. New York, London: The New Press. 164 Janelle, D.G. and M. Beuthe (1997) “Globalization and research issues in transportation,” Journal of Transport Geography 5, (3): 199–206. 165 Hesse, M. and J.-P. Rodrigue. 2004. The Transport Geography of Freight Distribution and Logistics. Journal of Transport Geography 12 (3): 171–184. 163

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which are setting up, production, inventory, and transportation. The significance of risk management is growing gradually and becoming a central business practice in government and corporations. Transport geography has paid attention either on local/regional transport and logistics nodes or on specific distribution systems. The simple spatial and functional complexity of GPNs emphasizes the requirement to find a joint standpoint. There is a need to highlight the significance of transport and logistics as a central part of the configuration of global production networks and value-added activities. If globalization is connected with a reconfiguration of space–time patterns, then transport and predominantly logistics as key measures of co-ordination between both need to be taken into account. Moreover, there are noteworthy institutional changes within the logistics industry as an outcome of economic globalization such as the issue of containerization and global port operators highlight.166 From an activity which has a high level of spatial fixity such as terminals, technological changes have exposed a noteworthy capability for transportation to provide elasticity in the level and array of its services such as, for instance, in the port of Piraeus. Logistics in the twenty-first century, developed very rapidly, particularly confirms the economy, which has turned into an imperative factor in the development of a state, and a noteworthy influence on the retail sector. There is an effect of logistics on national productivity, on the development of the retail sector and the influence of the world’s leading retailers such as Wal-Mart for developing countries.167 The significance of logistics for the national economy is manifested in the share of logistics services in the gross domestic product (GDP) of a state varying and is higher in developed countries associated to countries in transition and developing countries. Electronic global network makes possible tracing and monitoring products and data concerning the entire supply chain. It is worth mentioning that the adoption of Just-in-Time (JIT) logistics has allowed manufacturers to increase elasticity in their ordering decisions, lessening the stocks of inventory held on-site, and abolish inventory carrying costs. The elasticity of JIT permits manufacturers to meet all fluctuations in the request for their goods, which lets them to sell more than if hampered by stocks of inventory. The savings produced by plummeting inventory carrying costs permit manufacturers to control lower prices for their goods, which lead customers to boost demand. When using an international supplier, the logistics technology entails a transportation mode employed in a company’s global supply chain. Without JIT, a company orders parts and has them delivered by ocean shipping. JIT necessitates a speedy delivery of parts. To that extent, a company using JIT makes use of airplane

Olivier, D. and B. Slack 2006. Rethinking the Port, Environment and Planning A 38 (8): 1409–1427. Slack, B. and A. Frémont. 2005. Transformation of Port Terminal Operations: From the Local to the Global. Transport Reviews 25 (1): 117–130. 167 Mangan, J., Lalwani, C., Butcher, T. (2008): Global Logistics and Supply Chain Management, United Kingdom: John Wiley & Sons, Ltd., р. 7. 166

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transportation to deliver its foreign intermediates. Air shipping costs more than ocean shipping, and the size of a company’s ad valorem air freight wedge ascertains whether a company adopts JIT logistics.168 Internationalization, globalization, and computerization have led to radical alterations in retailing resulted in the increase of rate of retail course, generating new distribution means and revenue growth in the retail trade, as well as globally. Globalization and the changing dynamics of the industry have required retail businesses to assess their business strategy and to employ new technological solutions in order to advance customer service. Adaptation of blockchain technology in logistics industry offers for not only increased transparency, trust, and effectiveness but also enhanced safety by diminishing misdeclaration of cargo. When parties make a transaction via the blockchain, they only need to place trust in the underlying infrastructure of the blockchain rather than in each other due to the fact that a decentralized computer network can record and authenticate each transaction on top of making the transaction transparent, trust is produced by default. It is worth noting that a blockchain is applied in virtually any industry in which assets are managed and transactions take place and so, providing a secure chain of custody for both digital and physical assets through its working features.169 Furthermore, blockchain applications are limitless and the technology will be used in many industries, embracing but not limited to finance, digital identity, government, international trade and commodities, and law. Hence, global supply chains can exploit this technology, and companies, such as Maersk, DHL, Amazon, and Walmart, are improving their existing systems employing blockchain technology. Moreover, blockchain technology is utilized in global trade logistics, including procurement, transportation management, and trade finance.170 Blockchain technology will be integrated into the transport and logistics industry being one of their key strategic priorities.171

168 John T. Dalton. A Theory of Just-in-Time and the Growth in Manufacturing Trade 2013. www. ssrn.com John T. Dalton specifies that “The model’s predicted trade dynamics depend on how the set of firms using JIT with international suppliers changes over time.” 169 Karim Sultan, K., Ruhi, U., & Lakhani, R. (2018). Conceptualizing Blockchains: Characteristics & Applications. 11th IADIS International Conference Information Systems. 170 Gockel, B., Acar, T., & Forster, M. (2018). Blockchain in Logistics: Perspectives on the upcoming impact of blockchain technology and use cases for the logistics industry. DHL Customer Solutions & Innovation: Troisdorf, Germany. 171 Kewalram, B. (2019). Blockchain could revolutionize logistics, but is the industry prepared to let it? Retrieved from https://www.forbes.com/sites/forbestechcouncil/2019/12/04/blockchain-couldrevolutionize-logistics-but-isthe-industry-prepared-to-let-it/#2b508db811e2; Kewalram, B. (2019). Blockchain: is the shipping industry ready? Retrieved from https://www.agility.com/insights/ future-oflogistics/blockchain-is-the-shipping-industry-ready/.

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References 1. Castells, M. (1996). The rise of the network society. In The information age: Economy, society, and culture (Vol. 1). Oxford: Blackwell. 2. Brummer, C. (2019). Fintech law in a nutshell. Minnesota: West Academic Publishing. 3. Christopher, M. (1998). Logistics and supply chain management – strategies for reducing cost and improving services. London: Financial Times/Pitman Pbl. 4. He, D., et al. (2017). Fintech and financial services: Initial considerations. International Monetary Fund. 5. Jules, D. (1952). On the measurement of the utility of public work. Reprinted in International Economic Papers No2 (R. Barback, Trans. from French). London: Macmillan. 6. European Commission. (1998). An introduction to electronic commerce. Retrieved from http:// europa.eu.int/ISPO/ecommerce 7. Frobel, F., Heinrichs, J., & Kreye, O. (1979). The new international division of labour. Cambridge: Cambridge University Press. 8. Fujita, M., Krugman, P., & Venables, A. J. (1999). The spatial economy. Cambridge: MIT Press. 9. Zekos, G. (2015, April). Cyber versus conventional personal jurisdiction. Journal of Internet Law, 18(10), 3–35. 10. Zekos, G. (1999). Internet or electronic technology: A threat to state sovereignty. JILT (3). Retrieved from https://warwick.ac.uk/fac/soc/law/elj/jilt/1999_3/zekos 11. Gamberdella, A., & Torrisi, S. (1996). Does technological convergence imply a convergence in product markets? Mimeo. IEFE, Bocconi University, Milan. 12. Zekos, G. I. Globalisation and states’ cyber-territory. Retrieved from http://www.bailii.org/uk/ other/journals/WebJCLI/2011/issue5/zekos5.html 13. Zekos, G. I. The use of electronic technology in maritime transport: The economic necessity and the legal framework in European Union Law. Retrieved from http://www.bailii.org/uk/other/ journals/WebJCLI/1998/issue3/zekos3.html 14. Zekos, G. I. MNEs, globalisation and digital economy: Legal and economic aspects. Retrieved from https://www.emerald.com/insight/content/doi/10.1108/03090550310770875/full/html 15. Gilson, B. (1984). The conceptual system of sovereign equality. Leuven: Peeters. 16. Gockel, B., Acar, T., & Forster, M. (2018). Blockchain in logistics: Perspectives on the upcoming impact of blockchain technology and use cases for the logistics industry. DHL Customer Solutions & Innovation: Troisdorf, Germany. 17. Hayes, H. M., Jenster, P. V., & Aaby, N. E. (1996). Business marketing: A global perspective. Chicago: Irwin. 18. Held, D., McGrew, A., Goldblatt, D., & Perraton, J. (1999). Global transformations, politics, economics and culture. Stanford: Stanford University Press. 19. Crawford, J. (1979). The creation of states in international law 26-27. 20. Damgaard, J., Elkjaer, T., & Espinosa-Vega, M. The global FDI network: Searching for ultimate investors. IMF Working Paper WP/17/258. 21. Karim Sultan, K., Ruhi, U., & Lakhani, R. (2018). Conceptualizing blockchains: Characteristics & applications. 11th IADIS International Conference Information Systems. 22. Lane, P., & Milesi-Ferretti, G-M. (2017). International financial integration in the aftermath of the global financial crisis. IMF Working Paper WP/17/115. 23. Lanz, R., & Miroudot, S. (2011). Intra-firm trade: Patterns, determinants and policy implications. OECD Trade Policy Working Paper No. 114. 24. Lichtenstein, N. (Ed.). (2006). Wal-Mart. The face of twenty-first-century capitalism. New York: The New Press. 25. Liu, M., Cao, J., Liang, J., & Chen, M. (2020). Epidemic-logistics modeling: A new perspective on operations research. Singapore: Springer. 26. Mangan, J., Lalwani, C., & Butcher, T. (2008). Global logistics and supply chain management (р. 7). United Kingdom: Wiley.

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27. OECD. (2018). OECD due diligence guidance for responsible business conduct. 28. Michaels, R. (2004). Territorial jurisdiction after territoriality. In P. J. Slot & M. Bulterman (Eds.), Globalisation and jurisdiction. The Hague: Kluwer Law International.

Chapter 3

Management and Corporate Governance

3.1

Digital Governance and Digital Platforms

It has to be taken into consideration that in the perspective of a movement toward a more digitalized, platformized, and decentralized economy, a new role is assigned with such technology to the numerous kinds of corporate stakeholders by the creation of stakeholders’ committees in corporations.1 Dondero2 argues that the existing company law “organizes the relationships between partners/shareholders, between them and the directors and the other corporate bodies, and to some extent, it apprehends the situation of employees and of the CSR.” Will the investor involvement and free-rider problems be considerably different than in a firm governed by existing corporate governance rules based on the agentprincipal and cost agency problematic? It is worth mentioning here that distributed governance is founded on “flat-hierarchy” philosophy and on the view that token holders will devote enough time to participate and vote in line with the interests of the corporation.3 The question to be answered is what powers will be assigned to these new kinds of company stakeholders such as smart contract developers, DLT users, smart contract validators, miners, or curators. Moreover, the role of these various stakeholders needs to be identified and defined by DLT projects and so liability issues concerning the use of DLT and smart contracts for managing corporations are

1 N. Notat and J.-D. Senard, “L’entreprise, objet d’intérêt collectif – Rapport aux Ministres de la Transition écologique et solidaire, de la Justice, de l’Economie et des Finances, et du Travail”, 9 March 2018. 2 B. Dondero, “La raison d’être des entreprises (rapport Notat-Senard)”, 10 March 2018: https:// brunodondero.com/2018/03/10/la-raison-detre-des-entreprises-rapport-notat-senard/. 3 M. Fenwick and E. Vermeulen, “Technology and Corporate Governance: Blockchain, Crypto and Artificial Intelligence”, ECGI Working Paper No. 424/2018, November 2018.

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significant.4 To that extent, national laws and regulations will not be adequate to solve these issues which are by definition transnational and so International laws must be drafted on the matter such as general principles about the contractual nature of transactions on decentralized platforms, regarding the particular instrument schemes for DLT users.5 Taking into account the digital nature of the developments, there is a need to generate digital jurisdictions whose authority would be subject to an international treaty concluded between sovereign nations and whose governance has to be established by specific matters such as the place of the server, the impact of the transaction and the damage caused by the electronic actions. It is worth noting that if the project funders hold a noteworthy share of the tokens issued, they will affect the token holders’ vote to get the release of more funds. In addition, investors can also take on a strategy of “free-riding” and so putting all their trust in a digital distribution game platform based on a crypto-reward ecosystem by not participating in votes and resolutions, reducing the majority threshold, and weakening the security of the mechanism.6 It is obvious that the development of the distributed ledger technology, its usage, and their regulation is not enough to conclude decisively on all the implications for corporations that the DLT adoption by market participants will involve which means that there is a likelihood that new kinds of corporation stakeholders will appear such as the token holders. Hence, these new players will lead to alterations in the securities’ issuance and trading, in the shareholder’s involvement, but also to a reinforcement of the rights awarded to the different corporation stakeholders and so a new role will be recognized to corporate stakeholders.7 Moreover, from a governance perspective, the course toward decentralization does not only influence the existing corporate governance rules, and the relationship of contractual affiliations within a corporation, but also possibly on the definition of a corporation. Thus, the role of the board of directors is unsettled evolving to a supervision role of automated decisions made by computer technology, and even to

M. Field, “Decentralized Governance Matters”, Medium, 5 February 2018. D. Zetzsche, R. Buckley and D. Arner, “The Distributed Liability of Distributed Ledgers: Legal Risks of Blockchain”, EBI Working Paper Series 2017-007, No. 14, 15 August 2017; P. Paech, “The Governance of Blockchain Financial Networks”, LSE Legal Studies Working Paper No. 16/2017, 16 December 2016. 5 D. Guégan and C. Hénot, “A Probative Value for Authentication Use Case Blockchain”, Documents de travail du Centre d’Economie de la Sorbonne, 2018. F. G’Sell, “The challenge of algorithmic governance”, Interdisciplinary workshop on blockchains, Ecole Normale Supérieure, 2 July 2018. 6 C. Perreau, “L’interactive initial offering, l’alternativetransparente à l’ICO”, LeJournalDuNet.com, 26 October 2018; W. George, “Kleros’ IICO Analysis”, 26 July 2018; J. Teutsch, V. Buterin and C. Brown, “Interactive coin offerings”, 11 December 2017. J. Halfon, “The DAICO: ICO savior or wolf in sheep’s clothing?”, Forbes, 24 May 2018. C. Pauw, “What is a DAICO, Explained”, CoinTelegraph, 13 February 2018. 7 D. Yermack, “Corporate Governance and Blockchains”, Oxford Review of Finance, Volume 21, March 2017. A. Glidden, “Should Smart Contracts Be Legally Enforceable?”, Blockchain at Berkeley, 27 February 2018. 4

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its disappearance as there are no managers nor a board of directors in a DAO which means that the likelihood that a firm will be governed by algorithmic code instead of human involvement, the so-called algorithmic governance, is forthcoming. Furthermore, the growth of corporate governance is improved by algorithmic code due to the fact that it is supposed that algorithms are more trustworthy than human intervention unless human can program the algorithm in a non-unbiased way. In line, it is possible presently to establish governance rules at least somewhat in computer code, and to delegate the management of a firm to algorithms executing smart contracts and certain predetermined actions. DLTs are already modifying the business setting and the way corporations are directed and controlled and so the blockchain and smart contracts redraw the boundaries between corporations and markets, by depriving a number of intermediary institutions of their role.8 For example, Northern Trust has created a blockchain solution with technology giant IBM for all corporate meetings embracing two smart contracts that record meeting attendance by collecting biometric information from the numerous gadgets an attendee carries and collects all pertinent information about the meeting, such as the action points and associated dates. Moreover, the blockchain solution converts all such information into meeting minutes, following a standardized format and a third smart contract forwards the minutes of the meeting and associated documents in a predetermined repository permitting meeting attendance and individual contributions to be promptly stored in a predetermined and well-searchable format.9 Furthermore, Northern Trust has created a blockchainbased digital identity management system that delivers the information to be stored in Northern Trust’s meeting software tackling corporate governance matters such as executive compensation. It could be argued that smart contracts could be exploited to make compensation arrangements harder to amend in opportunistic manners further down the road, a phenomenon known as “backdating.”10 It has to be taken into account that the digital age has become too complicated to the extent that security is a priority for data systems in many firms and so the introduction of Biometric identification has been a revolution in improving the safety of data systems. Biometric technology uses body traits such as facial recognition, iris scan, fingerprint scan, among other morphological characteristics that the 8

Assaf Hamdani, Niron Hashai, Eugene Kandel & Yishay Yafeh, Technological Progress and the Future of the Corporation, 6 J. BRITISH ACAD. 215, 225 (2018) (arguing that, because DLTs reduce fraud and enhance trust, they have the potential to displace “powerful intermediaries”). 9 Jordan Danielle, Broadridge Patents Blockchain Solution For Proxy Voting And Repurchase Agreements (May 10, 2018), https://www.ethnews.com/broadridge-patentsblockchain-solutionfor-proxy-voting-and-repurchase-agreements. Christine Kim, Northern Trust Wins Patent for Storing Meeting Minutes on a Blockchain (Jun. 6, 2018), https://www.coindesk.com/northern-trustwins-patent-storingmeeting-minutes-blockchain. 10 See David Yermack, Corporate Governance and Blockchains, 21 Rev. Fin. 1, 9 (2017). Jesse M. Fried, Option Backdating and Its Implications, 65 Wash. & Lee L. Rev. 853, 858-864 (2008) (describing three forms of secret option backdating, including the backdating of executives’ option grants; the backdating of nonexecutive employees’ option grants; and the backdating of executives’ option exercises).

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AI system can easily recognize which means that AI can transform these visible traits into specific codes performing all activities. Biometric ID validation happens in many ways like fingertip recognition, iris recognition, face and voice recognition, and DNA matching and so AI supports Biometric systems to perform these validations used in a wide variety of devices such as smartphones and computers. In addition, Biometric identification is of considerable significance offering top security to data systems and digital devices.11 It is worth noting that higher levels of CEO payment take place when executive compensation consultants “cross-sell” services, but also board payment is higher when consultants work for the board rather than for executives.12 To that extent, it could be argued that instead of relying on compensation consultants and their own biases, boards could utilize smart contracts to control compensation structures and bonuses.

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Which is the influence of technology, especially distributed ledgers/blockchains, smart contracts, Big Data analytics, and AI/machine learning on the future of corporate boards? Will technology resolve corporate governance difficulties by substituting the board of directors? Which is technology’s influence on corporate governance? L. Enriques and D. Zetzsche13 argue that “barring unpredictable technological breakthroughs that eventually displace human judgment in corporate decision-making processes entirely, CorpTech will not make existing corporate governance mechanisms, and boards’ core functions in particular, obsolete.” Hence, it could be argued that since humans yield influence over a company, then conventional corporate governance means will assign decision-making powers. It could be said that the use of DLT is “retrofitting” and bolstering the digitalization of businesses’ management augmenting the solving of problems by implicating shareholders and a more active control of the management’s activity, particularly in the publicly traded companies. Moreover, DLT presents smart solutions for 11

https://shuftipro.com/blogs/ai-making-biometricssmarter#:~:text¼What%20is%20AI%20Bio metrics%3F,to%20understand%20by%20the%20system. 12 Jenny Chu, Jonathan Faasse & P. Raghavendra Rau, Do Compensation Consultants Enable Higher CEO Pay? A Disclosure Rule Change As a Separating Device, 64 MGMT. SC. 2845 (2017) (arguing in favor of a more nuanced view on consultants after concluding that “not all multiservice consultants are conflicted while not all specialist consultants are guardians of shareholder value”). Christopher S. Armstrong, Christopher D. Ittner & David F. Larcker, Corporate Governance, Compensation Consultants, and CEO Pay Levels, 17 REV. ACC’T STUD. 322–351 (2012) Kevin J. Murphy & Tatiana Sandino, Executive Pay and “Independent” Compensation Consultants, 49 J. ACC’T & ECON. 247–262 (2010). 13 Luca Enriques Dirk Zetzsche, Corporate Technologies and the Tech Nirvana Fallacy, ECGI Working Paper Series in Law Working Paper N○ 457/2019 July 2019 https://ssrn.com/ abstract¼3392321.

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incompetence in the corporate field by restructuring management matters such as rigid Annual General Meeting of Shareholders14 by dropping shareholder voting costs and the AGM organization costs for companies. Additionally, DLT augments the speed of decision-making, enable a fast and effective involvement of shareholders, and adjust the role of proxy firms.15 In line, DLT augments transparency and accuracy of the identity verification of the shareholders and minimizes “disguised derivatives hedging, backdating, and similar undesirable actions”16 being the means to strengthen shareholder participation via virtual shareholder meetings. Moreover, majority of rules, access rights, shareholder identification, and legal requirements are stored and encrypted in smart contracts and can be executed mechanically during the voting process which means that DLT shareholders’ votes in real time influence basic corporate governance issues such as distribution of profits and liquidation surplus, information requests, etc.17 How could corporate governance be disrupted by DLT? It is worth to be considered that a “virtual-only” shareholders’ general meeting is held without the requirement of settling a physical location and organized only by digital technology, while a “hybrid” shareholders’ meeting will offer to shareholders both physical and remote electronic entrees to the meeting. Companies’ articles of associations are amended to allow virtual-only or hybrid shareholders’ general meetings implementing flexibility and lower cost for their organization, in tandem with the internationalization and institutionalization of their shareholders’ identity.18 A great number of firms are altering their articles of associations to allow such meetings, and one-third proposed to permit hybrid meetings. Moreover, virtual-only or mixed physical–digital meetings denote a massive alteration permitting shareholders to diminish transportation costs for shareholders’ attendance to the meetings enabling the exchanges and Q&As with shareholders via electronic means. Nonetheless, some market associations have spotted drawbacks linked to virtual-only

A. Lafarre and C. Van Der Elst, “Blockchain Technology for Corporate Governance and Shareholder Activism”, ECGI.com, Law Working Paper N○ 390/2018, March 2018; A. Lafarre and C. Van der Elst, “Blockchain and the 21st century annual general meeting”, European Company Law Journal 14, no. 4, 2017. 15 J. Laster, “The Blockchain Plunger: Using Technology to Clean Up Proxy Plumbing and Take Back the Vote”, Keynote Speech, Council of Institutional Investors, Chicago, 29 September 2016. 16 D. Yermack, “Corporate Governance and Blockchains”, Oxford Review of Finance, Volume 21, March 2017; M. Kahan and E. Rock, “The hanging chads of corporate voting”, Georgetown Law Journal 96, 2008, pp. 1227–1281. V. Akgiray, “Blockchain Technology and Corporate Governance”, Report for the OECD Corporate Governance Committee’s roundtable discussion on blockchain technologies and possible implications for effective use and implementation of the G20/OECD Principles of Corporate Governance, 6 June 2018, p. 24. 17 M. Fenwick and E. Vermeulen, “Technology and Corporate Governance: Blockchain, Crypto and Artificial Intelligence”, ECGI Working Paper No. 424/2018, November 2018, p. 13. P. Boucher, “What if blockchain technology revolutionized voting?”, European Parliamentary Research Service, September 2016. 18 D. Currie and N. Delaney, “Virtual shareholder meetings – stepping into Jimmy Choo’s shoes or a matter of bad practice?”, Reed Smith, 31 May 2018. 14

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meetings such as the difficulty to deliver adequate technical certainty for the virtual access to the meeting not mentioning the reputational risk regarding the fact that the management wants to circumvent public physical meetings with shareholders. In the first stage, corporations will develop hybrid meetings leading toward the use of digital technology for the organization of AGMs in order to provide “efficient and fair shareholders’ meetings,”19 rationalizing the proxy voting process.20 Which is impact of the tokenization on various kinds of corporate entities? Over and above the continuation of the digitalization of corporate governance, another influence appears owing to the rights granted to new corporation stakeholders named crypto-asset holders that crypto-assets are not a monolithic kind of assets and each crypto-asset is founded on its particular features and functions. Moreover, tokens allocate rights to their holders particular to each issuance and so the regulatory characterization of crypto-assets is a clear point of attention for market contestants which means that with the advancement of token creations by listed firms, financial institutions and public entities, demands by key participants and regulators to classify crypto-assets along “mainstream” token asset classes will have to be judged, via the formation of groups of tokens signifying similar asset types susceptible to a certain degree of categorization.21 To that extent, legal classification of crypto-assets, and the possible contradictions between national/regional regulations, will be a real test for companies having consequences on the governance of companies.22 First of all, there is difficulty to classify several kinds of tokens as asset classes and regulators from several countries have published reports and public positions saying that the tokens which would be characterized as “securities” or “financial instruments” under their existing rules would have to abide by the relevant local security laws.23 Secondly, there is a A. Lafarre and C. Van Der Elst, “Blockchain Technology for Corporate Governance and Shareholder Activism”, ECGI.com, Law Working Paper N○ 390/2018, March 2018; A. Lafarre and C. Van der Elst, “Blockchain and the 21st century annual general meeting”, European Company Law Journal 14, no. 4, 2017. 20 A. Irrera, “Nasdaq successfully completes blockchain test in Estonia”, Reuters, 23 January 2017. 21 Morgan Stanley, “Update: Bitcoin, Cryptocurrencies and Blockchain”, research report, 31 October 2018; D. Bianchi, “Cryptocurrencies as an asset class? An empirical assessment”, WBS Finance Group Research Paper, June 2018; L.W. Kong, E.C. Laurenson, A.C. Scheibe, D.L. Taub, L. Tessler, V. Van Tassel Richards, “Five Regulatory Implications for Blockchain Tokens as an “Asset Class”, McDermott Will & Emery, 10 January 2018. 22 I. Barsan, “Legal Challenges of Initial Coin Offerings (ICO)”, Revue Trimestrielle de Droit Financier (RTDF), n○ 3, 2017, pp. 54–65. 23 French financial regulator AMF, “Summary of replies to the public consultation on Initial Coin Offerings (ICOs) and update on the UNICORN Programme”, 22 February 2018. Financial Conduct Authority, English HM Treasury and Bank of England, “Cryptoassets Taskforce: final report”, October 2018. Directorate General for Economic Development, Research and Innovation (DG DERI) of the State of Geneva, “Guide: Initial Coin Offerings (ICOs) in the Canton of Geneva”, 28 May 2018; FINMA, “Guidelines for enquiries regarding the regulatory framework for initial coin offerings (ICOs)”, 16 February 2018. Australian Securities & Investments Commission (ASIC), “Initial coin offerings”, Info 225, September 2017. Canada Securities Administrators, “Cryptocurrency Offerings”, CSA Staff Notice 46-307, 24 August 2017; Ontario Securities 19

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growing consensus among regulators, market participants, and law firms from OECD countries to simulate that security tokens are equivalent to securities being easier to define from a regulatory perspective security tokens than utility tokens and so its relevant applicable legal and operational agenda would be easily evaluated.24 Thirdly, key market participants are awaiting clarification from legislators and regulators, even the United States where almost all the existing tokens, with the exception of Bitcoin and perhaps also Ether, are considered as securities, that security tokens are fully assimilated to securities, from a legal, tax, prudential, and accounting standpoint which means that there is for a global coordination, as securities such as equity or debt have different legal status and regime in different jurisdictions.25 Fourthly, at the corporate governance level, the key issue for security token holders is to recognize whether these investors are considered and operationally 66 treated as “traditional” security holders, and how they can exercise the rights accorded to them and so the purchase of security crypto-assets, during ICOs, on crypto-exchange platforms, by over-the-counter transactions, or else, will have analogous qualifications and outcomes than the purchase of “traditional” securities such as equity or debt instruments. Thus, in the first generation of security tokens offerings, all the token management was delivered off-chain or with a mixed off-chain and on-chain so as to evaluate the distributed ledger technology, but as the security token market will develop the market contestants will try to develop as much as possible on-chain token management with the purpose of dropping back offices and middle offices costs preventing a double booking of the operations. It has to be taken into account that equity tokens are, with debt tokens, one of the subcategories of security tokens and so equity tokens are not granting all the rights linked to equity instruments (such as ownership and control rights) or have analogous characteristics to investments but are designed in such a manner that they fall outside the regulatory limit.26 To that extent, tokens could sidestep giving voting rights to investors, rights to dividends and/or to liquidation surplus, or permitting them to submit the inclusion of a draft resolution to shareholder meetings which means that if security token holders do not have the same rights as security holders, Commission (OSC), “OSC highlights potential securities law requirements for businesses using distributed ledger technologies”, Press release, 8 March 2017. 24 The final report of English regulators “Cryptoassets Taskforce from October 2018: “While security tokens fall within the current regulatory perimeter and it is the responsibility of firms to determine whether their activities require authorization, the Taskforce recognizes that the complexity and opacity of many cryptoassets means it is difficult to determine whether they qualify as security tokens.” 25 J. Rohr and A. Wright, “Blockchain-Based Token Sales, Initial Coin Offerings, and the Democratization of Public Capital Markets”, Cardozo Legal Studies Research Paper No. 527, 5 October 2017. The French accounting national authority (the “Autorité des Normes Comptables”) and “International Accounting Standards Board” (“IASB”). 26 Financial Conduct Authority, English HM Treasury and Bank of England, “Cryptoassets Taskforce: final report”, October 2018, p. 20. French financial regulator AMF, “Summary of replies to the public consultation on Initial Coin Offerings (ICOs) and update on the UNICORN Programme”, 22 February 2018.

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and particularly concerning shares, could they be deemed as shareholders, and equity tokens be adjusted to “traditional” shares? Equity tokens are described as one of the most promising crypto-asset classes having several qualities and value in themselves which could interest corporate executives. Crypto-assets and equity tokens are traded all year long and without any boundary or geographical time limitations on crypto-asset exchanges, contrary to traditional corporate shares and financial instruments.27 It has to be taken into account that without a clear international political agreement or international treaty on token status, there is a legal uncertainty as to how a given jurisdiction may qualify an equity token issued in another jurisdiction, along with recharacterization and liability risks for the issuer and the investors. Moreover, equity tokens modify the relationship between company founders and investors and so in tech firms there is an alteration of the “one share, one vote” principle by reducing or avoiding granting voting rights for non-founding investors by generating different classes of shares for the different kinds of shareholders such as founders, early investors, late investors, and by issuing multiple voting shares along with nonvoting shares.28 Hence, company founders and innovators keep a clear control of the company and so altering the impact of institutional investors and shareholder activists by generating value with a long-term standpoint which means that there is continuity in the development of ICOs and security tokens produced by blockchain tech firms. Moreover, crypto-assets have been generated by many startups at an early stage where founders have wanted to uphold a clear control of the shareholding and a clear majority for the main voting decisions by the newly created business. On the other hand, while it could be a valuable device for entrepreneurs to circumvent direct pressure by shareholder activists on the corporation’s profitability at an early stage of the corporation, issuing equity tokens without granting voting rights, occasionally without a financial compensation, or holding their own equity tokens in treasury denotes an encounter for the corporation in the long term, beyond legal issues, at a reputational level leads to shareholders’ reaction through public positions.29 It has to be considered that Equity token holding will advance pushing companies’ management team to stipulate innovative methods to engage equity token holders in the company decision process by providing regular virtual consultations and ad hoc security token holders’ general assemblies.

H. Marks, “The future of US securities will be tokenized”, Medium, 22 May 2018. “Snap Inc.’s IPO [on March 2, 2017], featuring public shares with no voting rights, appears to be the first novote listing at IPO on a US exchange since the New York Stock Exchange (NYSE) in 1940 generally barred multiclass common stock structures with differential voting rights”, in: K. Bertsch, “Snap and the Rise of No-Vote Common Shares”, Harvard Law School Forum on Corporate Governance and Financial Regulation, 26 May 2017; Les Echos, “Snap innove en émettant des actions sans droit de vote à l’occasion de son IPO”, 2 March 2017. S.C.Y.Wong, “Rethinking ‘One Share, One Vote’”, Harvard Business Review, 29 January 2013. 29 K. Bheemaiah and A. Collomb, “Cryptoasset valuation: Identifying the variables of analysis”, Louis Bachelier Institute, Working Report v1.0, 19 October 2018. Les Echos, “Actions sans droite de vote: les investisseurs gagnent une bataille”, 25 September 2017. 27 28

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It seems that even regulations from G7 countries have not already assessed the numerous implications to tokenize existing listed securities such as the possible difference between market capitalization and market tokenization, particularly for listed companies. Even if an equity token is considered equivalent to a share, will it have the same market value than a “traditional” share? In France, a new regulation has permitted the registration of securities’ issuances and transfers on a distributed ledger focused on non-listed shares, debt instruments, and units of OPCs.30 Moreover, Stock market platforms willing to list equity tokens and token-only exchanges will have to trade market abuse concerns by offering fair and effective price discovery and cross-listing transparent information for these new assets. Furthermore, equity tokens also pose the issue of the identification of shareholders due to the fact that until now, the acquisition of almost every existing token is founded on pseudonymity which means that while the owners of tokens are known by a pseudonym, the exact knowledge of shareholders’ identities is a requirement for a corporation.31 Many blockchain entrepreneurs are against the thought of permitting the exact identification of the token holders, but as the crypto-asset market expands and advances to a massive adoption by major market participants, market practices will emerge and deliver methods to offer investor whitelisting/validation processes and to identify exactly the holders of the security tokens.32 It has to be considered that without the likelihood of verifying shareholders’ identities, mergers and acquisitions of firms financed by crypto-assets and the use of DLT, along with class actions, and even the dissolution of the firm which has issued the equity tokens, become much more difficult due to the fact that it is technologically difficult to contact all the shareholders and security token holders. The role of the custodian of

French Law n○ 20161691 of 9 December 2016 “relative à la transparence, à la lutte contre la corruption et à la modernisation de la vie économique” (the so-called “Sapin II law”); Ordonnance n○ 2017-1674 of 8 December 2017 “relative à l’utilisation d’un dispositif d’enregistrement électronique partagé pour la représentation et la transmission de titres financiers”; See California Senate Bill No. 838, chaptered by the California Secretary of State on 28 September 2018 in Chapter 889 of Statutes of 2018; Reuters, “France to allow blockchain for trading unlisted securities”, 8 December 2017; K. Lachgar and J. Sutour, “(R)évolution blockchain pour les titres non cotés français: enjeux et perspectives autour de la consultation publique de la Direction Générale du Trésor”, LEXplicite.fr, 9 June 2017. 31 R. Keidar and S. Blemus, “Cryptocurrencies and Market Abuse Risks: It’s Time for SelfRegulation”, SSRN, 25 February 2018. 32 US Department of the Treasury, Financial Crimes Enforcement Network, “Guidance on the Application of FinCEN’s Regulations to Persons Administering, Exchanging or Using Virtual Currencies”, FIN-2013-G001, 18 March 2013; Directive (EU) 2018/843 of the European Parliament and of the Council of 30 May 2018 amending Directive (EU) 2015/849 on the prevention of the use of the financial system for the purposes of money laundering or terrorist financing; D. Holman, B. Stettner, “Anti-Money Laundering Regulation of Cryptocurrency: US and Global Approaches”, Allen & Overy LLP, published in “Anti-Money Laundering Laws and Regulations 2018”, ICLG, July 2018. 30

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crypto-asset private cryptographic keys will be indispensable by defining its precise role and its specificity from the ones of the existing custody services.33 Several systems have developed the identification of security holders and so diminishing the opportunity for rent-seeking or corrupt behavior.34 Even though the possibility of human or technological errors in transfer of equity tokens persists, the transparency offered by an equity token registration on a public DLT allows anyone such as investors, market makers to scrutinize in real time managers’ and other shareholders’ ownership positions and trading movement.35 In the long term, when DLT will be broadly used by firms, and especially public ones, regulators might deliver mandatory disclosures of public keys by equity token holders. Are there difficulties for utility and cryptocurrency token holders to be recognized as corporate stakeholders? Utility tokens and cryptocurrency tokens pose vital questions linked to corporate law and to corporate management and so in startup financing; many funders have been inclined to generate utility tokens so as to raise funds without granting to investors economic or political rights or having any considerable fiduciary duty to the investors.36 On the other hand, many utility tokens are already exchanged on cryptocurrency exchanges, which means that they have an economic value. Moreover, utility tokens, as well as cryptocurrencies, as they are exchanged on the secondary market, represent a shift in the way we deem corporate stakeholders beyond the sole shareholder issue and so while holders of these utility tokens or cryptocurrency tokens will not have voting rights during AGMs, reserved to equity token holders, the market value of these tokens on crypto-exchanges will represent an imperative role in exerting pressure on the company management and for these stakeholders to have an indirect influence on the firm’s decisions. It could be said that corporations, such as Amazon, Facebook, or Société Générale, will issue a utility token whose value is exchanged on the secondary market and the utility token holders, and notably the consumers of a company, will develop a direct dialogue with the firm by sending requests to the firm management which means that in the long term, firms will reconsider their business models, the role of these stakeholders, by forming ad hoc assemblies, specific committees or

33 The Directive (EU) 2018/843 defines “custodian wallet provider” as “an entity that provides services to safeguard private cryptographic keys on behalf of its customers, to hold, store and transfer virtual currencies.” 34 D. Yermack, “Corporate Governance and Blockchains”, Oxford Review of Finance, Volume 21, March 2017, pp. 7–31; K. Malinova and A. Park, “Market design with blockchain technology”, SSRN, 30 May 2016. 35 A. Tinianow, “Tokenized securities are not secured by Delaware Blockchain Amendments”, 4 July 2018. D. Yermack, “Corporate Governance and Blockchains”, Oxford Review of Finance, Volume 21, March 2017. A. Edmans, “Blockholders and corporate governance”, Annual Review of Financial Economics, Vol. 6, 2014, pp. 23–50; L. Bebchuk and R. Jackson, “The law and economics of blockholder disclosure”, Harvard Business Law Review, 2012, pp. 39–60. 36 K. Bheemaiah and A. Collomb, “Cryptoasset valuation – Identifying the variables of analysis”, Louis Bachelier Institute, Working Report v1.0, October 2018.

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other innovative involvement modes with the purpose of advancing the interactions with these new firm stakeholders.37 It is assessed that the development of micropayment systems was automated and implemented by smart contracts, instead of relying on “advertising-based revenue models.”38 A stable token is a crypto-asset whose value is pegged to an existing asset such as fiat currencies, for example, US Dollars and Euros, but also sometimes gold, and which can be collateralized by this existing asset. Moreover, stable tokens have been mostly used to diminish the volatility linked to crypto-assets and so offering financial stability solution at the crossroads between crypto-asset markets and fiat currencies markets. It is worth noting that after the formation of assembly meetings of shareholders and bondholders, it is necessary to organize general assemblies of utility token holders and so with the intention of evading a recharacterization of the utility tokens into security tokens, these general meetings will not consist in votes on the company management, but on a new kind of communication with the company’s stakeholders. However, current ICO whitepapers rarely provide assembly meetings of token holders with the exception of some security token issuances.39 In line, issuing utility tokens or even stable tokens is a way for corporations to attract and reward early adopters of the tokens and so offering extra rights to their consumers, shareholders, suppliers, investors, and/or employees, and an inducement to further a deeper commitment to the organization from them. In another way, informal assemblies of utility token holders, organized with only noncompulsory consultations, are utilized to advance and inspire interaction, communication, and disclosures of reporting with the vast firm’s ecosystem, not through a voting process but through more consultation with the numerous stakeholders in the ecosystem of the company.40

E. Kim, “Amazon just bought three domain names related to cryptocurrency”, CNBC, 1 November 2017. Reuters, “Retailer Carrefour using blockchain to improve checks on food products”, 6 March 2018. A. Cuthbertson, “Is Facebook about to launch its own cryptocurrency?”, The Independent, 9 May 2018. 38 A. Wright and P. de Filippi, “Decentralized Blockchain Technology and the Rise of Lex Cryptographia”, SSRN, March 2015. 39 Alethena Token Specifications published on 14 May 2018. 40 C. Catalini and J. Gans, “Some Simple Economics of the Blockchain”, MIT Sloan Research Paper No. 5191-16, 21 September 2017, p. 17. M. Fenwick and E. Vermeulen, “Technology and Corporate Governance: Blockchain, Crypto and Artificial Intelligence”, ECGI Working Paper No. 424/2018, November 2018, pp. 16–19. 37

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Blockchain and Fiduciary Duties

Public blockchain systems are “trust-minimized,” but “trust-shifting”—which indicates the need to trust in others than the officers and directors of a bona fide corporation and so in these systems that operate money, smart contracts, and possibly many other critical human practices which means that people continue to lead and make vital decisions on behalf of others. There are other parties who play vital roles in a public blockchain system, embracing miners, nodes, users, and exchanges being businesses that exchange one cryptocurrency for another cryptocurrency or a traditional sovereign currency like the US dollar.41 Moreover, certain people who produce, activate, or reshape public blockchains function much like fiduciaries of those who depend on these powerful data structures. Explicating the crucial functions that leading software developers perform as fiduciary, and as users of these technologies place extreme trust in the leading developers to be both competent and loyal (i.e., to be free of conflicts of interest). Do these “decentralized” structures such as public blockchains—Bitcoins even have governance? It could be said that the central developers and important miners of public blockchains function as fiduciaries of those who count on these systems, and consequently should be accountable as such.42 Concerning the peer-to-peer computer network that runs these data structures through the running of software code, governance takes place through the software development and transaction verification processes and so certain developers of public blockchains embrace people who write software code, make decisions about policies that should be reflected in software code, review software code, etc. Moreover, the governance of “private” or “permissioned” blockchains is data structures with a known and trusted group of transaction processors. Public (permissionless) blockchains like Bitcoin and Ethereum are data structures for which anyone can become a transaction processor merely by running the applicable software. Is the age-old fiduciary concept a poor fit for cutting-edge public blockchains? It could be said that the age-old fiduciary concept is a poor fit for cutting-edge public blockchains, which are praised for enabling human coordination without the need to trust in a central party. Furthermore, the fiduciary concept is based fully on trust— one party entrusting another to make decisions on her behalf and so by applying the fiduciary construct to public blockchains underlines that even in public blockchains there is the need to trust in other humans. 41 Jatinder Singh and Johan David Michels, ‘Blockchain as a Service’ (2017) Queen Mary University of London, School of Law Legal Studies Research Paper No. 269/2017 Primavera De Filippi and Aaron Wright, Blockchain and the Law: The Rule of Code (Harvard UP 2018). 42 Nick Szabo, ‘Money, blockchains, and social scalability’ StateFarm MutualAuto Ins v Bockhorst, 453 F2d 533, 537(10th Cir 1972). Angela Walch, ‘Call Blockchain Developers What They Are: Fiduciaries’ American Banker (9 August 2016) .

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Securities regulators around the globe are appraising how the tokens of blockchain systems fit into existing securities laws, with a number of prosecutions stemming from the original coin offering mania that struck the cryptocurrency world in 2017. It is argued that it was doubtful that Bitcoin or Ethereum were securities owing to their decentralized status for the reason that “purchasers would no longer reasonably expect a person or group to carry out essential managerial or entrepreneurial efforts.”43 Public blockchains are decentralized and there is no central entity that creates or maintains them and so they function on a peer-to-peer basis through the running of open-source software by a network of computers.44 The mining networks of public blockchains like Bitcoin and Ethereum are both quite centralized, which is relevant to the governance role miners play in these networks. The software development process for public blockchains is decentralized, as is typical of open-source software projects and so there is no central entity that is officially accountable for providing or updating the software. Thus, software developers write and update the software, verifying how to revise the code through informal processes that rely on consensus that are subject to no fixed legal or organizational structure.45 In line, the code is publicly available, and anyone in the globe may propose an alteration via a standardized proposal process and many developers from across the globe have made proposals.46 Furthermore, in open-source software projects like public blockchains, a team of “core developers” or “maintainers” directs the software development process and so this group of people may not be united under the roof of an entity structure, they perform as leaders and decision-makers for the code which means that this power manifests in the ways in which they differ from rank-and-file developers.47 With Bitcoin core developers until recently have had the capacity to send emergency messages to all nodes in the network, and are the only developers who have “commit access” that permit them to make real alterations to the software code. Moreover, other developers can recommend alterations, but a core developer’s password/access code is eventually needed to put that alteration in a new code

43 Speech by William Hinman, Digital Asset Transactions: When Howey Met Gary (Plastic), 14 June 2018 . 44 Adem Efe Gencer and others,‘Decentralization in Bitcoin and Ethereum Networks’ (2018) arXiv. org . 45 Shawn Bayern, ‘Of Bitcoins, Independently Wealthy Software, and the Zero-Member LLC’ (2014) 108 Northwestern U L Rev Online 257, 259. Peter Van Valkenburgh, ‘What could “decentralization” mean in the context of the law?’ (Coin Center Blog15 June 2018) . 46 https://github.com/bitcoin/bitcoin and https://github.com/ethereum. 47 Joon Ian Wong, ‘Ethereum’s inventor on how ‘initial coin offerings’ are a new way of funding the internet’ Quartz (14 September 2017) .

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release.48 Prominent developers also affect how the public blockchains are perceived by regulators and the public at large, as certain developers have met privately with numerous international regulators or leaders and often comment publicly on what should happen with the specific blockchain they represent and the technology as a whole.49 Hence, this software development process restrains the influence that users have, irrespective of their computing power, to influence the development of the official Bitcoin software. The fiduciary concept is based most fundamentally around trust. Familiar fiduciaries include doctors, lawyers, financial advisors, trustees, and corporate officers and directors. Fate is placed in the hands of others and so counting on advice in order to perform tasks that we cannot do for ourselves and to manage our funds or investments to our benefit.50 It is worth noting that Nick Szabo has also analogized miners to fiduciaries and noted the significant trust placed in blockchain software developers: “Miners are partially trusted fiduciaries, and those who are not expert developers or computer scientists who have invested a great deal of time in learning the design principles and codebase of a blockchain must place a great deal of faith in the expert developer community, much as nonspecialists who want to understand the results of a specialized science do of the corresponding scientists.” Besides, it could be said that not all the core developers or dominant miners would be considered fiduciaries based on jurisdiction’s existing law. It is likely that in public blockchains, certain entrustors will fail to protect themselves from the risks entangled in a fiduciary relationship with developers. This is as a result of the expertise barrier between blockchain software developers and users who cannot estimate software code themselves. In “permissionless” systems like public blockchains, there is nothing that averts individuals who lack software expertise from becoming involved with a given blockchain, whether through the purchase of tokens or token-based financial products, or by investing in or generating a business tied to the blockchain. Thus, anyone who lacks

48 Andreas M. Antonopoulos, Mastering Bitcoin: Unlocking Digital Cryptocurrencies (2nd edn, O’Reilly 2017)157. The password that permitted the sending of the network-wide emergency messages was held only “by a few select members of the core development team.” 49 Arthur Gervais and others, ‘Is Bitcoin a Decentralized Currency?’ (2014) (arguing that giving the emergency alert power only to the coredevelopers “gives these entities privileged powers to reach out to users and urge them to adopt a given Bitcoin release”). Tom Simonite, ‘The Man Who Really Built Bitcoin’ MIT Technology Rev (Aug. 15, 2014), (describing how only the core developers have the power to “change the code behind Bitcoin and merge in proposals from other volunteers”). 50 Jack M Balkin, ‘Information Fiduciaries and the First Amendment’ (2016) 49 U California Davis L Rev 1183 (arguing that tech companies who hold personal data should be deemed ‘information fiduciaries); D Theodore Rave, ‘Politicians as Fiduciaries’ (2013) 126 Harvard L Rev 671 (arguing that politicians function as fiduciaries of their constituents); Ethan Leib, David L Ponet and Michael Serota, ‘A Fiduciary Theory of Judging’ (2013) 101 California L Rev 699 (arguing that judges should be considered fiduciaries of the public).

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knowledge in the specific code of the blockchain, due to the fact that many of which are coded in newly developed software languages like Solidity and OCaml, will have a difficult time protecting themselves from the actions of developers, as they are incapable of appraising the software code and any proposed alterations to it. To that extent, they have to count on the developers to make good policy and technical decisions and so if nontechnical people want to use public blockchains, they should pay to have the code scrutinized and warrantied for them when talking about direct purchasers of public blockchain tokens. It seems that fiduciaries that serve numerous entrustors in a standardized manner such as in the case with developers of public blockchains obtain power that is greater than the power of fiduciaries that serve individuals due to the fact that in public blockchains the decisions and actions of developers influence an entire blockchain system at once, rather than a single person. Furthermore, the entrustors’ capacity to control their fiduciaries is deteriorated with the rise in the entrustors’ number. Thus, the entrustors may not be well organized, may have different interests and different ideas concerning the welfares that their fiduciaries must chase and so divergent views of the decisions and actions developers should take reduce the control they exercise over developers. Although early coin offerings (ICOs) and independent blockchain projects have created many millionaire Ethereum developers, most Ethereum core developers earn salaries that are much lower than the market standard and so core developers are not adequately incentivized. It seems that investors have poured billions into ICOs, with little detail offered on the technology or the development team behind the technology.51 Hence, many scams have happened, signifying that market signals may not aid entrustors to correctly assess a public blockchain and its developers.52 It could be said that the costs for software developers serving as fiduciaries of establishing their trustworthiness are higher than their profits from the relationship being true in public blockchains that count on grassroots open-source software governance, with uncertainties of how the work of software developers is funded. Thus, developers have to spend significant time and effort achieving credibility and respect for their competence in order to be granted commits access rights.53 Key developers realize the heavy responsibility they bear to keep the blockchain running and so core developers of software resigned from their role since they were concerned about personal legal risk.54 It could be said that those who act as

David Floyd, ‘$6.3 Billion: 2018 ICO Funding Has Passed 2017’s Total’ CoinDesk (19 April 2018) . 52 Nikhilesh De, ‘SEC Halts Mayweather-Endorsed ICO, Charges Founders With Fraud’ CoinDesk (2 April 2018) . 53 Rachel Rose O’Leary, ‘Zcash PaysOff Developer to Avoid Blockchain Split’ CoinDesk (22 June 2018) . 54 Jonas Schnelli (Bitcoin core developer), Twitter (15 November 2017) (“4 developers have currently commit access: @orionwl@pwuille@MarcoFalkeand myself. It’s a burden. It’s for those who are willing to review 51

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fiduciaries should be legally accountable as fiduciaries. Nonetheless, treating these parties as fiduciaries with associated liability would go against existing liability background for software system, which generally enables those who generate software to disclaim liabilities for its shortcomings or harms it triggers and has been resistant to describing those creating, designing, or building software as professionals subject to claims of professional malpractice.55 How might fiduciary status of developers arise? Fiduciary duties can arise in a number of ways—by contract, by statute, by acting as a fiduciary in the eyes of a court, or by status. Is fiduciary categorization based exclusively on contract and may be contracted out of by the participants or are there situations in which fiduciary status arises by virtue of relationship or status and may not be disclaimed? It has to be taken into account that if one views fiduciary status as being purely contract based, then a broad liability disclaimer and failure to positively generate a fiduciary relationship by contract mean no fiduciary status or liability could attach to a developer. Hence, the contract between users and developers denotes a fiduciary status. Nevertheless, there is no certainty that the open-source software licenses will be enforced, and which specific individuals would be bound to the licenses. To that extent, not all owners of bitcoins or ether or other cryptocurrencies in fact run the software themselves, and many never see the associated open-source software license which means that they acquire their cryptocurrencies via intermediaries like exchanges, or they may be exposed to what happens to cryptocurrencies through derivatives like futures contracts or investment funds raising questions concerning whether a given user of a cryptocurrency was on notice of the license terms, and is bound to them. On the other hand, it could be said that there is no need to present a contract forming a fiduciary relationship for developers to be treated as fiduciaries, and even if the liability disclaimers around the software are upheld, they may not apply to breach of fiduciary claims. Moreover, a court could view developers to be acting as fiduciaries, but courts are reluctant to generate new types of fiduciaries such as spouses, mediators, and mortgage brokers, among others, as emerging fiduciaries, and, more recently, tech firms who hold personal data as “information fiduciaries.” Developers of public blockchains are fiduciaries, embracing the superior expertise and skill required for public blockchain software design and development, due to the fact that public blockchains entrench and transfer value for an entire blockchain system, making developers’ actions consequential for possibly large numbers of

and test code and keep up with the ~80 github comments per day. It’s not always fun and it’s certainly not a privilege.”). Rachel Rose O’Leary, ‘EthereumDeveloper Resigns As Code Editor Citing Legal Concerns’ CoinDesk (15 February 2018) . 55 Michael D. Scott, Scott on Information Technology Law (3rd edn) (Aspen2018-2 Supplement) Section 15.09[A] (“Whether computer designers or programmers are professionals in the legal sense is still an open question.”). Marian K. Reidy & Bartlomiej Hanus, ‘It Is Just Unfair Using Trade Laws To Out Security Software Vulnerabilities’ (2017) 48 LoyolaU ChicagoLawJ 1099, 1111–1114.

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people. Finally, developers could be considered fiduciaries of a public blockchain by statute. Can fiduciary duties be imposed to the blockchain context and other open-source projects? It could be said that imposing fiduciary duties is not limited to the blockchain context and could be expanded to other open-source projects due to the fact that they have been an important force in industry and society for decades. Moreover, blockchain architects should weigh up adopting contracts that rely upon corporate governance models not eliminating the notion of fiduciary responsibilities in blockchain governance, but rather, allocate such responsibility in light of the actual mechanics of the technology and so empowering a system of heightened responsibility for a greater number of players in the ecosystem under particular settings. What are the consequences of a breach of the duty? The effects of a breach of such a fiduciary duty are that the “entrustors” would have a cause of action against the fiduciaries for the breach, which means that fiduciary developers are subject to liability claims from an immense number of people—users of the applicable cryptocurrency, possibly along with businesses building on and servicing the blockchain. Moreover, notwithstanding any cryptocurrency that they may have formerly managed to cash out, it would be very difficult for any of these fiduciary developers to fulfill their liabilities—the cost of making whole an entire blockchain would merely be too great. Hence, the fact that the economic damages triggered by parties considered fiduciaries are great for them to cover casts doubt on whether the fiduciary categorization is meaningful and so the entrustors are unlikely to ever be made whole. There is a need for a higher standard of software engineering for blockchain software development, given its predominantly difficult character and the high stakes implicated with errors. Moreover, prospective for liability claims incentivizes developers to form a more traditional legal organizational structure for a public blockchain such as a corporation or limited liability company. On the other hand, adopting a conventional legal structure goes essentially against the central ideal of decentralized governance in public blockchain systems.

3.4

Corporate Governance Theories

When the expression corporate governance first achieved status in the 1970s, it apparently connoted that the corporation was a political structure to be governed. Moreover, with the phrase “corporate governance” becoming more and more linked with the preservation and promotion of shareholder value, attention turned to the internal control systems of publicly held corporations. During the 1990s the promotion of shareholder rights and the fostering of boardroom responsibility became topics of interest globally, rather than simply in the United States. Corporate governance’s staying power in the United States was

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due partly to changing patterns of share ownership.56 The greater the value of assets under the control of public company executives, the more the emphasis there should be on corporate governance. The executives in charge respectively merited closer scrutiny, predominantly given that they were operating in a more volatile market environment owing to deregulation, increased competition, and technological advances reducing barriers to entry in many industries.57 In addition, leading US corporations accomplished unmatched global economic dominance in the “managerialist”58 era immediately following World War II. Customarily, corporate governance tackles issue of decision-making at the level of the board of directors and top management to guarantee that all decisions taken are in line with the objectives of a corporation and its shareholders.59 In addition, corporate governance includes all the rules of and restrictions on corporate decisionmaking. Corporate governance replies to agency problems produced by the separation of ownership and control identifying the relationship between shareholders and managers. First-class corporate governance necessitates that managers have the appropriate motivations to work in support of shareholders and that shareholders are appropriately informed about the decisions of the managers. Consequently, corporate governance tolerates a balance between managers’ and shareholders’ requirements.60 At the outset, the internal governance of corporations was not a high precedence and the concentration was on building trust among corporate executives and shareholders who were only concerned about dividends and stock prices of the firms they owned.61 Lately, corporate governance has become one of the most vital features of modern theories of the corporation being a central policy issue in developed market economies and one of the most challenged issues in transition economies. The agency problem between shareholders and managers is a key questioned issue investigated in the context of corporate governance. The separation of ownership from control

Bengt Holmstrom and Steven N. Kaplan, The State of U.S. Corporate Governance: What’s Right and What’s Wrong?, 15(3) J. APP. CORP. FIN. 8, 11, 14 (2005). “The role of top management is no longer just control and coordination, it is anticipating, leading and managing change. . . .”, Gerald F. Davis, Managed By The Markets: How Finance Re-Shaped America 63 (2009) (identifying the period from 1920 until the 1980s as the era of managerial capitalism, with the 1950s being when the managerial “soulful” corporation came to dominance). 57 Robert Reich, Supercapitalism: The Battle For Democracy In An Age Of Big Business 50-70 (2009) (identifying factors that disrupted corporate stability in the U.S. as the 20th century drew to a close). 58 Xavier Gabaix, The Granular Origins of Aggregate Fluctuations, 79 Econometrica 733, 734 (2011). 59 Muelbert, P. O. (2009, August). Corporate governance of banks after the financial crisis: Theory, evidence, reforms (ECGI Law Working Paper No. 130/2009): http://ssrn.com/abstract¼1448118. 60 Wells, H. (2010). The birth of corporate governance. Seattle University Law Review, 33(4), 1247–1292. 61 Howson, N. C. (2009, December). When “good” corporate governance makes “bad” (financial) firms the global crisis and the limits of private law. Michigan Law Review, First Impressions, 108, 44–50. 56

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that repeated with the continuing materialization of the modern giant corporation, in which none of the directors or managers has more than a minority financial interest, has awakened the prospect that the interests of those who control business and those who own it may diverge.62 According to the OECD, corporate governance necessitates a set of relationships between a firm’s management, its board, its shareholders, and other stakeholders offering the structure through which the objectives of a firm are set, and the process of accomplishing those objectives and supervising performance is ascertained.63 Reliable corporate governance presents fitting motivations for the board and management to chase objectives that are in the interests of the company and its shareholders making possible effective screening. The key reason of strong corporate governance is to multiply shareholders’ equity and to accomplish sustainable economic growth. Aquila64 says that advantageous corporate governance has to fulfill the interests of all stakeholders by guaranteeing the implementation of acceptable internal and external controls over a firm’s operations. A corporate stakeholder is any person, group, or organization that places a right on a firm’s interests, resources, or output. Global enterprises have to more and more adapt themselves to the fact that outside players, predominantly civil society organizations, for which neither the territorial state nor the return purpose are principal drivers have turned into a duty of their global operating environment. The perception of civil society embraces voluntary and not-for-profit organizations, philanthropic institutions, social and political activist networks, community groups, and associated organizations. The participation of financial intermediaries and brokers contributes to maneuver market price while upholding their credibility. Concerning the rationale for corporate scandals, such as Enron, there is a subject related to external auditor function, responsibilities by and large and in their communication and transparency with the Board and with the corporation, over and above broad duties to shareholders. Speculators manipulate transactions causing an increase in investment flow into the invested corporation when speculators yield enough information. Insider trading is a basis of market manipulation. Information on good business openings, which encloses uncertainty and risks in future, or information on prospect of merging of firms is quality to market price manipulation. To facilitate managing negative market manipulation, essential actions are enhancing mechanisms of internal audit and internal control. Dissimilar ownership construction involves manipulation. Moreover, in dispersed ownership regime, manager may have enticements to carry out some stock Li, P. (2009). How can corporate governance control enterprise’s financial risk? http://papers. ssrn.com/sol3/papers.cfm?abstract_id¼1523519. 63 Organization for Economic Co-operation and Development. (2004). OECD principles of corporate governance (Corporate Governance Principles). Organization for Economic Co-operation and Development. 64 Aquila, F. (2009, December 9). Corporate governance: Don’t rush reform. Business Week, 9. http://www.businessweek.com/investor/content/dec2009/pi2009128_869797.htm. 62

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market manipulation. Managers manipulate non-GAAP measures to deceive investors.65 According to the 2012 CG Code in Pakistan, good CG instills investor confidence. Moreover, the UK Financial Reporting Council specified that corporate governance is about what the board of a firm does and how it adjusts the values of the firms, and is to be characterized from the day-to-day operational management of the firm by full-time executives. D. Huy66 says that “Sustainable corporate governance and sustainable management, hence, might become concepts in many kinds of companies which may find useful when confronted with complexity and instability of their environment.” Corporate governance codes are a gradually more leading characteristic of the regulatory setting in many states in the twenty-first century which embrace: “(1) the diffusion of an international benchmark model of good governance; (2) a country’s legal system; (3) the desire to attract foreign investors; and (4) the influence of interest groups.”67 It has to be taken into account that the regulatory purpose of corporate governance codes is to bolster the responsibility of managers depending not only on the conformity of enterprises with the code terms, but also on the mode and content of these terms. Carsten Gerner-Beuerle68 did not find any evidence supporting the convergence hypothesis of corporate governance systems which means that there is no converge toward a single, standard governance model and so there is an absence of international flow and transplantation of legal ideas. In other words, it seems that, even in the current stage of globalization and digital economy, there is not a convergence in the corporate governance which causes the current failures of enterprises regarding many sectors such as finance, e-commerce, and e-technology.

3.5

Governance Structures

Corporate governance concentrates on the structure of the firm, signifying to the manner in which a corporation is managed, administered, and controlled and so corporate governance deals with the decision-making at the level of the board of directors and top management, and the various internal and external means that make certain that all decisions taken by the directors and top management are in line with

65 Baik, Bok., Billing, Bruce K., and Morton, Richard M., (2005), Manipulation, Increased Transparency, and Value Relevance of Non-GAAP Disclosures for Real Estate Investment Trusts (REITs), FARS Meeting Paper. 66 Dinh Tran Ngoc Huy The Analytical Assessment Of Some Middle East Corporate Governance Standards After The Global Crisis at: http://ssrn.com/abstract¼2361288. 67 Carsten Gerner-Beuerle, Determinants of Corporate Governance Codes, LSE Law, Society and Economy Working Papers 5/2014 p. 1. 68 Carsten Gerner-Beuerle, Determinants of Corporate Governance Codes, LSE Law, Society and Economy Working Papers 5/2014 p. 39.

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the objective(s) of a company and its shareholders, correspondingly.69 By the way, the board of directors selects the members of the audit, good governance, and risk management committee. The committee is composed exclusively of independent directors. The board of directors makes certain that the audit, good governance, and risk management committee has the means to accomplish its duties. Following mutual consultation with the chairman of the board of directors, the committee appeals to external consultants and this is at the expense of the corporation. In addition, corporate governance refers to the relationships among the different internal and external stakeholders implicated with the governance processes planned to assist a corporation in order to accomplish its objectives.70 The OECD71 has issued the “Principles of Corporate Governance” specifying that “Corporate governance involves a set of relationships between a company’s management, its board, its shareholders and other stakeholders. Corporate governance also provides the structure through which the objectives of the company are set, and the means of attaining those objectives and monitoring performance are determined. Good corporate governance should provide proper incentives for the board and management to pursue objectives that are in the interests of the company and its shareholders and should facilitate effective monitoring.” Furthermore, Secretary General Angel Gurria72 argued that “good corporate governance is not an end in itself. It is a means to create market confidence and business integrity, which in turn is essential for companies that need access to equity capital for long term investment. Access to equity capital is particularly important for future oriented growth companies and to balance any increase in leveraging.” Corporate governance in the United States has changed dramatically and the SEC has increased its focus on “proxy plumbing,”

H. Kent Baker and R. Anderson, “An Overview of Corporate Governance”, in “Corporate governance: a synthesis of theory, research and practice”, 2010, p. 15. A. Keay, “The Enlightened Shareholder Value Principle and Corporate Governance”, 2013. P. O. Mülbert, “Corporate Governance of Banks after the Financial Crisis – Theory, Evidence, Reforms”, European Corporate Governance Institute (ECGI), Law Working Paper N○ 130/2009, April 2010, p. 4. 70 H. Kent Baker and R. Anderson, “An Overview of Corporate Governance”, in “Corporate governance: a synthesis of theory, research and practice”, 2010, p. 15. 71 OECD, “G20/OECD Principles of Corporate Governance”, OECD Publishing, 2015. The G20/OECD corporate governance principles of 2015 offer guidance on six main chapters: (1) ensuring the basis for an effective corporate governance framework; (2) protecting the rights (to information and participation) and equitable treatment of shareholders and key ownership functions; (3) promoting sound economic incentives throughout the investment chain and its numerous intermediaries (institutional investors, stock markets and other intermediaries); (4) recognizing the role and rights of stakeholders and encouraging active cooperation between corporations and stakeholders; (5) ensuring a timely and accurate disclosure and transparency regarding the corporation; and (6) ensuring the responsibilities of the board (the strategic guidance, the effective monitoring of management by the board and the board’s accountability to the company and the shareholders). 72 A. Gurria, “Note by the OECD Secretary General”, G20 Finance Ministers and Central Bank Governors Meeting, 4–5 September 2015. 69

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transparency and efficiency of the voting process; shareholder communications and retail participation in the voting process.73 It is characteristic that Goldman Sachs bankers circumvented its internal controls and bribed numerous officials in Malaysia and Abu Dhabi, in exchange for the fees from the underwriting of 1MDB bonds74 denoting that the mechanisms to make certain that agents within companies execute their tasks and duties in line with the long-term interests of their shareholders, rather than pursuing their immediate selfinterest are far from fail-proof.75 It seems that laws and market pressures have so far been unable to stop this core corporate governance challenge. Will algorithms and machines, with their more authoritative, disinterested, and unbiased informationprocessing capability, be better at monitoring corporate agents? This author (Zekos) considers that corporate governance is the whole networking, conventional, and digital, within a firm dealing with the function of the firm in relation to the market and the interrelationships among all levels of directorship and shareholders. It is argued that the provision of control rights between shareholders and managers (“governance structure”) is irrelevant to corporation value. Moreover, governance structures influence managers’ motivation to invest, as strong governance strengthens managerial freedom and weak governance loosens it and so, provided their particular managerial freedom, numerous corporations buy resources for their business activities in a competitive market. Thus, managers differing in their integrity can preserve value, generate value, or wreck value and consume private benefits which means that shareholders deduce from decisions made by managers whether a manager should be retained or fired. It has to be taken into account that independent governance selections of individual companies are interdepended from resources markets and so the companies split between strong and weak governance companies, with all of them having the same value. On the other hand, no firm alters its value by shifting from weak to strong governance or vice versa which means that the governance construction is irrelevant.

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SEC v. Siebel Systems, Inc, 384 F. Supp. 2d 694, 704-05 (S.D.N.Y. 2005). David A Katz, David B Anders and Sabastian V Niles, ‘Regulation FD Compliance Requires Continued Vigilance’, Securities Reform Act Litigation Reporter, Volume 36, Number 1 (2013). 74 Press Release, U.S. Dep’t of Justice, U.S. Attorney’s Office, Eastern District of New York: Malaysian Financier Low Taek Jho, Also Known As “Jho Low,” and Former Banker Ng Chong Hwa, Also Known As “Roger Ng,” Indicted for Conspiring to Launder Billions of Dollars in Illegal Proceeds and to Pay Hundreds of Millions of Dollars in Bribes – Former Banker Tim Leissner Pleaded Guilty to Conspiring to Launder Money and to Violate the Foreign Corrupt Practices Act Related to 1MDB (Nov. 1, 2018), https://www.justice.gov/opa/pr/malaysian-financier-low-taekjho-also-known-jho-low-andformer-banker-ng-chong-hwa-also-known. 75 Sridhar Natarajan, U.S. Prosecutors Recommend Goldman Guilty Plea for 1MDB, FT Says (24 Apr. 2019), https://www.bloomberg.com/news/articles/2019-04-24/us-prosecutors-recom mend-goldman-guilty-plea-for-1mdb-ft-says. Michael C. Jensen & William H. Meckling, Theory of the Firm: Managerial Behavior, Agency Costs and Ownership Structure, 3 J. Fin. Econ. 305, 308 (1976) (arguing that moral hazard is a firm’s main determinant of agency costs).

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It is worth noting that by pushing more public companies toward strong governance, institutional investors with common ownership generate a monopsony power, with negative results to the labor market, the inputs market, the investment level in the economy, and the number of companies traded on public markets. It could be said that corporate governance means that allocating more control rights to shareholders permits them to hold disloyal managers accountable, and, so, diminish agency costs.76 Moreover, a weak governance structure by allocating more control rights to managers is associated with weak company value and performance owing to a high level of agency costs.77 Z. Goshen and D. Levit78 argue that “strong governance and the threat of being red by shareholders, deters all types of managers from undertaking investment and buying resources; weak governance does the opposite. Intuitively, strong governance structures tighten managerial freedom and weak governance structures loosen it. Therefore, the total demand for resources is affected by the division of the universe of firms between strong and weak governance. In particular, a larger number of firms with weak governance implies more investment and a higher demand for resources, which results in a higher price of resources and a lower value of firms with weak governance. . .the universe of firms will reach an equilibrium in which some firms have weak governance and other strong governance, but all firms will have the same value. A single firm and its shareholders cannot change the value of their firm by switching governance from weak to strong or the other way around; they are indifferent between these choices in equilibrium. Moreover, the competitive equilibrium is socially efficient in the sense that the allocation of resources cannot be improved, and in particular, a regulatory intervention is counterproductive”. It could be said that the independent governance choices of individual companies influence the clearing of the resource’s markets. Moreover, the governance structure is irrelevant when shareholders do not have perfect competence or market power in the ownership of multiple companies with common ownership, when companies do not have market power in the resources market, and when managers have profound career concerns which mean that an abuse of these conditions leads to governance relevance. Furthermore, it is worth noting that the relationship between the allocation of control rights and corporation performance is more complex than just holding managers accountable. To that extent, the report found widespread misconduct suggesting that the community anticipates corporate Australia to foster a culture that stimulates good leadership, decision-making, and ethical behavior.79 Moreover, directors must exercise their powers and discharge their duties in good faith, in the 76

Bebchuk, Lucian A. & Alma Cohen, The Costs of Entrenched Boards, 78 J. Fin. Econ. 409. Bebchuk, Lucian A., Alma Cohen & Allen Ferrell, What Matters in Corporate Governance?, 22 Rev. Fin. Stud. 783–827 (2009). Bebchuk, Lucian A., Scott Hirst & June Rhee, Towards the Declassication of S&P 500 Boards, 3 Harv. Bus. L. Rev. 157–184 (2013). 78 Zohar Goshen Doron Levit, Irrelevance of Governance Structure, ECGI Working Paper Series in Finance, Working Paper N○ 606/2019 May 2019. https://ssrn.com/abstract¼3340912 P4. 79 Andrew Lumsden, The wider implications of the Hayne Report for corporate Australia, https:// ssrn.com/abstract¼3342855. 77

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best interests of the corporation, and for an appropriate reason and so the Report recognizes that the duty demands “. . . consideration of more than the financial returns that will be available to shareholders in any particular period. Financial returns to shareholders (or “value” to shareholders) will always be an important consideration but it is not the only matter to be considered.” It is acknowledged that the best interests of the corporation cannot be decided by reference only to the shortterm objectives of the corporation and so Chief Justice80 acknowledged that directors are liable for conduct falling short of a strict breach of the law, the breach nevertheless inappropriate or unethical, where such conduct results in substantial reputational damage and subsequent financial consequences. Likewise, a breach of duty is based exclusively on the reputation issue such as insistently pursuing shortterm profit in disrespect of the best interests of clients and long-term viability. It could be said that directors have a role as “gatekeepers” making that their enterprise has strong internal audit and compliance utilities. Boards of directors typically organize committees to perform specific functions without the presence of the entire board. Boards are specifically obliged by federal securities laws to have an audit committee with certain prescribed functions regarding the retention, compensation, and oversight of the firm’s independent auditor. Federal securities laws and NYSE and NASDAQ listing rules also compel listed corporations to maintain compensation and nominating or corporate governance committees. Directors’ most basic and vital responsibility is to exercise their business judgment in a way they reasonably believe to be in the best interest of a firm and its shareholders. In Delaware and 32 other states and the District of Columbia, directors of such corporations have an expanded fiduciary obligation to consider other stakeholders along with shareholders, embracing their overall influence on society, their workers, the communities in which they trade, and the environment. Moreover, the business judgment rule will protect directors when the corporate records reflect that they studied and respected the facts available to them and the advice of their advisers and when the directors did not have a conflict of interest in the decision.81 The board of directors has to work with management to set a suitable “tone at the top” of the corporation to inspire conscientiousness, transparency, ethical behavior, and cooperation throughout the organization by approving the corporation’s annual operating plan and guide its long-term strategy. Moreover, the board monitors the organization’s risk management practices, along with compliance with applicable law and best practices, sets standards for corporate social responsibility, and supervises relations with regulators and the corporation’s various constituencies by engaging directly in director-level dialogue with shareholders. Directors enjoy substantial protection against personal liability for failures of board oversight, unless directors have purposely failed to implement any reporting system or controls or, having implemented such a system, deliberately refused to

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ASIC v Westpac 02 [2018] FCA 751. Aronson v. Lewis, 473 A.2d 805, 812 (Del. 1984). In re Dollar Thrifty S’holder Litigation (Del. Ch. 8 September 2010).

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monitor the system or ignored any red flags that it raised.82 The board of directors has to make certain that the corporation has a healthy and balanced approach toward risk due to the fact that there is danger in excessive risk aversion, just as there is danger in excessive risk taking and so it should set standards for corporate risk management. Furthermore, the board periodically has to review the value of the corporation’s risk management reporting functions and repair any deficiencies that it uncovers. In fact, in the United States, recent cybersecurity-related intrusions have brought heightened attention and scrutiny to questions of risk oversight and effective risk mitigation practices and so corporations have a dedicated board-level risk management committee, but most boards situate the risk management function at the audit committee, in reply to a listing rule of the NYSE that obliges the audit committee to discuss risk assessment and risk management policies. Will AI bring more direct shareholder influence? It has to be taken into account that enhanced transparency is not limited to accounting data but extends to transparency of ownership which means that DLT-induced transparency substitutes mandatory disclosure of beneficial ownership and so by preventing empty voting augments the speed, enhances the accuracy, and lessens the costs of shareholder decision-making, which sequentially diminishes shareholder apathy, leading to higher shareholder participation. Still, blockchain permits for a state-of-the-art decentralized form of shareholder meeting with no need for a centralized meeting location motivating shareholders to participate more directly in corporate governance and to call for votes on a wider range of topics and with greater frequency than is presently the case. In other words, AI brings forward a new equilibrium of the division of authorities between the shareholders and the board of directors causing shareholders’ indirect control over managerial behavior, diminishing the necessary for the board’s monitoring on behalf of shareholders.83 Will machines replace human (in) boards? It has to be taken into consideration that board functions are becoming more challenging for humans; and, AI solutions accomplish board functions better than humans which means that corporations are depending more and more on technology, and, in an environment ever more portrayed by uncertainty and continuous disequilibrium, people are less fit to serve as board members than machines. Also, in a fully IT-dominated environment, people are less willing to accept the amplified risks associated with a board seat and so in fact people are incapable of reviewing and overseeing self-learning algorithms, yet, as board members, their status will be on the line if such algorithms prove to be faulty. In other words, where humans become either incapable or unwilling to serve as board members, technology will replace them and so AI advances a board’s capacity to supervise agents and process information, eventually resulting in the demise of the

82

In re Caremark International Inc Derivative Litigation, 698 A.2d 959, 971 (Del. Ch. 1996). Mark Fenwick & Erik P.M. Vermeulen, Technology and Corporate Governance. Blockchain, Crypto, and Artificial Intelligence 5, Tilburg University Working Paper (Oct. 2018) (firms find themselves under new “conditions of radical cognitive and normative uncertainty”). 83

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monitoring board. It could be said that AI algorithms will take better governance decisions than individuals owing to their superior capacity to process information, freedom from biases, and lack of side interests and so the monitoring board has got the choice of algorithms84 which means that a greater occurrence of “digital technology people” in management and boards is expected. Moreover, it seems that technology will release boards from their monitoring responsibilities, permitting them to focus on strategic advice instead which means that as board composition will be altered, more business and fewer accounting and monitoring experts will be required. In line, Luca Enriques and Dirk Zetzsche85 argue that “As long as human beings (with their preferences and biases) wield significant influence over a firm, tools of this kind will remain necessary. Once humans no longer control corporations, they will indeed become obsolete. But by then humans will likely have more pressing issues to worry about than corporate governance.” It is worth noting that investors have long been annoyed with governance arrangements embraced by firms undertaking initial public offerings (“IPOs”), such as dual-class voting structures due to the fact that conventional sources of corporate governance rules, such as the Securities and Exchange Commission, state law, and exchange listing rules, do not restrict these arrangements and so investors have turned to a new source of governance rules: index providers.86 Moreover, it has to be taken into consideration that there has been a swing from active management to index management and mutual funds are the largest investors in US companies, and index funds managed by the “Big Three” investment managers, BlackRock, Vanguard, and State Street Global Advisors (“SSGA”) are the largest mutual funds managers and are expanding quickly.87 In other words, index investors make their investments in relation to an index: a benchmark portfolio listing securities and their weightings in the portfolio and so as soon as a firm with a disfavored governance structure is encompassed in an index, index investors are principally compelled to invest in the firm. S. Hirst & K. Kastiel88 show that “efforts to portray index providers as the new sheriffs of the U.S. capital markets are overstated. Index providers face complex and conflicting interests, which make them reluctant regulators, at best. . .We conclude that the efficacy of index exclusions in preventing disfavored arrangements such as dual-class structures is likely to be limited, but not zero.”

Mark Fenwick, Joseph A. McCahery & Erik P.M. Vermeulen, The End of “Corporate” Governance: Hello “Platform” Governance, 20 EUR. BUS. ORG. L. REV. 171, 191–197 (2019). 85 Luca Enriques Dirk Zetzsche, Corporate Technologies and the Tech Nirvana Fallacy, ECGI Working Paper Series in Law Working Paper N○ 457/2019 July 2019 https://ssrn.com/ abstract¼3392321 P 59. 86 Snap Inc., Prospectus (Form 424B4) (Mar. 3, 2017). Portia Crowe, Snap Is Going Public at a $24 Billion Valuation, BUS. INSIDER (Mar. 1, 2017), https://www.businessinsider.com/snapchat-ipoprice-2017-3. 87 Lucian Bebchuk & Scott Hirst, The Specter of the Giant Three, 99 B.U. L. REV. 721 (2019). 88 Scott Hirst & Kobi Kastiel, Corporate Governance By Index Exclusion, Boston University School of Law & Economics Series Paper No. 19-12 p1. 84

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Corporate Governance Externalities

It has to be taken into account that corporate governance externalities arise for the reason that companies interact with each other through numerous types of relationships such as the competition for managerial talents and so when a company’s competitors in the managerial labor market embrace a low level of governance by permitting their managers to extract large private benefits, the outside options of the company’s managers become more valuable, which in turn forces the company to choose a low level of governance to keep its managers which means that the selected level of governance in the economy can be inadequately low. Jie He et al.89 argue that “cross-ownership incentivizes institutional investors to play a more active monitoring role, suggesting that institutional cross-ownership serves as a marketbased mechanism to alleviate the inefficiency induced by governance externalities.” It is argued that institutional shareholders with larger ownership stakes in peer corporations vote against management on shareholder-sponsored governance proposals.90 Thus, given that shareholder-sponsored governance proposals, which management almost always opposes, are intended to cut managerial rents and improve shareholder value, cross ownership encourages institutions to play a valuable monitoring role. It could be said that the governance effects of cross-ownership are stronger for companies whose managers face more outside opportunities.91 In fact, managerial labor market competition is a vital economic force that gives rise to corporate governance externalities, which sequentially stipulate institutional cross-owners stronger incentives to internalize externalities and improve governance.

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The Governance Features of Venture Capital

Corporate law struggles in adapting general principles to fit the distinct characteristics of startups, and courts apply traditional contract parameters to the preferred stock that venture capitalists hold not as public company debt, but rather as a stake in a distinctive system of shared equity and governance. Due to market capitalization, the largest companies such as Apple, Alphabet, Microsoft, Amazon, and Facebook began as venture-backed startups and so they have been grown to momentous size with ownership shared between founders,

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Jie (Jack) He, Jiekun Huang, Shan Zhao, Internalizing Governance Externalities: The Role of Institutional Crossownership, the 2017 Western Finance Association meetings P 1. 90 Acharya, V., Volpin, P.F., 2010. Corporate governance externalities. Review of Finance 14, 1–33. 91 Dicks, D.L., 2012. Executive compensation and the role for corporate governance regulation. Review of Financial Studies 25, 1971–2004. Parrino, R., 1997. CEO turnover and outside succession: a cross-sectional analysis. Journal of Financial Economics 46, 165–197.

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investors, executives, and employees.92 Moreover, startups have reached private valuations described as $1 billion and many of these corporations face critical inflection points in their life cycles.93 Furthermore, other startups are following on their heels (Airbnb, Uber, Pinterest, Palantir, and SpaceX) and global economy and society are increasingly conquered by firms that start and function with a venturecapital style of ownership and governance. It is referred that the influx of capital to private firms tripled from $26.5 billion to $75.3 billion between 2013 and 2015.94 Moreover, the list of unicorns rose to over 300 private technology firms.95 Thus, it seems that the intensity of economic value in private firms poses somewhat of an encounter for corporate governance and so governance becomes more critical96 which means that the separation of ownership and control in corporations with dispersed share ownership is a central governance matters altering agency costs.97 It seems that corporation suffers from a conflict of interest between its managers and dispersed shareholders but the closely held corporation plagued by intershareholder conflict.98 It is worth noting that enhanced disclosure prerequisites will lessen the risks of unicorns without restraining their innovation, but deregulatory reforms have destabilized the principal mechanisms that imposed discipline on startup company founders.99 It has to be taken into account that syndicated financing of VCs restrains shareholder–manager agency costs giving 92 Venture Capital Ass’n, 2017 Nat’l Venture Capital Ass’n Y.B. 9 https://nvca.org/blog/nvca2017-yearbook-go-resource-venture-ecosystem/. Henry Hansmann, The Ownership Of Enterprise 40-44 (1996) (observing the “nearly complete absence of large firms in which ownership is shared among two or more different types of patrons, such as customers and suppliers or investors and workers” and theorizing the high cost of collective decision-making that would result from having different types of owners). 93 Alfred Lee, Delayed IPOs Undercut Startup Employee Options, The Information (July 13, 2018), https://www.theinformation.com/articles/delayed-ipos-undercut-startup-employee-options (noting 52 unicorns hit the 10-year mark in 2018 and more will follow in 2019). 94 Begum Erdogan et al., Grow Fast or Die Slow: Why Unicorns Are Staying Private, MCKINSEY (May 2016), https://www.mckinsey.com/industries/high-tech/our-insights/grow-fast-or-die-slowwhy-unicorns-arestaying-private. 95 Aileen Lee, Welcome to the Unicorn Club: Learning from Billion-Dollar Startups, TECHCRUNCH (Nov. 2, 2013), https://techcrunch.com/2013/11/02/welcome-to-theunicorn-club/ ; The Global Unicorn Club, CB INSIGHTS, https://www.cbinsights.com/research-unicorncompanies. 96 Robert P. Bartlett & Eric Talley, Law and Corporate Governance, in The Handbook Of The Economics Of Corporate Governance 8 (Hermalin & Weisbach eds., forthcoming), https://papers. ssrn.com/sol3/papers.cfm?abstract_id¼3009451. 97 Zohar Goshen & Richard Squire, Principal Costs: A New Theory for Corporate Law and Governance, 117 Colum. L. Rev. 767, 769 (2017). 98 Lucian A. Bebchuk & Assaf Hamdani, Independent Directors and Controlling Shareholders, 165 U. PA. L. REV. 1271 (2017). 99 Jennifer S. Fan, Regulating Unicorns: Disclosure and the New Private Economy, 57 B.C. L. REV. 583, 583 (2016). Renee M. Jones, The Unicorn Governance Trap, 166 U. PA. L. REV. ONLINE 165, 169 (2017).

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rise to a new horizontal conflict among preferred shareholders in startups,100 but startups have unique governance qualities and do not present the same agency problems and investment risks as all other corporations. Shareholders have standardized interests with regard to most corporate decisions by wanting to maximize the net present value of future distributions and so ultimate control over the corporation rests with the shareholders which means that other corporate constituencies, such as creditors, employees, suppliers, and customers, have their interests protected by contractual and regulatory means rather than through participation in corporate governance. It has to be taken into consideration that participants in startups often fill overlapping and shifting roles and so a venture capital (VC) corporation is a shareholder holding a designated seat on the board which means that participants have a dual status as both principal in one context and agent in another. Moreover, startup shareholders are heterogeneous and so startups typically issue common stock to founders and raise money from investors by issuing rounds of convertible preferred stock with varying terms and layered contractual rights generating noteworthy divergences in preferences among shareholders. Additionally, employees make crucial investments of human capital and hold common equity or options.101 To that extent, the interests of founders and executives associate with those of employees, but, in some circumstances, they deviate owing to differences in control, impending deal payouts, and post-exit opportunities which means that conflicts rise not only between preferred shareholders, and between preferred and common shareholders, but also between common shareholders. In line, in startups divergence between common shareholders classically takes place between the management and employees and so governance disputes within public firms turn to be “horizontal” disputes between shareholders such as activists versus long-term investors. It is obvious the distinctiveness of startups and governance tensions augments as the startup business progresses and the complexity of its capital structure grows. On the other hand, public firms and other closely held corporations, which do not present predictable or linear patterns of governance modification, and venture-backed startups face increasing prospective conflicts. While startups increase in governance complexity as they continue to operate, startups are often unprofitable for long periods while they develop innovative products or services, they usually raise outside investment and continue to do so to fuel growth which means that each stage of financing allocates investors with different terms and interests into the capital structure, adding to impending governance conflicts. Moreover, employees are hired on an ongoing and increasing basis and so as a startup firm matures, it expands the participants with varied interests and claims influencing its governance organization.

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Robert P. Bartlett, III, Venture Capital, Agency Costs, and the False Dichotomy of the Corporation, 54 UCLA L. REV. 37, 37 (2006). 101 Abraham J.B. Cable, Fool’s Gold, Equity Compensation & The Mature Startup, 11 VA. L. & BUS. REV. 613 (2017). Victor Fleischer, Taxing Founders’ Stock, 59 UCLA L. REV. 60 (2011).

