Games In Everyday Life: For Play 9781838679385, 9781838679378, 9781838679392

In this book, Nathan Hulsey explores the links between game design, surveillance, computation, and the emerging technolo

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Table of contents :
Cover
Title
Copyright
Table of Content
Introduction
Chapter 1 Game Studies and Gamification
Chapter 2 Defining Gamification
Chapter 3 Gamespace, Simulation, and Gamification
Chapter 4 Histories of Gaming and Computation
Chapter 5 Gamification, Power, and Networks
Chapter 6 Gamified Health and Bodies
Chapter 7 The Labors of Play
Conclusion
References
Index
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Games In Everyday Life: For Play
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Games in Everyday Life: For Play By NATHAN HULSEY Nazarbayev University, Kazakhstan

United Kingdom – North America – Japan – India – Malaysia – China

Emerald Publishing Limited Howard House, Wagon Lane, Bingley BD16 1WA, UK First edition 2020 © 2020 Nathan Hulsey Published under exclusive licence by Emerald Publishing Limited Reprints and permissions service Contact: [email protected] No part of this book may be reproduced, stored in a retrieval system, transmitted in any form or by any means electronic, mechanical, photocopying, recording or otherwise without either the prior written permission of the publisher or a licence permitting restricted copying issued in the UK by The Copyright Licensing Agency and in the USA by The Copyright Clearance Center. Any opinions expressed in the chapters are those of the authors. Whilst Emerald makes every effort to ensure the quality and accuracy of its content, Emerald makes no representation implied or otherwise, as to the chapters' suitability and application and disclaims any warranties, express or implied, to their use. British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library ISBN: 978-1-83867-938-5 (Print) ISBN: 978-1-83867-937-8 (Online) ISBN: 978-1-83867-939-2 (Epub)

Table of Contents Introduction Chapter 1

Game Studies and Gamification

Chapter 2

Defining Gamification

Chapter 3 Gamespace, Simulation, and Gamification Chapter 4 Histories of Gaming and Computation Chapter 5

Gamification, Power, and Networks

Chapter 6

Gamified Health and Bodies

Chapter 7

The Labors of Play

Conclusion References Index

Introduction In 1960 the German philosopher Eugen Fink wrote Spiel als Weltsymbol , or “Play as a Symbol of the World.” The work portrayed play as a wellspring of creation, a sort of cosmic power source that generated “the world”: the process by which all phenomena make themselves known to human beings (Loht, 2016). Fink also claimed that play revealed the fundamental purposelessness of the world, a vast tumbling whirlpool of causalities. For Fink, the human need for play is rooted in the desire to be co-constituted, embodied, in the world (Fink, 1974). We wish to exercise freedom reflexively, to live and create without consequence. The work went relatively unnoticed in the English-speaking academic world. Play (for the pragmaticminded) has primarily been treated as a theoretical dead end by “serious” thinkers. Perhaps its absence in most critical scholarship is because, as Fink noted, nothing comes of it – play roots itself in irreality, or what might be rather than what is. Despite play's often slippery ontological status, both play and games have begun to creep once again into the modern conscience. Video games have become one of the largest media forms in the world, spawning a global “gamer culture.” Films such as Black Mirror's Bandersnatch and Spielberg's Ready Player One muse on the world as gameplay, a series of choices and consequences directed and designed by an enigmatic gamemaster. These narrative universes place the modern individual in a maze of choices and rewards. The concern with the vast matrix of technology that precedes every collective thought and action is a common theme in both games and gaming culture. Thus, gaming culture and play have become seemingly ubiquitous topics in the study of technology and media. Outside of deep subcultures and media narratives, our everyday, quotidian existence also seems increasingly gamelike. Ever:

multiplying categories of gamelike applications such as Facebook , the social media giant that contains game elements like points and rewards, or Trello , productivity software that provides level-like tracking for tasks and “power-ups” that give a playful façade to labor, inundate consumers. Also, the mobile applications market is suffused with free-to-play, free-to-buy, and “freemium” products that draw on the gaming boom. They promise to enhance daily life, to give it new meaning by drawing on the wellspring of play while also providing direction with the rules and rewards of a game. In the digital age, play becomes a wellspring of possibilities and also a wellspring of profitable data. Collectively, humanity is entering into the age of surveillance capitalism , where data-hungry corporations and governments increasingly influence everyday life (Zuboff, 2019). All of our “free” applications are not for charity. They expand the base of users via a nonexistent entry price and then profit on the data users' produce, mining it for themselves and third parties. All these data have produced a cottage industry of data brokers, selling to the highest bidders (Steel & Dembosky, 2013). Every action becomes quantified, monitored, and fed into advanced predictive algorithms and machine learning systems, which are driven by dispersed human labor (Lanier, 2013). Culture, capital, labor, and consumption are increasingly driven by “playful” applications that borrow from games but never fulfill the category of a game. As Fink suggests, play is a type of energy source, but in surveillance capitalism, the consequences and the stakes of play are genuine. This book is meant to address these liminal applications, which are commonly referred to as gamified applications by industry professionals. In 2018, the market share of gamification was expected to hit around $11 billion by 2022 (Gamification Market, 2017). These statistics are only drawn from companies that brand themselves as selling gamified services; many more companies rely on gamified design, such as Facebook , Instagram , Twitter , and many other social media sites. The rate of gamified applications has increased significantly in recent years, but they remain relatively unaddressed in critical scholarship. Gamification is a unique practice: while gamified applications draw on games, they do not

purport to be games. Gamification draws from a vast array of practices and pursuits associated with game design and play in order to produce social and behavioral change. In recent years, scholars have examined how games and play have evolved within the context of our digitally oriented societies. While this project, in many ways, is the focus of many collaborative efforts across disciplines, my small contribution focuses on how games and play are tools in maintaining large-scale social and economic simulations that seep out into our lives, guiding our actions and beliefs for profit. To do this, I explore how game design, in concert with surveillance, produces a method of seductive control . This phrase will be unpacked over the course of the book, but the simple definition is pleasure-oriented, playful control without an endstate . Unlike control that utilizes punishment and discipline, seduction works as a motivator based in games and play. Surveillance capitalism revolves around a profound asymmetry in “knowledge and the power that accrues knowledge” (Zuboff, 2019, p. 11). The institutions that collect and model out data know everything about us, but we seem to be unaware of their slow incursion into our everyday lives. I argue that play and seduction are two critical aspects of what Shoshanna Zuboff calls a “psychic numbing” to the effects of wide-scale dataveillance. She states that gamification presents a significant technique in the collection of data, serving to motivate use while obscuring surveillance and manipulation (Zuboff, 2019, p. 314). As such, games and game design have become an instrumentalized so-called “big data” revolution. However, the use of game design in building large-scale data mining and surveillance enclosures has yet to be explored in full. Oversights occur because of two significant issues. First, a critical history of digital games as “serious” computational media has yet to emerge (Lowood, 2009a). Second, due to this lack of history, scholars have not developed a critical vocabulary to examine games beyond the current focus on “gaming” as a type of leisure culture. By this, I refer to the primary aim of critical scholarship on games, which contextually examines digital games , game industries , and game cultures : the material, social, cultural, political, and economic aspects of playing games.

This project intervenes in Game Studies by framing a game design as an innate extension of computation and simulation. Games and game design played a large role in determining the current stage of computing: networked surveillance, big data, simulation, and predictive modeling all utilize elements of games and game design. I hope to provide a set of terms that can aid in expanding the ways that games are studied, expanding scholarship beyond the immediate concerns with gaming culture and looking at how game design is affecting people's everyday life. In short, this book is dedicated to establishing gamification as a theoretical process , an assemblage of techniques with histories rooted in simulation, computation, and social control. As such, studying gamification goes beyond market predictions, business applications, and social effects: gamification is part of a wider push to assimilate, monitor, and manage human populations through a unique brand of seductive design that focuses on power without force and control without discipline. As such, I argue that gamification contributes to an emerging form of governmentality rooted in an increasingly technocratic society. It is a design philosophy mired within the global deluge of surveillance capitalism.

Seduction and the Stack To some degree, the growth of gamified applications is related to the increasing complexity, and digitalization, of play. Digital gaming is a combination of technology, play, and sociability that relies on the technological embodiment of players. These attributes identify digital games as a particularly conspicuous aspect of “new media” (Dovey & Kennedy, 2006). Gaming relies on the convergence of play, consumption, simulation, media technologies, human feedback to manipulate and to create pleasurably seductive human (or nonhuman) bonds with machinic systems and computational protocol (Giddings, 2007a). The intensive bond between human and computer, cemented by seductive design, is leading to new approaches in social and economic organization. Even more important, though, it is leading to new forms of governance and control.

Scholars have long looked for some type of teleology in media history and its eventual “remediations” (Bolter & Grusin, 2000; Kittler, 1986). However, the most substantial changes in our sociotechnical lives tie into a computer-based “architecture of governance,” or what Benjamin H. Bratton (2015) calls The Stack . The Stack is oriented around planetary-scale computation, a “metainfrastructure” that collects and parses increasingly large amounts of information. This large-scale technical infrastructure provides the backbone for new ways of control backed by the multilayered technocracy of largescale networked “layers” that “arrange technologies vertically within a modular, interdependent order” (Bratton, 2015). The Stack comprises large-scale technological agencies (which shape political and economic geographies) and also vast layers of data archives (which shape the ways we interpret concepts like politics, economics, or geographies). The Stack may seem like a hyper-object; too large to properly wield in any meaningful theoretical way. However, Bratton makes sure to note that the Stack is made up of heterogeneous layers, a messy (slightly) accidental assemblage whose architecture grows more real and more embedded every year. It operates on six distinct layers: Earth, Cloud, City, Address, Interface, and User. Bratton (2015, p. 11) states, “each layer is understood as a unique technology capable of generating is own kinds of integral accidents…These layers are not just computational…The Stack is also composed of social, human and concrete forces.” Each layer, from bottom to top, can insert modes of control at almost any point in the chain. The scenario Bratton puts forward consists of human and nonhuman “Users” bound together by “Interfaces.” The interfacial layers parse user data into a series of tagged geographical “Addresses” which form a simulative map of “Cities” and “Earth,” which are stored and accessed by the “Cloud” layer (Bratton, 2015). In short, the Stack produces multiple totalities of control all cobbled together via vast, networked architectures. My primary argument is that the gamified design performs an increasingly necessary task: gluing the user to the interface and encouraging prolonged cooperation with technological conditions. Bratton (2015, p. 220) states that “the interface layer consists of any

technical-informational machine, compressed into graphical or objective formats, that links or delinks Users and the Addressed entities up and down columns within the Stack. Its role is to telescope, compress, and expand layers of the Stack, routing User actions both up and down as they go.” Interfaces are not only the graphic user interfaces we toy with on our screens; they comprise a “generic structuring of links and boundaries” forming “any point of contact between two complex systems” that “govern conditions of exchange” between systems and users (Bratton, 2015, p. 220). In short, interfaces provide logics of control and exchange between ourselves and our technicized daily lives. As we will see in later chapters, the history of computation and simulation has been a long, complicated dance with games and game design. Game theory, contingencies, probabilities, and possibilities have driven social, genetic, and evolutionary simulations to new heights (Erickson, 2015). At each turn, however, game theoretical systems only produce outcomes oriented to rational or nonrational actors; the results of such simulations are only sometimes useful (Erickson, 2015). Social and economic modeling is best achieved through dataveillance, a combination of programmatic surveillance and algorithmic control (Clarke, 1988; Eposti, 2014). Algorithmic protocol increasingly impacts everyday life, and we live in a society that encourages and justifies dataveillance (Clarke, 1988; Eposti, 2014; Smith, 2018). Algorithmic control involves “sprawling assemblages involving many forms of human labor, material resources, and ideological choices” (Finn, 2017). Because data drive capital in the Stack, I often see a critical focus on data rather than the user–interface networks that produce it. To me, this appears to why we have overlooked (game) design as a key aspect of our collective experience with interface. As Bratton (2015) notes, the Stack runs in real time. It needs, among other things, constant input. That input also has to be “real” in the sense that models must be actionable within a short frame of time. We have real-time climate models, the product of thousands of sensor and satellite inputs observing the atmosphere at fraction-of-asecond intervals. Why not have real-time social and cultural models, as well?