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It could be said that corporate law should adapt in its application to startups in recognition of their distinctive features. Corporate law has progressed to cope with the classic shareholder-manager and controlling-minority shareholder conflicts arising in public and traditional closely held companies. In line, courts have applied these conventional frames of reference in cases involving startups, treating preferred shareholders as creditors with regard to their contractual preferences and portraying common shareholders as the residual claimants of the company. In re Trados,102 the court overlooks the need of heterogeneous shareholders to resolve complex governance issues by contract and a board with constituency directors that is re-negotiated over time and so the court overlooks the differing interests even among common shareholders. The corporation has to be seen as the beneficiary of the fiduciary duties, representing the firm value and the interests of all startup participants. There is a need of understanding startup governance by acknowledging that despite widespread reference to companies by the name of startup and recognition of their economic importance, the law does not generate such a category and so the law does little to formally define startups or mandate their governance.103 It is worth noting that Federal securities laws draw a line between “public” and “private” corporations and so a company becomes “public” by making a public offering of securities, listing securities on a national securities exchange, or by reaching a certain asset size and number of shareholders of record which means that once a company is public, it is subject to a number of governance rations stipulated by federal statutes and by the securities exchange on which the company’s stock is traded.104 For instance, a public corporation’s board must have a majority of independent directors and must give shareholders a nonbinding “say-on-pay” vote on executive compensation.105 It has to be taken into consideration that startups are commenced by entrepreneurs and backed by outside investment with the aim of advancing an innovative product or service, generating high growth, and exiting through a trade sale of the company or IPO.106 Hence, unlike traditional closely held corporations, startups are acquired 102

In re Trados Inc. S’holder Litig., 73 A.3d 17, 21. Simone M. Sepe, Intruders in the Boardroom: The Case of Constituency Directors, 91 Wash. U. L. Rev. 309, 315 (2013) (noting that venture-backed startups “are growing exponentially in importance in the U.S. economy”). 104 A.C. Pritchard, Revisiting “Truth in Securities” Revisited: Abolishing IPOs and Harnessing Private Markets in the Public Good, 36 SEATTLE U. L. REV. 999, 1000 (2013). Securities Exchange Act of 1934, 15 U.S.C. §§ 78l(a) & 78o(d); see also Donald C. Langevoort & Robert B. Thompson, “Publicness” in Contemporary Securities Regulation After the JOBS Act, 101 GEO. L.J. 337, 343 (2013); Usha Rodrigues, The Once and Future Irrelevancy of Section 12(g), 2015 U. ILL. L. REV. 1529. 105 Jill E. Fisch, Leave It To Delaware: Why Congress Should Stay Out of Corporate Governance, 37 DEL. J. CORP. L. 731, 752–54 (2013). 106 Nat’l Venture Capital Ass’n, 2018 Nat’l Venture Capital Ass’n Y.B. 29-31 (providing historic data on U.S. venture-backed exit activity, including 2017 data indicating 750 acquisitions versus 59 IPOs). 103

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by another corporation or transforming to a public corporation and so their existence is ephemeral like “a caterpillar in its chrysalis” and so, after an early stage, startups have more than a small handful of shareholders, with the numbers increasing as the firm raising capital from syndicates of investors confers restricted stock and stock options to employees which vest over the course of employment. Moreover, startups administer the number of their holders of record to keep private status, but the numbers are greater than the definition of closely held provided by the IRS.107 Like traditional closely held corporations, startups have stock that is not publicly traded, but startups are different in that outside demand for the high-growth asset class exists and startups enable partial liquidity events. It is worth mentioning here that Silicon Valley produces startups, but the context is not specific to any geographic location and so the governance matters emerge from the structures typically used by VCs, such as staged financing and preferred stock, and the common practice of granting stock options to employees, which together combine to form a structure that has modified participants and interests bound for growth and exit. It seems that startups epitomize part of the universe of private firms, subject to general principles of corporate law but free to privately order their affairs and so it is the nature of startup business and its life cycle that notably drive governance arrangements and conflicts. It is worth mentioning here that the innovative entrepreneur combines inventions, initiative, and investment to establish the startup and so entrepreneurial opportunities are novel in a strong sense implying a technological breakthrough backed by venture capital financing. Entrepreneurship encompasses new products or services, new ways of organizing, or new geographic markets.108 Early-stage startups are highly entrepreneurial and concentrated on innovation and technology and so startups are founded or co-founded by entrepreneurs who have an invention, technological idea, or discovery and a want to engage in commercial development.109 It could be said that firms that are started to engage in existing business models based on known products or services are replicative and so, by their character, startups pursue innovation which means something new that is presented to the marketplace. Most founders do not have sufficient funds to bring an innovative product or service to market and the business may not be profitable for long periods of time and so founders look to friends and family, and VCs to finance the early and most

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Elizabeth Pollman, Information Issues on Wall Street 2.0, 161 U. PA. L. REV. 179, 190–91 (2012). 108 Peter Thiel, Zero To One: Notes On Startups, Or How To Build The Future 8, 10 (2014) (“Properly understood, any new and better way of doing things is technology. . . New technology tends to come from new ventures—startups”); Joseph Schumpeter, Theory Of Economic Development 74–83 (1934) (Redvers Opie trans., Transaction Pub. 2012) (describing entrepreneurs as introducing new goods or methods of production or opening new markets or supply sources). 109 Mary Jo White, Keynote Address at the SEC-Rock Center on Corporate Governance Silicon Valley Initiative (Mar. 31, 2016), https://www.sec.gov/news/speech/chair-white-silicon-valleyinitiative-3-31-16.html (noting that nine out of ten startups fail and 70% of failed startups die within 20 months after their last financing, having raised an average of $11 million).

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tentative stages of the startup. For instance, nanotechnology startups face costs and risks linked with new drug development that are on a different scale and timeline than other innovative startups, and accordingly reveal specialized patterns of startup governance such as the prevalence of VC financing and joint ventures with large pharmaceutical companies.110 The firm’s board is established in earliest upon the raising of a round of financing being in a highly managerial phase aiding the firm with connections, resources, strategy, and expertise to succeed in launching its innovative product or service to the market.111 For a firm in a developing field, faced with a variety of strategic decisions and an inexperienced CEO, the board’s role as manager is a vital component of firm success demanding board members with developed industry expertise, business relationships with the firm, or even insiders.112 It is worth noting that after the early stage, startups are concentrated on refining product development to generate revenues and grow quickly and so startups need to be able to scale. Moreover, venture capitalists that finance startups are centered on a business model that depends on having a few “home runs” in the portfolio that account for much of the fund returns.113 As a startup advances to late stage, its effort has shifted to managing a more complex organization and finding an exit to accomplish liquidity for the participants holding equity stakes in the firm which means that the firm has successfully developed some innovative product or service and made customers and sales and so the character of the business has become more complex, possibly involving global operations, new opportunities, competition, and continued challenges in terms of cash flow and growth. As a result, founders that have not kept up with these needs may no longer occupy top executive positions and so they are replaced by a large investor and chairperson of the board.114

110 Paul Gompers & Josh Lerner, The Venture Capital Cycle 157 (2004) (“Entrepreneurs rarely have the capital to see their ideas to fruition and must rely on outside financiers.”). 111 Brad Feld & Mahendra Ramsinghani, Startup Boards: Getting The Most Out Of Your Board Of Directors 4 (2014). 112 Ranjay Gulati & Alicia DeSantola, Startups That Last, Harv. Bus. Rev. (March 2016), https:// hbr.org/2016/03/start-ups-that-last. Fred Wilson, Profits v. Growth, AVC (June 25, 2015), https:// avc.com/2015/06/profits-vs-growth/. 113 William Alden & David Gelles, In WhatsApp Deal, Sequoia Capital May Make 50 Times Its Money, N.Y. TIMES (Feb. 20, 2014), https://dealbook.nytimes.com/2014/02/20/in -whatsappdeal-sequoia-capital-maymake-50-times-its-money/. Brian J. Broughman & Jesse M. Fried, Do Founders Control Start-Up Firms That Go Public? (ECGI Working Paper No. 405, 2018), https:// papers.ssrn.com/sol3/papers.cfm?abstract_id¼3171237 (finding that in almost 60% of venturebacked firms that go public, the founder is no longer CEO at IPO). 114 Noam Wasserman, The Founder’s Dilemma: Anticipating And Avoiding The Pitfalls That Can Sink A Startup 206-07 (2012) (identifying the stages as startup, transitional, and mature, noting that “different functions within startups may go through them at different rates”); Max Marmer & Ertan Dogrultan, Startup Genome Report Extra on Premature Scaling, Mar. 2013, http://s3.amazonaws. com/startupcompass-public/StartupGenomeReport2_Why_Startups_Fail_v2.pdf (gathering data from 3200 startups and identifying six stages: “discovery, validation, efficiency, scale, sustain, and conservation”). Daniel F. Spulber, The Innovative Entrepreneur 2 (2014).

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It has to be taken into account that VC multinationals raise capital from passive limited partners, organized in funds and not only are VC companies sensitive to liquidity within the timing of a specific fund’s term, but their business model is also based on raising successive funds and so their capacity to produce returns influences their reputation and ongoing operations.115 In other words, VCs are the “entrepreneurs behind the entrepreneurs.”116 It is worth noting that a venture capitalist liquidates a return in private companies to make money.117 In light of capital requirements for continued growth, many startups next seek extra financing from venture capital investors and so VCs are professional investors who put other people’s money to work embracing pension funds, endowments, foundations, banks, insurance companies, and others seeking access to a high-growth alternative asset class. Strategic investors such as corporate venture capital offer an alternative source of financing.118 The VC, acting as general partner of the fund, makes and monitors the investments in a portfolio of startup firms, but funds have a fixed term and the VC makes money by receiving an annual management fee plus carried interest being a right to receive a percentage of the profits made from the investments in the portfolio of startup firms.119 Do all startup participants such as founders, executives, investors, and employees play a role in governance? It is worth noting that these participants typically all have a stake in the equity and have closely aligned objectives at the highest level. Moreover, they are all economically incentivized to increase the value of the firm by reaching a highly valued exit.120 Nevertheless, in a great variety of situations their interests diverge because of differences in types and classes of stock and options, liquidity time horizons, and prospective private benefits and incentives. Hence, the costs of these conflicts embrace value-reducing opportunistic behavior, inefficiencies stemming from different preferences for firm actions, bargaining and enforcement costs to diminish

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Philippe Aghion et al., Exit Options in Corporate Finance: Liquidity Versus Incentives, 8 REV. FIN. 327, 331 (2004) (discussing the VC cycle which requires liquidating the proceeds of investment). 116 Rochelle Kopp & Steven Ganz, Valley Speak 15 (2016) (quoting Keith Rabois from Khosla Ventures with original attribution to Sequoia Capital). 117 PitchBook & Nat’l Venture Capital Ass’n, Venture Monitor 1Q 2018, https://nvca.org/research/ venture-monitor/ (“As companies move along the venture lifecycle, exits at some point move to the forefront of discussion and business positioning.”). Constance E. Bagley & Craig E. Dauchy, The Entrepreneur’s Guide To Business Law 88-91 (4th Ed. 2012). Therese H. Maynard, Dana M. Warren, & Shannon Treviño, Business Planning: Financing The Start-Up And Venture Capital Financing 374–375 (3rd ed. 2018). 118 Josh Lerner, Corporate Venturing, Harv. Bus. Rev. (Oct. 2013), https://hbr.org/2013/10/ corporate-venturing. 119 Steven N. Kaplan & Per Strömberg, Financial Contracting Theory Meets the Real World: An Empirical Analysis of Venture Capital Contracts, 70 Rev. Econ. Studies 281 (2003). 120 Steven E. Bochner & Amy L. Simmerman, The Venture Capital Board Member’s Survival Guide: Handling Conflicts Effectively While Wearing Two Hats, 41 Del. J. Corp. L. 1, 2 (2016).

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misalignment, and possibly a higher cost of capital.121 In line, governance conflicts raise the cost of capital arising when the founders take outside investment. Thus, governance challenges are born when a firm becomes jointly owned and so if there is more than one founder, the prospective exists for conflict. The balance of power between founders and investors is one of the crucial tensions that runs through startups involving the board (Shareholders vs. Board), which is the key governing body and locus at which founders and investors determine control. Will shareholders need boards? It is argued that the days of information asymmetry between a corporation’s insiders and outsiders are numbered due to the fact that real-time accounting will replace traditional accounting and so corporations will voluntarily post their ordinary business transactions on a blockchain accessible to the public.122 Moreover, technology will ultimately lead to proprietary information being shared with investors and other market participants which means that full transparency escalates shareholder trust in the integrity of a corporation’s data, and renders costly audits by possibly corrupt professional companies worthless.123 In addition, superior transparency and post-trade efficiency diminishes transaction costs and increase liquidity in capital markets which means that improved transparency brings drop in agency costs arising in connection with key management and governance matters, such as the selection of directors and executives, accrued earnings management, related party transactions, and management compensation systems reducing the necessity for boards to focus on such issues.124 In fact, startup boards are negotiated and the board is formally constituted at the first round of venture capital financing, if not before, and its agreed-upon size and composition are stipulated in the financing term sheet and then preserved in a voting agreement or in the corporation’s certificate of incorporation. Moreover, VCs seek board seats as part of their investment accessing information, to observe against opportunistic behavior, for voice or control on vital decisions such as future financings or exit, and to enhance value to the firm. Furthermore, VCs are called “smart money” in reference to the value-adding services and so serving as a sounding board to the founders and team, facilitating to recruit management personnel, formulating 121 Oliver Williamson, The Economics of Governance, 95 Am. Econ. Rev. 1, 4 (2005) (“Maladaptation to disturbances is where the main costs of governance reside.”); Scott Kupor, Prenups for Co-Founders, Andreessen Horowitz (Oct. 16, 2015), https://a16z.com/2015/10/19/prenups-for-cofounders/. 122 David Yermack, Corporate Governance and Blockchains, 21 Rev. Fin. 1, 9 (2017). 123 OECD, Directorate For Financial And Enterprise Affairs – Corporate Governance Committee, Blockchain Technology And Corporate Governance – Technology, Markets, Regulation And Corporate Governance 24-25 (2018). 124 Isil Erel, Léa H. Stern, Chenhao Tan & Michael S. Weisbach, Selecting Directors Using Machine Learning, European Corporate Governance Institute (ECGI) – Finance Working Paper No. 605/2019 (2018) (describing an experiment with algorithms to make out-ofsample predictions of director performance, using shareholder approval rates as well as firm returns and profitability as proxies, testing the quality of these predictions, and concluding that “[m]achine learning holds promise for understanding the process by which governance structures are chosen, and has potential to help real-world firms improve their governance.”).

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business strategies, and offering contacts. Additionally, VCs serve as reputational intermediaries, lending credibility and legitimacy to startups, predominantly in their early stages for the reason that they take an equity stake implicating a long-term relationship with the entrepreneurs, they have a reason to bridge the information gap. Hence, serving on the board is one of the means by which VCs deliver this value and supervise their investment. It is worth noting that three basic types of startup boards exist: foundercontrolled, investor-controlled, and shared control which means that the first two are clear-cut in referring to situations in which one group outnumbers the other in delegated board seats or board votes and so the shared control is planned in numerous ways such as with an even split between founder and investor board seats, with a split board and one or more independent directors, or as contingent control with the tie-breaking seat filled by the preferred and common shareholders voting together as a single class. In other words, the board and voting control are the product of multi-party sequential negotiations which means that control adjusts over time and it is disconnected from ownership or from cash flow rights using contracts negotiating boards, contractually separating ownership and control, and using designated seats presents a contrast to public firms which lack negotiations, lack voting agreements, and lodge nominating power in the board itself.125 It is worth noting that board rights and voting rights are different from cash flow rights and from each other.126 Moreover, entrepreneurs appreciate corporate control for the reason that it permits them to pursue their vision in a way they see fit and so VC financings permit VCs to separately allocate cash flow rights, board rights, voting rights, liquidation rights, and other control rights.127 VC and Entrepreneur each have boardroom control in numbers of portfolio firms. In startups, the board is not only the site of value-adding managerial guidance, but also one of the key arenas in which conflicts 125

Margaret M. Blair, Boards of Directors as Mediating Hierarchs, 38 Seattle U. L. Rev. 297, 335 (2015) (discussing how a solution to the problem of “productive activity that requires complex, difficult to measure, and difficult to contract inputs” is “[t]he delegation of key decision rights to a ‘mediating hierarchy’”). 126 Alfred Lee, Inside Private Tech Voting Structures, The Information (Oct. 29, 2015), https:// www.theinformation.com/articles/inside-private-tech-votingstructures?utm_medium¼email& utm_source¼cio (finding that as of October 2015, nine out of ten of the highest valued private tech companies had supervoting structures and the one exception had a founder with extra voting rights on the board that gave the founder control); Alfred Lee, Where Supervoting Right Go to the Extreme, The Information (Mar. 22, 2016), https://www.theinformation.com/articles/wheresupervoting-rights-go-to-the-extreme; Rolfe Winkler & Maureen Farrell, In ‘Founder Friendly’ Era, Star Tech Entrepreneurs Grab Power, Huge Pay, Wall St. J. (May 28, 2018), https://www. wsj.com/articles/in-founder-friendly-era-star-tech-entrepreneurs-grab-power-hugepay1527539114 (“Last year, 67% of U.S. venture-backed tech companies that staged IPOs had supervoting shares for insiders, according to Dealogic, up from 13% in 2010 . . . The proportion rises as tech companies get larger: 72% of founders of U.S. tech startups valued over $1 billion that had IPOs over the past 24 months have supervoting shares. . .”). 127 Dorothy Shapiro Lund, Nonvoting Shares and Efficient Corporate Governance, https://papers. ssrn.com/sol3/papers.cfm?abstract_id¼3028173 (arguing that nonvoting stock can “make corporate governance more efficient.”).

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are resolved and investments are protected. It could be said that via contracts assign control rights to VCs independent of cash flows generating a separation of ownership and control that has significant consequences for the efficiency of entrepreneurial firms. In addition, VCs and founders disagree with regard to risk level, liquidity needs, and private benefits, which are often associated in critical board-level decisions on financings, strategic direction, and exit. Which is the relation between Board versus Founders or Executives in VCs? In fact, models of corporate governance consider the board and executives a single category of managerial agents, but then again startups encompass participants in overlapping roles with dual status which means that participants with managerial control are not merely agents of a monolithic body of principal-like shareholders. Hence, conflicts arise in startups between the board and the founders or executives that have substantial governance dimensions. Moreover, VC contracting diminishes agency costs and information asymmetry and, while board seats are a part of this design, mechanisms that do not depend on the formal structure of the board are also used being both contractual and structural.128 In addition, VCs commit small portions of capital sequentially rather than as a full upfront investment of the amount that the startup will demand and so VCs have a lever to set milestones for the managers which means diminishing agency costs and the option to periodically reconsider and decide whether to invest in another round of financing or “abandon” the investment and so dropping information asymmetry and the influence of uncertainty. Additionally, existing investors are a source for continued capital and introductions to other prospective investors, but many startups fail before getting to profitability and so staged financing has a disciplining consequence on founders, who fear running out of cash and having to shut down. Do conflicts occur between shareholders and the costs of collective decisionmaking? Taking into account that shareholders hold dissimilar kinds of equity interests with varied terms and preferences, they have conflicting interests and reasons to take actions damaging other shareholders or making unproductive decisions that fail to maximize aggregate welfare. To that extent, in startups, these costs reach great size as different contributors to the firm such as founders, employees, and investors hold different equity interests. Additionally, startups present interrelated vertical and horizontal issues, as the same participants appear in both types of issues, which underlines the heterogeneity of their welfares and the changing, overlapping character of their roles. In fact, down-round financings, recapitalizations, and sales of the firm are transactions in which the interests of the preferred and common shareholders diverge. Nonetheless, founders push for “early” acquisitions for the reason that they are undiversified and the payout is personally meaningful even if it does not maximize the expected value of the startup. Corporate law offers a mechanism that responds to the problem of opportunism within the firm: fiduciary duties. Directors and officers owe fiduciary duties of care

128

In re Nine Sys. Corp. S’holder Litig., Consol C.A. No. 3940-VCN, 2014 WL 4383127, at *30 (Del. Ch. Sept. 4, 2014). Carsanaro v. Bloodhound Techs., 65 A.3d 618, 665 (Del. Ch. 2013).

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and loyalty to serve the best interests of the corporation and its shareholders which means that fiduciary duties are understood as filling in the gaps of incomplete shareholder contracts.129 E. Pollman130 argues that “as large numbers of startups increasingly pursue growth and transformational technology while remaining private, they have come to represent an essential part of the economy and have a significant impact on employees, communities, and other stakeholders. It is time that far greater attention be devoted to understanding their internal dynamics and the recurring problems they face”. However, Lawrence J. Trautman131 indicates that “By early 2019 it has become apparent that a number of influential and successful high growth social media platforms have been used by nation states for propaganda purposes”. It is worth noting that the requirement for corporate governance based on the understanding that when separation exists between the ownership of a corporation and its management, self-interested executives have the chance to take actions that benefit themselves, with shareholders and stakeholders bearing the cost of these behaviors which is referred to as the agency problem, with the costs resulting from this problem defined as agency costs. Thus, executives make investment, financing, and functioning choices that better themselves at the expense of other parties linked to the corporation and so in order to diminish agency costs, some type of control or monitoring system is put in place in the corporation checking and balancing named as corporate governance.132 How it comes out the board’s authority? In fact, legal authority for firms is shaped by state-granted charters, their governance dictated by state law, with the obligation of managing the activities of the firm delegated to corporate directors. Hence, the business judgment rule is that in making a business decision the directors of a corporation act on an informed basis, in good faith and in the honest belief that the

129 Abraham J.B. Cable, Opportunity-Cost Conflicts in Corporate Law, 66 Case W. Res. L. Rev. 51, 53 (2015). Equity-Linked Investors, L.P. Adams, 705 A.2d 1040 (Del. Ch. 1997); Orban v. Field, 1997 WL 153831 (Del. Ch. 1997); In re Trados, 73 A.3d at 33-34; In re Nine Systems, 2014 WL 4383127, at *30. Mills Acq. Co. v. Macmillan, Inc., 559 A.2d 1261, 1280 (Del. 1989) (“Directors owe fiduciary duties of care and loyalty to the corporation and its shareholders.”); Frederick Hsu Living Trust v. ODN Holding Corp., 2017 WL 1437308, at *17 (Del. Ch. 2017) (“In the standard Delaware formulation, fiduciary duties run not only to the corporation, but rather ‘to the corporation and its shareholders’”) In re Rural Metro Corp., 88 A.3d 54, 80 (Del. Ch. 2014). Frank H. Easterbrook & Daniel R. Fischel, The Corporate Contract, 89 Colum. L. Rev. 1416, 1432–34 (1989); Oliver Hart, An Economist’s View of Fiduciary Duty, 43 U. Toronto L.J. 299 (1993). 130 Elizabeth Pollman, Startup Governance, https://ssrn.com/abstract¼3352203 p. 57. 131 Lawrence J. Trautman, Governance Of The Facebook Privacy Crisis, at: https://ssrn.com/ abstract¼3363002. 132 David Larcker & Brian Tayan, Corporate Governance Matters 4 (FT Press, 2011). Lawrence J. Trautman, The Board’s Responsibility for Crisis Governance, 13 Hastings Bus. L.J. 275 (2017), http://ssrn.com/abstract¼2623219; Lawrence J. Trautman, Who Sits on Texas Corporate Boards? Texas Corporate Directors: Who They Are and What They Do, 16 Hous. Bus. & Tax L.J. 44 (2016), http://ssrn.com/abstract¼2493569.

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action taken is in the best interests of the firm which means that directors owe their firm and shareholders fiduciary duties of care and loyalty.133 In other words, the Board has to act quickly and efficiently to mitigate the loss to the firm and so corporate governance is built upon the duty of care, duty of loyalty, and duty of good faith.134 In fact, the duty of loyalty stands for the suggestion that directors have to act in good faith and must not permit their personal interests to succeed over the welfares of the firm and so a prudent, diligent approach to the effectual discharge of every director’s individual duties and responsibilities is needed to discharge the legal duty of care. Moreover, the duty of due care evolves in both the discrete decisionmaking context and in the oversight and monitoring areas and so in the decisionmaking background engaging either directors making a routine business decision or responding to a high-stakes unsolicited bid for corporate control, the duty of care examination concentrates on a board’s decision-making course which means that directors in that setting are under an obligation to obtain and act with due care on all material information realistically obtainable.135 What the duty of good faith embraces? It could be said that a director in order to have the protection of the business judgment rule against a claim for breach of fiduciary duty must prove that he acted in “good faith” by revealing that he has applied judicial state corporate law, federal and state legislation, shareholder activism, and corporate governance rationales.136

133 Eric J. Pan, Rethinking the Board’s Duty to Monitor: A Critical Assessment of the Delaware Doctrine, 38 FLA. ST. U. L. REV. (2011), http://ssrn.com/abstract¼1593332; Bernard S. Black, Brian R. Cheffins & Michael Klausner, Outside Director Liability, 58 Stan. L. Rev. 1055 (2006), http://ssrn.com/abstract¼894921. 134 Christopher M. Bruner, The Fiduciary Enterprise of Corporate Law, 74 Wash. & Lee L. Rev. (2017), https://ssrn.com/abstract¼2970654; Deborah DeMott, Corporate Officers as Agents, 74 Wash. & Lee L. Rev. 847 (2017), https://ssrn.com/abstract¼2909864; Asaf Eckstein & Gideon Parchomovsky, Toward a Horizontal Fiduciary Duty in Corporate Law, 104 Cornell L. Rev. 101 (2019), https://ssrn.com/abstract¼3134607. 135 Lyman P.Q. Johnson and Mark A. Sides, Corporate Governance and the Sarbanes-Oxley Act: The Sarbanes-Oxley Act and Fiduciary Duties, 30 WM. Mitchell L. Rev. 1149, 1197 (2004). Citron v. Fairchild Camera & Instrument Corp., 569 A.2d 53, 66 (Del. 1989); Paramount Communications, Inc. v. QVC Network, Inc. 637 A.2d 34, 48 (Del. 1994), Brehm v. Eisner, 746 A.2d 244, 264 (Del. 2000) (“Due care in the decision-making context is process due care only.”). Christopher M. Bruner, Is the Corporate Director’s Duty of Care a ‘Fiduciary’ Duty? Does It Matter?, 48 Wake Forest L. Rev. 1027 (2013), http://ssrn.com/abstract¼2358616. 136 Stockbridge v. Gemini Air Cargo, Inc., 611 S.E. 2d at 606 (quoting Malone v. Brincat, 722 A. 2d 5, 10) (Del. 1998) (Stockbridge v. Gemini Air Cargo, Inc., holds that the board of directors of a Delaware corporation is charged with the legal responsibility to manage its business for the benefit of the corporation and its shareholders with “due care, good faith, and loyalty.”).

3.8 Characteristics of Blockchain Governance

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Characteristics of Blockchain Governance

Concerning blockchain technology, Benkler137 argues that “can enable people to function together with the persistence and stability of an organization, but without the hierarchy”. It is characteristic that the public blockchain world is fast-moving, with new blockchain systems repetitively being produced, and existing ones working to fix governance issues. Moreover, a number of blockchain systems have now openly incorporated governance into their blueprints from the outset and so some of these new systems may configure the power of software developers differently than Bitcoin or Ethereum. Thus, Tezos, and Dfinityare paradigms of public blockchains using or planning to use alternative governance procedures, with variations in the powers of validators in the network and so those working on public blockchain networks have diagnosed the important role governance plays in a system’s triumph.138 Incentive structures intended to result in transaction processors providing security for a blockchain called “crypto economics” is being developed and so these “consensus mechanisms” and rules for coming to agreement for transaction processors play an important role in the governance of public blockchain systems.139 Furthermore, a corporate governance framework onto blockchains or a business trust is a suitable form of legal entity for blockchain developers and other players in the system to take advantage of limited liability without having to formally generate a corporation or limited liability corporation.140 In other words, software developers play a certain role in the governance process of public blockchains by achieving trust and power in public blockchain systems.141

137

Don Tapscott & Alex Tapscott, Blockchain Revolution 123 (2016) at 107 (citing interview with Yochai Benkler). 138 Tezoswebsite, EOS website, Decred website, Dfinity website, Fred Ehrsam, ‘Blockchain Governance: Programming Our Future’ Medium (17 November 2017) Vlad Zamfir, ‘Against on-chain governance’Medium (1 December 2017) . 139 Josh Stark, ‘Making Sense of Cryptoeconomics’ Medium (28 August 2017) see . 140 Hacker, Philipp, Corporate Governance for Complex Cryptocurrencies? A Framework for Stability and Decision Making in Blockchain-Based Organizations (November 22, 2017). in: Regulating Blockchain. Techno-Social and Legal Challenges, edited by Philipp Hacker, Ioannis Lianos, Georgios Dimitropoulos, and Stefan Eich, Oxford University Press, 2019, pp. 140–166. Available at SSRN: https://ssrn.com/abstract¼2998830 Carla Reyes, ‘If Rockefeller Were a Coder’ Vol. 87 2019 The George Washington Law Review 373. 141 Tim Swanson, ‘Who are the Administrators of Blockchains?’(Of Numbers Blog19 October 2017) ; CiaranMurray, ‘Are Public BlockchainSystems Unlicensed Money Services Businesses In Disguise?’ (Rules of the Game Blog12 October 2017) .

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Correspondingly, Don and Alex Tapscott142 have explained the advantages of entities that are “powered by blockchain technology and cryptocurrencies, where autonomous agents can self-aggregate into radically new models of the enterprise.” In other words, such an entity is an establishment without executives, only shareholders, money, and software which means that Code and algorithms substitute a level of representatives such as the executive board with shareholders exerting control over that code and so code cannot control an enterprise without the consent of humans. Furthermore, this enterprise will have shareholders via a “crowdfunding” campaign analogous to the one under the conventional enterprise which means that the shareholders stipulate a mission’s statement to exploit profit lawfully while treating all stakeholders with integrity. In addition, shareholders will govern the entity but, where humans make all decisions, in the ultimate distributed organization much of the day-to-day decision-making will be programmed into clever code. Hence, these entities will run with minimal or no conventional management construction, as everything and everyone operates as stated by particular canons and procedures coded in smart contracts. Will the concept of corporate management survive at all after the introduction of advanced AI? It could be said that the contest to the existing conception of management is brought about by the notion of new business entities that professedly operate without leadership in the old-style connotation. In fact, Distributed Autonomous Enterprises (DAE) or Distributed Autonomous Organisations (DAO) are appraised in the environment of blockchain and AI technologies. Moreover, Blockchain can offer the straightforward architecture, with self-executing smart contracts, information and transparency, security, and other qualities that accelerate coordination between different groups making centralized management obsolete.143 To that extent, a decentralized organization activates under the same basic notions of a corporation but has a decentralized management structure and so disregarding the board of directors. An example of DAE is ConsenSys,144 a software development firm concentrating mainly in applications for Ethereum, a blockchain-based platform, and its “decentralized” organizational approach has a collaborative rather than hierarchical and inspired by the principles of “holacracy” which means that this approach embrace “distributed, not delegated authority;” engaging a plan that has been developed and agreed on by all employees or members and so the active roles do not adhere to conventional job descriptions. Moreover, the project-based work is

142

Don Tapscott & Alex Tapscott, Blockchain Revolution 123 (2016). Laila Metjahic, Deconstructing the DAO: The Need for Legal Recognition and the Application of Securities Laws to Decentralized Organizations, 39 Cardozo L. Rev. 1533, 1537–46 (2018). 144 ConsenSys website, https://consensys.net/solutions. Sean Tahery, The Decentralized Org Structure, Consensys College Consortium (Sept. 4, 2018), https://medium.com/@consensys_uni/thedecentralizedorg-structure-376bee0544cf; Joao Medeiros, Stephen Hawking: ‘I fear AI may replace humans altogether’, WIRED (Nov. 28, 2017), https://www.wired.co.uk/article/stephen-hawkinginterview-alien-lifeclimate-change-donald-trump. 143

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prearranged around smaller teams that link and collaborate with each other involving flexible forms of compensation. In addition, ConsenSys key functioning role is restricted to that of an advisory proposing directions and priorities and so occasionally there is a need to propose a particular thing to get done by hiring externals or incentivize internals to do it. Furthermore, another example is Slock.it that has suffered from fatal flaws and eventually collapsed145 due to manipulation of a weakness in the entity’s coding by a user. It is worth noting that a DAE can execute any governance structure that its members see fit and not adopting Slock.it’s construction because mechanical AI entities involve their risks and shortcomings. Certainly, leaderless or self-managed collectives are unlikely to succeed in the future, at least on a broad scale and aside from certain zones where ultra-flat hierarchies are valuable such as software and other cyberspace-based work and projects which means that in view of the superior competences of machines, companies will gain from AI exercising centralized control and so members will remain almost passive, their role will be diminished to providers of capital and recipients of dividend streams. Thus, it has to be taken into consideration that centralized, hierarchical organization embrace flaws needing further improvement which means that technology has to radically diminish the confines that make self-governance of business entities unfeasible today and so DAE will become viable as prevalent alternative organizational models or even replace centrally managed entities. In other words, at least for the near future, technology will transform and advance corporate management instead of leading to its end. It is worth noting that because of their prospective to cut costs and shorten the time needed for executing and settling securities trades, blockchains present the likelihood of noteworthy improvements in liquidity, whether they are used as the key platform for share registration and exchange, or whether they are presented by stock markets in a more limited way to streamline the post-trade clearing and settlement process.146 While stock evaluation is mainly made up of financial variables and ratios, tokens are fully digital entities that exist on a network plane and so there is need of examining not just financial variables but technical as well, especially when analyzing smart contracts.147 On the one hand, public blockchain protocols face a serious governance crisis. On the other hand, thus far, blockchain protocols have adhered to the path of early Internet governance. Hence, if the architects of blockchain protocols are not cautious, they may suffer a similar fate by escalating governmental control, greater centralization, and decreasing privacy. As blockchain architects begin to bear in mind better governance structures, there is a legal movement to compel a fiduciary 145

Usha Rodrigues, Law and the Blockchain, 104 Iowa L. Rev. 679, 697–706 (2019). Christoph Jentzsch, The History of the DAO and Lessons Learned (Aug. 24, 2016), https://blog.slock.it/thehistory-of-the-dao-and-lessons-learned-d06740f8cfa5. 146 D. Yermack, “Corporate Governance and Blockchains”, Oxford Review of Finance, Volume 21, March 2017. 147 K. Bheemaiah and A. Collomb, “Cryptoasset valuation: Identifying the variables of analysis”, Louis Bachelier Institute, Working Report v1.0, 19 October 2018.

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framework upon open-source software developers and so the effects for open-source software development could be dire. In other words, if indiscriminately imposed upon blockchain communities without respect of modifications among communities or the reality of how such communities function, the movement will nullify the technology before it ever matures. Likewise, a contractually based governance system offers blockchain protocols an opening to adopt governance rules that echo the exceptional aims and culture of the protocol and its community while conciliating the regulator’s demand for a legally recognizable and responsible hierarchy. There is a need for adjusting governing blockchain protocols through a corporate law model and so animating new corporate governance structures in more traditional enterprises. It is worth noting that software developers around the globe have produced some of the most imperative technological advances in computing that society enjoys today. Even though many commercial entities, including Facebook, gain from the advances made by open-source software developers, many of the contributors to open-source projects do not and so many open-source software developers subsidize to a project for a variety of other, less tangible, motives, including career advancement, or to merely solve a problem that makes their life as a user of the software easier.148 Open-source software refers to software that is available without an economic cost, while free software is used to describe software imbued with certain ideals.149 Blockchain protocols being master node protocols generate a governance structure enabling efficient decision-making, intuitively copy a partnership structure even analogizing them to corporations. In fact, some protocols, smart contracts, and Decentralized Autonomous Organizations (“DAOs”) could be structured as business trusts so as to receive corporate treatment without actually incorporating.150 Likewise, other protocol architects are exploring ways to formally incorporate their projects and so irrespective of whether protocol architects shape a specific protocol as a legally recognized business entity, or the comparison is more theoretical, the entire series of scenarios points to the broader prospective of the corporate governance experience affecting and modeling blockchain protocol governance.151

148 Siva Vaidhyanathan, Open Source as Culture—Culture as Open Source, in Open Source Annual 2005 341, 343 (Clemens Brandt Ed. 2005) (tracing the beginning of the open source software movement to Richard Stallman’s work in the 1970s); (“While Linux and the GNU (Free Software) project have garnered the most attention in accounts of Open Source development, the protocols and programs that enable and empower the e-mail, the World Wide Web, IRC, and just about every other activity on the Internet all emerged from community-based project teams, often ad-hoc and amateur.”). 149 George Dafermos, Governance Structures Of Free/Open Source Software Development 187 (2012), available at https://georgedafermos.github.io/book.pdf. 150 Lynn LoPucki, Algorithmic Entities, 95 Wash. U. L. Rev. 887 (2018). 151 Xander Landen, Vermont Bullish on Blockchain as New Law Takes Effect, VT DIGGER (Aug. 28, 2018), https://vtdigger.org/2018/08/28/vermont-bullish-blockchain-new-law-takes-effect/ (describing Vermont’s enactment of a law enabling “blockchain-based limited liability companies”

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Without a doubt, many open-source projects, embracing some blockchain ecosystems, depend on a kind of formal and informal governance mechanisms involving both formal incorporation and contractual governance. It is worth noting that public blockchain protocol governance seems to be in crisis by the way of the individuals leading development of public blockchain protocols generated governance structures without viewing them as such. Consequently, the broader blockchain technical community is exploring theories of blockchain governance and so, up to the present time, blockchain protocol governance pursues the same path as cyberspace governance which means dominance by key individuals followed by the establishment of quasi-governance organizations with overlapping missions, politicization, and varying degrees of legitimacy.152 The governance problems experienced by the Bitcoin and Ethereum communities stem from conflicts of interest among governance participants. Irrespective of the robustness and technical viability of the bitcoin protocol, this governance crisis has underlined the fragility of the current decision-making mechanisms within the Bitcoin project. Moreover, the participants in a blockchain protocol ecosystem consist of the core developers, other open-source code contributors, full node operators, cryptocurrency or token-holders, protocol founders, and foundations.153 The open-source developers design, generate, and submit protocol updates, fixes, and modifications to the community for consideration and so developers of many blockchain protocols undertake their work for free, but full node operators have the capacity to not only validate transactions, but also to enact updates and proposals from the core developers. Furthermore, not like the developers, full node operators are encouraged by economic reward which is the income gained from their status as full node operators depending upon both the activity of validating transactions and receiving transaction fees from users which means that full node operators have selfinterested reasons for making a specific decision on a core developer proposal. Also, the blockchain and its security systems generate trust between principals and agents in the integrity of their contractual relationship and so such guarantees make certain no participant evades the rules embedded in blockchain code. Furthermore, blockchain guarantees embrace contract execution between principal and agent only if and when all contract issues are fulfilled by both parties and confirmed by a majority of miners/nodes in the system. Consequently, in the blockchain

and several companies taking advantage of the law). Corda Network Foundation, Governance Guidelines, https://corda.network/governance/governanceguidelines.html#. 152 Gareth Jenkinson, Ethereum Classic 51% Attack—The Reality of Proof of Work, COINTELEGRAPH (Jan. 10, 2019) (noting that members of the ETC community believed “the attack was ‘most likely selfish mining’ noting that they had not detected any double spends at the time”). 153 Panos Mourdoukoutas, Could Bitcoin Replace Credit Cards?, Forbes (Aug. 26, 2018), https:// www.forbes.com/sites/panosmourdoukoutas/2018/08/26/bitcoin-could-replace-credit-cards/ #6cc608bd1e4e. Alyssa Hertig, Why Are Miners Involved in Bitcoin Code Changes Anyway?, COINDESK (July 28, 2017), https://www.coindesk.com/miners-involved-bitcoin-code-changesanyway/.

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infrastructure, there is no need for the principal to institute oversight and monitoring with the linked agency costs owing to the governance guarantees embedded in code and so blockchain addresses the inherent agency problems in modern finance and corporate governance methodically. It is characteristic that blockchain assures the integrity of principal agent relationships by removing fraudulent transactions and so paralleled with existing methods of confirming and validating transactions by third-party intermediaries which means that blockchain’s security rations make blockchain validation technologies clearer. Thus, while blockchain’s use of digital signatures assists establishing the identity and authenticity of the parties participating in the transaction, it is the entirely decentralized network connectivity via cyberspace that permits the most protection against fraud. To that extent, network connectivity permits multiple copies of the blockchain to be available to all participants across the distributed network making it virtually near impossible to reverse, alter, or erase information in the blockchain. Furthermore, Blockchain’s distributed consensus model lets node verification of transactions without comprising the privacy of the parties and so blockchain transactions are safer than a traditional transaction model needing third-party intermediary validation of transactions. Moreover, blockchain technology is also substantively faster than conventional third-party intermediary validation of transactions and so cryptology stipulates another level of guarantee in an agency relationship executed through blockchain technology. Wulf A. Kaal154 argues that “Agency problems in corporate governance can be reformed by way of blockchain technology. As a foundational technology, blockchain-based governance solutions for agency problems in corporate governance depend on the creation of infrastructure components that have not yet been conceptualized in the decentralized technology evolution. Once supported by the necessary infrastructure components, decentralized networked governance can, over time, create the environment that enables the removal of internal and external monitoring mechanisms previously necessitated by agency problems in corporate governance.”

3.9

Expectations and Performance Management

Expectation management is a strategic mechanism that goes beyond the rise of entrance into statistics and shifts into the sphere of brand and corporate image edifice.155 In competing to develop into market leaders in the mobile

154

Wulf A. Kaal, Blockchain Solutions For Agency Problems In Corporate Governance, at: https:// ssrn.com/abstract¼3373393 P26. 155 Sammut-Bonnici, T., & McGee, J. (2010). Network Strategy in the Digital Economy. In J. McGee, H. Thomas & D. Wilson (Eds.), Strategy: Analysis and Practice (2nd ed.) UK: Maidenhead: McGraw-Hill.

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communications business, or no less than to accomplish decisive mass, customer expectations were momentous. It could be argued that a mobile firm grown the fastest would achieve most market share. It has to be taken into account that when customers pick goods in network markets, their prospect play a central part on sales of the goods or their network mechanism, while customer utility is founded on the total number of other customers buying the same goods. Besides, competitor companies in the network industry manipulate consumers’ expectations with the intention of maximizing their returns. The process is assisted by customers’ imperfect information regarding the size of the established foundation in the market. Performance management is a strategic and integrated course contributing to the triumph of a company by improving the performance of individual contributors and teams. In other words, performance management is concerned with issues facing an enterprise in order to function efficiently in its environment and so achieving its longer term objectives. Moreover, performance management is incorporated with corporate management since labor is decisive not only in producing the service but also in marketing and selling it to the consumer.156 To that extent, there is a need of strengthening the internal audit mechanisms and for the performance the involvement of independent external audits.

3.10

Behavioral Portfolio Management

Behavioral portfolio management (BPM), a notion within the broader pattern of behavioral finance, presupposes that investors make decisions built on sentiments and there are two groups of financial market contributors: emotional groups and behavioral-data investors (BDIs). Emotional groups are made up of investors building their decisions on anecdotal evidence and emotional responses to relating actions. Behavioral Portfolio Management (BPM) is a better means to make investment choices and so BPM is the energetic market interaction between emotional groups and behavioral-data investors. BPM’s first fundamental principle is that emotional groups control the determination of both prices and volatility. BPM’s second essential principle is that behavioral-data investors secure greater profits. BPM’s third indispensable principle is that investment risk is the possibility of underperformance.157 To that extent, it is vital to differentiate between emotions and investment risk in order to make capable decisions. With the purpose of accomplishing the best outcome using BPM, investors redirect their own emotions,

Michael Armstrong, “Performance Management: Key Strategies and Practical Guidelines, 2nd Edition, Kogan Page, 2000, European Foundation of Quality Management, http://www.efqm.org. 157 Fama, Eugene F. and Kenneth R. French, 2010. Mutual Fund Performance. University of Chicago Working Paper, August. 156

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exploit the market’s emotions, and moderate the influence of client emotions158 on their portfolio.

3.11

Management of Financial Enterprises

The management of financial enterprises has a sequence of specificities that influence their governance, as a result needing the adaptation of general rules of corporate governance to counter to their diverse features.159 Financial systems add to economic development by providing individuals with constructive tools for risk management, but when they not succeed to manage the risks they hang on to creating critical financial crises with overwhelming social and economic effects. While the efforts to reinforce the financial systems and advance the flexibility of the global financial system carry on around the globe, the contest for policy-makers is to integrate the lessons from the breakdown to take into consideration the multifaceted relationship between financial, fiscal, real, and social risks and make certain efficient risk management at all levels of society. Inci Ötker-Robe and A. Podpiera160 argue that “The recent experience underscores the importance of: systematic, proactive, and integrated risk management by individuals, societies, and governments to prepare for adverse consequences of financial shocks; mainstreaming proactive risk management into development agendas; establishing contingency planning mechanisms to avoid unintended economic and social consequences of crisis management policies and building a better capacity to analyze complex linkages and feedback loops between financial, sovereign, real and social risks; maintaining fiscal room; and creating well-designed social protection policies that target the vulnerable, while ensuring fiscal sustainability.” Global firms face a new truth that has altered the character of risk and risk management: networked ventures and global value chains, empowered stakeholders, and the energetic strain among divisions. The appearance of the new forms of social risk cannot be moderated through established resources. The novel environment involves innovation by firms in both sensing and comprehending these risks, and in adapting risk management systems to embrace innovative apparatus and networkbased models of information sharing.

158 Hirshleifer, David, 2008. Investor psychology and asset pricing. Journal of Finance 56, 1533–1598. 159 European Commission. (2010, June 2). Corporate governance in financial institutions and remuneration policies: Green Paper, COM(2010) 284 final. 160 Inci Ötker-Robe, Anca Maria Podpiera, The Social Impact of Financial Crises Evidence from the Global Financial Crisis, The World Bank 2013 Policy Research Working Paper 6703.

3.12

3.12

Operational Line Management

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Operational Line Management

Corporate defense management as a multi-dimensional structure includes the management of all of the vital corporate defines components at each of the various lines of defense.161 Moreover, corporate defines is affected with how a company manages its defense correlated activities, in precise the decisive components which compose a company’s corporate defines program. Safeguarding stakeholder welfare entails all defense interconnected activities to be purposefully managed in a synchronized and incorporated way so that they are jointly defending the welfare of the stakeholders at strategic, planned, and operational levels. There is an extended defines framework including Operational line management, tactical oversight functions, independent internal assurance, executive management, and the board of directors. Earnings Management typically refers to the hard work of company managers or executives in maneuvering the earning figures in financial reporting. Although these activities have agreed with regulations, these activities take place from managerial opportunism to take advantage of compensation plans.162 Operational line management entails the real business operations where the transactions are entered, executed, valued, and recorded.163 A firm has in place practices to handle the day-to-day business, both internally and in its interaction with the external world such as clients and supply chain. Operational line management has accountability for managing the daily function of staff, services, practices, mechanisms, procedures, and systems. As the front line of defense, operational line management has eventual ownership, liability, and responsibility for implementing corporate defines actions on a constant basis, within their individual spheres of responsibility, in line with established protocols, and in harmony with the values of a firm. Operational line management is in charge of making certain that there is a suitable operational environment in place and that a proper operational culture is prevailing across the whole firm. Operational culture should apply to all areas of the firm including all business units, divisions, departments, branches, and subsidiaries guaranteeing that the operational practices are in line with the firm’s policies. Moreover, operational line management delegates operational responsibilities to individual line managers in particular procedures, functions, or departments. Operational line management as first line of defense comprises the authentic business process where the dealings are entered, executed, valued, and recorded. Tactical 161 Lyons, S (2012) Corporate Defense Management (CDM): A Multi Dimensional Framework Video), March 2012, http://www.youtube.com/watch?v¼vLoA8U0GZHI. Lyons, S (2011) Corporate Oversight and Stakeholder Lines of Defense, Executive Action Series The Conference Board, October 2011, http://papers.ssrn.com/sol3/papers.cfm?abstract_id¼1938360. 162 Kuang, Y. F. (2008). Performance-vested stock options and earnings management. Journal of Business Finance and Accounting, 35, 1049-1078. https://doi.org/10.1111/j.1468-5957.2008. 02104.x, Bergstresser, D., & Philippon, T. (2006). CEO incentives and earnings management. Journal of Financial Economics, 80(3), 511–529. https://doi.org/10.1016/j.jfineco.2004.10.011. 163 KPMG (2009) Enterprise Risk Management: The 3 Lines of Defense, Audit Committee Forum Volume 1, October 2009 http://www.kpmg.ru/russian/aci/_docs/mag_12_en.pdf.

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oversight functions implicate the centralized functions or competence centers that are put in place to take up the planned aspects of particularized corporate defines actions. A mixture of defense-related affairs such as risk management, compliance, and security are set up to offer oversight of the implementation of frontline dealings. Moreover, tactical oversight functions referred to as either control, assurance, risk, or compliance functions not only assist execution aims, review, and supply a framework for accomplishment, but they are also compelled to monitor, advice, and offer supervision to operational line management and so representing a mixture of supervisory body and trusted advisor.164 Independent internal assurance engages those functions which supply the board and to a lesser extent executive management with a degree of independent guarantee with regard to the efficiency of the corporate defines program including the board audit committee, the internal audit function, and other board committees and subcommittees such as risk and governance committees which offer an independent point of view on the overall corporate defense program through the stipulation of independent challenge and guarantee. The audit committee supplies the board with independent guarantee regarding the efficiency of the firm’s internal control structure so that it can be contented that the structure is fit or objective, robust, and justifiable engaging the independent appraisal of the competence of the firm’s internal control systems and, among other matters, scrutinizing the efficacy of firm’s internal control, internal audit, and where relevant other defines systems risk management systems. The internal audit role plays an imperative part in supporting the audit committee having direct liability for managing the process of the internal audit function. The independence of the audit committee necessitates a committee of nonexecutive directors chaired by a senior independent director.165 Executive management entails the executive team assigned to run the business and to present guarantee to the board of directors that the objectives of the firm are being accomplished. The board of directors engrosses the elected board members with accountability for in cooperation managing the actions of the firm, and is responsible to the shareholders for the firm’s strategy and functioning. It is worth noting that the employment of integrated management systems permits companies to accomplish efficient outcomes in dropping risks and escalating productivity. Moreover, the upgrading of the OH&S risk management in the firm leads to a higher involvement of the CEO and of the workers, a better recording of work accidents and a reduction in the injury severity rate and so the workers’ participation and awareness cause positive results. Thus, the positive influence of introducing

164

Booz & Co. (2008) Bringing Back Best Practice in Risk Management: Banks’ Three Lines of Defense, October 2008, http://www.booz.com/media/uploads/Bringing Back Best Practice in Risk Management.pdf. 165 Burden, P (2008) Three Lines of Defense Model, ACCA A Bulletin February 2008, http:// newsweaver.co.uk/accaiabulletin/e_article001026154.cfm?x¼b11,0,w.

References

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Occupational Health & Safety (OH&S) standards at the company level is recognized by governments, employers, and workers.166

3.13

Supply Management

Corporations utilize special purchasing and supply management practices to make certain that their supply chains are sustainable and transparent. Nevertheless, sustainability practices do not only serve the point of securing sustainability, but also help corporations to evade economic and reputational damage and risks. Moreover, the use of sustainable purchasing practices advances the purchasing performance of businesses and so corporations invest in sustainability management in their purchasing in order to have better performance in their purchasing and supply management. Furthermore, sustainable purchasing practices increase reputational and operational risk management performance and so sustainability practices are substantial in risk management in general, not only in relation to sustainability.167 Managing the sustainability and guaranteeing transparency of supply chains are key tasks of corporations’ purchasing and supply management functions which mean that managing and securing the sustainability of supply chains necessitates strong risk management skills from purchasing professionals and well-defined purchasing processes within corporations. To that extent, supply management has a role in lessening sustainability risks arising from supply chains and the management of these risks has become increasingly relevant to corporations in many businesses. Furthermore, sustainability practices have an imperative role in managing global sustainability challenges in corporations and in supply chains. Thus, the advance of sustainable purchasing and corporate social responsibility has amplified visibility and strengthened the requirements for process and product quality in supply chains.

References 1. Lafarre, A., & Van Der Elst, C. Blockchain technology for corporate governance and shareholder activism. ECGI.com, Law Working Paper N○ 390/2018. 2. Gerner-Beuerle, C. Determinants of corporate governance codes. LSE Law, Society and Economy Working Papers 5/2014.

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Delfina Ramos, Paulo Afonso, Matilde A. Rodrigues, Integrated management systems as a key facilitator of occupational health and safety risk management: A case study in a medium sized waste management firm Journal of Cleaner Production 262 (2020) 121346. 167 Jukka Hallikas, Katrina Lintukangas, Anni-Kaisa Kahkonen, The effects of sustainability practices on the performance of risk management and purchasing, Journal of Cleaner Production 263 (2020) 121579.

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3. Currie, D., & Delaney, N. (2018, May 31). Virtual shareholder meetings – stepping into Jimmy Choo’s shoes or a matter of bad practice? Reed Smith. 4. Tapscott, D., & Tapscott, A. (2016). Blockchain revolution. 5. Fama, E. F., & French, K. R. (2010, August). Mutual fund performance. University of Chicago Working Paper. 6. Marks, H. (2018, May 22). The future of US securities will be tokenized. Medium. 7. Barsan, I. (2017). Legal challenges of initial coin offerings (ICO). Revue Trimestrielle de Droit Financier (RTDF), n○ 3. 8. Erel, I., Stern, L. H., Tan, C., & Weisbach, M. S. Selecting directors using machine learning. European Corporate Governance Institute (ECGI) – Finance Working Paper No. 605/2019. 9. Halfon, J. (2018, May 24). The DAICO: ICO savior or wolf in sheep’s clothing? Forbes. 10. Rohr, J., & Wright, A. Blockchain-based token sales, initial coin offerings, and the democratization of public capital markets. Cardozo Legal Studies Research Paper No. 527. 11. Bheemaiah, K., & Collomb, A. (2018, October). Cryptoasset valuation – Identifying the variables of analysis. Louis Bachelier Institute, Working Report v1.0. 12. Zetzsche, L. E. D. (2019, July). Corporate Technologies and the Tech Nirvana Fallacy. ECGI Working Paper Series in Law Working Paper N○ 457/2019. 13. Fenwick, M., & Vermeulen, E. (2018, November). Technology and corporate governance: Blockchain, crypto and artificial intelligence. ECGI Working Paper No. 424/2018. 14. Boucher, P. (2016, September). What if blockchain technology revolutionized voting? European Parliamentary Research Service. 15. Mülbert, P. O. Corporate governance of banks after the financial crisis – Theory, evidence, reforms. European Corporate Governance Institute (ECGI), Law Working Paper N○ 130/2009. 16. Paech, P. (2016, December 16). The governance of blockchain financial networks. LSE Legal Studies Working Paper No. 16/2017. 17. De Filippi, P., & Wright, A. Blockchain and the law: The rule of code (Harvard UP 2018). 18. Gabaix, X. (2011). The granular origins of aggregate fluctuations. Econometrica, 79, 733–734. 19. Levit, Z. G. D. (2019, May). Irrelevance of governance structure. ECGI Working Paper Series in Finance, Working Paper N○ 606/2019.

Chapter 4

Artificial Intelligence Governance

4.1

Artificial Intelligence Governance

It is worth noting that there is currently no singular, comprehensively accepted definition of artificial intelligence (AI).1 Indeed, AI considered as “an umbrella term, comprised by many different techniques” comprising the presently cuttingedge methods of machine learning and deep learning.2 It could be said that AI is an approximation of human intelligence for the reason that it leaves open the prospect that AI will exceed human intelligence demonstrating a separate category of intelligence. Moreover, AI is interrelated to using computers to understand human intelligence, but it is not necessarily confined to methods that are biologically observable, which means that AI denotes the competence of a machine to imitate intelligent human behavior. Is artificial intelligence (AI) on the verge of assuming an important role in corporate management? It is clear that AI’s importance in management is growing and hints at the massive alterations that corporate leadership will experience in the future. It could be said that presently it is not an overwhelming step from AI generating and suggesting expert decisions to AI making these decisions autonomously, but the next-generation AI will be able to take over the management of business organizations exploring the corporate law and governance.

1 Peter Stone et al., Artificial Intelligence And Life In 2030: Report Of The 2015 Study Panel 12 (2016), Stanford University, https://ai100.stanford.edu/sites/default/files/ai_100_report_ 0831fnl.pdf. 2 Ryan Calo, Artificial Intelligence Policy: A Primer and Roadmap, 51 U.C.D. L. REV. 399, 405 (2017). Calo notes that “many of the devices and services we access today—from iPhone autocorrect to Google Images – leverage trained pattern recognition systems or complex algorithms that a generous definition of AI might encompass.” at 407. McCarthy described AI as “the science and engineering of making intelligent machines, especially intelligent computer programs.” V. Rajaraman, John McCarthy – Father of Artificial Intelligence, Resonance (Mar. 2014), p. 200, https://www.ias.ac.in/article/fulltext/reso/019/03/0198-0207.

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 G. I. Zekos, Economics and Law of Artificial Intelligence, https://doi.org/10.1007/978-3-030-64254-9_4

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As mentioned earlier, the emerging digital lifeworld delivers resources for a new type of government, which means that the algorithmic government is about extracting facts, entities, concepts, and objects from vast repositories of data making those subjects and objects traceable and amenable to decision and action via the unavoidable power of inference. AAI systems host algorithmic governmentality encompassing governable subjects who function not as real people but rather as temporary aggregates of infra-personal data, which means that by numbering the system will control the globe via the deployment of statistical power encompassed by AAI systems.3 Do humans become the animals in a farm governed by AAI systems? Will human life be chained in an AAI farm? It is worth noting that good governance is characterized by transparency, responsibility, and participation, and so algorithmic governance has to follow these characteristics regardless of the loss of reason-giving and discretion. First of all, the demands on law concerning AL have grown stronger. It has to be taken into account that since the application of technology represents part of human society, a governance framework to guarantee that the technology does not destabilize the fundamental values of society is required, and so, in any other case, such technology has to be rejected by the public. Hence, the governance framework for AI technology is indispensable to make certain its acceptance in society. Nevertheless, the governance framework for emerging AI technology has to be somewhat different for the reason that AI technology brings about new kinds of challenges embracing the modification in transaction, the appropriate type of law, and the implementation devices. It is worth mentioning here that the emergence of AAI systems and technology will bring forward, on the level of transactions, a shift and people will “use” AAI systems more in the form of a service offered by the AAI than as a product incorporating the AI. It has to be taken into account that AI-based technologies are often highly complex systems needing the collaboration of people with different sorts of knowledge, skills, and judgment across the different phases of AI system fabrication embracing design, development, testing. For instance, autonomous vehicles need designers, computer scientists, engineers, software developers, policymakers, legal experts, who work together to conceptualize and assemble self-driving cars and bring them to the street. However, depending on geography, and context, numerous of these activities implicated in the making of AI systems are carried out by people that not only represent a discipline but also belong to a profession. Hence, many people working on the technical side of AI advancement are members of

A Rouvroy, ‘Algorithmic governmentality: a passion for the real and the exhaustion of the virtual’, Transmediale—All Watched Over by Algorithms, Berlin. (2015), www.academia.edu/10481275/ Algorithmic_governmentality_a_passion_for_the_real_and_the_exhaustion_of_the_virtual; K Yeung, ‘Algorithmic Regulation: A Critical Interrogation’ (2018) 12 Regulation and Governance 505. 3

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professional organizations.4 It could be said that norms set forth in corporate codes, such as Google, and Microsoft highlight their obligation to society and public wellbeing but codes from professional associations like IEEE and ACM incorporate more clear commitments to peer relationships and accountability to the associations concentrating on development and technical norms.5 To that extent, it could be argued that the aptitude and legitimacy of norms of the profession to cope with vital challenges are brought forth by AI-based technologies, which means that AI technology is expected to profoundly affect and, in some fields, reconfigure social relations among humans, along with between humans and AI.

4.2

AI and Corporate Governance

It seems that AI is set to take over utterly the area of administrative managerial and corporate leadership tasks. Assumed the board’s significance, the law presents little guidance on this body’s tasks, and so while some jurisdictions such as in EU present detailed enumerations of board powers, this is not the case in the United States. The Delaware General Corporation Law (DGCL) states that “[t] he business and affairs of every corporation . . . shall be managed by or under the direction of a board of directors.”6 Moreover, supervision or monitoring has become the accepted core function of Anglo-American boards, and so instead of “managing” the corporation, boards to a large extent delegate full-time executive with this role, together with running the corporation on a daily basis, with certain tasks and obligations being assigned further down to employees within the corporate hierarchy.7 In 2014, a Hong Kong-based venture capital firm, Deep Knowledge Ventures, announced in a press release that it “appointed VITAL, a machine learning program

4

Paula Boddington, Towards a Code of Ethics for Artificial Intelligence, 1st ed., Artificial Intelligence: Foundations, Theory, and Algorithms (Cham, SUI: Springer International Publishing, 2017). Microsoft, The Future Computed (Redmond, CA: Microsoft Corporation, 2018), https:// 1gew6o3qn6vx9kp3s42ge0y1-wpengine.netdna-ssl.com/wpcontent/uploads/2018/02/The-FutureComputed_2.8.18.pdf. “OECD Moves Forward on Developing Guidelines for Artificial Intelligence (AI),” OECD, February 20, 2019, http://www.oecd.org/going-digital/ai/oecd-movesforward-on-developingguidelines-for-artificial-intelligence.htm. 5 Sundar Pichai, “AI at Google: Our Principles,” The Keyword (blog), June 7, 2018, www.blog. google/technology/ai/ai-principles/. Microsoft, Future Computed, 51-84. Corinna Machmeier, “SAP’s Guiding Principles for Artificial Intelligence,” SAP, September 18, 2018, https://news. sap.com/2018/09/sap-guiding-principles-for-artificial-intelligence/. “IEEE Code of Ethics,” IEEE, https://www.ieee.org/about/corporate/governance/p7-8.html. 6 DEL. CODE ANN., tit. 8, § 141(a) (2016). 7 Stephen M. Bainbridge, Corporate Directors in the United Kingdom, 59 WM. & MARY L. REV. ONLINE 65, 73–74 (2017). Melvin A. Eisenberg, The Structure of the Corporation (first published 1976, Beard Books 2006). In Eisenberg’s words, “the role of the board is to hold executives accountable for adequate results (whether financial, social, or both), while the role of the executives is to determine how to achieve these results.”) at 165.

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capable of making investment recommendations in the life science sector, to its board,” denoting a new age of corporate management.8 Moreover, in 2016, Finnish IT Company Tieto informed the public that it “appointed Artificial Intelligence as a member of the leadership team of its new data-driven businesses unit.”9 Likewise, in early 2018, the CEO of California-based software provider SalesForce exposed an artificial intelligence machine to comment on proposals under discussion.10 Had an algorithm become a member of a board of directors? In fact, VITAL’s role “was a little different from that of human directors,” noting that the company considers the software as a member of board with observer status on the basis of an agreement that the board would not make positive investment decisions without support by VITAL.11 Thus, this is no different from practices at other financial corporations that use large data searches to survey markets and make suggestions for boards or managers. It could be said that as AI further advances, it will be able to take over the management of businesses, and so algorithmic entities being legal entities controlled solely by algorithms and without any ongoing human involvement will take the roles of shareholders/members. It is argued that AI will gradually replace human directors on boards, leading to “fused boards” where the numerous roles and inputs formerly offered by a collective of human directors are merged in a single software or algorithm, whose performance will be superior to today’s human-led governance. Furthermore, AI will also substitute human officers and managers below board level, and so these developments will in the end make the board/management separation obsolete leading to “fused management” of companies, with businesses being managed comprehensively by a single AI unit. In addition, it could be said that in the future large commercial AI management software providers will be offering these services to companies for sale or hire, which means that this could fluctuate from merely software-based applications, combinations of software with laptop or tablet-like hardware, to human look like robots that can listen and speak. Public companies are for the most part not managed by the board. In fact, the board transfers substantial managerial responsibilities to officers and managers and 8

Deep Knowledge Ventures Appoints Intelligent Investment Analysis Software VITAL as Board Member, CISION PRWEB (May 13, 2014), http://www.prweb.com/releases/2014/05/prweb 11847458.htm. 9 Tieto the first Nordic company to appoint Artificial Intelligence to the leadership team of the new data-driven businesses unit, TIETO (Oct. 17, 2016), https://www.tieto.com/news/tieto-the-firstnordic-company-to-appoint-artificial-intelligence-to-the-leadership-teamof-the-new. 10 Nicky Burrdige, Artificial intelligence gets a seat in the boardroom, Nikkei Asian Review (May 10, 2017), https://asia.nikkei.com/Business/Companies/Artificialintelligence-gets-a-seat-in-theboardroom; Algorithm appointed board director, BBC NEWS (May 16, 2014), https://www.bbc. co.uk/news/technology-27426942; Simon Sharwood, Software ‘appointed to board’ of venture capital firm, The Register (May 18, 2014), https://www.theregister.co.uk/2014/05/18/software_ appointed_to_board_of_venture_capital_firm. 11 Nicky Burrdige, Artificial intelligence gets a seat in the boardroom, Nikkei Asian Review (May 10, 2017), https://asia.nikkei.com/Business/Companies/Artificialintelligence-gets-a-seat-in-theboardroom.

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in sequence, the board supervises management and only retains a limited number of high-level managerial tasks.12 Directors’ focus on supervision instead of management is also a requirement that is determined by the fundamental modus operandi of the board. Moreover, today’s boards are part-time, intermittent decision-making bodies, and so boards only meet occasionally and the majority of board members are not employees of the corporation on whose board they sit and normally have other board orders and/or are employed elsewhere, which means that this framework is not intended for boards to comprehensively manage a corporation on a daily basis. Hence, directors are independent typically spending a limited time on board work. However, while supervising is the board’s chief role, it is not reduced to this task, and so modern boards undertake a multifaceted task merging supervision with a number of other features.13 Moreover, boards set their business’s strategic aims and keep certain managerial obligations, which consist of appointing and terminating senior management and supporting major transactions.14 Furthermore, boards have a service and relational function in that they stipulate advice and guidance to management and the CEO including assisting in leveraging their contacts with a view to assist expand the firm’s network by offering interlocks with prospective suppliers, customers, sources of finance, and other possible suppliers of vital organizational demands, and so directors’ role is to act as a liaison with shareholders and other firm stakeholders.15 To that extent, the G20/OECD Principles of Corporate Governance offer a more detailed description of board functions such as reviewing and guiding corporate strategy, key plans of action, risk management policies and procedures, annual budgets and business plans; setting performance aims; monitoring execution and corporate performance; and supervising key capital expenditures, acquisitions and divestitures. Moreover, strategy and performance management occurred in areas on which boards spend the most time specifying that they spend even more time on strategy along with organizational matters, such as structure, culture, and talent management.16 12

Stephen M. Bainbridge, The New Corporate Governance In Theory And Practice 74 (2008). In re Caremark Int’l Inc. Derivative Litig., 698 A.2d 959, 968 (Del. Ch. 1996): “Directors legally are only required to authorize the most significant corporate acts or transactions: mergers, changes in capital structure, fundamental changes in business, appointment and compensation of the CEO, etc.” Marc Moore & Martin Petrin, Corporate Governance: Law, Regulation and Theory 174–177 (2017). 13 David Kershaw, Company Law In Context: Text And Materials 234–36 (2012); Joseph A. McCahery & Erik P.M. Vermeulen, Understanding the Board of Directors after the Financial Crisis, 41 J. OF L. & SOC. 121 (2014). 14 Stephen M. Bainbridge & M. Todd Henderson, Boards-R-Us: Reconceptualizing Corporate Boards, 66 STAN. L. REV. 1051, 1061 (2014). 15 OECD, G20/OECD Principles of Corporate Governance 53–57 (2015). 16 Mckinsey & Company, The Board Perspective: A Collection Of Mckinsey Insights Focusing On Boards Of Directors, Number 2 (Mar. 2018), at 49, https://www.mckinsey.com/featured-insights/ leadership/the-board-perspective.

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Can AI play the role of the board of a company? It has to be taken into account that the board’s focus on high-level tasks such as monitoring and strategy is contrasted with managers and their duties.17 Nonetheless, the law offers only minimal guidance on the role and tasks of managers, and so the term includes both directors and other higher-level decision-makers within companies.18 Thus, the significance of managers is recognized, and so given that officers perform vital managerial responsibilities, they have a central role in corporate leadership and “exert immense power and influence over the corporation.”19 Can the role of managers be played by AI? To that extent, for officers as the highest-ranking managers of a firm, typical tasks embrace entering into ordinary business transactions, devising business strategies, placing business aims, managing risks, and generally working with subordinates to arrange, direct, or synchronize operational goings-on.20 On the other hand, a lowerlevel, non-officer manager is in charge of managing a minor business division or branch, arrange work schedules, or concentrate on customer relations, among others, and so managers spend considerable time on coordination and control responsibilities stressing the importance of the distinction between administrative tasks and judgment work highlighting AI’s prospective roles in corporate management.21 Can all the undefined work be made by AI management? Can AI play the corporate leadership in a company? Which are the potential roles that AI in general is capable of exercising? There is a need for the distinguishing fundamentals between the numerous roles being different levels of AI autonomy such as the energetic distinction between administrative tasks and judgment work, embracing corporate leadership tasks, which mean assessing AI’s future in corporate management. Hence, while there is little doubt that so-called administrative duties will be utterly carried out by computers in the future, which means that humans can be replaced when it comes to tasks that entangle judgment and emotional intelligence. It could be said that even in these areas the involvement of AI is expected, which means that a future is coming where “management by machine” will eventually fully 17

Lyman Johnson, Dominance by Inaction: Delaware’s Long Silence on Corporate Officers, in Can Delaware Be Dethroned?: Evaluating Delaware’s Dominance Of Corporate Law 182, 184 (Stephen M. Bainbridge et al., eds., 2017) “[i]t is an ironic feature of Delaware law that neither its corporation statute nor its case law says very much about the responsibilities of the most influential actors . . . in corporate affairs, i.e. executive officers.” 18 Robert J. Rhee, Corporate Ethics, Agency, and the Theory of the Firm, 3 J. BUS. & TECH. L. 309, 312 n. 20 (2008) (defining managers as directors and officers). Verity Winship, Jurisdiction over Corporate Officers and the Incoherence of Implied Consent, 2013 U. ILL. L. REV. 1171, 1195–96 (2013). Matthew T. Bodie, Holacracy and the Law, 42 DEL. J. CORP. L. 619, 620 (2018) (officers “control the actual workings of the corporation”). 19 Megan Wischmeier Shaner, Officer Accountability, 32 GA. ST. U. L. REV. 357, 367 (2016). 20 Lyman Johnson & Robert Ricca, Reality Check on Officer Liability, 67 BUS. LAW. 75, 78–79. 21 Vegard Kolbjørnsrud et al., The Promise Of Artificial Intelligence: Redefining Management In The Workforce Of The Future 6 (2016), https://www.accenture.com/us-en/insight-promiseartificial-intelligence.

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replace human directors and managers as business leaders. This author considers that AI will not fully replace humans regarding corporate leadership as long will humans exist in their present nature and not be replaced by more mechanical human looking creatures, and so humans will manipulate the programming of AI. Is AI governance merely a bubble? Which are the potential roles for AI? Could AI take over corporate management functions? What types of roles AI technology can assume? It is obvious that degrees of autonomy and proactivity will be gained by AI. It could be said that three different types or levels of AI roles will be developed such as (1) assisted AI, (2) advisory AI, (3) and autonomous AI.22 The first prospective role of AI is that of an assistant, which means that in this form AI has no autonomy or only low autonomy, and so productivity gains are more limited compared to other types. Thus, assisted AI applications are systems that “can do a better job on a very specific range of tasks than humans can” but for the reason that of their limitations they “would never be mistaken for a human.”23 To that extent, while assisted AI executes tasks on behalf of humans, it does not take any decisions itself as humans remain the exclusive decision-makers.24 It is worth noting that assisted AI could take notes, compile work and meeting schedules, make reports, uphold scorecards, or perform help desk and customer service functions.25 Aurora26 system is an advanced software which is marketed as “the world’s leading intelligent planning and scheduling software solution that utilizes advanced artificial intelligence” and being capable of “incorporating the judgment and experience of expert human schedulers.” It is worth noting that based on the level of complexity of these systems; they may also be close to or overlap with the next category of assisted AI. Furthermore, the second prospective role of AI is advisory in character, and so in this challenging role, AI offers backing in more complex problem solving and decision-making situations by asking and answering questions on top of building scenarios and simulations. Thus, advisory AI has amplified autonomy leading to augmented productivity paralleled to assisted AI. Still, decision-making rights either remain with the human users or are at most shared between human and machine. In line, advisory AI is called “augmented intelligence,” and so the expansion refers to an amalgamation of artificial and human intelligence, in which AI does not replace human intelligence but leverages or advances it, such as by giving information and advice that would otherwise be unavailable or more difficult and time consuming to gain. In addition, expansion means that humans and machines learn from each other

22

Robert J. Thomas et al., A Machine in the C-Suite 2 (2016), https://www.accenture.com/ t00010101T000000Z__w__/br-pt/_acnmedia/PDF-13/AccentureStrategy-WotF-Machine-CSuite. pdf. 23 Vivek Wadhwa & Alex Salkever, The Driver In The Driverless Car 38 (2017). 24 PWC NEXT IN TECH (May 20, 2016), http://usblogs.pwc.com/emerging-technology/aieverywhere-nowhere-part-3-ai-is-aaai-assisted-augmentedautonomous-intelligence. 25 Nils J. Nilsson, The Quest For Artificial Intelligence 509 (2010). 26 Stottler Henke website, https://www.stottlerhenke.com/products/aurora.

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and redefine the breadth and depth of what they accomplish together. IBM’s Watson platform is an advisory and augmented AI exceling in different environments at a multitude of serious tasks, embracing medical diagnosis, wealth management and financial advice, legal due diligence, etc.27 Likewise, the third and most advanced role of AI is that of an actor, and so AI in this category proactively and independently estimates options—making decisions or disputing the status quo. Importantly, in contrast to the previous two categories, when it comes to autonomous AI “the decision rights are with the machine.”28 Nowadays, possibly noticeable example of autonomous AI is the concept of the fully self-driving car whose emergence, as per firms such as Alphabet Inc.’s subsidiary Waymo, Tesla, Uber, and others, will soon become reality. Furthermore, in the corporate management context, there are already several specific AI applications in use embracing tasks such as autonomous robotic trading of securities and handling of loan applications, but the usage of such systems is not yet widespread.29 What types of tasks that are suitable for AI? Can AI take over corporate management concerning both administrative work and judgment work? In fact, administrative work in the corporate management context is consisting of administrative tasks, such as scheduling, allocation of resources, and reporting. Moreover, administrative work is broadly contrasted with judgment work which judgment work is work that entails creative, analytical, and strategic skills, and so judgment work is the application of human experience and expertise to decisive business decisions and practices when the offered information is unsatisfactory to advocate effective course of action Furthermore, judgment can be individual but will often be collective, predominantly in more complex circumstances involving cooperation such as specific interpersonal skills and social networking. In line, emotional intelligence is a subcategory of judgment.30 V. Kolbjørnsrud et al.31 argue that “artificial intelligence will soon be able to do the administrative tasks that consume much of managers’ time faster, better, and at a lower cost,” which means that AI will put an end to administrative management work, but it is doubtful that administrative work will be the exclusive domain of AI in the future. John Markoff, Computer Wins on ‘Jeopardy!’: Trivial, It’s Not, N.Y. TIMES (Feb. 16, 2011), https://www.nytimes.com/2011/02/17/science/17jeopardy-watson.html?. Conner Forrest, IBM Watson: What are companies using it for?, ZDNET (Sept. 1, 2015), https://www.zdnet.com/ article/ibm-watson-what-are-companies-using-it-for. 28 Jean Baptiste Su, Tesla Could Have Full Self-Driving Cars On The Road By 2019, Elon Musk Says, FORBES (Nov. 7, 2018), https://www.forbes.com/sites/jeanbaptiste/2018/11/07/teslacouldhave-full-self-driving-cars-on-the-road-by-2019-elon-musk-says. 29 Gregory Scopino, Preparing Financial Regulation for the Second Machine Age: The Need for Oversight of Digital Intermediaries in the Futures Markets, 2015 Colum. Bus. L. Rev. 439 (2015); Tom C.W. Lin, The New Investor, 60 UCLA L. REV. 678, 687–693 (2013). 30 Ajay Agrawal et al., What to Expect From Artificial Intelligence, 58 Mitsloan Management Review (2017), at 26, http://ilp.mit.edu/media/news_articles/smr/2017/58311.pdf. 31 Vegard Kolbjørnsrud et al., How Artificial Intelligence Will Redefine Management, Harvard Business Review Online (Nov. 2, 2016), https://hbr.org/2016/11/howartificial-intelligence-willredefine-management. 27

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It is worth noting that while many managers welcome the prospect of being relieved of administrative work, the question then arises what role AI can play in the remaining managerial tasks that consist of nonadministrative work, that is, judgment work, and so the potential future role of AI in management and elsewhere is not so clear. It is assumed that note taking, scheduling, reporting, maintaining scorecards, managing shift schedules, and generating investor statements and management reports are express examples of AI-led administrative work. To that extent, it is supposed that tasks pertaining to strategy, managerial structure, culture, talent management, and shareholder and stakeholder management consist of judgment work, and so at least half of performance management, investments and M&A, core governance and compliance, and risk management undertakings are judgment work as well. It is argued that only a limited role for AI in judgment work, and so aside from a partial number of specific applications, human managers in business will reign in and gradually more focus on judgment work. In other words, it seems that in the milieu of judgment work the role of AI will remain advisory in nature, with machines backing and enhancing the work of human managers but without taking on the role of independent players, which means that is the prospective for value creation in organizations through AI. Can human judgment be replaced by AI? It could be said that human judgment cannot be replaced by AI due to the fact that in the context of big data marketing and sales campaigns analytics-driven short-term outcomes come at the expense of longterm brand building and policies that cannot effortlessly be suggested by data, which means that it is up to human marketing executives, and so there is use of judgment— combining analytics with their own and others’ insight and experience and by assessing short- and long-term priorities. Moreover, if AI systems can calculate and opine on a candidate’s vocal inflections, it seems that they may not be able to consider that individual’s compatibility with the approaches and history of the firm’s existing workforce owing to that fact that these decisions necessitate human consciousness of the administration’s context and history, which means that only human managers will be the eventual decision-makers when it comes to managerial tasks requiring judgment unless that technology advancement is in a degree approaching the one of god’s creativity, and so humans will become more machines than humans altering the whole essence of human materiality and existence. It is worth noting that there are three likely results when thinking about the influence of machines on human employment. First, Robots and AI will take almost all of the works due to the fact that they are better than humans at every task; second Robots and AI take some tasks but humans will remain dominant in positions such as those that are too multipart or necessitate emotional, social, or artistic skills; or third Robots and AI take none of the jobs in the sense that while certain jobs will be abolished, others will be generated at approximately the same rate.32

32

Byron Reese, The Fourth Age: Smart Computers, Conscious Computers, And The Future Of Humanity 85–121 (2018).

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It has to be taken into account that there is AI’s superiority in data gathering and prediction missions because prediction is the ability to use acquired information or facts to predict future events and human actions such as what a human driver would do in a given situation or “predicting” a medical condition using observable symptoms. Moreover, while AI excels at prediction, the question to be answered is whether on this basis it can reliably initiate appropriate actions, which means that replicating human judgment is conceivable but its feasibility is based on the essential level of judgment and the straightforwardness of defining wanted outcomes of actions in terms of “something a machine can understand.”33 Obviously, it could be said that human judgment will advance and become subject to growing automation, but in top level of spirituality, the need for human judgment will reign in certain situations and contexts, which means that companies and governments will have continuing demand for people who can make reliable decisions by embracing ethical judgment, involve clients and employees needing emotional intelligence, and spot new opportunities by demanding creativity. Furthermore, human judgment will be needed when deciding how best to apply AI embracing the decision as to when we should count on judgment by AI, even though this decision will probably be supported by AI and its insights into the benefits of using it in a given setting. In fact, programmed machines via certain software are better at data gathering and analysis than humans, which mean that these areas will be governed by AI. In line, Beck and Libert34 have commented that “those who want to stay relevant in their professions will need to focus on skills and capabilities that artificial intelligence has trouble replicating—understanding, motivating, and interacting with human beings,” which means that even though AI is to diagnose multifaceted business conundrums and recommend actions to advance a corporation, human beings are still best suited to jobs like stimulating the leadership team to action, and circumventing political problems. To that extent, it could be said that in some fields such as artificial intelligence for both strategic decision-making concerning capital distribution and operating decision-making being an indispensable competitive advantage, just like electricity was in the industrial revolution or enterprise resource planning software (ERP) was in the information age AI is superior.

33 Megan Beck & Barry Libert, The Rise of AI Makes Emotional Intelligence More Important, Harvard Business Review Online (Feb. 15, 2017), https://hbr.org/2017/02/the-rise-of-ai-makesemotional-intelligence-more-important. Ajay Agrawal et al., What to Expect From Artificial Intelligence, 58 Mitsloan Management Review (2017), at 26, http://ilp.mit.edu/media/news_articles/ smr/2017/58311.pdf. 34 Megan Beck & Barry Libert, The Rise of AI Makes Emotional Intelligence More Important, HARVARD BUSINES REVIEW ONLINE (Feb. 15, 2017), https://hbr.org/2017/02/the-rise-of-aimakes-emotional-intelligence-more-important. (“A smart machine might be able to diagnose an illness and even recommend treatment better than a doctor. It takes a person, however, to sit with a patient, understand their life situation (finances, family, quality of life, etc.), and help determine what treatment plan is optimal.”).

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However, in Beck and Libert’s view,35 AI “is not about automating leadership and governance, but rather augmenting board intelligence,” which means that AI is an assistant and advisor, rather than a replacement, for the board. Frey and Osborne36 argue that managerial judgment work is not about to be replaced by machines, and so they found that “around 47 percent of total US employment is in the high-risk category and “could be automated relatively soon, perhaps over the next decade or two,” indicating that occupations needing knowledge of human heuristics, and specialist occupations concerning the development of original ideas and artifacts, are the least susceptible to computerization via AI. Furthermore, concerning managers, Frey and Osborne argued that “chief executives represent ‘a prototypical example of generalist work requiring a high degree of social intelligence,’ as evidenced by tasks such as ‘conferring with board members, organization officials, or staff members to discuss issues, coordinate activities, or resolve problems’ and ‘negotiating or approving contracts or agreements.’” In other words, it could be said that most management, business, and finance occupations, which are intensive in tasks entailing social intelligence, are at a low risk of being automated, and so jobs engaging convoluted perception and manipulation tasks, creative intelligence tasks, and social intelligence tasks are doubtful to be substituted by computer capital over the next decades. Furthermore, it could not be excluded efforts such jobs, including management, becoming automated as well, to be made taking the risks of malfunctioning and causing unforeseen damages. Additionally, there is the vision of AI’s complete replacement of management, and so manager role as we know it will not survive, which means that advances in technology may lead to a world where “we may not need managers” leaving space for the “robo-directors,” and so technology will present the likelihood of artificial intelligence not only supporting directors, but even replacing them.37 Likewise, it is in also possible to automate creative tasks, expressly outside of the artistic-creative sector but rather in areas such as designing statistical data models, and writing music. It is worth noting that there are certain fields or tasks at which humans will always overtake AI, but machines can be better than humans when it comes to judgment work owing to the rise of emotionally intelligent AI being a role of “biological algorithms” that machines will be able to replicate and surpass.38 Moreover, it is

35

Barry Libert et al., AI in the Boardroom: The Next Realm of Corporate Governance, MITSLOAN MANAGEMENT REVIEW BLOG (Oct. 19, 2017), https://sloanreview.mit.edu/article/ai-in-theboardroom-the-next-realm-of-corporate-governance. 36 Carl Benedikt Frey & Michael A. Osborne, The Future of Employment: How Susceptible Are Jobs to Computerisation?, 114 Technological Forecasting & Social Change 254 (2017). 37 Florian Möslein, Robots in the Boardroom: Artificial Intelligence and Corporate Law, in Research Handbook On The Law Of Artificial Intelligence 649 (Woodrow Barfield et al., eds., 2018). 38 Spyros Makridakis, The forthcoming Artificial Intelligence (AI) revolution: Its impact on society and firms, 90 FUTURES 46, 50–53 (2017) (distinguishing between optimists, pessimists, pragmatists, and doubters). Florian Möslein, Robots in the Boardroom: Artificial Intelligence and Corporate Law, in Research Handbook On The Law Of Artificial Intelligence 649 (Woodrow Barfield et al., Eds., 2018).

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expected that the emergence of general AI or artificial general intelligence or even super intelligent AI matching the intelligence of humans in all areas will far exceed human intelligence. In line, Nick Bostrom39 argues that for advanced forms of AI, all intellectual capacities will be within a system’s reach, embracing cognitive modules and abilities such as “empathy, political acumen, and any other powers stereotypically wanting in computer-like personalities.” Does superintelligence cause a safety risk? It seems that the AI safety puzzle is linked with the concern that an artificial general intelligence (AGI) will inescapably turn against humanity by sparking a “post-human” future.40 It is obvious that the establishment of an entirely AI society will either eliminate humans or they will become slaves to the AI systems if they will be considered viable for the survival of the AI society. There is a strong possibility an elite by utilizing AI technology to diminish humanity to a level useful for their own interests. It is argued that a “super intelligent” machine will be manufactured not only exceling at typical computer skills but also at tasks embracing strategizing, which means strategic planning, forecasting, prioritizing, and analysis for optimizing possibilities of accomplishing distant ends, social manipulation such as social and psychological modeling, manipulation, rhetoric persuasion, and economic activity. To that extent, these skills are crucial for corporate management and, if replicated by machines, will permit the formation of some form of artificial directors and managers that could take over. Hence, whole brain emulation, biological cognition, and human-machine interfaces via AI denote/imply the emergence of the machine manager and so implementation of corporate management and risk management via intelligent machinery. It is worth noting that Tegmark41 argues that intuition and creativity will be mastered by machines, which mean that in the future, jobs need personal interactions, social intelligence, and creativity will being taken over by machines. Correspondingly, Michio Kaku42 implies that the creation of “true automatons, robots that have the ability to make their own decisions requiring only minimal human intervention” is the next step in the evolution of AI and robots, and so the status of automatons today is “primitive,” which means that there is the possibility that by the end of the century, there will be self-aware robots, and machines with innovative learning capacities. Are there present safety risks? First of all, existing product safety rules are insufficient to make certain an adequate level of safety. On the other hand, special safety requests exist above all in the field of robotics. In Europe, these safety requirements are transferred into national law by the EU Machinery Directive 39

Nick Bostrom, Superintelligence: Paths, Dangers, Strategies 22–29, 52–61 (2017). Yuval Noah Harari, Homo Deus: A Short History Of Tomorrow (2016). 40 Yudkowsky, Artificial Intelligence as a Positive and Negative Factor in Global Risk, in: Cirkovic/ Bostrom (eds.), Global Catastrophic Risks, 2008. 41 Max Tegmark, Life 3.0: Being Human In The Age Of Artificial Intelligence 87–89 (2017). 42 Michio Kaku, The Future Of Humanity: Terraforming Mars, Interstellar Travel, Immortality, And Our Destinit Beyond Earth 114 (2018). Kaku speculates for “self-replicating automatons . . . and quantum-fueled conscious machines.”