In terms of the Stack, most of my arguments place gamification at the levels of User and Interface. Games are, after all, modalities of design and Users are a creation of design (Bratton, 2015). However, if we begin to peel apart the history of computing and simulation, we can see that gamified design plays a significant part in the Stack's “new architecture” because it focuses on control through seduction rather than force . According to Baudrillard (1979), seduction is a form of play or playfulness. Seduction is a false weakness – it is not sovereignty or outright force, but instead acts through the inception and channeling of desire. Seduction, then, is the interplay of desire and potentiality. By channeling desire, seduction focuses on potentiality, not outcomes; it works through the possibility of a desire's fulfillment. As such, it is the primary origin of simulation – the ideation of possibility and the desire to pursue, consume, and possess its materialization (Baudrillard, 1981a, 2005). It is nondisciplinary power – it only exists through continued processes, meaning that any sort of finality is arbitrary for seduction: it acts only to continue itself. Baudrillard (1979) points out that seduction ends once a desire is fulfilled. Using sex as a metaphor, he states that once sex begins, seduction – or the process of sexual play – terminates and must be restarted. In short, seduction is the willing extension of desire, not the fulfillment of it. It is a design philosophy that produces an “infinite game” whose rules only seek to extend play without naming an end-state or a winner (Carse, 1987). Game design often uses the word “engagement,” which is the attentional resources of the player. Seductive design promises complete and willing engagement – a never-ending parade of contingency and desire (Anderson, 2011). Seduction begins with users and interfaces, but the result is what fuels the other layers of the stack: data and capital. The best outcome of application design is user data. With enough data, application designers can model and influence possible outcomes. Gamified design provides the seductive choice architectures that drive engagement. Gamified applications aim to produce the right data about users, data that can be put to use in making more efficient designs. Gamification is a vector for the gradual acceptance of real-time, digital governance. As such, I think

that games, and play, provide a window into how and why we continue to create and sustain the Stack. Bratton (2015) does an excellent job laying out a “big picture” of the Stack. In his scenario, the user is at the bottom of the totem pole, the base ingredient of our modern global technocracy. Are we forcibly arranged at the behest the Stack, or are we expected to arrange ourselves into the needed configurations? Tracing gamification back to its technical and philosophical roots, I believe, reveals that the latter is most important – we must arrange ourselves. For the foundation of a vertical structure to hold, it must be stable – and all the better if that stability is self-imposed. Gamification, in a nutshell, merely heeds us to follow our ludic desires, getting rewarded for doing the right things at the right time. For the most privileged among users, we should enjoy holding the layers above us stable.

Gamification at a Glance Practitioners typically define gamification as a business or marketing strategy that began to emerge after marketers and public relations professionals noticed the success of traditional video game platforms in driving behavioral practices among players (Campbell, 2011; Davenport, 2010; Delo, 2012; Zicherman & Linder, 2010). A key focus of gamified applications is promoting, regulating, and tracking engagement with products, services, spaces, institutions, and ideas through motivational tactics embedded within seemingly simple aspects of game design. For example, Google and Niantic's game Ingress uses competitive territory defense that players access and take hold via location-aware devices – resource nodes, via modified GIS systems, are embedded into physical spaces such as monuments, museums, and dog parks. Ingress was mobilized to drive research into navigational issues affecting pedestrian traffic and location-based advertising by studying the routes players take to reach individual nodes and their motivation in regards to rewards for traveling longer distances. Each incidence of gamified design is linked to surveillance and data gathering. However, it is unique because users seek out this mode of surveillance for its rewards.

Gamification represents a wide array of applications used for a variety of purposes. In a nutshell, it represents a new take on life, one that embraces playful-but-serious surveillance and introduces new techniques that attempt to redefine the categorical position of “player.” Gamification achieves this by introducing game mechanics into nonludic environments via design (Zicherman & Cunningham, 2011). In addition to design-oriented aspects, gamification embraces behaviorism by promoting playful behaviors, such as seeking and parsing information, arranging patterns, route finding, leveling, progression, self-archiving, socially exchanging information, and seeking positive feedback through intrinsic and extrinsic rewards. In short, gamification as a set of design practices takes a contradictory, but strangely unifying, approach to labor and leisure (Fuchs, 2014a; Raczkowski, 2014; Raessens, 2014; Schrape, 2014). It toys with boundaries between leisure and labor by circumventing the common definitions of both (Hamari, Huotari, & Tolvanen, 2014). Gamified applications profit from exploiting the idea that labor can be converted into a playful activity to increase productivity and engagement – that leisure can become labor. However, play is often associated with free-wheeling, nonproductive, redundant, and chaotic actions that do not directly interfere with quotidian processes of law, capital, or culture (Huizinga, 1950). Gamification seems to utilize play in a manner that promotes control, order, and capital. The outcomes of this experiment in design are thus far unknown. This contradictory set of purposes and outcomes is the primary focus of this project: a key question concerning gamification is “why play ?” Deploying play for the purposes of control seems counterintuitive; if play is truly nonproductive from the standpoint of capital why attempt to use it for purposes of production? If it eschews disciplinary tactics then why use it to promote processes of behavioral categorization? This question lies at the heart of gamification: how can a mode of control harness a force that, by some interpretations, inherently resists uniformity? The answer lies, primarily, in what can be considered play. Gamification uses play, but only in a particular context. Play is ambiguous and contains a variety of actions, outcomes, and

practices (Sutton-Smith, 1997). Some aspects of play, such as free play (Derrida, 1966), resist centralized constraints. There are also aspects of play that favor regulated, centralized, and rule-based competition (Baudrillard, 1979, 2001; Caillois, 1961). Gamification primarily leans toward these by using the compulsory nature of progression to promote behavioral modifications in players, specifically to increase efficiency in everyday actions by rewarding players for desired behavioral outcomes. On this level, play can be used as a definite set of potentialities aimed at individual or collective control. Since games are rule-based systems designed to structure play into ordered contingencies, game design and the resulting gameplay serve as a critical aspect of gamification's relationship with control. Games indeed exhibit control on an individual level, but they only instantiate it in terms of gameplay – the cybernetic loop between player and game that comprises a negotiation of agency rather than a system of outright control. Dovey and Kennedy (2006) state that gameplay is the site of power and control in gaming, and it is a constructive power that comprises “the site where the game and player contest each other's capacity to structure and give meaning to their ongoing interfacing” constructed through an “economy of desire.” Gameplay is actively constructed between the player's agency, the game's mechanics (its contingencies and rules) and its logics, or the intended outcomes and progressions (Lorant & Lieury, 2014; Sicart, 2008). Gameplay, as an ongoing negotiation of desire, cannot survive as a domineering mode of control. Instead, (game)play is seductive (Baudrillard, 1979; O'Donnell, 2014), meaning that it exhibits weak or soft control through challenges and promises made to the player – the player willingly engages in constructing his or her desires through the contingencies set forth by gameplay.

Seductive Design Baudrillard (1979) states that seduction, like play, is “entangled” with production and power, but must not be confused with either. Seduction is an inception of desire and possibility – it serves as an

alternative route to coercion that can either serve the ends of disciplinary power and production or reverse them. One aspect of seduction is its reversibility – it can go in a variety of ways, and it can reverse course just as quickly. Seduction presents a challenge but does not present a contract – it does not invite any conclusion or conclusive state of affairs (Baudrillard, 1979). If a conclusion is reached, seduction ends. Seduction is the key to gamification's relationship with power, productivity, and control. Gamified applications instantiate a gameplay loop by focusing on what is possible, rather than any final or actual outcomes. For example, gamified applications rarely offer an endpoint. Users of applications like Ingress can never “beat” the application. They engage in an endless stream of potential challenges and rewards. When they are rewarded for one challenge, another is generated. Thus, through gameplay, gamification achieves a state of equilibrium between leisure and labor by never conclusively being either one – it serves as an alternative to both. Gamified applications hint at the possibility of productivity, but never fully arrive at that point. Users are productive in terms of providing behavioral data, but they are subjectively working toward progression as it is interpreted via game dynamics – their productive behavior ties to the design of the gamified application: the continuance of play. Seductive power, as an alternative to coercive or disciplinary power, is at the heart of gaming and gamification. Understanding how this modulation of power acts on the everyday lives of people whose lives are increasingly gamified is largely the purpose of this study. Gamified applications often extend seductive gameplay into extensive networks while concealing the aspects of “games” or “play” embedded within the application – people become engaged in the loop of gameplay without fully being aware of their status as “player.” Rather, they are viewed as users, those who employ applications for quotidian social or technical outcomes. Gamified applications are rarely marketed as games, thus downplaying the idea that they are either leisure or labor. However, while players are productive, the applications also actively remove any sort of finality to the actions performed – gamified applications never end. Gamified applications

create continuance by introducing a sense of choice and variance. Thus, what users do through gamified applications does not entirely feel like labor, either. Their point of engagement is removed from a definitive endpoint and replaced with the intrinsic reasoning of gameplay – they do it because they can progress. At the same time, gamification drives the user-efficient production of useful (and profitable) data. Users maintain a consistent, live connection with the gamified interface, introducing a constant protocol aimed at control. It is crucial to address gamification as a mode of control because it brings new modes of surveillance, governance, and monetization to everyday life. It also creates different categories of players; when engaging in gamified activities, players are no longer engaging in purely self-referential gameplay – gameplay where actions taken ingame correspond only to the game itself. They are participating in a more comprehensive network of consumerism, education, and surveillance that has direct connections to power, capital, and modes of production. Addressing how everyday life is enhanced or disrupted through gamified applications because important evidence suggests that they are diffuse methods of control enacted through game design (Dragona, 2014; Raczkowski, 2014; Ruffino, 2014; Schrape, 2014). de Certeau (1988) states that “everyday life” involves distinct modes of collective and individual power: “strategic” and “tactical” practices. These strategic practices designed by large organizations such as governments, corporations, and militaries control the flows of ideas, bodies, and goods through space. Tactical practices, the methods by which people navigate and experience strategically designed spaces, originate from place-making activities that allow people to survive. The combination of strategies and tactics occurring throughout space constitutes a large part of everyday life, as it often determines who or what is allowed to move where and act in a particular context. In other words, gamification controls by taking on the appearance of a game based in seductive possibility of choice, risk, and reward by present strategic sets of rules requiring specific tactics rooted in gameplay. I want to explore play as a point of tension between seduction, domination, and resistance. I will reveal that, even as gameplay is used as a tool seduction by surveillance capitalists as a mode of

biopolitical data sifting, play can also be interpreted by players as a place of refuge within the inhumanities of the Stack. Gameplay is a way to rationalize or even enjoy life under surveillance capitalism. This book is not critical of big data or the Stack as concepts (I am not a Luddite by any means); it is critical of how the social and ludic became undermined under the current profit-obsessed machinations of ill-regulated entities of power. Exploring the possible benefits and consequences of seductive design choices strengthens our understanding of how playful media technologies and design practices are converging. For example, gamification curiously utilizes anti-gaming logics in its design to keep players within a set of clear boundaries (Zicherman & Cunningham, 2011). Players must not modify or “win” a gamified application – the goal of gamification is to produce measurable, contextualized data rooted in continuous behavior. However, not all gamified applications disguise their gamelike appearance, and they contain varying levels of antigaming logics. Depending on the level of control embedded into the design, gamified applications can be either more or less gamelike, meaning that gamification and games work on a spectrum of seductive power. The spectrum has play on one end, which leans toward intrinsically valuable activities (such as free play). On the other end of seductive power, highly controlled play leans toward ever-increasing modes of efficiency not just related to games but branching to serve other related forms of production and capital (Deterding, 2014). Gamification lies at the controlled end of the spectrum: it is neither entirely separate from gaming, nor is it the same. Some applications, like Ingress and Pokémon GO , are more recognizable as games. Others, such as Twitter and Facebook , have more deeply embedded links to game design. Exploring gamification as a full set of practices that allow varying degrees of freedom and transparency concerning game mechanics significantly improves upon current literature concerning gamification. However, it will also position the debate on gamification in a historical context, and establish it as a process that has been going on for quite some time.

Researching Gamification This book grounds the study of gamification on the history of games in general, and computer games explicitly. It also reaches out to broader spheres of media and software studies, touching on digital governance, surveillance, and power. Because there is relatively little literature on gamification on the level of play and everyday life, these research questions expand upon the work currently available. Four primary questions arise from considerations on why gamification has suddenly gained traction: (1)

What place does gamification hold in relation to seduction, games, and play? (2) What are the conditions of knowledge/power that enable gamification? (3) How is gamification materially and socially instantiated through gamified applications and uses? (4) What are the historical conditions that have enabled gamified applications and gamification, in general? These questions lend themselves to two pervasive metaquestions addressed throughout this analysis: what is gamification, and why does it use play as a mode of control? As such, the goal of this book is to empirically examine how gamification alters a variety of networks in favor of play, including social networking, healthcare, workplace productivity, and consumer research. Specifically, there are four primary theoretical lenses through which gamified applications are examined: (1) ontology/epistemology, (2) power/knowledge, (3) protocol/biopolitics, and (4) space/simulation. Each lens has a specific focus. Ontology/epistemology examines the definitional qualities of gamification and how they are deployed currently and historically to produce knowledge and capital. Power/knowledge addresses how gamification shapes and changes environments by redefining techniques of control within those environments. Protocol/biopower focuses on how gamification creates subjects and influences behaviors. Finally, space/simulation examines how gamification utilizes simulated spaces to collect data

and drive profits. Examining gamification through these separatebut-connected lenses requires the understanding that gamification did not just pop into existence with all of its technological, ethical, and ontological quandaries. We cannot assume that gamification is tautological – that it exists because it does. Gamification is not a “new” development. Rather, it is the product of historical relationships between play, games, power, and technologies. One key aspect of exploring gamified applications is analyzing power and knowledge in the context of networks. The well-known theorists used to this end are Michel Foucault, Jean Baudrillard, Gilbert Simondon, Gilles Deleuze, and Bruno Latour. Other scholars featured come from areas such as Game Studies , i.e., Galloway (2006); Software Studies , i.e., Benjamin Bratton (2015); and Algorithm Studies, i.e., Ed Finn (2017). Each of these theorists and works complements the other, in that all are interested in compiling a working history of computation, networks, culture, capital, and power. Hayles (2012), Simondon (1992, 2007), and Latour (2005) are scholars often controversially identified as “posthuman.” To put it simply, they assume that the human being is not always the center of relationships; instead, “humans” are a changeable category shaped by a variety of forces. Posthuman scholarship resists making humans a de facto focal point in any analysis of society, media, and technology. Earlier in this introduction, I used the Stack to note why unraveling the process of gamification is essential. Like Bratton (2015), my analysis of gamification also assumes that humans are just one of many unevenly distributed actors, each with its specific brand of affective capacity, or agency. Finally, this analysis also assumes via Foucault (1980) and Baudrillard (1979, 2005) that power and desire are inherent in all relational interactions and that the complexities of these interactions must be a focal point for research. I feel it is necessary to build a critical analysis of gamification by addressing several topics. First, I propose that gamification and games are like identical twins: they look the same, but they have very different personalities. Gamification can be dangerous and ethically murky, but it also fulfills a purpose in replacing former coercive surveillance and control mechanisms. I also think that

gamification presents a unique chance to look at a quiet revolution in “algorithmic surveillance” (O'Donnell, 2014). I state that gamified applications represent a new approach that draws from old sources – the concept of “life as play” can be traced back to the ancient Greek philosophers and Eastern Zen philosophies (Sutton-Smith, 1997). In the end, gamified applications use a ludic interface that serves purposes other than self-referential play – it is a mode of packaging and implementing simulation for the masses. Gamification may be “better” than more disciplinary methods like hard surveillance; at the same time, it is also a wolf in sheep's clothing – it does not propose any new solutions to old problems with control, surveillance, and hierarchy. This research primarily argues that gamification uses what was already present in play to implement far-reaching changes in environments where it is deployed, and it does that by seduction rather than coercion. The implementation of gamified applications depends on the ability of gamification to adapt to different spatial, technological, and social factors across a range of contexts. This assumption operates against the tendency of media theorists to emphasize the overarching agency of media technologies as a priori , as if “media were naturally the way they are without authors, designers, engineers, entrepreneurs, programmers, investors, owners or audiences” (Gitelman, 2008, p. 9). Because gamified applications operate via media, it is congenital in the production and maintenance of media-oriented protocol. Protocol does not assume media technologies are authoritative while “the social processes of their definition and dissemination are separated or forgotten” (Gitelman, 2008, p. 6). Examining gamification through different lenses relies on looking at related media technologies as historical subjects that coconstitute the environments through which they operate.

The Genealogy of Gamification The primary method I use is genealogy . Genealogy is a method developed by Foucault (2010) to account for the confluence of power, knowledge, and practices at the horizon of events as they occur. Genealogy, for Foucault (2003), is a “form of history that

accounts for the constitution of knowledges, discourses, domains of objects, and so on, without having to make reference to a subject which is either transcendental in relation to the field of events or runs in its empty sameness throughout the course of history” (p. 306). As a study of an “emergent history” of contextual power and knowledge, genealogy does not seek a teleological truth; instead, it attunes to the materialization of many historically situated truths (Kendall & Wickham, 1999). Genealogy, according to Kendall and Wickham (1999), is discursive – it focuses on statements (i.e., ideologies, beliefs, “knowledge,” and documentation) and visibilities (i.e., the material/technological conditions of practice). Of course, in order to fully understand the conditions of statements and visibilities, one must first tease out exactly how they came to be regarded as cultural or discursive truths. The exploration of cultural truths requires a second method, also developed by Foucault (2010), known as archaeology . Archaeology and genealogy are two branches on the same tree. While genealogy focuses on the conditions of power and knowledge; generally, archaeology utilizes specific historical events, processes, and technologies to “decouple” historical events from legitimacy (Foucault, 2007a). Archaeology does this by separating the “fact of acceptance” of the thing in question to “system of acceptance” that gives it legitimacy as a discursive fact (Foucault, 2007a). Foucault (2007a) moves the focus of historical inquisition from events or objects to the processes that allowed them to “exist” to the point that they legitimize as a part of an epoch or era. Specifically, Foucault (2007a, p. 63) states that archaeology is “proceeding from the fact of acceptance to the system of acceptability analyzed through the knowledge-power interplay.” Foucault's (2010) archaeology seeks to “excavate” objects, events, and statements from their previous place as naturally occurring, and bring to light questions of the organized deployment of statements and visibilities, which he calls discursive formations. I genealogically excavate gamified applications using analyses of technological objects, practices, structures, and computational programs in an archaeological fashion. These include early games, marketing tactics, simulations, and spatial representations.

Specifically, I focus on a collection of gamified mobile applications that span a wide array of uses, including location-based services, consumer research, social networking, health monitoring, and pet care. I also juxtapose these applications with previous technologies and programs that inform their design and use. Genealogy is unique in that it invites the use of case studies to excavate tensions and points of resonance between seemingly disparate examples.

Gamification: Old and New Genealogy allows me to juxtapose older examples of “protogamification,” such as Nimbi , with newer ones, like Ingress . Tracing the route of gamification can reveal that, as a set of practices, it shares many traits with the current “algorithmic sublime” occurring in algorithm and data studies: it is either demonized or lauded (Smith, 2018). This is, perhaps, because gamification shares a history with the current push for algorithmic modes of control. For this reason, I trace points of contact in the development of gamification across different temporal and spatial contexts. For example, Chapter 3 analyzes the historical connections between games, game theory, and early computation, especially the development of game-based algorithms. In Chapter 4, I examine the history of game theory's goal of mapping and simulating humans and animal behavior, and link these pursuits' historical examples of simulation-based programs like Game of Life , early geographic information systems such as radar, and early games like Pong and Spacewar . Each piece of historical evidence suggests that gamification's history has primed it as a design tool for linking user and interface. These examples are combined with a variety of applications like Strava and Clue that address gamification's modern uses in the context of historical conditionality. The selection of analyses contained in this book aims to chart relationships between knowledge, power, and the material conditions that enable gamification to be identified and deployed as a mode of control in service to surveillance capitalism. The historical analyses serve as the archaeological exploration of processes that give gamification meaning and place it as part of the base layers of the