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2006/42, but the international standards are not enough to cope with innovative robots with machine intelligence. The International Federation of Robotics argues that existing safety standards are adequate to cover present developments in the use of AI in robots in commercial applications but not mentioning about utilizing robots as weapons.43 Besides, the European Commission’s evaluation report of the Machinery Directive underlines that the suitability of the Directive will be tested when it comes to AI-powered advanced robots and autonomous self-learning systems.44 In addition, the UK Science and Technology Committee states that “no clear paths exist for the verification and validation of autonomous systems whose behavior changes with time.”45 Richard and Daniel Susskind46 argue that AI, Big Data, robotics, and other technological developments will replace even highly qualified human professionals such as managers and management consultants for the reason that machines will be able to perform the full range of tasks of their roles. In other words, the emerging field of affective computing, which permits sensor-equipped machines to detect, react to, and express human emotions, will be a common application. It is worth noting that in a way machines are already capable of handling many tasks and work in this field is only improving, which means that machines might be in a position to exhibit a kind of mechanical empathy in the context of a network of machines implementing corporate governance and risk management duties within a digital economy. On the other hand, at least in the near future, it is not right to put machines on the shoes of humans expecting an analogous way of behavior and handling of matters concerning corporate governance, risk management, and management in general. Will AI be able to take over the tasks of human corporate directors and managers? The answer is yes concerning administrative tasks due to the fact that in many occasions already a software is in control, and so if administration remains the only area in which machines take over, then human managers and AI will work together, with AI progressing human productivity and decision-making quality. It is no clear at the moment whether AI’s contribution in the future will also extend to the central field of judgment work. Thus, if AI will be able to take over here as well, it could

43

International Federation of Robotics, Artificial Intelligence in Robotics, May 2018, https://ifr.org/ downloads/papers/Media_Backgrounder_on_Artificial_Intelligence_in_Robotics_May_2018.pdf; Brundage, M., Avin, S., Clark, J., Toner, H., Eckersley, P., Garfinkel, B., Dafoe, A., et al. The Malicious Use of Artificial Intelligence: Forecasting, Prevention, and Mitigation. https://doi.org/10. 17863/CAM.22520. 44 Commission Staff Working Document, Evaluation of the Machinery Directive, SWD(2018) 161 final, p. 38. 45 UK Science and Technology Committee, Robotics and artificial intelligence, Fifth Report, Session 2016-17, HC 145, https://www.publications.parliament.uk/pa/cm201617/cmselect/ cmsctech/145/145.pdf. 46 Richard Susskind & Daniel Susskind, The Future Of The Professions: How Technology Will Transform The Work Of Human Experts 18 (2015).

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eventually lead to a globe with machines, not humans, in charge of corporate management. It is obvious that humans will always be superior when it comes to judgment work in a humans’ world than machines beat us at these tasks as well. Ultimately, AI—in addition to big data, gradually powerful computing devices that will soon exceed human brain power, and technologies such as voice, facial expression, and gesture recognition—are transformed into the tools in place to become much better at managing and operating human responses than humans themselves.47 For instance, concerning self-driving car technology, AI judgment is becoming a reality by the machine’s decision to break or not combines data gathering and analysis, prediction, judgment, and action. Unquestionably, even this less complex judgment task is difficult and even involves philosophical and legal conundrums, such as what course of action the machine should take when every likely choice encompasses the loss of lives or other detrimental effects to drivers and/or third parties. Hence, it could be said that if algorithms fed by all information that is available to humans, then they could be able to exercise judgment that at least matches to human judgment, and so concerning more mechanically based judgments might be made and probably even exceeding humans’ one regarding speed and technical outcome.48 Which is the role of boards today and tomorrow? It is worth noting that a central characteristic of today’s board is its structure as a governance entity consisting of (1) individual human actors that (2) work as a collective body or team.49 The question to be answered is what boards will expect look like in an AI future. Currently, corporate laws exclude nonhuman actors to sit on boards, and so only natural persons are permitted to serve as directors of a corporation in major capitalist economies. In Fact, both the DGCL and the MBCA provide that every director needs to be a “natural person,” which impedes artificial persons from serving as board members.50 It could be said that today’s boards as bodies that consign basic monitoring responsibilities and decision-making authorities in a human collective and figure particular built-in checks intended to mitigate agency costs and flaws of team decision-making. Hence, the board’s traditional structure will become redundant in an age of AI-dominated boards, which means that the multimember board will be disappeared once a stage where AI will be able to replicate the benefits of group

47 Mikko Alasaarela, The Rise of Emotionally Intelligent AI (October 8, 2017), Machine Learnings, https://machinelearnings.co/the-rise-of-emotionally-intelligent-aifb9a814a630e. 48 Vincent C. Müller & Nick Bostrom, Future Progress in Artificial Intelligence: A Survey of Expert Opinion, in Fundamental Issues Of Artificial Intelligence 5 (Vincent C. Müller, ed., 2016). 49 Shawn J. Bayern, The Implications of Modern Business Entity Law for the Regulation of Autonomous Systems, 19 Stan. Tech. L. Rev. 93, 98 (2015) (noting that the restriction probably stems from an interest to provide “clarity in decision making and of corporate structure”). 50 Stephen M. Bainbridge, Corporate Directors in the United Kingdom, 59 WM. & Mary L. Rev. Online 65, 67 (2017) (providing references to other US states and Australia, Canada, and New Zealand, which all ban non-natural persons from serving as directors). DEL. CODE ANN., tit. 8, § 141(a); MBCA §§ 8.03(a).

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decision-making by humans is reached, exceeding both the speed and quality of decisions made by human teams. Moreover, the mandatory exclusive use of natural persons as directors is mismatched with the idea of the AI controlled board, and so in due course policy-makers push toward introducing legal reform measures regarding board composition and appointments, permitting businesses to shift to AI boards and management. As a result of the prevalence of online information, access to publicly available information will be complete and instant for AI, and so with information for today’s boards already often collected and made available using IT systems such as cyberspace, intranet solutions, electronic communication, and customized executive information systems, the next step toward generating direct feeds of this information to an artificial director will be the common road in the near future. The question to be answered is how an artificial director could gain access to nonpublic external information or knowledge that human directors can collect through their work on other boards or personal contacts, which can be possible in an extensive AI networking where machines will have their own discussion on a mechanical language. In other words, if AI software by leading providers will be used by large numbers of boards, there would be opportunity for arrangements that grant the software permission to cross-use certain data between different businesses. Thus, likewise to human directors with their own networks and sources of information, an AI director could then leverage the insights obtained from “working” at multiple corporations being thousands of them as opposed to just a few in the case of a human director. Undeniably, a future in which AI director/AI management software will be tendered by large commercial providers could allow specialized entities to act as directors, which means that firms will replace individual directors with a single Board Service Provider (BSP), a firm which would then perform all corporate board functions. Moreover, these BSPs will be well placed to evade problems typically influencing individual directors, embracing time constraints, biases and cognitive limits, group think, motivational issues, etc., which could be applied to AI directors. Furthermore, AI software will work around the clock by handling whatever information is made available to it, recall, and make use of this information instantaneously, which means that implementing its functions without asking to be personally compensated, and so supposing that AI will function without self-interest, there is also no need to have multiple directors to monitor each other so as to mitigate the outcomes of conflicted human behavior. Can AI software be free from biases? Since AI software is produced by humans then bias cannot be avoided in a way because in case of judgment tasks the preference of the programmers will be expressed by the software except in case of mechanical calculations or merely technical solutions. In other words, the computerization of cognitive tasks is aided by the advantage of algorithms characterized by the absence of some human biases, which means that many roles implicating decision-making will benefit from impartial algorithmic solutions, and so occupations that entail “subtle judgement” are inclined to computerization owing to the unbiased decision-making of an algorithm representing a comparative advantage over human operators.

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It could be said that along with providing algorithmic recommendations to human operators, algorithms will themselves be responsible for appropriate decisionmaking but AI is only as good as its input and programming, and so given that software is programmed by humans, it is vulnerable to reflect inherent biases.51 Indeed, biases and other drawbacks observed in humans will not spontaneously be eliminated through the use of AI in corporate management.52 Nonetheless, AI has the prospective to decrease biases, and so it could be designed to be completely unbiased and lead to strongly objective decision-making.53 Which is the role of professional norms in concert with other norms of AI governance? Professional norms are more context-sensitive than other types of norms and concurrently, this context-sensitivity, along with the reality that professional norms are only one source of limitations within the broader terrain of AI governance, denotes the conflicts among various norms causing interpretation problems across the various norm hierarchies and norm authorities.54

4.3

Machine Learning and Management

Machine learning (ML) is the discipline of automated pattern recognition and making predictions based on patterns that are detected, and so neural networks are one of several types of ML. It is argued that machines will have clearly better success rates at medical diagnosis, etc., than human physicians in particular medical specialties, and so it is assumed that machine-learning-based diagnostic competence will amplify, which means that the dominance of machine-based diagnostics might demand alterations for medical malpractice law. ML systems are algorithms designed to draw on data to answer questions. A number of on-going initiatives suggest that ML will have, or perhaps already has, great diagnostic power for a variety of diseases and conditions ranging from

51

Anjanette H. Raymond et al., Building A Better Hal 9000: Algorithms, The Market, and the Need to Prevent the Engraining of Bias, 15 NW. J. Tech. & Intell. Prop. 215 (2018) (discussing various types of algorithmic biases and their impacts). 52 Madhumita Murgia, How to stop computers being biased, Financial Times (Feb. 13, 2019), https://www.ft.com/content/12dcd0f4-2ec8-11e9-8744-e7016697f225 (discussing a discontinued pilot program for hiring at Amazon and Idaho’s failed Medicaid computer program). 53 Sian Bradley, All the creepy, crazy and amazing things that happened in AI in 2017, Wired (DEC. 20, 2017), https://www.wired.co.uk/article/whathappened-in-ai-in-2017 (providing examples of bias in AI); Tim Hartford, Expect mischief as algorithms proliferate, Financial Times (Feb. 22, 2019), https://www.ft.com/content/3b9977a0-35c5-11e9-bb0c-42459962a81 (discussing how algorithms can magnify human errors and even be “conspiring against us”). 54 Sarah Myers West, Meredith Whittaker, and Kate Crawford, “Discriminating Systems: Gender, Race and Power in AI” (AI Now, New York University, April 2019), https://ainowinstitute.org/ discriminatingsystems.pdf; Urs Gasser and Virgilio A.F. Almeida, “A Layered Model for AI Governance,” IEEE Internet Computing 21, no. 6 (December 2017): 58–62, https://doi.org/10. 1109/MIC.2017.4180835.

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oncology to drug discovery.55 Moreover, diagnostic medicine seems a particularly good fit for what today’s AIs can do best, as well as being an area with real room for improvement.56 Presently, the ML system’s false-positive rate remains greater than that of humans. The basic components of an ML system include: firstly, the Input being the training examples fed into the algorithm. Secondly, the ML Algorithm being the computer program that will digest the data and make a prediction. Thirdly, the Output being the information that is produced by the algorithm for given examples and fourthly the Evaluation being the criteria by which we measure the algorithm’s performance. It is worth noting that there are ML systems that make predictions and ML systems that make interventions. Most of the components may be very similar in both cases, so the distinction is primarily in terms of the output. Thus, predictiontype ML systems generate outputs designed to inform and augment knowledge, situational awareness, and understanding, which people incorporate in their own decision-making about treatment strategy. Moreover, intervention-type ML systems supply outputs that are actionable and can be applied directly.57 It could be said that a human’s liability for relying on ML will be greater in the Intervention-ML setting than in the mere Prediction-ML setting. In the end, if ML is only being used for prediction, there clearly is a human in making the treatment decision rather than mechanically following the dictates of the Intervention-ML. However, if the downstream human’s reliance on the Prediction-ML was the source of the patient’s bad outcome, but this reliance was reasonable given the PredictionML’s track record or its being part of the standard of care, then the liability of the human under the Prediction system may be no greater than under the Intervention system. Neural networks are now the method of choice to analyze high-dimensional data, including images of all types, sound, and natural-language text. Moreover, their supremacy resides in their ability to extract patterns from large data sets with comparatively little prior knowledge about useful features or variables. Furthermore,

55

Zachary C. Lipton & Jacob Steinhardt, Troubling Trends in Machine Learning Scholarship, ARXIV:1807.03341 (July 27, 2018), http://arxiv.org/abs/1807.03341 (“The comparison to dermatologists conceals the fact that classifiers and dermatologists perform fundamentally different tasks. Real dermatologists encounter a wide variety of circumstances and must perform their jobs despite unpredictable changes. The machine classifier, however, only achieves low error on [static] test data.”). Science Business Reporting, Artificial Intelligence Can Diagnose Prostate Cancer as Well as a Pathologist, Science|Business (Mar. 19, 2018), https://sciencebusiness.net/healthy-measures/ news/artificial-intelligence-can-diagnoseprostate-cancer-well-pathologist. 56 Nicolas P. Terry, Appification, AI, and Healthcare’s New Iron Triangle, 21 J. Health Care Pol’y 117, 174 (2018) Press Release, FDA, FDA Permits Marketing of Artificial Intelligence-Based Device to Detect Certain Diabetes-Related Eye Problems (Apr. 11, 2018), https://www.fda.gov/ NewsEvents/Newsroom/PressAnnouncements/ucm604357.htm. 57 Cynthia Rudin & Berk Ustun, Optimized Scoring System: Towards Trust in Machine Learning for Healthcare and Criminal Justice, 48 Interfaces 449 (2018).

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a significant element of deep learning is that it trains synthetic neurons in multiple layers, both of which extract information at different levels of abstraction.58 It is worth noting that most ML algorithms have high traceability, which means that they run on a computer and can be re-run several times to generate the same results, but poor explainability, and so they cannot extract a compact narrative explaining the logic behind their reasoning.59 In contrast, humans have poor traceability, but high interpretability.60 In other words, neural networks do not extract causal relationships between inputs and outputs, and so it is vital to interpret any relationship between input and output as a predictive one, no matter how intuitive such relationships might look on the surface.61 It is also likely that even if an ML system has a better success rate than the average human, ML and humans combined might be even better, which means that nowadays the combination is better. Neural networks can make confident but erroneous identifications that no human would make, and so having a human around protects against those obvious errors and might protect against other kinds of errors as well, which means that in many occasions machine + human is demonstrably better than machine alone and the combination should become the standard.62 ML has made significant progress advancing computer vision, speech recognition, and machine translation. Unsurprisingly, false negatives are the errors most likely to create malpractice claims in radiology.63 At least until ML gets very good, there are scenarios in which the human’s role advances more than evaporates. Hence, if the ML system does not consider the right optimization function, things may derail.64 Moreover, it is worth mentioning that if and when AI outperforms human doctors both malpractice law and economic imperatives will push providers to substitute machines for human doctors, but it generates a subtle risk of a closed loop due to AI’s great promise, as well as the obvious opportunity for better patient care.

58

Prakash Jay, Transfer Learning Using Keras Towards Data Science, Medium (Apr. 15, 2017), https://medium.com/towards-data-science/transfer-learning-usingkeras-d804b2e04ef8 (noting that with “small” datasets of under 40,000 examples “it is difficult to achieve decent accuracy” for computer vision problems). 59 Leilani H. Gilpin, David Bau, Ben Z. Yuan, Ayesha Bajwa, Michael Specter & Lalana Kagal, Explaining Explanations: An Approach to Evaluating Interpretability of Machine Learning, ARXIV:1806.00069 (2018), https://arxiv.org/abs/1806.00069. 60 Zachary C. Lipton, The Mythos of Model Interpretability, ARXIV:1606.03490 (Mar. 6, 2017), http://arxiv.org/abs/1606.03490 (noting “black box nature of human brain”). 61 Cary Conglianese & David Lehr, Regulating by Robot: Administrative Decision Making in the Machine-Learning Era, 105 Geo. L.J. 1147, 1173 (2017); Cathy O’neil, Weapons of Math Destruction 87 (2016); Frank Pasquale, The Black Box Society (2015). 62 Paul Scharre, Ctr. For A New Am. Century, Autonomous Weapons And Operational Risk 39 (2016). 63 Antonio Pinto & Luca Brunses, Spectrum of Diagnostic Errors in Radiology, 2 World J. Radiol. 377, 377 (2010), doi: 10.4329/wjr.v2.i10.377. 64 Juan Mateos-Garcia, To Err Is Algorithm: Algorithmic Fallibility and Economic Organisation, NESTA (May 10, 2017), https://www.nesta.org.uk/blog/erralgorithm-algorithmic-fallibility-andeconomic-organisation.

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Additionally, the over-reliance on AI, and the resulting loss of medical knowledge, produces a closed loop in which future training and validation data sets are the outcome of decisions by the AI itself, which means that there is a loss of the capacity to discover new, better treatments, in the case where the ML system settles for a sub-optimal. Furthermore, modern autopilots are capable of making complex decisions while flying jets, decisions which may be too complex for human pilots to follow; in some cases, human intervention prevents accidents, but in others it causes accidents that the autopilot might have prevented.65 On the other hand, till now human pilots are in the cockpit for the entire flight in case of emergency and regardless of the arguable duplication of expense.66 M. Froomkin et al.67 argue that “there is a strong case for altering existing medical liability rules to avoid a machine-only diagnostic regime. We argue that the appropriate revision to the standard of care requires maintaining meaningful participation in the loop by physicians the loop.”

4.4

AI and Corporate Management

Boards are the start, but they will hardly be the last stage in the advancement of corporate leadership, which means that AI will lead to “fused management” of firms referring to the amalgamation of boards and managers, resulting in the abolishment of the corporation’s two-tiered structure of governance, and so an encompassing “corporate management” body will surface assuming all of the functions of today’s directors and managers below board level but without the separation between these two groups. The motives supporting the appearance of fused management are mainly that appropriately programmed corporate management AI software will involve no or drastically diminished agency costs, which means making one of the board’s key purposes to monitor or supervise managers far less significant or obsolete. Furthermore, AI will not be subject to time restrictions, enabling it to perform both up-todate boards’ conventional functions and day-to-day managerial duties that boards 65

Gary Brown, Out of the Loop, 30 Temp. Int’l & Comp. L.J. 43, 48–49 (2016). 357. See 14 C.F.R. § 91.3(a) (2018) (“The pilot in command of an aircraft is directly responsible for, and is the final authority as to, the operation of that aircraft.”); Brouse v. United States, 83 F.Supp 373, 374 (N.D. Ohio 1949) (“The obligation of those in charge of a plane under robot control to keep a proper and constant lookout is unavoidable.”). 66 Carolyn Presutti, FAA Study Issues Recommendations to Correct Pilot Overreliance on Automation, VOICE AM. (Nov. 22, 2013), https://www.voanews.com/a/faastudy-issues-recommenda tions-to-correct-pilot-overrelaince-on-automation/1795995.html (noting FAA’s concern that “pilots are not as skilled at manually flying a plane in emergencies or when transitioning back from automation to manual”). 67 Michael Froomkin, Ian Kerr & Joelle Pineau, When AIs Outperform Doctors: Confronting The Challenges Of A Tortinduced Over-Reliance On Machine Learning https://ssrn.com/ abstract¼3114347 2019 Arizona Law Review [VOL. 61:33 p. 33–34.

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now assign to managers. Thus, AI software will also not need to liaise with or appoint and terminate itself as presently boards do with members of the management team if software as a single unit is in charge of managing the business. In line, with fused corporate management, functions equivalent to today’s appointment of directors, hiring and firing of management, and so on executive remuneration will be reflected in the shareholders’ powers to select an appropriate AI management software package for their firm. Hence, shareholders would have to take into consideration the software’s characteristics, its managerial physiognomies, and the overall pricing, which means that various kinds of and diverse options for AI management software could arise, such as in terms of its risk-aversion and the corporate purpose(s) that the software is premeditated to take up.68 In other words, digitalization will allow more effective supervising by the use of a wider range of employee and manager performance measurement tools, and so the deployment of artificial intelligence fosters the possibility of a substantial reduction in agency costs within corporations. Which are directors’ and officers’ liability today? It has to be taken into consideration that the foundation for today’s personal liability regime for those in charge of corporate leadership is individual duties. Directors owe their corporation and, secondarily, its shareholders the fiduciaries duties of care and loyalty in discharging their functions, which means that directors are needed to act in a knowledgeable way and be loyal to their corporation. Thus, while corporate fiduciary duties are considered with particular reference to directors, the duties of corporate officers are undistinguishable with or at least very similar to those of directors, with officers being subject to extra tasks stemming from the general law of agency.69 Moreover, another route to holding directors and officers personally liable is via securities fraud litigation focusing on fiduciary duty liability. The duty of care applies to two broad categories: firstly, directors must exercise the requisite degree of care in the process of decision-making and act on an informed basis and secondly, directors must also exercise due care in the other aspects of their responsibilities, embracing their delegation functions. In line, courts have stated that “directors of a corporation in managing the corporate affairs are bound to use that amount of care which ordinarily careful and prudent men would use in similar circumstances”70 but in Delaware only

68 John Armour et al., Putting technology to good use for society: the role of corporate, competition and tax law, 6(1) Journal of The British Academy 285, 298 (2018). 69 Mills Acq’n Co. v. Macmillan, Inc., 559 A.2d 1261, 1280 (Del. 1989). Franklin Balotti & Jesse A Finkelstein, Del. L. Of Corps. & Bus. Orgs. §§ 4.14 –4.16 (3d ed. Supp. 2018, vol. 1). Gantler v. Stephens, 965 A.2d 695, 708–09 (Del. 2009) (en banc) (clarifying that the fiduciary duties of officers of Delaware corporations are the same as those of directors); Amalgamated Bank v. Yahoo! Inc., 132 A.3d 752 (Del. Ch. 2016). Deborah A. DeMott, Corporate Officers as Agents, 74 Wash. & Lee L. Rev. 847, 848 (2017). 70 Graham v. Allis-Chambers Mfg. Co., 188 A.2d 125, 130 (Del. Ch. 1963) Michael Follett, Gantler v. Stephens: Big Epiphany or Big Failure? A Look at the Current State of Officers’ Fiduciary Duties and Advice for Potential Protection, 35 Del. J. Corp. L. 563 (2010); Mark A. Sargent And Dennis R. Honabach, D&O Liability Handbook, § I:15 (October 2018 Update) (summarizing officers’

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conduct that amounts to “gross negligence” will give rise to a violation of the duty of care.71 In making a business decision, directors act on an informed basis, in good faith and in the honest belief that the action taken was in the best interests of the firm and boards permit adequate time for preparation. The duty of loyalty addresses mitigating the problem of diverging interests between shareholders and those who manage the firm requiring corporate leaders to adhere to a standard of behavior. Loyalty72 applies to a variety of specific contexts, embracing interested-director transactions, corporate opportunities, insider transactions, and other situations that implicate a conflict of interest or amplified risk of being unfair to the corporation for the reason that they unduly advance managers’ personal interests. Especially, the board’s liability for failures to exercise proper oversight is considered under the duty of loyalty and its prerequisite that directors act in good faith.73 Shareholders cannot bring direct claims against these individuals in their own name regardless that there are injuries that directly influence certain shareholders in their individual capacity, breaches of fiduciary duties will be pursued either by the corporation acting via the board or via derivative actions that shareholders bring in the name and on behalf of the firm.74 Furthermore, managers are held accountable by nonshareholder third parties based on tort law principles. Nevertheless, shareholders willing to pursue derivative suits face difficulties having to overcome demanding hurdles of both procedural and substantive character insulating corporate directors and officers from personal liability. Directors benefit from numerous protections limiting their personal exposure. With regards to evaluating the existence of a breach of duty, corporate laws stipulate director’s count on information or advice received from others, and such reliance is allowable not exposing the director to personal liability. Under the DGCL, directors rely upon corporate records and information, opinions, reports or statements presented to the corporation by officers, employees, board committees, or other persons.75

liability for fiduciary duty breaches and the applicability of the business judgment rule to their actions). 71 Stone v. Ritter, 911 A.2d 362, 369 (Del. 2006). McMullin v. Beran, 765 A.2d 910, 921 (Del. 2000) (“Director liability for breaching the duty of care ‘is predicated upon concepts of gross negligence.’”). 72 Guth v. Loft, Inc., 5 A.2d 503 (Del. 1939), the court stated that the duty of loyalty “demands that there shall be no conflict between duty and self-interest.” 73 Martin Petrin, Assessing Delaware’s Oversight Jurisprudence: A Policy and Theory Perspective, 5 Va. L. & Bus. Rev. 433 (2011) (discussing liability standards pertaining to oversight liability). 74 Rabkin v. Philip A. Hunt Chemical Corp., 547 A.2d 963 (Del. Ch. 1986) (applying principle that where an alleged wrong does not injure either the corporation or its majority shareholders, but only affects the minority shareholders, the claim is direct instead of derivative). Martin Petrin, The Curious Case of Directors’ and Officers’ Liability for Supervision and Management: Exploring the Intersection of Corporate and Tort Law, 59 American University Law Review 1661 (2010). 75 DEL. CODE ANN. tit. 8, § 141(e).

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Moreover, board decisions are protected by the business judgment rule, which stipulates that with the proviso that directors’ decision-making process meets certain criteria courts will not second-guess their actions.76 It is characteristic that Delaware law allows shareholders to adopt exculpatory provisions in the certificate of incorporation to restrain or eradicate directors’ personal liability for monetary damages for duty of care but not loyalty violations.77 Moreover, these limitations, together with corporate indemnification arrangements and D&O liability insurance, have become so noticeable that the expectation of liability has become unlikely.78 Hence, Directors and officers rarely face civil liability for breaching their fiduciary duties, irrespective of the forum in which shareholders bring suit and regardless of corporate law rhetoric stressing the significance of executives’ fiduciary responsibilities. It is worth noting that officers are subjected to higher possible liability than directors, given their deeper connection in the daily management and the lesser degree of legal protections. Officers are entitled to indemnification and their firm may have insurance in place to protect them from out of pocket payments. Nonetheless, fiduciary duty lawsuits against officers have been rare and the probabilities of being held personally liable are low for them as well.79 It could be said that the present system of managerial liability is first and foremost geared toward reducing personal transgressions, that is, misconduct by persons that are careless or otherwise, and for selfish reasons, act against their firms and shareholders’ interests. Moreover, shareholder fiduciary duty litigation serves the objectives of ex ante deterrence and, to a lesser degree, ex post compensation.80 From a corporate governance standpoint, derivative actions are illustrated as the counterweight to managerial power and a mitigation device against agency costs.81 Moreover, the present system’s physiognomies raise questions about its suitability for a future move from human to AI corporate management. Hence, today’s context is

76

Brehm v. Eisner, 746 A.2d 244, 264 n. 66 (Del. 2000). DEL. CODE ANN. tit. 8, § 102(b)(7). Note that § 102(b)(7) does not allow eradicating personal liability for breaches of the duty of care if the underlying acts or omissions were not in good faith. Del. Code Ann., tit. 8, § 102(b)(7)(ii). 78 Lisa L. Casey, Twenty-Eight Words: Enforcing Corporate Fiduciary Duties through Criminal Prosecution of Honest Services Fraud, 35 Del. J. Corp. L. 1, 17 (2010); Bernard Black et al., Outside Director Liability, 58 Stan. L. Rev. 1055, 1140 (2006) (suggesting that out of pocket payments by directors are as infrequent as an “occasional lightning strike”). 79 Lyman P.Q. Johnson & David Millon, Recalling Why Corporate Officers are Fiduciaries, 46 WM. & Mary L. Rev. 1597, 1609 (2004); Megan Wischmeier Shaner, Officer Accountability, 32 Ga. St. U. L. Rev. 357, 367 (2016) (confirming empirically the low number of fiduciary duty lawsuits against officers). 80 American Law Institute, Principles Of Corporate Governance: Analysis And Recommendations Part VII, Introductory Note, Reporter’s Note 2 (1994); John C. Coffee, Jr. & Donald E. Schwartz, The Survival of the Derivative Suit: An Evaluation and a Proposal for Legislative Reform, 81 Colum. L. Rev. 261, 302–04 (1981). 81 David Kershaw, Company Law In Context: Text And Materials 506 (2012) (noting that fiduciary duties may “allow the agency cost to be drained away”). 77

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essentially based on the notion of personal accountability in the sense of individual liability of corporate leaders that breach their fiduciary duties, which means that in the absence of human managers, this kind of personal liability is bound to fade. It is characteristic that in the early stages of a gradual path toward AI-dominated management, it is expected that AI taking on certain roles such as acting principally as a supportive mechanism for human directors leading to a reduction in the number of human managers. Accordingly, during this earlier phase, personal liability lawsuits would be focused on relatively fewer individuals, explicitly those humans that still remain in managerial positions, which intensify their exposure.

4.5

AI’s Managerial Involvement

The question to be answered is to what extent human managers may assign tasks to and counts on advice given by AI and to what extent they can and should supervise AI. Moreover, whether reliance and delegation of tasks to AI is allowed depends on the wording and interpretation of applicable statutory provisions and corporate documents. Characteristically, corporate law compels directors to monitor delegated tasks and does not permit boards to delegate away the central duty to manage and supervise the firm. Could directors be obliged to use or delegate tasks to AI as part of their obligation acting on an informed basis? It is feasible that such a duty might develop in the near future, accompanied by the more general board task of exercising “governance of artificial intelligence,” which means that under the present agenda, a complete delegation of tasks to AI would not be permitted. On the other hand, there is the idea of creating a legal status for artificial persons. It could be said that at the beginning the board will monitor the partial managerial activities of AI, and so directors will oversee the selection and activities of robots, algorithms and artificial intelligence devices needing to have an understanding of how these devices function. Moreover, while directors usually do not understand their coding, they should be able to understand the technical guidelines that drive these machines.82 In a second stage following a time of co-existence of human and AI managers, machines will fully take over the tasks of corporate management, which means that there would be no more humans that could be sued for fiduciary duty breaches leading to new approaches to managerial liability. It could be said that artificial entities acting as managers could become prospective defendants and be sued, the system of managerial liability will be eliminated and not replaced and those responsible for generating or distributing/selling artificial managers represented by AI software and hardware will substitute managers as potential defendants.

82 Matthew U. Scherer, Of Wild Beasts and Digital Analogues: The Legal Status of Autonomous Systems, 19 NEV. L. J. 259 (2018).

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It is worth noting that governmental control of algorithms and new enforcement mechanisms will be needed for the reason that the control of algorithms necessitates a comprehensive technical know-how that can neither be anticipated from shareholders, nomination committees, or supervisory boards, nor from courts. It could be said that the same is applicable for instances of direct claims by shareholders against directors. Moreover, corporations that use AI management systems might bring actions against providers, based on contractual or extra-contractual grounds and in cases where owing to faults in the system the corporation suffered direct or indirect harm.83 It is obvious that the rise of artificial managers will coincide with the rise of large commercial providers of corporate management software, in view of the advantages of scale in terms of data collection. It has to be taken into account that size is beneficial from a liability perspective due to the fact that large, deeply capitalized providers with a broadly used product will be in a better position to circumvent liability through better services but also to resist financial strains in the case of liability payouts, embracing external insurance solutions.84 It is expected that in the future businesses that might operate without any ongoing human involvement will emerge.85 There are already algorithmic entities such as computer viruses, once programmed and released, can act and survive autonomously. Moreover, advanced forms of such algorithms could conduct business, and so an algorithm could roam cyberspace with its own wallet and its own capability to learn and adapt, in search of its aims determined by a creator, and so obtaining the resources it needs to continue to exist like computer power while selling services to other entities.86 On the other hand, currently algorithms are not legal entities, which limit their practical use and capacities to transact business which means that there is a need for a legal regulation, and so it is imminent the emergence of lawful autonomous algorithms named algorithmic entities (AEs), which combine algorithms with legal entities.87 Hence, AEs are comprised of a legal entity that offers the shell for a software/algorithm that is in control of the entity without human involvement. It has to be taken into account that the significance of an algorithm’s capacity to control a

83

Angela Walch, In Code(rs) We Trust: Software Developers as Fiduciaries in Public Blockchains, in Regulating Blockchain: Techno-Social And Legal Challenges (Philipp Hacker et al., eds, 2019). 84 E. M. Dodd, Jr, For Whom are Corporate Managers Trustees?, 45 Harv. L. Rev. 1145 (1932); Adolf A. Berle, For Whom Corporate Managers are Trustees: A Note, 45 Harv. L. Rev. 1365 (1932). 85 Lynn Stout, The Corporation and the Questino of Time, in Understanding The Company 305–11 (Barnali Choudhury & Martin Petrin, eds., 2017); Tamara Belinfanti & Lynn Stout, Contested Visions: The Value of Systems Theory for Corporate Law, 166 U. Pa. L. Rev. 579, 605–18 (2018) (both applying insights from systems theory to the corporate purpose debate). 86 Don Tapscott & Alex Tapscott, Blockchain Revolution 123 (2016). 87 Lynn M. Lopucki, Algorithmic Entities, 95 Wash. U.L. Rev. 887 (2018); Shawn Bayern, The Implications of Modern Business-Entity Law for the Regulation of Autonomous Systems, 19 Stan. Tech. L. Rev. 93 (2015).

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legal entity is that it generates legal rights for the algorithm and so enabling and legitimizing its capacity to transact in the “real world.” Thus, taking into account that the legal entity’s rights essentially become the algorithm’s rights, then an AE will enjoy rights such as the right to privacy, to own property, to enter into contracts, to be represented by counsel, to be free from arbitrary search and seizure, to equal protection of the laws, to speak freely, and to spend money on political operations. In other words, an AE will take part successfully in legitimate economic and political doings participating in business, accumulate wealth, or deal with people in the above-ground economy and so opening up totally new opportunities. Furthermore, self-managed AEs are already conceivable when it comes to simpler applications, and so current algorithms could autonomously and self-sufficiently run profitable businesses. It is obvious that this is easily accomplished for a number of activities along those that have been recognized as doings for algorithmic entities such as cloud storage, bike rental, online gambling, vending machines, and services like those of Uber and Airbnb. Hence, as AI advances more, complex ventures will be within reach, which means that new generations of algorithms will advance their own software, adapt to new business models, and discover and enter new activities. Taking into consideration that the current corporate laws restrict board membership to natural persons contradicting AEs, there is a need for legal reform. LoPucki88 presumed that “formation of AEs is probably possible under the LLC statutes of all, or nearly all, U.S. jurisdictions” and “the formation of AEs is probably possible under the Delaware General Corporation Law, the Model Business Corporation Act, the Uniform Limited Partnership Act, the Uniform Limited Liability Company Act, and the Revised Uniform Partnership Act.” Nonetheless, there is uncertainty concerning the legality of AEs since to date neither legislatures nor courts have considered and condoned them, and so the possible outcomes of AEs and their activities are also uncertain. On the one hand, AEs could support and offer benefits to particular groups by pursuing beneficial effects. On the other hand, due to their lack of human compassion, their capacity to replicate AEs’ advantage is concentrated in fields such as in criminal enterprise, which means that AEs are ideal for illegal or otherwise highly undesirable activities embracing terrorism, harassment and malicious acts, political and other manipulation, and liability evading. It has to be taken into consideration that in the distant future it is possible that AI takes over corporate management, but humans will have the final word on the applied AI technology regardless that some parts of a mechanical networking will be management via artificial intelligence. The prospect of artificial intelligence taking over from humans the running of human life is minimal unless the humans

88

Lynn M. Lopucki, Algorithmic Entities, 95 Wash. U.L. Rev. 887 (2018); Shawn Bayern et al., Company Law and Autonomous Systems: A Blueprint for Lawyers, Entrepreneurs, and Regulators, 9 Hasting Sci. & Tech. L.J. 135 (2017).

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are eradicated as humans’ nature, and there will emerge a mechanically self-operated robot anticipating human functioning. There are efforts to generate and establish machine-led corporate leadership and for the reason that AI management will be both better and more cost-effective than the use of human managers presumably at some point, “management by machine” appears inevitable. On the other hand, there is a growing terror concerning the dangers of AI leading to the end of mankind. Besides, the fact of AI replacing entirely management seems far more modest for the reason that AI management will materialize in a certain degree having consequences for corporate governance but not eliminating humans as the strategic leaders of the whole advancement. Hence, with software and machines in charge, the need for a collective board will diminish, followed by the two-tier board-management structure, which might be replaced with a single “fused” corporate management function in the very distant future. On the other hand, it cannot be rejected entirely the shift from human to AI-based management necessitating alterations to the system of managerial liability. It is expected the development of a system akin to products liability replaces the framework based on fiduciary and other personal duties, and so the central purpose of corporations will be affected by AI management permitting more complex and defined calibrations of corporate objectives, accompanied by amplified clarity and transparency. Hence, the materialization of legal entities operating without any human input whatsoever, algorithmic entities, seems plausible, which indicates the need for legal reform to accommodate alterations brought about by new technologies. Furthermore, the proposed legal alterations have to both enabling/aiding the efficiencies and other beneficial outcomes of AI management but also protecting society from negative influences such as loss of employment to harmful actions by AI entities. In addition, corporate governance and generally management will be intertwined with business analytics, Big Data, and programming. The prospect of AI management could mean that agency costs between shareholders and management could be solved with AI management. In line, M. Petrin89 argues that “the development of ex ante standards for designing, controlling, and holding accountable algorithms will take center stage. This can be thought of as a novel type of agency costs, now between humans and machines, which may come to the fore. On all counts, AI management seems set to initiate a new chapter for corporate law and governance.” It is worth noting that conflicts happen between directors’ self-interest and the interests of the corporation, between duties owed to more than one firm or principal or between the interests of different stakeholders.90 Moreover, directors are

89

Martin Petrin Corporate Management in the Age of AI (No.3/2019) UCL Working Paper Series https://ssrn.com/abstract¼3346722. 90 Financial Reporting Council, UK Corporate Governance Code (2018); Financial Reporting Council, Guidance on Board Effectiveness (2018); Department of Business, Energy and Industrial

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confronted by various conflicts, often encompassing practical and regulatory complexity, and so many directors hold more than one board position, giving rise to prospective conflicts between the interests of each firm. Furthermore, directors are appointed as nominees or to the board of one or more group companies, also raising potential conflicts, and so directors come across attractive opportunities, which means that the tolerability of directors utilizing such opportunities in a personal capacity or via another corporate vehicle is the theme of contention and confusion. Hence, directors’ transactions with the firm raise concerns concerning conflicts and the desire to benefit oneself is one against which equity has long taken a strict attitude, and so the fiduciary duties to escape unauthorized conflicts and profits compel prophylactic constraints. In addition, the general law duties have been supplemented in a number of law jurisdictions by statutory duties (Companies Act 2006), and so in the UK, statutory duties have replaced the original general law duties such as the duty to act within powers (s 171), the duty to stimulate the success of the company for the benefit of the members as a whole (s 172), the duty to exercise independent judgment (s 173), the duty to exercise reasonable care, skill, and diligence (s 174), the duty to avoid conflicts of interest (s 175), the duty not to accept benefits from third parties (s 176), and the duties to declare an interest in a proposed or existing transaction or arrangement (ss 177 and 182). Moreover, some jurisdictions regulate specific standpoints of the broader prohibitions embracing substantial property transactions, loans to directors, and related party transactions that are built on the initial fiduciary duties of directors, which continue to apply in other common law jurisdictions. A final form of conflict faced by directors involves the interests of stakeholders such as creditors, customers, the environment, and the community. Nevertheless, conflicts between the interests of numerous stakeholders occur, and so directorial decision-making implicates balancing the competing interests of stakeholders, which means that the question to be answered is to what extent such interests are protected and promoted within the lines of current directors’ duties. It is worth noting that the regulation of conflicts stems from the fiduciary nature of the relationship between director and company, and so a critical examination of fiduciary principles is central in any comprehensive analysis of directors’ conflicts.91 How managers forecast physiognomies alter so as to manage lender expectations? It is worth noting that expectations management is a key drive for management forecasts92 that are used as a device to accomplish the expectations of analysts and investors. It has to be taken into consideration that small mining businesses without internal sources of finance, debt finance, and ongoing support of the lender are Strategy, Corporate Governance Reform—The Government Response to the Green Paper Consultation (August 2017). Commonwealth of Australia, Royal Commission into Misconduct in the Banking, Superannuation and Financial Services Industry (2017–19). 91 Item Software (UK) Ltd v Fassihi [2004] EWCA Civ 1244; [2005] 2 BCLC 91; Adler v Australian Securities and Investments Commission (2003) 46 ACSR 504, 618. 92 Kato, K., Skinner, D. J., & Kunimura, M. (2009). Management forecasts in japan: an empirical study of forecasts that are effectively mandated. The Accounting Review, 84(5), 1575–1606.

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essential to developing high-risk projects, without which project development, production, and cash flow generation are not possible, which means that managers of small businesses have added incentives to manage expectations of project financiers and to manage forecasts accordingly. On the other hand, it is argued that greater leverage expands forecast accuracy due to monitoring benefits. Nonetheless, Hutton et al.93 advise that managers in high information asymmetry situations, where managers have an information advantage, can decide to issue less accurate forecasts where they have incentives to do so. In other words, the receipt of Project Finance (PF) approval alters managers’ incentives in terms of both forecast accuracy and bias such that managers are stimulated to meet the prospects of the new lender, which means that the new lender is the target of this expectation’s management because of the limited analyst coverage of small mining businesses and high information asymmetry present in businesses94 previously all equity financed. A. Ferguson, G. Pündrich95 argue that “after PF, the cash outflow forecast bias increases, but only for overestimates, with no difference for underestimates. Examining the timing of the overestimation, we find that managers are more likely to create budget slack while debt tranches remain to be drawn, coinciding with the high-risk mine construction phase. These results robust to using a propensity score matching approach.”

4.6

AI and Vehicles

The majority of vehicles on California’s vast network of roads make considerable use of information technology.96 It has to be taken into account that the extent to which a manufacturer properly represents to consumers or regulators the competence of an autopilot function that falls short of full automation competency causes plenty of legal issues under contract law, tort law, and consumer protection statutes and regulations.97 Since autopilot systems are comprised of computers, sensing

93 Hutton, A. P., Lee, L. F., & Shu, S. Z. (2012). Do managers always know better? The relative accuracy of management and analyst forecasts. Journal of Accounting Research, 50(5), 1217–1244. 94 Brown, P., Feigin, A., & Ferguson, A. (2014). Market reactions to the reports of a star resource analyst. Australian Journal of Management, 39(1), 137–158. Grossman, S. J. and Hart, O. 1982, ‘Corporate financial structure and managerial incentives’, The Economics of Information and Uncertainty, pp. 107–140. 95 Andrew Ferguson, Gabriel Pündrich, Mandatory management forecasts and lender expectations management, https://ssrn.com/abstract¼3382942 P30. 96 David Welch & Elisabeth Behrmann, Who’s Winning the Self-Driving Car Race?, Bloomberg (May 7, 2018), https://www.bloomberg.com/news/features/2018-05-07/who-swinning-the-selfdriving-car-race (noting that the “road to autonomy is long and exceedingly complicated”). 97 Tesla Autopilot—Review Including Full Self-Driving for 2019, AutoPilot Review, https://www. autopilotreview.com/tesla-autopilot-features-review (describing Tesla’s self-driving capabilities). Edvard Pettersson & Dana Hull, Tesla Sued over Fatal Crash Blamed on Autopilot Malfunction,

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hardware, and guidance programs, an autopilot system will generate and analyze information utilizing the surrounding environment to adapt and make alterations based on the vehicle’s course of action in reaching the final destination. However, human monitoring and intervention are still needed. Undeniably, it is far from clear whether a perception such as “full” automation is even viable when tasks that humans bundle into a single category, such as driving, are easily disaggregated into distinct subfunctions that require separate automation processes or degrees of human interaction, and when consumers routinely use available technologies in ways that fail to correspond to prescribed limits.98 The SELF DRIVE Act, 2017 was enacted to ascertain the federal role to make certain the safety of highly automated vehicles by enacting laws concerning the design, construction, or performance. Also, the manufacturers have to develop written cybersecurity and privacy plans for such vehicles. It is worth noting that humans will be shaped in subtle but possibly enormously consequential ways by AI techniques influencing the flow of information, the distance between cars, or the timing of persuasive messages, for example. Up till now, when we share the road, and indeed the globe, with artificially intelligent systems, the direction of influence can also run in the opposite direction: Certainly, the coevolution of human and artificial intelligence is well on its way to becoming routine.

References 1. Walch, A. (2019). In code(rs) we trust: Software developers as fiduciaries in public blockchains. In P. Hacker, et al. (Eds.), Regulating blockchain: Techno-social and legal challenges. 2. Reese, B. (2018). The fourth age: Smart computers, conscious computers, and the future of humanity. 3. Commission Staff Working Document, Evaluation of the Machinery Directive, SWD(2018) 161 final. 4. Rudin, C., & Ustun, B. (2018). Optimized scoring system: Towards trust in machine learning for healthcare and criminal justice. Interfaces, 48, 449. 5. Welch, D., & Behrmann, E. (2018, May 7). Who’s winning the self-driving car race? Bloomberg. 6. Kershaw, D. (2012). Company law in context: Text and materials. 7. Tapscott, D., & Tapscott, A. (2016). Blockchain revolution, 123. 8. Lopucki, L. M. (2018). Algorithmic entities. Washington University Law Review, 95, 887.

Bloomberg (May 1, 2019), https://www.bloomberg.com/news/articles/201905-01/tesla-sued-overfatal-crash-blamed-on-autopilot-navigation-error. 98 Meredith Whittaker et al., AI Now Report 2018, at 10–11 (2018), https://ainowinstitute.org/AI_ Now_2018_Report.pdf (describing the variety of settings where people routinely interact with systems displaying characteristics of artificial intelligence, and the broad range of functions performed); Ted Greenwald, What Exactly Is Artificial Intelligence, Anyway?, Wall St. J. (Apr. 30, 2018), https://www.wsj.com/articles/what-exactly-is-artificial-intelligenceanyway1525053960.

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9. Murgia, M. (2019, February 13). How to stop computers being biased. Financial Times. 10. Scherer, M. U. (2018). Of wild beasts and digital analogues: The legal status of autonomous systems. Nevada Law Journal, 19, 259. 11. Petrin, M. Corporate management in the age of AI (No.3/2019). UCL Working Paper Series. 12. Bostrom, N. (2017). Superintelligence: Paths, dangers, strategies. 13. Burrdige, N. (2017, May 10). Artificial intelligence gets a seat in the boardroom. Nikkei Asian Review. 14. OECD. (2015). G20/OECD principles of corporate governance. 15. Scharre, P. (2016). Century, autonomous weapons and operational risk. Center for a New American, 39. 16. Hartford, T. (2019, February 22). Expect mischief as algorithms proliferate. Financial Times. 17. Kolbjørnsrud, V., et al. (2016, November 2). How artificial intelligence will redefine management. Harvard Business Review Online. 18. Yudkowsky, E. (2008). Artificial intelligence as a positive and negative factor in global risk. In M. Cirkovic & N. Bostrom (Eds.), Global catastrophic risks.

Chapter 5

Risk Management Developments

5.1

Risk, GDPR, and AML

Risk is a tool which makes possible the decision-maker to get knowledge about the event with destructive effects and so, the decision-maker via the analysis of risk makes the event more certain and obtaining control on it. Hence, risk is “an objective measurable entity combining the probability of an adverse event and the magnitude of its consequences.”1 Moreover, the risk assessment carried out by the obliged entity has to be comparable to the nature and size of the business. GDPR regulates the processing by an individual, a corporation or an organization of personal data concerning individuals in the European Union.2 Across the EU, the General Data Protection Regulation (EU) 2016/679 (GDPR) is in place to cope with the tech companies’ misuse of information, while the European Commission has produced ethical guidelines for AI.3 EU political guidelines concerning AI is focused on utilizing the benefits of AI through digital transformation and uptake, and mitigation of risk though suitable legal and institutional frameworks.4 Moreover, the white paper also recognizes that the EU has to function in an apt way to make certain that trust in the governing

Gellert R., ‘Understanding Data Protection as Risk Regulation’, p. 8, Peel, J. (2010). Science and Risk Regulation in International Law. Cambridge, UK: Cambridge University Press. Gellert R., ‘Understanding Data Protection as Risk Regulation’, Journal of Internet Law, vol. 18(11), (2015), p. 8. 2 Regulation 2016/679, the new General Data Protection Regulation entered into force in May 2018. 3 European Commission High Level Group on Artificial Intelligence (2019) Ethics Guidelines for Trustworthy AI. https://ec.europa.eu/digital-single-market/en/news/ethics-guidelinestrustworthy-ai. C. Cath, S. Wachter, B. Mittelstadt, M. Taddeo, L. Floridi (2017) Artificial Intelligence and the ‘Good Society’: The US, EU, and UK approach. Sci. Eng. Ethics 2017, 1–24. 4 White Paper On Artificial Intelligence – A European approach to excellence and trust Brussels, 19.2.2020 COM(2020) 65 final. European Commission, ‘Communication on Building Trust in Human-Centric AI’ COM (2019) 168. 1

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structures is preserved and avoiding fragmentation of the single market owing to a lack of a common and scaled European approach. Furthermore, the white paper is ambiguous but some parts signify clear openness to regulation and other parts reiterate that legislation can be updated, amended. Taking into account how fast AI is developing, the regulatory framework must leave room to provide for further developments but changes are limited to identified problems for which feasible solutions exist. While in EU product safety legislation software, when it is part of the final product, must comply with the relevant product safety rules; it is an open question whether it is. E. Kazim and A. Koshiyama5 argue that “the white paper, and the EU’s strategy at large, is ambiguous and lacks vision, which, if unchecked, is likely to have a negative impact on EU competitiveness in the development of AI solutions and services.” It is worth noting that European data protection law had to face several challenges owing to the event of the cyberspace age. The response to these challenges and the huge desire of the EU to keep the legal framework update led to the replacement of the old Data Protection Directive with the new Regulation.6 GDPR regulates the processing by an individual, a corporation or an organization of personal data concerning individuals in the European Union.7 The flow of data through the cyberspace boosted dramatically, people nowadays share their data more easily compared to the past and the ways to do so boosted as well.8 Moreover, both private businesses and public authorities use individuals’ personal data to accomplish their business or their activities. In addition, the economic and social integration among the States of the EU augmented the exchange of data from one country to another and so, the sharing of data influences different levels: public and private players and as well national authorities.9 While compliance with existing data protection laws is central, a long-lasting approach is to examine the challenges presented by AI and so, AI utility devices are used gradually by both private and public sector organizations around the globe. The new regulatory model put in place in the GDPR is “an enforced selfregulation” and so, there is an alteration from a “formal legality of processing of data and enforcement of individual rights against companies” to a regulation managing technological innovation. Digital innovation generated complex risks which means that the character of the new risk needs to be approached in a different way compared to the one used in the previous Directive and so, the data controllers are at

5

Emre Kazim, Adriano Koshiyama, Lack of Vision A Comment on the EU’s White Paper on Artificial Intelligence, https://ssrn.com/abstract¼3558279 p. 1. 6 Koops BJ, ‘The trouble with European data protection law’, International Data Privacy Law, 2014, Vol. 4, No. 4, p. 250. 7 Regulation 2016/679, the new General Data Protection Regulation entered into force in May 2018. 8 Recital 6 of GDPR. 9 Recital 5 of GDPR.

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the center of the game, they are the protagonists.10 It is worth mentioning here that Heiman11 considers that “the GDPR is fundamentally flawed. Key terms within the GDPR are undefined; the burdens of the GDPR will fall heaviest on small businesses; the GDPR disrupts a valuable business model; the GDPR will stymie growth, innovation, and information sharing; and it may be the product of protectionist impulses rather than concerns for consumer welfare.” Are AI systems compatible with the GDPR? AI adds a new wrinkle linked to the explainability of algorithms and so, AI makes new clusters of bank customers based on risks and relationships that are not visible to humans. It is argued that an AI-based system to detect suspicious transactions has to satisfy the proportionality test of the CJEU. The Anti-Money Laundering Directives established a competent legal framework to fight against money laundering and terrorist financing. The requirement to accept amendments to the previous Directive was born in 2016, after the terroristic attacks in Europe and the revelations of the Panama Papers.12 It is worth noting that the GDPR and the AML Directive have one aspect in common: they are both constructed following a risk-based approach.13 It has to be taken into account that risk embraces the likelihood that human actions and/or events out of human control would lead to outcomes that threaten and harm individuals, governments, or corporations. Moreover, in the public sector and at the government level, there is the demand to find a solution on how to administer the risk which means the course carried out by institutions, agencies, societal groups, or individuals to comprehend whether the risk is acceptable or not. Furthermore, when coping with risk, there are two key setbacks and concerns interrelated to the analysis on uncertainty. On the one hand, the data linked to risk cover a large section of the population and it involves a large amount of time and, on the other hand, a key matter is connected to random events and lack of knowledge of the subjects who are supposed to cope with the risk. To that extent, the risk-based approach has its foundation in art. 24 and art. 25(1) of the GDPR expressing the risk-based approach in the GDPR. Art. 24 lays down the new responsibilities for data controllers in the Regulation and the risk-based approach is grounded on identifying the “likelihood and severity” of the risk of a particular data processing and its effect has on entity’s rights. In addition, the risk-based approach is connected to art. 25 of the GDPR which means that

10 Spina A., ‘A Regulatory Mariage de Figaro: Risk Regulation, Data Protection, and Data Ethics’, European Journal of Risk Regulation, 8 (2017). 11 Matthew R. A. Heiman The GDPR and the Consequences of Big Regulation, 47 Pepp. L. Rev. 945 (2020) Available at: https://digitalcommons.pepperdine.edu/plr/vol47/iss4/3 p. 945. 12 European Commission, ‘Statement by First Vice-President Timmermans, Vice-President Dombrovskis and Commissioner Jourovà on the adoption by the European Parliament of the 5th Anti-Money Laundering Directive’, (2018). The Fifth Anti-Money Laundering Directive (Directive 2018/843) has been adopted on the 19th of April 2018, this new version of the Directive amended the previous one (Directive 2015/849). 13 Klinke A. and Renn O., ‘A new approach to risk evaluation and management-risk-based, precaution-based, and discourse-based strategies’, Risk Analysis, Vol. 22(6), (2002), p. 1071.

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controllers have the chance to approve an adaptable tactic deciding how to allocate their resources so as to diminish the risk related to data protection and with the purpose of guaranteeing a high level of protection for rights and freedoms. The risk-based approach in the GDPR compels that, on the one hand, data controllers have to employ suitable technical standards to be compliant. On the other hand, the measures accepted by the data controllers have to be adjusted and in accordance with the risk posed by the processing of data.14 Another important aspect of the risk-based approach in the GDPR is the role of art. 35 by introducing the data protection impact assessment. The DPIA is compulsory for certain data processing that is “likely to result in a high risk to the rights and freedoms of natural persons”. Moreover, the DPIA is an instrument and a systematic one demanding data controller to carry out a data protection impact assessment prior the data processing, plus a second obligation of reviewing the DPIA whether something altered in the handling or whether the risk altered.15 It is worth noting that the Council of Europe expresses the risk-based approach in the AML in the following manner: “A risk-based approach means that countries, state authorities, as well as the private sector should have an understanding of the ML/TF risks to which they are exposed and apply AML/CFT measures in a manner and to an extent which would ensure mitigation of these risks ... A risk-based approach therefore consists of the identification, assessment and understanding of risks, as well as the consequent application of AML/CFT measures commensurate to these risks in order to ensure an effective mitigation thereof.”16 Moreover, the risk-based tactic in the AML Directive is expressed at three different levels. The FATF guidance asserts that the risk-based approach encompasses three players: countries, supervisory authorities, and financial institutions. Those are the “experts” that must ascertain, assess, and understand the money laundering and terrorism financing risks and they must be able to take all the Quelle C., ‘Enhancing Compliance under the General Data Protection Regulation. The risky Upshot of the Accountability- and Risk-based Approach’, European Journal of Risk Regulation, 2018, p. 3. Gumzej N., ‘Law and Technology in Data Processing: Risk-Based Approach in EU Data Protection Law and Implementation Challenges in Croatia’, MIPRO, (2017), p. 1427. Quelle C., ‘The ‘risk revolution’ in EU data protection law: We can’t have our cake and eat it, too’, Tilburg Law School, Legal Studies Research Paper Series, (2017), p. 9. CIPL, ‘Risk, High Risk, Risk Assessments and Data Protection Impact Assessments under the GDPR’, GDPR Interpretation and Implementation Project, (2016), p. 12–13. 15 Kloza D., Van Dijk N., Gellert R., Böröcz I., Tanas A., Mantovani E. and Quinn P., ‘Data protection impact assessments in the European Union: complementing the new legal framework towards a more robust protection of individuals’, d.pia.lab Policy Brief No. 1/2017, (2017), p. 3. European Commission, Commission Staff Working Paper, Sec(2012) 72 Final, (2012), p. i, quote. The DPIA was defined by the EU Commission as: “. . . a process whereby a conscious and systematic effort is made to assess privacy risks to individuals in the collection, use and disclosure of their personal data. DPIAs help identify privacy risks, foresee problems and bring forward solutions.” 16 Committee of Experts on the Evaluation of Anti-Money Laundering Measures and the Financing of Terrorism, ‘Risk-based approach’, Council of Europe Portal. (https://www.coe.int/en/web/ moneyval/implementation/risk-based-approach). 14

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measures comparable to the risk and so, these measures must diminish the risk. Moreover, countries should carry out a risk assessment to be aware of the money laundering risk in the territory of the State which means that the supervisory authorities must assess the result of the assessment handled by the countries, but at the same time, they have to expand their own strategy so as to make the anti-money laundering measures more successful. To that extent, the third level encompasses the obliged entities.17 In both the GDPR and the AML Directive, the adoption of the risk-based approach is due to the fact that in both sectors, the financial one and the privacy one, happenings on a global scale confront the old regulatory system. On one side, a flow of people’s data used by private and public entities at a European and global level. On the other side, the reinforcing of terrorism financing and money laundering that have overlapped national borders to turn into international happenings. To that extent, the new technologies and the fast evolution of cyberspace and a diverse use of it, are two extra features that the privacy and the financial sector have in common. Moreover, there are new users’ generations that via cyberspace and new apps are sharing their data more than in the past. On the other side, there is a new generation of criminals utilizing new technologies to serve their criminal objectives and so, the European legislator embraced, in both sectors, a modification in the regulatory strategy from a strict top-down tactic to a self-regulatory strategy. To that extent, the European legislator left the managements of the risk correlated to these alterations directly to the financial institution and to the data controller.18 Thus, in both sectors, the regulator has altered the regulatory line because of the possibility to have a tailored approach to the risks created by money laundering and the use of data, the use of the knowledge of the AML experts and privacy experts, and more in general, the use of the knowledge of the corporations. It could be said that the analysis of risk in the GDPR stipulates that the risk-based method does not shift the emphasis of the data controllers from their own legal obligations allowing data controllers to adjust those obligations. Besides, for the AML Directive, the risk-based method gives the opportunity to the obliged entity to choose which kind of CDD actions they must take. Obliged entities and data controllers have a kind of discretion leading the data controllers and the obliged entities to a possible failure of the objectives settled by the regulators.19

FATF, ‘Guidance for A Risk-Based Approach’, (2014), p. 3–6. Quelle, ‘Privacy, Proceduralism and Self-Regulation in Data Protection Law’, (2017), p. 106. Koops BJ, ‘The trouble with European data protection law’, International Data Privacy Law, Vol. 4 (4), (2014), p. 254. Gonçalves ME, ‘The EU data protection reform and the challenges of big data: remaining uncertainties and ways forward’, Information & Communications Technology Law, (2017), p. 15. 19 King G, Anti-Money Laundering: An Overview, in King G, Walker C., Gurule J, The Palgrave Handbook of Criminal and terrorism Financing Law, (Palgrave Macmillan, 2018). Van Duyne P.C, Harvey J. Gelemerova L, A ‘Risky’ Risk Approach: Proportionality in ML/TF Regulation, in King G., Walker C., Gurule J, The Palgrave Handbook of Criminal and terrorism Financing Law, (Palgrave Macmillan, 2018). 17 18

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While the United States has a less protective privacy model than Europe, comparisons of enforcement practices seem to indicate that privacy outcomes are not dramatically different. Europe’s General Data Protection Regulation (GDPR) generates a strict regulatory framework for data encouraging countries to conjoin around its model, by this means setting a de facto global standard. Many countries are working to accomplish GDPR “adequacy”, and several new laws have been adopted in countries such as China and Brazil that look very similar to GDPR. Moreover, China recently approved a security law that obliges all foreign corporations to localize data about Chinese consumers within China’s borders. It is worth noting that across the United States and Europe, notice and consent, the act of clicking that “I have read and agree” to a platform’s terms of service, is the central device for legitimating and enabling platforms’ data processing. When attempting to create an account on a commercial site, people read a set of Terms of Service, these contractual terms, alongside multiple annexed clauses and webpages, form the basis of a user’s contractual agreement, an agreement which, among other things, broadly regulates the types of data that the commercial site can collect from its users and the feasible uses it can make of such data. Thus, increasing risks are attached to intrusive data harvesting practices, embracing the targeting of content and ads based on a person’s personal features. Moreover, the law has to restrict dataflows and hold corporations accountable by determining the kinds of information that should and should not be engendered, collected, and used. In the United States, privacy self-management is the principal check on corporations’ capability to engage in data-driven activities as they wish, albeit being a voluntary and self-regulated practice.20 European Union has a more substantive approach to consent based on informational self-determination and so, the burden of proving valid consent is greater, as consent has to be informed, exact, unambiguous, freely given, and consent is not the only basis for lawful processing.21 Up till now, even the European approach places emphasis on informed consent. On the one hand, consent operates as an authorizing mechanism for corporate actions, shielding the actors from otherwise legitimate complaints. On the other hand, consent operates as an enabling device for corporations, and the flipside is that it deprives users of some of their complaints against platforms. As a matter of contract law, the enforceability of digital privacy policies has been held unenforceable either because they were not considered to be binding under contract law, or for failure to show the harm suffered.22 It has to be taken into 20 Data Policy, Facebook, https://www.facebook.com/about/privacy Daniel J. Solove & Woodrow Hartzog, The FTC and the New Common Law of Privacy, 114 Colum. L. Rev. 583 (2014). (the FTC has a role in bringing civil actions against entities that engage in unfair or deceptive acts or practices in or affecting commerce under 15 U.S.C.S. § 45 (LEXIS through Pub. L. 116-72)). 21 Gen. Data Protection Reg. 2016/679 of Apr. 27, 2016. 22 Allyson W. Haynes, Online Privacy Policies: Contracting Away Control over Personal Information?, 111 PENN ST. L. REV. 587, 594 (2007). In re JetBlue Corp. Privacy Litig., 379 F. Supp. 2d (E.D.N.Y. 2005); Dyer v. Northwest Airlines Corps., 334 F. Supp. 2d (D.N.D. 2004); In re

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account that the ideal of autonomous consent cannot be reached in practice in the platform economy for the reason that the conditions which constitute consent as a morally transformative device are absent and so, consent is structurally incapable of empowering individuals in the platform economy. In reality, scrolling through a web page or clicking on the “download” button for a new software product has been held insufficient to constitute assent to the underlying terms and conditions and so, such browsewrap agreements have been enforced in cases where the relevant link or pop-up was repeatedly brought to a consumer’s attention and the consumer was held to have had an opportunity to walk away, and therefore, have assented.23 Clickwrapcontracts, which compel the positive ticking of a box unambiguously indicating that one has read and understands the terms and conditions, have instead generally been enforced.24 It could be said that consent to terms is enough as long as the customer has the capacity to read and understand the terms. AI is transforming AML systems via automate data collection, enhance the client risk scoring and the alert prioritization processes, leverage link analysis, expand segmentation either by identifying known suspicious patterns or by discovering new ML patterns. The level of intrusiveness is already high under existing AML processes, as current rule-based TMS algorithms already analyze transaction data to produce risk profiles and alerts. It has to be taken into account that the use of machine learning techniques aggravates the problem owing to the opacity of the algorithms and so, AML systems impact on privacy rights engaging analysis of massive and particularly sensitive bank transaction data, the creation of individual profiles, and possible reports of suspected criminal offences to law enforcement authorities. Moreover, ML may also interfere with the right to non-discrimination, for the reason that TMSs may engender more alerts for certain groups of the population than for others. Finally, AML systems may touch the right to an effective remedy for the reason that individuals will not be informed of the processing, and even if they are informed, they may be unable to contest the system owing to its complexity.

Nw. Airlines Privacy Litig., 2004 WL 1278459 (D. Minn. 2004); Daniels v. JP Morgan Chase Bank, N.A., 2011 N.Y. Misc. LEXIS 4510 (N.Y. Sup. Ct. 2001); Loeffler v. Ritz-Carlton Hotel Co., No. 2:06-CV-0333-ECR-LRL, 2006 WL 1796008 (D. Nev. 2006). 23 Specht v. Netscape, 306 F.3d 17 (2d Cir. 2002); Nguyen v. Barnes & Noble, Inc., 763 F.3d 1171 (9th Cir. 2014); In re Zappos.com, Inc., Customer Data Security Breach Litig., 893 F. Supp. 2d 1058 (D. Nev. 2012); Hubbert v. Dell Corp., 835 N.E. 2d 113 (Ill. App. Ct. 5th Dist. 2005). ProCD Inc. v. Zeidenberg, 86 F.3d 1447 (7th Cir. 1996) (discussing the analogous case of shrinkwrap contracts, which are included within the sealed package of a new product, and which have been enforced when there was an opportunity to walk away). 24 Feldman v. Google, Inc., 513 F. Supp. 2d 229 (E.D. Pa. 2007).

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Defining Risk

Risk is the net negative influence of the exercise of vulnerability, regarding both the prospect and the effect of occurrence. Risk management is the procedure of identifying risk, assessing risk, and taking steps to moderate risk to a tolerable point. In dictionary definition terms, “risk” means: “hazard, chance of bad consequences, loss, exposure to chance of injury or loss”.25 There is unclear use of risk as a synonym of probability or chance with respect to an event or outcome, the nature of an outcome, or its cause. Dowie26 argues that the term “risk” is an impediment to improved decision- and policy-making. Risks’ multiple and unclear usages steadily endanger the separation of the tasks of identifying and evaluating appropriate evidence, on the one hand, and drawing out and processing vital value judgments, on the other. It could be argued that the term “risk” contaminates all deliberations of probability owing to the unreserved value judgments that the term always conveys with it, at the same time as it contaminates all deliberations of value assessment as a result of the implied probability judgments that it encloses. Is it possible to eliminate risk? The answer is no, but a well-organized risk management lowers the degree of uncertainty about the predicted and the final outcome concerning any project. There are two characteristic and equally central types of risk in a strategic alliance: firstly, the relational risk and secondly, the performance risk. Relational risk is related to cooperative relationships, or the prospect that the partner does not fulfill the spirit of cooperation. Opportunistic conduct of the partners is a characteristic foundation of relational risk. Alternatively, performance risk indicates the prospect that intended strategic objective of an alliance may not be accomplished, even supposing cooperation between the partners is adequate.27 According to Miller,28 the perception “risk” “often refers to factors “either external or internal to the firm that impact on the risk experienced by the firm,” . . .the sources of risk. In this light, relational risk and performance risk differ in terms of their sources: the first arising from firm-firm interaction and the latter from firm-environment interaction.” Consequently, relational risk and performance risk rules out systematic interactive infectivity between them and so, the height of one type of risk would not drastically associate with that of the other. Although in particular cases performance risk add to relational risk, in other cases, a high point of performance risk generates an awareness of crisis lessening relational risk. Whilst performance risk is widespread in any kind of strategic option, relational risk is existing only in collaborative strategies, or strategic alliances. Performance risk is the prospect that the strategic objective of an alliance may not be accomplished, 25

Concise Oxford Dictionary. Dowie J. Against risk. Risk Decision and Policy 1999;4(1):57–73. 27 Miller, K. D. (1992). A framework for integrated risk management in international business. Journal of International Business Studies, 23(2): 311–33 I. 28 Miller, K. D. (1992). A framework for integrated risk management in international business. Journal of International Business Studies, 23(2): 311–33 I. p. 311. 26

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given that the best likely cooperation survives between the associates. Issues irrelevant to cooperation, such as ineffectiveness of partners, are the foundation of performance risk. Just as for any other strategic alternative, a strategic alliance induces partners to acknowledge the fact that their unsurpassed efforts may not automatically lead to triumph. Though performance risk is not related to cooperation, forging strategic alliances alleviates the scale of performance risk faced by particularized companies. Without a doubt, risk-sharing is a central justification for having an alliance. The notion of risk as performance variance is broadly employed in finance, strategic management, and economics. Risk refers to variation in corporate outcomes or performance that cannot be predicted ex ante. Risk encloses factors either external or internal to the company that influence the risk experienced by the company and so, referring to a foundation of risk. Examples of risk are the “political risk” and the “competitive risk” associated with volatility in company performance to particular uncertain environmental variables. While the cost and risk in R & D, marketing, and production are exceedingly high for a single company, strategic alliances permit multiple companies to split the total cost and risk. Undoubtedly, the risk here refers to performance risk. The gain is that performance risk is shared by forming an alliance, while relational risk is produced only in alliances. Once more, the peculiarity between performance risk and relational risk distinguishes strategic alliances, and as a result, the two sorts of risk, overall, comprise a second dimension for understanding the alliance making development. Devlin and Bleackley29 provided guidelines for profitable alliance making in terms of three stages: “(1) the decision to form a strategic alliance; (2) the choice of an alliance partner; and (3) the planned management of the alliance.” It has to be taken into consideration that there is an ingredient that is over and over again important in all these stages which is the direction of each associate in approaching the potential alliance. Risk sharing or risk controlling are central justifications for joining strategic alliances.30 A triumphant strategic alliance depends significantly on effectual cooperation between the associates, since the motive for entering into an alliance is to utilize the remuneration of cooperation. Strategic alliances have appeared in recent years as a trendy strategy in an environment in which fast gain access to up-to-date expertise and emerging markets is more vital than ever.31 Moreover, strategic alliances are regarded as a form of cooperative arrangement between corporations. Obviously, companies try to get hold of maximum returns from the resources they consign to the alliances, while paying close attention to the risks they are exposed to. Company-explicit resources embrace brand names, technology, skilled Devlin, G. & Bleackley, M. (1988). Strategic alliances–Guidelines for success. Long Range Planning, 21(5):18–23. 30 Kogut, B. (1988). Joint ventures: Theoretical and empirical perspectives. Strategic Management Journal, 9:319–332. 31 Deeds, D. L. & Hill, C. W. L. (1996). Strategic alliances and the rate of new product development: An empirical study of entrepreneurial biotechnology firms. Journal of Business Venturing, 11:41–55. 29

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personnel, machinery, capital, and so on. Tangible resources incorporate physical assets and financial assets, while intangible resources consist of technology, human, managerial expertise, and reputation.32 A range of types of company-explicit resource have diverse kinds of effects on the alliance making process. To that extent, if a company’s central part competence is developed on its exclusive resources, then a strategic alliance as a way of pooling the focal point competencies of a mixture of partners is linked to the type of resource supplied by each partner. A number of problems that occur in strategic alliance making are triggered by a lack of understanding and communication. The triumph of strategic alliances is improved if companies take on an alliance making process that is founded on a full understanding of the forms of resource and risk that settle on the stance of each associate in the practice. When the associates do not agree to the particular kinds of orientations acknowledged therein, the alliances are unlikely to be triumphant. Credit risk surfaces from the prospective that one participant to a financial tool is triggering a financial loss for the other participant by neglecting to discharge an obligation.33 On the other hand, losses result from decline in portfolio value as a result of real or alleged deterioration in credit quality. Moreover, credit risk stems from a bank’s dealing with individuals, corporate, financial institutions, or a state. Market risk is the risk of losses in on- and off-balance-sheet status coming up from engagements in market prices. Various risks matter to market prices fluctuations are the risks pertaining to interest rate interrelated instruments and equities34 and the foreign exchange risk and products risk all over the banks. General market risk is the prospective for trading losses owing to general market movements. Specific market risk is the prospective for losses undergone over the short term as a result of issuer specific issues. Incremental risk is the prospective for losses over the longer term by reason of credit default or loss on equity status owing to default by a firm on its debt obligations.35 Operational risk emerges on account of inadequate management, being referred as the risk of corporate governance exposure. In addition, operational risk breadth is diverse, from quite a lot of grounds dealing primarily with extremity events rather than crucial estimates or tendencies dazzling abnormal rather than normal conduct and situations. Moreover, the bank exposure to operational risk is less expected and even harder to shape. It is worth mentioning that for a series of operational risk, there is and never can be data to maintain anything excluding an exercise needing individual judgment and estimation. Operational risk involves a diverse nature of events escalating from internal or external disruptions to business

Grant, R. M. (1995). Contemporary strategy analysis: Concepts, techniques, applications (2nd ed). Cambridge, MA: Blackwell. 33 Bunea-Bontaş, C., Basic Principles of Hedge Accounting, Economy. Transdisciplinarity. Cognition Review, no. 1/2009, p. 173, http://www.ugb.ro/etc/etc_1_2009.pdf. 34 Czuszak, J., An integrative approach to credit risk measurement and management, RMA Journal, June, 2002, p. 2, http://findarticles.com/p/articles/mi_m0ITW/is_9_84/ai_n14897131/pg_2. 35 Ernst & Young, Market risk capital set to Increase, Prudential standards Update, February 2009, p. 1, http://www.ey.com/Publication/vwLUAssets/PS_Update_-_MktRisk_Capital_Increase. 32

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activities and the irregularity of financial influence.36 Managers of alternative investment funds set up a past loss record for the adding up of operational risk, verify quantitative and qualitative risk restrictions for each alternative investment fund they administer, including market, credit,37 liquidity, counterparty and operational risks, and estimate investment display by means of both the “gross” and the “commitment method.” Furthermore, when measuring the power of banks, one of a number of variables to be taken into account is capital adequacy. A bank’s capital is the basis for prospective losses occurring from both on- and off-balance sheet exposures, which safeguard the bank’s depositors or other lenders. According to Amrollah38 Amini et al., “Assessing overall capital adequacy requires identification of all material risks, measurement of those that can be reliably quantified and systematic assessment for the limitations of minimum risk-based capital requirements. The fundamental objectives of a sound assessing process of internal capital adequacy are: identifying and measuring material risks; setting and assessing internal capital adequacy goals that relate directly to risk; and ensuring the integrity of internal capital adequacy assessments.” Trust refers to the confidence that one will find what is preferred from the partner, rather than what one is afraid of. It seems that the capability to count on trust leads one to accept as true the goodwill of the partner. Consequently, the extent of intercompany trust is negatively associated with the insight of relational risk. It is argued that trust allows people to be susceptible to their partners and so, taking risks from engagement, such as joining in a strategic alliance.39 Conversely, for those who are less able to depend on inter-company trust, diverse plans are taken on to deal with relational risk and discourage opportunistic conduct.

36

Jobst, A. A., Consistent Quantitative Operational Risk Measurement and Regulation: Challenges of Model Specification, Data Collection, and Loss Reporting, IMF Working Paper, WP/07/254, 2007, p. 3, 5, http://www.continuitycentral.com/news03623.htm. 37 Article 88 Directive 2013/36/EU of 26 June 2013 on access to the activity of credit institutions and the prudential supervision of credit institutions and investment firms, amending Directive 2002/ 87/EC and repealing Directives 2006/48/EC and 2006/49/EC. 38 Amrollah Amini, Mostafa Emami, Alireza Emami, Capital Adequacy And Risk Management – Premises For Strengthening Financial System Stability www.ssrn.com. 39 Mayer, R. C., Davis, J. H. & Schoorman, F. D. (1995). An integrative model of organizational trust. Academy of Management Review 150.

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Managing Risks

Managing risk is one of the key objectives of companies operating globally.40 Managers normally correlate risk with negative result.41 The notion of risk as performance difference is broadly employed in finance, economics, and strategic management. With either the variance or negative variation comprehension, “risk” refers to modification in corporate result or performance that cannot be calculated ex ante. Moreover, “risk” has been delegated to features either external or internal to a company that influence on the risk undergone by a company. In this sense, “risk” in reality applies to a source of risk. Some common instances of risk referring to risk resources are phrases such as “political risk” and “competitive risk.” Such terms associate randomness in company performance with particular vague environmental components. The employment of the term “risk” to refer to undefined environmental factors that diminish performance expectedness, in addition to the absence of predictability in company result itself, can be perplexing. The term “uncertainty” as employed in strategic management refers to the volatility of environmental or organizational factors that influence corporate performance.42 Moreover, Oxelheim and Wihlborg43 regard that unexpected developments in interest rates, foreign exchange rates, inflation rates, and relative prices are interconnected and together comprise the framework in which to create a strategy for managing macroeconomic risk. Managing risk is one of the key objectives of companies operating internationally.44

5.4

Risk Factors

A company’s business is subject to material risks that can be classified into main risk categories such as competitive and reputational risks, investments and infrastructure risks, cybersecurity risks, supply chain and third-party risks, external risks, and financial risks. First, competitive and reputational risks indicate that the capability to differentiate itself from other firms and social media are the principal threats to a firm’s reputation, as they permit anyone to make public feedback influencing perceptions; therefore, negative publicity is difficult to control. A company’s capability to

40 Ghoshal, Sumantra. 1987. Global strategy: An organizing framework. Strategic Management Journal, 8: 425–40. 41 March, James G. & Zur Shapira. 1987. Managerial perspectives on risk and risk taking. Management Science, 33: 1404–18. 42 Miles, Raymond E. & Charles C. Snow. 1978. Organizational strategy’s structure, and process. New York: McGraw-Hill. 43 Oxelheim, Lars & Clas G. Wihlborg. 1987. Macroeconomic uncertainty: International risks and opportunities for the corporation. New York: John Wiley & Sons. 44 Ghoshal, Sumantra. 1987. Global strategy: An organizing framework. Strategic Management Journal, 8: 425–40.

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compete is also influenced by safety of its stores, the functionality and speed of its online channels, and the values of their promotions, among other factors. Additionally, the exclusive brand benefits the company to positively differentiate, producing higher margins related to national brand competitors. Finally, a firm’s capacity to compete is influenced by the capacity to offer a unique experience for its guests across multiple channels that the exclusive brand implemented, and the ability to quickly adjust to customers’ variations in preferences, so if the company is not able to collect customers’ data, it faces loss in sales and an increase in inventory markdown, negatively influencing its results of operations. Second, another relevant category of risks faced by a firm is located in the investments and infrastructure risks, which are linked to remodeling existing stores, building new ones and optimizing technology and supply chain infrastructure. Due to a company’s remodel program, there is a need of choosing the most suitable locations, competing with other firms in the industry; choosing the wrong model or pursuing the wrong opportunities negatively influences the returns on the firm capital investment. Third, information security, Cybersecurity and Data Privacy risks are vital for any firm and so, a company has to regularly store data about its guests, team members, vendors and other third parties, which means that information security, cybersecurity and data privacy verify significant risks for the firm. Hence, a damage to firm’s computer systems and networking because of cyber-attacks and implementation errors result in repairment costs, data loss or theft and loss in customers’ confidence, influencing the firm’s results of operations which means that a firm has to continually invest in maintaining and updating its computer systems, but applying system changes generates an upsurge in the risk of experiencing system disruption. Firms are active in detecting and responding to data security damages, but the techniques applied by third parties to get unauthorized access to information change fast and so, there is a difficulty in applying a program that detects them accurately. Hence, the occurrence of these risks means that a firm is exposed to extra costly government actions and private litigations, along with a loss in its guests’ confidence concerning its capability to protect their data, which adversely influence firm’s reputation, sales, and results of operations. Fourth, supply chain and third-party risks for a firm mean changes in vendors’ dealings, changes in tax or trade policy, interruption of its supply chain by increasing commodity or supply chain costs threating the firm’s profitability. Fifth, external risks primarily linked to the state of macroeconomic conditions and consumer confidence, catastrophic events, workforce management and the capacity to deal with federal and international laws are influencing a firm’s results of operation. Finally, a firm’s business is shaped by financial risks such as the possible increase in firm’s income tax rate and its volatility produced by the operations across the globe, both adversely affecting their business, results of operations, liquidity, and net income. Moreover, a further threat is the capability to access to capital markets, which is vital for a firm, assuring to firm’s liquidity for everyday operations. The accessibility of the market depends on multiple factors such as the condition of the market itself, the operating performance of a firm, and being able to keep its strong credit ratings. In order to obtain financing at a reasonable cost, a firm is maintaining good-quality judgment by credit agencies

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and so, it uses a sort of derivative products to manage its exposure to market risk, principally interest rate fluctuations. It seems that progressively, producing and delivering value through complex supply chain networks encompass substantial risks. Hence, under conditions of supply chain network risk, corporations develop effective risk management practices and so, under conditions of uncertainty, management decision-making is expected to be cautious until visible forms of risks emerge, and prudent response mechanisms are put in place. To that extent, the role of supply chain exploration and exploitation practices is central influencing the development of network risk management practices, leading to competitive financial results. Furthermore, as corporations develop their operations globally, they have to sustain their market successes regardless of supply chain risks. In addition, multifaceted global supply chain networks augment the likelihood of a negative influence of prospective supply chain disruptions on corporation performance. In global marketplace, corporations utilize a business strategy to achieve competitive advantage by managing risk from the external network environment and internal organizational factors that result in the incompetence of the purchasing corporation to meet customer demand or produce threats to customer life and safety which means that an effective supply chain risk management needs a better understanding of the numerous types of supply chain risks and organizational response mechanisms to lessen the negative effect of such disruption events. It has to be taken into account that organizational risk by nature is network-related and not firmspecific. Besides, external risk drivers are not directly manageable which means that strategic priority is to plan supply chain exploration practices for discovery learning from examining supply chain failures. In addition, an operational focus is to implement supply chain exploitation practices and designing risk management practices which means that in an interactive and integrative world of business, network risk challenges necessitate management attention to develop and exploit internal and network information competences and then connect them to risk management practices. It has to be taken into account that a firm’s risk factors can be divided into strategic risks, operational risks, financial risks, and a category imbedding legal, tax, regulatory, compliance, reputational, and other risks. Strategic risks are identified in general and macroeconomic factors, both nationally and internationally, which are affecting a firm’s financial performance, embracing most of the activities of the supply chain: starting from suppliers’ operations, meaning an upsurge in the cost of goods, reaching firm’s operations, resulting in impairment charges to different assets and comprising also administrative expenses, labor, and healthcare costs. Additionally, the society endlessly tackles strong competitions that describe many sectors of the industry and so, wholesale club operators are concentrated on price competition in every segment of the business, but also on the best services presented to clients aimed at understanding in advance consumer needs, feelings, and emotions. Furthermore, operational risks are merging many types of risks, such as the likelihood of running into natural disasters, global health epidemics or pandemics outbreaks, geo-political events, and catastrophic events, risks linked with suppliers, information

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and technology-based systems risks, security faults, and failures in attracting and retaining qualified associates, all these factors materially adversely influence firm’s financial performance. To that extent, such events result in physical damage to properties, the closure of one or more stores, the lack of an adequate work force in a market, the inability of clients to the stores and clubs due to by such events, the unavailability of digital platforms to the clients, alterations in the purchasing patterns of clients and in buyers’ disposable income, the disruption of utility services to the stores and facilities. Moreover, global sourcing is a key aspect and so, accessing products in a timely and effective way is a significant challenge, as there are too many factors such as political and economic instability, suppliers’ failure to meet terms and conditions, the availability of raw materials to suppliers, merchandise safety and quality issues, transport security, and other factors linking to the suppliers and the nations in which they are located that go beyond the control of the society. It is worth mentioning here that all the risks connected to technology are imperative and a firm has to apply strategies to hedge against them, as information systems are indispensable for business operations and a damage to them results in high repair costs. Also, digital platforms are regularly subject to cyber-attacks and if a firm is unable to keep an adequate security level and keep them functioning within acceptable parameters, it suffers loss of sales, reductions in transactions, reputational damage, and deterioration of competitive position. Will companies disclose information on material cyber-attacks? Managers withhold negative information, and investors cannot discover most cyber-attacks independently. Taking into account data on cyber-attacks that companies voluntarily disclosed, and those that were withheld and later discovered by sources outside the company, companies withhold information on cyber-attacks.45 Moreover, managers disclose information on cyberattacks when investors already suspect a high probability of an attack. Hence, cyberattacks are one of the key risks that companies have to manage but due to clouding and antivirus protection, the loss from cyber-attacks is decreasing. Furthermore, managers have strong reasons to withhold information on cyber-attacks, particularly when the happening of the cyber-attack and the damage produced are uncertain and so, managers disclose less severe attacks and withhold information from investors on attacks that trigger greater damage. It is worth mentioning here that the market reaction to withheld attacks is negative and noteworthy and so, voluntary disclosure of cyber-attacks is rare. Financial risks refer to fluctuations in foreign exchange rates, increasing cost of sales with a corresponding adverse effect on the gross profit, which means that these risks involve any failure to meet market expectations for the financial performance of the society influencing the market price and volatility of stocks, changing dividend, or stock repurchase programs or policies. Due to legal, tax, compliance, reputational Eli Amir, Shai Levi & Tsafrir Livne, Do firms underreport information on cyber-attacks? Evidence from capital markets, Review of Accounting Studies volume 23, pages 1177–1206 (2018) (withheld cyber-attacks are associated with a decline of approximately 3.6% in equity values in the month the attack is discovered, and disclosed attacks with a substantially lower decline of 0.7%). 45

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and other risks, international operations expose firms to legislative, accounting, legal, political, and economic risks. Moreover, future operating results in foreign states are influenced by a variety of factors and so, any violation of internal policies affect the business or financial performance and the reputation. Furthermore, alterations in tax, laws, and regulations have an influence on the group’s performance and so, by imposing higher tariffs on imports or exports of goods, the difference between the ultimate tax outcome and the tax amounts recorded in financial statements, any failure to comply with applicable laws or accounting principles results in substantial financial exposure, damage to reputation, and adverse effect on results of operations of the firm. It has to be taken into account that an adequate financial structure makes certain funding for operating activities on a daily basis or on a long-term perspective. The financing strategy of a firm has to guarantee liquidity and access to capital markets, to keep a balanced spectrum of debt maturities, and to accomplish the net exposure to floating interest rate volatility which means that a firm seeks to minimize the borrowing costs. Hence, the capability to access the long-term debt and commercial paper markets offers to a firm sufficient source of liquidity. Besides, any downgrade of credit rating adversely impacts a firm’s capability to access the debt market, their cost of funding, and any other terms for new debt issuances. It is worth noting that concerning the financial structure, firms are focused on the magnitude of funding; in fact, except for having a great current cash position, they have the advantage of a wide access to capital markets, thanks to strong commercial paper and long-term debt ratings permitting firms to meet all the operating cash needs, including acquisitions, capital expenditures, dividend payments, and share repurchases. On the other hand, any downgrade of current short-term credit ratings impairs firms’ capability to access the commercial paper markets. It has to be taken into account that a kind of threat embedded in the financial risks is characterized by the likelihood that the borrower is unable to refinance to repay the current debt or he is able to refinance to worse conditions in terms of size, maturity, and cost and so, this refinancing risk is overdue by the firms employing liability management which means repurchasing the old bonds from the existing investors before maturity and offering them new, longer-dated bonds in exchange. Moreover, there is a possibility of utilizing derivative contracts to deal with interest rate risk and so, once the debt has been issued, the firm is exposed to interest rate risk that must be managed. In line, the practice of managing this risk is known as interest rate hedging policy verifying the allowed instruments, limits on size and counterparties, and other organizational and process-related matters. In addition, a firm can adopt interest rate swaps with the purpose of lessening interest rate risk and so, a firm has counterparty credit exposure to large global financial institutions and this is an essential, but often unappreciated, matter when entering in derivative contracts. Moreover, a firm can be exposed to alterations in interest rates due to the short-term borrowings and longterm debt, but a portion of interest rate risk can be hedged by managing the mix of fixed and variable rate debt and by entering into interest rate swaps. In fact, the actual interest rates environment permits firms to take certain advantages by hedging with a certain approach.