Stack. As a whole, my history contributes to an overall look at how gamified applications toy with concepts of power and knowledge in a variety of contexts. According to Kendall and Wickham (1999), a genealogy typically involves analyzing statements, visibilities, contingencies, and techniques that situate the topic in terms of a knowledge/power dichotomy. Statements focus on discursive statements about gamification, which I developed in Chapters 1 and 2. These chapters respectively analyze insights into gamification from recent game studies literature and explore ambiguity in past ludological texts utilized in concert with gamified applications. By analyzing both recent game studies literature and past ludological texts, I explore why gamification has not been fully recognized as a practice directly related to play and gaming. Despite shared techniques and visibilities. Visibilities deal with actions and materials – to put it simply, what is seen. Visibilities are related to practices. In this case, practices connote the daily strategies of individuals dealing with the power relations they encounter in the course of their ordinary, everyday lives (de Certeau, 1988). Practice also implies that a critical focus of genealogy is not necessarily the abnormal or the crucial historical event, but rather the assumption that all cultural production is ordinary, and in its ordinariness, we can find the relations that make cultural production visible (Williams, 1989). Excavating relations involves selecting commonly used current applications which, on the surface, are not often cited as unique. However, the popularity of applications like Foursquare also gives a clear picture of how gamified applications insert themselves into the middle of ordinary cultural production. Additionally, I focus on past computational technologies that enable modern gamified applications. This focus on juxtaposing current, popular applications with lesser-known historical developments serves to highlight the slow inflation of gamification from research to reality. Contingencies account for how and why statements and visibilities are identified. They are the defining characteristics of historicized power relationships. By separating contingencies into categories, or “lenses,” I am following Foucault's

(1980) insistence that an examination of power's conditions of possibility must not be localized “in the primary existence of a central point” (p. 93). Rather, gamification can only be “seen” as it becomes “known.” In other words, multiple contingencies are in action simultaneously and form as a web of relationships. In Chapters 3 and 4, I uncover how games', design's, and computation's shared histories help to reveal the material conditions of gamified power and its impact on culture. Cultural contingencies denote the relationships between power and knowledge. Ontological contingencies denote how an object operates in a particular context. Epistemological contingencies denote what processes or institutes contribute to the visibility of a technique or technology, or how we come to “know” it. Finally, material contingencies are the physical conditions that enable the network to support itself – the arrangements of actors (players, social contexts, and technologies) that provide gamification's identity as a distinct set of relations that are deployed in a certain manner. This project derives its research questions concerning the ontology, epistemology, and affective capacity of gamified applications from the study of contingencies. I examine how gamification generates knowledge about different subjects – pet owners in Chapter 5 and employees in Chapter 7 – as they operate in their chosen environments. In turn, the data gathered on subjects as they go about their daily gamified business alter the very environments that applications were meant to monitor and the subjects they were meant to categorize. Examining how gamification alters the environments where it is used involves understanding how gamified applications shift physical and discursive conditions strategically. Techniques relate directly to the issue of deployment. Techniques are the technical modes of enacting power relations. They can be juridico-political, material, or cultural. Technological objects deploy power through their interface, conditional to what acts can be performed (Gane & Beer, 2008; Manovich, 2002). Panoptic modes of surveillance are deployed in certain ways and with specific goals, and games themselves circulate power through arrangements of mechanics and logics. For example, in Chapter 6, I examine

international health protocols and their relationship with gamification. Understanding how health-related applications generate capital through knowledge is key to understanding why gamification fulfills a practical need in the current healthcare market. Chapter 8 explores the effects of making public discourse a zero-sum game, altering the ways that culture circulates. Also, in Chapter 2, I examine the ideological value of gamification in the form of a comparative literature review; specifically, I look at how it works as a technique for exploiting power and progress via playful behavior. The web of techniques presented in this book is not meant to be all-inclusive of the archaeological or genealogical method. Each chapter examines, in part, why gamification is viewed as valuable in the area where it is deployed. Gamification must be a theoretical design technique that involves both games and play, and recognizing it as such places it squarely within the context of Game Studies. However, it must also be recognized for what makes it unique – the use of game mechanics is more brazen and manipulative than self-referential games. Understanding the similarities and differences between games and gamification, in addition to exploring the historical signatures that account for these differences, will contribute to a more balanced understanding of gamification and its applications. Additionally, it will lay the groundwork for the critical study of gamification from the standpoint of Media and Game Studies. A genealogy of gamification that addresses its ontology, epistemology, history, and environmental effects reveals that game mechanics are in play across a variety of applications that are not immediately recognizable as “games.” Each application, in turn, affects the everyday activities the applications are intended to facilitate. In short, understanding why and how gamification works in terms of statements, visibilities, contingencies, and techniques is imperative to producing a clear and relevant picture of how and why it has skyrocketed in popularity. What does gamification provide that another method of engagement and control lacks? I suggest that gamification's focus on continually evolving epigenetic spaces spell its inevitable obsolescence. One key point of seduction is that it does not end at a certain point – instead, its very

purpose is the continuation of desire. Seduction bypasses power and production by eliminating any endpoint – seduction is the embodiment of procedurality. Once the boundary between play and labor is dissolved, only the arbitrary process of play remains. The outcomes of gamified applications will cease to be meaningful or informative outside of the intrinsic value of play. If everything is reduced to play, then gamified applications and the institutions they serve are no longer needed. When labor is eliminated, so is capital. The need for a nonplayful outcome, such as the production of capital or profit, or any productive outcome at all (like labor), becomes pointless. By employing seduction, the institutions formerly served by gamification will become reliant on its continuation. Applications meant to harness seductive design will result from play rather than utilize it. Once a process results from play, it becomes a game – rendering its results arbitrary. To explore this point, I examine how the inevitable failure of antigaming logics embodies the future of gamification. In order to maintain an equilibrium, gamification resorts to the very disciplinary measures it seeks to circumnavigate – it utilizes a set of fail-safes to keep play in check, to keep it productive. However, discipline cannot survive when seduction is in play. Seduction requires that desire must never be fulfilled – the seductive game must continue. To do this, the gamifications' architectural components must constantly be modulated to continue channeling desire. Like modding and cheating a game, which inevitably alters the game's architecture, players will continue to evolve gameplay in gamified applications to suit their wishes (and not the wishes of the designers). As such, the institutions who seek to control gamification will find themselves controlled by the desire of the players they rely upon. Players, whose gameplay is profitable data, will push gamification's ludic environments increasingly toward a game by circumventing the logics in place to make their data a source of capital. This does not mean that the data will cease to be useful, but it will only be useful in the context of the game itself. The institutions, then, will be at the mercy of the game rather than the gatekeepers of play. This book combines theoretical work with a genealogical approach to critically examine the pervasiveness of gamification

across temporal, spatial, and social contexts while also suggesting that gamified applications are far more than a marketing ploy. It carefully examines gamification's relationship with everyday life and therefore advances the idea that the impact of gaming, as an industry and a set of practices, is greater than the production, dissemination, and use of video games themselves (see Galloway, 2006). Gamification continues to fan outwards, manifesting itself within diverse, emergent, and sometimes contradictory social and technical matrices. For example, gamification crops up in areas as diverse as healthcare, big data, simulation, consumerism, design practices, and even pet care. These matrices have, up to this point, been ignored in the broader conversation concerning media technologies and practices. Gamification comprises a collection of many procedures that are used differently across contexts.

Chapter 1

Game Studies and Gamification Media scholars have been reticent to study gamification as a legitimate product of media or gaming culture. Since its public dismissal by Ian Bogost (2011), gamification has only had a small amount of play in the broader debate concerning media and games. While Bogost's pronunciation that gamification was “bullshit” could be considered heavy-handed, it was also written for a mass audience and published on the popular gaming site Kotaku . However, scholarly articles have been no less caustic. One, published in Games & Culture and written by game designer John Ferrara (2013), dismisses it in a no less totalitarian fashion – Ferrara calls it a “lie.” He states that the gamification “fad” assumes games can be “strip-mined for ‘useful’ bits that, when tacked onto conventional applications, should be expected to have the same effects as true games” (p. 289). Rather than viewing games and gamification as a spectrum of similar practices with differing outcomes, Ferrara makes it seem as if gamification has a predatory with games. He states: “This lie exposes a disdain for play and an incapacity to perceive games themselves as useful and worthwhile endeavors” (p. 289). Ferrara's claim is based on a formal argument about games – that there are “true” games – and it is a caveat that is repeated often by many early game studies scholars (Bogost, 2006, 2007; Juul, 2005; Salen & Zimmerman, 2003). This project takes a different viewpoint. Rather than assuming there is any sort of “true” game, I question the narrative that games have a definite form and that play has a definite function.

In 2014, the debate concerning gamification was encapsulated in The Gameful World (2014), an edited volume that sought to lay out the “rhetorical positions” of various gaming and media scholarship. In its opening chapter, Sebastian Deterding (2014) provides a succinct map of the current debate on gamification centering on the current “ludification of culture” and its ethical, material, economic, and material fallouts. Deterding also argues that understanding gamification also has to do with the “cultivation of ludus,” or the movement of games (and game design) to the center of modern consciousness in the West. He notes that distinct differentiation between scholars working in design and industry who are excited about the prospects of gamification, and the more dour resistance of scholars. Like Bogost's early claim, scholars have claimed that gamification is a “colonizing attempt” (Aarseth, 2001) and a theft of innocence from play in favor of “playbor” (Rey, 2014). Of course, things are rarely simple. Deterding states that the debate concerning gamification has fractured into several rhetorics, including exploitation, performance, feedback, systems, pleasure, status, wellbeing, and cultural form. He also notes that finding common ground between these positions will take a leap of theory. Gamification's discontents may be because its theoretical roots are not thorough or grounded in the past or present. While Deterding (2014) presents a modern history of gamification, one which will be revisited in this book, but only briefly. With the exception of one other book chapter that primarily lists historical practices that resemble gamification (Fuchs, 2014b), there has been relatively little examination of gamification's material or social history beyond its “invention” in Silicon Valley (Deterding, 2014). Also, at present, critical approaches to gamification either treat gamification as a unified “thing” (Bogost, 2011; Ferrara, 2013; Fuchs, Fizek, Ruffino, & Schrape, 2014; Kirkpatrick, 2015) or only looked at single applications of gamification (Foxman & Forelle, 2014). Each of these critiques portrays gamification as a simple set of exploitative practices. In critical scholarship, gamification seems to inspire a rhetorical debate on the meaning of play. Often, it is treated as a new development with a short history, a simple computationally driven

design process. What results is a relatively narrow pool of literature to pull from when examining it. Compounding the issues of meaning, there is a reticence in applying critical theory concerning games or gameplay to gamification. While I will not dwell on the reasons for this, one can assume it is because, up until now, gamification has been accepted as a category ethically and ideologically separate from gaming. Couching gamification as an ambivalent set of practices leaves it with no theoretical home and no real body of critical or historical literature for scholars to use. It does not help that the term “gamification” stems from practitioner manuals, industry sites, marketing books, and popular scholarship. Zicherman and Cunningham's (2011) Gamification by Design is one of the first manuals produced that defines and teaches marketers and application designers how to build and distribute successful gamified applications. It also contains one of the first succinct definitions of gamification as a design practice that utilizes game mechanics to increase loyalty, contextual data, and end-user motivation (Zicherman & Cunningham, 2011). In a move that perhaps informs how practitioners view gamification, the cover of Gamification by Design portrays a group of monkeys imitating one another in play. The illustration draws from behaviorist studies of animals. Specifically, the cover evokes the process of “aping,” or using cues to motivate a primate to perform a specific action in a certain context. The cover overtly hints at the behavior-oriented design behind gamification. Because gamification focuses on behavioral control in the context of motivated application or software usage, it has been targeted by software designers as an alternate form of usability methodology (Kumar & Herger, 2013). Data curators suggest gamification as a contextualizing method for data collection (Paharia, 2013). Information on gamification is also frequently curated via online zines, blogs, and industry analyst sites. Popular blogs such as Gamification.co sustain a cohort of industry journalists and commentators. In marketing blogs and books, gamification was touted as a way to produce loyal customers that willingly submit to market-based surveillance and categorize their information (Burke, 2014; Paharia, 2013; Zicherman & Linder, 2010). However, these

practices are portrayed in marketing literature, such as Paharia's (2013) Loyalty 3.0 , as better alternatives to traditional marketing methods like repetitive advertisements and industry prying that are unpopular with consumers (Burke, 2014). From industry and design standpoints, gamified applications are an efficient way to inspire loyalty while also collecting mounds of useful data without coercive or underhanded methods. Pop scholarship portrays gamification with very little criticism – it is often viewed as the opposite of disciplinary approaches to management, labor, and education. For example, McGonigal (2011) claims that gamification can free workers and consumers from the trappings of bureaucracy and disciplinary surveillance by introducing play into formerly invasive practices. Her approach situates gamification as a possible gateway to a slightly less disciplinary utopia. Manuals on education-oriented gamification have suggested that gamified applications are a way to break the disciplinary mold of current educational practices (Kapp, 2012b). By adding play to the classroom, gamification may help in addressing motivational issues that decrease student interest (Kapp, 2012a). Gamification, in most instances, is viewed as a positive practice and a step forward from panoptic modes of consumer surveillance and disciplinary educational approaches (Burke, 2014; Kapp, 2012a; McGonigal, 2011). The positive attitude evinced by pop scholarship is decidedly absent from academic works concerning gamification. Whitson (2013) has introduced gamification into conversations about surveillance, particularly from the standpoint of quantifying everyday activities via wearable technologies like health monitors. Following this, O'Donnell (2014) stated that gamification posed a vital moment to study “algorithmic surveillance.” While The Gameful World (2014) presented a reasonable overview of differing areas of gamification research, the edited volume Rethinking Gamification (Fuchs et al., 2014) presents a complete example of scholarly work to date concerning the impact of gamification as a mode of control and surveillance. The volume approaches gamification from a critical and historical standpoint; it examines gamification as an ideological practice rooted in design (Ruffino, 2014). Gamified applications utilize pedantic

practices linked to educational methodologies (Fuchs, 2014b). The current mode of gamification aligns with behaviorism and the rise of psychology-based marketing approaches (Raczkowski, 2014). However, Rethinking Gamification often casts gamification as a dangerous and ethically murky practice that exploits the human desire to play (Poltronieri, 2014; Raessens, 2014; Ruffino, 2014; Schrape, 2014). Collectively, the chapters in this collection warn that gamification represents new and dangerous examples of capitalism's assault on the everyday life of consumers (Dragona, 2014; Raessens, 2014). In other publications, gamification classifies as a type of “ludic interface,” a collection of design-oriented practices that place gamelike qualities at superficial levels of interaction (Fuchs, 2012). It has also been suggested that any gamified application can also be “degamified” in order to reveal its true nature as a controloriented tool (Dragona, 2014; Mosca, 2012). Critical research into gamification points out that behind the gamelike exterior of gamified applications lies a complex web of control-oriented practices aimed at communal surveillance and complex problem-solving via metadata (Hulsey, 2015; Hulsey & Reeves, 2014; Whitson, 2013). From a critical standpoint, gamification is just now coming “under the knife.” However, the knife often still identifies gamification as its own “thing” – what O'Donnell glibly refers to as the “thingification” of gamification – rather than as a spectrum of practices, related to seductive control and efficiency. I feel that current scholarship is missing the chance to do meaningful theoretical work, viewing gamification as a modern philosophy of design with a long history. Gaps in gamification scholarship arise because gamification is in its infancy despite that its combined market impact is projected to reach over $10 billion in 2020 (BusinessWire, 2015). As I will note in later chapters, this number only includes services that admit to gamified design. Social media giants such as Facebook and Twitter also rely on game mechanics to promote constant engagement. While gamification has been notably successful in the commercial, mobile, and healthcare sectors, little work has been done to explore how game design contributes to its success (Mosca, 2012). Furthermore, there is a dearth of scholarship on the convergence of game-related technologies and practices across additional areas,

particularly in regards to information management, labor, materiality, and surveillance (Byrne, 2012; Danforth, 2011; Fuchs, 2012; Nicholson, 2012; Whitson, 2013). I want to critically examine how gamification acts as a new framework of control that manifests itself as a series of seductive design choices that affect environments, bodies, and spaces. Pop scholarship concerning gamification has been hypercritical (Bogost, 2011), utopian (McGonigal, 2011), or practice-related (Zicherman & Cunningham, 2011). Academic scholarship has been more precise; however, it also tends to separate gamification from games due to supposed ethical differences, a stance which fails to take into account the fact that seductive power is present in both gaming and gamification. So, there are gaps concerning the ontological, historical, and epistemological aspects of gamification. Gamified applications are addressing a practical need espoused by educators, marketers, and software designers. Based on revenue alone, it appears to succeed in its initial goal of motivating consumers and workers (BusinessWire, 2015; Comer, 2012; Deterding, 2012; Environment, 2012; Gopaladesikan, 2012; Krogue, 2012; Scofidio, 2012; Swan, 2012; “The play's the thing,” 2011). If it is ethically flawed, there is little work done to address why and even less that explores what play or fun means in a gamified application. Because a theory of gamification remains undeveloped in terms of theory, history, and use, current critical and academic works often miss the proverbial mark. Except for scattered articles, it received relatively little attention from critical, social, and humanities-oriented scholarship until the two edited volumes: Rethinking Gamification (2014) and The Gameful World (2014). Both volumes sum up a debate with relatively little work toward a useable theoretical term. Both volumes also frame gamification as a “trend,” or a “thing” with little historical evidence beyond the argument that began in 2011 when Bogost fired the initial volley. More recently, Shoshanna Zubof (2019) dedicated an entire chapter to it in Surveillance Capitalism , signaling that there is much more to gamification than meets the eye. I hope to expand on Zuboff's premise that gamification is a significant aspect of modern life and software design by rectifying historical, terminological, and theoretical gaps.

The Genetics of Gamification This chapter addresses gamification within the broader debates on digital games and play. I explore the shared DNA of games and gamification. Also, I thematically engage useful issues covered in critical game studies literature – issues that lead us back into a murkier, more technical history of gamification in the upcoming chapters. Power is the theme that I use to examine the shared links between gaming and gamification. Power encompasses the unique properties of seduction in gameplay, which is linked to disciplinary power and yet serves as an alternative modulation focused on desire rather than fulfillment. Power, here, is used in the Foucauldian sense: it is circulated via relationships between actors, institutions, and discourses. As we will see, power in gaming is a challenging and complex subject. However, games' relationships with power have far-reaching consequences for players, who willingly engage in the negotiation of power in gaming through simulation, technology, space, and embodiment. By examining power, I will explore a constructive set of concepts that are useful for examining both games and gamification. I show that both games and gamification share similarities and that the study of gamification should separate from the study of games. I suggest scholars consider gamification and gaming as shared practices that exist along a spectrum of power. In other words, we cannot genuinely separate gamification as a buzzword, as it shares the same DNA as digital games and game design. Instead, gamification is a new theoretical turn, one that utilizes game design for a new set of goals aligned with surveillance capitalism. Game design, as we will see, attempts to immerse the player in the ludic environment, making them an “instrument” of play, a process known as instrumentality (Dovey & Kennedy, 2006). Surveillance capitalism also thrives on “instrumentarian power” (Zuboff, 2019). Zuboff (2019) claims that, within the net of surveillance capitalism, the human experience becomes “free raw material for translation into behavioral data” (p. 8). Using machine processes, alongside application and software design, surveillance capitalism seeks to go beyond merely observing behavior. According to Zuboff, it seeks to “shape our

behavior at scale” (p. 8). With this move, surveillance capitalism represents a significant reorientation in how power and knowledge relate to our lives: “it is no longer enough to automate information flows about us ; the new goal is to automate us ” (Zuboff, 2019, p. 8). In short, both games and gamification share the goals for behavioral modification at large. However, games have a unique was of wielding the power of instrumentality. In-game actions are intrinsic , and rewards and failures apply only to the gameworld. Gameplay relies on the lusory attitude of players, who can choose to suspend disbelief. Users, however, focus on the end-state of use, which can easily lead to compulsion. Gamification, on the other hand, is all about generating extrinsic behavioral results. Applications that are more gamified produce increasingly efficient behaviors which are directly related to capital. Zuboff states that these moves toward total behavioral modification represent a new mode of instrumentarian power, which “knows and shapes behavior toward others' ends.” With this in mind, gamification's ideological take on behavior modification represents a new set of considerations for theories concerning play and games. By centering on power, I wish to directly link gamification's seductive control to more extensive conversations about the Stack and surveillance capitalism, specifically in the sense of “user” and “interface.” To do this, I will mainly look at the relationships between the player and the game itself, a process known as “gameplay.” Specifically, I argue that gameplay represents a unique take on the traditional Foucauldian model of power, one which gamification is currently exploiting. Doing so will hopefully open up some new areas of inquiry about the role of game design utilized as a social and cultural mode of control while also setting the stage for further theoretical links between games, play, design, and power.

Games and Power The debate over power and control in games is complex, and to properly discuss power in gaming, we must attend to a few major issues. The first issue is the tendency to separate games from broader culture and to localize the effects of games to the intrinsic

value of the game itself. If there is power and control in gaming, then they are sometimes assumed to be bounded off or localized. The second issue is that power and control are often understood to stand in a dichotomous relationship as if the player resists or fights against the control of the game. Power, in this case, is not understood as being neutral or seductive, but as a negative, disciplinary force. This section employs critical literature (e.g., Galloway, 2006) to address each of these issues, which provides a roadmap for ensuing chapters on gamification. Games, in the past, were considered “outside” of reality, and as such any circulation of power related to gameplay was considered to be contained within the process of play. That is, power circulated in a game was intrinsic to that game. Game studies scholars centered much of the debate concerning reality along the boundaries of the so-called “magic circle” (Consalvo, 2009; Huizinga, 1950; Salen & Zimmerman, 2003). The circle, which I cover in depth in the next chapter, has been interpreted as the boundary between gaming and everyday life (Salen & Zimmerman, 2003). Like a boundary, what happens within the magic circle of the “virtual world” does not cross over or influence “the real world” – the game is considered a “halfreal” or “synthetic” space that players make an “exodus” to in order to escape a “broken” reality (Ball, 2000; Juul, 2005; McGonigal, 2011; Meadmore, 2004; Salen & Zimmerman, 2003). However, recently, game studies scholars have moved past the idea of a binary between what occurs in a game and what occurs “outside.” One issue with contrasting games and reality concerns a dichotomous approach to what constitutes “the real.” T. L. Taylor (2006b, 2009b) states that games and play are nondichotomous models that do not separate games from reality or play from labor, life, and capitalism. This is in direct opposition to a formalist approach to games centered on a “truth” that they have a distinct form or function separate from everyday life. Following Taylor, Steinkuehler (2006) states that games are a “mangle” of categories: production/consumption and leisure/labor. Games highlight several struggles that intertwine with issues concerning everyday life. For example, gameplay contains conflicts of human intent (especially differences between game designers and players),