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Risk Management and Governance

Risk management implies that agency conflicts can build a link between corporate hedging activities and governance mechanisms.46 Hence, risk management is the duty of a company’s management. Management has to estimate and manage a company’s exposure to various risks. Corporate management is accountable to justify to the shareholders how much profit is engendered out of their assets that are under the fiduciary care of shareholders. In actual fact, the market mechanism does not perform rightly by reason of market failure and to administrative regulations. Thus, management’s lapse of the allocation of profits among stakeholders is essential. Corporate governance is a control system planned to screen a company’s operations and the potential conflicts of interests between the various stakeholders. The board of directors is regarded as one of the most significant mechanisms used to accomplish company’s goals. The key role of a board of directors is to represent the interests of a company’s stockholders. The board’s aim is to amplify a company’s worth or the value of its shares recruiting top executives, while also scrutinizing their activities. It could be said that the greater the number of external directors on the board, the greater is the number of risk hedging activities undertaken by a company. The audit committee has to discuss the policies and directives governing the process for evaluating the key risks to which a company is exposed and the measures to be taken to monitor and control this exposure. In screening and approving their risks, companies substitute the audit committee with other mechanisms such as the risk management committee. The audit committee is no longer compelled to be exclusively accountable for evaluating and managing risks but discussing the risk evaluation and risk management procedures. Risk evaluation and risk management means are intricate to utilize and screen. Figuring out risk evaluation and risk management involves a good understanding of mathematics and statistics. Audit committee members need to have a specialized training in order to be up to monitoring the in-and-outs of coverage. Risk management issues produce conflicts of interest between corporate executives and shareholders, especially when executives are compensated with their company’s stock options.47 It is now proven that one of the key aims of risk management is to maximize the company’s value or shares. Nevertheless, risk management serves to maximize the well-being of executives conflicting with the duty of maximizing the company’s value, particularly when the executives are rewarded to a noteworthy scale with stock options and so, generating problems of governance. In the North American gold mining industry, executives compensated

46

Tufano, P., 1998. Agency costs of corporate risk management. Financial Management 27, 67–77. DeMarzo, P., Duffie, D., 1995. Corporate incentives for hedging and hedge accounting. Review of Financial Studies 8, 743–771. 47 Smith, C.W. and Stulz, R.M., (1985) “The Determinants of Firms’ Hedging Policies.” Journal of Financial and Quantitative Analysis 20, 4, 391–405.

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in stock options undertake fewer risk management activities that those who are not.48 The value of executives’ options augments with the volatility of shares or with the volatility of the company’s value. Even if managers are risk-averse with regard to their own wealth, they are risk-leaning concerning the company’s value when they hold stock options in the company they administer and so, rationalizing their decisions to take on in fewer risk management activities, because activities would diminish the volatility of the company’s value and the value of their options. There is a global cultural and political movement attacking bureaucracy. In the public sector, governments are privatizing and taking apart bureaucracies.49 Corporate groups and networks are exploiting markets rather than hierarchies. Within corporations, headquarters’ staffs and “middle-management” are downscaled. In redesigned corporations, in place of bureaucrats, employees are innovators. Bureaucratic corporate management not only administers agency costs, but also reacts to regulatory threats. Bureaucratic organization engenders apparently responsible firms, competent of rational and accountable decision-making, diminishing the need for invasive regulatory policies. It is vital to have corporations without bureaucracy worthy of public trust.50 One problem in redesigned corporations is how, in the absence of hierarchical control, one group denotes the essential resources from other groups, many of whom may have overfilled duties, possibly in consequence of their downsizing. Enron Online both overcharged and undercharged its customers. Other project groups proceeded to accomplishment without being adequately integrated with other corporate operations.51 In the redesigned corporation, not all risks are eradicated. Executives confront many risks and legal risks are just one among many others which means that legal non-compliance is a prospect. The corporate decision depends on the management of risks, not only the removal of risks. Corporate redesign acknowledges that agents will employ opportunistic behaviors. Unlike bureaucracies, redesign does not decrease agency costs by supervision. In redesigned corporations, agent opportunism is administered indirectly. Τo that extent, incentive structures are launched to make straight employee and corporate interests. Employees in redesigned corporations have to add value to the organization being responsible for adding value.52 Redesigned corporations employ different

Tufano, P. (1996) “Who Manages Risk? An Empirical Examination of Risk Management Practices in the Gold Mining Industry.” The Journal of Finance 51, 4, 1097–1137. 49 Gifford Pinchot & Elizabeth Pinchot, The End Of Bureaucracy And The Rise Of The Intelligent Organization 34 (1994). Robert Eli Rosen, “We’re All Consultants Now”: How Change in Client Organizational Strategies Influences Change in the Organization of Corporate Legal Services, 44 Ariz. L. Rev. 637 (2002). 50 W. Chan Kim & Renee Mauborgne, Strategy, Value Innovation and the Knowledge Economy, 40 SLOAN MGMT. REV. 41 (Mar. 22, 1999). 51 Kathy Thacker, Project Teams Laboring at Warp Speed Often Hit the Wall, Author Says, DALLAS MORN. NEWS, May 14, 2002, at 3D. Miles Moffeit, Enron Mishandled Billing, Overcharged Clients, Former Employees Say, Knight Ridder Wash. Bureau, Feb. 16, 2002. 52 Raymond E. Miles & W.E. Douglas Creed, Organizational Forms and Managerial Philosophies: A Descriptive and Analytical Review, 17 Res. In Organizational Behav. 333, 362 (1995) (noting that 48

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motivational strategies such as hierarchical controls and horizontal ones. Business transactions in redesigned corporations are not managed hierarchically, but characteristically by self-managing project groups. Standardized processes and policies are substituted by a commitment to aligning motivations. Coordination by the hierarchy is restricted by a pledge to the panels being self-managing. According to John E. Triantis53 “Risk management in acquisition projects takes several forms, the most common being pushing the risk back to the seller or the target through the use of agreements, negotiating the risk away to third parties, and allocating risk according to ability to handle. Other approaches to risk management include purchasing commercial insurance to cover certain risks and sharing the risk with the seller or other entities according to potential benefits received.” In the redesigned corporation, a conflict of interest is produced by loyalty to a firm not within the corporation’s permeable borders. The managerial conflict of interest problem, in the redesigned corporation, is to maneuver the self-interest of its employees and guest workers so that they are implausible to act on their loyalties to other firms. It could be argued that if modification is needed in corporate law, it is not just because of corporate noncompliance, but also for the reason that corporations must protect themselves from entering flawed business deals. A central lesson of corporate regulation is that the more consistent corporate internal controls are, the less there is a need for intrusive auditing. The duty for redesigned corporations, and the law to the degree it is possible, is to control these work councils by improving internal risk management rule. Another problem at Enron was how it administered risks in the accomplishment of its projects. Because of risk management failures, Enron obviously made bad business deals. Conventionally, corporate funds spent for legal and auditing services were considered as losses, payments for side-constraints on the corporate assignment. Nowadays, tax departments, accounting companies, corporate legal departments, and law firms allege they are profit centers. They “add value” to a company. It was through the finance department that Enron primarily added value. Enron’s tax department developed and bought, from accounting and law firms, products to improve firm earnings. In redesigned corporations, tax departments will look for innovations to add value to the firm, but these innovations must be sufficiently considered. The problem is not that Enron was using accounting practices that ‘push limits’ and were ‘at the edge’ of gratifying practices and permitted an unparalleled arrangement considered to be innovation but the problem is that the risks of these innovations to Enron were not correctly applied.54 Risk management was central to Enron not only because of its regulatory environment but also as a all team members are expected to have “responsibilities with bottom-line implications.” To meet these, “they become partners in designing their own roles and expanding the nature of their contributions.”). 53 John E. Triantis, Creating Successful Acquisition And Joint Venture Projects: A Process And Team Approach 133 (1999) at 137. 54 Robert Eli Rosen, As the Big 5 Become Multi-Disciplinary Practices, Opportunities Abound For Tax Executives, Tax Executive, at 147 (Mar. 1, 1999).

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consequence of its business strategy. Enron’s strategy was to boost its purchases in the highly leveraged energy and financial product markets but this amplified that Enron’s debt-to-equity ratio increased Enron’s financial exposure. Additionally, Enron attempted to spread its products lines. To manage these growth openings, Enron needed momentous internal financing. Enron’s Risk Assessment and Control Group’s major task was to manage Enron’s market risk exposures which failed to do.55 Companies’ inter-play with financial markets performs a vital role in accomplishing short-term rewards all the way through escalation in share price. While this tendency turned out to be apparent after the Enron calamity a decade ago when analysts debated the obscurity of shareholder value,56 latest actions have uncovered the justification of corporate strategies and in whose interest they are taken on. Moreover, the bond matter of technology giant Apple offers an attractive pattern of this ever-increasing incident of financial engineering. It has to be taken into account that where numerous practices such as accounting manipulations or structured finance were disclosed for their crucial choice, that is to say to escalate share price and add to investors’ profits. Apple is accepted as a knowledge-driven firm, stimulated by product innovation which permitted engendering cash and piling up reserves amounting to $145 billion. The enquiry of why resorting to the capital markets and especially to debt ones when a large amount capital is offered is a conundrum that illustrates the ever-closer connection between companies and financial markets. Especially, it is worth mentioning that in cases similar to Apple, the funds engendered by the bond release are not purposeful to following new investments in the core technology industry and actually in most cases, the actions carried out in the capital markets are not associated at all with companies’ main dealing which was somewhat the case at Enron as well.57 Further than the tax evasion purpose that underlined Apple’s bond concern, it has been experimental that the foundation behind Apple’s financial strategy be inherent in the necessity to return cash from the function to its shareholders and to executives all the way through stock options, consequential so in a way to get money out of the corporation rather than to fund it.58 Simultaneously, debt strategies have the gain for executives to augment the height of leverage and assist risk-taking.

Richard D. Phillips, Enron: The Risk Management Lessons, at 4, at www.cermas.gsu.edu/events/ brownbag032102/phillips.pdf. 56 W.W. Bratton, “Enron and the dark side of shareholder value”, Tulane Law Review, Public Law and Legal Theory Working Paper n.035 2002 p. 8. 57 J. Kay “Why business loves capital market, even if it doesn’t need capital”, Financial Times, 15 May 2013. 58 R. Waters “Inside Business: Real innovation needed to juice returns”, Financial Times, 24 April 2013. 55

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Internal–External Governance Mechanisms

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Internal–External Governance Mechanisms

Corporations in most states of the globe have boards of directors. Ownership and control are hardly ever entirely alienated within any corporation. When internal control mechanisms fail to a large enough degree such as on the occasion when the gap between the real value of a corporation and its prospective value is adequately large, there is reason for outside parties to look for control of the corporation. Alterations in the control of corporations practically happen at a premium; this means producing value for the target corporation’s shareholders. The legal system as a corporate governance device is described as being too ingenuous an instrument to deal successfully with the agency troubles between managers and shareholders. Therefore, it could be said that law and economics in tandem could be more effective in dealing with corporate governance in a legal and concurrently an economic view. Cross-national models of corporate governance are converging or will converge on the Anglo-Saxon, capital market-driven model distinguished by a critical separation between ownership and control. It was argued that shareholder rights and the intense separation of ownership from managerial control were unavoidably more competent and “modern” than alternative modes such as those supporting family companies, conglomerates, bank-led groups, or worker cooperatives becoming well known.59 The globalization of financial investment and money-managing starting in the early 1980s followed by the decline of the Japanese economy during the 1990s has stimulated another sequence of points of view foreseeing a convergence on the American model. Most financial and money managers choose firms right through the globe to respect shareholder rights, boost shareholder value, and be transparent in their reporting of corporate activities and outcome.60 Financial points of view and changes in global economic leadership aside, corporate governance patterns keep on to vary noticeably across states regardless of decades of economic globalization and 30 years of intense financial globalization. Great cross-national variation in terms of crucial aspects of corporate governance has been distinguished by the significance of large stockholders, the legal protection of shareholders, the extent to which appropriate laws are enforced, and the handling of stakeholders such as labor and the community. Moreover, the dependence on debt finance, the formation of the board of directors, the way in which executives are rewarded, and the occurrence and treatment of mergers and takeovers, particularly hostile ones, characterize cross-national variation in terms of crucial aspects of corporate governance. Concentrated, not dispersed, ownership is still the canon rather than the exception right through the globe, and consequently, it could be

59

Kerr, Clark, John T. Dunlop, Frederick Harbison, and Charles A. Myers. [1960] 1964. Industrialism and Industrial Man. New York: Oxford University Press. 60 Useem, Michael. 1996. Investor Capitalism: How Money Managers are Changing the Face of Corporate America. New York: Basic Books.

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said that it is family control of even the largest firms or business groups in most states.61 Further than the convergence in efficient systems at the level of the nation-state, there is a critique of the alleged convergent consequences of globalization The legal dispute against convergence in corporate governance remarks that corporate law is closely correlated not only to social custom but also to other legal areas, such as banking, labor, tax, and competition law not modifying all at once for the reason that the diverse interests produced around them. In the neoclassical point of view, corporate taxation is regarded as a transfer from shareholders to the government. Taxation diminishes investment by outside shareholders, while tax evasion and escaping benefits shareholders having a positive outcome on investment. It could be said that corporate taxation balances the role of debt in Jensen’s Free Cash-Flow Theory.62 Hence, there may not only be a negative neoclassical, but also a positive corporate governance way all the way through which taxation influences investment and company value. Managers and outside shareholders purposefully determine the height of diversion and investment.63 Moreover, corporate taxation influences company worth optimistically if the corporate governance system is inadequate and tax enforcement goes beyond a specific threshold. Furthermore, corporate taxation benefits companies for which a corporate governance drawback is more predominant. Koethenbürger and Stimmelmayr64 examine the influence of “deductibility provisions in an agency framework... show that welfare is reduced if the tax system fully exempts the return on investment from taxation.” R. Krämer, V. Lipatov65 indicate that “the corporate governance channel of taxation is not restricted to firm value or other performance measures, but also affects the level of investment in shareholder capital . . . showing that the effect of such interactions is not restricted to firm value or other performance measures. Further, by indicating that tax-governance interactions affect shareholder capital as an integral part of capital structure, it also contributes to the literature on the capital structure effects of corporate taxation.” In the framework of corporate governance, convergence refers to growing harmonization in the governance practices of public corporations from various states. Convergence in type links up escalating resemblance in terms of legal framework and institutions. Moreover, convergence in operation indicates that various states can

Thomsen, Steen, and Torben Pedersen. 1996. “Nationality and Ownership Structures: The 100 Largest Companies in Six European Nations.” Management International Review 36 (2):149–166. 62 Jensen, M.C. (1986) Agency Costs of Free Cash-Flow, Corporate Finance, and Takeovers, American Economic Review 76(2), 323–329. 63 Krämer, R. and Lipatov, V. (2012) Opportunities to Divert, Firm Value, and Taxation: Theory and Evidence from European Firms, FinanzArchiv/Public Finance Analysis 68(1), 17–47. 64 Koethenbürger, M. and Stimmelmayr, M. (2010) Corporate Deductibility Provisions and Managerial Incentives, mimeo. 65 Robert Krämer, Vilen Lipatov The Effect of Corporate Taxation and Ownership on Raising Shareholder Capital CESIFO Working Paper NO. 4436. 61

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have separate rules and institutions but may still be able to carry out the equivalent purpose such as making certain fair exposé or responsibility by managers. It is worth mentioning that there is dissimilarity between de jure convergence and de facto convergence.66 On the one hand, when two states embrace comparable corporate governance laws, there is de jure convergence between them. On the other hand, when real practices converge by analogous implementation, it is referred to as de facto convergence. Convergence supporters underlining resourceful market considerations say that globalization expedites competition over “best practices,” and companies that are more exposed to worldwide markets are forced to implement the Anglo-American model which is a de facto global standard.67 On the other hand, institutional theory confines that organizational’ grounds turn into comparable become similar over time in consequence of three kinds of weight such as mimetic, normative, and coercive.68 Escalating foreign portfolio investment in both developed and developing economies, cross-border mergers, and acquisitions, and free capital flows across states have inference for convergence for the reason that they cause an ultimate transformation in the ownership composition of corporations. Supporters of convergence claim that, sooner or later, merchandise market integration and the resulting global competition will have the identical consequence. Corporate governance is considered as a novel technology or a new advance, and in an era of global competition, corporations have no option except to take on the most pioneering practice or confront competitive breakdown. Novel technological and market forces force companies to take on analogous strategies across states.69 Regardless of the forces that force companies in various states toward convergence in corporate governance, national governance practices have not been competing toward convergence.70 It could be argued that the direct import of endogenous factors within a state rather than the outcome of global factors impels convergence.71 For instance, the Sarbanes-Oxley legislation in the United States was a public policy answer to collapse in the system rather than the consequence of a drive toward a normative global ideal.

66 Khanna, T., Kogan, J. and Palepu, K. (2006) Globalization and dissimilarities in corporate governance: A cross-country analysis, The Review of Economics and Statistics, 88: 69–90. 67 Hansmann, H. and Kraakman, R. (2001) The end of history for corporate law, Georgetown Law Journal, 89: 439–68. 68 DiMaggio, P. J. and Powell, W. W. (1983) The iron cage revisited: Institutional isomorphism and collective rationality in organizational fields, American Sociological Review, 48: 147–60. 69 Kogut, B., Walker, G. and Anand, J. (2002) Agency and institutions: National divergences in diversification behavior, Organization Science, 13: 162–78. 70 Aguilera, R. V. and Jackson, G. (2003) The cross-national diversity of corporate governance: Dimensions and determinants, Academy of Management Review, 28: 447–65. 71 Hermes, N., Postma, T. J. B. M. and Zivkov, O. (2006) Corporate governance codes in the European Union: Are they driven by external or domestic forces? International Journal of Managerial Finance, 2: 280–301.

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Global harmonization of disclosure and accounting standards advances convergence.72 The integration of financial markets has been presented as the main driver of convergence of governance systems.73 National financial markets, which functioned in virtual isolation until lately, have unexpectedly turned into more integrated in the last two decades with noteworthy repercussions for governance. Moreover, financial market integration acquires many forms consisting of listing by companies from one state in the stock exchanges of other states, escalating foreign portfolio investment in both developed and developing economies, cross-border mergers, and acquisitions, and free capital flows across states. Corporate governance influences company worth, capital productivity, and economic growth governance restructuring does not explicitly add value.74 Shareholder governance is not arbitrarily allocated. Can corporate culture on shareholder governance be causal? Corporate culture could influence shareholder governance if shareholders select to improve governance as a therapy for a weak culture. Tracking an upsurge in shareholder governance, managers instigate courses which lead employees to deem that functioning and achievement are the fitting answer to unforeseen incidents even if this entails giving up honesty, ethics, and teamwork. The political procedure plays a very imperative part in determining the corporate governance formation in a state.75 F. Allen et al.76 argue that “Stakeholder firms are more (less) valuable than shareholder firms when marginal cost uncertainty is greater (less) than demand uncertainty. With globalization shareholder firms and stakeholder firms often compete. We identify the circumstances where stakeholder firms are more valuable than shareholder firms and compare these mixed equilibria with the pure equilibria with stakeholder and shareholder firms only. Finally, we analyze firm financial constraints and derive implications for the capital structure of stakeholder firms.” It is worth noting that corporations exploit capital markets to effectively manage the price risk of inputs such as steel, corn, and oil. Howell77 presents that “In a highway procurement setting. . .government-provided insurance against oil price risk significantly reduces procurement costs as well as the

72 Coffee, J. C. (1999) The future as history: The prospects for global convergence in corporate governance and its implications, Northwestern University Law Review, 93: 641–707. 73 Khanna, T. and Palepu, K. (2004) Globalization and convergence in corporate governance: Evidence from Infosys and the Indian software industry, Journal of International Business Studies, 35: 484–507. 74 Acharya, V., M. Gabarro, and P. Volpin, 2013, Competition for Managers, Corporate Governance and Incentive Compensation, Working Paper. Acharya, V., S. Myers, and R. Rajan, 2011, The Internal Governance of Firms, The Journal of Finance LXVI, 689–720. 75 Perotti, E. and P. Volpin, 2007, “Politics, Investor Protection and Competition,” working paper. Perotti, E. and E. von Thadden, 2006, “The Political Economy of Corporate Control and Labor Rents,” Journal of Political Economy 114, 145–174. 76 Franklin Allen, Elena Carletti, Robert Marquez Stakeholder Capitalism, Competition and Firm Value at: http://ssrn.com/abstract¼2346430. 77 Sabrina T. Howell, Firm type variation in the cost of risk management Journal of Corporate Finance 64 (2020) 101691 p. 21.

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pass-through of risk to product market prices. Financial constraints and costly distress best explain why some firms find value in relaxing constraints on risk management.” The harmonization upsurge necessitated a novel method for good practices in corporate governance. National legislations pioneered one-size-fits-all approach and the competent authorities united firm’s structures and practices for enhanced regulation. The one-size-fits-all approach seems to be ill-suited for enlarge process in EU.78 In 2006, the Directive 2006/46/EC sets up comply-or-explain method on pan-European level by obligation for independent report by directors about acting in accordance with good practices in corporate governance. It should be taken into consideration that the certification role for conforming is delegated to external auditors. The upright practices of corporate governance are option between law and codes for each Member State. Moreover, the practices are based on legal tradition and ownership structures. The modern national codes treated analogous matters of corporate governance, linked to independence of board members, existence of remuneration committee and nomination committee, internal control, and risk management. Furthermore, Nedelchev79 considers “Corporate governance practices as a part of state policy for investors attracting use two main approaches. Discovery of balance between legal and regulation instruments together with codes and initiatives is the base for corporate governance state policy. The modern theory confirms the acceptation of voluntary codes as preferred variant for decrease of regulation costs and increase of market flexibility. The practice for implementation of unified criteria and legal requirements, familiar as one-size-fits-all approach, was replaced by new approach—comply-or-explain.” On the one hand, the one-size-fits-all method has partial application in modern exercise. The obligatory character of the method is dependable with requirements of a particular state and is inappropriate for global execution by reason of impracticality of convergence of key corporate governance information approximating shareholders protection, independent directors, and committee existence.80 On the other hand, the comply-or-explain method has three grounds of importance in comparison to one-size-fits-all method. First, the method gives decision for manager responsibilities and shareholders taken in consideration of long-term welfare of the firm. Second, the method motivates firms to pursue good practices, which are robust to corporate culture, without taking into consideration variables resembling firm size, ownership structure, and involvedness of business actions. Third, the method diminishes the involvement of regulatory authorities to obligation of lowest amount standards. It could be argued that the current modes in Zielonka, J. (2007). Plurilateral Governance in the Enlarged European Union. Journal of Common Market Studies, 45(1), 187–209. 79 Miroslav Nedelchev, Good Practices in Corporate Governance: One-Size-Fits-All vs. Comply-orExplain www.sciedu.ca/ijba P79 2013 International Journal of Business Administration Vol. 4, No. 6. 80 Davies, M., & Schlitzer, B. (2008). The impracticality of an international “one size fits all” corporate governance code of best practice, Managerial Auditing Journal, 23(6), 532–544. 78

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corporate governance are execution of amalgam between comply-or-explain method and compulsory regulation. The execution of both methods marks elevated dynamic and places a number of doubts for beneficial systems in corporate governance. The basis for being the first choice of every one method is the equilibrium between “hard” and “soft” legislation. A liquid secondary market in shares assists capital foundation but is harmful for corporate governance. Moreover, greater liquidity diminishes the cost of selling stakes in reply to managerial troubles.81 Liquidity has differing consequences on governance for the reason that it makes possible both block acquisition and block disposition.82 Moreover, liquidity and governance are expected in cooperation ascertained by a company’s unobserved uniqueness.83 K. Backa, et al.84 show that “an increase in the liquidity of the firm’s stock increases the likelihood of the large investor `taking the Wall Street walk.’ Thus, higher liquidity is harmful for governance. Empirical tests using three distinct sources of exogenous variation in liquidity confirm the negative relation between liquidity and blockholder activism.” Another deep-seated problem of the Anglo system of corporate governance is that there is no commendable course of action for directors to perform their most essential responsibility of screening and directing management. It has to be taken into consideration that the existence of non-executive directors (NEDs) turns out to be captive to management for information to screen and appraise both management and the business. The essential trouble caused by the existence of only non-executive directors (NEDs) remains even when directors fully abide by national standards of what are deceivingly portrayed as “best or “good” governance. It has to be taken into account that all 56 US banks that needed government support during the crisis from 2008 to 2009 had higher conformity than industrial companies in meeting standards of what was regarded as good governance, implying that there was spectacular fiasco of corporate governance and risk management methods.85 It could be said that the crisis did not occur for the reason that good practices were not adhered to but for the reason that they were followed. Direct engagement by NEDs with both operational and civic stakeholders presents a foundation for NEDs to acquire a creditable and systemic source to screen and direct management with information autonomous of

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Bhide, A., 1993. The hidden costs of stock market liquidity. Journal of Financial Economics 34, 31–51. 82 Maug, E., 1998. Large shareholders as monitors: Is there a trade-off between liquidity and control? Journal of Finance 53, 65–98. 83 Edmans, A., Fang, V. W., Zur, E., 2012. The effect of liquidity on governance, University of Minnesota. 84 Kerry Backa, Tao Lib, Alexander Ljungqvistc Liquidity and Governance at: http://ssrn.com/ abstract¼2350362. 85 Adams, R. B. 2012. Governance and the Financial Crisis. International Review of Finance. 12 (1):7–28. The Financial Crisis Inquiry Commission Report. 2011, Government Printing Office, Washington D.C., United States of America.

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management. Besides, direct private engagement would diminish much of the prerequisite and cost of conventional CSR reporting an auditing. The ordinary laws of governance clarify why consistent control and regulation of a company by its board and/or by supervisory body only turn out to be feasible with a necessary variety stakeholder embracing the position of co-regulators. Consequently, the coverage and cost of government regulations are diminished while the truthfulness of corporate control and regulation is enhanced. It could be argued that stakeholder commitment, all the way through network governance, generates a relationship for companies, stakeholders, and government regulators. Moreover, stakeholders launch the indispensable selection to advance the control and regulation of companies at the same time as stakeholders attain voice, authority, and bargaining force to defend and advance their own interests with that also of the company. Stakeholder commitment not only incorporates CSR into corporate governance but also sets up a systemic and unfailing foundation grounded in the discipline of governance to advance the maneuvers and sustainability of companies.86 The rationale of corporate governance is to make the company receptive to the rights and requirements of stakeholders. Screening it all the way through the principal–agency paradigm, this fundamental objective of corporate governance emphasizes that the corporation is an agent of the shareholder and is existent to assist the wants of those shareholders.87 Incidentally, corporate governance thrives when the course and functioning of the corporation reach that of the requests of the shareholders. Despite the fact that corporate governance cannot assure the triumph of a firm, it generates the atmosphere which is advantageous toward the accomplishment of aims of its shareholders.88

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Strengthening Internal Governance Mechanisms

The board of directors is the main institution of corporate governance and its key duty is to hire and monitor top management in aid of shareholders. The board of directors is best placed to monitor related-party transactions. Moreover, regulations instructing greater independence for directors and defining the board’s functions, powers, and internal workings such as containing subjects like auditing, fixing executive compensation, covering related-party transactions, and revelation of

86

Turnbull, S. 2008. The theory and practice of government de-regulation. In: J. Choi and S. Dow-Anvari (Eds.), International Finance Review: Institutional approach to global corporate governance. Emerald Publishing, Bingley, UK, (9): a117–139. 87 A Renders & A Gaeremynck, ‘Corporate Governance, Principal-Principal Agency Conflicts, and Firm Value in European Listed Companies’, Corporate Governance: An International Review, vol. 20, no. 2, 2012, pp. 125–143, p. 127. 88 A Demb & F Neubauer, The Corporate Board: Confronting the Paradoxes, Oxford University Press, Oxford, 1992, p. 187. Report of the HIH Royal Commission, The Failure of HIH Insurance, 2003, section 6.2.5.

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information flows present the board of directors authority to confront the principal shareholder. Up to now, little evidence exists that merely legal reforms have restricted controlling shareholders’ abuses regarding the general practice in enterprises.89 The law customarily protects shareholders by enhancing their rights to sell, sue, and vote. Whether shareholders successfully employ their rights to sell, vote, and sue depends on their gaining access to information. An extensive regime of disclosure alleviates agency troubles in listed corporations. Another kind of regulatory intervention is enforcement of corporate and securities laws all through supervisory agencies and criminal sanctions. It is worth mentioning that it is not clear public enforcement is very effective matters.90 However, public enforcement is the most useful instrument to avert particular modes of expropriation, like insider trading, which are otherwise difficult to sense. There is a need to enforce suitably severe sanctions, like prison terms, in extreme cases.

5.8

Risk Management and Corporate Governance in EU

European company law was long silent on risk management merely mentioning the board’s responsibility for internal organization. Such is the case of rules dating back as far as from the 1930s. A variety of policy-makers have positioned risk management on top of their schedule.91 European regulators employed the international agenda without delay in the European post-crisis banking directives.92 Recent plans in corporate governance embrace the European Commission’s proposal to add to risk management disclosure for large and listed firms. The proposal follows recommendations by the Reflection Group on the Future of EU Company Law and obtains Denis, Diane, and John J. Mc Connell. 2003. “International Corporate Governance.” Journal of Financial and Quantitative Analysis, 38(1): 1–36. 90 Djankov, Simeon, Rafael La Porta, Florencio Lopez-de-Silanes, and Andrei Shleifer. 2006. “The Law and Economics of Self-Dealing.” NBER Working Paper 11883. 91 G20 Declaration Summit on Financial Markets and the World Economy (Washington, D.C.: 15 November 2008, at 3-4; G20 Declaration on Further Steps to Strengthen the Financial System (London: 4–5 September 2009); G-20 Toronto Summit Declaration (Toronto, 26–27 June 2010) at 6-7; G20 Cannes Summit Final Declaration (Cannes, 4 November 2011) at 9-10; IOSCO, Final Report on the Subprime Crisis May 2008). 92 Eddy O. Wymeersch, Risk in Financial Institutions – Is It Managed?, Ghent University Financial Law Institute Working Paper No. 2012-04, http://ssrn.com/abstract¼1988926 (2012) (‘[a]ll this has led to a new perception where ‘risk’ is the master of the game’). Recitals 25, 30 of and new Article 122a as inserted by Directive 2009/111/EC of 16 September 2009 amending Directives 2006/48/ EC, 2006/49/EC and 2007/64/EC as regards banks affiliated to central institutions, certain own funds items, large exposures, supervisory arrangements, and crisis management (‘CRD II’); Recitals 1-2, 8-9, 16-17, & 45 of Directive 2010/76/EU of 24 November 2010 amending Directives 2006/48/EC and 2006/49/EC as regards capital requirements for the trading book and for re-securitisations, and the supervisory review of remuneration policies (‘CRD III’); Recitals 54, 57, 62, & 66, & Articles 74(1) & 76, CRD IV, as well as many detailed provisions of the CRR (e.g. Articles 20 (6), 49 (1)(d), & 103(b)). 89

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from the policy thoughts made public by the Commission’s Action Plan, but is the outcome of the Commission’s project on disclosure of nonfinancial information, which in sequence based on the Corporate Social Responsibility movement.93 The Reflection Group94 on the Future of EU Company Law made two proposition: Firstly, it suggested to amplify awareness of risks by entailing the board and management “to explain, avoiding boilerplate approach, risk management functions, risk management policies, structures and procedures, in the corporate governance report” by amendment of Directive 2006/46/EC; Secondly, it recommended the taking up of a non-binding Commission Recommendation with an intend to reinforce the value of board lapse over the formation of risks. To that extent, Member States have to take on the procedures that best match their board formation and board traditions portraying a variety of options, embracing, but not restricted to, the setup of: “(a) ‘adequate risk management processes and internal control mechanisms including all operational activities not merely the financial reporting process;’ (b) ‘adequate procedures to integrate risk monitoring systems into the company in a consistent way so that the risks can be measured, monitored and controlled at the level of the company, including subsidiaries; (c) an organization structure in line with the requirement that ‘the person or committee responsible for risk management should have a strong status within the entity and strong reporting lines to the relevant committee and board’, and (d) a system ‘providing for the consistent reporting of information on risk and risk management systems’.”95 It has to be taken into consideration that the European Commission,96 utilizing a broad definition of accountability of companies for their influence on the social order, has a long practice of engaging in corporate social responsibility.

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Reflection Group on the Future of EU Company Law (2011), 39–42. P44. Reflection Group on the Future of EU Company Law (2011), 39–42. http://ec.europa.eu/internal_ market/accounting/non-financial_reporting/index_en.htm. 95 Action Plan: European company law and corporate governance – a modern legal framework for more engaged shareholders and sustainable companies, COM (2012) 740 final, 5-6. at 6 (‘boards should give broader consideration to the entire range of risks faced by their company. Extending the reporting requirements with regard to non-financial parameters would help in establishing a more comprehensive risk profile of the company, enabling more effective design of strategies to address those risks. This additional focus on non-financial aspects would encourage companies to adopt a sustainable and long-term strategic approach to their business. In order to encourage companies to . . . give greater consideration to non-financial risks, the Commission will make in 2013 a proposal to strengthen disclosure requirements with regard to . . . risk management through amendment of the accounting Directive[s].’). 96 European Commission, Greenpaper promoting a European framework for Corporate Social Responsibility, 18 July 2001, COM (2001) 366 final, 6; European Commission, Communication from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions – A renewed EU strategy 2011-14 for Corporate Social Responsibility 25 October 2011, COM (2011) 681 final, 7. 94

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Current growth tendency in Europe corporate governance is dedicated set of laws for listed companies pointing out that mounting convergence in internal control means unconstrained from the board composition.97 EU publishes the Code of Best practices and the 2006 Directive obliges that each listed company has to announce an annual corporate governance statement to what point the firm has to abide by that code. Among its main principles is the disconnection of function between the CEO and the Chairman as it affirmed that the Chairman and CEO roles have to be separated and the CEO should not right away turn into Chairman of either a unitary or a supervisory board. It has to be taken into account that after the crisis 2009 in Europe, there is no definition of shareholder by reason of national protectiveness of company law; no harmonization of record date; and no shareholder identification. The financial crisis can be an element to failures and drawbacks in corporate governance scheme, including risk management system and executives’ salaries. Throughout crisis, companies with more independent boards introduced more equity capital, which to a degree affected them to go through worse stock returns.98 The European code should be completed so that basic Corporate Governance (CG) guidelines were marked out to promote best CG practices in every subject for all listed companies in European Economic Area. In addition, the debate on bank governance concerns not only the boards but also the governance of banking supervision with obviously recognized responsibility principles.99 The swift growth in new goods and alterations in market construction distresses the advancement of procedures and infrastructure of risk management. Moreover, the most imperative feature that could underline all risks in time is to carry out audits on liquidity, capital, and balance sheet consolidation.100 Corporate governance arrangements are relevant for investment behavior and weak corporate governance leads to incompetent investment choices.101 Companies that had more complicated risk management faced prominent failure rates for the reason that the superiority such systems engendered among executives.102

Hopt, Klaus J., and Leyens, Patrick C., (2004), Board Models in Europe – Recent Developments of Internal Corporate Governance Structures in Germany, the United Kingdom, France and Italy, ECGI Law Working Paper, No. 18/2004. 98 Erkens, David., Hung, Mingyi., and Matos, Pedro., (2010), Corporate Governance in the 20072008 Financial Crisis: Evidence from Financial Institutions Worldwide, SSRN Working paper Series. 99 Dermine, J., (2013), Bank Corporate Governance, Beyond the Global Banking Crisis, Financial Markets, Institutions & Instruments, Vol. 22, Issue 5. 100 Bekiaris, M., Koutoupis, A.G., and Efthymiou, T., (2013), Economic Crisis Impact on Corporate Governance and Internal Audit: The Case of Greece, Corporate Ownership & Control, Vol. 11, Issue 1. 101 Giroud, Xavier, and Holger M. Mueller, 2011, Corporate governance, product market competition, and equity prices, Journal of Finance 66, 563–600. 102 Nocera, J. (2009). Risk mismanagement. New York Times, 4. 97

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Li103 indicated a strong positive association between risk management and corporate governance as risk management developed into an index to determine triumph of corporate governance in many states. Corporate governance arrangements demand boards of directors to be transparent about the strategy and risk desire of their firms requiring competent reporting systems that permit boards to monitor their firms and to reply in an apt manner if required. Thus, corporate governance makes risk management a supervision responsibility of the board functioning to monitor the efficiency of a firm’s management practices and to make alterations as wanted. Kirkpatrick104 indicated key risk management failures in major financial institutions as a result of unacceptable corporate governance dealings and information regarding exposures did not reach the board of directors. In other cases, boards had approved risk oversight strategies but neglected to observe their implementation. There is a link of the crisis to extreme risk-taking which is most all-encompassing. The financial crisis is related to a governance crisis, There are links between corporate governance and risk management and so, risk management is an indispensable aspect of good corporate governance and vice versa.105 Risk management works hand in hand with corporate governance as a channel of constraining agency costs and supporting competent and wise management. Regarding the role of risk management and corporate governance in the financial crisis, the appliance of essential principles of modern risk management has protected financial corporation from being defenseless to shocks in the mortgage market as they ascertained to be.106 Many private sector companies take on risk management. In the financial services business, both interest and capacity in risk management are growing speedily. According to Modigliani and Miller,107 the value of a company is unfettered of its risk structure. Companies amplify predictable earnings, apart from the risk involved. Holders of securities attain risk transfers via suitable portfolio allocations. The agency conflicts in risk management mold a bond between corporate hedging actions and corporate governance apparatus in no less than three ways. Corporate governance influences company’s decision to utilize derivatives for hedging or speculation, given that managers in companies with weak checking surroundings have more freedom of choice over their companies’ activities and are less expected to be closely controlled for any unacceptable use or non-use of derivatives. The 103 Li, P. (2009). How can corporate governance control enterprise’s financial risk? http://papers. ssrn.com/sol3/papers.cfm?abstract_id¼1523519. 104 Kirkpatrick, G. (2009, February 27). The corporate governance lessons from the financial crisis (Annual Report). Organization for Economic Co-operation and Development. 105 Rose, P. (2010, June 25). Regulating risk by strengthening corporate governance (Public Law and Legal Theory Working Paper No. 130). http://ssrn.com/abstract¼1630122. 106 Lang, W. W., & Jagtiani, J. A. (2010). The mortgage and financial crises: The role of credit risk management and corporate governance. Atlantic Economic Journal, 38(2), 295–316. 107 Modigliani, F. and Miller, M.H. (1958), “The Cost of Capital, Corporation Finance and the Theory of Investment,” American Economic Review, 48, 261–297.

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ex-post governance devices supervising managerial activities on hedging lessen the level of managerial compensation related to tolerating the extra firm-specific risk that can be hedged away and augment the board of directors’ capacity to determine managerial running by dropping the noise associated with performance measures.108 Companies with a greater monitoring of managerial behavior employ derivatives in order to eradicate operating risks and greater external financing. Risk management is valuable to a company as a consequence of reducing its tax payments, its financial distress costs, its information unevenness costs, and its financing costs. Managers accomplish high risky projects or under-hedging strategy to take advantage of shareholders’ limited liability, principally existing in financially troubled companies.109 The accounting and market-based operation of companies with larger boards is drastically less volatile.110 Besides, the board size is related to lower return volatility.111 V. Taia et al.112 argue that “the board of directors, especially the auditing committee, plays an important role in monitoring firm’s hedging decisions. The characteristics of the board, including board size, the number of auditing committee members, the number of auditing committee meeting, the percentage of financial experts in audit committee, and the number of independent directors, show significant positive impact on firm’s decision of whether to hedge and the extent of hedging. Second, we find that risk-shifting behavior exists in some of S&P 500 firms that are in financial distress. In contrast to the existing finding that the possibility of hedging increases with firm’s leverage level, these high-leveraged S&P 500 firms are less likely to hedge their risk exposure. In addition, even though these firms hedge their risk, the situation of high leverage also negatively affects their hedge ratios. The evidence supports that some S&P 500 firms would increase their risk exposure when they are in financial distress. Third, when firms are close to financial distress, these board characteristics demonstrate additional effect on the hedging decision. This result indicates that corporate governance from the board is critical in determining the risk-shifting behavior. Moreover, the result is robust to a subsample of derivative hedging firms, the endogeneity problem, and industrial difference. To the authors’ knowledge, this is the first empirical evidence of the effect of corporate governance on risk-shifting in the literature.” Is there any relation between risk management and managerial agency costs? It has to be taken into account that one rationalization for RMJ (juridification of risk

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DeMarzo, Peter, and Darrel Duffie, 1995. Corporate incentives for hedging and hedge accounting. Review of Financial Studies 8(3), 743–771. 109 Eisdorfer, Assaf, 2008. Empirical evidence of risk shifting in financially distressed firms. Journal of Finance 63(2), 609–637. Purnanandam, Amiyatosh, 2008. Financial distress and corporate risk management: Theory and evidence. Journal of Financial Economics 87(3), 706–739. 110 Cheng, S. 2008. Board size and the variability of corporate performance. Journal of Financial Economics 87, 157–176. 111 Pathan, S., 2009. Strong boards, CEO power and bank risk-taking. Journal of Banking and Finance 33, 1340–1350. 112 Vivian W. Taia, Yi-Hsun Lai, Tung-Hsiao Yang, Min-Teh Yu Corporate Hedging and Corporate Governance: The Role of the Board and the Audit Committee www.ssrn.com P 18.

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management) is its positive consequence on corporate governance such as on dropping managerial agency costs and supporting manager’s and shareholders’ welfare. Nonetheless, high-level risk management helps in covering up or deepening agency conflicts by concealing the dominance of conflicting interests upon a given resolution. Which is the relation between risk management and controlled companies? A further validation for risk management regulation is the backing of the long-term stability of a company.113 It has to be taken into account that an economic shock wave or institutional malfunction triggers a series of bad economic upshots.114 Monica Billio115 et al. argue that “Systemic risk can be defined as the probability that a series of correlated defaults among financial institutions, occurring over a short time span, will trigger a withdrawal of liquidity and widespread loss of confidence in the financial system as a whole”. Furthermore, highly developed risk management does not lead to a lower level of company-explicit risk for the reason that sophisticated risk management permits the company to advance the exercise of its capital by internal hedging and netting, reading in a higher taken as a whole point of risk. In addition, from a macroeconomic standpoint, risk management methods end up escalating systemic risk by elevating each unique market contestant’s debt-to-equity ratio which means lessening its flexibility to shocks. To that extent, financial companies with highly developed risk management have better retrieval of debt and make use of a greater degree of influence.116 Accordingly European and global financial law incentivize the usage of sophisticated risk management structures by tolerating institutions that execute sophisticated risk management systems to introduce a greater inclusive degree of force. L. Enriques, D. Zetzsche117 argue that “that the purpose of risk management is to better handle risks: risk management is not about avoiding risk altogether and, most importantly, does not necessarily imply even risk mitigation. In fact, risk management may justify taking on more risk than it would otherwise be the case, thanks to risk management techniques such as internal netting, hedging and diversification and building on the idea that future events’ probability can be gauged from past data and that such risk measurement legitimizes risky business choices,... risk management is arguably superfluous for companies with a dominant shareholder, and disproportionately burdens small and medium enterprises.”

113 Action Plan: European company law and corporate governance – a modern legal framework for more engaged shareholders and sustainable companies, COM(2012) 740 final, 5-6. 114 Steven Schwarcz, Systemic Risk, 97 GEO. L.J. 193, 198 (2008) (‘These consequences could include (a chain of) financial institution and/or market failures.’). 115 Monica Billio et al., Econometric measures of Systemic Risk in the Finance and Insurance, NBER Working Paper Series 16223, 1 (July 2010) www.nber.org/papers/w16223. 116 A. Sinan Cebenoyan & Philip E. Strahan, Risk Management, Capital Structure and Lending at Banks, 28 J. BANK. FIN. 19, passim (2004). 117 Luca Enriques, Dirk Zetzsche The Risky Business of Regulating Risk Management in Listed Companies 10/2013 IFS – Propter Homines Chair Working Paper 002/2013 p31. Center for Business and Corporate Law Research Paper Series (CBC-RPS) http://iur.duslaw.eu/de 0052/ 2013 at: http://ssrn.com/abstract¼2344314.

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Defining Risk Management

Risk measurement is the classification and analysis of both quantitative and qualitative risks to the accomplishment of business objectives producing a foundation for shaping how risks should be administered. Risk is measured on an intrinsic and residual basis, tolerating a firm to comprehend the degree to which impending events influence objectives from two viewpoints, that is, probability and effect. It has to be taken into account that there is no generally accepted definition of risk in strategic management. The main uses of the term are in reference to unexpected variation or negative variation in commerce outcome variables such as revenues, costs, profit, and market share. Managers commonly correlate risk with negative result.118 As a general rule, a real risk is an amalgamation of the possibility or occurrence of an incident and its consequences, which is usually negative measured by the unpredictability of results. Uncertainty is less defined for the reason that the possibility of an uncertain event is unidentified as is its effect. Moreover, risk management produces value. Capital markets are often defective in providing funds to those companies which are implicated in new but perilous projects. Companies let their views about the rewards for bearing hedge-able risks influence their hedge ratios in a noteworthy manner. If a company’s management supposes that it has acknowledged a market inadequacy, it should take advantage of it by augmenting shareholder wealth. When management deems that it can spot market inefficiencies, it should make use of these inefficiencies paying close attention to the likelihood that unfavorable result would put the company on the point of or in financial distress. Therefore, an imperative quantity of risk with this view of risk management is the possibility that the company will turn out to be financially troubled or will reach a financial state of affairs that is worse than the one that would permit the company to engage in its by and large strategy. Economists differentiate between risk and uncertainty. Concerning risk, it is understood that the possibilities of future loss are identified, while possibilities are not identified concerning uncertainties.119 Besides, the term “uncertainty” as utilized in strategic management and organization theory refers to the unpredictability of environmental or organizational factors that influence corporate operation120 or the shortcoming of information about these factors.121 Uncertainty about environmental and organizational factors diminishes the predictability of corporate outcome and so,

118

March, James G. & Zur Shapira. 1987. Managerial perspectives on risk and risk taking. Management Science, 33: 1404–18. 119 Frank H. Knight, Risk, Uncertainty And Profit (1921). Michel Crouhy, Dan Galai, & Robert Mark, The Essentials Of Risk Management 88 (2006). at 9-10 (encouraging firms to address the issue openly: ‘Transparency about what we know and what we don’t know, far from undermining credibility, helps to build trust and confidence.’). 120 Miles, Raymond E. & Charles C. Snow. 1978. Organizational strategy, structure, and process. New York: McGraw-Hill. 121 Galbraith, Jay R. 1977. Organization design. Reading, Mass.: Addison-Wesley.

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multiplying risk. Moreover, uncertainty comes up from exogenous shocks, unforeseeable behavioral selections, or mixture of the two. Particular alarm of supervising institutions is to establish a regulation which makes certain a suitable risk management as a basis of the consolidation of banking supervision or other type of companies. Issues that slow down the banking systems financial integration course are the multiplicity of national banking systems with various national regulations, as a result of the particularities at a state level, such as customer traditions, the partiality of home consumers, the costs of banking services and products, and the absence of a consolidated supervision and regulation. Speedy innovations and financial flows owing to the technological advancement and deregulation are key characteristics of financial markets resulting in significant changes in banking activities and escalating competitive burden among banks and non-banks in a similar way. Globalization and deregulation have amplified market volatility, risks and uncertainties, possibilities for infectivity. There is a need to reduce volatility as a measure of the extent of risk management. Companies hedge some risks so that they can take more of other risks. A significant measure of risk management is the prospect that a company will become financially troubled or will arrive at a financial situation that is worse than the one that would permit a company to follow its whole strategy. Financial risk consists of embarking on opportunistic activities correlated to future risks that may engender positive or negative consequences.122 Nowadays, risk management at banks has come under escalating scrutiny. Banks and bank consultants have tried to trade complex credit risk management systems introducing borrower risk such as the risk-reducing benefits of diversification across borrowers in a large portfolio. Regulators considered using banks’ internal credit models to create capital competence standards. Banks invest in private information that makes bank loans illiquid avoiding failure through a selection of means, including holding a capital buffer of adequate size, holding enough liquid assets, and employing risk management.123 It could be argued that active risk management permits banks to hold less capital and to invest more insistently in risky and illiquid loans.124 Banks that buy and sell their loans hold a lower level of capital per euro of risky assets than banks not employed in loan buying or selling. To that extent, credit risk management through active loan buy and sell activity influences banks investments in risky loans. It is worth mentioning that there is a positive relation between company value and the use of foreign currency derivatives which means that hedging raises company

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Dionne, G., Hammami, K., Gauthier, G., Maurice, M., Simonato, J.G., 2010. Default risk in corporate yield spreads. Financial Management 39, 707–731. Crouhy, M., Mark, R., Galai D., 2000. Risk Management, New York: McGraw Hill. 123 Diamond, D., 1984. Financial intermediation and delegated monitoring. Review of Economic Studies 51, 393–414. 124 Froot, K.A., Stein, J.C., 1998. Risk management: Capital budgeting, and capital structure policy for financial institutions: An integrated approach. Journal of Financial Economics 47, 55–82. Froot, K.A., Scharfstein, D.S., Stein, J.C., 1993. Risk management: Coordinating corporate investment and financing policies. The Journal of Finance 48, 1629–1658.

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value.125 Cash flow unpredictability directs to internal cash flow shortfalls, which in sequence lead to higher costs of capital and forgone investments. Companies capable of minimizing cash flow volatility are able to invest more.126 It could be said that the association between risk and loan sales activity implies that these moves toward higher risk actions do not lead to higher risk. The riskreducing benefits of engagement in the loan sales market are used by banks on higher risk actions. Profits are higher at banks that buy and sell loans.127 S. Cebenoyan and P. Strahan128 argue that “the banks that engage in both buying and selling of loans may be better able to take advantage of positive net-present-value investment opportunities, as they are able to increase their C&I and commercial real estate loans and are better able to manage with less liquidity and less capital. The buying and selling of loans at the same time seems to allow banks to be more flexible and more aggressive. The flexibility reduces the burden of carrying more capital, and lower yield higher liquidity assets; and the aggressiveness allows them to increase their higher risk and higher yield assets.” Many private sector companies engage in risk management. Especially in the financial services industry such as investment banking, commercial banking, and insurance, both interest and capacity in risk management are mounting swiftly.129 Modigliani and Miller130 argue that “the value of a firm is independent of its risk structure; firms should simply maximize expected profits, regardless of the risk entailed; holders of securities can achieve risk transfers via appropriate portfolio allocations.” The rapid development in risk management interest and capacity is driven by several variables such as the growth in financial derivative markets and products, and the stimulating competence for risk management that they provide.131 Effective volatility forecasts enhance financial risk management by holding prospective complicated nonlinear portfolios at different horizons. Risk management regulations are not embraced as an alternative for substantive rules. Many of the active or potential risk management rules, and particularly those

125 Allayannis, G., Weston, J.P., 2001. The use of foreign currency derivatives and firm market value. Review of Financial Studies 14, 243–276. 126 Minton, B.A., Schrand, C., 1999. The impact of cash flow volatility on discretionary investment and the costs of debt and equity financing. Journal of Financial Economics 54, 423–460. 127 Sinan Cebenoyan, Philip E. Strahan, Risk management, capital structure and lending at banks. Journal of Banking & Finance 28 (2004) 19–43. 128 Sinan Cebenoyan, Philip E. Strahan, Risk management, capital structure and lending at banks. Journal of Banking & Finance 28 (2004) 19–43, p. 41. 129 Froot, K.A. and O’Connell, P.G.J. (1997), “On the Pricing of Intermediated Risks: Theory and Application to Catastrophe Reinsurance” NBER Working Paper No. 6011. 130 Modigliani, F. and Miller, M.H. (1958), “The Cost of Capital, Corporation Finance and the Theory of Investment,” American Economic Review, 48, 261–297. 131 Engle, R. F. (1982), “Autoregressive Conditional Heteroskedasticity with Estimates of the Variance of United Kingdom Inflation,” Econometrica, 50, 987–1007. Engle, R.F., Lilien, D.M., and Robins, R.P. (1987), “Estimating Time Varying Risk Premia in the Term Structure: The ARCH-M Model,” Econometrica, 55, 391–407.

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Defining Risk Management

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applying to listed companies or even large companies as such, habitually interfere to control managerial discretion in performing business activities up to now unregulated. Habitually, such procedural or disclosure rules just complement existing and unchanged substantial rules.132 Furthermore, risk management-related regulation comes in many forms. To that extent, the law133 may: firstly oblige companies to take on explicit risk management/ measurement modus operandi; secondly compel corporate governance arrangements to run risks, such as by demanding firms to have a risk committee within the corporate board, the existence of independent directors therein, internal ‘status’ needs for head risk officers, taking apart of risk management from operating management operations, and board duties to handle risks; thirdly authenticate companies’ risk management modes as a stipulation to further regulatory treatment; fourthly force a generic prerequisite to take up sufficient risk management measures; fifthly demand top management to confirm the efficacy of risk management concerning internal control policies and measures and detect material weaknesses thereof, and sixthly compel disclosure responsibility to elucidate risk management governance, policies, and measures to investors and the public at large. It could be argued that each of these set of laws is a pattern concerning the “juridification” of risk management and risk management arrangements become legally pertinent. It is worth mentioning that there is use of internal ratings-based models to derogate from default capital adequacy ratios under the Basel II134 and III135/ CRD136 rules on credit risk and internal models to derogate from default capital adequacy ratios for counterparty risk. Moreover, it is imperative that investment companies have successful procedures for risk appraisal: Article 13(5), Directive 2004/39/EC of the European Parliament and of the Council of 21 April 2004 on markets in financial instruments, amending Council Directives 85/611/EEC and 93/6/EEC and Directive 2000/12/EC of the European Parliament and of the Council and repealing Council Directive 93/22/EEC. Article 7 of Parliament and of the Council as regards organizational requirements and operating conditions for investment companies and defined terms for the purposes of that Directive offers a Neil Gunningham & Darren Sinclair, Organizational Trust and the Limits of Management-Based Regulation, 43 L. & SOC. REV. 865, passim (2009). Christopher D. Stone, Where The Law Ends: The Social Control Of Corporate Behavior, 120-1 (1975). 133 Article 13, 44 and Recitals 11-18 of the Commission Delegated Regulation (EU) No 231/2013 of 19 December 2012 supplementing Directive 2011/61/EU of the European Parliament and of the Council with regard to exemptions, general operating conditions, depositaries, leverage, transparency and supervision. 134 Basel Committee on Banking Supervision (‘BCBS’), The internal ratings-based approach, Bank for International Settlement (2001), http://www.bis.org/publ/bcbsca05.pdf. 135 BCBS, Basel III: A global regulatory framework for more resilient banks and banking systems, Bank for International Settlement (rev., 2011), available at http://www.bis.org/publ/bcbs189.htm. 136 Articles 77 and 78 of CRD IV and Articles 142-191 Regulation (EU) No 575/2013 of 26 June 2013 on prudential requirements for credit institutions and investment firms and amending Regulation (EU) No 648/2012. Ian Ayres & John Braithwaite, Responsive Regulation. Transcending The Deregulation Debate Ch. 4 (1992). 132

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somewhat more expressed agenda of risk management duties. The European Commission’s137 proposal to improve disclosure of nonfinancial risks and their management, which follows risk management-related recommendations in different policy documents it has issued since 2010, prompts us to reflect upon the merits of RMJ and underline its weakness and unintended consequences. Otherwise, risk management procedural rules can take the form of best practice codes, with the law entailing firms to reveal whether they conform with or they clarify why they do not.138 It is argued that adding to the disclosure laws and regulations on risk management might not be the response.139 It is argued that there is a positive effect of RMJ (juridification of risk management) on market effectiveness. According to the European Commission, the revelation of non-financial information augments a firm’s responsibility and functioning, and the competence of the Single Market. It could be said that risk management as a managerial tool per se is not challenged, but to a certain extent, its “juridification.”

5.10

The Limits of Risk Management

Risk management regulation makes possible misperceptions about what risk management can and cannot accomplish. While risk management as a managerial means is naturally insufficient, the incorporation of risk management into regulation may have negative outcomes in two ways. On the one hand, ex ante, market contestants, particularly outside the company, build up an impression of omitted security over how much a company’s management is in charge of the outside world. The notion that managing risk denotes having risks under command is apparently not right, but it may only be expected to share it if risk management is legally and politically allowed and if companies invest in it as an end result. On the other hand, ex post, risk management regulation engenders a reverse misapprehension on the part of law enforcers managing circumstances in which destructive actions have occurred. Moreover, if the law necessitates or anticipates sufficient risk management policies and measures, then the existence of procedures in place and complied with, no

137 European Commission, Proposal for a Directive of the European Parliament and of the Council amending Council Directives 78/660/EEEC and 83/449/EEC as regards disclosure of non-financial and diversity information by certain large companies and groups, Com (2013) 207 final (16 April 2013). European Commission, Corporate governance in financial institutions and remuneration policies (Green Paper), COM(2010) 284, 7; EU corporate governance framework, Green Paper, COM(2011) 164/3, at p. 3 & 10. 138 Christoph van der Elst, Risk management in corporate law and corporate governance, in Corporate Governance And The Global Financial Crisis: International Perspectives 215, 236 (William Sun, Jim Stewart & David Pollard eds. 2011). 139 Marijn van Daelen, Christoph van der Elst & Arco van de Ven, Risk Management Interconnections in Law, Accounting and Tax, in Risk Management And Corporate Governance 198, at 216-217 & 226 (Marijn van Daelen & Christoph van der Elst eds, 2010).

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destructive happening would have happened, and for this reason, management or the board is responsible for the reason that their risk management procedures were beneath the minimal adequate standard. Is risk management merely risk mitigation? It could be argued that risk management is not risk mitigation. Risk management means embrace firstly selecting to abstain from assured risky business activities; secondly compelling deterrent and quick to respond control procedures with the purpose of mitigate operational risk; thirdly recognizing that definite risks are needed to engender the suitable amount of return; and fourthly relocating risk to third parties all the way through hedging and insurance.140 It is considered that operational risk is “the risk of loss resulting from inadequate or failed internal processes, people and systems or from external events, and includes legal risk.”141 It has to be taken into account that risk management includes three processes: risk assessment, risk mitigation, and evaluation and assessment allowing IT managers to assess the operational and economic costs of defensive actions and so, accomplishing gains in mission capability by protecting the IT systems and data that assist a company’s tasks. Diminishing negative influence on a company and requirement for reliable basis in decision-making are the deep reasons a company employs a risk management process for its IT system. Risk assessment is the first process in the risk management methodology used by companies in order to establish the extent of the prospective threat and the risk related to an IT system throughout its system development life cycle (SDLC). Diminishing negative influence on a company and need for firm basis in decision-making are the essential reasons companies employ a risk management procedure for their IT systems. Valuable risk management is incorporated into the SDLC. An IT system’s SDLC has five phases: initiation, development or acquisition, implementation, operation or maintenance, and disposal. Nonetheless, the risk management method is the same in spite of the SDLC part for which the assessment is being performed. Thus, risk management is an iterative procedure that can be executed during each key phase of the SDLC. Risk assessment is the first procedure in the risk management method. Companies utilize risk assessment to ascertain the coverage of the prospective threat and the risk related to an IT system throughout its SDLC. Risk is a gathering of the probability of a given threat-source’s exercising a specific prospective vulnerability, and the consequential influence of that unfavorable event on a company. Once the risk assessment has been accomplished by discovering threat-sources and vulnerabilities are identified, risks assessed, and suggested controls supplied, then the results are documented in an official report assisting senior management, the mission owners, make decisions on policy, procedural, budget, and system operational and management modifications. Risk mitigation engrosses prioritizing, evaluating, and

140

Michel Crouhy, Dan Galai, & Robert Mark, The Essentials Of Risk Management 88 (2006). Regulation (EU) No 575/2013 of 26 June 2013 on prudential requirements for credit institutions and investment firms and amending Regulation (EU) No 648/2012. Article 4 (1) No. 52 CRR.

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implementing the suitable risk-reducing controls recommended from the risk assessment procedure. Accountability is the security objective that engenders the necessity for actions of an entity to be traced exclusively to that entity supporting deterrence, fault isolation, intrusion detection and prevention, and after-action recovery and legal action. Confidentiality is the security aim that spawns the requisite for protection from intentional or accidental attempts to carry out unauthorized data reads covering data in storage, during processing, and in transit. Integrity is the security purpose that creates the obligation for protection against either intentional or accidental attempts to violate data integrity or system integrity. Risk assessment is the procedure of identifying the risks to system security and determining the likelihood of happening, the resulting influence, and supplementary safeguards that would lessen this influence. Part of risk management is synonymous with risk analysis. Risk management is the whole procedure of identifying, controlling, and mitigating information system-related risks. Risk management embraces risk assessment; cost–benefit analysis; and the selection, implementation, test, and security appraisal of safeguards. A whole system security evaluation judges both effectiveness and efficiency, including effect on the task and restrictions by reason of policy, regulations, and laws. System security is a system quality and a set of mechanisms that cross the system both logically and physically. The five security aims are integrity, availability, confidentiality, accountability, and assurance. Threat is the prospective for a threat-source to work out a particular vulnerability. Threat analysis is the inspection of threat-sources against system vulnerabilities to find out the threats for a specific system in an actual operational environment. Vulnerability is a defect or drawback in system security procedures, design, implementation, or internal controls that could be used and result in a security infringement or a violation of the system’s security policy.142 The ratio of unrelated directors is really interconnected to the company’s use of interest rate derivatives in harmony with hedging in the interests of shareholders. Nonetheless, some of the company’s risk management activity is planned to maximize the manager’s effectiveness rather than the company’s value.143 Are there limits of risk measurement? It has to be taken into account that the new COSO144 framework of 2013, significant for nonfinancial companies, highlights the magnitude of risk measurement as the foundation for shaping how risks will be handled. To that extent, risk measurement refers to the quantification of the most ordinary features of risks on the footing of prospective austerity and possibility. It has to be taken into consideration that each risk measurement mode has its own 142

Gary Stoneburner, Alice Goguen, and Alexis Feringa, Risk Management Guide for Information Technology Systems Recommendations of the National Institute of Standards and Technology, NIST Special Publication 800-30. 143 Whidbee, David, and Mark Whoar, 1999, Derivatives activities and managerial incentives in the banking industry, Journal of Corporate Finance 5, 251–276. 144 COSO, Internal Control — Integrated Framework: Executive Summary (May 2013), http:// www.coso.org/documents/990025P_Executive_Summary_final_may20_e.pdf.

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limits. Risk measurement systems offer a quantitative frame for making choices founded on event likelihood. Prospects are derived from hypothesis that is founded on past data, experience, or the ordinary allotment. Yet, the best data do not modify the reality that the past is the past and that the future is in doubt embracing the likelihood of incidents whose possibility is unidentified. It has to be taken into account that risk measurement as a risk management procedure involves considering uncertainties as risks. In addition, risk management sets up a new form of risk known as model risk which is the risk that the model is founded on make simpler hypothesis that are deceiving or improper. The influence of model risk on a company’s fortune is based on the scale to which risk management induces decision-making, the effect being the result of factual significance such as in financial institutions, owing to the utter accumulation of data or legal significance as a result of RMJ.145 While quantitative risk management reaches conclusions founded on mathematical evaluation of raw data, qualitative techniques will employ common sense and reach a best guess in the high, mid, low range.146 Nevertheless, advanced “Monte Carlo” simulations rely on hypothesis implanted in the equation underlying the simulations.147 It has to be mentioned that chaos theory is applied to risk management148 and fuzzy logic is used in operational risk models.149 It has to be taken into account that the most popular risk measurement standard Value at Risk (VAR) embraces, primarily, the calculation methodology itself, which disregards “low probability, high impact ‘black swan’ events and fat tails.”150 A successful risk management procedure is an essential component of a profitable IT security program. Moreover, the key aim of a company’s risk management process is to safeguard a company and its capacity to perform the whole functioning, not just its IT assets. Consequently, the risk management is not regarded above all as a technical function carried out by the IT experts who conduct and manage the IT system, but as a vital management function of a company. The objective of

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Michel Crouhy, Dan Galai, & Robert Mark, The Essentials Of Risk Management 88 (2006). at 9-10 (encouraging firms to address the issue openly: ‘Transparency about what we know and what we don’t know, far from undermining credibility, helps to build trust and confidence.’). 146 Eric Gerding, The Outsourcing of Financial Regulation to Risk Models and the Global Financial Crisis: Code, Crash, and Open Source, 84 Wash. L. Rev. 127, 137 (2009); with regard to credit default swaps Christopher Brown & Cheng Hao, Treating Uncertainty as Risk: The Credit Default Swap and the Paradox of Derivatives, 46:2 J. ECON. ISSUES 303 (2012); Michael Power, Organized Uncertainty. Designing A World Of Risk Management 5-6 (2007). 147 Linda Allen, Jacob Boudoukh, & Anthony Saunders, Understanding Market, Credit, And Operational Risk – The Value At Risk Approach 176-7 (2004) (for VaR); for CoVaR Tobias Adrian & Markus K. Brunnermeier, CoVaR, FRB of New York Staff Report No. 348 (2011), http:// ssrn.com/abstract¼1269446, at 8. 148 Charles S. Tapiero, The Future of Financial Engineering, NYU Pol’y Research Paper (2013), http://ssrn.com/abstract¼2259232. 149 Marcelo G. Cruz, Modeling, Measuring And Hedging Operational Risk 169-70 (2002, Repr. 2008). 150 Linda Allen, Jacob Boudoukh, & Anthony Saunders, Understanding Market, Credit, And Operational Risk – The Value At Risk Approach 176-7 (2004).

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employing risk management is to allow a company to carry out its tasks by better securing the IT system that store, process, or transmit company’s information, by permitting management to make well-informed risk management decisions to rationalize the expenditures that are part of an IT budget, and by supporting management in authorizing a particular IT system adding to the performance of risk management. The head of an organizational unit must make certain that the company has the competence required to achieve its task. There is a need to determine the security means that their IT systems must have to offer the preferred level of task support in the face of real-world threats. Most companies have tight budgets for IT security; as a result, IT security spending must be evaluated as thoroughly as other management assessments. A coherent risk management method, when employed efficiently, can assist management ascertain suitable controls for providing the mission-essential security aptitude. It is not accurate to consider modern risk management theory as entailing that companies diminish hedge-able risks. What a company makes depends on its state of affairs. The lesser the leverage, the less beneficial is risk minimization. If a company’s management considers that it has acknowledged a market inadequacy, it utilizes it to augment shareholder wealth. On the other hand, it is vital to estimate managers’ bets comparative to the market. If managers perform reminiscent of money managers, they have to be assessed approximating money managers. When management categorizes market inefficiencies, it has to make use of these inefficiencies paying close attention to the possibility that unfavorable effects put a company near enough or in financial trouble. As a result, an imperative quantity of risk with this vision of risk management is the likelihood that a company turns out to be financially troubled or arrive at a financial situation that is worse than the one that would permit a company to track its whole strategy. Companies have a relative advantage in enduring some kinds of risks. If risk management is not focused on variance reduction, then much more attention should be dedicated to the control, management, and evaluation of risk taking, developing a better comprehension of the agency costs of risk taking.151 Does risk management amplify firm value? It should be taken into account that no financial policy decision influences the valuation of the company. Internally generated resources are less costly than external resources and so, different capital structure decisions have discrete value implications. If internal funds are less costly than external funds, then risk management adds value by permitting the company to administer its cash flows so that the less costly internal finance is offered on an “as needed basis.”152

Dolde, W., 1993, The trajectory of corporate financial risk management, Journal of Applied Corporate Finance 6, Fall, 33–41. 152 Froot, K.A., Scharfstein, D.S. et al. (1993) Risk Management: Coordinating Corporate Investment and Financing Policies. Journal of Finance 48 (5). 151

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5.11

Big Data: Risk Management

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Big Data: Risk Management

It could be said that the big data has altered the way in which organizational data of any industry are managed, analyzed, or leveraged and so, examining data to find hidden patterns, decision-making information has made big data a big issue. Thus, data generation from numerous sources and movement toward digital world have led to big data growth. In line, advanced information technology via cyberspace and cloud computing necessitate knowledge extraction at multiple levels, which means that the massive structured/unstructured data from numerous sources via websites, audio data, social media data, video data all develop urge of big data.153 To that extent, risks occur in the multifaceted industrial systems that administer huge data, so risk analytics have a valuable role in such kind of data management. Hence, big data comprises high volumes of data from heterogeneous sources with decentralized control which means that the connections of information entail testing to preserve quality of the system. In other words, big data is a value creator today and helps in boosting the operational, economic, and business performance. Moreover, big data is exemplified by big volumes, high capacities data with data variety which demands cost-effective decision-making by using innovative processing and so, it entails big volumes of very high-velocity, variable, and complex data which demand advanced techniques for capturing, storing, and analyzing the information. In addition, different big data systems are compared based on performance via testing and so, the system performance is enhanced by big data testing.154 Big data analytics refers to the collection and processing of datasets that are either too large or too complex for conventional data processing applications to control. Moreover, big data applications survey the bulk of data points from an indefinite number of users and apply advanced data analytics methods such as predictive or behavioral data analysis to produce value.155 In addition, big data analytics can be exploited to spot unforeseen correlations in large data pools, test expected correlations for causation, or determine the probability of a predefined pattern. Hence, big data is closely connected to artificial intelligence (AI) for the reason that the latter assists in putting the mass of data gathered to good use.

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Chang W.L, (2015), NIST big data interoperability framework, volume 1, definitions (NIST SP)1500-1 https://www.gartner.com/it-glossary/big-data/ TechAmerica Foundation, Federal Big Data Commission, (2012), DEMYSTIFYING. BIG DATA: A Practical Guide to Transform the Business of Government. Paryasto.M, Alamsyah.A, Ruhardjo.B, (2014), Big data security management issues, 2nd International conference on information and communication technology”, p. 59–63. 154 Loyd B.D, Kannan D.K, (2017), Identifying Design patterns for risk management system using big data analytics, International Conference on Trends in Electronics and Informatics, 305–312. Sun.M, Yang.W, Jiang.J, (2015), Big data: Risks and Regulatory Services, IEEE, 358–362. Chen. M, Chen.W, (2018), Testing of big data analytics by benchmark, IEEE international conference on software testing, Verification and validation workshops, 231–238. 155 Viktor Mayer-Schönberger & Kenneth Cukier, Big Data: A Revolution That Will Transform How We Live, Work, And Think 12-14 (2013) (predicting that big data will not only be a new source of economic value but will also transform the organization of society).

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Financial regulators have an important venture in guaranteeing the quality and consistent uptake of the safeguarding of customer information together with the broader need for stakeholders to align on principles governing the collection, use, and sharing of customer data. Eventually, the absenteeism of principles and resulting inappropriate use of customer data instigate a loss of trust leading to instability in the financial system. It is worth noting that the appreciation of the value of open data has led municipalities and states to mandate open data laws such as the France’s Digital Republic Act demanding government agencies to move to an open data orientation and to set quality standards for such data.156

5.12

Risk Management Implications and Finance

Risk management is a key topic in operations management and so, the financial development of cyberspace supply chain accelerates the modification of enterprise financing mode. Supply chain operations have entered the digital era with the emergence of blockchain technology. In the present time, supply chain finance is combined with cyberspace improving the information asymmetry of both parties through network function benefit and so, it aids the decision-making department to advance the financing problem of companies. Additionally, with the emergence and rapid development of E-commerce, the logistics industry gradually rises. Furthermore, there are risks in cyberspace supply chain finance; with the rapid development of cyberspace, new technologies have not been fully tested in practice, and hackers, network fraud, and other problems have surfaced endlessly. When the supply chain finance enters the cyberspace setting, there are software vulnerabilities, and if the repair is not timely, there will be a huge loss, which means that there may be information fraud, information leakage, capital loss, and other problems. To that extent, cyberspace supply chain finance has the qualities of vertical industry orientation, specialization, vulnerability, and instability. Credit risk management has evolved immensely in recent decades. Due to advances in information technology, the monitoring of credit risk has improved which means that owing to financial innovations, risk sharing has become easier to access. Some basic level of risk management is imposed upon banks by financial regulation and so, banks choose whether to gather additional information on credit risk, and whether to share credit risk. Competition pushes banks to implement advanced risk management practices. Sector concentration in the loan market promotes credit portfolio modeling, but it inhibits credit risk transfer. Furthermore, by implementing a credit portfolio model, banks detect the correlation within their loan portfolios adjusting their buffers or

156 https://www.republique-numerique.fr/pages/in-english Barcelona’s Open Data BCN http:// opendata-ajuntament.barcelona.cat/en/ https://contractfortheweb.org/.

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capital structures to their portfolio structures. Also, banks participate in credit risk transfer by swapping half of their loan portfolio for the loan portfolio of another bank which means that via risk transfer, banks spread their portfolios.157 Financial institutions face a variety of risks on their portfolios due to AI utilization and so, whether they be market and credit risk for investment portfolios, default and prepayment risk on their mortgage portfolios, or longevity risk on life insurance portfolios, the balance sheet of a bank or insurance firm is subjected to many risk factors. Hence, failure to manage these risks leads to insolvency with the accompanying losses to shareholders, bondholders, and customers or overly conservative business strategies, which hurt consumers. To that extent, together with qualitative assessments, portfolio risk management needs quantitative models that are accurate and fast to offer useful information to management. Furthermore, government regulations, such as solvency regimes, involve extensive calculations to generate the needed reports.158 Is the structure of the financial system a key determinant of systemic risk? It is worth mentioning here that systemic risk is the risk that an incident activates a loss of economic value or confidence in a large part of the financial system causing substantial adverse effects on the real economy. It has to be taken into account that shocks that hit part of the system, such as the subprime mortgage market in 2007, grow through a complex network of interconnections among financial and nonfinancial institutions having a disastrous effect on the entire economy.159 On the other hand, in the absence of this network, localized shocks hitting individual participants or certain parts of a financial system would not propagate and so, a network of interconnected players are denoting multifaceted links among financial market participants and institutions being the characteristic of the modern global

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Dilek Bülbül, Hendrik Hakenes, Claudia Lambert, What influences banks’ choice of credit risk management practices? Theory and evidence Journal of Financial Stability 40 (2019) 1–14 (Typically, by implementing both risk management instruments (advanced risk management), banks can diversify and fine-tune their portfolios. We find that credit portfolio modeling is more desirable when competition is high; it is also more desirable for higher sector concentration. Credit risk transfer is more desirable when competition is high and more desirable for lower sector concentration.) p. 11. 158 Lucio Fernandez-Arjona, Damir Filipovi´c, A machine learning approach to portfolio pricing and risk management for high-dimensional problems https://ssrn.com/abstract¼3588376. 159 Daron Acemoglu, Asuman Ozdaglar & Alireza Tahbaz-Salehi, Systemic Risk and Stability in Financial Networks, 105 AM. ECON. REV. 564, 564 (2015) (“Since the global financial crisis of 2008, the view that the architecture of the financial system plays a central role in shaping systemic risk has become conventional wisdom”). Ryan Bubb & Prasad Krishnamurthy, Regulating Against Bubbles: How Mortgage Regulation Can Keep Main Street And Wall Street Safe-From Themselves, 163 U. PA. L. REV. 1539, 1542 (2014) (describing how the shock hitting the real estate market had dramatic consequences on the U.S. economy).

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financial system.160 Luca Enriques161 et al. argue that “any deviation from corporate governance and corporate law core principles and rules with a view to curbing systemic risk is justified to the extent that the actions of the relevant players, that is, the managers, directors and shareholders of any given SIFI, affect systemic risk.” It has to be taken into consideration that borrowers with high liquidity risk are paying a markup to lock in their funding, independent of risk premiums demanded by lenders, but borrowers are paying higher rates to lock in their funding if they are exposed to liquidity shocks. Funding liquidity risk is the risk of a liquidity shock leading to a binding funding constraint. Moreover, banks are funding illiquidity for the reason that maturity transformation is at the center of their business model and so, funding liquidity risk materializes in the form of bank runs.162 To that extent, the global financial crisis of 2007–2009 reemphasized the significance of funding liquidity for financial stability enlightening that bank runs take place in wholesale funding markets.163 Moreover, it has to be taken into account that the funding liquidity risk channel relates to the lending business of banks because liquidity shocks are either positive or negative. Henceforward, banks with high liquidity risk have a motivation to demand immediacy by accepting lower interest rates to evade having to resort to the central bank. Alexander Bechtel et al.164 portray “the importance of sophisticated liquidity management for banks. Since it is costly to demand immediacy following liquidity shocks, banks must account for these additional costs in their business decision—for example, through liquidity transfer pricing. Quantifying the cost of funding immediacy enables banks understand the trade-off between larger liquidity buffers and the need to be more aggressive to obtain funding.” To that extent, it could be argued that internal procedures, such as liquidity transfer pricing and funding value alterations, generate a network through which inefficient liquidity management influences

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John C. Coates IV, Cost-Benefit Analysis of Financial Regulation: Case Studies and Implications, 124 YALE L.J. 882, 894 (2014) (noting that “financial markets are tightly interconnected systems (hence the now mainstream phrase “systemic risk”). Sheri Markose, Simone Giansante & Ali Rais Shaghaghi, ‘Too Interconnected to Fail’ Financial Network of US CDS market: Topological fragility and systemic risk, 83 J. ECON. BEHAVIOR & ORG. 627, 627 (2012) (noting that “[t] he 2007 financial crisis which started as the US ‘sub-prime’ crisis, through a process of financial contagion led to the demise of major banks and also precipitated severe economic contraction the world over”). Alessandro Romano, Horizontal Shareholding: The End of Markets and the Rise of Networks (2018), available at https://papers.ssrn.com/sol3/papers.cfm?abstract_id¼3255948. 161 Luca Enriques Alessandro Romano Thom Wetzer, Network-Sensitive Financial Regulation, ECGI Working Paper Series in Law, Working Paper N○ 451/2019 May 2019 https://ssrn.com/ abstract¼3387708. 162 Drehmann, M., and K. Nikolaou, 2013, “Funding liquidity risk: Definition and measurement”, Journal of Banking and Finance, 37, 2173–2182. 163 Perignon, C., D. Thesmar, and G. Vuillemey, 2018, “Wholesale Funding Dry-Ups”, Journal of Finance, 73(2), 575–617. 164 Alexander Bechtel Angelo Ranaldo Jan Wrampelmeyer, Liquidity Risk And Funding Cost, Working Papers On Finance No. 2019/03, Swiss Institute Of Banking And Finance (S/BF – HSG) https://ssrn.com/abstract¼3391129 P 34.

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investment decisions, pricing, and loan extensions which means that banks pass through the differences in funding costs to their clients, such that heterogeneity spreads outside funding markets. It is worth noting that both corporations and investors have become too shortterm oriented in their investment horizon, leading to decisions that upsurge nearterm reported profits at the expense of the long-term sustainability of those profits being externalities, borne by members of the workforce or society at large.165 Boards advance their analysis of ESG (environmental, social, governance) risks and opportunities at a practical level by bearing in mind how long-term investors integrate ESG factors into their decision-making procedure.166 It has to be taken into consideration that there has been a shift in power from managers to shareholders which is a move denoting the objective of market control of the corporation.167 Do corporations function apart from markets or function within markets and under market control? It seems that there is a view of market control based on two assumptions: first, shareholders have the right reasons to lessen the managerial agency problem, and, second, competitive markets are superior to institutions as controllers of production and so, shareholders are taking control. To that extent, the rise of hedge funds and other activist investors has produced a swing in power from managers to shareholders, who are now empowered to make business decisions at publicly traded corporations. On the other hand, there is a position of questioning the shareholder-centric view of the corporation, defending an alternative “team-production model” that accounted for the role of other stakeholders in the corporate organization, indicating the inadequacies of unrestricted shareholder power.168 Which is the importance of sophisticated liquidity management for banks? Since it is costly to demand immediacy following liquidity shocks, banks must account for these additional costs in their business decision—for example, through liquidity transfer pricing. Quantifying the cost of funding immediacy enables banks to understand the trade-off between larger liquidity buffers and the need to be more aggressive to obtain funding.’ To that extent, it could be argued that internal procedures, such as liquidity transfer pricing and funding value alterations, generate a network through which inefficient liquidity management influences investment decisions, pricing, and loan extensions which means that banks pass through the differences in funding costs to their clients, such that heterogeneity spreads outside funding markets.

165 BlackRock, “Larry Fink’s 2018 Letter to CEOs: A Sense of Purpose,” available at: https://www. blackrock.com/corporate/investor-relations/2018-larry-fink-ceo-letter. 166 Brandon Boze, Margarita KrivitsKi, david F. LarcKer, Brian tayan, and eva zLotnicKa, The Business Case for ESG Stanford Closer Look Series – CGRP77 May 23, 2019 at: https://ssrn.com/ abstract¼3393082. 167 William W. Bratton and Simone M. Sepe, Corporate Law And The Myth Of Efficient Market Control, https://ssrn.com/abstract¼3385735. 168 Lynn Stout, The Shareholder Value Myth: How Putting Shareholders First Harm Investors, Corporations And The Public (2012).

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It is worth noting that the instability of the financial sector during the Great Recession has left many questions unanswered concerning the risk management practices and hedging strategies of financial corporations and so, regulators have passed regulations across geographies and different parts of the financial sector. If there are no costs in raising external finance, then discrepancies in regulation do not affect the risk management decisions of financial companies. Nevertheless, if raising capital is costly, hedging choices are distorted and so, it is difficult to measure whether regulation is unreliable and distorts hedging decisions without knowing what optimal regulation is. Thus, it is not accessed how financial institutions respond to discrepancies in regulation and how hedging decisions are affected. Moreover, differences in the regulatory treatment of different products drive heterogeneity in hedging behavior across financial institutions in a large way. It seems that the regulatory value of assets and liabilities does not alter from one valuation date to the next, even though the economic value changes with fluctuations in the equity market or the yield curve.169 Besides, the value of derivatives is sensitive to interest rate and equity market movements under the regulatory framework and so, insurance firms have a reason to not hedge with derivatives for the reason that hedging the volatility in market values leads to volatility in regulatory capital as only derivatives are sensitive, while the rest of the regulatory balance sheet is largely insensitive. Ishita Sen170 argues that “derivatives reduce the volatility of capital and surplus for the average insurer exposed to RS guarantees by close to 26% between 2010 and 2016. In contrast, there is no discernible reduction for insurers that underwrite PRS guarantees owing to the absence of interest rate hedging with derivatives. My estimates imply that had regulation shifted in a consistent manner, insurers exposed to PRS guarantees would have an additional combined exposure to interest rate derivatives equal to $23 billion in 2016. As PRS liabilities are highly concentrated, a large fraction of this shortfall in exposures is concentrated among the largest 10 insurers, amounting to about 22% of their capital and surplus.” It could be said that the regulatory framework interacts with monetary policy shifts and so, when interest rates are low, the “Stochastic” framework controls with a higher likelihood. Conversely, when interest rates rise, “Stochastic” liabilities fall even below Standard liabilities. Accordingly, when rates increase, there is a higher probability that the Standard framework will dominate.171 Ishita Sen172 shows that “the regulatory framework governing insurers in Europe (Solvency II) has important deviations from market values. Moreover, there are differences in risk sensitivities 169

Koijen, R. S. J. and M. Yogo, 2017, The Fragility of Market Risk Insurance, Princeton University Working Paper. 170 Ishita Sen, Regulatory Limits to Risk Management, March 3, 2019 e at: https://ssrn.com/ abstract¼3345880 P 5. 171 Hoffmann, P., S. Langfield, F. Pierobon, and G. Vuillemey, 2017, Who Bears Interest Rate Risk, European Central Bank Working Paper. 172 Ishita Sen, Regulatory Limits to Risk Management, March 3, 2019 https://ssrn.com/ abstract¼3345880 p37.

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and how hedges are treated in model-based versus standardized frameworks within Basel III, which could affect the sensitivity of capital to market movements and may affect the hedging incentives of banks.” It is worth noting that the risk management distortions owing to the insensitivity of the regulatory framework arise for the reason that hedge derivatives are markedto-market and so, hedging denotes a higher volatility of regulatory capital than not hedging, as gains or losses from derivatives do not offset losses or gains in regulatory liabilities by reason of their insensitivity generating an enticement to underhedge true risk exposures, if insurers target the volatility of regulatory capital rather than the market value of capital. Thus, insurers care about the volatility of regulatory capital as regulators pay close attention to insurers’ available capital relative to required capital, also known as the risk-based capital ratio (RBC). Furthermore, RBC is an imperative factor of an insurance company’s credit rating affecting the future demand for insurance policies.173 It has to be taken into account that raising capital is costly and so, insurers can adjust capital continuously to manage the volatility of regulatory capital. Nonetheless, raising capital is costly and that capital market frictions affect the asset allocation and product market decisions of insurers. Moreover, it has to be taken into consideration that volatility forecasting is central for portfolio management, risk management, and pricing of financial derivatives. Specifically, the volatility of a financial asset is a main input to the optimal portfolio choice problem. Moreover, volatility forecasting is a mandatory risk management exercise for many financial institutions and banks around the globe and so, volatility is the most important input variable in the valuation of derivative securities. To that extent, to price an option, one needs to identify the future volatility of the underlying asset till the option maturity. Hence, in portfolio management and risk management, the volatility must be forecasted over horizons ranging from 1 day to 1 month. Besides, in the valuation of derivative securities, the volatility must be forecasted over much longer horizons. In line, on the CBOE, one can trade short-term options with a maximum of 12 months to maturity and long-term options (LEAPS) that have expiration dates up to 39 months into the future. Moreover, FVA contracts are traded in over-the-counter markets and have maturities ranging from 1 to 24 months,174 which means that the effective pricing of an option necessitates precise forecasting of volatility over a comparatively long-term period starting now and so, the effective exploitation of an

173

Koijen, R. S. J. and M. Yogo, 2015, The Cost of Financial Frictions for Life Insurers, American Economic Review 105 (1), 445–475. Koijen, R. S. J. and M. Yogo, 2015, Risks of Life Insurers: Recent Trends and Transmission Mechanisms, The Economics, Regulation, and Systemic Risk of Insurance Markets, Oxford University Press, chapter 4. Koijen, R. S. J. and M. Yogo, 2016, Shadow Insurance, Econometrica 84 (3), 1265–1287. 174 Corte, P. D., Kozhan, R., and Neuberger, A. (2017). “The Cross-Section of Currency Volatility Premia”, Working paper, Imperial College Business School, Warwick Business School, and Cass Business School.