material constraints, sociocultural practices, and chance (Steinkuehler, 2006). Gameplay has also been called “part of what makes games and play so fundamentally an aspect of the human (and nonhuman) condition” (O'Donnell, 2014, p. 406). Espen Aarseth (1997) states that games are “dynamic” processes composed of an interdependent ecology of simulation engines, players, databases, technologies, and nonplayer bots. Seth Giddings (2007a, p. 428) states, “we should recognize [digital games'] images and environments as marked by the semiotic excess of other commercial popular cultural forms…actual and virtual, embodied and distributed, human and nonhuman. They generate reality.” Digital games are not “Euclidean (cyber)spaces forming stages for the interaction between discrete bodies and objects” (Giddings, 2007a, p. 428). Gameplay and gamespaces comprise cybernetic systems – loops that are brought into being by, and bring into being both virtual and actual objects and entities, including players. It is equally important to note that these loops cannot be considered “outside” or “inside” a specific realm (Giddings, 2007a, 2007b). Instead, the cybernetic loop of gameplay has direct ramifications for everyday life by globally influencing cultural forms, flows of capital, and technological practices (Dyer-Witheford & de Peuter, 2009). When studying power and control in games and gameplay, it is essential to note that while power/control may take different forms, they very much “exist” and exert real influence on the circulation of goods, information, and culture around the world (Dyer-Witheford & de Peuter, 2009). However, it is equally valuable to discuss the process by which games enter into broader circulations of power. Games impact a wide variety of processes through instrumentality, or the uptake of technological logics into everyday practice (Grimes & Feenberg, 2009). Instrumentality is essentially the spread of logics that are associated with a technological object. For example, the cell phone (a technological object) has initiated widespread changes in cultural practices across the globe; it is instrumental in affecting a wide array of processes not directly related to the logics of the cell phone itself. In gaming, the mangle of player/technology/game allows games to expand their territory. Digital games imbue a sense of instrumentality to play, which leads

to a broader process called “ludefication,” or the uptake of technologically influenced game logics in broader culture (Grimes & Feenberg, 2009). They state: “It is not that social order recapitulates certain features of games, but rather that games have themselves become forms of social order…Eventually, these games begin to generate their own form of social rationality” (p. 109). Tom Boellstorff (2006) and Alexander Galloway (2006) claim that the instrumentality of games has led to the culture beginning to reflect a game. The creation of a class of subjects, the “gamer,” influences the design and implementation of other systems that hope to reproduce the subject in differing contexts. Players make themselves instruments of specific technological logics (or techniques ) to acquire the desired state of being in the context of gaming. Designers and purveyors of games utilize techniques freely – the voluntary instrumentality of the player on a mass scale designates that a gaming technology or logic could be instrumental in other sociocultural contexts. As already noted, game design (and by extension gamification) has become instrumental in healthcare, navigation, and economics. One example of this is the sudden influence of gaming and gamification in neuroscience, cognition, and the science of aging. Lumosity , a gamified website that hosts a variety of “brain training” games, has millions of unique users according to its website. Lumosity claims to improve cognitive functioning with a vast regimen of games designed by “neuroscientists.” However, Lumosity also shares and sells its enormous data set with researchers, driving research into cognition, memory, attention, sleep, and aging. The games, taken from schematized tests used to measure IQ, memory, and cognition, are modified and hosted on the site. Users compete against themselves and others to improve the baseline cognition. In addition to lateral surveillance and self-archival, Lumosity sells and shares its data with “over 70 research partners” through its “Human Cognition Project.” While its partners are kept a secret, its site lists its clients such as “healthcare providers” and “top universities.” Lumosity single-handedly provides the most significant cognitive and intelligence-based data sets in the history of neuroscience and psychology (Kontour, 2012). Gaming's formal qualities – it is widespread, pleasurable, easily monitored, and consists of

cognitively stimulating processes – have led to its instrumentalization as a research tool of enormous proportions. Lumosity is one example of how instrumentality circulates the seductive power of gaming outwards, and ludefication touches the lives of more people than one might think. Because game design and gaming are successful in a variety of contexts, the fundamental designs of other processes (such as healthcare, advertising, or consumer research) are altered to reflect this success. Players, as such, adopt instrumentality about games and “play comes to operate as a source of institutional order” (Grimes & Feenberg, 2009). As Trammell and Gilbert (2014, p. 402) put it: Our playful imprints in big data have produced depositories filled with beings that possess powers and ramifications far greater than those possessed by most individuals, yet we constantly and consistently deny our hand in their production. Play allows us to neglect responsibility for these creations, while simultaneously allowing them to take on lives of their own. Along these lines, critical Game Studies literature has allowed scholars to move beyond the idea that power and control stay localized in gameplay. Instead, games and their related technologies spread and evolve well beyond any magic circle. As Galloway (2006) puts it, games have become harbingers of algorithmic culture, one where the cybernetic loops of gaming become present in a variety of contexts, and gameplay shows up in everyday life where it otherwise would not. It is this algorithmic culture that breeds “algorithmic surveillance,” such as the types used in gamification and serious games (Sternberg et al., 2013). However, the idea of localized power and instrumentality serves to highlight a fundamental difference in games and gamification. Games are instrumentalized based on the success of their design. However, their outcomes are still intrinsically motivated. The success of a specific element of game design may be used for other processes, but the game remains the same. Pac-Man or its

outcomes are not changed because its design was instrumentalized for other games and external processes. Intrinsically, Pac-Man remains the same. However, Lumosity (which contains several games based on the design of Pac-Man .) links to a variety of other nonlocalized processes. Perhaps then, gamification is not just evidence of instrumentality: it is the direct result of instrumentality. If this is the case, then it follows that not just design elements become instrumentalized. Instead, it is the seduction-oriented methods of control utilized successfully in games that are being mined and exported across a variety of networks. So, the study of gamification is mostly an exploration of how game design has become instrumentalized, leading to gamification in healthcare, pet care, personal fitness, productivity management, and other sectors. The instrumentalization of games' unique mode of power and control provides the conditions surrounding the existence of gamification. Gamification, and projects like Lumosity 's “Human Cognition Project,” shows how power in games is a decidedly nonlocalized matter. Because power and control, enacted through games, spread they cannot be viewed as minimally intrinsic or localized practices. However, games, to be effective, must have active players. Thus, power and control must also be explored within the context of gameplay.

The Player/Game Dichotomy In the Introduction to this dissertation, I laid out a view that seduction is the primary modulation of power in games and gamification. Seduction answers what form power takes in gameplay, but looking at how power and control are generated in gaming has been a longrunning debate and is the result of a “player/game dichotomy” (Lee, 2008). For Voorhees (2013), the player/game dichotomy focuses on the diffuse mechanisms of control in gaming by posing the question: “does the player control the game or does the game control the player?” The answer, of course, should dictate which agent holds power over the other. The player/game dichotomy led to two primary approaches in Game Studies: one that studied the design/mechanics of the game

as the primary agent exerting control and those who explored players as the primary agents who shape and build meaning in the game. According to Voorhees, liberal arts and effects studies research backed the player-centric model in which an active subject constructs meaning in the game. Thus, design can be put to use by educators and policymakers to influence and guide active and engaged players. Some examples of this type of research are studies of community in video games (Williams et al., 2006), studies of embodiment/meaning-making (Crick, 2011; Lainema, 2009), and studies of effective design (Whitton, 2011). In these studies, the player initiates and sustains meanings through the game, and the game merely provides a framework. In these studies, the game is a tool for the player (or designer) to use. This model is also commonly used to test gamification and provides the majority of articles concerning gamification (Lieberoth, 2015; Nicholson, 2012). The game-centric category essentially views the player as a function of the game, meaning that there is no active subject and the game's mechanics limit and determine experience. In these studies, the structure, design, logics, and visual representations of games come under scrutiny (Lee, 2008). Critical studies locate the source of power within the game, and players become subject to it. Examples of this scholarship are in the exploration of ideology/economics/warfare in games (Crogan, 2011; DyerWitheford & de Peuter, 2009) and the interfaces that structure play (Galloway, 2006; Rush, 2011). For Gerald Voorhees, the formalist camp believes “a game is meant to be played, but it is…the game that controls critical practice. Players are not objects acted upon by games; they are objects within the machinic apparatus of the game; they are pieces in play.” (p. 15). Thus, control is only dictated by rules, representations, interfaces, and mechanics. The only logics are those put forth by the game designers and enforced by games. This method of inquiry is what forms the basis of critical gamification literature, such as studies concerning governmentality (Schrape, 2014) and modes of “counter-gamification” (Dragona, 2014). However, Voorhees (2013) states that the player/game dichotomy is false, maintaining that gameplay is the concept that embodies power and agency: gameplay is the site of co-constructed control

that exists on the part of the player and the game. Similarly, N. Taylor, Bergstrom, Jenson, and de Castell (2015) describes gameplay as an “economy of desire that operates between the player and the game” that contains a variety of elements including narrative, visuals, technology, space, pleasure, and attention. This economy is based on coagency and negotiation; it is the seductive aspect of gameplay and continuous and procedural engagement with desire and possibility. The conceptualization of gameplay as control situates control at the “nexus of structures of domination and individual agency” (Voorhees, 2013). Voorhees states that gameplay can be understood from the perspective of Foucauldian power: the relationship between the subject and power is not antagonistic, but rather a process of negotiating desire through the circulation of continuous possibilities. Gameplay, then, is a “possibility space” that is “bounded by but not bound to game rules” (Voorhees, 2013). Voorhees' concept of gameplay as a space of possibility that is the nexus of a positive, seductive form of control echoes critical scholarship concerning the rules and mechanics of games. It is here that I would like to locate the critical study of gamification, within the seductive loop of gameplay. One way to examine how gameplay operates in gamified applications is through examining how players interact with rules.