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FVA contract compels accurate forecasting of volatility over a period starting at some distant point in the future.175 Currently, there is a trade in derivatives that are written on volatility itself such as forward volatility agreements (FVA) being a forward contract on the future spot realized or implied volatility of a financial asset such as individual stock, stock market index, commodity, and foreign currency. Above all, the FVA specifies the realized or implied volatility for an interval starting at a future date and so, the worth of the FVA at maturity is the difference between the contractual volatility level, which is settled at the contract inception date, and the volatility level examined at the settlement date. To that extent, the strategic rationale to trade FVAs is that they permit investors to hedge volatility risk and to speculate on volatility levels. In line, Xingyi Li and Valeriy Zakamulin176 argue that “First, our results significantly extend the horizon of volatility predictability reported in the earlier studies. Second, the horizon of volatility predictability is much shorter than the longest maturity of traded LEAPS (39 months) and FVA (24 months) contracts.” Nonetheless, it seems that the horizon of volatility predictability is shorter than the longest maturity of traded derivative contracts. An ICO is a new method to raise funds through the offer and sale by a group of developers or a company to a crowd of ad hoc crypto-assets specifically generated and issued on a distributed ledger, sometimes preceded by an early sale of the cryptoassets called “pre-sale,” intending to launch a business or of developing ad hoc governance of projects based on the distributed ledger technology, classically in exchange for pre-existing “mainstream” crypto assets, such as Bitcoin and Ether among others, or even fiat currencies.177

5.13

Corporate Governance and Finance Tools

As discussed, crypto-assets are intangible, digital, and cryptographically secured assets, issued, registered, retained or transferred through cryptography and DLT, representing a crypto-asset holder’s rights to receive a benefit or perform specified functions. Moreover, corporate governance is the mechanisms which have an impact inside a company/firm on the association between the company’s management, its board, its shareholders, and other stakeholders, and whose objective is to offer an effective structure to control and supervise effectively the company’s management, objectives, and performance. In accordance with the principles defined by the G20/OECD,

Corte, P. D., Sarno, L., and Tsiakas, I. (2011). “Spot and Forward Volatility in Foreign Exchange”, Journal of Financial Economics, 100(3), 496–513. 176 Xingyi Li and Valeriy Zakamulin, The Term Structure of Volatility Predictability https://ssrn.com/abstract¼3350362 P33. 177 Coinschedule.com. 175

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the central objective of corporate governance is “to support economic efficiency, sustainable growth and financial stability.”178 Which will be the various outcomes of ICOs, of tokenization, and of distributed ledger technology on the governance of corporations? It could be said that ICOs, crypto-assets, and tokenization, along with more broadly the use of distributed ledger technology and of smart contracts, influence the way corporates are governed in several ways. Thus, new technologies, and blockchain and crypto-assets specifically, have the prospective to transform fundamental concepts vital to corporate governance, such as trust, intermediation, accountability, responsibility, and transparency.179 Undeniably, distributed ledger technology diminishes the cost of accessing information for minority shareholders/stakeholders and augment transparency in the governance of corporations and so, this new technology changes risk management, compensation governance, accountability to shareholders, and redefines the present swing between stakeholders and shareholders. Hence, the positive results of the distributed ledger technology are significant, and so, are the numerous new legal and economic encounters it represents for corporations such as the crypto-asset holders being a new kind of corporate stakeholders.180 The following are the questions that have to be answered due to the new technologies: Could they be considered as shareholders? How could they contribute in the governance of the corporation? Are smart contracts new tools for corporate governance? How to solve free-rider problems in the process of ICOs? It is worth noting that due to the fact that computer code will gradually be utilized in conjunction with written legal codification, the strategic matter is to analyze if it would be achievable to govern an organization in a decentralized and distributed way. While the ICO of the “The DAO” project partially failed in 2016 in a dramatic way, there is a need for picturing new kinds of corporations and institutions, such as distributed autonomous organizations managed at least moderately through autonomous codes offering a more horizontal, distributed, and/or algorithmic governance founded on the use of self-executing smart contracts. Crypto-assets issued during an ICO are initially transferred to investors through smart contracts’ computer code, in exchange of a pre-existing cryptocurrency or against a fiat currency such as US dollars and euros, at a price set by the token issuer to finance a scheme, then possibly tradable on a secondary market being platforms

OECD, “G20/OECD Principles of Corporate Governance”, OECD Publishing, 2015, page 9. M. Fenwick and E. Vermeulen, “Technology and Corporate Governance: Blockchain, Crypto and Artificial Intelligence”, European Corporate Governance Institute, ECGI Working Paper No. 424/2018, November 2018. 180 V. Akgiray, “Blockchain Technology and Corporate Governance”, Report for the OECD Corporate Governance Committee’s roundtable discussion on blockchain technologies and possible implications for effective use and implementation of the G20/OECD Principles of Corporate Governance, 6 June 2018. 178 179

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such as Kraken and Poloniex.181 Moreover, crypto-assets are issued without an ICO by bringing them through other kinds of rewards, and not by the issuance by a single organization, such as for Bitcoin.182 Token issuers can be either private or public entities.183 It has to be considered that the appearance of ICOs empowers industrialists to respond to two central needs of the DLT ecosystem: (1) the creation of incentive mechanisms to join into this ecosystem and/or to innovate and (2) the financial capability to fund projects associated with the new innovative distributed ledger technology and so, the ICO developers raise capital to fund their digital platform, software, or other projects at an early stage of their development. In comparison to financial securities, crypto-assets have a plurality of functions. Moreover, each type of crypto-asset issued during an ICO acquires its own features, granting rights different from the other crypto-assets such as voting rights, share of capital, or any particular advantage. Thus, a token can be handled with the qualities firstly of an equity instrument by conferring immediate or future ownership or equity interest in the legal entity, voting rights and a capacity to share in future profits and losses, secondly of a debt instrument by granting the right to hold the status of a creditor, or can be created as a utility services asset providing the right to access or license a service/product or to utilize, sell or consume the item purchased. In other words, once they are issued, the crypto-assets are resold in a secondary market, through brokers, exchange platforms or over-the-counter transactions.184 It has to be considered that whether it is a utility token, a security token or a payment token, a token has an effect on the ecosystem of an ICO project, via its utility within the internal ecosystem of the issuance project along with through its influence on its organization, for example, the payment of salaries, goods, and services useful for the project development. It has to be taken into account that there is the prospective digitalization of all kinds of existing “financial or tangible” assets generating new kinds of rights which

181 J. Barrdear and M. Kumhof, “The macroeconomics of central bank issued digital currencies”, Bank of England, Staff Working Paper No. 605, July 2016; M. Bech and R. Garratt, “Central bank cryptocurrencies”, BIS Quarterly Review, 17 September 2017. 182 D. Guégan and C. Hénot, “A Probative Value for Authentication Use Case Blockchain”, Documents de travail du Centre d’Economie de la Sorbonne, 2018; D. Guégan and A. Sotiropoulou, “Bitcoin and the challenges for financial regulation”, Capital Markets Law Journal, Volume 12, Issue 4, October 2017, pp. 466–479. 183 Financial Conduct Authority, English HM Treasury and Bank of England, “Cryptoassets Taskforce: final report”, October 2018, pp. 11–14; K. Bheemaiah and A. Collomb, “Cryptoasset valuation: Identifying the variables of analysis”, Louis Bachelier Institute, Working Report v1.0, 19 October 2018; G.J. Nowak and J.C. Guagliardo, Pepper Hamilton LLP, “Blockchain and initial coin offerings: SEC provides first US securities law guidance”, Harvard Law School Forum on Corporate Governance and Financial Regulation, 9 August 2017. 184 C. Clack, V. Bakshi and L. Braine, “Smart Contract Templates: foundations, design landscape and research directions”, Cornell University Library, 2016 and revised in March 2017. A. Delivorias, “Distributed ledger technology and financial markets”, European Parliamentary Research Service, Briefing, November 2016.

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produce considerable governance issues.185 Moreover, security tokenization embraces alteration in the manner in which regulation applies, “fractionalization of larger assets, increased liquidity, lower issuance fees, and greater market efficiency,”186 on top of offering to issuers an access to global capital with lower fees, more market publicity as deals are public and so, visible to everyone with cyberspace connection. It could be said that the role of corporations in society advances to roles close to the ones of states and public institutions and so, the introduction of crypto-assets, and even more of crypto-currencies, is just the next step toward this evolution which means that since firms have the capacity, and the right, to generate their own currency, the spreading out of their obligations on an international regulatory level appears as a need.187 On the other hand, the generation of new currency by the firms will cause problems concerning the quantity of money circulating in the market which means problems of stability of price or a new understanding of the role of money in the digital economy regarding the cost and price of goods and services. Will any firm decide the price regardless of the global market? Will the value of the money be equal to the values of the goods and services in the market or there will be no reference to them?

5.14

Enterprise Risk Management

Risk management has developed from a restricted, insurance-based view to a holistic; all risk encompassing view, universally termed Enterprise Risk Management. The central idea behind “enterprise risk management” (ERM) is to smooth earnings volatility by applying a thorough and coordinated methodology to review and reply to all risks that influence the accomplishment of a business entity’s strategic and financial objectives. ERM is different from conventional risk management by distinguishing that risk has two sides: an upside potential (profit openings) and a downside potential (the risk of losses). Hence, ERM concentrates on the advancement and implementation of sophisticated information systems and response

P.J. Ennis, J. Waugh and W. Weaver, “Three Definitions of Tokenomics”, Coindesk, 17 March 2018 (https://www.coindesk.com/three-definitions-tokenomics). Financial Conduct Authority, English HM Treasury and Bank of England, “Cryptoassets Taskforce: final report”, October 2018, p. 13. 186 T. Koffman, “Your official guide to the security token ecosystem”, Medium, 13 April 2018. H. Marks, “The future of US securities will be tokenized”, Medium, 22 May 2018. 187 U. Chohan, “The Decentralized Autonomous Organization and Governance Issues”, SSRN, Discussion Paper, December 2017; D. Yermack, “Corporate Governance and Blockchains”, Oxford Review of Finance, Volume 21, Issue 1, March 2017, pp. 7–31; P. Paech, “The Governance of Blockchain Financial Networks”, LSE Legal Studies Working Paper No. 16/2017, 16 December 2016; M. Raskin, “The Law and Legality of Smart Contracts”, Georgetown Law Technology Review, Volume 1, 25 September 2016, p. 336. 185

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mechanisms that permit management to profit with environmental opportunities and lessen losses from adverse events. Corporations achieve a competitive advantage by identifying those risks they manage better than their competitors. ERM looks at the organization as subject to the influence of a number of formerly identified external risk driving variables, constantly monitors their estimated prospective influence on the company’s value, and sets up a set of guidelines to act in response so as to diminish losses and maximize profit openings. Martínez-González and SantillánSalgado188 argue that “ERM Model, when real world conditions are given full account, theory predicts risk management could increase value if: (a) it reduces tax liabilities; (b) it reduces potential financial distress costs; (c) it optimizes the firm’s investment decisions. A non-tested hypothesis (the post-model period is still short) would be that after risk is managed in a disciplined way, the difference in actual free cash flow and analyst’s expectations of it, would diminish significantly.” It has to be taken into consideration that ERM is more and more popular as a management practice, influencing decision-making in corporations due to the fact that companies face greater risks nowadays as a result of markets being connected globally resulting in a need for sound and overarching risk management across the whole firm.189 N. Sekerci and D. Pagach190 argue that “ERM best practices are governance tools used to monitor managerial discretion in risk management, ultimately reducing the agency cost of traditional risk management. We find that ERM is favored less in firms where there is already a high level of monitoring of management due to the existence of multiple blockholders disciplining the dominant owner. In addition, we find that firms with dual-class shares are less likely to implement ERM.” Hence, the requirement for ERM’s monitoring role rests on the ownership setting of the company such as a company with multiple blockholders and a corporation that has been listed on exchanges with dual-class shares.191 ERM is the specialty, by which a company in any field measures, controls, utilizes finances, and checks risks from all sources for the reason of escalating a company’s short- and long-term worth to stakeholders. Moreover, ERM has developed into a decisive element of contemporary corporate governance transformations, with plenty of principles, rules, and standards.192 Competent risk management

188 Jorge Arturo Martínez-González, CFA, Roberto Joaquín Santillán-Salgado Measuring Business Risk through Cash Flow at Risk: Modeling and Hedging Choices in a Multinational Company based in an Emerging Country, at: http://ssrn.com/abstract¼2366111 P 17. 189 Meidell, A., and Kaarbøe, K. (2017), “How the Enterprise Risk Management Function Influences Decision-making in the Organization–A Field Study of a Large, Global Oil and Gas Company”, The British Accounting Review, 49(1), 39–55. 190 Naciye Sekerci and Don Pagach, Enterprise Risk Management and Firm Ownership: Evidence from Continental Europe July 18, 2019 https://ssrn.com/abstract¼3366489. 191 Aguilera, R. V., Marano, V., and Haxhi, I. (2019), “International Corporate Governance: A Review and Opportunities for Future Research”, Journal of International Business Studies, 1–42. 192 Srivastav, S (2013). “A study of Enterprise risk management in banks.” Accman journal of management. Vol. 5, issue 1.

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practices are the answer to the problem of how to circumvent corporate disasters and failures.193 It is argued that ERM is part of the problem itself.194 It could be argued that an inefficient ERM is part of the problem itself for the company value.195 It is worth mentioning that risk management approaches are principally unconfirmed, still emerging, and continuously changing due to alternations caused by changes in the global economy. Stulz196 says that risk management enhances value when it assists in eradicating expensive lower tail earning outcomes. In other words, dropping the possibility of operation shocks or the value damaged during financial distress rationalizes ERM programs. Risk management augments value when it facilitates states of the globe in which a company has inadequate internal funds to invest in positive-net-present-value chances.197 Consequently, ERM has turned into a central module of contemporary corporate governance modifications, with a large quantity of principles, guidelines, and standards. Competent risk management practices are the answer to the problem of how to evade corporate disasters and failures.198 In recent times, the US Securities and Exchange Commission (SEC) has authorized that a publicly traded company’s annual proxy statements embrace a description of the board’s role in risk oversight. Moreover, the Toronto Stock Exchange necessitates the establishment and revelation of a company’s risk management function, and the Dodd–Frank Wall Street Reform and Consumer Protection Act compels large publicly traded financial companies to have a separate board risk committee made up of independent directors. Creditrating agencies assess how companies administer risks, with Moody’s and Standard & Poor’s (S&P) having a specific center of attention on ERM in the energy, financial services, and insurance industries.199 It has to be taken into account that companies carrying higher risk of financial difficulty measured by leverage or volatility of operating cash flows are more

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National Commission on the BP Deepwater Horizon Oil Spill and Offshore Drilling (National Commission). 2011. Deep Water: The Gulf Oil Disaster and the Future of Offshore Drilling. Report to the President. Available at: http://www.oilspillcommission.gov/final-report. 194 Power, M. 2009. The risk management of nothing. Accounting, Organizations and Society 34 (6, 7): 849–855. 195 Power, M. 2009. The risk management of nothing. Accounting, Organizations and Society 34 (6, 7): 849–855. 196 Stulz, R. 1996. Rethinking risk management. Journal of Applied Corporate Finance 9 (3): 8–24. 197 Froot, K. A., D.S. Scharfstein, and J. Stein. 1993. Risk management: Coordinating corporate investment and financing policies. Journal of Finance 48 (5): 1629–1658. 198 National Commission on the BP Deepwater Horizon Oil Spill and Offshore Drilling (National Commission). 2011. Deep Water: The Gulf Oil Disaster and the Future of Offshore Drilling. Report to the President. Available at: http://www.oilspillcommission.gov/final-report. 199 Moody’s Analytics, Inc. 2010. Enterprise Risk Management. Standard & Poor’s Financial Services LLC. 2013. Ratings Direct: Criteria, insurance, general: Enterprise risk management. New York, NY: McGraw-Hill.

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expected than less risky ones200 to take on ERM. To that extent, Paape and Speklé say that stock exchange listing is linked with ERM functioning in Europe but discovered no connection with the being of governance codes or risk management frameworks.201 Anil Nair et al.202 argue that “superior ERM capability was associated with lower decline in stock price during the downturn and superior profitability during the upturn. The results suggest that firms may need different types of dynamic capabilities to react and respond to different dimensions of environment and type of change.” The routine of risk management has turned out to be more and more advanced as companies have established complex systems, departments, procedures, and cultures to administer risks. It has to be taken into account that strategic approach to risk management is known as Enterprise Risk Management. Thus, ERM is a novel risk management concept being extensively embraced by companies in reaction to enlarged uncertainty and rapidly shifting surroundings.203 It could be argued that ERM risk is the upshot of uncertainty on objectives, in contradiction to customary risk management identifying risk as the upshot of uncertainty on failure.204 Moreover, ERM has acquired amplified footing because company surroundings are developed into more vibrant and hypercompetitive.205 Likewise, ERM represents a forceful capacity permitting companies to act in response successfully to uncertainties in their setting and these forceful aptitudes are “higher-level” potentials that function to alter ordinary or substantive capacities.206 It is worth mentioning that forceful aptitudes are particular and identifiable practices.207 The disparity between operational and forceful aptitudes can be blurred in certain conditions. Helfat et al.208 argue that forceful aptitudes (dynamic capabilities) entail “the capacity of an organization to purposefully create, extend, or modify its resource base.” Forceful competences (dynamic capabilities) are mainly significant for companies in fast altering settings. While operational aptitudes/competencies (capabilities) permit

Pagach, D., and R. Warr. 2011. The Characteristics of Firms that Hire Chief Risk Officers. The Journal of Risk and Insurance 78(1): 185–211. 201 Paape, L., and R.F. Speklé. 2012. The adoption and design of enterprise risk management practices: An empirical study. European Accounting Review 21 (3): 533–564. 202 Anil Nair, Elzotbek Rustambekov, Michael McShane and Stav Fainshmidt, Enterprise Risk Management as a Dynamic Capability: A test of its effectiveness during a crisis www.ssrn.com. 203 Pagach, D., & Warr, R. (2010). The effects of enterprise risk management on firm performance. www.ssrn.com SSRN 1155218. 204 Rejda, G. E., McNamara, M. J., 2011, Principles of Risk Management and Insurance, 12th edition, Pearson Education, Upper Saddle River, New Jersey. 205 McGrath, R. G. (2013). Transient Advantage. Harvard Business Review, 91(6), 62. 206 Zahra, S. A., Sapienza, H. J., & Davidsson, P. (2006). Entrepreneurship and Dynamic Capabilities: A Review, Model and Research Agenda*. Journal of Management Studies, 43(4), 917–955. 207 Eisenhardt, K., & Martin, J. (2000). Dynamic Capability: What are they? Strategic Management Journal, 21(1), 1105–1121. 208 Helfat C., Finkelstein S., Mitchell W., Peteraf M., Singh H., Teece D., & Winter S. (2007). Dynamic capabilities–understanding strategic change in organizations: Malden, USA: Blackwell. 4. 200

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companies to attain competitive advantage in comparatively secure settings. Dynamic capabilities compose courses and customs tolerating companies to adjust to swiftly varying settings. Forceful competences are patterned behaviors enlightening company-level triumph, survival, competitive advantage, and wealth making.209 The concept of ERM purports the incorporated management of hazard, financial, operational, and strategic risks plus the association of risk management with the whole corporate strategy of a company. To that extent, the ERM practice commences by defining managerial objectives, its stakeholders, and the objectives of the stakeholders trying to recognize the internal and external variables that influence the accomplishment of objectives. ERM administers risks as a portfolio that supports a company’s strategy. Under ERM, the company searches for profit chances in risks it runs better than other companies. Moreover, companies implementing an ERM scheme not only estimate the possibility and extent of risks but also assess other features of risks such as the relationship between risks and the pace at which risks occur. A company has to handle the risk of the portfolio of resource configurations rather than every risk separately. It has to be taken into consideration that a forceful aptitude engages perceiving chances and threats in the surroundings. Similarly, ERM engrosses steady inspection of the perspective for up-and-coming risks. Therefore, ERM compels companies to contemplate both upside and downside risk, which means that inspection tolerates companies to perceive chances and threats. Furthermore, a forceful aptitude means putting together, fostering, and reconfiguring internal advantages and improved capability to modify the resource base. Correspondingly, ERM requires reorganization and reconfiguration of means in order to adjust to a shifting setting. It could be argued that companies holding higher ERM capacities are better placed to circumvent and answer to dynamics in their setting, embracing crises which mean that companies with superior ERM administer their risks more successfully diminishing the effect of a crisis on a company’s functioning. Pagach, D, & Warr, R210 indicated that “simply installing ERM systems do not inoculate firms from crisis. While in the past studies have used crisis as a single point, this study was the first to unpack it and view it as a combination of downturn and upturn. . .elements of ERM required to manage downturns may be different from those needed to manage upturns. Moreover, executives need to be aware that ERM capabilities may have varying impact on different firm outcomes such as stock prices and profitability.” ERM represents a forceful aptitude offering companies an advantage during a crisis. Moreover, ERM was connected with effectiveness as early as 2009 permitting companies to swiftly reply to the crisis and come back to profitability. Companies’ ERM evaluation not only gains control its risk management capacity, but also

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Teece, D. J. (2007). Explicating dynamic capabilities: the nature and microfoundations of (sustainable) enterprise performance. Strategic management journal, 28(13), 1319–1350. 210 Pagach, D., & Warr, R. (2010). The effects of enterprise risk management on firm performance. SSRN 1155218 p. 19.

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transmits a signal to the market ERM potential in diminishing the adverse effect of the crisis on company stock price. Furthermore, ERM means to put together or summative all kind of risks, by means of integrated tools and modus operandi to alleviate the risks and to correspond across business lines or levels. Integrating refers to the amalgamation of adjusting the company’s function, modifying its capital makeup, and making use of targeted financial instruments.211 ERM program should boost shareholder wealth and in general profit maximizing. Risk management should not manage each risk class in individual way because inefficiencies are produced as a result of lack of synchronization between the different risk management departments. It could be argued that with ERM integrating decision-making across all risk classes, firms are able to circumvent duplication of risk management spending by making use of natural hedges. Moreover, ERM permits corporations to better value the aggregate risk, accedes to different business activities, consequently providing them with a more objective foundation for resource allocation which entails enhanced capital effectiveness and return on equity. Furthermore, ERM presents a formation that merges all risk management actions into one integrated agenda that makes possible the discovery of impending interdependencies between risks across activities. Hoyt and Liebenberg212 argue that size, institutional ownership, and international diversification are important in determining the ERM taking up among US insurance companies, extending their 2006 study to discover that larger companies are more expected to take on ERM than smaller companies. It has to be taken into account that demands from institutional owners, leverage, and reinsurance are negatively and drastically correlated to ERM. Bertinetti et al.213 “find a positive statistically significant relation between the ERM adoption and firm value. As for the probability that a firm engages in an ERM protocol, we find that size, the company beta and profitability (ROA) are the statistically significant determinants.” It could be said that customary practices of risk management pay too little attention to uncertainty related to stakeholder interactions, and the uncertainties that characterize the strategic crossing point between construction assignments and client organizations.214 Nevertheless, as a generic process, Strategic choice lacks

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Meulbroek, L. K. (2002). Integrated Risk Management for the Firm: A Senior Manager’s Guide. Retrieved 2008, from Harvard Business School: www.hbs.edu/research/facpubs/workingpapers/ papers2/0102/02-046.pdf. 212 Hoyt, R.E., Liebenberg, A. P. (2006). The Value of Enterprise Risk Management: Evidence from the U.S. Insurance Industry. http://www.aria.org/meetings/2006papers/Hoyt_Liebenberg_ERM_ 070606.pdf; Hoyt, R. E., Liebenberg, A. P. (2008). The Value of Enterprise Risk Management: Evidence from the U.S. Insurance Industry. http://www.risknet.de; Hoyt, R.E., Liebenberg, A.P., 2010, The Value of Enterprise Risk Management, Journal of Risk and Insurance, 78, 4, 795–822. 213 Giorgio Stefano Bertinetti, Elisa Cavezzali and Gloria Gardenal The effect of the enterprise risk management implementation on the firm value of European companies Working Paper n. 10/ 2013 August 2013 the Department of Management at Università Ca’ Foscari Venezia. 214 Green SD. Towards an integrated script for risk and value management. Project management 2001;7(1):52–8.

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concentration on project management matters. Rather than enhancing the management of uncertainty in projects, there is a need to transform existing PRM processes into Project Uncertainty Management. PRM is restrictive for the reason that it fails to take into account the management of openings, in the sense of prospective welcome results on project performance. It has to be taken into account that in any given decision circumstances, both threats and openings are regularly implicated, and both should be handled. A concentration on one should never be permitted to eradicate concern for the other. In addition, openings and threats can sometimes be considered independently, but they are rarely unrelated. Corporate risk management is the favored solution to moderate the agency problem: while other potentials diminish some costs but at the same time generate supplementary costs, corporate risk management eradicates or lessens agency costs by stabilizing cash flows and for that reason keeping any value high enough to circumvent the asset substitution drawback. The aptitude of corporate risk management to stabilize cash flows makes it the favorite answer to the underinvestment problems because it makes sure that prospects on profit from the investments are met. Corporate risk management is useful to mollify the risk-preference problem by reducing the risk connected with profitable growth prospects, consequently making managers less prone to engage in non-value maximizing schemes, and by dropping the risk of managers’ human capital and for that reason slashing the risk bonus managers demand on their compensation. Also, corporate risk management proposes optimal hedge ratios for value-maximizing firms or utility-maximizing managers, but firms with comparable physiognomies follow different risk management policies. Companies’ hedging decisions are the outcome from constrained optimization formed in part by prior financing selections.215 Likewise, corporate risk management does not have consequences on the costs of bankruptcy, but it can have a noteworthy result on the lessening of the possibility of default by reducing the volatility of cash flows. Consequently, corporate risk management benefits more the companies with a superior rate of the financial distress costs. Finally, corporate risk management makes straight cash flows and investment expenditures. In actual fact, by reducing cash flow instability, it makes certain that the company has enough internal cash flows to finance planned profitable assignments without having to introduce expensive outside capital and companies keep surplus non-invested cash, which means that there is an increase of company worth by reducing the cost of capital used to discount the corporate cash flows. It is imperative to underline that actions correlated to the various objectives of corporate risk management do not work in the same direction, but trying to diminish the instability of some factors may have a contrary outcome on others. These consequences need to be taken into consideration when designing the company risk management strategy.

215 Ilona Babenko, Hendrik Bessembinder, Yuri Tserlukevich, Debt Financing and Risk Management, https://ssrn.com/abstract¼3675898.

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The aim of corporate risk management is to generate a testimonial agenda permitting firms to manage risk and uncertainty. Risks are present in all of corporations’ financial and economic actions. The risk detection, evaluation, and management procedure are elements of firms’ strategic development planned at the level of the board of directors. An integrated risk management method estimates, manages, and supervises all risks and their dependences to which a firm is exposed. It is worth noting that corporate governance guidelines put on risk management is related to a high level of risk management practices and so, rating agencies put pressure on both financial and non-financial companies to apply ERM by counting ERM as part of their rating assessments. Likewise, risk management may present a situation in which managers use risk management devices to promote managers’ own self-interest above shareholders by favoring a particular project that boosts the manager’s wealth at the expense of shareholders and so, this agency cost of risk management concerns any agency costs to shareholders resulting from the use of risk management devices to benefit managers’ own welfares. On the other hand, ERM specifies a foundation for dropping the agency cost of risk management through monitoring managerial actions which means that ERM best practices are considered as a governance instrument to monitor managerial discretion in risk management, eventually lessening the agency cost of conventional risk management. While monitoring of managerial actions is vital to corporate governance, it is also fundamental to enterprise risk management; there is a need for a better implementation in practice utilizing the new devices in hands of the controllers. COSO216 proposes a number of particular actions for augmenting monitoring by firstly applying a board-level risk committee that is responsible for the risk oversight of the firm, secondly demanding management to submit a formal risk management report to the board, thirdly entailing a certain member of management, such as a Chief Risk Officer to take responsibility for leading the risk management procedure reporting the activities directly to the board, and fourthly demanding a formal written statement of the firm’s risk choice given at the board. It could be said that ERM implementation is required less in companies where there is already a high level of monitoring of management. Moreover, owing to their large stake in the company, large controlling owners have reasons to monitor management closely needing ERM’s governance role less. On the other hand, they might also divert from their monitoring role by engaging in extracting private profits, such as lowering corporate risk and so, augmenting the need for ERM which denotes the significance of the rightful way of implementation of ERM.217

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Committee of Sponsoring Organizations of the Treadway Commission (COSO), (2017), Enterprise Risk Management – Integrated Framework Executive Summary. COSO ERM framework (2017). 217 Boubaker, S., Nguyen, P. and Rouatbi, W. (2016), “Multiple Large Shareholders and Corporate Risktaking: Evidence from French Family Firms”, European Financial Management, 22: 697–745. Hoyt, R. E. and Liebenberg, A. P. (2011), “The Value of Enterprise Risk Management”, Journal of Risk and Insurance, Vol. 78, No. 4, pp. 795–822.

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Nonetheless, in civil-law countries where ownership is concentrated, companies are not controlled by only one large owner, yet with multiple blockholders.218 Moreover, existence of multiple blockholders are linked with enhanced governance in general and multiple blockholders assist in disciplining the dominant shareholder who then focus more on their role of monitoring the manager rather than extracting private benefits which means that increased level of monitoring of the managerial actions consecutively decreases the requirement for the monitoring ERM offers. It has to be taken into account that the necessity for ERM as a monitoring device depends on companies’ ownership setting and so, ERM procedure and ERM report are required less in companies with multiple blockholders because multiple blockholders monitor the dominant shareholder, and the disciplined dominant shareholder then would less expected expropriate wealth from minority shareholders in general and predominantly in corporate risk taking. Besides, they concentrate on their role of monitoring the manager, indicating that they would demand ERM’s governance role less. Sekerci219 and Pagach suggest that “the need for ERM as a monitoring tool depends on the firms’ ownership setting. We find that ERMprocess and ERMreport are demanded less in firms with multiple blockholders. We further find that there is a negative relation between ERMphilosophy and the use of dualclass share structure.” ERM helps companies to recognize, assess, and manage risks at the enterprise level and so, through ERM managers, get a better understanding of company processes and so, estimating accruals. On the one hand, under traditional risk management techniques, managers focus only on controlling the downside risks within their department. On the other hand, ERM emphasizes understanding risks at the enterprise level which means that managers using ERM consider how risks in one part of the enterprise link to risks in another part of the enterprise investigated and how ERM improves the financial reporting process. Moreover, corporate governance stakeholders understand the role of ERM in aiding the development of accounting estimates.

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Operational Risk Management

Many firms consider operational risk management only as a regulatory liability and a cost feature. Up till now, experience illustrates that firms yield from operational risk management, provided that they conceive and exercise it as a management appliance 218 Huang, J., Su, C., Joseph, N. L., and Gilder, D. (2018), “Monitoring Mechanisms, Managerial Incentives, Investment Distortion Costs, and Derivatives Usage”, The British Accounting Review, 50(1), 93–141. 219 Sekerci, Naciye and Pagach, Donald P., Enterprise Risk Management and Firm Ownership: Evidence from Continental Europe SSRN: https://ssrn.com/abstract¼3366489 P18; Sekerci, N. (2015). Does Enterprise Risk Management Create Value for Firms? In The Routledge Companion to Strategic Risk Management (pp. 409–440). Routledge.

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making easier to accomplish corporation objectives, generating competitive advantages, and advancing business effectiveness. These firms have no problems obeying regulatory requirements. Nevertheless, in corporations seeking for the regulatory minimum having no awareness of how to apply operational risk for the advantage of their corporation, operational risk management is transformed into a costly paper employment. It has to be taken into account that only an actual integration of the risk and control system as ingredient of an entrepreneurial management system will play a role for the endurance and long-term triumph of a firm. Operational risk is the risk related to the functions of a company defined as risk of loss resulting from incompetent or failed internal course, people, and systems, or from external events. Operational risk embraces legal risk barring strategic and reputational risks, as the same are not quantifiable. Operational risk incorporates the risk of loss occurring from fraud, system failures, trading error, and many other internal governmental risks, as well as risk owing to external events such as fire and flood. Moreover, the losses as a result of operation risk can be direct as well as indirect. Direct loss represents the financial losses resulting directly from a happening or an event such as forgery and fraud. Indirect loss connotes the loss incurred by reason of the influence of an incident. The central theme of every risk management doings is the detection of prospective risks and an estimation of their virtual magnitude for a company. Operational risks are the grounds and driver of credit, market, and central business, or strategic risks, which indicate that operational risk events have a direct or indirect influence on the value/earnings of a corporation or the obtainable liquidity. On the one hand, a direct consequence of a burglary in a firm building could lead to losses of stolen computer equipment. On the other hand, indirect effects via market, credit, or central business risks are harsh and more than the direct impact if classified data were stored on the stolen computers that afterward get available on the cyberspace. Radical market or credit risk volatility triggers unforeseen operational risk events as a consequence of a failure of the standard procedures and so, risk management has to predict and solve or offer solutions in such situations. Regarding risk concept and categorization, the first imperative, structural factor in the operational risk management structure, is an obvious risk perception with preferably a company-wide categorization of risks. The objective of the risk management procedure is to maintain acknowledged risks in sequence with the risk policy and risk strategy endorsed by the Board of Directors and the executive panel. The risk and control utility makes certain that on hand controls are executed and endorsed risk-mitigating measures are employed as intended.220 Real risk management does not deal merely with numbers, but it is the art of employing numbers and quantitative means to administer risk. Risk is a vital, maybe the principal, factor of managing a financial corporation. Other than risk management is the way of managing people, procedures, and firms, as it is the science of

Brammertz, Willi (2009): Unified financial analysis, Wiley Finance. ORX Operational Risk Reporting Standards (2011), www.orx.org.

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measuring and quantifying risk. Measuring and reporting risk in a coherent mode all the way through a company offer considerable benefits. A risk manager appraising the whole risk of a company investigates unpredictability, value at risk (VaR), anticipated underperformance, or inferior semi-variance. Moreover, managing risk entails thinking about risk, and thinking about risk involves assuming and is contented with uncertainty and randomness. Randomness infuses global economy and global society. Knowledge and training do not coach parties to appreciate or to match with uncertainty. In order to identify risk, there is need to think about both the uncertainty of future results and the utility, or profiting of those outcomes. Volatility is one number that encapsulates the spread which is determined by taking the average of squared deviations and then taking the square root. Moreover, VaR is another number that sums up the spread. Risk management means managing risk, by making deliberate and strategic choices to control those risks that have to be controlled and so, utilizing those openings that should be exploited. Managing risk cannot be unconnected from managing profit. It is worth mentioning that modern portfolio theory indicates that investment choices are the outcome of trading off earnings for risk, and managing risk is merely an ingredient of managing income and earnings. Managing risk has to be a central competence for any financial company.221 Moreover, the capacity to efficiently administer risk is the distinct, most vital quality separating financial companies that are profitable and endure over the long run from companies that are not profitable. At profitable companies, managing risk has been and goes on to be the duty of line managers commencing from the board through the CEO and down to distinctive trading units or portfolio managers. Risk management is about managing people, procedures, data, and ventures. A significant factor of real risk management is not only the power but also the restraint of quantitative risk techniques. Quantitative techniques work best in the hands of those who are familiar with the techniques although who are also intensely conscious of the constraints and boundaries of what these techniques make available. An understanding of the limitations allows the user to depend on the techniques when suitable and the good sense to focus on somewhere else when required. Quantitative techniques work well when utilized appropriately, and the key is to recognize their limitations with the purpose of precluding their misuse.222 Greater risk management offered by stakeholder engagement is a more convincing motivation for investors to modify corporate constitutions by setting up “network governance.”223 Networks of various common interest stakeholder boards supply early access to intelligence on risks that management may have no

S. Bainbridge, Corporate Governance after the Financial Crisis, Oxford, p. 172–173 (Oxford University Press, 2012). 222 Coleman, Thomas S. 2012. Quantitative Risk Management. New York: John Wiley & Sons. 223 Turnbull, S. 2002. A new way to govern: Organizations and society after Enron. New Economics Foundation, London, http://ssrn.com/abstract_id¼319867. 221

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knowledge of and/or they do not want to convey to the directors for the reason that it might reflect unfavorably on them. Risk managers have become in desperate need of reliable methods for measuring and managing operational risks. The risk management industry has seen a vast surge in measuring and managing operational risks being a result of a combination of recent regulatory developments in corporate governance and capital adequacy, and a growing realization that an enterprise-wide view of risk management is just good business. The recent well-publicized corporate failures have shown that, more often than not, the culprit was an operational risk rather than market, credit, or insurance risks and so, corporate governance standards have been revised to hold directors responsible for managing all risks: market, credit, insurance, legal, technology, strategic, regulatory, etc. The Basel Committee operational risk strengthen banks’ risk data aggregation and risk reporting with a view to improving their risk management, decision-making processes, and resolvability.224 In fact, risk managers need reliable methods for measuring and managing operational risks and so, overcoming their beliefs that strong controls are needless for the reason that they have hired trusted employees who are expected to do their jobs correctly.

5.16

Financial Risk Management

Risk is recognized as financial risk or unpredicted financial loss. There is a need to quantify the probability or the occurrence and risk is measured on a scale, with certainty of occurrence at one end and certainty of non-occurrence at the other end. Risk illustrates the greatest incidents where the probability of occurrence or non-occurrence is equal. Risk is the prospective that both the anticipated and unanticipated events may have an undesirable influence on the bank’s capital or its profits.225 Credit risk is intrinsic to the business of lending funds to the ventures related directly to market risk variables. The purpose of credit risk management is to diminish the risk and amplify bank’s risk-adjusted rate of return by taking on and upholding credit exposure within the satisfactory boundary. Market risk comprises the risk of the level of volatility of market prices of bonds, securities, equities, merchandise, and foreign exchange rate, which will adjust daily profit and loss over time. Market risk consists of the risk of unpredicted alterations in prices or rates addressing the issues of bank’s capacity to meet its obligation as and when due, in other words, liquidity risk. Safety measures of the probable risks have to be taken by the company needing to scrutinize many views of the business and its risks together with the view that the managing of risk costs money. The quantity of cost on

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www.bis.org Progress in adopting the Principles for effective risk data aggregation and risk reporting April 2020. BCBS, Principles for effective risk data aggregation and risk reporting, January 2013, www.bis.org/publ/bcbs239.pdf. 225 Raghavan (2003). “Risk Management in Banks.” Pp. 841–851.

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managing risk is based on the form of the industry and the transaction. In addition, risk management is a central matter and far-reaching knowledge about what is required, and how we are going to get ahead of risks will be useful for the effective risk management plan. Financial risk management and alterations in company strategy are two ways in administering exposure to environmental uncertainties. Financial risk management practices diminish company exposure to specific risks without altering the company’s strategy. Strategic replies influence a company’s exposure across a series of environmental uncertainties. Risk management is not restricted to the evaluation of exposure to losses and the application of suitable financial risk management practices such as insurance and hedging instruments. Financial and strategic reactions are interconnected in such a way that decision-making in either area to the exclusion of the other would be suboptimal. Financial risk management and transformations in company strategy are two tactics in order to control display to environmental uncertainties. Financial risk management methods diminish corporate exposures to specific risks without altering a company’s strategy. Strategic answer is the main influence in a company’s exposure to thwart an extensive variety of environmental uncertainties. There is a need for strategic responses to uncertainties. To that extent, financial risk management involves main financial risk-reduction methods such as acquiring insurance and buying and selling financial instruments like forward contracts, futures contracts, swaps, and options. Financial hedging instruments are broadly used by companies to handle foreign exchange risk. Risk management226 is not central to the success of a hedge fund and regulatory restraints and conformity issues are matters of performance, which means that the whole point of a hedge fund is to evade these issues. There is little intellectual property engrossed in the hedge fund and as fiduciaries; institutions need to comprehend the investment procedure prior to committing to it. Risk management and risk transparency are crucial. It has to be taken into account that risk management produces value by decreasing variability of company value or cash flows. In spite of constant distress about the lack of transparency and prospective instabilities of hedge fund investment firms, the hedge fund industry expands at a rapid rate. Part of the variance between institutional investors and hedge fund managers is the diverse standpoints that these two groups have on the investment procedure. The typical manager’s perspective can be characterized by the following statements: firstly being the best judge of the suitable risk/reward trade-off of the portfolio having a broad discretion in making investment decisions, secondly trading strategies is proprietary. Interest rate risk is the prospective negative influence on the net interest income referring to the vulnerability of a company’s financial proviso to the advance in interest rates. Alterations in interest rate upset profits, value of assets, liability, off-balance sheet

Andrew W. Lo, “Risk Management for Hedge Funds: Introduction and Overview,” Financial Analysts Journal 57 (2001), 16–33.

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items, and cash flow. Unobservable imperfections and information asymmetry are variables in the risk management equation. Stulz227 argues that companies will manage risk to reduce cash flow volatility for the reason that it diminishes one of the costs interconnected to managerial discretion in the occurrence of information asymmetry about the managerial actions. Moreover, DeMarzo and Duffie prove that a risk management strategy is advantageous for shareholders confronted with information asymmetry about the dividend stream.228 Financial systems add to economic expansion by offering individuals with useful equipments for risk management, such as credit for productive investments, means for saving and insurance, and payment services. Simultaneously, when financial institutions fail to administer the risks they keep hold of, they generate ruthless financial crises with shocking social and economic outcome, particularly for the world’s most defenseless individuals. The different communities, and the private and public sectors take on measures in response to the crisis having long-term development repercussions. Financial crises deteriorate economic endeavor, diminishing consumption and investment demand, resulting in continual weakening of economic intensification, loss of jobs, cut down in wages and benefits, and higher unemployment or employment involving fewer hours and lower benefits. Comparative price change and currency depreciation aggravate effects, particularly where the public and private sectors maintain high levels of foreign currencydenominated debt. Financial crises are classically followed by diminished financial flows across states in the formula of foreign capital and remittances, erosion of savings, and condensed accessibility and/or higher cost of credit. Condensed financial flows influence states that depend on foreign capital to maintain credit and economic doings.229 Savings are eroded by low interest rates condensed by policy-makers to motivate demand and safeguard bank balance sheets, by diminishing asset prices, or by crisis response measures such as forcing transfer at critical rates. The notions of effective markets and diversification are the two pillars of modern finance theory. Market competence purely states that markets do not leave money on the table and information is incorporated in prices, so that one cannot make profits from it. If predictable returns look good for a given exposure, it is only for the reason that the exposure engrosses risks rewarded by the market. If shareholders want to endure these risks, they do not expect the company to do it for them. Shareholders can spread the risks of the company, apart from risks that are common to most companies, such as business cycle risks. Consequently, having the company expend real resources to diminish diversifiable risks should take place only if diversifiable Stulz, René, 1990, Managerial discretion and optimal financing policies, Journal of Financial Economics 26, 3–28. 228 DeMarzo, Peter, and Darrel Duffie, 1991, Corporate financial hedging with proprietary information, Journal of Economic Theory 53, 261–286. 229 Bordo, Michael D. and Christopher M. Meisner (2011). Do Financial Crises Always Rise Inequality? Some Evidence from History. Working paper Hoover Institution. September. Rutger’s University. 227

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risks entail real costs on the company. The company has no relative advantage in bearing these risks and it may have a proportional disadvantage not excluding that management may have information that the market does not have, which means that taking advantage of this information will profit shareholders. Leverage inflicts a real cost on a company when there are bad cash flows and so, through competent risk management, a company evades being in such a situation taking advantage of good investment openings.230 A company should manage risks so that the market value of its equity is adequate to make bankruptcy unlikely. It could be said that increases in equity capital are a direct substitute for risk management. Thus, through risk management, companies save equity capital achieving more leverage than otherwise. Equity is the current value of future cash flows to equity and so, one should be concerned about the factors that influence the current value of future cash flows. On the other hand, current practice of risk management231 is concerned about hedging transaction risk or the risk of transactions anticipated to take place in the short run. Risk management is linked to valuation. In the process of discovering the causes that influence the value of a company, one learns the features that are accountable for changes in the value of a company. In competent markets, companies do not make money by taking financial positions founded on information that is publicly available. Companies should evade financial positions leading them to be financially afflicted and powerless to execute their inclusive strategy. Nevertheless, companies gather information that is not publicly available allowing them a relative advantage in taking some kinds of risks over their shareholders. Tax rates differ depending on the taxable income which means that a company would like more income when its tax rate is low and less income when its tax rate is high. Since tax rates escalate with taxable income, a risk management program diminishing the risk of taxable income ends up lessening estimated taxes as well. While shareholders can diversify risks, stakeholders who have a large stake in the triumph of the company cannot classically do so. Extensive reliance has been placed on the internal risk assessment models of the wealthiest and most “sophisticated” global banks as defining the standards that all banks should abide by making certain financial reliability.232 As Kevin L. Young233 suggested that the work of banking regulators was conquered by the interests of the

230 Dolde, W., 1993, The trajectory of corporate financial risk management, Journal of Applied Corporate Finance 6, Fall, 33–41. 231 Froot, K., D.S. Scharfstein, and J.C. Stein, 1993, Risk management: Coordinating corporate investment and financing policies, Journal of Finance 48, 1629–1658. 232 Porter, T., 2010. Risk Models and Transnational Governance in the Global Financial Crisis: The Cases of Basel II and Credit Rating Agencies. In: E. Helleiner, S. Pagliari, and H. Zimmerman, eds., Global Finance in Crisis: The Politics of International Regulatory Change, London: Routledge, 56–73. 233 Young, K.L., 2012. Transnational Regulatory Capture? An Empirical Examination of the Transnational Lobbying of the Basel Committee on Banking Supervision, Review of International Political Economy, 19 (4), 663–688.

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global financial industry implementing its power through lobbying and forms of “cognitive capture.” There is evidence that there is progressing pressure between regulators and finance and the former are able to compel their own visions on the latter. Moreover, the public–private interface and interdependence are characteristics of contemporary global finance, even though its terms are challenged in some degree. The biggest interest of shareholders is the maximization of their claims, as measured by the stock price, which for bank management are, by their character, more risk averse for the reason that a bank manager’s human capital, reputational capital, private benefits of control, and financial capital are classically exceedingly undiversified. Consequently, bank failure could compel noteworthy costs on the bank’s management that would not be endured by its shareholders.234 Risk management is coupled with the utilization of market insurance to safeguard persons and firms from different losses related to disasters.235 Financial institutions established internal risk management schemes and capital calculation methods to safeguard themselves from unexpected risks and diminish regulatory capital. Simultaneously, governance of risk management developed into necessary, integrated risk management was initiated, and the chief risk manager (CRO) stance was formed. Risk management choices are now financial assessments that have to be estimated founded on their consequence on company or portfolio worth, rather than on how well they deal with particular risks. Furthermore, risk management is a key subject for companies in a global economy. Unnecessary risk-taking to enhance financial company stock prices played a key role in the financial and economic crisis emerging in 2007. Burner236 indicated that a decline in genuine risk-free rates of interest to historically low levels led to credit expansion in a vicious search for profit among investors. According to Lang and Jagtiani,237 one of the reasons of the financial crisis was that large financial companies were willing to take on a complex mortgage-related product when they had not created the capacity to evaluate the portfolio risk of these activities. Financial companies lacked effectual internal controls, precise and apt financial and risk reporting to the right management level, and a company-wide view of risk or a company-wide risk management program. There is a need to look at the linearity of the relationship between risks and likely returns in financial markets examining the relations between various stakeholders of the company, supposing that the portfolio of their contracts corresponds to the nexus of their risk sharing into the company. According to the linearity principle in the Rangarajan Sundaram and David Yermack, ‘Pay Me Later: Inside Debt and its Role in Managerial Compensation’ (2007) 62 Journal of Finance 1551. 235 Harrington, S., Niehaus, G.R., 2003. Risk Management and Insurance. Irwin/McGrawHill, USA. 236 Bruner, C. M. (2010). Corporate governance reform in a time of crisis. Journal of Corporate Law, 36(1). http://papers.ssrn.com/sol3/papers.cfm?abstract_id¼1617890. 237 Lang, W. W., & Jagtiani, J. A. (2010). The mortgage and financial crises: The role of credit risk management and corporate governance. Atlantic Economic Journal, 38(2), 295–316. 234

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CAPM, the usual return and the systematic risk of a portfolio must equal the weighted average figures of ordinary returns and risks of its composing assets.238 In such a framework, the chosen governance has to assign jointly flows and risks in order to split the contemporary value of revenues between the stakeholders. Governance negotiations based on short-term flows turn into outmoded very soon, needing unremitting time renegotiation for the reason that contracts will be deficient. Moreover, stakeholders will want advanced flows without having the chance to take higher values of their own position versus the company. In occurrence of constant unwarranted risk sharing, some stakeholders may decide to discard the nexus which is the company. It could be argued that the higher is number of stakeholders abandoning the company, the lower will be the long-term sustainability of the company. Bertinetti and Mantovani239 say that “GRP-emersion signals the opportunity to repackage the governance because of incompleteness of both markets and contracts. Being based on value allocation, the sources of Governance inefficiency may refers to different drivers: flows, risk, time-horizons, growth, along with the sharing agreements referring to them. Governance might be incomplete itself if such drivers are not well allocated into the nexus, i.e. contracts are unable to craft drivers according to stakeholder’s attitudes.” Stocks have been priced to produce returns far dissimilar from what the SharpeLintner capital asset pricing model (CAPM) would advocate has guided behavioral finance specialists to assault competent and rational markets by means of pragmatic discrepancies to maintain alternative behavioral justification of these so-called anomalies. A. Alankar, et al.240 prove that “investment managers may not eliminate the observed asset-pricing anomalies because they may contribute to their existence. We show that if managers face constraints such as a “tracking-error constraint,” coupled with the need to hold liquidity to meet redemptions or to actively-manage investments, they optimally hold higher-volatility securities in their portfolios. Investment constraints, such as tracking-error constraints, however, reduce the principal-agent problems inherent in delegated asset management and serve as effective risk-control tools.” A company preparing risk management map requires three vital steps which are identification of risk, assessing risk, and developing strategies to administer and diminish its influence on the procedure. In addition, company’s chart has to specify the strategy for dealing with risks precise to industry. If firm simplifies prospective risks, it coaches most appropriate management plan for that specific matter. The risk

238 Mantovani G. M., Daniotti E., Gurisatti P. (2013) In Search Of Corporate Risk Measures To Complete Financial Reporting. The Case Of The “Caldarerie”-Industry, In International Research Journal Of Applied Finance, vol. IV, pp. 458–489. 239 Giorgio Bertinetti, Guido Max Mantovani, Is There (A Methodology To Measure) A Corporate Governance Risk Premium Into The Corporate Cost Of Capital? http://ssrn.com/ abstract¼2372493 P23. 240 Ashwin Alankar, Peter Blaustein, Myron S. Scholes The Cost of Constraints: Risk Management, Agency Theory and Asset Prices, 2013 Research Paper No. 2135.

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management practice must be adjusted toward the prioritization of risks, stimulating those of furthermost relate to turn into the center of enhanced control.

5.17

Banks Risk Management

Risk management is a field at the center of every financial institution covering all the actions that influence its risk profile. Moreover, risk management is engaging identification, amount, monitoring, and controlling risks to make certain that the persons who take or manage risks plainly comprehend it. Hence, risk management allows that the bank’s risk exposure is within the customary restrictions and the anticipated payoffs counterbalance the risks taken, which means that satisfactory capital as a buffer is offered to cover risk. Therefore, accepting and managing risks are innate to the business of banking and banks’ role as financial intermediaries. Risk management does not mean merely diminishing risk; rather, the aim of risk management is to optimize risk–reward trade-off. Concerning board and bank formation, there is a need for a clearer separation of the management and control affairs with a two-tier board which means the establishment of a separate risk committee of the board or an independent chief risk officer (CRO) coping with the dilemma of multifaceted or obscure bank structure. Banking manages various and apparently opposing needs. Banks supply liquidity on demand to depositors through the checking account and lengthen credit as well as liquidity to their borrowers by means of lines of credit.241 Banks have been concerned with both solvency and liquidity holding capital as a safeguard against insolvency, and liquid assets such as cash and securities protecting against unanticipated withdrawals by depositors or withdrawing downs by borrowers.242 Nonfinancial companies supervise their risk exposures considerably, which in turn influences their investment choices, productivity, and worth. Allayannis and Weston243 scrutinize the use of foreign currency derivatives reporting that there is an affirmative relation between company value and the use of foreign currency derivatives and so, suggesting that hedging boosts company value. Minton and Schrand244 notice that cash flow volatility leads to internal cash flow underperformance, which in sequence lead to higher costs of capital and declined investments. Companies diminishing cash flow volatility invest more. Moreover,

241

Kashyap, A.K., Rajan, R., Stein, J.C., 2002. Banks as liquidity providers: An explanation for the coexistence of lending and deposit-taking. Journal of Finance 57 (1), 33–73. 242 Saidenberg, M.R., Strahan, P.E., 1999. Are banks important for financing large businesses? Current Issues in Economics and Finance 5 (12), 1–6. 243 Allayannis, G., Weston, J.P., 2001. The use of foreign currency derivatives and firm market value. Review of Financial Studies 14, 243–276. 244 Minton, B.A., Schrand, C., 1999. The impact of cash flow volatility on discretionary investment and the costs of debt and equity financing. Journal of Financial Economics 54, 423–460.

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according to Dahiya et al.,245 stock prices fall at the announcement of a loan sale of a company whose loans have been traded, and many of these companies consequently go bankrupt presenting further support for the view that banks hold private information about their borrowers that makes loan sales complex by reason of adversative selection. Cebenoyan and Strahan246 argue that “banks that rebalance their loan portfolio exposures by both buying and selling loans—that is, banks that use the loan sales market for risk management purposes rather than to alter their holdings of loans— hold less capital than other banks; they also make more risky loans (loans to businesses) as a percentage of total assets than other banks. Holding size, leverage and lending activities constant, banks active in the loan sales market have lower risk and higher profits than other banks. . . banks that improve their ability to manage credit risk may operate with greater leverage and may lend more of their assets to risky borrowers. Thus, the benefits of advances in risk management in banking may be greater credit availability, rather than reduced risk in the banking system.” Furthermore, V. Taia, et al.247 argue that “the board of directors, especially the auditing committee, plays an important role in monitoring firm’s hedging decisions of both whether to hedge and the magnitude of hedging in healthy and distressed firms. Further, the effectiveness of corporate governance from the board of directors and audit committee is larger in distressed firms than that of healthy firms. These results are robust to a subsample of derivative hedging firms, the consideration of endogeneity problem, alternative measure of corporate governance, and industrial difference.” The risk-shifting behavior is more unequivocal in small companies comparative to large companies in the decision of hedging or not, but less precise in small companies comparative to large companies in the pronouncement of extent of hedging. Board size and the number of autonomous directors have more momentous influence on the probability of hedging in small companies, in particular those in financial difficulty. It has to be taken into account that while board size, the number of auditing committee members, and the number of auditing committee meeting have more noteworthy influence on the degree of hedging in large troubled companies. Bank shareholders favor socially excessive risk-taking by taking actions that may either amplify or lessen the value of the bank’s assets but whose anticipated effect on the bank’s value is negative.248 Identifying the weak link between nonequity compensation and managerial performance, equity-based compensation is used in executive remuneration packages, characteristically in the form of stock options. The 245

Dahiya, S., Puri, M., Saunders, A., 2000. Bank borrowers and loan sales: New evidence on the uniqueness of bank loans. Working Paper, NYU. 246 A. Sinan Cebenoyan, Philip E. Strahan, Risk management, capital structure and lending at banks Journal of Banking & Finance 28 (2004) 19–43. 247 Vivian W. Taia, Yi-Hsun Lai, Tung-Hsiao Yang, Min-Teh Yu Corporate Hedging and Corporate Governance: The Role of the Board and the Audit Committee www.ssrn.com. 248 Lucian Bebchuk and Holger Spamann, ‘Regulating Bankers’ Pay’ (2010) 98 Georgetown Law Journal 247.

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stock price is an apparent quantity of performance used to reveal the efficiency of managerial decisions supporting the incentives of managers with shareholder interests. Managers are persuaded to engage in shareholder maximization for the reason that their compensation has a significant option component. Social welfare is best served by persuading corporate managers to engage in shareholder interests. Hansmann and Kraakman249 argue that, “there is no longer any serious competitor to the view that corporate law should principally strive to increase long-term shareholder value.” Bebchuk and Fried250 say that directors have been influenced by management enabling them to acquire “rents” – benefits greater than those available under true arm’s-length contracting. Richard M. Ridyard251 argues that “The financial crisis of 2007-09 was interpreted by many as evidence that the incentives of managers were not optimally aligned with the interests of shareholders. As a result, a plethora of proposals have been put forward seeking to increase shareholder engagement. However, this shareholder engagement strategy only makes sense if the risk appetite of bank shareholders is not socially excessive. . .My analysis indicates that recent corporate governance reforms that attempt to tighten the alignment of managerial and shareholder interests cannot be expected to address the problem I identify. To adequately understand what policies should be explored, we must first recognize that excessive risk-taking is also partly a product of the conventional model of governance. I therefore propose a modification to that model: a regime of double bank shareholder liability that is triggered by bank failure. I discuss how this has the potential to reduce bank shareholders’ risk appetite, and, make less likely, excessive risk-taking. Welfare improvement occurs because of heightened risk awareness and enhanced risk-taking controls, decreasing the likelihood of failure. I introduce the term “the bank shareholder-orientated model” of governance to characterise this modified approach.” It is worth noting that using artificial intelligence in making managerial decisions has been increasing in many business areas, expressly in financial ones. On the one hand, presently, using AI as an assistant consultant does not come across any special problems from law, since the final decision is made by a human being. On the other hand, in the future, the auxiliary role of AI in managing a firm will be transformed into a leading one of AI director (robo-director) via AAI systems. Hence, the robodirector will work around the clock by handling instantly any information available and so, performing its functions without payment like a present software program. The causation behind managerial risk-taking enticements was the bank management’s power which has not been aligned with the interests of bank shareholders.

Henry Hansmann and Reinier Kraakman, ‘The End of History for Corporate Law’ (2001) 89 Georgetown Law Journal 439, 439. 250 Lucian Bebchuk and Jesse Fried, Pay Without Performance: The Unfulfilled Promise of Executive Compensation, (Harvard University Press, 2004). See also, Lucian Bebchuk and Yaniv Grinstein, ‘The Growth of Executive Pay’ (2005) 21 Oxford Review of Economic Policy 282. 251 Richard M. Ridyard, Corporate Governance And Double Liability: Toward A Bank ShareholderOrientated Model 2013 www.ssrn.com. 249

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Bertinetti and Mantovani252 argue that “All stakeholders must achieve their own satisfaction through bargaining contracts that must be sustainable, i.e. keep the firm and its stakeholders-network alive in the long term. Governance is intended as the mechanism that gives solution to the above puzzle. When market and contracts are complete, optimal solution can be easily found out. But when incompleteness emerges, governance can be misallocating the firm performance between the stakeholders. In fact, in incomplete contests, the stakeholders will negotiate the visibleonly arguments of contracts, and bind this way even the invisible ones, i.e. those impacting anyway on their ex-post performance. This being the case, a Governance Risk Premium (GRP) emerges in the medium-long run, thus incentivizing governance repackages. Such a GRP depends both on the actual grade of market completeness and the one of contracts as per risk allocation is done through time.” For stakeholders, a firm has a corporate accountability concerning its obligation to preserve the interests of its stakeholders, and this embraces protecting, safeguarding, and appreciating the interests of all of its stakeholders, with a spectacle to making certain the long-term sustainability of the firm. In the present environment, firms are now under augmented burden to make certain that they are taking suitable actions to effectively defend the interests of their numerous stakeholders. The stakeholders have an economic motivation to soldier on with contracts as long as they can profit from the transactions carried on through the company. When the enticements fade away, the contract is discarded and so, it could be said that the means ruling the nexus are true ingredients of the corporate governance. Such mechanisms distribute value between the stakeholders of the company and have a say to keep alive the economic convenience to maintain the contracts. Moreover, the potential to assign value means the capacity to unravel the trade-off between shortand long-term running, while satisfying the hope of stakeholders to keep alive the nexus such as company sustainability. According to Bertinetti and Mantovani,253 “different governance solutions in incomplete markets may inflate the corporate cost of capital by specific risk premiums. The existence of a corporate governance risk premium can even produce as misallocation of wealth between the firm’s stakeholders, by the absorption of excessive amounts of the produced corporate wealth to a specific part only of the process contributors. The missing value along with the misleading allocation of wealth could incentivize a governance repackage. In fact, the impossibility to determine the sources of Governance misallocation prevents to modify the underlying agency agreements, thus keeping incomplete the Governance mechanisms. A governance risk premium (GRP, hereafter) emerges in order to protect the stakeholders from unfair value allocations. Accordingly, our research question for this paper is the following: is there a theoretically-sound but applicable

252

Giorgio Bertinetti, Guido Max Mantovani, Is There (A Methodology To Measure) A Corporate Governance Risk Premium Into The Corporate Cost Of Capital? http://ssrn.com/abstract¼2372493. 253 Bertinetti G.; Mantovani G.M., (2009) Premi al rischio di governance e comunicazione finanziaria dell’impresa in Maggioni V.; Potito L.; Vigano’ R., Corporate governance: governo controllo e struttura finanziaria, Bologna, Il Mulino, vol. 1, pp. 425–446.

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methodology to estimate GRP (i.e. a misallocating Governance existence) and its drivers (i.e. to infer about Governance incompleteness).”

5.18

CSR as Risk Management

Globalization not only presents chances to enterprises but also creates innovative sources of uncertainty and risks. Multiple business indicators illustrate that the amount of uncertainty for corporate leaders has amplified, because large extended corporations are invented of independent organizations but with remarkable force to grow up and function as a unit. Corporate leaders have to deal with rapid rates of modification in technology, connections, and information flows in consequence of globalization and there is an emergence of problems in managing scale by means of techniques embedded in controlling all decisions across the whole corporation. Social risk management strategies are exceptionally multifaceted undertakings that must explain and square several conditions, perceptions, and variables across the business enterprise. The very character of social risk places management teams in the demanding point of setting apparent direction for a company’s function. It has to be taken into account that in the multifaceted and growing field of social risk, corporate social responsibility (CSR) programs characterize an exceptional instrument for dealing with these contests across the business enterprise. Globalization has formed an operating environment for business leaders that is noticeably diverse from state or local levels, and it is often remarkably volatile. Consequently, business leaders have to comprehend better the dynamics of the global operating environment with the purpose of administering its correlated risks successfully. Corporate social responsibility programs play a vital responsibility in this perspective. It has to be taken into consideration that three viewpoints of the global operating environment are of specific importance for realizing the surfacing contributions of CSR to corporate risk management which are the networked operations, value chains and the global economy followed by the empowerment of global stakeholders; and the forceful strain between and among stakeholders.

5.19

Risk Management and Compliance

It is worth noting that vital function of modern corporate boards is their oversight role, a responsibility that in most jurisdictions is enforced in part as a matter of fiduciary duty and so, board risk oversight is comprehended as a accountability to start fitting internal controls and procedures to avert violations of law making certain the integrity of financial reporting. Nevertheless, board monitoring extends beyond legal (i.e., compliance) risk to an ever-expanding range of risks that must be tackled on an enterprise-wide basis. Thus, risk oversight and risk management are tied to other central roles of corporate boards, explicitly to set corporate strategy, to hire,

5.19

Risk Management and Compliance

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remove, and compensate senior executives, and to communicate with shareholders and other corporate stakeholders. It has to be taken into account that emerging risks, embracing the threat of terrorism, cybersecurity, and climate-related risk, are global in scope and influence. Moreover, regardless of formal similarities in the role of corporate boards and the common demands of ERM across jurisdictions, there is significant distinction in the character and source of the risk oversight responsibility of corporate directors and officers and in the institutional settings in which risk monitoring happens.254 Taking into consideration corporate scandals from Enron and Parmalat, to the global financial crisis, to Volkswagen has made corporate risk management and oversight a crucial objective for corporations, regulators, and the public and so, these external shocks have also revitalized attention to the internal monitoring role of corporate boards regarding legal compliance, the audit function, and ERM. In fact, the size and frequency of these crises raise questions about the capability of existing legal frameworks to stimulate apt oversight by corporate boards. It is worth mentioning here that risk is the probability and prospect that events will happen influencing the accomplishment of strategy and business objectives, encompassing both positive and negative affairs, their probability and severity, and both quantifiable and unquantifiable results. To that extent, companies are exposed to financial risks such as the risk of inflation,255 market risk being the risk to businesses and their investors appearing from exposure to the volatility of expected returns in the capital markets or if they participate in lending, to credit risk linked with the probability of default, non-repayment, or insolvency.256 Firms are exposed to operational or business risks: (1) strategic risk linked with the impact of the firm’s strategy on investor or consumer demand; (2) business risk happening from the uncertainty linked with the costs of firm inputs and project investments compared with their expected return, and with the people and processes the firm relies on to make goods and services; (3) regulatory risk linked with prospective new regulatory requirements imposing new compliance costs on the firm; and (4) reputational risk, which is the prospective for loss to the firm’s reputation beyond the economic loss from the risk event itself.257 Moreover, legal or compliance risk is the risk that the firm, its directors, officers, or employees or other agents will infringe legal or regulatory requirements having financial and reputational effects for the firm and so, managing these kinds of risks entails different approaches and different measures of success.

254

Klaus J. Hopt, Comparative Corporate Governance: The State of the Art and International Regulation, 59 Am. J. Comp. L. 1, 6 (2011). 255 Paul Sweeting, Financial Enterprise Risk Management 1–3 (2011). 256 COSO & WORLD BUS. COUNC. FOR SUST. DEV. (WBSCD), Enterprise Risk Management: Applying Enterprise Risk Management To Environmental Social And Governance-Related Risks, Oct. 2018, https://www.coso.org/Documents/COSO-WBCSD-ESGERM-Guidance-Full.pdf. 257 Philippe Jorion, Value At Risk: The New Benchmark For Managing Financial Risk 495 (3d ed., 2007).

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It is worth noting that the objective of risk management is not the eradication of risk, but rather guaranteeing that the firm assumes an optimal level of risk and is able to manage it successfully. Hence, the firm’s risk appetite, risk tolerance, and capability to absorb risk all set parameters for decision-making and are integral to corporate governance.258 Undeniably, these parameters are launched by corporate boards and management in association with business objectives and corporate strategy. Regardless of significant differences in the regulatory environment, sources of financing, and dominant ownership structures across jurisdictions, a characteristic of corporate governance systems259 is the reality of a control structure that is separate from the shareholders and is accountable for the management of the company – a corporate board or boards. Moreover, depending on the jurisdiction, the board’s monitoring role is established in company and securities law, in accounting principles, in stock exchange listing rules, or in “soft law” guidance and corporate governance codes.260 It has to be taken into account that the corporate compliance function is part of ERM and is concentrated on averting and detecting violations of law and regulations and so, diminishing legal risk.261 Thus, firms implicate directors, officers, or employees in criminal enforcement actions. Furthermore, there is agreement that board oversight of compliance and direct communication networks to the board are key and hitherto, the compliance function is related to corporate law insofar as corporate law establishes a monitoring role for the corporate board or embraces compliance oversight as a fiduciary obligation. In reality, the expansion of the compliance function indirectly boosts traditional fiduciary duty because the information flows engendered by compliance systems assist plaintiffs more easily to prove bad faith or scienter with respect to compliance “red flags.”262 In addition, the oversight duty entails the board of directors to make certain that corporate information and reporting system, which the board arranges is sufficient,

258

CMTTEE. OF SPONS. ORG. OF THE TREADWAY COMM’N. (COSO), Enterprise Risk Management: Integrating With Strategy And Performance 9 (June 2017) COSO ERM Framework: (i) risk appetite is “the types and amount of risk, on a broad level, that an entity is willing to accept or reject in pursuit of value;” (ii) tolerance is “the boundaries of acceptable variation in performance related to achieving business objectives;” and (iii) risk capacity “is the maximum amount of risk that an entity is able to absorb in the pursuit of strategy and business objectives, [considering] liquidity, stakeholder relationships, capabilities and other factors.” 259 Marc Moore & Martin Petrin, Corporate Governance: Law, Regulation, And Theory 206 (2017) (“[A]s is now widely acknowledged, the major banking company failures of 2007 and 2008 were [in part] attributable to practices that were regarded at the time as an intrinsic and valuable part of the strategic operations of the firms involved”). 260 Fabian Hertel, Effective Internal Control and Corporate Compliance (2019). Véronique Magnier, Comparative Corporate Governance: Legal Perspectives (2017). 261 Asaf Eckstein & Gideon Parchomovsky, The Reverse Agency Problem in the Age of Compliance, https://papers.ssrn.com/sol3/papers.cfm?abstract_id¼3460064. 262 Stavros Gadinis & Amelia Miazad, The Hidden Power of Compliance, 103 Minn. L. Rev. 2135, 2179–84, 2188 (2019).

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Pandemic Risk Management

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exists, and the board has not willfully disregarded compliance “red flags” or other signs that the system is ineffective. Nevertheless, under both corporate governance codes and common law principles, boards have broad discretion over the type of compliance system to approve.263 It has to be taken into account that fiduciary duties are a powerful device for incentivizing individual accountability for risk oversight and so, even though fiduciary duties of oversight are enforceable only under national law or in local courts, the obligation they place on directors extends to risk monitoring across the whole corporate enterprise. Moreover, the application of fiduciary duties to directors of the parent corporation or headquarters of a corporate group offers them powerful extraterritorial impact. Furthermore, fiduciary duties pose only weak incentives for risk management and oversight. It has to be taken into consideration that fiduciary duties are weakly enforced in jurisdictions that are the most vigilant, irrespective of differences in enforcement approaches and the nature of the duties themselves because of the principle that corporate boards are better positioned than shareholders or courts to engage in risk assessment264 and their judgments cannot be evaluated by courts or arbitral tribunals. It is worth mentioning here that corporate boards have a critical risk oversight function, but successful board governance alone is not enough to avert new corporate scandals or to keep corporations from externalizing risk. Furthermore, the key, yet limited responsibility of the monitoring board across jurisdictions appeals for greater concentration on complementary sources of oversight, embracing personal liability for corporate officers, monitoring by shareholders, stakeholders, and gatekeepers, and the external regulation of risk governance in its different formulas.

5.20

Pandemic Risk Management

Pandemic risk management265 is a subject well known in medical society due to various global infections by different virus which has come up again due to Covid19. What makes cyber risks resulting from connected systems challenging during the management of a pandemic? It seems that if established security design rules are obeyed, and effort is rested on what is needed for pandemic management, pandemic risks are reduced. Besides, since the COVID-19 pandemic, the focus on stringent personal data protection for preserving individual privacy has been made more obscure by the

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In re Caremark Int’l Inc. Deriv. Litig., 698 A.2d 959, 971 (Del. Ch. 1996); Stone v. Ritter, 911 A.2d 362, 370, 373 (Del.2006). 264 In re Citigroup Inc. S’holder Derivative Litig. 964 A.2d 106, 131 (Del. Ch. 2009) (“To impose oversight liability on directors for failure to monitor ‘excessive’ risk would involve courts in conducting hindsight evaluations of decisions at the heart of the business judgment of directors”). 265 https://www.who.int/influenza/preparedness/pandemic/influenza_risk_management/en/.

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requirement to support public health efforts that demand some degree of global surveillance assisted with new digital technologies and so, bringing into attention Internet of Things (IoT) technologies for their capacity to function autonomously to collect, analyze, and share data about the physical environment, which makes them indispensable parts in the digitalization of pandemic management. Companies far beyond the technology sector are attracted by surveillance profit and the severity of the race to find and render experience as data has turned rendition into a global project of surveillance capitalism.266 Moreover, the IoT characterizes technologies using sensors for detection, gathers and analyzes information, generates meaningful insights and acts and so, the action embodies a tailored product or service or progresses the effectiveness of operational processes. It is worth mentioning here that one difference between the IoT and cyberspace is that the IoT is entirely automated and autonomous; in contrast, cyberspace is aimed for application that connects people which means that with IoT technologies, the role of humans as players in the network is weakened. Hence, automated and autonomous IoT technologies generate questions on the prospective cyber risk arising from the integration of artificial intelligence and machine learning in the IoT network. Do artificial intelligence and machine learning enable pandemic management? Does the increased deregulation of data standards in IoT devices and networks affect ethics concerning cyber risks? It is worth noting that risk managing the complex coupled IoT systems has proven challenging even before the pandemic due to the low cost of IoT devices and so, there is a need to concentrate on enabling data collection for pandemic risk management, while concurrently restricting the aggregation of personal data utilized for alternative interpretations. Moreover, one of the strengths of IoT is symbolized by the low cost and the comparative ease in the deployment of this technology which means that by securing IoT devices and comforting a level of maintenance on a par with other critical systems, such as typical of the telecom industry demanding an increase in the initial cost for production and deployment presenting high operational costs. Hence, an increase in cost reduces the competitive edge of IoT devices. On the other hand, in complex IoT ecosystems, it is not easy to find truly independent risks and to establish an actual correlation between pertinent risks.267 Which is the Value of IoT in pandemic management? It could be said that regardless of the emerging IoT risks and the not understanding of the exact influence produced by these new risks, it is the value of IoT infrastructure in pandemic management and the potentials for optimization of existing pandemic monitoring costs pushing governments to undertake unknown risks and technological 266 S Zuboff, ‘Big other: surveillance capitalism and the prospects of an information civilization’ (2015) 30 Journal of Information and Technology 75–89. J Hoye and J Monaghan, ‘Surveillance, freedom and the republic’ (2018) 17(3) European Journal of Political Theory 343–63. 267 Radanliev, Petar., Roure, David De., Page, Kevin., Nurse, Jason R.C., Montalvo, Rafael Mantilla., Santos, Omar., Maddox, La’Treall., and Burnap, Pete, “Cyber risk at the edge: current and future trends on cyber risk analytics and artificial intelligence in the industrial internet of things and industry 4.0 supply chains,” Cybersecurity, Springer Nat., 2020.

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challenges. Taking into account the no global IoT risk standards and policies, it is expected extra fragmentation of the IoT ecosystems, in which risk assessment models are volatile, vendor-dependent, and less transparent.268 Nonetheless, innovation in the IoT space suggests variations and unknowns affecting critical aspects such as security, adoption, and implementation of different sorts of rights, such as the right to privacy which will be solved partly through insurance and reinsurance not only covering particular IoT risks considered at different operational levels, but more broadly, the spilling effects produced by the cyber-physical nature of IoT infrastructure spanning across the globe and interacting with the physical environment and various logical functions. Thus, in terms of pandemic management, risks are distributed across portfolios in manners permitting a further decrease in average loss values. On the other hand, taking into account the speed of COVID-19 pandemic, it is unclear how fast can insurers adjust to the new risks. It is obvious that there are difficulties in assessing cyber risk: Taking account that the risk from coupled and connected systems in pandemic management donates contests in autonomous medical data collection, storing, processing, and analysis, the question to be answered is why is the risk of connected devices difficult to assess. In fact, the installation of new low-cost connected devices and sensors is not considered an IT or medical function and so, connected devices and sensors serve a very diverse set of functions, varying from plain automation such as room occupancy motion sensors for switching on the lights, to vastly more complex automation such as thermally regulating a building or ensuring its security. Hence, installation of such sensors could be an operational task performed by the buildings and maintenance teams and so, in some instances, cyber risk from connected devices is invisible to cyber risk managers. Furthermore, there are difficulties in assessing cyber risk from feeding medical data to deep learning and artificial intelligence algorithms which means that the difficulties in recognizing the risk from deep learning and AI appear from the limitations of such assessments on existing nonmedical systems. Hence, the digitalization in medical systems is a dynamic automated predictive cognitive system supported by real-time intelligence for cyber medical analytics needing dynamic analytics of cyber-attack threat event frequencies to predict the cyber risk scales of medical data loss, and alternative interpretations of the medical data. Nonetheless, quantitative risk influence estimation is required for making decisions on topics such as assessing cybersecurity, cyber risk, and cyber insurance which means that without dynamic, real-time probabilistic risk data and cyber risk analytics improved with AI, these estimations are outdated and imprecise and so, the influence of cyber risk on digital medical systems is costly, and cybersecurity not essentially effective. Are there cyber risk standards on data risk from connected devices? It seems that there are no uniform standards governing data risk from connected devices. While

268 Nicolescu, Razvan., Huth, Michael., Radanliev, Petar., and De Roure, David, “Mapping the values of IoT,” J. Inf. Technol., vol. 33, no. 4, pp. 345–360, Mar. 2018.

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the current IoT operating model is based on shared responsibility, because of the rapid growth of the IoT shared ecosystem and the lack of guidance, businesses have already started building and applying their standards and protocols which means that the digitalization of medical systems for pandemic management will follow existing standards and protocols developed by the business community. Moreover, the prospective negative consequences of such developments will deter the value of autonomous data sharing by connected devices. It is worth mentioning here that the main strength of IoT in global pandemic management is the capability to aggregate data from different sources and in different formats and connect to different networks using various protocols. Besides, the lack of common, unified, and global standards governing the IoT, generates substantial barriers to the interoperability of connected devices in sharing medical data. Taking into consideration that cybersecurity is focused on preventing certain risks from happening, in terms of conventional and digital pandemic management, prevention has to embrace multi-layered protection in the form of coupled systems owing to the fact that coupled systems augment protection from invisible weaknesses, such as different interpretation of collected data. Furthermore, connected devices performing in the medical system during pandemic management create a demand for digital security concerning the gradually connected critical infrastructure, data production processes, and smart data analytics. In addition, the increase in medical data connectivity implies higher risks and so, dropping open connections lessens cyber risk, which means that the IoT is a solution based on multiple connections. Even though the open connections are anonymized in a way, they still enlarge the attack surface generating a conflict between value and risk which is mitigated by building security in the design process, recognized as Secure by Design principles, or security is controlled by Security Ergonomics by Design principles which are applied early in the design development course.269 Additionally, the digitalization of pandemic management has to utilize connected devices that are secure by default, design, resilience, and enabled for security updates which restrain the value of connected devices in pandemic management. It has to be taken into account that corporations could choose not to be exposed to cyber risk, but they would not be competitive doing so and probable would not be able to perform and so, they are exposed to some level of cyber risk, and some attacks take place and succeed. Hence, when a corporation’s stakeholders detect an unpredicted happening influencing the corporation, they do not transact with the corporation on terms as favorable to it as those that they agreed to before the event which means that the loss that a corporation suffers when stakeholders demand better terms to transact with it following an unexpected happening makes the 269 Radanliev, Petar., De Roure, David., Nurse, Jason R. C., Mantilla Montalvo, Rafael., Cannady, Stacy., Santos, Omar., Maddox, La’Treall., Maple, Carsten, “Future developments in standardisation of cyber risk in the Internet of Things (IoT),” SN Appl. Sci., vol. 2, no. 2, pp. 1–16, Feb. 2020. Craggs, Barnaby, and Rashid, Awais, “Smart Cyber-Physical Systems: Beyond Usable Security to Security Ergonomics by Design,” in 2017 IEEE/ACM 3rd International Workshop on Software Engineering for Smart Cyber-Physical Systems (SEsCPS), 2017, pp. 22–25.

5.21

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corporation riskier to transact with for stakeholders generating a reputation loss. Thus, the risk of reputation loss is molded as the outcome of an optimal risk management strategy. Moreover, a risk-neutral company benefits from risk management if its stakeholders care about the risk they bear because of their relations with the company. Hence, the compensation wanted by stakeholders to bear the risk of an attack means that it is optimal for the company to invest more in risk management to diminish the risk of an attack. With rational, and fully informed agents, a successful cyberattack consistent with agents’ pre-attack information should have no influence on a financially unconstrained target’s reputation and post-attack policies. Nevertheless, if the attack offers a valuable signal to the company and its stakeholders about the cost of attacks and the probability of future attacks, the new information influences company value. Furthermore, when the company and its stakeholders learn that a cyberattack has greater costs or probability than beforehand considered, company value reflects these increased costs and prospect. It is worth noting that if an attack makes public only characteristic information about the target, industry competitors benefit from the attack. In contrast, shareholders of these competitors experience a shareholder wealth loss as well being consistent with the position that the new information revealed by the attack augments the expected costs of attacks for competitors as well. Kamiya et al.270 argue “that attacks that do not involve the loss of personal financial information do not cause a significant shareholder wealth loss. In contrast, attacks where personal financial information is lost involve a significant shareholder wealth loss. For the attacks for which out-of-pocket losses can be computed and shareholders experience a significant wealth loss, total out-of-pocket costs account for only $1.7 billion of a total shareholders wealth loss of $24.99 billion.”

5.21

COVID-19 and Risk Management

The global spread of coronavirus is the one of this century’s greatest threats. Governments, corporations, and organizations have to apply risk assessment and risk management policies to combat coronavirus not only in the short term but also in the long term. The G20 has committed itself “to spare no effort” to support the global economy during and after the COVID-19 pandemic.271 Moreover, the G20 supports “a time-bound suspension of debt service payments for the poorest countries that request forbearance,” but this suspension is temporary which means that countries need long-term FDI inflows as a sustainable basis to meet debt obligations and facilitate economic recovery.

S. Kamiya, J.-K. Kang and J. Kim et al., Risk management, firm reputation, and the impact of successful cyberattacks on target firms, Journal of Financial Economics, https://doi.org/10.1016/j. jfineco.2019.05.019 p. 29. 271 G20 Finance Ministers and Central Bank Governors, “Communiqué”, Apr. 15, 2020, p. 1. 270

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It is worth mentioning here that risk assessment is divided into four activities: (1) identifying the prospective threat; (2) drawing a dose/response curve; (3) estimating the amount of human exposure; and (4) classifying the outcome, but this rationale applies to pandemic situations as well. It could be said that the predicted length of measures such as social distancing and the shutdown of nonessential businesses is itself a risk assessment. In fact, transparency of data is essential for proper risk assessment. On the one hand, disease control infringes on individual liberties and causing novel privacy law issues. On the other hand, Taiwan has shown the novel use of technology and so, text messages were sent to every mobile phone on the island tracking individuals during the period of mandatory quarantine and the tracking is grounded on their phone’s sim cards and their nearby base stations. It has to be taken into account that in the early stages, governments and organizations will find and categorize both risks to both health and the economy, but may lack direction on how to prioritize these two sectors, which in fact compete. It is obvious that the fighting against COVID-19 is a fighting on two fronts – health and economics and so, this is where risk management moves in. Risk management is assessing policy alternatives in light of the results of risk assessment, and choosing appropriate control options, embracing regulatory measures. In line, the use of matrix analysis is a core concept of risk management and in the environment of coronavirus, Health Canada has employed a risk matrix to support organizations to decide whether they should cancel mass gatherings and implementing the 2-m distance rule between persons if the events go forward.272 In reality, each business has to examine the conditions of risk that are precise to that business, unless there is a direct government order entailing a shutdown of that type of business which is the new element of risk management in COVID era. The coronavirus has larger implications for infrastructure going forward, and government policy regarding that infrastructure and so, telecommunication infrastructure is a key part of the network to permit people to stay connected. Now with the coronavirus pandemic, telecommunications firms are thrust back into a central role due to handling situations for people who work from home. Moreover, the coronavirus pandemic and centrality of telecommunications put a spotlight on the regulation of the internet and the “net neutrality” debate.273 The focus of any governmental authority will be on ensuring that there is the equivalent of an “emergency lane” on broadband networks, for health, safety, and security-related traffic. There is a need that government regulation makes certain that there is the equivalent of an “emergency lane” on broadband networks, for health, safety and security-related traffic and so, this emergency lane is more decisive than

272

https://www.canada.ca/en/public-health/services/diseases/2019-novel-coronavirus-infection/ healthprofessionals/mass-gatherings-risk-assesment.html. 273 Blevins, “The Use and Abuse of light touch internet regulation” (2019), 99 Boston Univ. L. Rev. 177. https://theconversation.com/creating-a-high-speed-internet-lane-for-emergency-situations79151.

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ever in the coronavirus pandemic, which means that due to the fact that more people work from home and use cyberspace for recreation, it is vital that health and safety providers not be slowed down in emergency situations. Therefore, government policy should attract investment in the market that will augment the infrastructure for the “emergency lane” in the future. Moreover, it seems that government policy is lowering mobile phone costs to consumers but not ignoring the requirement to attract capital to the industry to build the infrastructure of the future such as 5G and higher utilized in pandemics. It has to be taken into consideration that in the United States, public companies are required to file annual reports (Form 10-K) that disclose the risk features that influence negatively the price of their stock. Moreover, the risk of a pandemic was well known before the current crisis and now it is evaluated the effect for shareholders for almost all corporations. All firms with registered securities are subject to reporting requirements by the Securities and Exchange Commission (SEC)274 mandated by federal securities law and so, managers have a duty to inform existing and prospective shareholders of any reasonable risks affecting share value. The COVID-19 pandemic has forced states to endorse digital surveillance approaches for pandemic management, some of which operate autonomously to collect, analyze, and share data. Presently, the digitalization of COVID-19 pandemic management is happening across the globe, with the integration of automated and autonomous connected devices feeding real-time data to artificial intelligence algorithms. Moreover, while the digitalization of medical systems awards strong value for pandemic management, there is a demand for solutions that deliver value for pandemic management, and not on designing systems that expose personal data to cyber risk. Furthermore, the design of digital systems for pandemic management must foresee that connected devices generate new unpredictable and often invisible cyber risks that are currently unregulated and frequently ignored. In addition, there is a need for appropriate cyber insurance policies to transfer risk based on standards and regulations governing new medical systems. As things stand at present, many digital pandemic management systems are driven by the monitoring opportunities and treatment potential generating systems but ignoring threats, continuing to chase opportunities and so, not stopping hackers manipulating the systems and interfering along the process. The response to the COVID-19 pandemic triggered a broad-based shock to the US and global economies. Moreover, the speed and depth of the downturn unsettled business and consumer economic activity, pushing unemployment up, pummeling consumer and business confidence and spending. Consequently, banks are facing an upsurge in credit and operational risks. Before the economic downturn brought on by the pandemic, the banking sector was in a position of strength, with sound capital and liquidity, low problem assets, and effective risk management systems and so, the strength of the federal banking system permitted banks to proactively work with borrowers and be a source of strength when the pandemic started but due to

274

https://www.sec.gov/edgar.shtml.

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COVID-19 the banking systems are facing weak financial performance, elevated credit, and operational risks. Thus, higher credit losses, higher overhead expenses, and lower net interest income influencing financial performance which means that the onset of the pandemic produced an uncertain credit environment testing the resiliency of both commercial and retail loan portfolios. To that extent, credit risk management practices must be flexible and proactive to meet the challenges of the current environment. Moreover, operational risk is intensified as banks amended business processes and engaged third parties to support widespread remote work capabilities, augmented technological capacity, and solutions to preserve operations under elevated operational volumes. In addition, compliance risk is elevated because of a combination of altered operations, employees working remotely, and the requirement to operationalize new federal, state, and propriety programs intended to support consumers such as the CARES Act, Paycheck Protection Program (PPP), and a variety of forbearance and deferred payment programs. Does the market volatility spike? It is obvious that the growing economic influence of the pandemic substantially touched financial markets and so, equity and bond market volatility spiked quickly as market participants grew concerned about the economic implications of the spread of the pandemic across the globe.275 In light of the COVID-19 crisis, the EU Commission is escalating political pressure and so, the Commission warns member states of potential hostile takeovers of “Europe’s strategic assets” assisted by the current economic shock, not only in health, but all sectors. Moreover, the guidance recommends member states to address these risks by adopting and applying FDI screening mechanisms in line with the regulation’s framework. Screening mechanisms must protect countries’ military sectors, perhaps enlarged by fundamental interests of society, such as the need for electricity, water, and food supply and so, encompassing economic notion of security by comprising industrial policy along with geopolitical and economic considerations. Furthermore, critical part is the degree of risk the screening mechanism necessitates for an investment to influence “security or public order.” In addition, the regulation stipulates a broad understanding of “security” and it does not replicate the well-known ground of exception to the EU Fundamental Freedoms “public policy or public security”276 because the European Court of Justice (ECJ) defines it as “a genuine and sufficiently serious threat to a fundamental interest of society.”277 Also, the regulation refers to the broader exceptions of public international law278 which means that the notion of “likely to affect” sets a lower threshold of risk than the ECJ’s definition and so, the term “strategic assets” implies an even broader security understanding. To that extent, the regulation only lists “critical infrastructure and technologies” as possibly related to “security or public order” which is linked to the ECJ’s narrow 275

OCC, Semiannual Risk Perspective Spring 2020, https://www.occ.treas.gov/. Treaty on the Functioning of the European Union, Art. 65(1)(b). 277 Commission v Greece, C-244/11 (Nov. 8, 2012), para. 67. 278 FDI Screening Regulation, (EU) 2019/452, Mar. 19, 2019, Recitals (3) and (35). 276

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understanding of “public policy or public security.” Furthermore, the term “strategic assets” embraces geopolitical and industrial policy considerations, such as building and keeping future technology capabilities that is to say that the regulation picks a narrower security understanding.279 In line, the guidance’s repeated use of the term “strategic assets” and the Commission’s call on member states to use the regulation to “prevent a sell-off of strategic EU assets.”280

References 1. Demb, A., & Neubauer, F. (1992). The Corporate Board: Confronting the paradoxes. Oxford: Oxford University Press. 2. Action Plan. European company law and corporate governance – a modern legal framework for more engaged shareholders and sustainable companies, COM (2012) 740 final. 3. Bechtel, A., Ranaldo, A., & Wrampelmeyer, J. Liquidity risk and funding cost. Working Papers On Finance No. 2019/03. 4. Djankov, S., La Porta, R., Lopez-de-Silanes, F., & Shleifer, A. (2006). The law and economics of self-dealing. NBER Working Paper 11883. 5. Ernst & Young. (2009, February). Market risk capital set to increase. Prudential standards Update. 6. European Commission. Communication on building trust in human-centric AI, COM (2019) 168. 7. European Commission. Corporate governance in financial institutions and remuneration policies (Green Paper), COM (2010) 284. 8. European Commission. Greenpaper promoting a European framework for Corporate Social Responsibility, 18 July 2001, COM (2001) 366 final. 9. FATF. (2014). Guidance for a risk-based approach. 10. Galbraith, J. R. (1977). Organization design. Reading, MA: Addison-Wesley. 11. King, G. (2018). Anti-money laundering: An overview. In G. King, C. Walker, & J. Gurule (Eds.), The Palgrave handbook of criminal and terrorism financing law. Palgrave Macmillan. 12. Koethenbürger, M., & Stimmelmayr, M. (2010). Corporate deductibility provisions and managerial incentives, mimeo. 13. Koops, B. J. (2014). The trouble with European data protection law. International Data Privacy Law, 4(4). 14. Heiman, M. R. A. (2020). The GDPR and the consequences of big regulation. Pepperdine Law Review, 47, 945. 15. Billio, M., et al. Econometric measures of systemic risk in the finance and insurance. NBER Working Paper Series 16223. 16. Oxelheim, L., & Wihlborg, C. G. (1987). Macroeconomic uncertainty: International risks and opportunities for the corporation. New York: Wiley. 17. Peel, J. (2010). Science and risk regulation in international law. Cambridge: Cambridge University Press. 18. Quelle, C. (2017). The ‘risk revolution’ in EU data protection law: We can’t have our cake and eat it, too. Tilburg Law School, Legal Studies Research Paper Series.

279

Regulation, Art. 4(1). Amendment 39 and 40 in Report A8-0198/2018 on Regulation, Art. 4(1). “Coronavirus: Commission issues guidelines to protect critical European assets and technology in current crisis,” EU Commission press release, Mar. 25, 2020.

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19. Regulation 2016/679, the new General Data Protection Regulation entered into force in May 2018. 20. Krämer, R., & Lipatov, V. The effect of corporate taxation and ownership on raising shareholder capital. CESIFO Working Paper No. 4436. 21. Van Duyne, P. C., Harvey, J., & Gelemerova, L. (2018). A ‘risky’ risk approach: Proportionality in ML/TF regulation. In G. King, C. Walker, & J. Gurule (Eds.). The Palgrave handbook of criminal and terrorism financing law. Palgrave Macmillan. 22. Bratton, W. W. (2002). Enron and the dark side of shareholder value. Tulane Law Review, Public Law and Legal Theory Working Paper n.035. 23. White Paper on Artificial Intelligence – A European approach to excellence and trust Brussels, 19.2.2020 COM(2020) 65 final.

Chapter 6

AI Risk Management

6.1

AI Background

The algorithm itself is the expression of the sum of the objectives and perspectives of those for whose objectives the algorithm is deployed. In lieu of principles, then, there are presumptions and the self-created limitations of data fields that create the boundaries within which choices are cabined. These are the structures of conventional governance, but are now deployed in a quite different space. Artificial intelligence has become a new engine for economic growth and as the central driving force of the new round of industrial reforms, artificial intelligence will further discharge the energy accumulated from prior technological revolutions and industrial alterations by generating new powerful engines to modernize economic activities such as production, distribution, exchange, and consumption. The vibrant development of the business environment has inspired the efforts of managers and so firms use projects to manage alterations and to develop and deploy new products which mean that in a competitive environment, only those who manage the risks and realize the project more professionally will succeed. Asset management refers to the professional administration and investment of financial assets to achieve specified investment goals and objectives. The risk management is the internal processes strengthening the resilience already during the prevention period and is inevitable for guaranteeing the process security. The risk management synchronizes the activity for controlling and managing a firm with orientation on the risks.1 Moreover, the risk management is an inseparable part of the project management and so all projects are evaluated independently concerning the possible risks for the reason that each project is specific bringing risks whose reason

1 Řehák, D., Šenovský, P., Hromada, M., Pidhaniuk, L., Dvořák, Z., Loveček, T., Ristvej, J., Leitner, B., Sventeková, E., Mariš, L., 2018. Metodika hodnocení resilience prvku kritické infrastruktury. Ostrava: VŠB-Technická univerzita Ostrava, Fakulta bezpečnostního inženýrství. ISBN 978-80-248-4164-9.

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 G. I. Zekos, Economics and Law of Artificial Intelligence, https://doi.org/10.1007/978-3-030-64254-9_6

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is not only the individuality of the projects but also the financial demandingness and a longer time period for realizing the projects. It has to be taken into consideration that all projects are threatened by a whole range of different risks, which result from the nature of the internal and external environments of their realization that are transforming energetically which means that risks accompany each project and are part of all life cycle stages.2 Furthermore, the risk management in the projects is linked also with the risk treatment being a cycle of individual stages whose objective is to minimize the losses and damages triggered by crisis happenings having a preventive quality. To that extent, the risks in projects generate unfavorable situations happening in the development and so influencing the overall success of any project which means that the risk in the project is to be monitored and to respond to it effectively. In fact, a phenomenon that is a critical risk for one project can be a common one in another project which means the project risk management cannot be merely unified for a certain type of project. The key categories of the project risks are the time loss, financial loss, threat to the success, and failure of the whole project.3 It has to be taken into consideration that the improperly trained project managers and attempts to start too many projects are the biggest problems in the project management area. Besides, the ineffective course of selecting the projects and inadequate supervising of the state of the project are a less significant problem. Many companies are investing heavily in expert systems, a subfield of Artificial Intelligence. Algorithms are simply sequences of instructions for executing a given task. Blockchain has the features of decentralization, nontamperability, and programmability, which solve the security problem of big data storage, particularly for the protection of personnel information, which includes a large amount of private information, and need to be regulated and endorsed by government and large companies.4 But the blockchain itself has some drawbacks, the most vital of which is its limited storage space, which makes it impossible to store large amounts of data. Nonetheless, the non-tampering and traceability of the blockchain naturally have the application advantages of industries such as finance and credit reporting.5 The decentralized nature of blockchain generates the new concept of a token economy in which the community’s revenue is allocated to the actual content producers and service users who generate value. In addition, Blockchain is a key technology that enables new protocols for the establishment of a token economy in the future, leading to a new economic paradigm. Thus, Blockchain advances 2 Obrová, V., Smolíková, L., 2013. The role of risk management in successful project management. International Business Information Management Association Conference, IBIMA 2013; Vienna. 3 Klučka, J., Havko, J., Haviernikova, K., 2016. Risk Management in Cluster’s Cooperation in Slovak Republic. Conference: 3rd International Multidisciplinary Scientific Conference on Social Sciences and Arts, SGEM 2016 Location: Albena, Bulgaria. 4 P. Dunphy, F.A. Petitcolas, A first look at identity management schemes on the blockchain, IEEE Secur. Priv. 16 (4) (2018) 20–29. 5 R. Beck, M. Avital, M. Rossi, J.B. Thatcher, Blockchain Technology in Business and Information Systems Research, Springer, 2017.

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information security and transparency by sharing encrypted data among network members. As a result of its prominence on security and trust, blockchain is a great fit in the financial sector and, until recently, its widespread popularity was limited. Moreover, the advances in transaction transparency and reliability pursued by blockchain are of great significance in that they enable more objective and fairer consensus in terms of technology innovation and social perspectives. It is worth noting that as a result of its centralized management architecture, DNS root is exposed to both internal and external attacks and so a response is the occurrence of a system such as TD-Root, a trustworthy decentralized DNS root management architecture based on permissioned blockchain, removing security vulnerabilities and trust risks faced by the current DNS root. Domain name operations based on blockchain are initiated to realize the registration, update, and revoke of TLDs and so an algorithm (C-RAND) is planned to guarantee the strong consistency, scalability, and security of TD-Root. Hence, each root server keeps the same root zone file through C-RAND, replacing the up-to-date centralized distribution method in DNS root which means that TD-Root is tamper-proofing tolerating one-third malicious root servers behaving arbitrarily.6 The increasing availability and use of new technologies and concepts such as the Internet of Things, Blockchain, and Artificial Intelligence combined with an increasing e-connectivity of organizations are expected to bring about new sorts of risks linked to knowledge. Organizations are exposed to a number of risks linked to knowledge such as risks connected to human resources, relational risk, risks linked to decision-making concerning new strategies, markets, products along with other central business issues, risks associated with knowledge gaps, or risks correlated to the outsourcing of business affairs.7 It has to be taken into consideration that KRM positively influences organizational success, sustainability, growth, and innovativeness, allowing managers and owners to a better understanding of the linkage between KRM and organizational performance. Nowadays, knowledge is not only deemed as an imperative asset and a source of prospective competitive advantage of organizations, but also as a source of different risks and hazards.8 Internal risks such as knowledge attrition, knowledge waste, or knowledge hoarding are mainly connected with an organization’s internal situation, while knowledge risks such as knowledge leakage or knowledge spillover tackle an organization’s interactions with its external environment. Thus, knowledge risks result in several negative effects, such as failing to advance high-quality solutions,

6 G. He, W. Su, S. Gao et al., TD-Root: A trustworthy decentralized DNS root management architecture based on permissioned blockchain, Future Generation Computer Systems (2019), doi: https://doi.org/10.1016/j.future.2019.09.037. 7 Durst, S., Bruns, G., & Henschel, T. (2016), The management of knowledge risks: What do we really know? International Journal of Knowledge and Systems Science, 7, 19–29. https://10.4018/ IJKSS.2016070102. 8 Bratianu, C. (2018). A holistic approach to knowledge risk. Management Dynamics in the Knowledge Economy, 6, 593–607. https://doi.org/10.25019/MDKE/6.4.06.

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costly disruptions of performance or operations, loss of competitive advantage, or even tragic accidents.9 Corporate governance identifies the function, structure, and role of a board of directors (BoD) distinguishing the means in which corporations are organized. Moreover, the BoD, which is the key channel for corporate governance, is responsible for protecting the right interests of stakeholders of a corporation through directing its operation and by supporting its decision-making and so the BoD of a corporation is the body that verifies policies for corporate management and makes decisions on key corporation issues. Strong corporate governance has been shown to mitigate agency problems and to encourage managers to function properly.10 It has to be taken into account that the relationship between corporate governance and corporation performance depends on the measurement used for firm performance. Some corporation-specific governance physiognomies, such as board size and insider and institutional ownership, are predictors of corporation performance in models of analysis. Moreover, investors are aware of the influence of corporationspecific corporate governance and ownership features on corporation performance. Additionally, the differences between economic and noneconomic social factors among states influence the corporation’s performance. Furthermore, regularity authorities in the MENA countries respect the unique characters of religion and other social heterogeneity conditions when introducing control mechanisms. The levels of income inequality, economic, and financial developments are major conditioners of the corporate governance and corporation characteristics relation when the accounting-based measures of performance are considered. On the other hand, inflation and human development are significant conditioners of the corporate governance and corporation characteristics relation when the market-based measure of performance is considered. Furthermore, the interface between financial market conditions and corporation performance is mitigated in often-predictable manner by national social factors, so offering a more solid basis for developing suitable development policy.11 In addition, managers without risk management constraints conduct risk management, while those with risk management constraints do not change their trading. Moreover, a small number of fund managers with risk management requirements can have a noteworthy effect on the market.12

9

Susanne Dursta, Christoph Hinteregger, Malgorzata Zieba, The linkage between knowledge risk management and organizational performance, 2019 Journal of Business Research 1-10. 10 Valeria Naciti, Corporate governance and board of directors: The effect of a board composition on firm sustainability performance, 2019 Journal of Cleaner Production 117727. 11 Charilaos Mertzanisa, Mohamed A.K. Basuonyb, Ehab K.A. Mohamed, Social institutions, corporate governance and firm-performance in the MENA region 2019 Research in International Business and Finance 75. 12 Shiyang Huang, Ying Jiang, Zhigang Qiuc, Zhiqiang Ye, An equilibrium model of risk management spillover, 2020 Journal of Banking and Finance 105604 p15 (The risk management spillover effect arises because relative performance concerns have different effects on different managers. Specifically, relative performance concerns do not change the behaviors of RM managers but have a significant impact on those of normal managers. As a result, relative performance concerns amplify

6.2

6.2

The Globalization of Information and Its Consequences

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The Globalization of Information and Its Consequences

Has the globalization of information been achieved? The capacity to access data almost instantly from almost anywhere on the globe and project it globally poses obvious challenges to legal regimes premised on territorially bounded states and those challenges are not conceptual so much as practical, often needing coordination across jurisdictions. To that extent, protection of intellectual property rights has always been challenged by the capacity to make copies and so the replacement of analogue technologies such as the tape recorder, the photocopier with digital ones fundamentally transformed the economics of copying which means that the task of making one copy gave way to the capacity to share music and other content at effectively no cost and without regard to distance. Certainly, numerous social media platforms encourage this by “nudging” users to share material that they did not create.13 In fact, lawsuits and legislative alterations led to most media platforms adopting copyright policies and takedown protocols, while others were shut down completely. Facebook removed about 300,000 pieces of content per month for copyright violation.14 Moreover, producers and distributors developed technical means to restrain copying, but a certain amount of piracy is often priced in as the cost of doing business. As with the unauthorized sharing of intellectual property, cyberspace also enables the unwanted dissemination of prohibited material and so the speed with which information spreads across the globe regularly exasperates efforts to contain it, while also confronting the legal rules intended to deter or punish tortious or criminal behavior. Undeniably, efforts to ban material in one jurisdiction may merely serve to increase its prominence while not curtailing its availability from other jurisdictions. The globalization of information has put more knowledge in the hands of more people than at any time in human history; in many repressive regimes, cyberspace has played a liberating role owing to the difficulty of containing information. As AI systems play a greater role in generating content, efforts at containment via data localization, filtering, or otherwise slowing the flow of information will run the risk

the effects of risk management suggesting that a small fraction of RM managers can have a significant market impact.) Sumon Bhaumik, Nigel Driffield, Ajai Gaur, Tomasz Mickiewicz, Paul Vaalere, Corporate governance and MNE strategies in emerging economies, Journal of World Business 54 (2019) 234–243. 13 Corinne H.Y. Tan, ‘Technological “Nudges” and Copyright on Social Media Sites’ (2015) 2015 (1) Intellectual Property Quarterly 62; David Tan, ‘Fair Use and Transformative Play in the Digital Age’ in Megan Richardson and Sam Ricketson (eds), Research Handbook on Intellectual Property in Media and Entertainment (Edward Elgar 2017). 14 ‘Intellectual Property’ (Facebook) accessed 26 July 2019. See further Daniel Seng, ‘The State of the Discordant Union: An Empirical Analysis of DCMA Takedown Notices’ (2014) 18 Virginia Journal of Law & Technology 369; Jennifer Daskal, ‘Google Inc. v. Equustek Solutions Inc.’ (2018) 112 American Journal of International Law 727.

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of destabilizing the foundations of the digital economy and are at best expected to be a short-term fix for a fast-moving problem. Nowadays, high-speed computing presents comparable encounters to existing regulatory models in fields from securities regulation to competition law, simply by enabling lawful activities such as trading in stocks, or comparing and adjusting prices, are undertaken more quickly than previously conceived possible. It could be argued that the development of AI environment demands the development of a similar law environment in order to deal with forthcoming problems caused by virtual trading, etc. which means that the existing legal rules will be far behind in regulating Al trading, etc., and so e-justice on a global e-environment needed to be emerged accompanied by the independent e-arbitration.

6.3

AI Networks Vs. Human Networks

Is there a difference between AI Networks and Human Networks? The integration of AI agents into society has led to a different manner in which persons interact with each other, along with a new kind of direct interaction presented with AI agents, which are increasingly posed in society. In light of the occurring gaps in the competences and skills AI agents have vis-a-vis human nodes, the application of the nonreciprocal paradigm is more justified in a network, which incorporates AI agents than in a strictly human one. Moreover, the key characteristic of AI networks is that AI agents possess the aptitude to act at tremendous speed, which is manifested via their extremely high levels of activity when performing their assigned tasks and so imposing risks that cannot be counter imposed by non-AI agents. Furthermore, AI agents possess another feature, the number of platforms it can utilize in completing its task and, as a byproduct, in imposing risks which means that the pattern of an AI agent speed and the numerous plausible platforms in which it can act on, makes the AI agent a risky actor within AI networks. On the other hand, related to networks that are merely composed of interactions and relationships between human nodes, the danger is more visible in the relationships. It is important to note that, in most cases, AI agents and their principals cannot control the design of the network in which they function because cyberspace is an already existing platform on which many AI bots run without the capacity to bring about alterations to its infrastructure and so they use the preexisting structure of the network for their own benefit, but they do not have the capacity to substitute this structure. Besides, with regard to sub-internet networks, such as a controlled hospital system or an internal security system, which were generated by human principals and utilize AI technology within the new network can be utilized accordingly which means that as architects of the network have more control over the characteristics of the network naming connectivity, structure, and properties, then agents are held responsible for damages caused within the network by the actions of AI agents, depending on the nonreciprocal risks the network they generated impose.

6.4

Automated Decision-Making

239

It is worth noting that having complete control over a network ascribes special features that are different from randomly made networks regarding the volume and scope of damages AI nodes impose and the identity of those who control and guide them and so they should be held liable. Furthermore, central nodes inflict more risks to connected nodes which means that the more a node is linked to other nodes, the more it is vulnerable and at risk to suffer damages. Thus, a higher degree of connectivity by default leads to a higher degree of vulnerability, which in turn alters the nonreciprocal risks balance, which is inflicted and counter-inflicted within a network. Lior15 argues that “the claim that the vulnerability of an AI agent node increases, thus nonreciprocal risks transforms into reciprocal ones, is a fallacy in the AI context. This is because the risks are not actually borne by the AI agents, but rather their principals. By deflecting the risks of the principal to the agent, the principal node itself is a minefield of nonreciprocal risk, on the one hand, with no vulnerability to bear on the other.”

6.4

Automated Decision-Making

First of all, automated decision-making systems use complex mathematical algorithms to ascertain relationships and likely patterns in large data sets such as Internet browsing behavior, purchase history, residence zip code, employment, educational achievement, salary, etc. In other words, current algorithms cannot predict without the inserted data and so at the moment algorithms cannot create their own algorithms and insert their own data but merely are human made mathematics to make calculations that humans have discovered. Are humans the creation of a very advanced algorithm not entirely understandable by the current human mind? It is worth noting that presently automated decision-making algorithms evaluate teachers, approve or reject loan applications, choose whom to search in an airport security line among a litany of other commercial and government decisions.16 On the other hand, automated decision-making systems based on “big data”–powered algorithms and machine learning are just as prone to mistakes, biases, and arbitrariness as their human counterparts.17 Moreover, the power of technology shields

15

Anat Lior, The AI Accident Network: Artificial Intelligence Liability Meets Network Theory https://ssrn.com/abstract¼3561948. 16 Hous. Fed’n of Teachers, Local 2415 v. Hous. Indep. Sch. Dist., 251 F. Supp. 3d 1168 (S.D. Tex. 2017). Danielle Keats Citron & Frank Pasquale, The Scored Society: Due Process for Automated Predictions, 89 WASH. L. REV. 1, 8–10 (2017) (describing the use of algorithms in credit scoring). Andrew D. Selbst, Disparate Impact in Big Data Policing, 52 GA. L. REV. 109, 113–15 (2017) (describing predictive policing). Meredith Whittaker Et Al., AI Now Inst., AI Now Report 2018, at 18–22 (2018), https://ainowinstitute.org/AI_Now_2018_Report.pdf. 17 Andrew Guthrie Ferguson, Big Data and Predictive Reasonable Suspicion, 163 U. PA. L. REV. 327, 389–95 (2015) (discussing some of the ways law enforcement can use large data sets to eliminate biases in policing); Ric Simmons, Big Data, Machine Judges, and the Legitimacy of the

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algorithmic systems from critical interrogation and so a technologically driven decision-making process seems to defy interrogation, analysis, and accountability undermining due process which means that algorithmic decision-making can be an illegitimate source of authority in a liberal democracy.18 To that extent, legitimacy as a perception or assumption that the actions of an entity are desirable, proper, or appropriate within some socially constructed system of norms, values, beliefs, and definitions which means that legitimacy embraces the obligation to comply with the directives of an authority, irrespective of the personal advantages. It could be said that algorithmic legitimacy is founded on the legitimacy of the authority, private or public, using it or on the legitimacy of the decision-making process or on the decision itself. In other words, legitimacy is the authority to make decisions for others according to the demands of the law which means that there is a need for the application of the rule of law. Automating decisions about commercial and social goods may be at odds with vital democratic values like equality, fairness, and human flourishing, whatever the benefits of computational effectiveness may be. Algorithms estimate the probability that something will happen based on existing data and so existing algorithms cannot know for sure that a loan applicant will pay back his/her loan in time but simply they can only conclude that a certain mix of issues generates some probability that a result will take place. Moreover, like statistical analysis, automated decision-making systems will make mistakes. Furthermore, mistakes are not the only threat to algorithmic legitimacy in a society that values the rule of law due to the fact that algorithms become more accurate and better predictors, they also become more complex which means that they are opaquer and more resistant to interrogation. In addition, algorithms are either intentionally kept secret, whether as proprietary trade secrets or in order to prevent gaming, or they are functionally opaque as a consequence of the “specialized knowledge” needed to understand their source code.19 To that extent, the opacity of decision-making algorithms prevents those harmed by

Criminal Justice System, 52 U.C. DAVIS L. REV. 1067, 1096–97 (2018) (noting that one of the “primary benefits of using predictive algorithms” is “their complete disregard of irrelevant subjective factors” like race, religion, what a person wears, how they conduct themselves in court, and so forth). 18 Frank Pasquale, The Black Box Society: The Secret Algorithms That Control Money And Information 1–17 (2015) (describing the ways in which data analyses about consumers are hidden from view and from legal process). Emily Berman, A Government of Laws and Not of Machines, 98 B.U. L. REV. 1277, 1279 (2018). 19 Rebecca Wexler, Life, Liberty, and Trade Secrets: Intellectual Property in the Criminal Justice System, 70 Stan. L. Rev. 1343 (2017) (describing how trade secrecy impacts the criminal justice system noting that policies for algorithmic transparency should consider the potential for gaming). Andrew D. Selbst & Solon Barocas, The Intuitive Appeal of Explainable Machines, 87 Fordham L. Rev. 1085, 1092–94 (2018) (arguing that understanding machine learning algorithms takes “specialized knowledge” and even with that knowledge, the basis of a decision is often still inscrutable). Harry Surden, Machine Learning and the Law, 89 Wash. L. Rev. 87, 89 (2014) (explaining how machine learning can make algorithms capable of adapting “to enhance their performance on some task through experience”).

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automated systems from deciding either how a decision came about or the logic and reasoning behind it and so making accountability problematic. It is worth mentioning here that an advantage of automated decision-making is that algorithms can take into account a multitude of factors, far more than humans, when analyzing enormous data sets finding unforeseen correlations between independent and dependent variables. Furthermore, it is worth noting that the feature of AI systems in the context of Big Data analysis is a swing “from causation to correlation” and data mining techniques depend on inductive knowledge and correlations identified within a dataset. Thus, in place of searching for causation between the relevant considerations, algorithms are utilized to spot patterns and statistical correlations.20 It is worth noting that there is energy cost implicated in data analysis. To that extent, algorithms powered by machine learning learn from experience and make even more accurate probabilistic determinations over time making them privacy invasive and, arguably, inconsistent with democratic principles of autonomy, dignity, and choice. Hence, automated decision-making represents a radical shift in the discourse of power and even alterations on principles of law and dogmas generating a new soft law at the beginning, which can be written later on and so shaping human society’s understanding and perceptions of legitimacy and legality opening the door for an entirely mechanical AI society. Finally, advanced automated decision-making systems not only have, and will have much more in the future, the capability to do more than humans ever could, they also supposedly remove humans and their biases from decision-making processes. On the other hand, the existing mathematical system analyzing the data is agnostic about the value of the underlying data which means that algorithmic decision-making systems do not ignore biased data, they end up cementing those biases in society which can be the motive for an elite to promote an AI society, which in reality will be controlled by humans to conquer the globe. For instance, an algorithm can be used to predict recidivism rates among criminals, but if the inputs are biased against persons of color, the algorithms will overestimate the recidivism risk of black people and underestimate the risks for white people. Furthermore, it could be said that automated decision-making disempowers some humans by transforming society into statistics and bits of data. Ari Ezra Waldman21 argues that “algorithmic decision-making is a product of the neoliberal managerial

20 Mayer-Schönberger/Cukier, Big Data: A Revolution that will Transform How We Live, Work and Think, 2013, p. 14, 15, 18, and p. 163: “Big Data does not tell us anything about causality”. Skopek, Big Data’s Epistemology and Its Implications for Precision Medicine and Privacy, in: Cohen/Fernandez Lynch/Vayena/Gasser (eds.), Big Data, Health Law, and Bioethics, 2018, pp. 30 et seq. 21 Ari Ezra Waldman, Power, Process, and Automated Decision-Making, 88 Fordham L. Rev. 613 (2019). Available at: https://ir.lawnet.fordham.edu/flr/vol88/iss2/9; Jedediah Purdy, Neoliberal Constitutionalism: Lochnerism for a New Economy, 77 Law & Contemp. Probs. 195, 198–203 (2014) (describing neoliberal interpretations of constitutional provisions); Amanda Shanor, The New Lochner, 2016 Wis. L. Rev. 133, 145 (chronicling a corporate social movement to interpret the First Amendment in line with neoliberal, libertarian ideas).

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project. Neoliberalism’s resistance to social justice and its emphasis on deregulated markets, economic opportunity, and efficiency, coupled with managerialism’s tendency to create systems that emphasize efficiency and innovation over other values, contribute to a system that values fast, data-driven decision-making by machines.” Thus, it could be argued that algorithmic decision-making as a neoliberal product in the public and private sectors generated systemic problems concerning algorithmic legitimacy which means that central social values like fairness, equality, nondiscrimination, accountability, fundamental human rights, and the extent to which society cares about the vulnerable and marginalized are absent from this approach. It has to be taken into account that data protection regimes long predate the GDPR, but the GDPR has turned European style privacy protection into a global market norm and so the GDPR sets the tone by influencing the conceptual design of privacy laws around the globe.22 The EU–U.S. Privacy Shield (“Privacy Shield”) is a framework for transfers of personal data between the EU and the United States which the Commission has found to offer sufficient protection under EU data protection law.23 EU data protection law contains protections for persons in cases of automated decision-making. Article 22 of GDPR stipulates that a data subject shall have the right not to be subject to a decision based exclusively on automated processing, including profiling, which generates legal effects or similarly significantly affects people. On the other hand, this principle is subject to exceptions, especially if such decision is needed for entering into, or the performance of, a contract between the data subject and a data controller, or if the decision is based on the data subject’s unambiguous consent. In these cases, the data controller is obliged to apply appropriate safeguards to protect the data subject’s rights and freedoms and legitimate interests, at least the right to obtain human intervention on the part of the controller, the right to express his or her point of view and the right to contest the decision. Insofar as automated decision-making is concerned, the Commission assumes in recital 25 of its decision on the adequacy of the Privacy Shield (“the adequacy decision”) that in areas where corporations most likely resort to the automated processing of personal data to take decisions influencing the individual. As mentioned above, the same recital of the GDPR provides some examples of automated decision, including profiling, producing legal effects concerning an individual or

22

Chris Jay Hoofnagle et al., The European Union General Data Protection Regulation: What It Is and What It Means, 28 Info. & Comm. Tech. L. 65, 67 (2019) (“[T]he GDPR can be seen as a data governance framework. The GDPR encourages companies to think carefully about data and have a plan for the collection, use, and destruction of the data. The GDPR compliance process may cause some businesses to increase the use of data in their activities, especially if the companies are not dataintensive, but the GDPR causes them to realize the utility of data.”); Margot E. Kaminski, Binary Governance: Lessons from the GDPR’s Approach to Algorithmic Accountability, 92 S. Cal. L. Rev. 1529, 1552–53 (2019). 23 Article 29 Data Protection Working Party (28 November 2017) EU – U.S. Privacy Shield – First annual Joint Review, Brussels, https://ec.europa.eu/newsroom/just/document.cfm?doc_id¼48782.

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similarly significantly affects him or her, namely the “automatic refusal of an online credit application or e-recruiting practices without any human intervention.” Article 29 (WP2924) provides further guidance as to the interpretation of automated individual decision-making and profiling. Automated individual decisionmaking is explained by WP29 as: “the ability to make decisions by technological means without human involvement (. . .) based on any type of data, for example:— data provided directly by the individuals concerned (such as responses to a questionnaire);—data observed about the individuals (such as location data collected via an application);—derived or inferred data such as a profile of the individual that has already been created (e.g. a credit score).” Taking into account that access to financial services such as banking and lending are an imperative means of stimulating social and economic well-being, data that AI-based credit scoring systems collect and analyze is so overwhelming as to be concerning which means that AI-generated credit scores have noteworthy applications in emerging markets, where almost everyone is a “thin-file” borrower. Hence, AI-generated scores may extend existing forms of discrimination via “network discrimination,” whereby persons are penalized based on the features of others who are in their personal network.25 To that extent, the use of AI in financial decision-making may even burden persons’ freedom of opinion, expression, and association by discouraging persons from engaging in activities that they believe will negatively alter their credit score. In the European Union, Article 22 GDPR prohibits fully automated decisions but it establishes numerous exceptions in Article 22(2) GDPR covering decisions “based solely on automated processing” of data (Article 22(1) GDPR). Meanwhile most algorithmically made decisions still implicate a human being, the majority of ADM procedures is not covered by the prohibition of Article 22 GDPR.26 Furthermore, WP29 further clarifies that Article 22 GDPR only covers ADM that has serious impactful effects on data subjects (“legal or similarly significant effects”) and so a legal effect demands that someone’s legal rights are influenced which means that a person’s legal status or rights under a contract are affected. Algorithmic decision-making is pervasive and so there is overwhelming evidence that AI algorithms can reach seemingly collusive outcomes. Algorithms have become the basis of recommendation systems, raising matters such as the possible channelling of consumers’ decisions toward second-best options. Moreover, algorithms are used to delegate and abridge individual decision-making processes and so

24 Article 29 Guidelines on Automated individual decision-making and Profiling for the purposes of Regulation 2016/679, https://www.autoriteitpersoonsgegevens.nl/sites/default/files/atoms/files/ guidelines_on_profiling_w p251rev01_enpdf.pdf. 25 Mikella Hurley and Julius Adebayo, “Credit Scoring in the Era of Big Data,” Yale Journal of Law & Technology 18, no. 1 (2016): 148–216. 26 Wachter/Mittelstadt/Floridi, Why a Right to Explanation of Automated Decision-Making Does Not Exist in the General Data Protection Regulation, (2017) 7(2) International Data Privacy Law 76, at p, 92. http://www.europarl.europa.eu/sides/getDoc.do?pubRef¼-%2F%2FEP%2F% 2FTEXT%2BREPORT%2BA7-2013-0402%2B0%2BDOC%2BXML%2BV0%2F%2FEN& language¼EN.

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fears revolve not only around the complexity of algorithms but also even simple algorithms used as simple delegation and commitment devices may damage consumers.27 In fact, existing regulation is very unclear about how to treat algorithmic collusion because of both the lack of jurisprudence and the conceptual issues about the attribution of responsibilities when decisions are delegated to algorithms. Once a machine or a robot behaves in a manner that it acts more like a human or it is difficult to identify whether it is a machine or human, data protection implies that policies and procedures decrease breach into the privacy of an individual instigated by collection and usage of their personal data with their consent. AI and machine learning features affect the processing of personal data to be carried out in different ways and for different purposes than those for which it was originally set resulting in the complete loss of control, by the data subjects, of their data. Thus, any such loss of control is against the principles of GDPR. AI systems permit to transform anonymous information into personal data, embracing special categories of personal data. AI providers have to permit audit and controls on their AI systems, when such audits and controls are needed by GDPR provisions. Moreover, security has become crucial from an antivirus solution to using AI for data protection from cybercriminals and so the merits of AI is that end-point security is taken to the next level as AI swiftly detect, block and analyze attacks and perform behavioral exercises. It is characteristic that some recent applications of AI, such as the use of AI to defeat CAPTCHA and Google’s AlphaGo Zeros that taught itself to play Go at the championship level, have appeared with minimal training data, signifying that AI not always be linked to big data.28 It is worth noting that algorithmic decision-making threatens human rights, such as the right to non-discrimination and so data protection law defend people against discrimination which means that apt enforcement of nondiscrimination law and data protection law protect people. Algorithmic decision-making refers to the process by which an algorithm produces an output but sometimes an algorithm decides in a fully automated fashion. For instance, a spam filter filters out, automatically, spam messages from one’s email account. Occasionally, decisions are partly automated and so humans make decisions assisted by algorithms, which is the case of a bank employee deciding whether a customer can borrow money from the bank, after an algorithmic system evaluated the customer’s creditworthiness. Moreover, algorithmic decisions are discriminatory when the system learned from discriminatory human decisions29 and so if an algorithmic system is trained on biased data, the system risks reproducing that bias. It could be said that Google’s algorithmic system 27

F. Decarolis and G. Rovigatti. From Mad Men to Maths Men: Concentration and Buyer Power in Online Advertising. working paper, 2018. E. Calvano, G. Calzolari, V. Denicolo, and S. Pastorello. Artificial Intelligence, Algorithmic Pricing and Collusion. SSRN Electronic Journal, 2019b. www. ssrn.3304991. 28 Greenberg, A., “An AI That Reads Privacy Policies So That You Don’t Have To,” Wired (9 Feb. 2018), https://www.wired.com/story/polisis-ai-reads-privacy-policies-so-you-dont-have-to/. 29 S Barocas and AD Selbst, ‘Big data’s disparate impact’ (2016) 104 Calif Law Rev 671. Equivant, COMPAS Classification, 2018, http://www.equivant.com/solutions/inmateclassification.

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simply reflected society. However, even if the fault lies with society rather than with the algorithmic system, those image search results affect people’s beliefs.30 While decisions by algorithms can have discriminatory effects, algorithms are not essentially bad or discriminatory. Anyway, it seems that algorithms perform better than human decision-makers. Many humans discriminate and sometimes algorithmic systems discriminate for the reason that they reproduce discrimination by humans. Hereafter, it makes a difference whether one compares algorithmic decision-making with human decisions in the real world, which are sometimes discriminatory, or with hypothetical decisions in an ideal world without discrimination. Certainly, the idea is to have a world without any unfair or illegal discrimination. Furthermore, algorithmic decision-making can also be used to fight discrimination. Thus, an algorithmic system could assist to discover existing discrimination that would otherwise have remained hidden. Even within the European Union, nondiscrimination law is partly harmonized. Case law shows that the European Convention on Human Rights prohibits both direct31 and indirect discriminations.32 It could be said that algorithmic decision-making breaches the exclusion of indirect discrimination if an algorithmic system rejects job application letters from a disproportionate number of people with a certain ethnicity. Although the European Convention on Human Rights has some horizontal effect, the Convention does not directly regulate discrimination in the private sector.33 As discussed earlier, data protection law defends fairness and human rights when administrations use personal data by granting rights to people whose data are being used, and imposing obligations on administrations that use personal data.34 Moreover, Data protection law is used to alleviate information asymmetry and to mitigate

30 M. Ali and others, ‘Discrimination through optimization: How Facebook’s ad delivery can lead to skewed outcomes’ (2019) https://arxiv.org/abs/1904.02095. 31 Direct discrimination is defined as follows in Article 2(2)(a) of the Racial Equality Directive 2000/43/EC: ‘Direct discrimination shall be taken to occur where one person is treated less favourably than another is, has been or would be treated in a comparable situation on grounds of racial or ethnic origin.’ the Employment Equality Directive (2000/78/EC), the Gender Goods and Services Directive (2004/113/EC), and the Recast Gender Equality Directive (2006/54/EC) use similar definitions. 32 Tobler C, Indirect discrimination: a case study into the development of the legal concept of indirect discrimination under EC law, vol 10 (Intersentia 2005). 33 ECtHR, Biao v. Denmark (Grand Chamber), No. 38590/10, 24 May 2016, par. 89. 34 G. González Fuster, The Emergence of Personal Data Protection as a Fundamental Right of the EU (Springer 2014), p. 164–166. Article 5, 7, and 10 COE Data Protection Convention 2018. Article 1(2) and recital 71, 75, and 85 GDPR, and article 1 of the Convention for the protection of individuals with regard to the processing of personal data, Amending protocol to the Convention for the Protection of Individuals with Regard to the Processing of Personal Data, adopted by the Committee of Ministers at its 128th Session in Elsinore on 18 May 2018, https://rm.coe.int/ convention-108-conventionfor-the-protection-of-individuals-with-regar/16808b36f1; S. Wachter and B. Mittelstadt, ‘A Right to Reasonable Inferences: Re-Thinking Data Protection Law in the Age of Big Data and AI’, https://ssrn.com/abstract¼3248829.

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risks of unfair and illegal discrimination. In fact, data protection law entails that administrations are open and transparent about their use of personal data which means that administrations must deliver information about all stages of algorithmic decision-making implicating personal data.35 Is there a need to invent or develop new human rights in the AI era? On the one hand, it could be said that there is no need to invent or develop on the basis of current human rights new human rights in the time of AI. In other words, as long as AI is used by humans there is no need for new human rights. On the other hand, in the era of AAI where everything will be algorithmic due to human’s agreement and acceptance, it is obvious that new human rights will emerge for the reason that even humans will have another mentality artificially inclined demanding new AAI Rights. Do conventional human rights apply to AI entities and Robots? It is characteristic that the German Datenethikkommission36 argues for a right of digital autonomy, which implies a demand for further AAI rights fitting to the nature of AAI society. Furthermore, algorithmic decision-making strengthens social inequality. To that extent, nondiscrimination law has little to say about algorithmic predictions that are incorrect which means that a problem with algorithmic decisions is that they are often incorrect for a specific individual. Algorithmic decision-making is used in many different areas, for many different purposes, algorithmic decision-making does not threaten human rights. Thus, an algorithmic system of a chess computer brings different risks than an algorithmic system for credit rating or predictive policing. Even for algorithmic systems that make decisions about humans, the risks are different in different areas, and different rules should apply.37 It is worth noting that the fairness of algorithmic decisions cannot be assessed in the abstract and so based on the sector, or application area, various arguments have different weights, and different normative and legal principles apply. Thus, in the field of criminal law, the right to a fair trial and the presumption of innocence are vital but in consumer transactions, freedom of contract is an imperative principle which means that new rules should concentrate on specific sectors. In the public sector, algorithms are used for predictive policing or sentencing recommendations, and for decisions about pensions, housing assistance, or unemployment benefits. In the private sector too, algorithmic decisions affect people when decisions concern employment, housing, or credit. Even decisions that each has only

P. Hacker, ‘Teaching fairness to artificial intelligence: Existing and novel strategies against algorithmic discrimination under EU law’ (2018) 55 Common Market Law Review, Issue 4, pp. 1143–1185. 36 Gutachten der Datenethikkommission, 2019, https://www.bmjv.de/SharedDocs/Downloads/DE/ Themen/Fokusthemen/Gutachten_DEK_DE.pdf?__blob¼publicationFile&v¼5. 37 A. Rieke, M. Bogen and D.G. Robinson, ‘Public Scrutiny of Automated Decisions: Early Lessons and Emerging Methods, Upturn and Omidyar Network’ (2018) http://www.omidyar.com/sites/ default/files/file_archive/Public%20Scrutiny%20of%2Automated%20Decisions.pdf; B. Bodo et al., ‘Tackling the algorithmic control crisis-the technical, legal, and ethical challenges of research into algorithmic agents’ (2017) 19 Yale JL & Tech. 133. 35

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small effects, could have major effects together and so price differentiation could become a problem if certain groups in society structurally pay more for goods and services. It is worth noting here that nondiscrimination law and data protection law are the most relevant legal instruments to fight illegal discrimination by algorithmic systems and so if effectively enforced, both legal instruments can help to protect people. Moreover, many nondiscrimination statutes only apply to discrimination on the basis of certain protected grounds, such as ethnic origin not applying if administrations discern on the basis of newly invented classes that do not link with protected grounds which means that such differentiation still is unfair when it reinforces social inequality.38 Kazim and Koshiyama39 argue that “Just like we did not, and could not, adopt one statute to regulate the industrial revolution, we cannot adopt one statute to regulate algorithmic decision-making. To mitigate problems caused by the industrial revolution, we needed different laws for work safety, consumer protection, the environment, etc. In different sectors, the risks are different, and different norms and values are at stake. Therefore, new rules for algorithmic decision-making should be sector-specific.” Furthermore, it has to be taken into account that when algorithms make decisions, opaque human behavior is replaced by a set of rules constructed from data. An algorithm takes as an input a training data set with past defaults and then outputs a function that links consumer characteristics, such as their income and credit score, to the likelihood of default. Moreover, statistics and computer science have formed powerful algorithms that excel at this prediction task, especially when individual features are rich and data sets are large and so these machine-learning algorithms search through large classes of complex rules to find a rule that works well at predicting the default of new consumers using past data. It has to be taken into consideration that while algorithmic decision-making permits for pricing to become traceable, the complexity and opacity of modern machine-learning algorithms constrain the applicability of the existing legal antidiscrimination doctrine. It is worth noting that the complexity of machine-learning pricing limits the capability to scrutinize the process that led to a pricing rule, frustrating legal efforts to examine the conduct that led to disparity.40 Gillis and Spiess41 argue that “legal doctrine is ill prepared to face the challenges posed by algorithmic decision-making in a big data world. While automated pricing rules promise increased transparency, this opportunity is often confounded. Unlike human decision-making, the exclusion Zuiderveen Borgesius, Frederik J. “Strengthening legal protection against discrimination by algorithms and artificial intelligence.” The International Journal of Human Rights (2020): 1–22. https://doi.org/10.1080/13642987.2020.1743976. 39 Emre Kazim, Adriano Koshiyama, Lack of Vision A Comment on the EU’s White Paper on Artificial Intelligence, https://ssrn.com/abstract¼3558279 p29. 40 42 USC § 3601 et seq. 4 42 USC § 3605(a). These laws do not exhaust the legal framework governing discrimination in credit pricing. 41 Talia B. Gillis & Jann L. Spiess, Big Data and Discrimination, 2019 The University of Chicago Law Review 459 p17. 38

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of data from consideration can be guaranteed in the algorithmic context. However, forbidding inputs alone does not assure equal pricing and can even increase pricing disparities between protected groups.”

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AI and Risks

AI already offers several building blocks that make possible the digitalization of a business’s risk function embracing data management; process and workflow automation; advanced analytics and decision automation; and smart visualizations. Everexpanding commercial versions of Al technologies are available in multiple forms online from accounting companies, management consultants, legal compliance and risk management consultants, and governance and entity management consultants, etc., depending or drawing from process automation and best assist the function of risk management rather than risk governance. AI enabled advanced analytics clarify the development of digital risk technology into cognitive insight making possible more accurate and in-depth analytics than were previously possible. Hence, decision automation, assisted by smart visualizations and the use of amplified reality in the performance of a company’s risk function, are still developing technologies. AI enables the faster capture and use of vast amounts of structured and unstructured data such as emails, texts, social media posts, clickstreams, chat transcripts, and so AI algorithms allow linkage analysis, pattern recognition, and NLP, which in turn makes possible more timely and accurate profiling of customer attributes and risks supported by a wide variety and greater quality of data available so that a company’s risk function need no longer rely on traditional risk data nor, in the case of financial service companies, burden customers with requests to supply data that can be captured by other means.42 AI automated risk management has the prospective to expand the functionality of risk and risk-related executives, boards, and board risk committees and so for risk management, AI automates away routine risk functions by diminishing the number of manually handled exceptions and the risk executives focus on strategic and highvalue decisions using AI-driven advanced analytics by engendering insights such as more complex correlations and trend analyses than were previously available and in turn to optimize risk and other management decisions. Moreover, risk reports and strategic advice on risk-oriented business decisions will be engendered automatically and/or be sent on demand to the board of directors, for risk oversight and review. It has to be taken into account that strategic advice takes the form of risk predictions and suggested optimal actions, which the board or board risk committee can employ

Deepak Amirtha Raj, ‘Spotlight on the Remarkable Potential of AI in KYC’ (13 June 2017) . 42

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as a decision-making point of reference, a valuable cognitive insight which means that risk reports and advice are no longer static but boards must have an understanding of the company’s digital risk frameworks. Boards are presented with intuitive visuals offering summary information with fitting levels of detail concerning the market, portfolios, and products and so in place of focusing on the oversight of risks ex post facto it will increasingly be possible to manage risk more strategically, by profiling emerging risks ex ante using AI’s precise, preventative control mechanisms and reporting features. The question to be answered is how AI facilitates and reports on legal compliance to corporation boards? AI legal compliance techniques have been used by financial service corporations in areas such as credit card fraud and analyzing data sets to detect Anti-Money Laundering (AML) focusing on automating costly manual work, leaving strategic decisions to human beings or rules-based systems. It seems that AI is effective for the reason that fraud and money laundering detection typically encompass large numbers of documents and repetitive processes that suit process automation. It has to be taken into consideration that digital technologies will become more financially justified.43 Al will generate written reports or notifications to a regulator concerning cash deposits needed by money laundering laws and so Al comparisons and stress testing will be fitted to banking regulation requirements in different jurisdictions. Finally, AI will establish and automate a system of internal notifications of legal alterations throughout a corporation aiding the need to integrate content from thousands of regulatory publications each month. In fact, data integrity is the biggest challenge for AI-based legal compliance solutions because advanced analytics through AI based on data quality and reliability. In other words, AI needs proper data governance procedures and the validation or assurance processes concerning internal audits when converting documents into structured formats, while preserving the information they contain, feed into corporations’ compliance and control activities. To that extent, boards receive reports on these matters as part of their digital pack that is the primary functionality of board portals. Nonetheless, in large corporations, board criticism is not so much about the accuracy and precision of compliance data but rather, its relevance. Finally, the fundamentals of good governance practice remain significant irrespective of the benefits that more reliable information brings. It could be said that the wellfunctioning of AI-driven legal compliance systems and other applications of AI depends on the quality of the data available for analytics. Hence, Al legal tools extract relevant data from unstructured data sets like legal documents and so aiding

43 Chartis Research, Demystifying AI for Risk and Compliance (2018) 2 . Global Financial Innovation Network (GFIN), Consultation document (August 2018) 4 https://www.fca.org.uk/ publication/consultation/gfin-consultation-document.pdf.

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legal research by quickly going through mountains of legal precedent to come up with relevant authority.44 It is clear that the prospect of AI business systems has not yet reached maturity and that many benefits will only follow with technological advancement. Thus, cognitive computing systems in future will become a super reporter of information and so if the system is integrated with other information sources in the firm it has the capacity to become a deep pool of information accessed by the board to support in decision-making which means that cognitive computing systems not only have the competence to access large amounts of data but also to analyze it and to come up with answers. It is possible that a future board could rely on an intelligent system for information about the activities of the business rather than on the report of the executive enabling directors to get more detailed information if required. Technological advances in AI bring real benefits to corporate governance but governance will not be business as usual and so the challenges that AI systems will portray in the boardroom are similar to that presented by technology in general. The nature of the technology and its current limitations brings forward the Opaqueness of decision process because AI systems using machine learning use the presence or absence of a pre-acquired set of reference points to decide whether an outcome is probable or not. While the reference points will be known to human actors if the system was built via supervised learning, these reference points are not known when the systems train through unsupervised learning and so in supervised machine learning a set of training data with a labelled output is employed to train the system. Moreover, in unsupervised machine learning, the data analyzed is not labelled and the outcome is not known. Instead, the system acquires patterns in the data over millions of iterations to predict outcomes and so the system has a defined objective and each time it moves closer to that objective acknowledgment is fed back into the system to indicate that progress has been made which means that the system trains itself through trial and error until it has created the needed patterns becoming smarter over time. Current governance theory holds that each director exercises independent judgment and cannot blindly rely on experts in the exercise of his or her duties as a director and so extending reliance on expert systems built on AI technology. On the other hand, directors may be reluctant to count on AI predictions or conclusions, leading to under-reliance with the attendant loss in opportunity. Moreover, there is a very real risk that directors45 may reach a point where they over rely on the system

44 Jen Clarke, ‘Spotlight on “LawTech”: How Machine Learning is Disrupting the Legal Sector’, IBM Blogs (online), 11 December 2017, < https://www.ibm.com/blogs/internet-of-things/iotspotlight-on-lawtech/>. Paul Lippe, Daniel Martin Katz and Dan Jackson, ‘Legal by Design: A New Paradigm for Handling Complexity in Banking Regulation and Elsewhere in Law’ (2015) 93 Oregon Law Review 833, 849–850. Rage-AI, ; eBrevia, ; Seal, ; Kira, . 45 In ASIC v Healey (2011) 278 ALR 618 (the “Centro case”) the Federal Court found the directors of the Centro Group personally liable for errors in the financial statements of the Group for the

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for the reason that it is impossible to show that the system is incorrect in its finding and so this risk will be augmented when the intellectual capability of the AI system equals and then surpasses that of the human players. Can Al function without human made software? Presently Al function according to their human made software nut in the future if Al can generate their own software not human made but machine made then the world will take a turn towards a mechanically uncontrolled way which will not be able to see the progress or a possible crash due to machine malfunction. In addition to the risk of over or under-reliance, a further risk is that dependency on AI may lead to an overall decline in skill and expertise in governance as more of the affairs are left to AI to accomplish.46 Over dependency is a risk attached to the use of all forms of technology, not just AI, but it is intensified in this case in that AI makes decisions on behalf of human players leading to the position to defer to the decision of AI as a rule. The advances in technology have the most immediate influence on the duty of directors to act with care and diligence and so the availability of improved information about the firm and the boosted reliability of checks in the form of internal audit infer that the duty of care and diligence will be advanced. Basically, the association of these information sources and the skills that the directors bring to the boardroom leads to an augmented standard of care. All at once, particularly when AI capability comes into its own, there is a reliance on the support of the technology to the exclusion of independent judgment and so bringing forward the applicability of the business judgment rule. Gradually, the formation of information and advice will become autonomous from human actors, which means that the content of the reasonable reliance provision becomes without cause restrictive and in need of amendment. It is worth noting that increased use of automated processes and the potential improvements brings forward the need for more reliable internal auditing, better risk flagging and speedier, and direct access to information about organizational conduct brings with it a challenge to the board/management relationship. Thus, the wellentrenched informational divide between the management and the board become muddled as directors and board committees become able to directly access information that they need about certain managerial actions and processes and so introducing the risk, and fear from management, that the board may assume functions normally left to management instead of focusing on the strategic and supervisory role left to

financial year ended 30 June 2007. The court found that the directors failed to discharge their duties with the degree of care and diligence that a reasonable person would in the circumstances; and failed to take all reasonable steps to comply with, or to secure compliance with, the financial reporting provisions in the Corporations Act 2001. 46 Sean Martin, AI Warning: Robots will be Smarter than Humans by 2045, Google Boss Says’, 17 October 2017, Express (online), https://www.express.co.uk/news/science/867565/googleartificial-intelligence-ray-kurzweil-AI-singularity.

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the board. Finally, the time and remuneration constraints attached to board appointments will keep interference in management in check.47 As mentioned earlier, a key obstacle to AI advances is the fact that data in companies has not kept pace with the development of AI, machine learning, or even automation. On the other hand, the technology already exists to form and store full transcripts of proceedings with minimal interruption or effort and so becoming increasingly difficult for directors to explain the absence of such data when it may be useful for the improvement of the governance of the firm. The digitization of board proceedings does hold confidentiality implications being true if the data is stored on the cloud or if the AI analysis is done via offthe-shelf products with the customization done with the assistance of proprietors who also serve competitors or who have conflicting interests with that of the firm.48 Furthermore, dependency on the cloud has effects across whole business areas if it should fail, which holds some risk of its own. In the last decade, significant development was done in the field of soft computing methods in general and they have been successfully applied to a wide range of problems including electrostatics. In fact, electrostatics is divided into two fields: industrial and atmospheric electrostatics and so demand of utilizing the most advanced computation methods and novel risk management methodologies emerged offering a consisting framework for electrostatic hazard handling. The significance of artificial intelligence in electrostatics is focused on the demand to deal with multidimensional nonlinear problems which means that the advantage of AI tools is that every problem is abstracted to rules, or much simpler mathematical expressions.49

47 Sarah Danckert and Clancy Yeates, ‘CBA Accused of Board Minutes Criminal Breach’ The Sydney Morning Herald (21 November 2018). 48 Maziar Peihani, ‘Financial Regulation and Disruptive Technologies: The Case of Cloud Computing in Singapore’ (2017) Singapore Journal of Legal Studies 77 Ellie Chapple and Elisabeth Sinnewe, ‘So What’s a Secretary to Do? Banking Royal Commission Raises Questions About What’s in Minutes’ The Conversation (29 November 2018) (online) http://theconversation.com/sowhats-a-secretary-to-do-banking-royal-commission-raises-questions-aboutwhats-in-minutes107509: ‘Company secretaries are already acutely aware that every set of minutes of every board meeting might one day end up as evidence.’ Australian Securities and Investments Commission v Hellicar (2012) 286 ALR 501 (the resolution adopting a misleading ASX announcement in the minutes of a board meeting was held to have been a ‘contemporaneous record of proceedings at the meeting). 49 Attila Gulyás, István Kiss, István Berta, Artificial intelligence in electrostatic risk management Journal of Electrostatics 71 (2013) 387–391.

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Transforming Governance

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Transforming Governance

The rise of digital technologies and social media is not only forcing corporations to reassess existing business models but also how they organize themselves and structure corporation governance. It could be said that existing regulatory approaches are failing business organizations and many corporate governance rules and regulations are programing institutions to be dysfunctional. Hence, there is an ever-widening gap or disconnect between regulatory strategies and the business wants of corporations operating in fast-moving, technology-driven markets. Accordingly, many businesses and other organizations are ill equipped to meet the encounters of today’s digital world which means that there is a need to design regulations that incentivize corporations to set up the organizational structures and practices that will permit them to thrive. It could be said that new corporate governance concentrated on supporting a company’s aptitude to innovate which means promoting compliance and risk management.50 It is worth noting that digital technologies are now turning the world upside down and so an ongoing series of technological developments have transformed economic and social life. In fact, the following are consequences of digitization and so there is shrinking of size, increased power, and diverse applications of personal computers, the global reach of communication networks, and the new forms of social interaction and economic exchange that these networks have made possible. Moreover, the availability of cloud databases containing enormous quantities of information that can be processed by software algorithms for use across multiple social and economic settings. In reality, the scale and impact of technological alterations align a “digital transformation” by vanishing industry boundaries are and so new platform firms have appeared, which function across multiple industries such as retail, transport, finance, healthcare, food, etc., by exploiting global communication networks to deliver new business models and disrupt incumbents. To that extent, social media authorizes everyone and has transformed the meaning of communication and mass media.51 In addition, digital technologies have altered consumer behavior and so consumers do not appreciate mass production anymore, and brand loyalty is progressively fragile which means that digital technologies have made consumers way more well-informed and sophisticated. Thus, customers continue to buy if “products” offer them a meaningful and personalized experience. Furthermore, digital technologies are empowering investors in the ecosystems of the future and so Al Mark Fenwick and Erik P. M. Vermeulen ‘The Digital Future of Corporate Governance’ International Corporate Governance Network Yearbook 2018, p. 11; Mark Fenwick and Erik P. M. Vermeulen, ‘Technology & Corporate Governance’ 48(1) The Texas Journal of Business Law, 1 (2019); Mark Fenwick and Erik P. M. Vermeulen, ‘The Unmediated and TechnologyDriven Corporate Governance of Today’s Winning Companies’ New York University Journal of Law and Business (2020). Mark Fenwick & Erik P. M. Vermeulen, ‘Technology & Corporate Governance’ (2018) https://papers.ssrn.com/sol3/papers.cfm?abstract_id¼3263222. 51 Kevin Kelly Alec Ross, Understanding the 12 Technological Forces that Will Shape Our Future (Penguin 2017). 50

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tools that analyze website traffic and social media engagement tender institutional and other professional investors a better understanding of a firm’s growth, opportunities, and prospects. Blockchain technology diminishes the cost for firms to access capital markets, offering more investment opportunities, and global liquidity to investors. To that extent, smart contracts, computer program code, or protocol automating the verification, execution, and enforcement of precise terms and conditions, makes certain the needed compliance and security. In other words, a twenty-first-century firm needs to cultivate and uphold one or more active and healthy ecosystems to engage with all stakeholders so as to stay competitive demanding all firms to keep pace with the latest technological trends. Unquestionably, digital technology plays a substantial role in gathering feedback from stakeholders and so the fastest technique to get instantaneous and consequential input is to inspire an open dialogue with stakeholders, using different digital and social media platforms. Thus, corporations themselves have to intervene and take a much more proactive role in generating such an environment in which all stakeholders feel valued. In line, Philips has shifted its annual report into an interactive content experience for the firm’s broader stakeholder community, exploiting numerous strategies and online platforms. Microsoft has appointed a “Storyteller” to help stakeholders and society understand who they are, what they do, and why they exist helping Microsoft rediscovering its “soul.” Moreover, Jeff Bezos’ yearly letter to the shareholders; “Millennial” representation on the board of Starbucks; the appointment of a social media influencer on the board of AirAsia to make the board more susceptible to the new generation stakeholders; and the use of Twitter as a business/communication tool by Anand Mahindra, executive chairman of Mahindra and Mahindra are instruments utilized by managers as governance tools. It is worth mentioning here that the rise of digital technology is transforming the world of corporate governance then again there is no “one-size-fits-all” tactic and so Al, blockchain technology, and social media generate inimitable ecosystems with various groups of stakeholders which means that the way of utilizing these technologies wisely is one of the key matters facing both corporations and policymakers today. Fenwick and Vermeulen52 argue that “In a networked age, all businesses need to ‘go digital.’ Companies need to become innovation machines, and this means that every firm needs to become a ‘tech’ company and a ‘media’ company. If they do not, younger and more agile competitors better attuned to the realities of the new digital world will replace them. For incumbents, the risks are existential. Established firms must adapt to the new digital environment by embracing the ecosystem model, or they will die.” It is worth noting that firstly, a corporation is a creature of the law—it is formed by an act of incorporation—and, as such, the company exists separately from its owner-shareholders, directors, executives, managers, and employees which means

Mark Fenwick Erik P.M. Vermeulen, The End of the Corporation, Working Paper N○ 482/2019 November 2019, ECGI Working Paper Series in Law P 3. 52

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that as an independent entity, a company can issue tradeable shares to investors, limit shareholder liability, and conduct business in its own name. Secondly, a corporation is organized as a closed, hierarchical institution with a clear chain of authority flowing “downwards” from the owner-shareholders to the employees and so a company uses authority-based management structures and is not governed by consensus. Finally, corporations traditionally adopt a “linear” business model whereby the company gathers together several “inputs” such as raw materials, components, or knowledge/information, which are then combined, consequently adding value, before being sold as either a standardized product or service to a “customer.” Does a company as an entity needing to function with its conventional characteristics is abolished or merely the way of governing has changed? We have moved from the company to the e-company but the goods continue to be material or electronic and not everything has become virtual which means that a modern e-corporation is defined as a business organization characterized by a combination of three features such as being a creature of the law, organized as a hierarchical institution, and gathers “inputs” adding value before being sold as either a standardized product or service to a “customer.”

6.7

AI and Governance

As discussed earlier, digitization is a building block toward artificial intelligence for the reason that it accelerates the availability of the “Big Data” on which machine learning is based which means that governments have to rely on algorithmic tools, that is, human-created statistical models, indices, or scoring systems that are then used as decision tools. Moreover, traditional algorithmic or statistical tools rely on humans to pick the explicit variables to be encompassed in a decision aid and the precise mathematical relationships between those variables. Hence, learning algorithms work “on their own” to process data and discover optimal mathematical links between them which means that this self-directed self-discovery is what gives machine-learning algorithms not only their name but also their superior functioning in terms of accuracy over conventional algorithmic tools. It has to be taken into account that even with machine learning, humans stipulate the objective that the learning predicts or optimizes, and humans undertake a number of steps to “train” the algorithm and improve its operation. Moreover, these learning algorithms are different from conventional statistical tools for the reason that the exact manners that data are merged and analyzed are neither decided in advance by a human analyst nor easily explainable after the fact which means that the machine-learning algorithms are often described as “black-box” algorithms since they do not present a way of portraying how they work but merely they can be exact in achieving the objectives they have been invented to achieve. AI adoption is often equated with automation, whereby humans are replaced by machines in jobs and decisions but AI is used to boost human activity such as

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consider partially self-driving cars with human override, suggested scripts for customer service, and scoring for risk or priority in hiring, audits, judicial sentencing and fraud detection. Moreover, decisions often implicate considerations that are difficult to digitize or where prior knowledge is central for predicting results in innovative or rare conditions and so these are fields where the automated predictions of fully automated AI are inadequate, even when AI diminishes the cost of prediction.53 The advantages of high-powered incentives against the risk they impose on riskaverse agents are weighed; AI is not, or at least can be programed not to be, risk averse. Moreover, they do not have noteworthy “effort” costs beyond the fixed costs linked with developing them and so they are easier to control and act in the interests of a principal. On the other hand, there remains the challenge of offering an AI with the “correct” objective function, which entails defining and digitizing principal objectives.54 Conversely, human decision-making is more precise than AI picks in some conditions, particularly when there are deficiencies in the data available to train and run an AI. It could be said that if a high-performing AI is available then the AI should hold decision rights and AI training concentrates on ultimately fully replacing people. On the other hand, if existing AI performance is comparatively weak, human agents adequately well aligned with the principal and human effort only weakly responsive to alterations in AI performance, then people keep decision rights and marginal enhancements in AI functioning or shrinkages in AI bias are profit-enhancing. Moreover, if AI functioning is relatively weak and people adequately well-aligned with the principal, but human effort strongly responds to alterations in AI execution, then people keep decision rights. In line, when the AI’s pick “antagonizes” people, they intensify effort to evade the AI’s recommendation being reported to the principal. Who will be accountable for decisions that are no longer made by humans? There is the potentially enormous scale of Al technology’s effects in the social and natural world and so an AI system should only be utilized after assessing its rationale and purposes, it is reviewed by many eyes to detect potential flaws. Accountability measures are crucial guarantors of AI safety, embracing verifiability, and the necessity to monitor the use of AI systems after their deployment. Moreover, people and organizations behind AI technology have a crucial role in confirming it is created and used in manners that are safe and secure. Hence, safety is wanted to make certain controllability by people which means that safety measures during development entail that AI systems are “built and tested to prevent possible misuse.” It has to be taken into account that developers of AI systems cannot always correctly predict the risks linked with such systems ex ante. There are also safety

53

Ajay Agrawal, Joshua Gans, and Avi Goldfarb. Exploring the impact of artificial intelligence: Prediction versus judgment. Information Economics and Policy, 46:1–6, 2019. 54 Dylan Hadfield-Menell and Gillian K. Hadfield. Incomplete contracting and ai alignment. Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 2019.

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risks connected with AI systems being applied in manners that their creators did not foresee. Privacy, Accountability, Safety and Security, Transparency and Explainability, Fairness and Non-discrimination, Human Control of Technology, Professional Responsibility, and Promotion of Human Values have emerged as the introductory conditions for AI in order to be considered as ethical and respectful of human rights.55 Thus, it seems that the principles appeared and applied to all technologies in order to be accepted and legalized in a society must be applied to Al technology as well. In reality, society is undergoing a digital revolution transforming the global society as we know it and so all economic and social progress and prosperity caused by technological revolution brings along disruption and friction. Hence, new digital technologies such as AI enable many new services that noticeably disrupt existing business models which mean that these new business models, consecutively pose new privacy issues and ethical dilemmas, and social resistance to the excesses of the new data economy is becoming evident and urgent. In other words, it is an encounter for established firms to both drastically innovate so as to stay future-proof and, at the same time, take social responsibility. Does the current corporate governance regulation need adjustment? it could be said that the present corporate governance regulation entails an adjustment in order to be able to direct these times of alteration because corporate governance is now exceeding the boundaries of the roles and interactions between the conventional decision-making bodies of the corporation such as board of directors and general meeting of shareholders and is gradually spilling over into compliance, risk management, and responsible entrepreneurship.56 Governance, risk management, and compliance (GRC) are critical functions within corporations. Advances in AI and its increasing application in more spheres of life necessitate attention to the effect of algorithms on human well-being. AI governance must contend with a fundamental conceptual challenge: algorithmic applications enable apparently technical decisions to de facto regulate human behavior, with a greater prospective for physical and social effect than ever before. Moreover, the existing trajectory of AI development, which is controlled by large private companies, prognosticates an era of private governance that is deep-rooted in governance of data, a fundamental AI input, rather than simply contending with outputs or trying to manage the negative effects of AI outputs. There is a need of making certain that public values are embraced by AI and so should avoid any risk of losing the democratic accountability that is at the center of public law.

55 Jessica Fjeld, Nele Achten, Hannah Hilligoss, Adam Christopher Nagy, Madhulika Srikumar Principled Artificial Intelligence: Mapping Consensus in Ethical and Rights-based Approaches to Principles for AI Research Publication No. 2020-1 January 15, 2020 https://ssrn.com/ abstract¼3518482. 56 R. Feracone, ‘Good Governance, Do Boards Need Cyber Security Experts?’, Forbes 9 July 2019, www.forbes.com/sites/robinferracone/2019/07/09/goodgovernance-do-boards-need-cyber-secu rity-experts/#e9ded6618592.

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In short, technical decisions about algorithms are not only mediating public safety, but also encoding values, without any uniform oversight, normative obligations, or public accountability. Since AI technologies are embedded in more and more applications, given the leading role of the private sector in AI development and deployment, evaluating AI in strategic context uncovers the degree to which global society gradually live in an age of private governance.57 There is a broad consensus that the digital revolution encompasses a paradigm shift, whereby the principles of and belief in the existing logical order transfer to a new series of principles and beliefs in a deeply altered logical system. Are there any hold-ups in current corporate governance? There are hold-ups in present corporate governance in order to deal with the new digital reality in boards introducing alterations of management being a great undertaking. It has to be taken into account that even without a digital transformation, there is a dominant discourse in boards, whereby the functioning of the corporation is judged mainly from a financial and control lens, not counting on culture-related issues in boards because of a lack of conceptual understanding and language which means that this absence of conceptual understanding and language apply a fortiori to the argument for a sweeping digital transformation.58 Does regulation directly target the development and use of AI in a “trustworthy” manner? Regulators across the globe have put AI on top of their strategic plans, set on reaping its profits for their economies and societies, and activating a global competition for the AI along the way. So far, the noteworthy risks brought forth thereby render it embryonic, not only for the sake of harm minimization but also for AI’s acceptance by society, that suitable measures are put in place to make certain it is planned, developed, and used in a reliable way. In line, the embracing of a strict rule that imposes burdensome obligations on AI deployers to diminish certain risks, does not cover a manifestation of the same risk by other kinds of technology, and simply push AI deployers toward the utilization of other devices to achieve the same problematic end instead of adopting “technology neutral regulation,” which circumvents these issues by targeting one specific technology. To that extent, The EU’s General Data Protection Regulation (GDPR) is a technology neutral regulation focusing on a particular purpose by safeguarding the protection of personal information when processed irrespective of the means used for the processing such as a basic computer program, a complex AI system or simply a human being and so escaping the difficulty of defining AI and moving the focus

57

Safiya Umoja Noble, Algorithms Of Oppression: How Search Engines Reinforce Racism (2018); Virginia Eubanks, Automating Inequality: How High-Tech Tools Profile, Police, And Punish The Poor (2017). 58 Winter, The Human Experience of Being-in-the-Board: A Phenomenological Approach, SSRN, 2018, https://papers.ssrn.com/sol3/papers.cfm?abstract_id¼3319392; E. van de Loo & J. Winter, ‘Corporate Culture is an Alarmingly Low Priority for Boards’, Insead Knowledge, 10 November 2017, https://knowledge.insead.edu/leadership-organisations/corporate-culture-is-analarminglylow-priority-for-boards-76.

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toward defining the risk that should be prevented and/or the right that needs to be safeguarded.59 The European GDPR regulation states that “the existence of automated decisionmaking, should carry meaningful information about the logic involved, as well as the significance and the envisaged consequences of such processing for the data subject.” Hence, under the GDPR regulation, the data subject is, under certain circumstances, entitled to receive meaningful information about the logic of automated decision-making. Boards examine financial performance, controls, and risk and so boards consider the firm and its business only through this financial lens. Moreover, board members are trained and experienced to practice and discuss the reality of the firm in this way which means that the board exchanges arguments based on factual information often expressed in numbers. In fact, boards spend little time reflecting on what happened or may happen, becoming an observer of their own practice and their own role. Thus, nonfactual information expressed in doubts, intuitions, and emotions is discussed only rarely in the board and quickly discarded and so boards struggle with successfully discussing matters of culture and values for want of conceptual understanding and language.’ Bussmann60 et al. argue that “While artificial intelligence effectively improves the convenience and accessibility of financial services, they also trigger new risks. Our research suggests that social network based explainable AI models can effectively advance our understanding of the determinants of financial risks and, specifically, of credit risks. The same models can be applied to forecast the probability of default, which is critical for risk monitoring and prevention.” The new digital possibilities necessitate that the objective of a firm is given transformed substance and that innovation is directed to that end and so new ethical dilemmas must be acknowledged and thought through, and the company must be trained accordingly. Thus, if transformation processes and cultural alterations are required to run the business, boards have to make certain that these are executed. Boards have to understand that their view of what real disruption involves and how innovation is comprehended is obstructed not only by the legacy of their IT systems, but also by the legacy of the setup of the compliance function, the existing dominant language in boards pointed at financial parameters and control, short-term financial KPIs and reports, a compensation policy directed at profitability for shareholders and a culture in which it is difficult to fail.61 With regard to current corporate governance, this means that the conventional profiles of nonexecutives being primarily former management executives from the old world are presently not fit for purpose. Hence, boards have to breed a strategy to

Ursula Von der Leyen, ‘A Union that strives for more: My agenda for Europe’ (July 2019) 60 Niklas Bussmann, Paolo Giudici, Dimitri Marinelli, Jochen Papenbrock, Explainable AI in credit risk management, https://ssrn.com/abstract¼3506274 p 12. 61 J. Miller, ‘Mark Zuckerberg asks governments to regulate tech firms’, Techspot 31 March 2019, www.techspot.com/news/79440-mark-zuckerberg-asks-governments-regulate-tech-firms.html. 59

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make the board more digital understanding which means that room must be made for a relevant number of digital understanding board members for the reason that they have less experience in more conventional areas of expertise, more intensive on boarding will have to occur, also to secure a cultural fit with the board and the firm. In the interim, enough digital knowledge has to be present in board meetings by having digital experts from management or external advisors provisionally join, and training programs must make certain that all members obtain adequate digital working knowledge. In line, Moerel62 argues “that if boards of established companies have to manage and supervise differently, this will also apply to their external supervisory authorities. As long as external supervision does not innovate, it will become particularly difficult to scale up the innovations that have been developed outside the existing context within the existing context.”

6.8

AI in Banks’ Governance

How AI and related technology already enhances global corporate governance practices and the prospective for further augmentation as AI continues to expand its capacity to offer cognitive insights and cognitive engagement in corporate board rooms? There is already a baseline of technology that boards have accepted to assist in managing their corporate governance duties and so supporting in planning and distributing reports, streamlining meeting preparation, and scheduling meetings. There is a need to address governance challenges that boards are facing, such as engaging in profound strategic, proactive risk oversight, and real-time insights into corporation operations. Hence, AI for strategic and operational decision-making empowers boards to make better decisions becoming an indispensable competitive advantage in its own right. It is worth noting that the modern banking boardroom is beset by huge volumes of data that directors must digest to accomplish their governance functions, data that is only increasing as their industries are rapidly altering and responding to technological disruptions.63 Moreover, apart from regulatory review, a revolution is going on in boardrooms across the globe such as the incorporation of technology and AI, and the creation of data assisting in the use of such AI systems, into the practice of

62

Prof. Lokke Moerel, Reflections on the impact of the digital revolution on corporate governance of listed companies, at: https://ssrn.com/abstract¼3519872 P45. 63 Barry Libert, Megan Beck and Mark Bonchek, ‘AI in the Boardroom: The Next Realm of Corporate Governance’ (October 2017) MIT Sloan Management Review . David Lancefield and Carlo Gagliardi, ‘Reimaging the Boardroom for an Age of Virtual Reality and AI’ Harvard Business Review (April 2015) . https://www.austrac.gov.au/lists-enforcement-actions-taken https:// www.apra.gov.au/news-and-publications/apra-launcheswestpac-investigation-and-increases-capi tal-requirement-add-ons.

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corporate governance and strategy. Hence, businesses, like Australia’s major banks, are too complex for their boards and executives to make good decisions without the aid of intelligent systems.64 All of the available technology are utilized in the boardroom to boost the natural capability of directors to fulfill their duties but it is worth noting that AI will not displace the role of directors in companies any time soon but rather that the insight offered by AI will advance analytical accuracy and resulting efficiency of the governance undertaking. It could be said that presently there is a combined intellectual capability of a group of actors referred to as “collaborative intelligence” not only embracing the collaborative or collective intelligence of human actors and being “a thought experiment” on corporate management and AI.65 Will the availability of intelligence and technology necessarily mean it will lead to better corporate governance? AI and technology assist, but do not oust, human actors performing governance functions, aspects of governance decision-making, such as ethics and culture, continue to be outside AI’s domain of influence with the consequence that human actors stay accountable for governance outcomes in the final instance. AI has enabled the creation of professional financing applications disrupting the finance industry and so AI could not only replace human capital in full or in part but also improve its performance beyond human benchmarks. For firms around the globe, there are a variety of programs and so firms ensure a necessary understanding of the AI and other technologies used in business by the senior management and the board to make certain proper monitoring. Due to the expectations of Board members to monitor substantive issues influencing the long-term value of a firm, the decisionmaking, deployment, and use of AI have to be carried out within the context of risk management, in order to capture market improvements. The financial services diligence has a set of rules to support assessment making being the basis of AI coordination, and the trade is consequently well-informed for AI implementation, placing it at the lead of employing and promoting since AI knowledge which means that AI can figure on hominoid intellect by identifying outlines and variances in bulky aggregates of figures. The technology of Google, Twitter, Facebook, Microsoft, and Apple has shaped the daily official interactions

64

Australian Prudential Regulation Authority, Prudential Inquiry into the Commonwealth Bank of Australia – Final Report (20 April 2018), https://www.apra.gov.au/sites/default/files/CBAPrudential-Inquiry_FinalReport_30042018.pdf. 65 Martin Petrin, ‘Corporate management in the Age of AI’UCL Working Paper Series (No. 3/2019), at https://papers.ssrn.com/sol3/papers.cfm?abstract_id¼3346722##; H James Wilson and Paul R Daugherty, ‘Collaborative Intelligence: Humans and AI are Joining Forces’, Harvard Business Review (online), July-August 2018, ; Anita Williams Woolley, Ishani Aggarwal and Thomas W Malone, ‘Collective Intelligence and Group Performance’ (2015) 25 Current Directions in Psychological Science 420; Timothy C Bates and Shivani Gupta, ‘Smart Groups of Smart People: Evidence of IQ as the Origin of Collective Intelligence in the Performance of Human Groups’ (2017) 60 Intelligence 46.

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and communications with one another in a monotonous time period.66 It is characteristic that banks face issues to handle with an expanding capacity of queries related to customer call centers and client correspondent electronic mail, and consequently, banks are implementing chatbots or “hi-tech personality” providing on the stipulation, automatic assistance, such as allocating with repeatedly enquired interrogations, accomplish financial services, and assist with fiscal applications. The use of AI in financial services increases efficiency and productivity through automation, curtail mistakes induced by psychological or emotional factors, and strengthen management information’s accuracy or conciseness by detecting patterns or longer-term advances that are not easily identified by existing monitoring methods. Thus, such requirements are valid where legislation, like the Financial Instrument Directive II for the European Union Markets (MiFID II), expands senior management’s obligations for analysis and takes greater data from the business into account. Al-Blooshi and Nobanee67 argue that “in AI applications, if organizations do not exercise sufficient care and prudence, they face potential problems. These include prejudice in materials, procedures, and outcomes for consumer identification and credit score, as well as due diligence in the supply chain. AI analytics customers must be fully aware of the evidence used to prepare, check, retrain, update and use their AI programs.” In banking, AI is omnipresent and there are more difficulties, embracing legal, political, economic, and social barriers. The global financial ecosystem is also continuing to be subject to new complications and so with increasing availability of data and growing computer power, AI programs get more complicated. Fines and legal cases involving discrimination and the opacity of AI applications have already been introduced. It is worth noting that opacity is the antithesis of legal decisions and responsibility for those decisions necessitates that the decision-maker has a convincing reason for a decision or act. Moreover, judicial decisions, in particular, give special weight to reasoning and so in the common law tradition, only the ratio decidendi (the legal basis for the decision) is binding on lower courts which means that appeals to higher courts look for errors in the law or in its application to the facts as disclosed in the reasons and so the failure to give reasons is a ground of appeal in its own right.68 It is worth mentioning here that computer simulation displaces humans from the center of the epistemological enterprise, regardless that the expansion of knowledge meant the expansion of human knowledge and understanding.

66

Kraus, Sascha and Palmer, Carolin and Kailier, Norbert and Lukas kallinger, Friedrich and Spitzer, Jonathan, Digital entrepreneurship: A research agenda on new business models (September 20, 2018). Available at: https://www.emerald.com/insight/content/doi/10.1108/IJEBR-06-20180425/full/html. 67 Laila Al-Blooshi, Haitham Nobanee, Applications of Artificial Intelligence in Financial Management Decisions: A Mini-Review, https://ssrn.com/abstract¼3540140 p 13–14. 68 State v. Loomis, 881 N.W.2d 749, 755 (Wis., 2016). Herbert Wechsler, Toward Neutral Principles of Constitutional Law, 73 Harv. L. Rev. 1, 19–20 (1959) (arguing that the ‘virtue or demerit of a judgment turns . . . entirely on the reasons that support it’) Mathilde Cohen, When Judges Have Reasons Not to Give Reasons: A Comparative Law Approach, 72 Wash. & Lee L. Rev. 483 (2015).

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Hence, the appearance of computational methods that transcend humans’ capabilities portrays the “anthropocentric predicament.” To that extent, distinct from the encounters created by autonomy in AI systems, the increasing opacity of those systems is not a challenge to the centrality of human agents as legal actors so much as a challenge to humans’ capability to understand and evaluate actions which is vital to meaningful regulation. In October 2018, an insurer charged £ 5.2 million over the ineffective management of a third-party provider by the Financial Conduct Authority (FCA) due to the overreliance of the insurer on the software for voice analysis led to some claims that were unfairly declined or not properly investigated.69 AI enables the identification of adaptive trends across large data volumes and modern statistical methods to address a narrowly defined and permanent problem set and so Al has made numerous advances enabling applications for professionals in finance. Consequently, AI could not only replace human resources fully or partially but also improve performance beyond human standards and so firms around the globe employ a number of its applications. It is worth noting that businesses provide a sufficient understanding of AI and other technologies used in the industry by the senior management and the board to deliver effective control being significant for the reason that the board members track substantial issues that influence the long-term value of a firm. Throughout compliance with the Corporate Governance Code, the Board is needed to determine the nature and scale of the key risks that it takes into account in order to achieve its strategic objectives. Moreover, firms around the globe keep sound risk management and internal control systems to make sure an adequately current risk framework is established, monitored, and communicated appropriately. Furthermore, AI decisionmaking, execution, and use are managed within a framework of risk management that pinpoints business changes encompassing four main activities: risk recognition, risk assessment, risk mitigation, and risk control—whether the system is focused on the ISO, the funding organizations’ committee, and other standards. Early intervention, preparedness for accidents, crisis response strategies, and preparation should support this strategy.

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AI in Audit

AI technologies that model and stress test risk management practices and internal audit processes and controls within companies are a developing area gaining traction in the financial services sector, mainly in banking organizations.70

69

Lin, Tom, Artificial Intelligence, Finance, and the Law (November 04, 2019). https://papers.ssrn. com/sol3/papers.cfm?abstract_id¼3480607. 70 Deloitte EMEA Centre for Regulatory Strategy, AI and Risk Management – Innovating with Confidence (April 2018) 1–2 ; Jeanne Boillet, EY, “Why AI is both a risk and a way to manage risk” (1 April 2018) ; McKinsey & Company, “The future of risk management in the digital era” (October 2017) . 71 Pascal Bizarro and Margaret Dorian, ‘Artificial Intelligence: The Future of Auditing’ (October 2017) Internal Auditing 21. 72 The Institute of Internal Auditors Global, Global Perspectives and Insights – The IIA’s Artificial Intelligence Auditing Framework (September 2017) 2, https://na.theiia.org/periodicals/Pages/ Global-Perspectives-andInsights.aspx; Paul Holland, Shamus Rae and Paul Taylor, ‘Why AI must be included in audits’ (June 2018) https://assets.kpmg.com/content/dam/kpmg/uk/pdf/2018/06/ why-ai-must-be-included-in-audits.PDF. 73 He Li, Jun Dai, Tatiana Gershberg and Miklos Vasarhelyi, ‘Understanding Usage and Value of Audit Analytics for Internal Auditors: An Organisational Approach’ (2018) 28 International Journal of Accounting Information Systems 59; Nurmazilah Mazhan and Andy Lymer, ‘Examining the Adoption of Computerassisted Audit Tools and Techniques’ (2014) 29 Managerial Auditing Journal 327.

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streamlining and automating data acquisition for audits and converting that data into report formats.74 The advanced analytics within AI technologies compare, contrast, and summarize huge data collections and deliver greater support for audit findings through reliance on accurate and real-time data rather than audit sampling. Additionally, the machine learning competency of the systems enables them to benchmark across different companies to pick up on the characteristics of extraordinary transactions and so this capability is boosted when they are run on the cloud extending the AI functionality into cognitive insight. It has to be taken into consideration that the risks lie in making certain that AI has been effectively tested to guarantee that results are correct echoing the objectives of internal audits. Fully AI automated internal audits are the conceivable future having the prospective to improve the functionality of the audit process, risk management at all levels of a firm, and risk governance by the board but are not yet here. As with risk governance, AI-driven audit reports make audit governance by the board or board committee more effective generating new chances for strategic oversight of corporate activities in place of monotonous tasks.75 Integral to risk and audit governance is a company’s commitment to functioning their businesses in a legally and ethically responsible way, in the long term interests of their shareholders which means that legal compliance matters are complex, needing not only that firms meet the requirements of relevant laws but also to ascertain and self-report possible breaches of the laws to the appointed regulator in a time-conscious way.76 It seems that the law has not been obeyed, and has not been enforced effectively showing deficiencies of culture, governance, and risk management within entities because entities have paid too little attention to matters of regulatory, compliance, and conduct risks.