Gameplay, Rules, and Power Critical literature on rules and players situates collisions between the two on separated but connected planes. The collision is between the rules of the game and the player, and the second is between the players and the gameplay. Rowan Tulloch (2014) states: “Power in games is also about the rules of the game; who follows them and who does not” (p. 347). As such, power does not necessarily occur by force outright. In other words, games do not have power over players. Rules enable players to interact with the game at the most basic levels and thus they enable players to begin the process of coagential meaning-making and creation with games and their related technologies. Far from restricting players, rules are the very basis of players' agency within games. This is an important point is freeing

gameplay, whether or not it is gamified, from the player/game dichotomy. The notion of power in gameplay must be productive of relations outside of abject domination – otherwise, gamification's success in controlling populations is already written in stone. This interpretation of power in gaming works against the concept that rules in games are restrictive. The idea that rules are enabling is a Foucauldian interpretation, one that takes the agency of the player into account (Tulloch, 2014). For Michel Foucault (1977), a subject is a creation of power and also how power sustains itself. Tulloch maintains that this approach sheds light into the pleasure of gameplay and why players take it upon themselves to either police or violate the rules of play within a gamespace by any means possible. Modders work countless hours to create personalized effects within games by programming against the rules, working in a balance for and against the design of the game (J. Kücklich, 2009a; J. R. Kücklich, 2009b; Wood & Ball, 2013). Popular mods like Counter Strike (CS ) and Defense of the Ancients (DOTA ) are picked up by game companies and sold as bonafide games in and of themselves. The labor of modding led to entirely new practices and genres of games. DOTA spawned the enormously popular genre of Multiplayer Online Battle Arenas (MOBAS), and CS was one of the first games to be played professionally in the then-nascent e-sports scene. In these cases, the mods (and modders) became instrumental. On the other hand, illegal mods are sometimes viewed as cheating, and they are banned or removed. In either case, the modders (and cheaters) actively modulate the mechanics of gameplay (the process of “techno-semiotics”) in order to extend the life of the game itself (J. Kücklich, 2009a). The precarious position of the modder shows the lengths that players will go to extend the process of seduction within a familiar mode of gameplay. For Tulloch (2014), the outright obedience to rules in a game “is not a given but rather a complex negotiation” (p. 348). Rules that are banal or unnecessary may result in a game being shelved or intentionally modified. Rules that are restrictive kill a game simply because, as I have noted, a game cannot force players to play. Rules are the building blocks that create games; they are also constructive elements that sustain gameplay. While set up by

designers, they do not always result in expected outcomes. Tulloch states that games “must offer the player the kinds of experiences and pleasures they are looking for or the rules will be challenged… Players are far from unwitting prisoners of restrictive rules; they are active agents in the construction of play” (p. 348). This idea that players push and pull with and against the rules, using them as a source of power, is vital to the study of gamification because it pictures gamification as a series of relationships between players, designers, and the game itself. These relations form the basis of tensions between power, knowledge, and control in gamified environments. Power in games is a process of co-construction that “allows us a way of viewing rules and player agency not as competing forces but rather as part of the same force” (Tulloch, 2015, p. 348). Rules enable the economy of desire that comprises gameplay. If a player desires to complete an objective, then she utilizes the rules to do so. In this model, the rules are not antagonistic: gameplay is the purpose of a game, and the purpose of the player is to gain pleasure from playing. The rules aid her in procedurally generating and sustaining her desire, and the challenge they present is a large part of the pleasure. Because the game is partly comprised of rules and mechanics designed to present a space of possibilities, they also aid the player in exploring it. However, players negotiate power alongside designers and their rule systems. Key evidence of power as negotiated between players is demonstrated by T. L Taylor (2006b) in the multiplayer online games of World of Warcraft . Taylor (2006b, p. 318), one of the first authors to reformulate formalist positions taken by early Game Studies authors, notes: Life in game worlds is not exempt from forms of playerbased regulation and control…systems of stratification and control can arise from the bottom up and be implemented in not only everyday play culture but even player-produced modifications to the game system itself.

While game designers do make rules to govern how conflict and complexity unfold, often built into the architecture of the game, they do not always represent the desires of players to manage their play about others. Taylor found that players created their mods to manage relationships with other players. These mods filled several gaps within the provided architecture of World of Warcraft ; namely, the ability to monitor other players' behaviors. The mods were “an extensive network of tools and functions that consistently monitor, surveil, and report at a micro level a variety of aspects of player behavior” (Taylor, 2006b, p. 329). The fact that players created their tools for addressing needs in gameplay supports the idea that rules, enabled and abetted by technological modding, support players in their desire to play with one another in a precise manner, rather than restrict them. Surveillance and power go hand in hand, and the ability to laterally monitor (and self-monitor) play behaviors about the rules is inherent to gaming's relationship to the deployment of power as it plays out among players. Within the larger structure of rules, players mod the game to negotiate power with one another, determining who shares power. While one aspect of power in gameplay is players' negotiations of rules, players also create their rule systems within the game, which may challenge the protocol set up by designers (T. L. Taylor, 2006b). The importance of rules coinciding with and supporting desire is equally essential to counterplay or alternative methods that forgo or outright change the rules through heavy modding or cheating. It is in bending the rules that players shape the mode and modulation of gameplay to suit their desires and ensure that the seductive state of gameplay remains active. Additionally, it is this pushback that keeps the game itself in a constant state of evolution. It is important to note for gamification since counterplay involves constant evolution, a point I bring up in subsequent chapters. Rules in a game can be perfect, but no matter how wonderful the rules, part of seduction revolves around negotiating the desires and imagination of the player. All gameplay invites counterplay and cheating, creativity and bending the rules. Mia Consalvo (2009) maintains that counterplay, and specifically cheating, is an example of players circumventing designated rulesets to create pleasure

outside of the modulated possibilities present by the game. The cheater, states Consalvo, is the most aware of the rules: in order to cheat, the cheater must assume that everyone else is following the rules or else “the cheater gains no real advantage” (p. 409). “Cheating can be an excellent path into studying the gameplay situation,” Consalvo says, “because it lays bare player's frustrations and limitations” (p. 415). Like Taylor (2006b), Consalvo points out that game rules must inevitably be taken up, bent, modified, extended and, in some cases, ignored by players in order sustain the economy of desire that embodies gameplay. Game Studies scholars have located the nexus of control and power in the process of gameplay. Additionally, they have also explored how rules enable or disallow the circulation of desires of the player in the interest of sustaining gameplay. Sustaining gameplay sustains seduction, and players will inevitably alter and modulate rules in order to continue the process of being seduced. The study of power and control in gaming is valuable to the study of gamification because the conditions of gamification are rooted in the instrumentality of gameplay. Instrumentalized, seductive modulations of power allow services like Lumosity to exist. At the same time, seduction is also entirely reliant on the desire of the user to continue. So, users also exert power by enacting changes to rules in order to modulate their pleasure. These demands can be taken up within the game through modding, which allows players to “customize” their relationships with the game's design and with each other. However, when rules do not allow for modification, players are willing and able to counterplay, which effectively allows them to modulate which types of control they are willing to endure. This issue leaves gamified application like Lumosity in an awkward position: if users attempt to modify or cheat, then the data that have been so useful to researchers suddenly become useless. If the data are useless, then the use value of the game from the standpoint of both users and researchers is diminished, and the game effectively ends. Herein lies a critical difference between gaming and gamification: while gaming can absorb and even encourage counterplay and modding to extend the pleasure of gameplay, gamification is not nearly as flexible. Because the data in

gamification are extrinsically useful and profitable to users (who believe the game is scientifically accurate) and researchers (who rely on the results to prove that accuracy) the game cannot be modified, and cheating would be disastrous for the veracity of the data. Both modding and counterplay serve to illustrate how the negotiation of desire and the economies of pleasure in gaming and gamification are the result of two forces (player and game) acting in tandem to mutually extend a state of seduction. However, they also serve to illustrate a key mutation in gamification: gameplay is fully instrumentalized and networked into more extensive flows of capital by making user data the critical endpoint. Data, for other games, can be used to intrinsically modify the game itself or inform design aspects in other processes. In gamification, data are a productive process. However, another issue arises: what does gameplay generate and, more importantly, where does instrumentality occur? If gameplay is a seductive modulation of power that controls via economies of desire, then what is the logic of this economy? Furthermore, while we have explored the concept of a “user” in games and gamification, we are missing a key component: the “interface.” In short, instrumentarian power, if viewed through a conceptualized “stack,” needs a point of contact between the two foundational layers: the users and their interfaces. After all, the interface is what allows for mass computing, guiding almost all of our relationships with technologies. Game Studies often portrays gameplay as occurring within a specific set of boundaries, the gamespace . Examining gamespace also reveals a complex portrait of what gameplay's outcomes mean for both players and the broader economy in general. They also lead to pressing questions about economies of desire in highly instrumentalized gameplay. Game Studies literature has evolved from the idea that games exist in a “magic circle” (Salen & Zimmerman, 2003) to the idea that “there is no magic circle” (Consalvo, 2009). For gameplay, the conceptual breakdown of the magic circle leads to the exploration of nonlocalized power and control through gameplay. However, it stands to reason that instrumentality cannot exist unless gameplay exhibits some form of use value. Gameplay must generate data that

are utilized for a large number of institutions. Seductive power is undoubtedly on the outcomes of gameplay; however, games also have an economic output that entwines with everyday life (DyerWitheford & de Peuter, 2009; Galloway, 2006). Capitalism itself is a global game of enormous scale (Baudrillard, 1998a, 2005) and science and knowledge are “games of truth” or “language games” (Foucault, 1988; Toft-Nielsen & Norgard, 2015). However, these games are so diffuse they have (unfortunately) lost their sin qua non status as “games” in critical scholarship. What can the actions of players contribute to larger circulations of power? To explore relationships between player and gameplay, we must begin by exploring the space where play takes place. As geographer Harvey (1990) states, capitalism is linked to spatial practices concentrated around moving resources, ideas, and power from one place to another. According to Harvey, the production of spatial relations is key to the continuance of capitalism. Locating capital through gameplay entails locating the type of space that gameplay produces. We must begin by discussing the generation and design of gamespace .

Building the Gamespace Scholarship on gamespace originally located the space of games within the set boundaries of their rule systems (Salen & Zimmerman, 2003). As such, gamespaces in early formalist takes on games constituted them as purely “half-real” spaces that are generated solely by players' interactions with rules and mechanics (Juul, 2005). Gamespace, then, was considered to be a “procedurally generated” rhetorical space that contained and constrained actions (Bogost, 2007). However, this idea has been altered by recent game studies scholarship that focuses on gamespace as a process linked to gameplay (Dovey & Kennedy, 2006; Lee, 2008). Gamespace, then, primarily entails the “spaces of possibility” that are opened up by gameplay, meaning that players actively generate gamespace rather than gamespaces generating players (Lee, 2008). Gameplay, then, is supposed to be cooperative, to an extent.