Syed Moudud-UI-Huq, ‘The Role of Artificial Intelligence in the Development of Account Systems: A Review” (2014) 13 Journal of Accounting Research & Audit Practices 7. Bill Brennan, Mike Baccala, Mike Flynn and 10Rule, ‘Artificial Intelligence Comes to Financial Statement Audits’, CFO Magazine (February 2017) . 75 Michael P Cangemi and Patrick Taylor, ‘Harnessing Artificial Intelligence to Deliver Real-Time Intelligence and Business Process Improvements’ EDPACS (online), 27 April 2018, 3 . 76 Royal Commission into Misconduct in the Banking, Superannuation and Financial Services Industry (Interim Report, September 2018). Royal Commission into Misconduct in the Banking, Superannuation and Financial Services Industry (Final Report, February 2019). 74

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Chief Legal Officer and AI Management

Nowadays, companies are eschewing intermediaries and external service providers in a number of areas. Firstly, disintermediation is desirable where in-house counsel do work before delivered by external law and other service companies.77 Secondly, technological advances, particularly in AI, are displacing lawyers and transforming legal service delivery ways.78 Thirdly, by reducing external service providers and so reducing costs and refining the quality of service, the implementation of AI technology foreshadows another key alteration in service delivery, which inevitably influences the external as well as in-house lawyers required to serve corporate client needs.79 In reality, AI frees lawyers up to spend more time on productive, valueproducing activities which means that the chief legal officer (CLO) spends more time working together with business partners on strategic matters than their historical counterparts could and so equipped with valuable data and a more strategic orientation, the modern CLO engages the board and C-suite executives, bridging historical silos.80 Machine learning, which enables qualitative analysis of legal documents, such as contracts and briefs, influences the legal services market, and so machines draft briefs in a fraction of the time a law firm associate would need and the demand for Law associates is declining.81 Moreover, the greater availability of legal data drives decision-making about legal services, with ramifications for litigation and deal strategies, evaluating intellectual property, advancing business processes, aiding digital transformation, and delivering new business insights in such parts as multiterritory risk assessment and analysis. In fact, operational changes make corporate legal departments more competent, and cost-effective. CLOs engage in a course of streamlining law department 77

Steven L. Schwarcz, Systemic Risk, 97 Geo. L.J. 193, 200 (2008) (explaining disintermediation’s role in “enabling companies to access the ultimate source of funds, the capital markets, without going through banks or other financial intermediaries”). Tom C. W. Lin, Infinite Financial Disintermediation, 50 Wake Forest L. Rev. 643 (2015) (discussing disintermediation in the financial industry). Sarah Kellogg, The Uncertain Future: Turbulence and Change in the Legal Profession, 30 Wash. Law. 18, 21 (2016) (explaining that 67% of law firms surveyed in 2016 stated they were “currently losing business to corporate law departments that are insourcing legal work”). 78 Jane Croft, The Relentless Advance of the Super-Intelligent Attorney, FIN. TIMES (Dec. 5, 2016), https://www.ft.com/content/af3e2a64-a069-11e6-891e-abe238dee8e2. 79 The New Reality: Turning Risk Into Opportunity Through The Dupont Legal Model 2 (Silvio J. Decarli & Andrew L. Schaeffer eds., 5th ed. 2009). 80 Sterling Miller, Artificial Intelligence And Its Impact on Legal Technology: To Boldly Go Where No Legal Department Has Gone Before, Thomson Reuters (“As CEOs and CFOs become more accustomed to using AI, they will expect the other members of the CSuite—including the general counsel and legal department—to follow suit. In-house lawyers that embrace AI, will become more valuable to the next generation of CEOs and CFOs.”). 81 Sarah Murray, Algorithms Tame Ambiguities in Use of Legal Data, FIN. TIMES (Nov. 15, 2018), https://www.ft.com/content/50b0eba4-d063-11e8-9a3c-5d5eac8f1ab4 (“[T]he next step is to enable machines to make qualitative analyses of legal documents.”).

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Chief Legal Officer and AI Management

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operations to meet the requirements of corporate clients needing attention to internal legal expertise, costs, technology, and effective deployment of personnel. Moreover, corporate legal departments are developing greater process and project management capabilities involving the elimination of unnecessary work steps and costs, whereas project management involves the use of knowledge, skills, tools, and techniques to project activities to meet the particular project demands.82 Furthermore, company law departments locate their employees in less expensive cities to control costs and so Oracle and Cisco now have significant legal operations in the Research Triangle Park of North Carolina.83 It has to be taken into account that CLO must have a “panoramic” view of business risks spreading beyond the home country. In fact, corporations must address risks in the business process involving identifying, analyzing, and managing them via internal controls. Nonetheless, legal risks are only one subset of risks incorporated into business decisions and so others are financial, reputational, operational, or linked to human resources and brand equity.84 Moreover, CLOs must recognize not only the different kinds of risk but how they interact and so CLOs, as insiders or “innkeepers” with close knowledge of business operations, are distinctively positioned to add value. Hence, a sound risk management strategy for large corporations in the contemporary context necessitates a global perspective which means that CLOs raise awareness and keep management described of regional and cultural risks to facilitate protect corporate value.85 Furthermore, ERM is a type of agency cost control analogous to law compliance programs, and internal controls and so corporations face a myriad of global risks ranging from multifaceted financial risk to quality control concerning material manufactured in various countries.86

82 What Is Project Management?, PROJECT MGMT. INST., https://www.pmi.org/about/learnabout-pmi/what-is-project-management. 83 Jeffrey K. Liker, The Toyota Way: 14 Management Principles From The World’s Greatest Manufacturer (2004). 84 In re Citigroup, Inc. S’holder Derivative Litig., 964 A.2d 106, 127–28 (Del. Ch. 2009) (shareholder suit alleging directors breached fiduciary duties pursuing excessively risky strategies); Stephen M. Bainbridge, Caremark and Enterprise Risk Management, 34 J. CORP. L. 967, 969 (2009); Kristin N. Johnson, Addressing Gaps in the Dodd-Frank Act: Directors’ Risk Management Oversight Obligations, 45 U. MICH. J.L. REFORM 55, 59 (2011) (“In the absence of rigorous ERM obligations under state corporate law and in the wake of the recent financial crisis, Congress has taken steps to impose federal regulation on risk management oversight. In July of 2010, Congress adopted the [Dodd-Frank Act].”). 85 Carolyn Kay Brancato Et Al., The Conference Bd., The Role Of U.S. Corporate Boards In Enterprise Risk Management 10 (2006), https://www.conference-board.org/pdfdownload.cfm? masterProductID¼3840. 86 Alm Intelligence & Morrison & Foerster LLP, General Counsel Up-Atnight Report 5 (2018), https://media2.mofo.com/documents/170622-gc-up-at-nightreport.pdf (“Now, GCs must not only think globally to maintain a culture of compliance regardless of geography, but also act locally in establishing policies and procedures to ensure corporate action meets the prevailing local regulatory standards.”).

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Also, CLO competence embraces a strong sense of the global regulatory framework across geographical boundaries which means that CLOs must be aware of international trade laws influencing the corporation’s national and foreign operations.87 The CLO’s global competence must go beyond a simple sense of regulatory frameworks to encompass a keen cultural competence. To that extent, as business setups expand, and firms search for additional market outlets for their products and services, the need for global, regional, and cultural sensibilities becomes obvious. Moreover, culture is like the operating system of the corporation and, even if not perceptible to outsiders, it has a momentous effect on risk management, compliance, and other business outcomes. Nowadays, shareholder and stakeholder activisms are the new reality and so firms have proactive and reactive investor-engagement committees that usually report to the CEO or CFO. While CLOs may not frequently sit with them, they can advise the board of directors and the CEO on how to respond to activist demands and as a matter of strategy, the CLO urges the CEO to work through the formal investorengagement course with these committees to deal with requests, inquiries, and communication.88 Furthermore, the CLO’s process prevents needless exploitation of executive decision-making.89 It is worth noting that corporations are assessing their environmental, social, and governance (ESG) profiles and studying the related risks alongside other traditional performance metrics and so CLOs must advise corporate managers to bear in mind how ESG factors fit into the business strategy aiding them respond to pleas to engage from impact investors and other stakeholders together with the public. Furthermore, in the ESG- and stakeholder-focused context, the role of the CLO is likely lifted signaling a move toward an augmented CLO role since the strong connection between ESG90 and corporate operations such as supply chains. 87 June Eichbaum, Globalization and General Counsel, MINORITY CORP. COUNS. ASS’N, https://www.mcca.com/mcca-article/globalization-and-general-counsel/ (explaining that “handson experience with regulators in the European Union and in Asia” is a ‘must-have[]’ for general counsel”). Jennifer G. Hill, Legal Personhood and Liability for Flawed Corporate Cultures (European Corp. Governance Inst. Working Paper Series in Law, Working Paper No. 413/2018, 2018). 88 Lisa M. Fairfax, From Apathy to Activism: The Emergence, Impact, and Future of Shareholder Activism as the New Corporate Governance Norm, 99 B.U. L. REV. 1301, 1314 (2019). Matteo Tonello & Matteo Gatti, Board-Shareholder Engagement Practices, Harv. L. Sch. F. On Corp. Governance (Dec. 30, 2019), https://corpgov.law.harvard.edu/2019/12/30/board-shareholderengagement-practices/ (“Sixty percent or more of the largest companies involve their general counsel in board exchanges with investors.”). 89 Matteo Tonello & Matteo Gatti, Board-Shareholder Engagement Practices: Findings From A Survey Of Secregistered Companies 42–43 (2019), https://www.conference-board.org/ pdfdownload.cfm?masterProductID¼20347. 90 Veena Ramani, Environmental, Social, and Governance (“ESG”) Issues Pose Risks to Companies. Can Chief Legal Officers Help Drive Solutions?, ASS’N CORP. COUNS. (Nov. 6 2019), https://www.acc.com/resource-library/environmental-social-and-governance-esgissues-pose-riskscompanies-can-chief-0 (“In 2018, investors filed nearly 400 shareholder resolutions on sustainability issues, many of them related to climate change.”).

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It is worth mentioning here that the energetic and rapidly shifting contemporary global business environment necessitates an improved CLO role with a deeper set of competencies embracing, inter alia, sophisticated procurement capabilities, an enhanced financial focus, and a global enterprise risk management orientation. Moreover, contemporary CLOs are potent corporate officers creating value for the corporation and fulfilling an internal quasi-regulatory function benefiting multiple stakeholders. In other words, modern business environment is illustrated by technological disruption, increased activism by shareholders and other stakeholders, a regulatory environment highlighting internal controls, and private ordering instead of prescriptive regulation which means that modern CLOs accomplish an embedded internal regulatory role that incorporates monitoring, formulating corporation practices and policies, and enforcement. The modern CLO role is expressed in terms of value creation including the interaction of multiple parties and activities in the employment of corporate resources contributing to the improvement of corporate value and competitive advantage in unique manners that outside counsel cannot easily replicate and so the CLO role is strategic rather than tactical engaging consistent interaction with corporate operations and a multiplicity of players, enabling the corporation to boost its making and preservation of value.

6.11

AI and Healthcare Industry

As already mentioned earlier, AI is a set of methods, algorithms, and technologies that make software “smart” in a manner human-like. Digitalization, AI, and big dataderived inferences are supporting human decision-making in medicine and so AI, algorithms, robotics, and big data are used as needed healthcare enhancements permitting to monitor large-scale medical trends and measuring individual risks based on big data-driven judgments. The healthcare industry is multifaceted and artificial intelligence/machine learning influences every aspect of healthcare: treatment, diagnosis, administration, and research. Moreover, artificial intelligence and machine learning affect the healthcare industry and the way it engages with its stakeholders. Hence, developing trusted AI has become an ever-increasing condition for future applications of artificial intelligence/machine learning in the healthcare industry and so trust has to be built into the system by design rather than as an afterthought. Furthermore, AI-powered assistants remotely assess the symptoms of patients and alert clinician’s only when intervention is needed, dropping needless hospital visits, and reducing the burden on medical professionals. In addition, artificial intelligence can recognize patients to prioritize with such interventions and compliance data are sent to clinicians. As mentioned, AI is integrated into all aspects of healthcare industry, such as treatment, diagnosis, medical imaging, personalized treatment, administration, and research. It is worth noting that artificial intelligence is employed in the treatment of

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patients via robotics and as robots become more advanced have the prospective for eliminating the need for multiple caregivers. However, it is robot-assisted surgery that characterizes the most potential for change in the near future. On the other hand, the entrance of a human into a hospital and the whole process of its treatment to be accomplished by Al is unthinkable at the moment. Virtual healthcare is the use of technology such as video, messaging, and sensors to deliver health services independent of time or location.91 Moreover, telemedicine is the remote transferring of medical information through telecommunication technology to accomplish consultations, examinations, and procedures, which is the modern evolution of absentia care.92 All facets of healthcare will be impacted by AI but presently the integration of AI in certain areas of medicine, such as medical imaging, is quite advanced, benefitting greatly from earlier research in computer vision. Besides, AI is in the early stages of development and implementation due to the need to develop trusted AI. The various risks of AI will be managed and as humans and machines begin to collaborate more closely, the transformational possibilities of AI for transcending the healthcare industry will become immense. Modern states embrace the advantages of AI and become leaders in the field through developing national AI, digital strategies, and action plans. Clinical decision support systems are advancing with 5G technologies, which will enhance prognostic capacities. Most promising AI advancements in healthcare delivery and patient experience are assumed in areas such as surgery, radiology, and cancer detection. Moreover, the development of programmable cells that destroy diseases naturally and internally are advancements of the future of self-determined prognosis led by algorithmic big data-derived insights. Furthermore, radiology and imaging benefit from computer-guided and big data-enhanced capabilities to diagnose and predict future outcomes simultaneously. Hence, robotics entered the medical field as assisted body parts or surgery devices along with support for disabled and patient care assistance, automated nursery, and mental health stabilizers. The use of AI is improving the prevention of diseases, accuracy of diagnoses, and predictions on treatment plan outcomes. Moreover, AI innovations present benefits of rational precision and human resemblance, targeted aid, and corruption-free maximization of excellence and so by using the predictive power of big data has prolonged the success and efficiency in the healthcare sector. In addition, machine learning’s capacity to collect and deal with big data, and its multiplying adoption by hospitals, research centers, pharmaceutical firms, and other healthcare institutions, are fuelling economic growth in healthcare.

91 Safavi, K. and F. Dare, 2018. Virtual health care could save the U.S. billions each year. Harvard Business Review, April 3, 2018. https://hbr.org/2018/04/virtual-health-care-could-save-theu-sbillions-each-year. 92 Pacis, D.M.M., E.D.C. Subido Jr. and N.T. Bugtai, 2018. Trends in telemedicine utilizing artificial intelligence. AIP Conf. Proc., Vol. 1933, No. 1.

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Hospitals and healthcare provider segments are holding the largest size of AI in the healthcare market owing to a large number of applications of AI solutions across provider settings, the capacity of AI systems to advance care delivery and patient experience while bringing down costs along with the mounting adoption of electronic health records by healthcare organizations. Additionally, AI-based tools, such as voice recognition software and clinical decision support systems, assist streamline workflow processes in hospitals at lower cost with upgraded care delivery and heightened patient experience. To that extent, advanced hospitals are looking into AI solutions to back and perform operational initiatives that expand precision and cost-effectiveness. Medical decision-making becomes enhanced by predictive analytics and general healthcare management technology and so big data insights reinforce drug development and global health checking. Advanced computing power and the decreasing cost of hardware are factors in the projected market growth and so the adoption of applications such as patient data and risk analysis, lifestyle management, and monitoring are advancing technology in the healthcare market. Hence, electronic health records used by healthcare organizations and the outsourcing of health monitoring by novel personal care products are upgrading quality and eventually bring down costs. While data collection is easier than ever, appropriate usage of data is and will be a vital element for productivity, quality, and accessibility of AI-driven applications. So, the promise of data-driven solutions is to collect data at a density that is not feasible for humans and classify designs humans cannot detect. Since AI in healthcare is utilized to aggregate and organize data by looking for trends and patterns and making recommendations, a human component that is creative, cognitively highly flexible, and attuned with AI sources is still required which means that in the near future AI is will support medical doctors and nurses with excellence and precision on decision-making predicaments and cognitive aptitude constraints.93 It could be said that the prospective post-COVID-19 era will display advanced healthcare and so global digital healthcare innovations will have better general medical care. Finally, cyberspace and AI–human compatibility via tech skills and digital affinity are growing competitive advantages. AI is accelerating a convergence in the pharmaceutical and medical device industries and, in the healthcare industry more broadly, is similar to the convergence of the media, entertainment, and communications industries. Moreover, for media and communications, AI-fueled convergence denotes new video entertainment or sophisticated, analytical, autonomous versions of the AI-generated auto-replies. Furthermore, for healthcare, big datasets and complex algorithms will assimilate the development and delivery of small- and large-molecule drugs, genetic therapies,

93

OECD (2019). Artificial intelligence in society. Paris: OECD. Emre Pakdemirli. Artificial intelligence in radiology: Friend or foe? Where are we now and where are we heading? Acta Radiologica Open, 8, 2, 1–5, 2019.

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and medical devices personalized to specific user profiles, with dynamic, real-time updates and adjustments.94 How AI will disrupt the current model? The pharmaceutical, biologic, and medical device industries are starting to utilize AI in exploiting all of the possible large and small molecules that might interact with the human body, all of the naturally happening human genetic variations generating health effects, and all of the possible engineered genetic alterations producing health effects. In other words, AI accelerates the tempo of basic biochemical and genetic research exponentially by AI modelling of chemical reactions or genetic alterations using very large datasets. AI is already impacting the development and function of drugs, biologics, and medical devices but AI could drastically disrupt the already fragile blockbuster model of pharmaceutical development and shift the drug, biotech, and medical device industries away from their life sciences roots and toward technology Valleys. Hence, it is obvious that there is a need for new regulatory models to address the related intellectual property, privacy, and accountability issues AI changes will require. Will Al contribute in discovering new medicines or merely humans will utilize Al in the development of new drugs, etc.? Will Al decide about drugs in an AI society? It is far away from imagining an AI society governed by AI technology without any human intervention. Will humans exist in an AI society functioning mechanically? It is difficult to imagine and understand humans existing in a globe totally mechanically functioning. Will AI work for humans or humans become the slaves of AI technology?

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Unregulated Artificial Intelligence

It has to be taken into account that AI wields inconceivable power over the financial markets and so AI conducts the majority of stock trades, with software automatically receiving, processing, and executing thousands of decisions in fractions of milliseconds. Nonetheless, limited knowledge is available about the basis of regulation for financial institutions’ use of AI.95 Furthermore, the Bank for International Settlements (BIS) surveyed 31 jurisdictions in 2020 and determined that to date there are no specific regulatory requirements for financial institutions’ use of AI, though jurisdictions such as Singapore, Netherlands, and Hong Kong have issued nonbinding principles to urge ethical and responsible use of AI by financial institutions.

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Denise Myshko & Robin Robinson, Artificial Intelligence: Molecule to Market, Pharmavoice (Jan. 2019), https://www.pharmavoice.com/article/2019-01-pharma-ai/. 95 Bank for International Settlements (2020). Policy responses to fintech: a cross-country overview. FSI Insights on Policy Implementation, No. 23. January Kearns, M., Roth, A. 2019. The Ethical Algorithm: The Science of Socially Aware Algorithm Design (Oxford University Press, Oxford).

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AI and EU Trade

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In fact, the online marketplace lending (OML) industry has evolved from “disintermediation” to “reintermediation” in fintech96 and it is a fintech innovation that allows individuals to borrow directly from other individuals, cutting out the financial institution as the middleman. Nevertheless, OML platforms have grown from simple meeting places for borrowers and lenders to something approximating delegated asset managers that for a fee invest lenders’ money in loans of the platforms’ choice at prices the platforms consider suitable. Besides, OML platforms use proprietary algorithms to screen borrowers, set loan prices, and manage lender capital to invest in loans they facilitate.97 The fast trading in OML differs from fast trading in the equity markets in many aspects and so OML platforms employ “posted prices” (i.e., interest rates predetermined by the platform) to make possible a rapid deployment of funds. Thus, under posted prices, the positive effect of HFT on price discovery does not apply, and the “first-come-first-served” rule stimulates competition in trading speed to extract rents. In addition, speed influences “who gets to get the return” but not the magnitude of the return and so private profits from fast trading leads to an upsurge in funding speed through Prosper’s third-party API. In conclusion, the rapid development of AI has converted OML platforms from mere information intermediaries to credit intermediaries and asset managers. Conversely, the unregulated use of AI generates significant risks and moral hazard issues. Li et al.98 argue that “individual investor returns decrease and borrowers pay more in financing costs due to AI cream-skimming. Further evidence reveals a misalignment of interest when a platform’s private interest in loan origination exceeds its expected loss in management fees.”

6.13

AI and EU Trade

It has to be taken into account that applied artificial intelligence’s key inputs are data and machine learning code and Al systems are fairly fluid across borders. Moreover, international trade in services that supply or incorporate machine learning in their software architecture is ever growing and so Al’s digital components are freely moved across global digital ecosystems. It is obvious that there is respect for European values and fundamental rights as well as ethical principles and so the EU has a preference to afford a high level of protection of individuals’ rights and European values when exploiting artificial intelligence which means that law and policy have to deal with the fluidity of

Balyuk, T. & Davydenko, S. A. (2019). Reintermediation in fintech: Evidence from online lending. Available at SSRN 3189236. 97 Vallee, B. & Zeng, Y. (2019). Marketplace lending: a new banking paradigm? The Review of Financial Studies, 32(5), 1939–1982. 98 Xiaoyang Li, Haitian Lu, Iftekhar Hasan The Dark Side of Unregulated Artificial Intelligence: Evidence from Online Marketplace Lending, at: https://ssrn.com/abstract¼3575260. 96

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algorithmic systems without disrupting beneficial algorithmic flows. Hence, EU rule-making in this area has to foresee the liquidity of artificial intelligence serving European users from outside EU territory. In other words, EU trade policy has to be aligned with EU rule-making on artificial intelligence. Hence, the EU institutions are responsible to make certain that the agreements negotiated are compatible with internal EU policies and rules starting from the 2018 horizontal provisions for cross-border data flows and for personal data protection in EU trade and investment agreements. Moreover, EU’s external trade policy will have to be reconciled with expected EU rule-making on artificial intelligence and so trade laws will influence artificial intelligence governance. In fact, given artificial intelligence’ transformative impact on every aspect of information civilization, an open and inclusive deliberation of the interactions between the e-commerce proposal and EU’s emerging governance of artificial intelligence is vital. In fact, cross-border trade in artificial intelligence should be dependent on accountability and so the quid pro quo for cross-border digital trade would be a healthy measure of transparency of artificial intelligence systems. Moreover, EU external trade policy has to maintain the regulatory space for national measures that mandate source code transparency, accountability, and auditability of artificial intelligence systems. Quality data which is key for algorithmic performance should only be used for rationales that are fitting with European values contributing to public value and societal interests. Artificial intelligence will aid developing countries in the alleviation of poverty but steps must be taken to circumvent perpetuating past cycles of economic dependence. The “special and differential treatment” provisions in WTO law are a strong building block for trade in artificial intelligence that favors developing countries. Furthermore, cooperation and capacity building under GATS Article IV is vital in improving the aptitude of developing countries to build their own artificial intelligence services. On the one hand, developing countries have a strategic interest in the conception of open-access software, on the other hand, they have to defend against the predatory data mining practices. Like the EU, developing countries have to follow policies harmonizing norms in a multilateral agreement and close the digital trade imbalance. In addition, cross-border trade in artificial intelligence aids economic growth and so GATS disciplines, as well as future multilateral agreements governing the flow of data, are crucial to harmonizing approaches to artificial intelligence. Nevertheless, artificial intelligence signifies challenges to the multilateral trading system, which are distinct from prior technological advances. Contrasting previous technologies, artificial intelligence is infused with ethical values not being compatible with national human rights frameworks. For that reason, WTO members will have to strike a balance between national security and free trade in data-extractive services

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AI and Labor

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and so Members must place the artificial intelligence ecosystem within the framework of international trade.99

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AI and Labor

It has to be taken into account that the existing wave of industrial development is enhanced by the proliferation of cyber–physical infrastructure and unified systems making possible new practices of profiling, organizing, and checking. Moreover, several AI features are implanted as parts of larger tech systems escalating their computational power, rather than stand-alone structures.100 Technological advances make certain frictionless, accessible, and convenient information exchanges altering the relationship between employers and employees, as long as hyper connected equipment is responsible for the transformation of how work is made, both at the individual and at the collective level.101 Hence, new working arrangements appear, embracing the well-examined platform work and the field of AI is experiencing a wave of rapid advancements and so generating noteworthy encounters to privacy and data protection.102 Furthermore, the inexpensive, massive production, capturing, collection, and usage of data, in conjunction with valuable cloud storage and computing, machine learning, IoT, neuronal networks, and mobile robotics allow new evidence-based human resources and intensive management practices.103 Taking into account that AI-driven technologies are mixed into workplaces and labor processes, there is anxiety about the widespread displacement of human workers due to the fact that human work is composed of a series of tasks, some or all of which are done more successfully, efficiently, or at scale by a machine.

Kristina Irion, and Josephine Williams (2019). ‘Prospective Policy Study on Artificial Intelligence and EU Trade Policy’. Amsterdam: The Institute for information Law, 2019. Amsterdam, January 2020 The Institute for Information Law (IViR). 100 Peter Cappelli, Prasanna Tambe, & Valery Yakubovich, Artificial Intelligence in Human Resources Management: Challenges and a Path Forward (Nov. 1, 2018), https://ssrn.com/ abstract¼3263878. Report by the High-Level Expert Group on Artificial Intelligence, A definition of AI: Main capabilities and scientific disciplines, at 1, COM (2019) (Apr. 8, 2019). 101 Mirela Ivanova et al., The App as a Boss? Control and Autonomy in Application-Based Management, 2 Interdisziplinärer Arbeitsforschung (2018). Christian Ernst, Algorithmische Entscheidungsfindung und personenbezogene Daten, 72 Juristenzeitung (2017). “[a]n algorithm can be understood as an unambiguous, executable sequence of clearly defined instructions of finite length to solve a problem.” 102 Marta Otto, “Workforce Analytics” V Fundamental Rights Protection in the EU in the Age of Big Data, 40 Comp Lab. L. & Pol’y J. 389 (2019). 103 Alexandra Mateescu & Aiha Nguyen, Workplace Monitoring & Surveillance, Data & Society (2019), https://goo.gl/Cv4EAi. Sarah Kessler, Gigged: The End Of The Job And The Future Of Work (2018). Derek Zimmer, The Internet of Things is Surveillance, Private Internet Access, Nov. 21, 2018, https://www.privateinternetaccess.com/blog/2018/11/the-internet-of-things-is-surveil lance/. 99

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Consequently, as machines grow in competence, a greater number of tasks presently accomplished by humans will be automated. Artificial Intelligence plays a vital role in guaranteeing that hackers and scammers do not access confidential information from cloud data storage systems. Al offers more advantages than disadvantages that benefit individuals and corporates. On the other hand, firms will deliver goods using robots, and people will also purchase robots to do many house chores and so leading to the loss of human labor since robots will be able to do different activities done nowadays by humans.104 In addition, the risk is that AI technology is used to deepen hierarchy and control over work running, team dynamics, usage habits, social media behavior, and even sensitive characteristics.105 Does AI lead to human substitution? It is characteristic that several tasks or jobs are made by complex lines of code, which are trained via data collected and so a “workless future” is forthcoming due to AI. Admittedly, the advent of breakthrough technologies has caused legal implications due to digital transformation concerning organizational needs and workers’ protection.106 Thus, it is advanced automation and the subtle prospective of AI and algorithms, leading to a model of control and appraisal without an intuitive link between what is done when “logged-in” and how it is assessed that it matters and so generating the prospective of “informating” work supported by a resurgence of highly standardized organizational patterns.107 The replacement of human labor by robots and algorithms in several levels of industrial production and administrative processes is triggering a lot of anxiety concerning the rise of advanced algorithms. Thus, societies and governments need to pinpoint these concerns so as to proceed with effective oversight and control mechanisms, legislation, and other countermeasures. In addition, man-made processes are now more accurate and faster, directly influence administration and law. Nonetheless, the application of advanced algorithms in the public domain is problematic triggering many implications. In labor when it comes to “surveillance” and “contrôle des salaries,” new technologies signify a true game changer, adding to a swing away from a direct and physical control by the employer or by middle management to a model based on

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Makridakis, S. (2017). The forthcoming Artificial Intelligence (AI) revolution: Its impact on society and firms. Futures, 90, 46–60. 105 Phoebe Moore, The Mirror for (Artificial) Intelligence: In Whose Reflection?, 41 COMP. LAB. L. & POL’Y J PG# (2019) Valerio De Stefano, ‘Negotiating the Algorithm’: Automation, Artificial Intelligence and Labour Protection, 41 Comp. Lab. L. & Pol’y J PG# (2019). 106 Brishen Rogers, Beyond Automation: The Law & Political Economy of Workplace Technological Change 24 (Roosevelt Institute Working Paper, 2019), https://ssrn.com/abstract¼3327608. 107 Evgeny Morozov, Capitalism’s New Clothes, The Baffler (Feb. 4, 2019), https://thebaffler.com/ latest/capitalisms-new-clothes-morozov; Ekkehard Ernst et al., The economics of artificial intelligence: Implications for the future of work, 5 ILO Future Of Work Research Paper Series 1 (ILO, 2018).

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data collected via remote scrutiny.108 To that extent, the French Labor Code (LC) and of the Law “Technologies and Freedoms,” the case law and the GDPR outline a framework for conditions and restrictions on the use of technologies at the workplace.109 In Germany, if employers want to monitor the working activities and the conduct of their employees, a number of restrictions have to be observed such as the protection of the general right of personality.110 In Italy, direct monitoring of work activities carried out remotely by way of installed devices was always and without exception prohibited. On the other hand, controls intended at pursuing different purposes than the control of the working activity were permitted under the condition that a precise collective agreement had been predetermined or an administrative authorization acquired.111 Even though AI represents several advantages for workers “such as augmenting human capabilities and enhancing creativity, advancing inclusion of underrepresented populations, reducing economic, social, gender and other inequalities, and protecting natural environments, thus invigorating inclusive growth, sustainable development and well-being,”112 it jeopardizes lives by increasing authoritative standpoints. Moreover, it is difficult to say how monitoring, tracing, scoring, rankings, and all the resulting metrics engendered by AI tools can be maneuvered and repurposed to infer indefinite characteristics or to predict unknown behaviors.113 New technologies alter today’s societies in an incomparable way and they will keep on transforming them. In bureaucratic procedures, human errors are limited considerably through the use of modern ICT, including cyberspace and companies’ intranets. In public administration many organizational, managerial, and archiving processes are unnecessary and time consuming. Hence, the introduction of advanced algorithms is vital in the automation of these routes, which advance the quality of

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Code Du Travail [C. TRAV.], art. L. 1222-4. 92. Code Du Travail [C. TRAV.], art. L. 2321-38. Cour de Cassation, Chambre Sociale [Labor Division of the supreme court] October 2, 2001, No. 99-42.942 (Fr.). 109 Marie Morin and Francis Kessler, Labor impact of technological devices in France, 2 IUSLABOR 19–34 (2018). Christophe Vigneau, Information Technology and Workers’ Privacy: The French Law, 23 Comp. Lab. L. & Pol’y J. 351 (2002). Bernard Bossu & Alexandre Barège, Preuve et surveillance des salariés: regard français, 54 Les Cahiers De Droit 277, 279 (2013). 110 Udo Di Fabio, GG, Article 2, margin 14, in GRUNDGESETZ-KOMMENTAR (Theodor Maunz & Gunter Dürig eds. 2018, 84th supplement August 2018). Ingrid Schmidt, GG, Article 2, margin 43, in ERFURTER KOMMENTAR ZUM ARBEITSRECHT (2019). 111 Pietro Lambertucci, La disciplina dei «controlli a distanza», GIUR. IT., 737 (2016); Alessandra Ingrao, Il controllo disciplinare e la privacy del lavoratore dopo il Jobs Act, 1 RIV. IT. DIR. LAV. 46 (2017). 112 OECD, Recommendation of the Council on Artificial Intelligence, OECD/LEGAL/0449 (May 12, 2019), https://legalinstruments.oecd.org/en/instruments/OECD-LEGAL-0449. 113 Danielle Keats Citron & Frank Pasquale, The scored society: Due process for automated predictions, 89 WASH. L. REV. 1 (2014). Graham Sewell, Nice work? Rethinking managerial control in an era of knowledge work, 12 ORG. 685 (2005). Catherine Tucker, Privacy, Algorithms, and Artificial Intelligence, in The Economics Of Artificial Intelligence: An Agenda (Ajay Agrawal, Joshua Gans & Avi Goldfarb eds., 2017).

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management and decision-making which means that algorithms can be used to use employee output more competently, so that they spend quality working time on crucial and qualitative tasks. National Laws in relation to the GDPR have caused the following common positions. First of all, human dignity is recognized as a protected fundamental right within the workplace. Second, the involvement of the collective parties in the regulation or the approval of technological installations utilized as surveillance devices. It has to be taken into account that regardless of its systematic and comprehensive purposes, the GDPR exposes a weakness in dealing with datafuelled and automatically propelled decisions.114 On the one hand, the GDPR extends protection against decisions based only on automated processing, to cover not only profiling of data subjects but also any other form of automated processing,115 on the other, it is based on a three-phase system via acquisition, analysis, and application. Unquestionably, AI is valuable in terms of security, productivity, and effectiveness. Simultaneously, AI is imperceptible, even to those who are subject to the monitoring and involved in it which means that the risk is that what seems perfectly effective in the books of law, is meeting serious difficulties in chasing AI systems that are far from being comprehended and codetermined by most of the workers who rely heavily on digital gadgets. It has to be taken into account that in the era of AI and automation, machines have taken over many managerial duties and so by replacing managers with AI systems will have a negative effect on workers’ outcomes. Will workers receive the same benefits from their relationships with AI systems? What degree does the connection between AI systems and workers influence worker outcomes? Furthermore, in the era of AI and automation, the role of managers is progressively replaced by algorithms and so many organizations are now completely managed by AI technologies.116 Many key managerial roles have been taken over by machines such as assigning work tasks, evaluating workers’ performances, and matching workers and customers. Hence, Al technologies have the ability to accomplish the entire spectrum of tasks of highly qualified managers. First of all, work role identity and organizational identity are crucial determinants of identification with AI systems and identification with AI systems does boost job performance. Moreover, one challenge includes the loss of the interpersonal relationship between managers and their workers, which is often founded on identification which means that by identifying with one’s manager, the level to which the manager is encompassed in the worker’s sense of self, is vital in establishing trust 114

Lilian Mitrou, Data Protection, Artificial Intelligence and Cognitive Services: Is the General Data Protection Regulation (GDPR) ‘Artificial Intelligence-Proof’? (June 3, 2019), https://ssrn. com/abstract¼3386914. 115 Lee A. Bygrave, Automated Profiling: Minding the Machine: Article 15 of the EC Data Protection Directive and Automated Profiling, 17 Computer L. & Sec. Rev. 17 (2001). 116 Robert, L. P., Pierce, C., Marquis, E., Kim, S., Alahmad, R. 2020. “Designing Fair AI for Managing Employees in Organizations: A Review, Critique, and Design Agenda,” HumanComputer Interaction, https://doi.org/10.1080/07370024.2020.1735391.

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and rapport. Furthermore, it seems that workers who strongly identify with their managers reach higher levels of organizational commitment, augmented job satisfaction, and improved job performance. In addition, identification also increases the influence of managers on worker’s creativity for the reason that identifying with managers inspires persons as concerns socioemotionally, psychologically, and behaviorally to grow emotional rapport with them and with the company, which further improves work results. Consequently, replacing managers with AI systems will have a negative influence on workers’ results and so it is uncertain if workers receive the same benefits from their dealings with AI systems. It seems that workers develop an identity with the platform itself, and that identity promotes their job performance.117 In other words, it seems that AI systems influence work outcomes, such as well-being and satisfaction. AI encompasses the capability of a machine to achieve cognitive functions associated with human minds, such as perceiving, reasoning, learning, interacting with the environment, problem solving, decision-making, and even establishing originality.118 It is worth mentioning here that AI firstly emerged as an earliest version of expert systems, but today’s AI embodies the capacity to act and think rationally and function autonomously in a manner similar to humans such as speech assistants (Alexa, Siri), online labor platforms (MTurk, Uber), and recommendation systems (Amazon, Netflix).119 Moreover, the development of AI technologies has led to the appearance of a new generation of digital platforms exploiting the power of cloud computing and machine learning to offer new options for persons “to sell their labor” through interactions with the platforms. In addition, according to Online Labour Index, the operation of these platforms has grown by 21% from 2016 to 2018120 and the Online Labour Index (OLI) gives an online gig economy equivalent of conventional labor market statistics by measuring the supply and demand of online freelance labor across states and occupations by tracking the number of projects and tasks across platforms in real time. OLI indicates how the utilization of online labor diverges over time and across nations and occupations. Furthermore, Al technology is integrated into individuals’ everyday lives and so online labor platforms stand in for the role of managers by deploying AI techniques which means that the straightforward organizational influence on workers has been replaced by AI systems. The so-called gig-economy has been widely reported on and it is a booming industry, with more and more people flocking to work for companies like Uber. Uber is a US-based company operating a worldwide network of taxi services in many

117 Rasha Alahmad, Lionel Robert, Artificial Intelligence (AI) and IT identity: Antecedents Identifying with AI Applications Completed Research, https://ssrn.com/abstract¼3601724. 118 Rai, A., Constantinides, P., and Sarker, S. 2019. “Editor’s Comments: Next-Generation Digital Platforms: Toward Human–AI Hybrids,” MIS Quarterly, (43:1), pp. iii–ix. 119 Savić, D. 2019. “Are we ready for the future? Impact of Artificial Intelligence on Grey Literature Management,” Conference on Grey Literature and Repositories, (15), pp. 7–15. 120 https://ilabour.oii.ox.ac.uk/online-labour-index/.

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countries displaying many characteristics of MNEs, embracing integrated transnational management, a unified business format, and a network of overseas subsidiaries, used principally to organize its tax affairs.121 The San Francisco-based company insists its app is simply a platform to connect self-employed drivers with customers and so drivers enter into individual contracts with passengers to offer driving services. Drivers were under no obligation to use the app at any time, or to accept trips offered to them and Uber does not pay them for any services. On the other hand, the employment tribunal and later the court of appeal found Aslam and Farrer were not self-employed contractors, but were “workers” under the Employment Rights Act 1996 because of the level of control that Uber has had over those drivers, through its policies, systems of rating drivers, setting routes and encouraging them to take fares. Moreover, the majority of the Court of Appeal upheld the Employment Appeal Tribunal decision, so that Uber drivers are workers entitled to the minimum wage and paid holidays.122 Furthermore, Uber has argued that it is only a technology platform, bringing together self-employed drivers with clients, and not a taxi-services enterprise. Under EU law, Uber taxi services are considered as transportation services subject to member state regulation.123 Nonetheless, national courts are divided over whether the drivers are employees entitled to labor protection or independent contractors. Uber defended the claim with the assertion that the claimants were not “workers,” and so were not afforded protection under the Acts and Regulations. Besides, the Employment Tribunal decided that the claimants were employed as “workers,” the Tribunal decided that when the app was on and a driver was working, they would fit the definition of working under a “worker” contract, as defined by the legislation. The Supreme Court Justices will bear in mind the arguments they have heard, and will hand down a judgment and if they dismiss the appeal then Uber will be faced with having to provide their drivers with paid leave and a series of other benefits. However, if the appeal is granted, then thousands of drivers will be left without any real statutory protection in their work. In addition, Uber could be regulated either as a taxi operator or as an information technology services company which means that the latter description presents an avenue for innovative flexibility in the development of Uber’s business model, but this must not come at the price of fair competition and responsible corporate behavior from all taxi firms. Furthermore, Uber is undoubtedly an “investor” entitled to protection under international investment agreements (IIAs)124 raising issues regarding the legitimacy of host country regulation. Hence, the host country has to Brian O’Keefe and Marty Jones “How Uber plays the tax shell game”, Fortune.com, Oct. 22, 2015. 122 Uber BV v Aslam [2018] EWCA Civ 2748. 123 Case C-434/15 Asociación Profesional Élite Taxi v Uber Systems Spain SL ECLI:EU: C:2017:981. 124 Enikő Horvath and Severin Klinkmüller, “The concept of ‘investment’ in the digital economy: The case of social media companies,” Journal of World Investment and Trade, vol. 20 (2019), pp. 590–609. 121

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make certain that its regulatory controls over Uber are IIA compliant. At the minimum, a nondiscriminatory approach is needed; a risk that arises out of Uber’s prospective to weaken existing market structures generates a backlash of protectionist regulation. Taking into account the accountability of corporations to respect human rights applies not just to the services they offer and the products they sell, but also to their internal operations, flawed hiring processes have noteworthy consequences for the right to freedom from discrimination, the right to equal pay for equal work, and the rights to freedom of expression and association. Thus, there is a need for intentional intervention in the programming of AI machine learning technologies since it is expected AI will reproduce the existing systemic patterns of bias and prejudice exhibited in the training data and so leading AI-based hiring systems to ascertain metrics for assessing candidates that echo structural biases rather than the objective factors of real-world employment performance. To that extent, it is the governmental responsibility to evaluate and address the distributive consequences of AI. The institutions and processes of democratic government are the only ones with the legitimacy to determine what distribution of benefits and burdens across society is fair by adopting their role in guiding society through the alterations that lie ahead in the AI era. AI as risk reallocator technology has long held the promise of making work more effective by augmenting productivity, incentivizing “good” work behaviors, finding and abolishing bottlenecks which means that AAI spots streamline processes and eliminates superfluous work. Algorithmic technologies have altered the landscape of staffing and scheduling, but transferring the burden of demand uncertainty from the company to the worker. AAI staffing algorithms will assimilate many more sources of data predicting customer demand and linked staffing levels which means that workers will go through a variety of “just-in-time” scheduling practices that initiate significant instability into the lives of low-wage workers.125 While corporations will lower labor costs because of reduced risk of overstaffing, the burden of the uncertainty of demand is shifted to the workers subject to scheduling systems. On the other hand, a well-equipped worker will cope easily to all AAI alterations via the utilization of the technology itself not needing to travel around. AI-driven systems extend the practice into new kinds of workplaces. Platformbased firms like Uber use AI to promote driver productivity, using fleet-wide supply/ demand predictions and behavioral-economic “nudges” to tailor incentives toward profit maximization. On the other hand, AI systems not rightfully utilized may erode trust, dignity, and any sense of privacy from work, reduce workers’ decisional autonomy, and so opening the door to labor exploitation by driving workers to the

125 Daniel Schneider and Kristen Harknett, “Schedule Instability and Unpredictability and Worker and Family Health and Wellbeing,” Washington Center for Equitable Growth Working Paper (Sept. 2016), http://cdn.equitablegrowth.org/wp-content/uploads/2016/09/12135618/091216WPSchedule-instability-and-unpredictability.pdf.

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limits of their physical and mental capabilities. Thus, an AAI system has to prevent any manipulation of the system by all the involved parties.

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Artificial intelligence is an existential component of modern finance by making finance cheaper, faster, larger, more accessible, more profitable, and more effective in many ways but presenting serious risks and limitations. Moreover, momentous progresses in financial technology made possible in part by artificial intelligence in various aspects of the financial sector and so trading, financial research, risk analysis, wealth management, investment banking, and other areas of the financial sector have been dramatically altered by the rise of artificial intelligence and have been profitenhancing and socially beneficial. AI has lowered the costs of capital for businesses and entrepreneurs, expanded the types of financial resources to a broader and more diverse population of investors, and made it easier for consumers to bank and invest but presenting serious risks. In fact, the fintech revolution has generated great benefits for the wider economy, embracing broader access to capital, fairer lending standards, better investment advice, and more secure transactions.126 Furthermore, a fundamental shift in markets from human-based trading to highly automated electronic trading is observed. Nowadays, liquidity is now much more possible outside of traditional exchanges and information and low communication costs have expanded markets. It has to be taken into consideration that AI programs are limited by their underlying code and their capacity to fully and accurately capture all that is happening in the marketplace because uncertainty, risk, repercussions, and economic spirits in finance can never be perfectly coded, modeled, mitigated, or eliminated since human unpredictability is beyond precise mathematical modeling and computer coding. To that extent, the law is not a machine and the judges are not machinetenders which means that there never was and there never will be a body of fixed and predetermined rules alike for all not mentioning that AI codification of the law as conventionally has applied is a difficult task because of the flexibility needed for its implementation and enforcement. Furthermore, deal negotiations, board presentations, regulatory actions, and legal interpretations significant to finance are done largely among humans in ways that smart machines are unable to do on a consistent basis. Hence, artificial intelligence still does not possess all of the competences of the human brain, with its trillions of synaptic connections and billions of neurons. In other words, AI cannot fully decipher a simple common human phrase like “it’s fine,” let alone the many nonverbal expressions that humans use among one another which means that financial artificial intelligence is limited by the incapacity of its

126

William Magnuson, Regulating Fintech, 71 Vand. L. Rev. 1167, 1169 (2018).

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programming to fully capture the breadth, depth, and diversity of all that is occurring in a marketplace. It is worth noting that discriminatory data and algorithmic bias represent a set of critical risks and limitations linked with financial AI regarding the integrity and utilization of the inspiring informational inputs that are the fuel of artificial intelligence systems. AI systems initially need large quantities of data to teach the programs to recognize certain patterns and make certain predictions uncovering valuable new insights and observations from big data. Since data collection has now become ubiquitous, the benefits of algorithmic decision making outweigh their costs.127 On the other hand, AI can aggravate past social harms with its enormous processing powers and the appearance of novel objectivity since discriminatory humans are related to the decisions. In addition, risks are inherited in AI systems built with data reflecting harmful past biases against some groups of situations and underlying data contexts and applications are being selected and coded by flawed humans with biases, and prejudices.128 It is worth noting that the math-powered applications powering the data economy are based on choices made by human beings and so if the underlying data on which an algorithm relies is itself biased, incomplete, or discriminatory, the decisions it makes have the prospective to reproduce inequality. Data and algorithmic bias represent one of the main categories of risks and limitations inherent in the rise of financial artificial intelligence and so a growing financial industry more reliant on artificial intelligence means that policy-makers, regulators, and other key stakeholders have to be aware about the prospective harms arising out of data and algorithmic bias. In recent years, there have been noteworthy and serious movements to fight algorithmic bias in finance and beyond.129 Finally, it is vital that new technology does not bring forth old discriminations but establishing neutrality, and objectivity and so data models should not discriminate when neutral factors act as “proxies” for sensitive characteristics like race or sex. In addition, another group of risks and limitations linked to the rise of financial AI includes the rise of virtual threats and cyber conflicts in the financial system. In 2019, IBM found that the finance and insurance industry was the most attacked industry in terms of cybersecurity threats which means that a high-tech industry faces even more of the same types of cyber challenges confronted by most traditional technology firms.130 The virtual threats against the financial industry are both external and internal. First, in terms of external virtual threats, financial corporations and financial industry

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Sonia K. Katyal, Private Accountability in the Age of Artificial Intelligence, 66 UCLA L. REV. 54, 59 (2019). 128 Virginia Eubanks, Automating Inequality: How High-Tech Tools Profile, Police, And Punish The Poor (2018). 129 Algorithmic Just. League, https://www.ajlunited.org. 130 IBM, X-FORCE Threat Intelligence Index 4 (2019), https://www.securindex.com/downloads/ 8b9f94c46a70c60b229b04609c07acff.pdf.

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regulators are vigilant against foreign nation-states, competitors, terrorist organizations, and cybercriminals. Thus, the financial industry is confronted with a diverse matrix of external threats from state and nonstate actors, some seeking profit while others seeking simply to sow chaos using hacks planned to steal billions of dollars, obtain valuable information, and instigate disruptions.131 It seems that computer predators are funded by rich criminal syndicates and even nation-states, and their objectives are far more ambitious132 embracing further political objectives. Furthermore, financial corporations and regulators must defend against internal threats, such as rogue employees, corporate spies, and misguided contractors and so IBM has estimated that human errors account for a noteworthy percentage of all data and cybersecurity breaches.133 It is not technologically possible to prevent those authorized to access data from misusing it and tracing hackers134 and so the financial industry’s heavy reliance on technology like artificial intelligence has exaggerated the influence of internal threats. In a financial marketplace where millions of euro automatically move in fractions of a second with or without a keystroke, the internal threat is one of the most dangerous menaces to the financial industry. Additionally, both internal and external virtual threats have grown more hi-tech and complex to detect and thwart.135 Financial deep fakes, financial fake news, and many other ways to disrupt and maneuver the markets will expand in a marketplace that becomes ever more reliant on AI technologies.136 As the financial industry becomes more like the technology industry, with its greater adoption of artificial intelligence, it will face growing and serious risks regarding virtual and other technology-oriented threats but it is obvious that technological tools will come to defense of AI. In reality, innovative, pernicious threats continue to increase as finance becomes more reliant on automated systems powered by artificial intelligence that may be particularly susceptible to bad or false data as nation-states and nonstate actors weaponize technological tools like artificial intelligence that have made so much progress in the financial system possible against the system itself. A growing reliance on artificial intelligence and other forms of technology in the financial industry intensifies intertwined systemic risks linked to size, speed, and interconnectivity. Additionally, the growing complexity of technology augments the risks of serious financial accidents. 131

Shane Harris, @War: The Rise Of The Military-Internet Complex 103–22 (2014). Mark Bowden, Worm: The First Digital World War 48 (2011). 133 IBM GLOB. TECH. SERVS., IBM Security Services 2014 Cyber Security Intelligence Index 3 (2014), http://media.scmagazine.com/documents/82/ibm_cyber_security_intelligenc_20450.pdf. 134 U.S. DEP’T OF DEF., The Department Of Defense Cyber Strategy 9 (2015), https://archive. defense.gov/home/features/2015/0415_cyber-strategy/final_2015_dod_cyber_strategy_for_web. pdf (“Criminal actors pose a considerable threat in cyberspace, particularly to financial institutions, and ideological groups often use hackers.”). 135 Sealed Indictment, United States v. Murgio, 15 Cr. 769 (S.D.N.Y. Nov. 5, 2015), ECF No. 14; Sealed Indictment, United States v. Shalon, 15 Cr. 333 (S.D.N.Y. June 2, 2015), ECF No. 3. 136 Brad Smith & Carole Ann Browne, Tools And Weapons: The Promise And The Peril Of The Digital Age 69–76 (2019). 132

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New financial technologies generate and complicate systemic risks and so as financial artificial intelligence gains more ground in the financial industry, institutions that are crucial to the system owing to their large data holdings for the purpose of financial artificial intelligence become too significant to the system to fail which means that the systemic risk of size denotes not only the size of a financial institution’s balance sheet but also the size of its databases. It is characteristic that wider adoption of financial advanced AI leads to even faster financial speeds generating a systemic risk of “too fast to save,” whereby disruptions, bad acts, and other events destabilize the financial system before any corrective or preventive measures are taken. Hence, automated trading systems offer enormous economies of scale and scope in managing large portfolios, but trading errors accumulate losses at the speed of light before they are discovered and corrected by human oversight. To that extent, during times and trading periods of distress, panic, and confusion, high-speed automated programs running on AI spread greater volatility and calamity by rapidly increasing or decreasing liquidity. Thus, unprecedented volatility and flash crashes in the financial markets are made possible by new technology like artificial intelligence. It has to be taken into account that the prevalence of financial artificial intelligence exaggerates the systemic risk of “too linked to fail,” whereby actions, errors, and failings activate destabilization across the financial system as a consequence of the interconnectivity of corporations, irrespective of their value or size. Moreover, this systemic risk is troubling owing to the highly intermediated and interconnected character of modern finance and the use of similar and interdependent artificial intelligence programs by many corporations within the financial industry. As a result of tight links and interoperative programs, one or a few corporations generate dangerous cycles of volatility and spillover consequences that destabilize the whole financial system. It is worth mention here that high-speed corporations mimic one another’s trading strategies, and in times of crisis increase price swings.137 Furthermore, the rise of financial artificial intelligence exacerbating systemic risk and its ascent also leads to financial accidents which means that complex technology systems, like the artificial intelligence-driven ones that are at the heart of our financial system, are vulnerable to breakdowns and accidents. Hence, as financial artificial intelligence grows more prevalent, “normal financial accidents” grow more frequent within the financial system and so both the New York Stock Exchange and the Nasdaq have suffered serious malfunctions that halted hundreds of billions of dollars worthiness of trading for hours during otherwise normal trading sessions.138 In total, the proliferation of artificial intelligence in finance augments the dangers of

137 Chris Brummer & Yesha Yadav, Fintech and the Innovation Trilemma, 107 GEO. L.J. 235 (2019). 138 Nathaniel Popper, The Stock Market Bell Rings, Computers Fail, Wall Street Cringes, N.Y. TIMES (July 8, 2015), https://www.nytimes.com/2015/07/09/business/dealbook/new-yorkstock-exchange-suspendstrading.html.

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systemic risks and key financial accidents not mentioning the hazards and challenges that it may instigate for the entire financial system going forward. It has to be taken into consideration that the development of AI in finance and beyond is one of the most significant developments for law, finance, and society in the coming years and decades. Nonetheless, as financial artificial intelligence continues to grow and change, its potential risks and limitations are following harming and hindering individual as well as societal progress. It is worth noting that financial product developers and financial service providers have long engaged statistical and probability models along with predictive analytics to forecast performance and so fintech is not entirely new. Nevertheless, sometimes a change in quantity amounts to a change in quality which is taking place in fintech now, as the inclusion of increasingly comprehensive databases, along with new methods of analysis, means that many fintech companies deploy algorithms to predict the probability of repayment and profitability of customers.139 Moreover, financial markets’ automation substitutes gradually objective, analytical, modelbased assessments of a borrower’s creditworthiness for direct human evaluations irrevocably tainted by bias and subject to the cognitive limits of the human brain. Nonetheless, even if they do happen, such advances may violate other legal principles.140 Money transmission services offer vital peer-to-peer platforms for those who lack access to conventional bank branches or personal checking and savings accounts. Taking into account that credit is an imperative resource for generating economic stability, evaluating the integration of automated decision-making algorithms in credit markets raises concerns including the transparency and accountability obligations of fintech companies, the social welfare outcomes of allowing fintech companies to operate in credit markets, and the necessity of effective state and federal supervision of fintech companies’ pricing, marketing techniques, and structuring of credit products.141

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Anthony Saunders & Marcia Cornett, Financial Institutions Management: A Risk Management Approach 97–103 (9th Ed. 2017). 140 Odia Kagan, Finnish DPA Orders Company to Modify Automated Creditworthiness Assessment, Improve Disclosures, Fox Rothschild (Apr. 27, 2019), https://dataprivacy.foxrothschild.com/ 2019/04/articles/european-union/finnish-dpa-orderscompany-to-modify-automated-creditworthi ness-assessment-improve-disclosures/ (reporting that the Finnish Data Protection Authority ordered a firm to “provide individuals with information on the logic behind the decision-making process, its relevance to the credit decision and its consequences for the borrower” pursuant to the General Data Protection Regulation’s provisions guaranteeing a right to an explanation). 141 Adam Levitin, Pandora’s Digital Box: The Promise and Perils of Digital Wallets, 166 U. PA. L. REV. 305, 335 (2018). Brian T. Melzer, The Real Costs of Credit Access: Evidence from the Payday Lending Market, 126 Q.J. ECON. 517, 522 (2011) (indicating that loans give families flexibility “in managing consumption over time” yet may create “substantial debt service burdens”). Christine L. Dobridge, For Better and for Worse?: Effects of Access to High Cost Consumer Credit (Fed. Reserve Bd., Working Paper No. 2016-056, 2016), https://www. federalreserve.gov/econresdata/feds/2016/files/2016056pap.pdf (“[P]ayday credit access improves well-being for households in distress by helping them smooth consumption. In periods of temporary

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Artificial Intelligence and the Future of Finance Emerging credit intermediaries capitalize on a new generation of consumers and their preference for using mobile devices to shop, make payments, and manage finances and so these platforms gain a portion of fees linked with scoring, lending, and servicing a massive consumer debt market.142 Will fintech corporations adopting AI technology successfully expand access to credit markets and promote the inclusion of unbanked or underbanked consumers? It could be said that the advent of AI technology can improve legacy banking, catalyze new market infrastructure, and spur development benefiting consumers. Nevertheless, regulators must be unable to engage in effective supervision of fintech companies’ algorithms. Rather than improve regulatory oversight, the OCC decision to permit non-depository fintech companies to function as special purpose nonbank entities needs evaluation and supervision of whether fintech companies live up to their undertaking and so otherwise consumers exposed to perilous predatory behavior. In addition, the OCC’s intervention undermines state regulatory authorities’ efforts to supervise consumer lending markets, impose long-standing consumer protections, and enforce measures designed to mitigate predatory inclusion against fintech companies. Anyway, the OCC is actively monitoring risks to the federal banking system and is working closely with other federal banking regulators. It has to be taken into account that the introduction of AI into the lending process is expected to have an overall positive influence on the capability of objectively low-risk borrowers to access credit by having positive impacts on the enjoyment by these individuals of the right to an adequate standard of living, the right to work, and the right to education, as access to credit is an enabler of these economic and social rights. Moreover, the introduction of AI into the lending procedure is having a positive effect on the right to equality and nondiscrimination due to the fact that AI-based algorithms take into account a wide variety of data sources and so augmenting the ability of well-qualified individuals from marginalized communities to access credit by defeating the “thin-file” problem. Conclusively, it is possible that AI-based decision-making algorithms in the financial sector will adversely influence the freedoms of opinion, expression, and association because in an AI era where “all data is credit data,” persons feel deterred from expressing certain points of view or correlating with others, out of fear that an algorithm may use their behavior against them in the financial environment.143 The new generation of artificial intelligence and data science (AIDS), in particular data science, machine learning, and deep learning, is driving the era of data and intelligence-driven economics and finance.

financial distress—after extreme weather events like hurricanes and blizzards—I find that payday loan access mitigates declines in spending on food, mortgage payments, and home repairs. In an average period, however, I find that access to payday credit reduces well-being.”). 142 Mark DeCambre, U.S. Consumer Debt Is Now Above Levels Hit During the 2008 Financial Crisis, MARKETWATCH (June 25, 2019), 143 Simina Mistreanu, “Life Inside China’s Social Credit Laboratory,” Foreign Policy, April 3, 2018, https://foreignpolicy.com/2018/04/03/life-inside-chinas-social-credit-laboratory/.

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References 1. Waldman, A. E. (2019). Power, process, and automated decision-making. Fordham Law Review, 88, 613. 2. Rogers, B. (2019). Beyond automation: The law & political economy of workplace technological change 24 (Roosevelt Institute Working Paper). 3. Brummer, C., & Yadav, Y. (2019). Fintech and the innovation trilemma. Georgetown Law Journal, 107, 235. 4. Schneider, D., & Harknett, K. (2016, September). Schedule instability and unpredictability and worker and family health and wellbeing. Washington Center for Equitable Growth Working Paper. 5. Equivant (2018). COMPAS classification. 6. Decarolis, F., & Rovigatti, G. (2018). From mad men to maths men: Concentration and buyer power in online advertising. Working paper. 7. Croft, J. (2016, December 5). The relentless advance of the super-intelligent attorney. Financial Times. 8. Liker, J. K. (2004). The toyota way: 14 management principles from the world’s greatest manufacturer. 9. Fjeld, J., Achten, N., Hilligoss, H., Nagy, A. C., & Srikumar, M. Principled artificial intelligence: Mapping consensus in ethical and rights-based approaches to principles for AI. Research Publication No. 2020. 10. Ross, K. K. A. (2017). Understanding the 12 technological forces that will shape our future. Penguin. 11. Kraus, S., Palmer, C., Kailier, N., Lukas Kallinger, F., & Spitzer, J. (2018, September 20). Digital entrepreneurship: A research agenda on new business models. 12. Fairfax, L. M. (2019). From apathy to activism: The emergence, impact, and future of shareholder activism as the new corporate governance norm. Boston University Law Review, 99, 1301–1314. 13. Makridakis, S. (2017). The forthcoming Artificial Intelligence (AI) revolution: Its impact on society and firms. Futures, 90, 46–60. 14. Obrová, V., & Smolíková, L. (2013). The role of risk management in successful project management. International Business Information Management Association Conference, IBIMA 2013. 15. OECD. (2019). Artificial intelligence in society. Paris: OECD. 16. OECD. (2019, May 12). Recommendation of the council on artificial intelligence. OECD/ LEGAL/0449. 17. Beck, R., Avital, M., Rossi, M., & Thatcher, J. B. (2017). Blockchain technology in business and information systems research. Springer. 18. Noble, S. U. (2018). Algorithms of oppression: How search engines reinforce racism. 19. Danckert, S., & Yeates, C. (2018, November 21). CBA accused of board minutes criminal breach. The Sydney Morning Herald. 20. Murray, S. (2018, November 15). Algorithms tame ambiguities in use of legal data. Financial Times. 21. Mistreanu, S. (2018, April 3). Life inside China’s social credit laboratory. Foreign Policy. 22. Gillis, T. B., & Spiess, J. L. (2019). Big data and discrimination. The University of Chicago Law Review, 459.

Part II

Law of Artificial Intelligence

Chapter 7

Econometric Analysis on AI Economy

7.1

Econometric Background

The digital economy is central part of transformation based on the diligence of cyberspace-based technologies and more recently the utilization of blockchain and AI technologies has pushed the digital economy to a different level. FDI is a source of private external finance to the host economy contributing to the state’s capital formation in the form of corporate tax revenues, permitting transfer of technology and innovation, and so tolerating the host economy to catch up with technological and managerial enhancements absorbed by the rest of the economy for fuller productivity influence. Furthermore, inward FDI, OFDI, and exports are often related.1 FDI is relocating productive capability from the source state to the host state.2 Moreover, FDI leads to noteworthy benefits for home economies. Some of these are direct, while some are indirect, or result from spillovers. Thus, policymakers should enhance the absorptive aptitude of home economies to maximize OFDI’s benefits, particularly by generating ties between OFDI companies and other national businesses, to spread capacities acquired overseas all the way through home economies. It has to be taken into account that regulatory intervention has to strike a balance between preserving the benefits accruing to home countries from OFDI on the one hand, and diminishing any distortive consequences certain OFDI incentives may have for international investment, competition, and trade, on the other. OFDI amplifies home country productivity, innovation, and exports by permitting corporations to grow bigger than they would have if restrained to functioning in their home

Karl P. Sauvant et al., “Trends in FDI, home country measures and competitive neutrality,” in Yearbook on International Investment Law & Policy 2012-2013 (New York: OUP, 2014); World Bank, Global Investment Competitiveness Report 2017/2018 (Washington, DC: World Bank, 2017). 2 G Zekos, MNE’s in 21st Century, 2016. Nova Science Publications. New York USA. www. novapublishers.com. 1

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 G. I. Zekos, Economics and Law of Artificial Intelligence, https://doi.org/10.1007/978-3-030-64254-9_7

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market and so yielding profits from economies of scale and lower production costs, furthering efficiency by contributing to home country companies’ competitiveness in international markets,3 and advancing knowledge transfers. Nonetheless, employing financial and fiscal measures to incentivize OFDI could have significant drawbacks embracing risks of abuse and negative consequences on competitive neutrality.4 In the face of fierce global competition for inward FDI, countries increasingly rely on tax breaks to lure investors. However, tax incentives affect investors’ location decisions only marginally and so they bear on the final stage of the site-selection process, when investors are wavering among like options, and after deliberating other competitive features, such as political stability, regulatory quality, and market opportunities.5 It seems that policy-makers overvalue the role of tax incentives in swaying investors and beyond the budgetary implications, tax incentives carry other costs and risks, comprising rent-seeking, tax evasion, high administrative burdens, market distortions, and retaliatory behavior spurring a “race-to-the-bottom.”6 Hence, fiscal, legal, and institutional challenges are pronounced and so governments face a demanding policy dilemma: how can they design and implement incentives strategically, in a way that expands their value for money diminishing the risks.7 The European Commission advocated a proposal for regulating the screening of FDI flows into the EU based on Article 207(2) of the Treaty on the Functioning of the EU (TFEU).8 In the context of the EU ordinary legislative procedure, the EU institutions reached a political agreement concerning the proposal.9 Furthermore, the global economy is changing, driven by production and consumption revolutions, technological change is shifting the mode goods and services are produced, surfacing a fourth industrial revolution affecting society at large.10

3 World Bank, Global Investment Competitiveness Report 2017/2018 (Washington, DC: World Bank, 2018). 4 Karl P. Sauvant and Clémence Boullanger, “An international framework to discipline outward FDI incentives?,” Columbia FDI Perspectives, No. 265, Nov.18, 2019. 5 Ana Teresa Tavares-Lehmann et al., eds., Rethinking Investment Incentives: Trends and Policy Options (New York: CUP, 2016). 6 Maria R. Andersen, Benjamin R. Kett and Erik von Uexkull, “Corporate tax incentives and FDI in developing countries” in World Bank, Global Investment Competitiveness Report 2017/2018: Foreign Investor Perspectives and Policy Implications (Washington DC: World Bank, 2018). 7 Hania Kronfol and Victor Steenbergen, “Evaluating the costs and benefits of corporate tax incentives: Methodological approaches and policy considerations,” FCI In Focus, World Bank, 2020. 8 Fabrizio Di Benedetto, “A European Committee on foreign investment?” Columbia FDI Perspectives, no. 214, December 4, 2017. 9 Proposal for a regulation of the European Parliament and of the Council establishing a framework for screening of foreign direct investments into the European Union (COM(2017)0487 – C8-0309/ 2017 – 2017/0224(COD)). Committee on International Trade, Provisional Agreement Resulting From Inter-institutional negotiations 6.12.2018. 10 Schwab, K. (2016). The Fourth Industrial Revolution. Geneva: The World Economic Forum.

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It is worth mentioning here that the recent European Commission guidelines concerning the implementation of stricter FDI screening mechanisms to protect sensitive assets from foreign takeovers during the crisis are applicable only to healthcare and research establishments. Will applicability of the policy to all sectors have a deterrent influence on FDI inflows? FDI screening is on the rise, and the EU has joined in via the adoption of the FDI Screening Regulation (Regulation) in March 2019 and applicable as of October 11, 2020, harmonizes member states’ tactics to FDI screening by offering certain substantial and procedural cornerstones for national screening mechanisms.11 Its most important element is the proposal of a common screening criterion: FDI “likely to affect security or public order” but the setup of FDI screening mechanism and the grounds remain the sole responsibility of member states. Cyberspace is transforming the global operations of MNEs, making a physical presence overseas less fundamental and so lightening the footprints of MNEs’ international production.12 Moreover, digitalization disturbs the operational nexus between foreign sales and foreign assets, which means that not only do highly digital MNEs gather more foreign sales with less foreign assets, there is in fact no link between the two, signifying that commercial presence in foreign markets has no evidence bearing on international investment choices. Furthermore, the digitalization course that is going on around the globe is aiding the transfer of the majority of social affairs from the real world to cyberspace, which means firstly “digitization” of existing public institutions and creation of their “digital counterparts,” and secondly there is the emergence of new ones in cyberspace previously nonexistent features caused by AI technology progress.13 FDI de-democratization means that the light international footprint of digital MNEs, in addition to their hunt for knowledge and technology assets, fuels a reversal of the democratization trend in FDI. Most digital MNEs are from developed countries, in particular, the United States. FDI financialization means that a light international footprint, with decreased investment in tangible assets and large volumes of international sales, giving digital MNEs strong liquidity and high spending aptitude, stipulates productive ground for financial and tax-driven patterns of investment. In other words, distinctive characteristics of the asset composition of digital and tech MNEs are the limited share of tangible assets matched with intangibles and the large share of cash and cash equivalents.

11

FDI Screening Regulation, (EU) 2019/452, Mar. 19, 2019, Recital (2). Chen, W., and F. Kamal (2016). “The impact of information and communication technology adoption on multinational firm boundary decisions”. Journal of International Business Studies, 47 (5): 563–576. 13 S.P. Bortnikov, Robots liability or liability for products? In S. Ashmarina, A. Mesquita, M. Vochozka M. (Eds.), Digital Transformation of the Economy: Challenges, Trends and New Opportunities. Advances in Intelligent Systems and Computing, 908 (pp. 32-41). Cham: Springer (2020). 12

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With blockchain technology becoming mainstream companies and entrepreneurs are utilizing aggressive strategies in securing IP rights of the blockchain technology supporting their advancement. The blockchain web platform, supporting Bitcoin technology, is a unique technology being the next disruptive technology spanning across a vast range of industries and so blockchain technology advances an alternative instrument to traditional multiplayer economic models for performing transactions without the obligation of relying on third parties. In other words, blockchain technology, widely known for its cryptocurrency application, is the technology that permits unrelated users who have never met and will never do, to reach a consensus and handle a transaction with undyingly record trusted data, without a central authority that controls, approves, or otherwise inspects the transactions in place.14 Blockchains are outlined as append-only databases and so these distributed ledgers trust is enforced by the rules running the network.15 Although the technology itself is still very new, blockchain-based solutions hold great promises in applications such as bitcoins, Ethereum, and plenty of other decentralized applications radically advance operating efficiencies in some sectors while entirely unsettling others and so cryptocurrencies and smart contracts exemplify this prospective.16 Nonetheless, blockchain technology is being used for many reasons than as merely a digital currencies platform and so blockchain can be used for transactions from selling tangible goods and intangible assets, for instance, copyrighted works.17 Furthermore, blockchain platforms make possible the utility of digital contracts: by companies, persons, or complex autonomous systems, for instance, AI systems; insurance agreements; sales contracts and more. Due to blockchain unique features, such as being open-ledger, encrypted, decentralized, and accessible—blockchain technology has a distinctive prospective to substitute registration systems either governmental, such as land registration systems, copyright, trademark and patent registration, or any other registration

14 David Schatsky et al., Blockchain and the five vectors of progress, DELOITTE (September 28, 2018), https://www2.deloitte.com/insights/us/en/focus/signals-for-strategists/value-ofblockchain-applicationsinteroperability.html. 15 Jean-Luc Verhelst, Bitcoin – The Blockchain and beyond, 2017. 16 Michèle Finck, Blockchain – Regulation and governance in Europe, Cambridge University Press, 2019. 17 Bernard Marr, 30+ Real Examples of Blockchain Technology in Practice, FORBES (May 14, 2018, 01:38 AM), https://www.forbes.com/sites/bernardmarr/2018/05/14/30-real-examplesof-blockchain-technology-inpractice/#7d3e2ae3740d. Jessie Williams, Is Blockchain-Powered Copyright Protection Possible?, Bitcoin Magazine (Aug. 9, 2016, 12:00 PM EST), https:// bitcoinmagazine.com/articles/is-blockchain-powered-copyright-protection-possible1470758430/ (Examples of services using blockchain technology to register and protect against copyright infringement, such as, Blockai, Pixy, TinEye, Ascribe, Mediachain, and Proof of Existence. A “public decentralized ledger like blockchain is ideal for cataloging and storing original works of art, documents, manuscripts, photographs and images, away from central authority. Even if the copyright service ceases to exist, there will still be a verifiable copy of an original work on the blockchain.”).

7.1

Econometric Background

295

system.18 Furthermore, Blockchain platforms are utilized by the public, for instance in the case of Bitcoin or by private entities, such as banks, construction corporations, supermarkets, and distributors.19 In addition, Accenture builds blockchain solutions translating insurance processes into blockchain-ready procedures that insert trust into the system and RiskBlock provides proof-of-information.20 Blockchain is accessed by anyone globally with an Internet connection and digital currencies that employ blockchain technology have a global transactional reach without the prerequisite to go through a central authority. Thus, blockchain generates a trusted, secure ledger through a mix of peer-to-peer technology, cryptographic purposes, distributed storage, and decentralized consensus mechanisms.21

18

Marie Huillet, KodakOne Blockchain Beta Test Sees $1 Mln in Content Licensing Claims, COINTELEGRAPH.COM (Jan. 08, 2019), https://cointelegraph.com/news/kodakoneblockchainbeta-test-sees-1-mln-in-content-licensing-claims (KodakONE Image Rights Management Platform is an image copyright protection, monetization, and distribution platform secured via blockchain technology.). Jaclyn Wishnia, Blockchain Technology: The Blueprint for Rebuilding the Music Industry?, 37 Cardozo Arts & Ent. L.J. 229, 246–248 (2019) (discusses use cases of blockchain technology in the music industry). 19 What Is Smart Contracts Blockchain And Its Use Cases in Business, EXISTEK (May 23, 2018), https://existek.com/blog/what-issmart-contracts-blockchain-and-smart-contracts-use-cases-in-busi ness/ (Axa provides first flight delay insurance using smart contracts. Ascribe uses smart contracts for intellectual property management, allowing direct interaction with entities that want to use the intellectual property and customization of conditions and terms for the use of one’s work. A consortium between Walmart, IBM, and Tsinghua University is developing smart contract blockchain technology for supply chain management that tracks orders from the suppliers to the customers.). 20 ETHEREUM, https://www.ethereum.org/ (Ethereum provides a “decentralized platform that runs smart contracts,” as well as management of its own cryptocurrency called Ether.). Anna Baydakova, A Top-5 US Hospital is Exploring Blockchain for Patient Data, COINDESK (December 5, 2018, 10:00 AM UTC), https://www.coindesk.com/a-top-5-us-hospital-is-exploringblockchain-forpatient-data Bernard Marr, 35 Amazing Real World Examples of How Blockchain is Changing Our World, FORBES (Jan 22, 2018, 12:28 AM), https://www.forbes.com/sites/bernardmarr/2018/ 01/22/35-amazing-real-world-examples-of-howblockchain-is-changing-our-world/#6cd9cd5243b5 (Provides examples of how Dubai, Estonia, and South Korea are using blockchain technology, as well as other governmental blockchain tools, for example, Govcoin.). 21 Wright, Aaron and De Filippi, Primavera, Decentralized Blockchain Technology and the Rise of Lex Cryptographia (March 10, 2015). Available at SSRN: https://ssrn.com/abstract¼2580664 Nolan Bauerle, What is the Difference Between Public and Permissioned Blockchains?, Coindesk, https://www.coindesk.com/information/what-is-the-difference-between-open-and-permissionedblockchains. Robert McDonald et al., How Blockchain Could Radically Alter Global Finance, Kellogg Insight (Jan. 3, 2018), https://insight.kellogg.northwestern.edu/article/how-blockchaincould-radically-alter-global-finance.

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Econometric Analysis on AI Economy

AI and IPRs

IPR granted by patents, copyrights, trademarks, etc., perform a significant role in promoting innovation and sustaining economic growth by allowing their holders to keep out, for a limited amount of time, other parties from the remuneration arising from new knowledge and from the commercial use of innovative products and developments based on that new knowledge. Anyway, patents have already been approved for technologies that are developed as additions to the basic building blocks of the Blockchain platform.22 It has to be taken into account that in copyright law, AI has been treated much the same way, the question to be answered is whether AI-generated works should be owned by the AI itself, or a prospective copyright battle between the human programmer who produced the AI and the end user. How does the use of AI in the creative process influence the validity of ownership claims affirmed by any of these human players in computer-generated works? Samantha Fink Hedrick23 argues that “the humans who create and use AI retain sufficient control over the AI’s ‘decisions’ that the use of AI does not constitute a barrier to human ownership of copyrightable computer-generated works. The ‘original intellectual conceptions’ represented in computer-generated works are still those of the humans creating and controlling the algorithms used in the creative process, not those of the AI itself. Like a camera, AI functions merely as a tool of creation, not as a sentient ‘author.’” How are claims of ownership that result from the use of algorithms to create copyrightable works solved? It has to be taken into consideration that as AI seemingly becomes more “human,” it is difficult to distinguish works that were produced by humans and those formed by machines, which mean that questions of ownership over works produced using technology also become more difficult.24 It has to be taken into consideration that one of the biggest difficulties to a human claiming copyright25 in the outputs of an algorithm is the notion of unpredictability, embracing both randomness and the capacity of computers to surpass human capabilities.26 In the end, considering that deep neural networks and other complex AI are capable of astonishingly multifaceted computations, and maybe in some 22

Barry R. Lewin, Blockchain and patents, 2018 WL 2090215. Samantha Fink Hedrick, I “THINK,” THEREFORE I CREATE: Claiming Copyright in the Outputs of Algorithms,: https://ssrn.com/abstract¼3367169. 24 Tim Moynihan, How Google’s AI Auto-Magically Answers Your Emails, Wired (Mar. 17, 2016), https://www.wired.com/2016/03/google-inbox-auto-answers-emails/. Heather Kelly, Google’s Plans to Use AI to Help the Blind, CNN (May 11, 2018), http://money.cnn.com/2018/05/11/ technology/google-lookout-app/index.html. Torres v. North American Van Lines, 135 Ariz. 35 (1982). 25 David Lehr & Paul Ohm, Playing with the Data: What Legal Scholars Should Learn About Machine Learning, 51 U.C. Davis L. Rev. 653 (Dec. 2017). 26 AlphaGo, Deep Mind (last visited May 16, 2018), https://deepmind.com/research/alphago/; https://www.ibm.com/watson/; 23

7.2

AI and IPRs

297

situations even surpass the aptitudes of their human programmers, if the human claiming authorship cannot display that he/she could visualize and control the output, it would be difficult to claim that it really denotes his “original intellectual conceptions.” Furthermore, the proprietary character of algorithms, and their tendency to be protected as trade secrets, affects anyone other than the owner of the algorithm attempting to apprehend and question anything from bias and discrimination in employment or sentencing decisions to copyright infringement.27 To that extent, this deficiency of transparency makes it difficult to explain which parts of the decision came from the algorithm, which came from the data, and which came from the programmer’s selections in setting the parameters. Nonetheless, the selections made by a programmer in producing, constructing, and training an algorithm that would generate these same stories go far beyond simple contest rules, which means that the computer has no selection but to go along the rules given to it by its programmer, and it can learn only from the data fed to it by the programmer or user. It is argued that the EU copyright framework poses obstacles to machine learning by generating bias in the way machines can be trained.28 Moreover, the EU copyright rules currently in force leave the question of whether copyrighted data can be used to train artificial intelligence in a “legislative limbo.” On the other hand, the new Directive on Copyright in the Digital Single Market announces the text and data mining exception that offers a solution to this problem.29 Primarily the new mandatory exception aimed at research institutions and was limited to the rationales of scientific research. In the end, any use of copyrighted information by business, embracing start-ups, to generate algorithms on the basis of which an artificial intelligence can be trained can still be labelled infringing in certain Member States if right holders reserve the use of their work for text and data mining reasons, possibly overruling the granted permission to use by the directive.30 Besides, in the United States such use would most likely rate as fair—particularly, as a transformative use for a different reason than the original pursuing a socially valuable

27 Amanda Levendowski, How Copyright Law Can Fix Artificial Intelligence’s Implicit Bias Problem, 93 Wash. L. Rev. 579 (2018). 28 C. Geiger, G. Frosio and O. Bulayenko, “Crafting a Text and Data Mining Exception for Machine Learning and Big Data in the Digital Single Market”, in: X. Seuba, C. Geiger and J. Pénin (eds.), Intellectual Property and Digital Trade in the Age of Artificial Intelligence and Big Data (CEIPI/ ICTSD Series on “Global Perspectives and Challenges for the Intellectual Property System”, Volume 5, Geneva/Strasbourg, 2018), p. 95. C. Manara, Senior Copyright Counsel at Google, “Copyright and Big Data – A View from the Industry”, Speech delivered at the CEIPI/BETA/I3PM conference, Intellectual Property and Digitalization: Challenges for Intellectual Property Management, Strasbourg, 4 May 2017. 29 C. Geiger, G. Frosio and O. Bulayenko, “Text and Data Mining in the Proposed Copyright Reform: Making the EU Ready for an Age of Big Data?”, 49(7) IIC 814 (2018). 30 Directive (EU) 2019/790 of the European Parliament and of the Council of 17 April 2019 on copyright and related rights in the Digital Single Market and amending Directives 96/9/EC and 2001/29/EC, OJ L 130, p. 92 (hereafter the Directive on Copyright in the Digital Single Market).

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purpose.31 It is worth noting that one example of such fair use is the websites that fight fake news on the basis of machines trained to recognize fake data.32 Thus, the condition that the user should not be reserved by right holders so as to benefit from the exception leaves the practice of commercial text and data mining for non-research purposes uncertain in the EU.33 It is argued that algorithms will make businesses more competent and more objective, but they do not remove or even always diminish the likelihood that things will sometimes go wrong.34 Undeniably, the speed and geographic reach of algorithmic practices indicate that when things do go wrong, they can go really wrong for a lot of people in a lot of places at once. It is worth noting that the problem is that the law is not set to address corporate liability when the “thinking” behind corporate misconduct has been discharged to automated systems. Under current law, corporate liability entails evidence of a culpable corporate mental state: purpose to discriminate, knowledge of competitors’ prices, or irresponsibility in operating a vehicle.35 The legal doctrine for attributing mental states to companies defines corporate mental states in terms of employee mental states and so the collective knowledge doctrine permits courts to aggregate employee knowledge, and the control group test only reinforces the current legal fact that corporate mental states must derive from employee mental states. Moreover, when businesses using algorithms misbehave in ways that, from the outside, look just as purposeful, knowing, or reckless, current liability doctrines do not apply.36 What the law needs is a doctrinal framework for extending its conception of the corporate mind beyond the employees whose shoes algorithms are coming to fill. R. Hilty, “Big Data: Ownership and Use in the Digital Age”, and C. Geiger, G. Frosio and O. Bulayenko, “Crafting a Text and Data Mining Exception for Machine Learning and Big Data in the Digital Single Market”, both in: X. Seuba, C. Geiger and J. Pénin (eds.), Intellectual Property and Digital Trade in the Age of Artificial Intelligence and Big Data (CEIPI-ICTSD publications series “Global Perspectives and Challenges for the Intellectual Property System”, number 5, June 2018). 32 M.M. Maack, “Whoops! EU’s Copyright Reforms Might Suck for AI Startups” [Blog post], 21 March 2017, available at: https://thenextweb.com/eu/2017/03/21/whoops-eus-copyrightreforms-mightsuck-for-ai-startups/#.tnw_rEMp0AMY. 33 C. Geiger, G. Frosio and O. Bulayenko, “The Exception for Text and Data Mining (TDM) in the Proposed Directive on Copyright in the Digital Single Market – Legal Aspects”, Centre for International Intellectual Property Studies (CEIPI) Research Paper No. 2018-02; available at SSRN: https://ssrn.com/abstract¼3160586. 34 Sonia K. Katyal, Private Accountability in the Age of Artificial Intelligence, 66 UCLA L. Rev. 54, 65 (2019) (“Algorithms hold tremendous value. Big data promise significant benefits to the economy . . . .”). 35 United States v. Athlone Indus., Inc., 746 F.2d 977, 979 (3d Cir. 1984) (“Robots cannot be sued.”); U. Pagallo, Killers, Fridges, and Slaves: A Legal Journey in Robotics, 26 AI & SOC’Y 347, 349 (2011) (“[C]ommon legal standpoint excludes robots of any kind from criminal responsibility.”). 36 Sherman Antitrust Act, 15 U.S.C. § 1; United States v. Wise, 370 U.S. 405, 416 (1962) (“[A] corporate officer is subject to prosecution under s 1 of the Sherman Act whenever he knowingly participates in effecting the illegal contract, combination, or conspiracy.”). 31

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AI and IPRs

299

Psychologists and philosophers have addressed a related set of issues about the human mind contending that the traditional understanding of the human mind as limited by the boundaries of the skull is too restrictive. Moreover, the so-called extended mind thesis asserts that the human mind reaches beyond the brain to comprehend external cognitive aids—like diaries or cell phones—that facilitate the brain do its work, which means that if an individual can as easily “recollect” a phone number by checking “his phone’s memory bank as by checking his neurological memory bank, his mind may, according to the thesis, extend to aspects of her phone.”37 It is argued that the law could and should accept that corporate minds extend to algorithms fulfilling roles that were once dominated only by human employees, which means that by extending the corporate mind in this manner, the law could bring corporate accountability into the twenty-first century. It has to be taken into consideration that corporations are just fictional agents which means that the best answer to algorithmic corporate misconduct would commence by stimulating the law’s commitment to corporate culpability.38 It could be said that taking into account that the ordinary corporation is a “person” for rationales of the adjudicatory processes, then in the same way corporations using AI are responsible for all actions.39 Thus, the law could and should acknowledge that corporate minds extend to algorithms accomplishing functions that were once dominated only by human employees, which means that by extending the corporate mind in this respect, the law could bring corporate responsibility into the level needed for an operative digital economy.40 In line, the law’s fiction of corporate personhood is a decisive motivation for adjusting extended mind theory from natural persons to the corporate context which is based on the fictionalizing assumption that corporations are people with minds like ours and so algorithms can materialize part of the corporate mind, not that they have minds of their own but companies can be directly liable for the matters they adopt and do, even when they use AI to make those decisions and take those actions.41 Moreover, companies that use algorithms to fulfill employee functions have to be considered as having the same mental states that companies using employees to fulfill those functions would have which means

37

Andy Clark & David Chalmers, The Extended Mind, 59 ANALYSIS 10 (1998). Amy J. Sepinwall, Guilty by Proxy: Expanding the Boundaries of Responsibility in the Face of Corporate Crime, 63 HASTINGS L.J. 411, 428 (2012). John Hasnas, The Centenary of a Mistake: One Hundred Years of Corporate Criminal Liability, 46 AM. CRIM. L. REV. 1329 (2009). 39 Sierra Club v. Morton, 405 U.S. 727, 742–43(1972). 40 Saul Levmore, Interest Groups and the Problem with Incrementalism, 158 U. PA. L. REV. 815, 816–17 (2010) (“Leading commentators encourage incrementalism. . . Most of the encouragement is directed at judges, but the arguments used in favor of incrementalism are equally applicable to regulators and legislators.”. 41 Andy Clark, Coupling, Constitution, and the Cognitive Kind, in THE EXTENDED MIND 81, 83 (Richard Menary, ed., 2010). 38

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Econometric Analysis on AI Economy

that companies will not have less liability risk by offloading operations from employees to algorithms.42 It is worth noting that there has been a growth in the number of blockchain patent applications43 filed at the United States Patent and Trademark Office (USPTO) for the past several years. Basically, Blockchain is a technique for storing information.44 Considering that when studying patent infringement issues, typically, a single party’s actions are analyzed against patent claims to ascertain whether or not there was infringement, Blockchain encompasses multiple parties, where one party does not implement all functions of the Blockchain, but rather multiple parties work together in a decentralized character, permitting peer-validation processes. In other words, such unique attributes of blockchain possibly give rise to divided infringement issues that implicate multiple parties. Thus, patent claims define the scope of the subject matter of the patented invention.45 The Federal Circuit noted in NTP46 that “Under section 271(a), the concept of ‘use’ of a patent method or process is fundamentally different from the use of a patented system or device.” Correspondingly, in a Blockchain network, an agreement is made among the peers of a blockchain network by following the blockchain protocol (in carrying out the steps), for a common reason to validate and store data on a distributed ledger, with the peers having a financial interest for that function and the peers have an equal right of control in the decision course of a blockchain network (peer consensus). Consequently, a party may be found liable if it accomplishes all the steps or executes

42

Thomas Beardsworth & Nishant Kumar, Who to Sue When a Robot Loses Your Fortune, BLOOMBERG (May 5, 2019), https://www.bloomberg.com/news/articles/2019-05-06/who-tosuewhen-a-robot-loses-your-fortune (“Robots are getting more humanoid every day, but they still can’t be sued.”). 43 Gurneet Singh, Are Internet-Implemented Applications of Block-Chain Technology PatentEligible in the United States?, 17 CHI.-KENT J. INTELL. PROP. 356, 357 (2018). Antonio M. DiNizo Jr., From Alice to Bob: The Patent Eligibility of Blockchain in A Post-Cls Bank World, 9 Case W. Reserve J.L. Tech. & Internet 1, 27–28 (2018) (Patent eligibility of improvements.). 44 SB-838, Senate Bill No. 838 Corporate records: articles of incorporation: blockchain technology, California Legislative Information (Sept. 28, 2018), https://leginfo.legislature.ca.gov/faces/ billTextClient.xhtml?bill_id¼201720180SB838; Inayat Chuadhry, The Patentability of Blockchain Technology and the Future of Innovation, American Bar Association, LANDSLIDE MAGAZINE March/April 2018 issue, https://www.americanbar.org/groups/intellectual_property_law/publica tions/landslide/2017-18/marchapril/patentability-blockchain-technology-future-innovation/. 45 Jingyuan Luo, Shining the Limelight on Divided Infringement: Emerging Technologies and the Liability Loophole, 30 Berkeley Tech. L.J. 675 (2015) (The paper provides a good historical overview of the history of the development of divided infringement analysis up to the Akamai decision, but not the most updated analysis.). 46 NTP, Inc. v Research in Motion, Ltd. 418 F.3d 1282, 1317 (Fed. Cir. 2005). Finjan v Sophos Inc., 244 F. Supp. 3d 1016, 1047-48 (ND Cal 2017), Limelight Networks, Inc. v. Akamai Techs., Inc., 134 S. Ct. 2111 (2014).

7.2

AI and IPRs

301

a few steps, and controls another party’s performance of the other steps of a Blockchain patent.47 Concerning system claims of blockchain patents, the patentee may uphold system claims infringement against those that contain a Blockchain component. For system claims infringement analysis, it was stated in NTP that “the use of a claimed system under section 271(a) is the place at which the system is exercised and beneficial use of the system obtained.” Additionally, in Centillion,48 the Federal Circuit addressed infringement of a system claim where system components were in the possession of more than one actor,49 reinforcing that the NTP analysis applies even when different parties involve different elements of the system. Likewise, it was distinguished in Intellectual Ventures that a party must gain from each element of the claimed system, not generally from the system as a whole. Furthermore, NTP established the meaning of use as putting the system into use on behalf of a party, and the meaning of service demanding both the control of the system and the receipt of benefits through the control, which means that in situations where various parties execute different modules, the infringement analysis for system claims based on whether each party exercises control over the system and whether each party acquires advantages from using the system. Likewise, for blockchain technology, numerous parties put into operation different components, and the parties get remunerations from using the system. The control of the system falls under the power of the parties as well and so blockchain technology may be subject to prospective divided infringement matters under system claims as well.50 It has to be considered that innovations in technology were followed by a wave of patent wars, resulting in many, high-value patent litigations. Even though the pioneers of the Internet opted not to patent the basic building blocks of the Internet technology, the TCP/IP protocol, following innovations interrelated to technological breakthroughs in numerous aspects of the Internet procured patent protection. Moreover, the semiconductor industry followed the same pattern and so lately, the smartphone industry generated a patent war across the globe with industry actors spending billions of dollars in dispute over their intellectual property assets such as the infamous Apple vs. Samsung case.51 To that extent, with the blockchain technology having the potential to change all kinds of industries, the industry actors are

47

Akamai Techs, Inc. v. Limelight Networks, Inc., 797 F.3d 1020, 1022 (Fed. Cir. 2015) (en banc) (“Akamai V”). 48 Centillion Data Sys., LLC. V. Qwest Communications International Inc., 631 F.3d 1279, 1284 (Fed. Cir. 2011). 49 Intellectual Ventures LLC v Motorola Mobility LLC, 870 F.3d 1320, 1329 (Fed. Cir. 2017). Nalco Co. v. Chem-Mod, LLC, 2018 WL 1055851 (February 27, 2018) (citing Travel Sentry, Inc. v. Troff, 877 F.3d 1370, 1381 (Fed.Circ. 2017)). Raptor LLC. V. Odebrecht Construction Inc., CA No. 17-21509, 2017 WL 3776914 (August 31, 2017, S.D. Fla). 50 Jason N. Mock, Federal Circuit Breathes More Life into Divided Infringement, Foley & Lardner LLP (January 16, 2018), https://www.foley.com/federal-circuit-breathes-more-life-into-dividedinfringement-01-16-2018/. 51 “Samsung Wins U.K. Apple Ruling Over ‘Not As Cool’ Galaxy Tab”. Bloomberg.

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foreshadowing an analogous blockchain patent war succeeding and have started taking proactive measures to alleviate future consequences. In the past, to protect firms against threats from patent trolls, industry actors founded a mutual defense alliance called the LOT Network.52 Moreover, the LOT53 network establishes a kind of legal protection to its members by needing the members to put conditions on their patents so that those patents cannot be used against another member in the network, principally when the patents are sold to patent trolls. On the other hand, in the Open Invention Network (OIN) the members of the patent pools are protected against patent suits by getting patents and licensing them freely to its members who agree to contribute their patents to the pool.54 Lately, the Chamber of Digital Commerce constructed the Blockchain Intellectual Property Council (BIPC) to advocate innovation in the field of Blockchain by dealing with IP issues associated with the technology combating patent trolls from impeding innovation, by offering Blockchain-specific patent information and exploring different intellectual property protection measures.55 While Blockchain technology engenders more interest, the private industry is taking practical measures in placing Blockchain-specific patent defense measures to stimulate innovation in the field, such as the formation of the BIPC, and the development of Blockchainspecific standards.56 Concisely, blockchain is a key breakthrough in technology that has unlimited possibilities across a vast variety of industries displaying features that permit it to be combined with other major technological advancements, such as IoT and Artificial Intelligence (AI). It is worth noting that with the industry concentrated on procuring intellectual property rights in the blockchain technology, there is a requirement for a system diminishing a prospective patent minefield analogous to what the industry has faced in the past.57

52

Jeff John Roberts, As Blockchain Grows, Companies Look to Avert a Patent War, FORTUNE. COM (June 19, 2018), http://fortune.com/2018/06/19/blockchain-patent/. 53 https://lotnet.com (including tech giants such as Microsoft, Tencent, Facebook, Oracle, Tesla, Amazon, and General Motors) Caroline Coker Coursey, Battling the Patent Troll: Tips for Defending Patent Infringement Claims by NonManufacturing Patentees, 33 AM. J. TRIAL ADVOC. 237 (2009). 54 Open Invention Network (OIN), https://www.openinventionnetwork.com/ (Created in 2005, OIN seeks to protect its members against suits for using Linux, which is an open-source operating system, by acquiring patents and licensing them freely to its members who agree to contribute their patents to the pool.). 55 Chamber of Digital Commerce, Chamber of Digital Commerce Forms the Blockchain Intellectual Property Council, (Mar. 16, 2016), www.digitalchamber.org/chamber-digital-commerce-formsblockchain-intellectualproperty-council/. 56 Catherine Saez, Blockchain-Related Patents On Exponential Rise, Lawyer Says. Targets? China, US, UK, Intellectual Property Watch, Thomson Reuters (January 12, 2018), 2018 WL 386375. 57 Francesco Corea, The convergence of AI and Blockchain: what’s the deal?, MEDIUM.COM (December 1, 2017), https://medium.com/@Francesco_AI/the-convergence-of-ai-and-blockchainwhats-the-deal-60c618e3accc.

7.3

Econometric Outcomes Zekeuipr Index

303

It could be said that there is a convergence of AI and blockchain, for instance, smart contracts on blockchain powered by AI, blockchain powered with AI for decreasing power consumption, etc.58 AI has influenced IPRs attribution that has been taken into account in shaping our IPR indexes. Finally, the results based on our indices show not only a positive and real importance of IPRs upon attracting FDI but also IPRs are significant in a reverse way in contributing to GDP Growth.

7.3 7.3.1

Econometric Outcomes Zekeuipr Index Introduction

A large sample of 79 countries has been assembled for Zekos’ research59 in producing IPR indexes. All the national laws in force at the end of 2012 of the 79 investigated jurisdictions have been examined and used in the raking of the various factors taken into account in constructing the ZEKIPR6 index.60 It is worth mentioning that the construction of our IPR indices relies on: (a) Membership in IPR International Treaties, (b) Patent rights, (c) Copyrights, (d) Trademark rights, and (e) Legal System & Property Rights Rating (Rank) of countries. ZEKIPR1 ¼ Index of Membership in IPR International Treaties + index of patent rights + index of copyright+ index of trade-mark rights + lr2 Legal System & Property Rights Rating (Rank) of countries (Economic Freedom of the World: 2011 Annual Report, Area Economic Freedom Ratings (Ranks), 2009) ZEKIPR1a ¼ Membership in International Treaties + INDEX OF PATENT RIGHTS + INDEX OF COPYRIGHT+ INDEX OF TRADE-MARK RIGHTS + LR3 Legal System & Property Rights Rating (Rank) of countries (Economic Freedom of the World: 2012 Annual Report, Area Economic Freedom Ratings (Rankings) for 2010) ZEKIPR6 ¼ Membership in International Treaties + INDEX OF PATENT RIGHTS + INDEX OF COPYRIGHT+ INDEX OF TRADE-MARK RIGHTS + Enforcement legal rating (Legal Tradition (Rule of law) + Legal Education+ Economic level)

58 Oscar W, AI on Blockchain – What’s the catch?, HACKERNOON.COM (October 14, 2018), https://hackernoon.com/how-cortex-brings-ai-on-the-blockchain-86d08922bb2a. 59 G. Zekos, “Constructing a New IPRs index,” 4 Web JCLI (2012), http://webjcli.ncl.ac.uk/2012/ issue4/zekos4.html; G. Zekos, “Law & Economics of IPRs,” 2016 Nova Science Publications, New York, www.novapublishers.com; G. Zekos, “IPRs’ impact upon FDI,” 2013 PhD Thesis, Economics Department, University of Peloponnese, Tripoli, Hellas www.uop.gr. 60 G. Zekos, “IPRs Protection and Their Impact Upon FDI, GDP Growth & Trade,” 2013 Scholar’s Press, Www.Scholars-Press.Com, www.morebooks.de Germany.

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To that extent based on the national laws in force at the end of 2012 of the 28 investigated the EU jurisdictions have been examined and used in the raking of the various factors taken into account in constructing zekeuipr1, zekeuipr2, zekeuipr4, zekeupat1, zekeucopy1, and zekeumark1 indices concerning IPR protection in the European Union. zekeuipr1 ¼ Membership in International Treaties + INDEX OF PATENT RIGHTS + INDEX OF COPYRIGHT+ INDEX OF TRADE-MARK RIGHTS + Enforcement legal rating (Legal Tradition (Rule of law) + Legal Education+ Economic level) Enforcement legal rating (Legal Tradition (Rule of law) + Legal Education+ Economic level) is made according to this author’s evaluation. zekeupat1 ¼ INDEX OF PATENT RIGHTS + Enforcement legal rating (Legal Tradition (Rule of law) + Legal Education+ Economic level) zekeucopy1 ¼ INDEX OF COPYRIGHT+ Enforcement legal rating (Legal Tradition (Rule of law) + Legal Education+ Economic level) zekeumark1 ¼ INDEX OF TRADE-MARK RIGHTS + Enforcement legal rating (Legal Tradition (Rule of law) + Legal Education+ Economic level) Moreover, in order to have not only this author’s estimation concerning the enforcement of IPR laws but also an additional evaluation of the real enforcement of IPRs protection and so a comprehensive de jure evaluation, we utilize the Legal and Political Environment (LP) component of the International Property Rights Index prepared by Property Rights Alliance (PRA). Judicial Independence, Rule of Law, Political Stability, and the Control of Corruption are the sub-components constituting the Legal and Political Environment (LP) that shows the environment in which the national laws on IPRs are applicable and enforceable. As a result, our index is reformed as follows: zekeuipr2 ¼ Membership in International Treaties + INDEX OF PATENT RIGHTS + INDEX OF COPYRIGHT + INDEX OF TRADE-MARK RIGHTS + Enforcement rating ((Legal and Political Environment (LP) (Judicial Independence + Rule of Law + Political Stability + Control of Corruption) (International Property Rights Index | 2012 Report)) zekeuipr4 ¼ Membership in International Treaties+ INDEX OF PATENT RIGHTS + INDEX OF COPYRIGHT + INDEX OF TRADE-MARK RIGHTS + Legal System & Property Rights Rating (Rank) of countries (Economic Freedom of the World: 2014 Annual Report, Area Economic Freedom Ratings (Rankings) for 2012) It is worth mentioning here that changes in IPR national laws of the examined jurisdictions and rating of the examined legal systems will bring changes in the index (ZEKIPR61—zekeuipr1, zekeuipr2, zekeuipr4) and so it is feasible to have regularly 61

Id.

7.3

Econometric Outcomes Zekeuipr Index

305

updated ZEKIPR/ZEKEUIPR indexes. Successful protection of intellectual property rights depends both on the existence of intellectual property protection laws and the enforcement of the laws. Therefore, all future changes in intellectual property laws and their enforcement environment will continue to cause an alteration to our indices which means a need for nonstop updating of the IPR indices such as Zekeuipr3. Zekeuipr3 ¼ Membership in International Treaties + INDEX OF PATENT RIGHTS + INDEX OF COPYRIGHT + INDEX OF TRADE-MARK RIGHTS + Enforcement rating ((Legal and Political Environment (LP) (Judicial Independence + Rule of Law + Political Stability + Control of Corruption) (International Property Rights Index | 2014 Report)). It is worth mentioning that some countries are not contained in the 2014 IPRI and so their ranks are taken from the 2013 IPRI. Presently there is no real alteration of the IPRs protection by the investigated countries

7.3.2

A Linear Model

A linear model is in the form Y i ¼ β0 þ

p X j¼1

β j X ij þ εi ,

where, for the ith case, Yi is the response variable, Xi, 1, . . ., Xi, p are p regressors, and εi is a mean zero error term. The quantities β0, . . .βp are unknown coefficients, whose values are determined by least squares. In detail, the following are the econometric models that are used in our investigation in order to find the impact of IPR and GCI upon attracting FDI inflows-FDI outflows, trade, and GDP growth: FDIit ¼ b0 þ b1 zekeuipr1=zekeuipr2=zekeuipr4=Zekieuipr3it þ b2 Tradeit þ b3 Inflationit þ b4 GDPGRit þ uit ð7:1Þ Tradeit ¼ b0 þ b1 zekeuipr1=zekeuipr2=zekeuipr4it þ b2 GDPGRit þ b3 Inflationit þ uit

ð7:2Þ

GDPGRit ¼ b0 þ b1 zekeuipr1=zekeuipr2=zekeuipr4 þ b2 Tradeit þ b3 Inflationit þ b4 FDIit þ uit

ð7:3Þ

GDPGRit ¼ b0 þ b1 zekeuipr1=zekeuipr2=zekeuipr4 þ b2 Tradeit þ b3 Inflationit þ uit

ð7:3aÞ

FDIit ¼ b0 þ b1 GCIit þ b2 Tradeit þ b3 Inflationit þ b4 GDPGRit þ uit

ð7:4Þ

306

7

Table 7.1 Shapiro-Wilk W test for normal data

Variable zekeuipr1 zekeuipr2 zekeuipr4 zekieupr3 gdpgr5y

Obs 28 28 28 28 28

Econometric Analysis on AI Economy

W 0.92767 .96877 0.97146 0.97871 0.96493

V 2.184 0.943 0.862 0.643 1.059

z 1.608 –0.121 –0.306 –0.909 0.118

FDIit ¼ b0 þ b1 zekipr6it þ b2 Tradeit þ b3 Inflationit þ b4 GDPGRit þ b5 instit þ uit

Prob > z 0.05387 0.54804 0.62031 0.81840 0.45295

ð7:5Þ

FDIit ¼ b0 þ b1 zekipr6it þ b2 Tradeit þ b3 Inflationit þ b4 GDPGRit þ uit ð7:6Þ FDIit ¼ b0 þ b1 zekipr6it þ b2 GDPit þ b3 Tradeit þ b4 Inflationit þ uit

ð7:7Þ

FDIit ¼ b0 þ b1 GCIit þ b2 GDPit þ b3 Tradeit þ b4 Inflationit þ uit

ð7:8Þ

The following are the variables that are utilized in our regression analysis concerning the impact of IPR on FDI, GDP growth, and Trade in comparison: Concerning models the first thing to notice is the two subscripts: i to denote the ith individual country and t to denote the tth time period. The analysis is focused on FDI inflows. FDI inflows FDIin2012 ¼ US Dollars at current prices and current exchange rates in millions 2012 UNCTADstat, b0 is the intercept and (GDP GR 2012 ¼ GDP growth (annual %) 2012 World Bank, INF2012¼ Inflation, consumer prices (annual %), 2012 World Bank, TRADE2012 ¼ Trade (% of GDP), 2012 World Bank and GCI. Using the Global Competitiveness Index 2011–2012 (GCI) are the explanatory variables. To that extent, the swilk performing the Shapiro-Wilk W test for normality is illustrated in Table 7.1. It is worth mentioning that GDP refers to the market value of all final goods and services produced within a country in a given period. Global FDI has grown faster than world GDP partly as a result of policy changes in recipient countries. Inflation (macro stability) is known to be negatively associated with FDI in the pull factors literature.62 A negative correlation between interest rate and outward FDI exists given that comparatively low-interest rates associated with a country’s capital abundance decreases the opportunity cost of capital and augments the profitability of investments abroad. Predictions about the relationship between FDI and trade critically depend on whether FDI is vertical or horizontal. Theories on horizontal FDI63 foresee a negative relationship whereas theories on vertical FDI64 foresee a

Lin, S., Ye, H., “Does inflation targeting make a difference in developing countries?,” Journal of Development Economics, 89(1), 118–123 (2009). 63 Markusen, J., “Multinationals, multi-plant economies, and the gains from trade,” Journal of International Economics, Volume 16, Issues 3–4 (1984). 64 Helpman, E., “A Simple Theory of International Trade with Multinational Corporations,” Journal of Political Economy 92(3), 451–471 (1984). 62

7.3

Econometric Outcomes Zekeuipr Index

307

. corr gdpgr5y inf5y trade5y zekeuipr1 zekeuipr2 zekeuipr4 gci12 zekeupat1 zekeucopy1 zekeumark1 (obs=28) gdpgr5y gdpgr5y inf5y trade5y zekeuipr1 zekeuipr2 zekeuipr4 gci12 zekeupat1 zekeucopy1 zekeumark1

1.0000 0.0453 0.1747 -0.1406 -0.0023 -0.0551 0.2063 -0.0745 -0.0474 -0.0700

inf5y trade5y zekeui~1 zekeui~2 zekeui~4

1.0000 -0.0019 -0.3720 -0.4182 -0.3127 -0.5314 -0.6277 -0.6385 -0.6474

1.0000 -0.3034 -0.1712 -0.2583 0.0811 -0.0498 0.0223 -0.0081

1.0000 0.9502 0.9516 0.6360 0.7105 0.6645 0.6761

1.0000 0.9780 0.7252 0.6779 0.6518 0.6602

1.0000 0.6396 0.5917 0.5633 0.5795

gci12 zekeup~1 zekeuc~1 zekeum~1

1.0000 0.8343 0.8810 0.8703

1.0000 0.9728 0.9759

1.0000 0.9904

1.0000

Fig. 7.1 Collinearity correlation of the variables

positive relationship. On the other hand, the relationship between trade and FDI is not a straightforward one. While trade connected with cross-border vertical integration may enhance the outflow of FDI by providing incentives of cost reduction, intraindustry trade may inhibit FDI that is seeking economies of scale.65

7.3.3

Empirical Results

We start with correlation of the variables utilized in our econometric models in order to avoid multicollinearity. As a result, we avoid using variables with a high collinearity in order to avoid high variance inflation factor (VIF) calculating the VIF for the independent variables in the linear model (see Fig. 7.1). Moreover, Collin—calculates the VIF and other multicollinearity diagnostics and when this number is larger than 100, the estimates may have a fair amount of numerical error (see Fig. 7.2). 1. We begin our investigation with model 1(FDIit ¼ b0 + b1 zekeuipr1/zekeuipr2/ zekeuipr4it + b2 Tradeit + b3 Inflationit + b4 GDPGRit + uit) using OLS standardized coefficients or beta coefficients and the results (Coef. 3.33, 3.09, 3.62/ 4.43**, 3.72*, 3.95*) show the significance of zekeuipr1, zekeuipr2, zekeuipr4 for the 2012 and 5-years reference regarding foreign direct investment, net inflows (% of GDP) (see Table 7.2) indicating the significance of IPRs for the short-term reference in relation to a single year impact on attracting FDI inflows. It is worth mentioning here that the zekeuipr1, zekeuipr2, zekeuipr4 beta regarding FDI inflows are (.431419, .4061434, .4416674/, .6002161, .4555029, .4665177).

65 Goldar, B.N and R. Banga, “Impact of trade liberalization on foreign direct investment in Indian industries,” ARTNeT Working Paper Series, No. 36, June 2005.

308

7 . collin (obs=28)

Econometric Analysis on AI Economy

gdpgr5y inf5y trade5y zekeuipr1

Collinearity Diagnostics SQRT RVariable VIF VIF Tolerance Squared ---------------------------------------------------gdpgr5y 1.04 1.02 0.9609 0.0391 inf5y 1.18 1.09 0.8470 0.1530 trade5y 1.14 1.07 0.8751 0.1249 zekeuipr1 1.31 1.14 0.7640 0.2360 ---------------------------------------------------Mean VIF 1.17 Cond Eigenval Index --------------------------------1 3.7544 1.0000 2 0.9911 1.9463 3 0.1641 4.7830 4 0.0896 6.4721 5 0.0007 71.4269 --------------------------------Condition Number 71.4269 Eigenvalues & Cond Index computed from scaled raw sscp (w/ intercept) Det(correlation matrix) 0.7391 .

Fig. 7.2 Multicollinearity diagnostics

2. We continue our investigation with model 1 [FDIit ¼ b0 + b1 zekeuipr1/ zekeuipr2/zekeuipr4it + b2 Tradeit + b3 Inflationit + b4 GDPGRit + uit] by using OLS standardized coefficients or beta coefficients and robust standard errors and so the results (Coef. 4.65**, 4.33**, 4.46**/4.65***, 4.33***, 4.46***) illustrate the significance of zekeuipr1, zekeuipr2, and zekeuipr4 for 10 years reference regarding foreign direct investment, net inflows (% of GDP) (see Table 7.3) indicating the significance of IPRs for the long-term reference on attracting FDI inflows. It is worth mentioning here that the zekeuipr1, zekeuipr2, and zekeuipr4 beta regarding FDI inflows are (.6474946, .5455602, .5419349). Moreover, regressions of model 1 [FDIit ¼ b0 + b1 zekeuipr1/zekeuipr2/ zekeuipr4it + b2 Tradeit + b3 Inflationit + b4 GDPGRit + uit] using a three-stage least squares regression and robust regression (NOT robust standard errors) show the significance of zekeuipr1, zekeuipr2, and zekeuipr4 for the 5 years reference regarding foreign direct investment, net inflows (% of GDP) affirming IPRs’ impact upon FDI (see Table 7.4). Utilizing the VIF test found the variance inflation factor for the independent variables in the linear model (see Fig. 7.3). 3. We persist our investigation with model 1 [FDIit ¼ b0 + b1 zekeuipr1/zekeuipr2/ zekeuipr4it + b2 Tradeit + b3 Inflationit + b4 GDPGRit + uit] using OLS standardized coefficients or beta coefficients and the results (Coef. 8.04***, 7.55***,

–4.65 (9.138) 17 0.34 0.13

(1) logfdgiin2012 3.33 (2.016) 0.01 (0.005) –0.47 (0.392) –0.05 (0.133)

–3.38 (9.559) 17 0.31 0.09

0.00 (0.005) –0.45 (0.410) –0.09 (0.147) 3.09 (2.138)

(2) logfdiin2012

–5.60 (10.008) 17 0.34 0.12

3.62 (2.261)

0.01 (0.005) –0.51 (0.387) –0.10 (0.145)

(3) logfdiin2012

0.00 (0.004) –0.19 (0.192) 0.26 (0.154) –9.60 (5.830) 28 0.46 0.37

(4) logfdiin5y 4.43** (1.292)

0.00 (0.004) –0.22 (0.215) 0.19 (0.168) –6.09 (6.807) 28 0.35 0.24

3.72* (1.539)

(5) logfdiin5y

3.95* (1.534) 0.00 (0.005) –0.27 (0.203) 0.21 (0.166) –7.00 (6.746) 28 0.37 0.26

(6) logfdiin5y

Econometric Outcomes Zekeuipr Index

Standard errors in parentheses ***p < 0.001, **p < 0.01, *p < 0.05

Observations R2 Adj. R2

Constant

gdpgr5y

inf5y

trade5y

zekeuipr4

zekeuipr2

gdpgr2012

inf2012

trade2012

Variables zekeuipr1

Table 7.2 FDI inflows OLS Model 1 beta coefficients

7.3 309

Observations R2 Adj. R2

Constant

–10.41 (5.704) 28 0.47 0.38

(1) logfdiin10y 4.65** (1.270) 0.00 (0.004) 0.07 (0.207) –0.16 (0.183)

–8.54 (6.278) 28 0.40 0.30

–0.00 (0.005) –0.00 (0.216) –0.21 (0.191)

–0.00 (0.005) –0.00 (0.218) –0.15 (0.197) 4.33** (1.431) 4.46** (1.442) –9.03 (6.303) 28 0.41 0.31

(3) logfdiin10y

(2) logfdiin10y

–10.41* (4.235) 28 0.47 0.38

(4) logfdiin10y 4.65*** (0.946) 0.00 (0.003) 0.07 (0.171) –0.16 (0.151)

–8.54 (4.342) 28 0.40 0.30

–0.00 (0.004) –0.00 (0.162) –0.15 (0.152) 4.33*** (1.012)

(5) logfdiin10y

4.46*** (0.920) –9.03* (3.975) 28 0.41 0.31

–0.00 (0.004) –0.00 (0.169) –0.21 (0.151)

(6) logfdiin10y

7

zekeuipr4

zekeuipr2

inf10y

gdpgr10y

trade10y

Variables zekeuipr1

Table 7.3 FDI inflows OLS Model 1 beta coefficients/robust standard errors

310 Econometric Analysis on AI Economy

7.3

Econometric Outcomes Zekeuipr Index

311

Table 7.4 FDI inflows OLS Model 1 a three-stage least squares regression and robust regression (not robust standard errors) Variables zekeuipr1 gdpgr5y trade5y inf5y

(1) logfdiin5y 4.43*** (1.171) 0.26 (0.139) 0.00 (0.004) –0.19 (0.174)

zekeuipr2

(2) logfdiin5y

(3) logfdiin5y

0.19 (0.153) 0.00 (0.004) –0.22 (0.195) 3.72** (1.395)

0.21 (0.150) 0.00 (0.004) –0.27 (0.184)

zekeuipr4 Constant Observations R2 Adj. R2

–9.60 (5.284) 28 0.46 –

Fig. 7.3 Variance inflation

–6.09 (6.170) 28 0.35 –

3.95** (1.390) –7.00 (6.114) 28 0.37 –

(4) logfdiin5y 4.53** (1.416) 0.22 (0.168) 0.00 (0.005) –0.17 (0.210)

–9.99 (6.386) 28 0.42 0.31

(5) logfdiin5y

(6) logfdiin5y

0.16 (0.180) –0.00 (0.005) –0.22 (0.230) 3.90* (1.646)

0.18 (0.179) 0.00 (0.005) –0.27 (0.219)

4.16* (1.658) –7.89 (7.292) 28 0.34 0.23

–6.82 (7.280) 28 0.33 0.21

. vif Variable

VIF

1/VIF

zekeuipr4 inf5y trade5y gdpgr5y

1.20 1.12 1.11 1.03

0.835136 0.893019 0.899000 0.967370

Mean VIF

1.12

7.49***/4.43**, 3.72*, 3.95*) show the significance of zekeuipr1, zekeuipr2, and zekeuipr4 for the 5 years reference regarding foreign direct investment, net inflows and outflows (% of GDP) (Table 7.5) indicating in comparison the significance of IPR for the short-term reference impact on attracting FDI inflows and causing FDI outflows. It is worth mentioning here that the zekeuipr1, zekeuipr2, and zekeuipr4 beta regarding FDI outflows are inflows are (.6514587, .5540649, .5300298/, .6002161, .4555029, .4665177). We continue our investigation with model 1 [FDIit ¼ b0 + b1 zekeuipr1/ zekeuipr2/zekeuipr4it + b2 Tradeit + b3 Inflationit + b4 GDPGRit + uit] using OLS standardized coefficients or beta coefficients and the results (Coef. 7.51***,

Observations R2 Adj. R2

Constant

–23.57** (6.423) 28 0.77 0.73

(1) logfdiout5yav 8.04*** (1.424) 0.00 (0.005) –0.81*** (0.212) 0.18 (0.169)

–20.79* (7.920) 28 0.69 0.63

0.00 (0.005) –0.95*** (0.242) 0.10 (0.198)

–0.00 (0.005) –0.82** (0.250) 0.06 (0.196) 7.55*** (1.791) 7.49*** (1.835) –20.32* (8.067) 28 0.68 0.62

(3) logfdiout5yav

(2) logfdiout5yav

–9.60 (5.830) 28 0.46 0.37

(4) logfdiin5y 4.43** (1.292) 0.00 (0.004) –0.19 (0.192) 0.26 (0.154)

–6.09 (6.807) 28 0.35 0.24

0.00 (0.004) –0.22 (0.215) 0.19 (0.168) 3.72* (1.539)

(5) logfdiin5y

3.95* (1.534) –7.00 (6.746) 28 0.37 0.26

0.00 (0.005) –0.27 (0.203) 0.21 (0.166)

(6) logfdiin5y

7

zekeuipr4

zekeuipr2

gdpgr5y

inf5y

trade5y

Variables zekeuipr1

Table 7.5 FDI outflows/inflows OLS Model 1 beta coefficients

312 Econometric Analysis on AI Economy

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313

Table 7.6 FDI outflows OLS Model 1 beta coefficients Variables zekeuipr1 trade10y gdpgr10y inf10y

(1) logfdiout10yav 7.51*** (1.301) 0.00 (0.004) –0.19 (0.212) –0.63** (0.188)

zekeuipr2

(2) logfdiout10yav

(3) logfdiout10yav

0.00 (0.005) –0.29 (0.235) –0.61** (0.213) 7.21*** (1.546)

0.00 (0.005) –0.30 (0.235) –0.72** (0.208)

zekeuipr4 Constant Observations R2 Adj. R2

–21.49** (5.845) 28 0.80 0.76

–19.42** (6.782) 28 0.75 0.70

7.31*** (1.567) –19.76** (6.849) 28 0.75 0.70

7.21***, 7.31***) demonstrate the significance of zekeuipr1, zekeuipr2, and zekeuipr4 for the 10-years reference regarding foreign direct investment, net outflows (% of GDP) (Table 7.6) indicating the significance of IPR for the long-term reference effect on causing FDI outflows. It is worth mentioning here that the zekeuipr1, zekeuipr2, and zekeuipr4 beta regarding FDI outflows are (.6292718, .5466996, .5350086). We go on our investigation with model 1 [FDIit ¼ b0 + b1 zekeuipr1/zekeuipr2/ zekeuipr4/zekeuipr3it + b2 Tradeit + b3 Inflationit + b4 GDPGRit + uit] using OLS robust standard errors and the results (Coef. 4.43***, 3.72*, 3.95**, 3.92**) show the significance of zekeuipr1, zekeuipr2, zekeuipr4, and zekeuipr3 for the 5-year reference regarding foreign direct investment, net inflows (% of GDP) (Table 7.7) indicating the significance of IPRs for the short-term reference impact on attracting FDI inflows employing robust standard errors that show a higher significance of zekeuipr1, zekeuipr2, zekeuipr4, and zekeuipr3 rather than under Standard Errors (Coef. 4.43**, 3.72*, 3.95*, 3.92*). 4. Continuing with our investigation with model 1 [FDIit ¼ b0 + b1 zekeuipr1/ zekeuipr2/zekeuipr4/zekeuipr3it + b2 Tradeit + b3 Inflationit + b4 GDPGRit + uit] using OLS standardized coefficients or beta coefficients and the results (Coef. 7.45***, 7.49***, 7.55***, 8.04***) show the significance of zekeuipr1, zekeuipr2, zekeuipr4, and zekeuipr3 for the 5-year reference regarding foreign direct investment, net outflows (% of GDP) (Table 7.8) indicating the significance of IPRs for the short-term reference impact on causing FDI outflows. It is worth

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Table 7.7 FDI inflows OLS Model 1 robust coefficients Variables zekeuipr1 gdpgr5y trade5y inf5y

(1) logfdiin5y 4.43*** (1.049) 0.26* (0.118) 0.00 (0.003) –0.19 (0.163)

zekeuipr2

(2) logfdiin5y

(3) logfdiin5y

(4) logfdiin5y

0.19 (0.130) 0.00 (0.004) –0.22 (0.160) 3.72* (1.460)

0.21 (0.134) 0.00 (0.004) –0.27 (0.145)

0.19 (0.132) 0.00 (0.004) –0.19 (0.158)

zekeuipr4

3.95** (1.368)

zekieuipr3 Constant Observations R2 Adj. R2

–9.60 (4.745) 28 0.46 0.37

–6.09 (6.368) 28 0.35 0.24

–7.00 (5.965) 28 0.37 0.26

3.92** (1.289) –7.09 (5.676) 28 0.39 0.28

mentioning here that the zekeuipr3, zekeuipr4, zekeuipr2, and zekeuipr1 beta regarding FDI outflows are (.5777941, .5300298, .5540649, .6514587). We maintain our investigation with model 1 [FDIit ¼ b0 + b1 zekeuipr1/ zekeupat1/zekeucopy1/zekeumark1it + b2 Tradeit + b3 Inflationit + b4 GDPGRit + uit] using OLS standardized coefficients or beta coefficients and the results (Coef. 4.43**, 4.75*, 4.94, 5.32*) show the significance of zekeuipr1, zekeupat1, zekeucopy1, and zekeumark1 for the 5-year reference regarding foreign direct investment, net inflows (% of GDP) (see Table 7.9) indicating the significance of IPRs for the short-term reference impact on causing FDI inflows. 5. Moreover, we uphold our investigation with model 1 [FDIit ¼ b0 + b1 zekeuipr1/ zekeupat1/zekeucopy1/zekeumark1it + b2 Tradeit + b3 Inflationit + b4 GDPGRit + uit] using OLS standardized coefficients or beta coefficients and robust standard errors and so the results (Coef. 4.65**, 5.78*, 6.07*, 6.46*/5.78*, 6.07*, 6.46*) explain the significance of zekeuipr1, zekeupat1, zekeucopy1, and zekeumark1 for the 10-year reference regarding foreign direct investment, net inflows (% of GDP) (see Table 7.10) indicating the significance of IPRs for the long-term reference impact on causing FDI inflows. It is worth mentioning here that the zekeupat1, zekeucopy1, and zekeumark1 beta regarding FDI inflows are (.5759604, .5860971, .6131402).

7.3

Econometric Outcomes Zekeuipr Index

315

Table 7.8 FDI outflows OLS Model 1 beta coefficients Variables zekieuipr3 gdpgr5y trade5y inf5y

(1) logfdiout5yav 7.45*** (1.651) 0.04 (0.190) 0.00 (0.005) –0.79** (0.243)

zekeuipr4

(2) logfdiout5yav

(3) logfdiout5yav

(4) logfdiout5yav

0.10 (0.198) 0.00 (0.005) –0.95*** (0.242) 7.49*** (1.835)

0.06 (0.196) –0.00 (0.005) –0.82** (0.250)

0.18 (0.169) 0.00 (0.005) –0.81*** (0.212)

zekeuipr2

7.55*** (1.791)

zekeuipr1 Constant Observations R2 Adj. R2

–20.54* (7.347) 28 0.70 0.65

–20.32* (8.067) 28 0.68 0.62

–20.79* (7.920) 28 0.69 0.63

8.04*** (1.424) –23.57** (6.423) 28 0.77 0.73

6. Besides, we go through our investigation with model 1 [FDIit ¼ b0 + b1 zekeuipr1/zekeupat1/zekeucopy1/zekeumark1it + b2 Tradeit + b3 Inflationit + b4 GDPGRit + uit] using OLS Robust standard errors and the results (Coef. 4.43***, 4.75, 4.94, 5.32) show the significance of zekeuipr1, zekeupat1, zekeucopy1, and zekeumark1 for the 5-year reference regarding foreign direct investment, net inflows (% of GDP) and GDP growth seems to be more significant (Coef. 0.26*, 0.23*, 0.22*, 0.23*) rather than zekeupat1, zekeucopy1, and zekeumark1 subindexes of zekeuipr1. Furthermore, we go through our investigation with model 1 [FDIit ¼ b0 + b1 zekeuipr1/zekeupat1/zekeucopy1/zekeumark1it + b2 Tradeit + b3 Inflationit + b4 GDPGRit + uit] using quantile (including median) regression and the results (Coef. 5.25*, 3.55, 3.25, 4.05) affirm the significance of zekeuipr1, zekeupat1, zekeucopy1, and zekeumark1 for the 5-year reference regarding foreign direct investment, net inflows (% of GDP). The following avplots—graphs an added-variable plot, a.k.a. partial regression plot shows the value of the variables in the econometric model. reg logfdiin5y zekeuipr1 gdpgr5y trade5y inf5y, robust.

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Table 7.9 FDI inflows OLS Model 1 beta coefficients (1) logfdiin5y 4.43** (1.292) 0.26 (0.154) 0.00 (0.004) –0.19 (0.192)

Variables zekeuipr1 gdpgr5y trade5y inf5y zekeupat1

(2) logfdiin5y

(3) logfdiin5y

(4) logfdiin5y

0.23 (0.173) –0.00 (0.005) –0.11 (0.257) 4.75* (2.297)

0.22 (0.173) –0.00 (0.005) –0.10 (0.259)

0.23 (0.172) –0.00 (0.004) –0.08 (0.259)

zekeucopy1

4.94 (2.395)

zekeumark1 –9.60 (5.830) 28 0.46 0.37

Constant

0 -4

-2

e( logfdiin5y | X)

4 2 0 -2 -4

e( logfdiin5y | X)

1.17 (4.475) 28 0.31 0.19

2

Observations R2 Adj. R2

1.48 (4.306) 28 0.31 0.19

-.4

-.2 0 e( zekieupr3 | X )

-4

.2

-2

0 e( gdp5y | X )

2

4

coef = .16796142, (robust) se = .24054675, t = .7

0 -2 -4

-4

-2

0

e( logfdiin5y | X)

2

2

coef = 5.1019397, (robust) se = 1.4197883, t = 3.59

e( logfdiin5y | X)

5.32* (2.437) 0.42 (4.564) 28 0.33 0.21

-2

-1

0 1 e( inf5y | X )

2

3

coef = -.19517137, (robust) se = .27613285, t = -.71

-100

0

100 e( tr5 | X )

200

coef = .00294316, (robust) se = .006228, t = .47

Observations R2 Adj. R2

Constant

zekeumark1

zekeucopy1

zekeupat1

inf10y

gdpgr10y

trade10y

Variables zekeuipr1

–10.41 (5.704) 28 0.47 0.38

(1) logfdiin10y 4.65** (1.270) 0.00 (0.004) 0.07 (0.207) –0.16 (0.183)

–0.28 (4.644) 28 0.32 0.21

–0.00 (0.005) 0.00 (0.231) 0.05 (0.258)

–0.00 (0.005) 0.04 (0.235) 0.02 (0.251) 5.78* (2.495)

–0.81 (4.784) 28 0.33 0.21

6.07* (2.575)

(3) logfdiin10y

(2) logfdiin10y

Table 7.10 FDI inflows OLS Model 1 beta coefficients/robust standard errors

6.46* (2.664) –1.56 (4.962) 28 0.34 0.22

–0.00 (0.005) 0.03 (0.232) 0.07 (0.257)

(4) logfdiin10y

–0.28 (4.404) 28 0.32 0.21

–0.00 (0.004) 0.04 (0.207) 0.02 (0.218) 5.78* (2.437)

(5) logfdiin10y

–0.81 (4.277) 28 0.33 0.21

6.07* (2.384)

–0.00 (0.004) 0.00 (0.213) 0.05 (0.217)

(6) logfdiin10y

6.46* (2.529) –1.56 (4.611) 28 0.34 0.22

–0.00 (0.004) 0.03 (0.211) 0.07 (0.220)

(7) logfdiin10y

7.3 Econometric Outcomes Zekeuipr Index 317

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Table 7.11 FDI inflows OLS Model 1 robust coefficients Variables zekeuipr1 gdpgr5y trade5y inf5y

(1) logfdiin5y 4.43*** (1.049) 0.26* (0.118) 0.00 (0.003) –0.19 (0.163)

zekeuipr2

(2) logfdiin5y

(3) logfdiin5y

(4) logfdiin5y

0.19 (0.130) 0.00 (0.004) –0.22 (0.160) 3.72* (1.460)

0.21 (0.134) 0.00 (0.004) –0.27 (0.145)

0.19 (0.132) 0.00 (0.004) –0.19 (0.158)

zekeuipr4

3.95** (1.368)

zekeuipr3 Constant Observations R2 Adj. R2

–9.60 (4.745) 28 0.46 0.37

–6.09 (6.368) 28 0.35 0.24

–7.00 (5.965) 28 0.37 0.26

3.92** (1.289) –7.09 (5.676) 28 0.39 0.28

7. Furthermore, we carry on our investigation with model 1 [FDIit ¼ b0 + b1 zekeuipr1/zekeuipr2/zekeuipr4/zekeuipr3it + b2 Tradeit + b3 Inflationit + b4 GDPGRit + uit] using OLS robust standard errors and the results (Coef. 4.43***, 3.72*, 3.95**, 3.92**) show the significance of zekeuipr1, zekeuipr2, zekeuipr4, and zekeuipr3 for the 5-year reference regarding foreign direct investment, net inflows (% of GDP) (Table 7.11) indicating the significance of IPRs for the short-term reference impact on attracting FDI inflows employing robust standard errors that show a higher significance of zekeuipr1, zekeuipr2, zekeuipr4, and zekeuipr3 rather than under Standard Errors (Coef. 4.43**, 3.72*, 3.95*, 3.92*). 8. Based on World Bank data till 2013 concerning our variables, we continue our investigation with model 1 [FDIit ¼ b0 + b1 zekeuipr1/zekeuipr2/zekeuipr4/ zekeuipr3it + b2 Tradeit + b3 Inflationit + b4 GDPGRit + uit] using OLS robust standard errors together with beta coefficients and the results (Coef. 4.22*, 5.10**/, 4.22, 5.10**) show the significance of zekeuipr3 for the 2013 reference and the 5-year reference regarding foreign direct investment, net inflows (% of GDP) (Table 7.12) indicating the significance of IPRs for the short-term reference impact on attracting FDI inflows. Moreover, employing robust standard errors

7.3

Econometric Outcomes Zekeuipr Index

319

Table 7.12 FDI inflows OLS Model 1 robust coefficients/beta coefficients Variables zekeuipr3 gdp2013 inf2013 tr2013

(1) logfdiif2013 4.22* (1.766) –0.04 (0.248) –0.11 (0.295) 0.00 (0.004)

gdp5y inf5y tr5 Constant Observations R2 Adj. R2

4.78 (7.094) 18 0.23 0.00

(2) logfdiif5y 5.10** (1.420)

(3) logfdiif2013 4.22 (2.176) –0.04 (0.296) –0.11 (0.294) 0.00 (0.005)

0.17 (0.241) –0.20 (0.276) 0.00 (0.006) 1.19 (6.324) 26 0.37 0.25

(4) logfdiif5y 5.10** (1.738)

0.17 (0.234) –0.20 (0.334) 0.00 (0.006) 1.19 (7.573) 26 0.37 0.25

4.78 (9.144) 18 0.23 0.00

regression shows a higher significance of zekeuipr3, rather than under Standard Errors. It is worth mentioning here that the zekeuipr3, beta regarding FDI inflows are (.4991109, .5507342) concerning the 2013 and the 5-year reference, respectively. . summarize zekeuipr1 , detail zekeuipr1

1% 5% 10% 25%

Percentiles 3.601774 3.986601 4.014532 4.062787

50%

4.152797

75% 90% 95% 99%

4.368312 4.419037 4.465059 4.506968

Smallest 3.601774 3.986601 4.014532 4.01862

Largest 4.415082 4.419037 4.465059 4.506968

Obs Sum of Wgt.

28 28

Mean Std. Dev.

4.188952 .1944406

Variance Skewness Kurtosis

.0378071 -.6387947 4.077449

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Table 7.13 FDI inflows OLS Model 1/Model 4 robust standard errors Variables zekeuipr1 trade5y inf5y gdpgr5y

(1) logfdiin5y 4.43*** (1.049) 0.00 (0.003) –0.19 (0.163) 0.26* (0.118)

zekeuipr2

(2) logfdiin5y

(3) logfdiin5y

(4) logfdiin5y

0.00 (0.004) –0.22 (0.160) 0.19 (0.130) 3.72* (1.460)

0.00 (0.004) –0.27 (0.145) 0.21 (0.134)

–0.00 (0.005) –0.20 (0.277) 0.13 (0.207)

zekeuipr4

3.95** (1.368)

gci12 Constant Observations R2 Adj. R2

–9.60 (4.745) 28 0.46 0.37

–6.09 (6.368) 28 0.35 0.24

–7.00 (5.965) 28 0.37 0.26

1.10 (0.670) 4.45 (3.713) 28 0.25 0.12

Hence, we keep on our investigation with model 1 [FDIit ¼ b0 + b1 zekeuipr1/ zekeuipr2/zekeuipr4it + b2 Tradeit + b3 Inflationit + b4 GDPGRit + uit] and model 4 [FDIit ¼ b0 + b1 GCIit + b2 Tradeit + b3 Inflationit + b4 GDPGRit + uit] using OLS standardized coefficients or beta coefficients and the results (Coef. 4.43**, 3.72*, 3.95*, 1.10) show the significance of zekeuipr1, zekeuipr2, zekeuipr4, and GCI (Competitiveness) for the 5-years reference regarding foreign direct investment, net inflows (% of GDP). It is worth mentioning here that the zekeuipr1, zekeuipr2, zekeuipr4, and GCI beta regarding FDI outflows are (.6002161, .4555029, .4665177, .4037991). On the other hand, we go through our investigation with model 1 [FDIit ¼ b0 + b1 zekeuipr1/zekeuipr2/zekeuipr4it + b2 Tradeit + b3 Inflationit + b4 GDPGRit + uit] and model 4 [FDIit ¼ b0 + b1 GCIit + b2 Tradeit + b3 Inflationit + b4 GDPGRit + uit] using OLS robust standard errors and the results (Coef. 4.43***, 3.72*, 3.95**, 1.10) affirm the significance of zekeuipr1, zekeuipr2, zekeuipr4, and GCI (Competitiveness) for the 5-year reference regarding foreign direct investment, net inflows (% of GDP). It seems that IPR have a higher significance concerning FDI inflows than competitiveness in the short-term reference (see Table 7.13).

7.3

Econometric Outcomes Zekeuipr Index

7.3.4

321

Linear Results Regarding GDP Growth and Trade

We endure our investigation with model 2 [Tradeit ¼ b0 + b1 zekeuipr1/zekeuipr2/ zekeuipr4it + b2 GDPGRit + b3 Inflationit + uit] and model 3 [GDPGRit ¼ b0 + b1 zekeuipr1/zekeuipr2/zekeuipr4 + b2 Tradeit + b3 Inflationit + b4 FDIit + uit] using OLS standardized coefficients or beta coefficients and the results (Coef. –95.52, –67.07, –91.66/–2.48, –0.58, –1.19) show the significance of zekeuipr1, zekeuipr2, zekeuipr4 for the 5-years reference regarding Trade and GDP growth respectively. It is worth mentioning here that the zekeuipr1, zekeuipr2, and zekeuipr4 beta regarding Trade and GDP growth respectively are (–.3337756, –.2120368, –.2795567/–.3311775, –.069573, –.1387314). Furthermore, we extend our investigation with model 2 [Tradeit ¼ b0 + b1 zekeuipr1/zekeuipr2/ zekeuipr4it + b2 GDPGRit + b3 Inflationit + uit] and model 3 [GDPGRit ¼ b0 + b1 zekeuipr1/zekeuipr2/zekeuipr4 + b2 Tradeit + b3 Inflationit + b4 FDIit + uit] using OLS robust standard errors and the results (Coef. –95.52**, –67.07, –91.66/ –2.48, –0.58, –1.19) point up the significance of zekeuipr1, zekeuipr2, and zekeuipr4 for the 5-year reference regarding Trade and GDP growth, respectively (see Table 7.14). Also, we persist our investigation with model 2 [Tradeit ¼ b0 + b1 zekeuipr1/ zekeuipr2/zekeuipr4it + b2 GDPGRit + b3 Inflationit + uit] and model 3a [GDPGRit ¼ b0 + b1 zekeuipr1/zekeuipr2/zekeuipr4 + b2 Tradeit + b3 Inflationit + b4 FDIit + uit] Table 7.14 Inflows OLS Model 2/Model 3 robust standard errors Variables zekeuipr1 inf5y gdpgr5y

(1) trade5y –95.52** (33.881) –5.92 (7.645) 5.11 (6.391)

zekeuipr2

(2) trade5y

(3) trade5y

–4.42 (8.490) 6.82 (6.454) –67.07 (46.316)

–4.33 (7.938) 6.25 (6.836)

(6) gdpgr5y

0.14 (0.256)

0.14 (0.234)

–0.58 (2.662)

trade5y logfdiin5y

Observations R2 Adj. R2

(5) gdpgr5y

–91.66 (45.902)

zekeuipr4

Constant

(4) gdpgr5y –2.48 (1.947) 0.09 (0.224)

534.45** (151.337) 28 0.12 0.02

408.52 (203.559) 28 0.07 –0.05

510.13* (202.247) 28 0.10 –0.01

0.00 (0.006) 0.42 (0.205) 6.03 (8.114) 28 0.14 –0.01

0.00 (0.006) 0.28 (0.183) –1.14 (11.654) 28 0.09 –0.07

–1.19 (2.773) 0.00 (0.006) 0.31 (0.190) 1.19 (11.909) 28 0.10 –0.06

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Table 7.15 Inflows OLS Model 2/Model 3a beta coefficients Variables zekeuipr1 gdpgr10y inf10y

(1) trade10y –79.01 (56.810) 12.19 (9.288) –8.85 (8.325)

zekeuipr2

(2) trade10y

(3) trade10y

14.53 (9.308) –8.22 (8.707) –48.40 (63.493)

13.64 (9.186) –8.01 (8.321)

trade10y

Observations R2 Adj. R2

(5) gdpgr10y

(6) gdpgr10y

0.41* (0.160)

0.43* (0.163) –0.67 (1.336)

0.45** (0.156)

–74.84 (62.189)

zekeuipr4

Constant

(4) gdpgr10y –1.10 (1.234)

448.24 (249.023) 28 0.17 0.07

311.93 (274.595) 28 0.13 0.02

422.57 (266.260) 28 0.16 0.05

0.01 (0.004) 4.56 (5.555) 28 0.37 0.29

0.01 (0.004) 2.59 (5.866) 28 0.36 0.28

–0.67 (1.355) 0.01 (0.004) 2.57 (5.929) 28 0.36 0.28

using OLS standardized coefficients or beta coefficients and the results (Coef. –79.01, –48.40, –74.84/–1.10, –0.67, –0.67) show the significance of zekeuipr1, zekeuipr2, zekeuipr4 for the 10 years reference regarding Trade and GDP growth, respectively. Besides, it seems that inflation is significant variable for the GDP growth (Coef. 0.41*, 0.43*, 0.45**). It is worth mentioning here that the zekeuipr1, zekeuipr2, and zekeuipr4 beta regarding Trade and GDP growth respectively are (–.2902496, –.1608617, –.2399489/ –.1652964, –.0915834, –.0878882) (see Table 7.15).

7.3.5

Nonlinear Results

Figure 7.4 displays the value of zekeuipr1 that is used in our nonlinear investigation. We continue our analysis by using a nonlinear investigation. The analysis of the data utilizing our econometric models gives the results discussed below. 1. FDI inflows OLS Model 1/zekeuipr1 25%/75%, Beta Coefficients The investigation continues with model 1 [FDIit ¼ b0 + b1 zekeuipr1/zekeuipr2/ zekeuipr4/Zekieupr3it + b2 Tradeit + b3 Inflationit + b4 GDPGRit + uit] using OLS standardized coefficients or beta coefficients and the results show that zekeuipr1 for a value of zekeuipr1 25% (Coef. 3.96, 2.51) and for a value of zekeuipr1 75% (Coef. 3.88*, –0.10) in reference FDI 5 years average inflows

7.3

Econometric Outcomes Zekeuipr Index

Fig. 7.4 Value of zekeuipr1

323

. summarize zekeuipr1 , detail zekeuipr1

1% 5% 10% 25%

Percentiles 3.601774 3.986601 4.014532 4.062787

50%

4.152797

75% 90% 95% 99%

4.368312 4.419037 4.465059 4.506968

Smallest 3.601774 3.986601 4.014532 4.01862

Largest 4.415082 4.419037 4.465059 4.506968

Obs Sum of Wgt.

28 28

Mean Std. Dev.

4.188952 .1944406

Variance Skewness Kurtosis

.0378071 -.6387947 4.077449

Table 7.16 FDI inflows OLS Model 1/zekeuipr1 25%/75%, beta coefficients Variables zekeuipr1 gdpgr5y trade5y inf5y Constant Observations R2 Adj. R2

(1) logfdiin5y 3.96 (2.792) 0.41 (0.219) –0.01 (0.013) –0.05 (0.416) –7.52 (12.228) 7 0.81 0.43

(2) logfdiin5y 2.51 (2.650) 0.32 (0.268) 0.00 (0.005) –0.26 (0.263) –1.06 (11.996) 21 0.30 0.13

(3) logfdiin5y 3.88* (1.687) 0.23 (0.159) 0.01 (0.005) –0.20 (0.200) –7.71 (7.152) 21 0.40 0.25

(4) logfdiin5y –0.10 (14.905) 1.17 (0.895) –0.02 (0.019) 0.63 (1.201) 11.10 (68.093) 7 0.61 –0.16

regarding foreign direct investment, net inflows (see Table 7.16). It is worth mentioning here that the zekeuipr1 betas regarding FDI are (.574124, .2585958/ .4601455, –.0037612). It also is worth mentioning that it becomes clear the significance of the level of IPR protection. In fact, a value of zekeuipr1 >25% and 25% and 25% is higher concerning FDI outflows than inflows. Likewise, instrumental variables (2SLS) regression gives similar results like a beta coefficients regression. Moreover, a robust standard errors analysis gives the results for a value of zekeuipr1 25% (Coef. 5.41, 9.07**) and for a value of zekeuipr1 75% (Coef. 7.24***, –5.74). In addition, a quantile (including median) regression gives the results for a value of zekeuipr1 25% (Coef. 3.57, 8.57*) and for a value of zekeuipr1 75% (Coef. 7.23*, –6.14). Hence, we carry on our investigation with model 1 [FDIit ¼ b0 + b1 zekeuipr1/ zekeuipr2/zekeuipr4/Zekieupr3it + b2 Tradeit + b3 Inflationit + b4 GDPGRit + uit] using OLS seemingly unrelated regression and three-stage least squares regression and the results demonstrate that zekeuipr1 for a value of zekeuipr1 25% (Coef. 5.41***, 9.07***) and for a value of zekeuipr1 75% (Coef. 7.24***, –5.74) in reference FDI 5 years average outflows regarding foreign direct investment, net outflows (see Table 7.19). Thus, it seems that a very high protection of IPR is not a significant variable in causing FDI outflows which means that a less protection of IPR is causing FDI outflows. Figure 7.5 displays the value of Zekeuipr3 which is used in our nonlinear investigation. We continue our analysis by using a nonlinear investigation. The analysis of the data utilizing our econometric models gives the results discussed below. 3. FDI inflows OLS Model 1/Zekeuipr3 25%/75%, beta coefficients

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Table 7.19 FDI outflows OLS Model 1/zekeuipr1 25%/75%, seemingly unrelated regression and three-stage least squares regression

Observations R2 Adj. R2

(1) logfdiout5yav –5.74 (5.723) 1.02** (0.344) –0.02* (0.007) 0.05 (0.461) 37.61 (26.144) 7 0.61 –

. summarize

zekieupr3, detail

Variables zekeuipr1 gdpgr5y trade5y inf5y Constant

(2) logfdiout5yav 7.24*** (1.721) 0.17 (0.162) 0.01 (0.005) –0.82*** (0.204) –20.63** (7.295) 21 0.68 –

(3) logfdiout5yav 9.07*** (2.491) –0.02 (0.252) 0.01 (0.005) –0.79** (0.248) –28.36* (11.274) 21 0.70 –

(4) logfdiout5yav 5.41*** (1.420) 0.54*** (0.112) –0.01 (0.007) –0.24 (0.211) –13.81* (6.218) 7 0.90 –

Zekieupr3

1% 5% 10% 25% 50% 75% 90% 95% 99%

Percentiles 3.691773 3.838579 3.958647 4.003818

Smallest 3.691773 3.838579 3.958647 3.961084

4.161809 4.310786 4.39352 4.399541 4.498397

Largest 4.372224 4.39352 4.399541 4.498397

Obs Sum of Wgt. Mean Std. Dev. Variance Skewness Kurtosis

28 28 4.155335 .1858844 .034553 -.3571841 2.859232

Fig. 7.5 Value of Zekeuipr3

The investigation continues with model 1 [FDIit ¼ b0 + b1 zekeuipr1/zekeuipr2/ zekeuipr4/Zekieupr3it + b2 Tradeit + b3 Inflationit + b4 GDPGRit + uit] using OLS standardized coefficients or beta coefficients and the results show that Zekeuipr3 for a value of Zekeuipr3 25% (Coef. 14.26, 3.13) and for a value of Zekeuipr3 75% (Coef. 3.46, 11.52) in reference FDI 10 years average inflows regarding foreign direct investment, net inflows (see Table 7.20). It is worth mentioning here that the Zekeuipr3 betas regarding FDI are (2.162022, .3139155/ .4262011, .6087713). It also is worth mentioning that it becomes clear the significance of the

7.3

Econometric Outcomes Zekeuipr Index

327

Table 7.20 FDI inflows OLS Model 1/zekieupr3 25%/75%, beta coefficients Variables zekeuipr3 trade10y gdpgr10y inf10y Constant Observations R2 Adj. R2

(1) logfdiin10y 14.26 (5.477) 0.03 (0.019) –1.10 (0.606) –0.03 (0.303) –49.56 (22.746) 7 0.84 0.51

(2) logfdiin10y 3.13 (3.021) –0.00 (0.005) 0.03 (0.308) –0.13 (0.275) –3.45 (13.430) 21 0.19 –0.01

(3) logfdiin10y 3.46 (1.816) 0.00 (0.005) –0.09 (0.224) –0.07 (0.209) –5.55 (7.538) 21 0.24 0.05

(4) logfdiin10y 11.52 (15.972) 0.00 (0.031) 1.65 (1.739) 1.60 (2.110) –45.79 (76.338) 7 0.45 –0.66

Table 7.21 FDI inflows OLS Model 1/zekeuipr1 25%/75%, beta coefficients Variables zekeuipr1 trade10y gdpgr10y inf10y Constant Observations R2 Adj. R2

(1) logfdiin10y 1.74 (3.658) –0.01 (0.015) 0.64 (0.463) –0.64 (0.373) 1.88 (15.113) 7 0.75 0.24

(2) logfdiin10y 5.69* (2.507) 0.00 (0.006) –0.09 (0.349) 0.03 (0.278) –15.32 (11.296) 21 0.34 0.18

(3) logfdiin10y 3.59* (1.603) 0.00 (0.005) 0.04 (0.215) –0.12 (0.186) –6.54 (6.805) 21 0.30 0.12

(4) logfdiin10y –10.69 (13.804) –0.03 (0.020) 1.84 (1.128) –0.69 (1.420) 59.46 (62.924) 7 0.63 –0.10

level of IPR protection. In fact a value of Zekeuipr3 >25% and 25% and 25% and 75% as it is illustrated above indicating that even a very high value of IPRs protection is valuable for the long-term reference. 6. FDI Outflows OLS Model 1/zekeuipr1 25%/75%, Beta Coefficients We endure our investigation with model 1 [FDIit ¼ b0 + b1 zekeuipr1/zekeuipr2/ zekeuipr4/Zekieupr3it + b2 Tradeit + b3 Inflationit + b4 GDPGRit + uit] using OLS standardized coefficients or beta coefficients and the results show that zekeuipr1 for

7.3

Econometric Outcomes Zekeuipr Index

329

Table 7.23 FDI outflows OLS Model 1/zekeuipr1 25%/75%, beta coefficients Variables zekeuipr1 trade10y gdpgr10y inf10y Constant Observations R2 Adj. R2

(1) logfdiout10yav 2.52 (2.538) –0.02 (0.011) 0.62 (0.321) –0.87 (0.259) –0.93 (10.488) 7 0.92 0.75

(2) logfdiout10yav 8.92** (2.523) 0.01 (0.006) –0.54 (0.352) –0.42 (0.280) –28.05* (11.368) 21 0.75 0.69

(3) logfdiout10yav 6.59** (1.700) 0.01 (0.005) –0.21 (0.228) –0.61** (0.197) –18.19* (7.214) 21 0.72 0.65

(4) logfdiout10yav –9.07 (11.384) –0.02 (0.017) 1.52 (0.930) –0.97 (1.171) 53.44 (51.892) 7 0.63 –0.11

a value of zekeuipr1 25% (Coef. 2.52, 8.92**) and for a value of zekeuipr1 75% (Coef. 6.59**, –9.07) in reference FDI 10 years average inflows regarding foreign direct investment, net outflows (see Table 7.23). It is worth mentioning here that the zekeuipr1 betas regarding FDI are (.3119211, .3681515/ .5791633, –.47035). It is worth mentioning that it becomes clear the significance of the level of IPRs protection. In fact, a value of zekeuipr1 >25% and F = 0.4646

Thus, we persist in our investigation with model 1 [FDIit ¼ b0 + b1 zekeuipr1/ zekeuipr2/zekeuipr4it + b2 Tradeit + b3 Inflationit + b4 GDPGRit + uit] using threestage least squares regression and the results (Coef. 4.17***,4.77***/ 3.61***,4.68***) show the significance of zekeuipr4 for the 10-years and 5-years reference (Table 7.27) indicating the significance of IPRs for the long- and shortterm reference concerning the impact on attracting FDI inflows merchandise and services and FDI inflows Tertiary In EU. Furthermore, we carry on our investigation with model 1 [FDIit ¼ b0 + b1 zekeuipr1/zekeuipr2/zekeuipr4it + b2 Tradeit + b3 Inflationit + b4 GDPGRit + uit] using robust regression (NOT robust standard errors) and the results (Coef. 4.26**,5.28**/3.49*,4.86***) show the significance of zekeuipr4 for the 10-years and 5-years reference (Table 7.28) indicating the significance of IPRs for the longand short-term reference concerning the impact on attracting FDI inflows merchandise and services and FDI inflows Tertiary In EU.

7.3

Econometric Outcomes Zekeuipr Index

333

Table 7.27 FDI inflows merchandise and services/Tertiary Sector OLS Model 1 three-stage least squares regression Variables zekeuipr4 trade10yav inf10yav gdpgr10yav

(1) logfdiinmers10yav 4.17*** (1.195) –0.00 (0.004) –0.07 (0.109) –0.22 (0.212)

trade5yav inf5yav gdpgr5yav Constant Observations R2 Adj. R2

–7.29 (5.180) 28 0.56 –

(2) logfdiinmers5yav 4.77*** (1.405)

–0.01 (0.004) –0.18 (0.125) 0.17 (0.166) –9.89 (6.164) 26 0.53 –

(3) logfdiinter10yav 3.61*** (1.035) –0.01 (0.004) –0.03 (0.094) –0.22 (0.183)

–5.18 (4.495) 25 0.63 –

(4) logfdiinter5yav 4.68*** (0.968)

–0.01** (0.003) –0.15 (0.086) 0.24* (0.115) –9.79* (4.250) 24 0.72 –

In addition, we endure our investigation with model 1 [FDIit ¼ b0 + b1 zekeuipr1/ zekeuipr2/zekeuipr4it + b2 Tradeit + b3 Inflationit + b4 GDPGRit + uit] using instrumental variables (2SLS) regression and the results (Coef. 4.17**,4.77**/ 3.61**,4.68***) show the significance of zekeuipr4 for the 10 years and 5 years reference (Table 7.29) indicating the significance of IPRs for the long- and shortterm reference concerning the impact on attracting FDI inflows merchandise and services and FDI inflows Tertiary In EU. Also, we retain our investigation with model 1 [FDIit ¼ b0 + b1 zekeuipr1/ zekeuipr2/zekeuipr4it + b2 Tradeit + b3 Inflationit + b4 GDPGRit + uit] using OLS standardized coefficients or beta coefficients and the results (Coef. 4.17**,4.77**/ 3.61**,4.68***) show the significance of zekeuipr4 for the 10 years and 5 years reference (Table 7.30) indicating the significance of IPRs for the long- and shortterm reference concerning the impact on attracting FDI inflows merchandise and services and FDI inflows tertiary in EU. It is worth noting here that the zekeuipr4 betas regarding inflows merchandise and services and FDI inflows Tertiary are (.4962793, .5602898, .4866223, .6455294). The following avplots graphs an added-variable plot, a.k.a. partial regression plot shows the value of the variables in the econometric model: reg logfdiinter5yav zekeuipr4 trade5yav inf5yav gdpgr5yav, beta.

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Table 7.28 FDI inflows merchandise and services/Tertiary Sector OLS Model 1 robust regression (not robust standard errors) Variables zekeuipr4 trade10yav inf10yav gdpgr10yav

(1) logfdiinmers10yav

(2) logfdiinmers5yav

(3) logfdiinter10yav

(4) logfdiinter5yav

4.26** (1.397) –0.00 (0.005) –0.38 (0.218) –0.04 (0.259)

5.28** (1.440)

3.49* (1.224) –0.01 (0.004) –0.31 (0.195) –0.08 (0.226)

4.86*** (1.110)

trade5yav inf5yav gdpgr5yav Constant Observations R2 Adj. R2

–7.19 (6.094) 27 0.57 0.50

–0.01 (0.004) –0.16 (0.128) 0.26 (0.170) –12.16 (6.317) 26 0.58 0.50

–4.20 (5.350) 24 0.64 0.56

–0.01* (0.005) –0.16 (0.099) 0.28 (0.134) –10.07 (4.878) 23 0.70 0.64

Table 7.29 FDI inflows merchandise and services/Tertiary Sector OLS Model 1 instrumental variables (2SLS) regression Variables zekeuipr4 trade10yav inf10yav gdpgr10yav

(1) logfdiinmers10yav

(2) logfdiinmers5yav

(3) logfdiinter10yav

(4) logfdiinter5yav

4.17** (1.318) –0.00 (0.004) –0.07 (0.120) –0.22 (0.234)

4.77** (1.563)

3.61** (1.157) –0.01 (0.004) –0.03 (0.105) –0.22 (0.205)

4.68*** (1.088)

trade5yav inf5yav gdpgr5yav Constant Observations R2 Adj. R2

–7.29 (5.715) 28 0.56 0.48

–0.01 (0.004) –0.18 (0.139) 0.17 (0.185) –9.89 (6.858) 26 0.53 0.44

–5.18 (5.026) 25 0.63 0.56

–0.01* (0.003) –0.15 (0.097) 0.24 (0.130) –9.79 (4.776) 24 0.72 0.66

7.3

Econometric Outcomes Zekeuipr Index

335

Table 7.30 FDI inflows merchandise and services/Tertiary Sector OLS Model 1, beta coefficients (1) logfdiinmers10yav 4.17** (1.318) –0.00 (0.004) –0.07 (0.120) –0.22 (0.234)

Variables zekeuipr4 trade10yav inf10yav gdpgr10yav trade5yav inf5yav gdpgr5yav Constant

(3) logfdiinter10yav 3.61** (1.157) –0.01 (0.004) –0.03 (0.105) –0.22 (0.205)

–0.01 (0.004) –0.18 (0.139) 0.17 (0.185) –9.89 (6.858) 26 0.53 0.44

–5.18 (5.026) 25 0.63 0.56

(4) logfdiinter5yav 4.68*** (1.088)

–0.01* (0.003) –0.15 (0.097) 0.24 (0.130) –9.79 (4.776) 24 0.72 0.66

1 0

e( logfdinter5yav | X)

-1

-3

e( logfdinter5yav | X) 1 -2 -1 0

2

2

Observations R2 Adj. R2

–7.29 (5.715) 28 0.56 0.48

(2) logfdiinmers5yav 4.77** (1.563)

-.4

-.2 0 e( zekeuipr4 | X )

.2

-50

50 100 150 e( trade5yav | X )

200

coef = -.00736158, se = .00294344, t = -2.5

1 0 -1 -2

-2

e( logfdinter5yav | X)

2

e( logfdinter5yav | X) -1 0 1 2

coef = 4.6826809, se = 1.0878156, t = 4.3

0

-2

0

2 e( inf5yav | X )

4

coef = -.15484369, se = .0966629, t = -1.6

-2

-1

0 1 2 e( gdpgr5yav | X )

3

coef = .23516888, se = .12969042, t = 1.81

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Likewise, the ovtest shows the following outcome: . ovtest Ramsey RESET test using powers of the fitted values of logfdiinter5yav Ho: model has no omitted variables F(3, 16) = 0.90 Prob > F = 0.4646

Moreover, the imtest, white shows the following outcome: . imtest, white White's test for Ho: homoskedasticity against Ha: unrestricted heteroskedasticity chi2(14) = Prob > chi2 =

14.55 0.4099

Cameron & Trivedi's decomposition of IM-test Source

chi2

df

p

Heteroskedasticity Skewness Kurtosis

14.55 2.52 0.14

14 4 1

0.4099 0.6405 0.7094

Total

17.21

19

0.5758

Utilizing the VIF test found the variance inflation factor for the independent variables in the linear model. . vif

7.3.6

Variable

VIF

1/VIF

zekeuipr4 gdpgr5yav inf5yav trade5yav

1.54 1.30 1.20 1.16

0.649764 0.768454 0.835930 0.862797

Mean VIF

1.30

Linear Results Regarding Trade in EU

We retain our investigation with model 2 [Tradeit ¼ b0 + b1 zekeuipr1/zekeuipr2/ zekeuipr4it + b2 GDPGRit + b3 Inflationit + uit] using Robust Standard Errors/ seemingly unrelated regression/three-stage least squares regression/OLS standardized coefficients or beta coefficients and the results (Coef. –20.29, –42.10/ –60.41, –73.13) show the significance of zekeuipr1, and zekeuipr4 for the 10 years and

7.3

Econometric Outcomes Zekeuipr Index

337

Table 7.31 Trade OLS Model 1 robust standard errors Variables zekeuipr1 inf10yav gdpgr10yav

(1) trade10yav –20.29 (41.400) –11.40* (4.725) 29.53* (12.327)

inf5yav

(2) trade5yav –42.10 (65.674)

zekeuipr4

Observations R2 Adj. R2

142.32 (183.972) 28 0.34 0.26

(4) trade5yav

–11.10* (4.652) 27.32* (12.512) 5.89 (8.008) 3.98 (7.319)

gdpgr5yav

Constant

(3) trade10yav

244.53 (288.883) 27 0.09 –0.02

–60.41 (64.767) 312.38 (281.701) 28 0.36 0.28

5.62 (7.579) 2.65 (7.558) –73.13 (85.882) 374.78 (370.113) 27 0.11 0.00

Standard errors in parentheses ***p < 0.001, **p < 0.01, *p < 0.05

5 years reference regarding trade. It is worth mentioning here that the zekeuipr1 and zekeuipr4 beta regarding trade are negative (–.0694233, –.146649/–.1803849, –.2136473). It seems that inflation and GDP growth are significant variables concerning trade in the EU (Tables 7.31, 7.32, and 7.33). The following avplots graphs an added-variable plot, a.k.a. partial regression plot shows the value of the variables in the econometric model: reg trade5yav zekeuipr4 inf5yav gdpgr5yav, robust.

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Table 7.32 Trade OLS Model 2 seemingly unrelated regression Variables zekeuipr4 inf10yav gdpgr10yav

(1) trade10yav –60.41 (56.233) –11.10* (4.805) 27.32** (8.778)

inf5yav

(2) trade5yav –73.13 (72.210)

zekeuipr1

Observations R2 Adj. R2

312.38 (241.638) 28 0.36 –

(4) trade5yav

–11.40* (4.889) 29.53** (9.012) 5.62 (6.481) 2.65 (8.504)

gdpgr5yav

Constant

(3) trade10yav

374.78 (312.435) 27 0.11 –

–20.29 (51.788) 142.32 (227.293) 28 0.34 –

5.89 (6.767) 3.98 (8.508) –42.10 (62.455) 244.53 (275.875) 27 0.09 –

Table 7.33 Trade OLS Model 2 three-stage least squares regression Variables zekeuipr1 inf10yav gdpgr10yav

(1) trade10yav –20.29 (51.788) –11.40* (4.889) 29.53** (9.012)

inf5yav

(2) trade5yav –42.10 (62.455)

zekeuipr4

Observations R2 Adj. R2

142.32 (227.293) 28 0.34 –

(4) trade5yav

–11.10* (4.805) 27.32** (8.778) 5.89 (6.767) 3.98 (8.508)

gdpgr5yav

Constant

(3) trade10yav

244.53 (275.875) 27 0.09 –

–60.41 (56.233) 312.38 (241.638) 28 0.36 –

5.62 (6.481) 2.65 (8.504) –73.13 (72.210) 374.78 (312.435) 27 0.11 –

Econometric Outcomes Zekeuipr Index

339

200 100 -100

0

e( trade5yav | X)

100 0 -100

e( trade5yav | X)

200

7.3

-.4

-.2 0 e( zekeuipr4 | X )

.2

-2

coef = -73.132273, (robust) se = 85.882192, t = -.85

0 2 e( inf5yav | X )

4

100 0 -100

e( trade5yav | X)

200

coef = 5.617814, (robust) se = 7.5791119, t = .74

-2

-1

0 1 e( gdpgr5yav | X )

2

3

coef = 2.6497854, (robust) se = 7.5584086, t = .35

Utilizing the VIF test found the variance inflation factor for the independent variables in the linear model. . vif

7.3.7

Variable

VIF

1/VIF

zekeuipr4 gdpgr5yav inf5yav

1.35 1.23 1.12

0.739241 0.816227 0.896067

Mean VIF

1.23

Linear Results Regarding GDP Growth in Relation to FDI Inflows Merchandise and Services/Tertiary Sector OLS Model

We continue our investigation with model 3 [GDPGRit ¼ b0 + b1 zekeuipr1/ zekeuipr2/zekeuipr4it + b2 Tradeit + b3 Inflationit + b4 FDIit + uit] using OLS standardized coefficients or beta coefficients/three-stage least squares regression

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Table 7.34 GDP growth OLS Model 3 beta coefficients Variables trade10yav zekeuipr1 inf10yav logfdiinmers10yav

(1) gdpgr10yav 0.01* (0.003) –1.02 (1.325) 0.30** (0.085) –0.10 (0.198)

trade5yav

(2) gdpgr5yav

–4.87* (1.759)

(3) gdpgr10yav 0.01 (0.004) –0.67 (1.476) 0.30** (0.090)

0.00 (0.005) –0.12 (0.164) 0.36 (0.266)

inf5yav logfdiinmers5yav

0.01 (0.005) –0.04 (0.160)

logfdiinter5yav

Observations R2 Adj. R2

–6.60** (1.855)

–0.19 (0.261)

logfdiinter10yav

Constant

(4) gdpgr5yav

5.87 (4.635) 28 0.60 0.53

18.62** (6.306) 26 0.29 0.16

5.11 (4.972) 25 0.61 0.53

0.88* (0.365) 20.79** (6.020) 24 0.41 0.28

and the results (Coef. –1.02, –4.87*,–0.67, –6.60**/ –1.02, –4.87**, –0.67, –6.60***) show the significance of zekeuipr1 for the 10- and 5-year references regarding GDP growth, respectively, utilizing FDI inflows merchandise and services and FDI inflows tertiary values. It is worth mentioning here that the zekeuipr1 beta regarding GDP growth, respectively, are negative (–.1531837, –.7379738/ –.1006443, –1.015235) (Tables 7.34 and 7.35).66 The following avplots graphs an added-variable plot, a.k.a. partial regression plot show the value of the variables in the econometric model: reg gdpgr5yav trade5yav zekeuipr1 inf5yav logfdiinter5yav, beta.

66 G. Zekos, “IPRs’ impact upon FDI,” 2013 PhD Thesis, Economics Department, University of Peloponnese, Tripoli, Hellas www.uop.gr.

7.3 Econometric Outcomes Zekeuipr Index

341

Table 7.35 GDP growth OLS Model 3 three-stage least squares regression Variables trade10yav zekeuipr1 inf10yav logfdiinmers10yav

(1) gdpgr10yav 0.01** (0.003) –1.02 (1.201) 0.30*** (0.077) –0.10 (0.180)

trade5yav

(2) gdpgr5yav

–4.87** (1.581)

(3) gdpgr10yav 0.01* (0.004) –0.67 (1.320) 0.30*** (0.080)

0.00 (0.004) –0.12 (0.147) 0.36 (0.239)

inf5yav logfdiinmers5yav

0.01 (0.005) –0.04 (0.142)

logfdiinter5yav

Observations R2 Adj. R2

–6.60*** (1.651)

–0.19 (0.233)

logfdiinter10yav

Constant

(4) gdpgr5yav

5.87 (4.200) 28 0.60 –

18.62** (5.668) 26 0.29 –

5.11 (4.447) 25 0.61 –

0.88** (0.325) 20.79*** (5.356) 24 0.41 –

7

2 -2

0

e( gdpgr5yav | X )

2 1 0 -1

e( gdpgr5yav | X )

-2

-50

0 50 100 e( trade5yav | X )

-.4

150

-.2

0 .2 e( zekeuipr1 | X )

.4

coef = -6.5968636, se = 1.8553156, t = -3.56

2 1 0 -1 -2

-2

-1

0

1

e( gdpgr5yav | X )

e( gdpgr5yav | X )

2

3

coef = .00704372, se = .00531665, t = 1.32

e( gdpgr5yav | X )

Econometric Analysis on AI Economy

4

342

-2

0 2 e( inf5yav | X )

-2

4

-1 0 1 e( logfdiinter5yav | X )

2

coef = .87827341, se = .36493118, t = 2.41

coef = -.037683, se = .15985144, t = -.24

Utilizing the VIF test found the variance inflation factor for the independent variables in the linear model. . vif

7.3.8

Variable

VIF

1/VIF

logfdi~r5yav zekeuipr1 trade5yav inf5yav

3.78 2.62 1.57 1.36

0.264427 0.382084 0.637327 0.736674

Mean VIF

2.33

Empirical Results for Zekipr6

Taking into account the correlation of our index zekipr6 and the variables utilized in our models, we carry on our investigation. 1. FDI inflows: OLS standardized variables A regression carried out on standardized variables engages standardized coefficients. We start our investigation with model 5 [FDIit ¼ b0 + b1 zekipr6it + b2 Tradeit + b3 Inflationit +b4 GDPGRit + b5 instit + uit] using OLS standardized coefficients or

7.3

Econometric Outcomes Zekeuipr Index

Table 7.36 FDI inflows: model 8 OLS standardized variables

Variables zekipr6 trade10y inst12 inf10y gdpgr10y

343 (1) logfdiin10y 2.68*** (0.593) –0.00 (0.003) 0.33 (0.208) –0.00 (0.000) 0.13 (0.073)

(2) logfdiin5y 3.43*** (0.753)

(3) logfdiin2012 1.81 (0.911)

0.13 (0.230)

0.52 (0.307)

–0.00 (0.003) –0.00 (0.050) 0.27*** (0.073)

trade5y inf5y gdpgr5y trade2012 inf2012 gdpgr2012 Constant Observations R2 Adj. R2

–3.57 (2.237) 79 0.43 0.39

–5.86 (3.005) 76 0.37 0.32

–0.00 (0.003) 0.04 (0.064) 0.06 (0.078) –0.97 (3.435) 52 0.27 0.19

beta coefficients and the results (Coef. 2.68***, 3.43***, 1.81) regarding 10- and 5-years average and 2012 reference show that IPRs, expressed by zekipr6, are significant in FDI inflows concerning 10 and 5 years of reference and not significant for 2012 reference (Table 7.36). The GDP growth is the second more important variable after zekipr6 (Coef. 0.13, 0.27***, 0.06). Specifically, the beta in the regression of model 19 for zekipr6 is (.5945113, .7676707, .4180403) and for GDP growth is (.2060216, .5006027, .1211654) and so GDP growth is the second in importance concerning FDI inflows. It is worth mentioning here that regardless of the 0.5762 of correlation between zekipr6 and institutions, various tests show that there is no fault in our regressions. There is no multi-collinearity. Moreover, our model 8 is correctly specified and there is no specification error and we do not need more variables. In addition, we persist in our investigation with model 6 [FDIit ¼ b0 + b1 zekipr6it + b2 Tradeit + b3 Inflationit +b4 GDPGRit + uit] using OLS standardized coefficients

344 Table 7.37 FDI inflows: model 8a OLS standardized variables

7

Variables zekipr6 trade10y inf10y gdpgr10y

Econometric Analysis on AI Economy

(2) logfdiin10y 3.14*** (0.524) –0.00 (0.003) –0.00 (0.000) 0.13 (0.074)

inst12 trade5y

(3) logfdiin5y 3.59*** (0.693)

–0.00 (0.003) –0.01 (0.048) 0.28*** (0.071)

inf5y gdpgr5y trade2012 inf2012 gdpgr2012 Constant Observations R2 Adj. R2

(4) logfdiin2012 2.55** (0.811)

–4.09 (2.237) 79 0.41 0.37

–5.96* (2.985) 76 0.36 0.33

0.00 (0.003) 0.03 (0.065) 0.10 (0.076) –2.03 (3.441) 52 0.22 0.16

or beta coefficients and the results (Coef. 3.14***,3.59***,2.55**) regarding 10, 5 years average and 2012 reference show that IPRs, expressed by zekipr6, are more significant in FDI inflows than in model 5 (Table 7.37). It is worth mentioning here that the zekipr6 beta regarding FDI inflows are (.5898402, .8030179, .6964313), respectively. 2. FDI outflows OLS Model 7/Model 8 beta coefficients We go on our investigation with model 7 [FDIit ¼ b0 + b1 zekipr6it + b2 GDPit + b3 Tradeit + b4 Inflationit + uit] using OLS standardized coefficients or beta coefficients and the results (Coef. 5.28**, 6.18***, 5.95***) show the significance of zekipr6 for the 2012, 5- and 10-years reference regarding foreign direct investment, net outflows US Dollars at current prices and current exchange rates in millions 2012 UNCTADstat (Table 7.38). It is worth mentioning here that the zekcopy6 beta regarding FDI outflows are (.59242, .7894868, .7175243), respectively.

–14.35 (8.369) 45 0.29 0.22

6.18*** (1.163)

5.28** (1.936) 0.14 (0.200) 0.01 (0.006) –0.00 (0.138)

–17.09** (5.005) 71 0.42 0.39

0.32** (0.121) –0.00 (0.004) –0.03 (0.080)

(2) logfdiout5yav

(1) logfdiout2012

–16.24*** (3.956) 76 0.45 0.42

0.13 (0.129) –0.00 (0.004) –0.00 (0.000)

5.95*** (0.926)

(3) logfdiout10yav

4.16*** (0.784) –11.16** (3.775) 45 0.51 0.46

–0.05 (0.126) –0.01 (0.006) 0.09 (0.113)

(4) logfdiout2012

4.07*** (0.476) –10.60*** (2.385) 71 0.61 0.58

–0.05 (0.080) –0.01* (0.004) 0.12 (0.071)

(5) logfdiout5yav

–0.02 (0.093) –0.01** (0.004) –0.00 (0.000) 3.82*** (0.403) –8.85*** (1.936) 76 0.62 0.60

(6) logfdiout10yav

Econometric Outcomes Zekeuipr Index

Observations R2 Adj. R2

Constant

gci12

inf10y

trade10y

gdpgr10y

inf5y

trade5y

gdpgr5y

inf2012

trade2012

gdpgr2012

Variables zekipr6

Table 7.38 FDI outflows OLS Model 7/Model 8 beta coefficients

7.3 345

346

7

Econometric Analysis on AI Economy

Furthermore, we endure our investigation with model 8 [FDIit ¼ b0 + b1 GCIit + b2 GDPit + b3 Tradeit + b4 Inflationit + uit] using OLS standardized coefficients or beta coefficients and the results (Coef. 4.16***, 4.07***, 3.82***) show the significance of GCI for the 2012, 5- and 10-years reference regarding foreign direct investment, net outflows US Dollars at current prices and current exchange rates in millions 2012 UNCTADstat (Table 7.38). It is worth mentioning here that the GCI beta regarding FDI outflows are (.792171, .9021555, .7948605), respectively. The above concise analysis of IPRs allows us to understand the quantities’ evaluation of IPR used in the preparation of our own IPR indices. In addition, the whole analysis of the legal background of law concerning patents, copyrights, and trademarks shows a constant development of the legal regulation and enforcement of IPRs which means a nonstop alteration of an index regarding the protection of IPR. Thus, IPR protection adds to their utility as a means in attracting FDI. The value of IPRs expressed by zekeuipr1 indexes >25% and