I argue that the generative powers of gameplay are shared. The spaces where play occurs hold an active role in creating and sustaining the subject position of the “player.” Thus, players exist so long as the process of gameplay continues and gamespace supports gameplay as the player negotiates ludic conditionality. Gamespace grants a body to the player so long as gameplay continues. The conversion of the quotidian body to the body in play is critical for the profitability of both games and gamification. Though gamification does not necessarily produce (or want) “players,” its design philosophy seeks to (re)produce the conditions set on the body of a player. The body in play is a watched body, a body that entangles itself in quantified rulesets. It is the active body that generates the data needed for gamification to occur, and it is gamespace that sustains this body as a source of capital. Once the gamespace terminates itself, the “player” and “space” return to inactivity; the game is over. For example, a simple game like Pac-Man cannot unfold without the player's input with the physical interface of the controller. Without input, the space of Pac-Man remains frozen – the entirety of gamespace consists of many different levels, environments, and possibilities. However, these possibilities cannot come into being unless they meet a variety of contingencies. The technology must work, and the player must master the physical use of the technology and decide that the gamespace is “worth it” in terms of pleasure. This last part involves the negotiation of gameplay – the economy of desire between the player, technology, and mechanics. Wood (2012) states that gamespace is “co-constituted” by gameplay: “This space is recursive, based on feedback between the state of the game (relations between the objects) and the state of the gamer” (p. 102). For Wood, gamespace instantiates in two ways: one is the player's engagement with the designed space of possibility via technology, and another is the procedural creation of co-agential gamespace that exists beyond the cybernetic loop. Thus, gamespace is a recursive space that exists based on contingency – the contingencies of the game's mechanics, the contingencies of the technology on which the game is played, and the contingencies of the player's body as it interacts with both mechanics and technology

(Malaby, 2007; Wood, 2012). While gamespace might formally classify as a series of procedural rules (Bogost, 2006, 2007), these rules require constant collisions and engagements between player, technology, and possibility – instantiated and sustained via gameplay – in order to exist. Creation and maintenance of gamespaces are of the utmost importance for gamified applications. At the same time, these applications must cede control to the desires of the players and users, and gamified spaces must be in constant lockstep with the economy of desire. This aspect of gamespace creates organizing principles that allow play to extend beyond the capacities of the game itself as meaning-making practices. Once again, gamespace is produced by a mangle. “Players manage their input to try and work with or against how the game recursively plays out…any action of an avatar mediated by the gamer has the potential to alter space” (Wood, 2012, p. 103). Recursive space proposes that gameplay interacts with both the meaning-making actions via technology – it is an entanglement of code, materiality, and actions as players deliberately build gamespace via technological co-agency. This view of cooperative instrumentality also brings the body into question. While gaming, the player's body extends through gamespace via technology – that is, the player is technologically embodied in gamespace via cybernetic loops continually reproduced through engagement with technology (Dovey & Kennedy, 2006; Simon, 2007a; Wood, 2012). In this seductive loop, the body is technologized; it is enabled and constrained by a willing negotiation with gameplay's requirements (Dovey & Kennedy, 2006). One example of this comes from the work that players put into the technologies that enable them within gamespace. Gameplay highlights the codependency of players and machines in the act of gameplay and the generation of gamespace. One example explored by Simon (2007a) involves practices such as case modding (or building and decorating the cases that house gaming equipment) and LAN parties, where players set up impressive networked spaces for localized multiplayer gaming. In both instances, players go through extreme effort to display and valorize their coproductive status with technology and materialize their relationship with

gamespace. The effort is essential to the study of gamification because these efforts to combine the body with both technology and mechanics are what produces data – the desire to meld with gamespace and its rules is the primary site of activity and the primary source of data. Many players produce aesthetic displays of the technology that gives them the chance to engage with gamespace. Simon's (2007a) study on case modders and LAN party enthusiasts shows that players often “revel in, and indeed identify with, the material guts of their computer systems” (p. 175). Simon points out that players, specifically those who game via computer rather than console, are in stark relief to the model of “invisible technology” famously proposed by design scholar Don Norman (2008, 2011), a rule of design that assumes technology should fade into the background during use. Simon states that “it is in the cultures of gaming…where the desire for escape and the imperative for invisible computing meet their sociomaterial limit” (p. 176). Gamespace relies on the body of the player as it engages with technology. Not only this, but it also relies on the pleasurable, material display of this relationship. A key example in the co-agency in the creation of gamespace is the gaming culture of e-sports, where public and competitive displays of technological prowess are regular features in the lives of players who classify themselves as “elite” or “professional” (N. T. Taylor, 2009a; T. L. Taylor, 2009b; Taylor, 2012; Taylor, Jenson, de Castell, & Dilouya, 2014; Taylor & Witkowski, 2010). In gamespace, “the software and the hardware are themselves objects of pleasure, fantasy, and possibility” (Simon, 2007a, p. 191). While the body might be a frustration, the case mod turns the player's technologically co-constructed body into a source of pleasure that is “coextensive” with the gameplay and gamespace (Simon, 2007a). Thus, the construction of gamespace links to the technologically enabled body of the player. The produced/productive body of the player is also crucial in the continuance of gameplay and gamespace. The body, then, is instrumental in gamespace: the players engage in what T. L. Taylor (2006b) calls “the joys of instrumentality” – a desire to become engaged in the process of

gameplay. The body of the player is the productive benchmark for the continuance of gameplay, gamespace, and seduction. For gamification, the technologized body of the user operates as the primary focus of productivity, as well. Like games, gamification targets the embodied behaviors of the user. Moving bodies are the primary source for gamification's capitalization on gamespace. Keystrokes, swipes of the finger, moves, clicks of the mouse, steps, breaths, and hours spent awake or sleeping – these build a space where efficient and meaningful action is the primary goal. However, gamification drives the body toward more efficiency in the context of everyday life. In nongamified gamespaces, gameplay can take a variety of actions and encourage them such as aimless exploration, experimentation, or free play. Gamified gamespaces almost always are geared toward making the user's body more efficient in the production of gamespace and, by extension, capital.

Conclusion The observations made in this chapter serve a few purposes in the scope of this dissertation. The first is to provide ideas and literature from which to proceed to unravel gamification. Born from the same DNA as games, gamification also raises many of the same questions concerning power and production. This chapter also provides an overview of the ontological position of gamification regarding games with a focus on critical studies. The observations listed here, and the fact that gameplay is an organizing principle that stretches well outside the boundaries of “a game,” gives an urgency to the critique of gamification from the standpoint of games, gameplay, and play. Furthermore, I hoped to establish just how important it is to understand the impact that gamification has on our ideas of power, design, and space. Conceptualizations of games and play are changing, and gamification is inching game design closer and closer toward absolute instrumentarian power. At the levels of user interface, it molds how people exist within their spaces and whether or not those spaces are focused on intrinsic or extrinsic effects. Game design and gameplay hold many of the keys toward unraveling power, control, and seduction within the context of

surveillance capitalism, primarily because of their perceived “benefits” to potential users and players. As we will learn in later chapters, our spaces have been gamified for longer than we think; it is only now that we are directly engaging with the collective interface binding users and spaces together. Games and play are unstable and ambiguous entities. Gamification, a set of practices that inserts game mechanics into nongaming situations, sits at the center of this situational ambiguity. Bart Simon (2006, p. 64) sums up this ambiguity between work and play neatly: We should continue to theorize the relationship between technology, culture, social interaction, and subjectivity but also more carefully consider the role of games and play in a world often defined only in terms of relations of work and stress. Similarly, Trammel and Gilbert (2014) states: “Not only can our reality be configured theoretically as a gamespace, but it is now also being explicitly and materially engineered as a sort of gamespace… games are becoming the predominant paradigm of the commercial sector” (p. 399). Beyond the commercial sector, gamified applications are being incorporated into a variety of “serious” undertakings such as healthcare and the reorganization of space. Exploring these instantiations is the purpose of this dissertation. While this chapter covers modern literature on games and gaming, I must also reconstruct past instances of theory about gamification. In Chapter 2, I move to a general history of gamification and its ideological roots, resulting in an excavation of “ludology,” or the study of play, from a variety of sources and applying it to the history of gamification. Chapter 2 covers the epistemological conditions of gamification, or how we come to “know” gamification through historical constructions of play.

Chapter 2

Defining Gamification Alan Watts (1995), a well-known Zen philosopher, is one of the first popular scholars to ever mention the core concept behind gamification in the early 1970s. In a series of lectures entitled “Work as Play,” Watts states that making everything a game, or “playing through” all aspects of life, is the key to conquering the fear of death. By “playing through” life, everyday tasks, such as love, work, and even dying become secondhand illusions to the process of obtaining enlightenment, or an awareness of one's self in the world (Watts, 1995). Life is a recurring theme in the study of play. As noted in the introduction, Fink (1974) stated that life and the universe might be composed of play. He envisioned all life as “play life” and all actions as “playing life.” Play, and its constant modulation through games, brings the focus back to the moment – because games are, by nature, a momentary pursuit. “Work-as-play” and “lifeas-play” are major conceptual sticking points for gamification. In order to understand how this schema works, I take on the task of understanding the nature of play and games as cultural and philosophical entities. Gameplay and design often produce ethically ambiguous results, one of which happens to be gamification. Because of its unique place in the schema of surveillance capitalism, there are many different and contradictory definitions of gamification and its ideological roots. This chapter focuses on exploring these and interrogating the philosophies of play that bring the modern history of gamification into focus.

My first chapter focused primarily on a reconceptualization of power in digital games, and what it can bring to the study of gamification (and vice versa). Here I step back and look at the history of “play” through past scholarship on ludology. In doing so, I question the discursive roots of ludology, and why those roots have hindered the study of game design and gamification as modalities of power and control. Gamification demands a nuanced definition of gameplay as a site of control and power in games. However, gamification does not always want to produce “players,” who can be a rebellious and challenging bunch. Exploring the complexities of gamification and play; we must look back to canonical ludological texts. Ludology and its discursive roots will help us understand why Game Studies dismissed gamification based on ideological assumptions about the “natural” state of play, games, and game design. Scholars agree on the point that gamification is a design-oriented set of practices. However, not all theorists and practitioners agree on what that design is meant to do. There are two significant deviations: One holds that gamification restricts choices while the other sees gamified design as granting a choice to escape from the trappings of coercive or stressful labor. One formation views gamification as disciplinary exploitation of play and the other couches it as an exercise in freedom. The difference between both of these views is the understanding of efficiency in play. Gamification, as noted in the introduction, is often geared toward promoting more efficient forms of play. Since the play links to everyday life, this efficiency in play also has direct effects on everyday productivity – everyday life becomes more efficient through play. For some, the increase in efficiency required by gamified design is a sign of coercion – players are tricked into perversely playful slavery. For others, the increased efficiency is attributed to the players' enjoyment of the design – the efficiency is the result of play. For example, Deterding (2012), one of the first scholars to directly address gamification as a concept, states that design choices are less about behaviorist control and more about motivation. The difference between the control and motivation lies in the idea of engaging out one's own volition rather than submitting to

conditioned responses. While exact reactions are required for conditioning, gameplay rewards creative responses, as long as they conform to the general rules of the game. Efficient behavior – such as better times in returning e-mail, completing tasks, or navigating spaces – and individualized forms of play reward through positive conditioning in gamification (e.g., points, progression, and customization). McGonigal (2011), a scholar-practitioner, states that games and gamified applications are productive designs that simulate, pervade, and alter “reality.” Gamified productivity stems from channeling the biological desire to play, which renders actions pleasurable. In other words, gamification may be a “way out” of the masterless slavery of our current labor conditions (McGonigal, 2011). Other accounts of gamification trace gamification's roots to behaviorism and simulation theory. For example, practitioners Zicherman and Cunningham (2011) also point out that gamification's design serves to drive or inform behavior by limiting actions, not necessarily enabling them. Also, Raessens (2014) states that gamification represents a ludification of labor and culture that is more, and not less, regulated since games require exact adherence to rules. All of these definitions are insightful in their ways, but they vacillate between gamification enhancing or curtailing choice. Perhaps the reason is that each definition only spans a few years. Gamification has a much longer history than many assume. The debate over what constitutes a “good” work–life–play balance is an old one, beginning with Aristotle, who valued play very highly, and Plato, who did not (Sutton-Smith, 1997). Examples of protogamification are pervasive in the history of human thought and practice (Fuchs, 2014b). Proto-gamification accounts for historical uses of games that share some similarities with modern gamification. Because modern gamification thrives on networked surveillance, examples of proto-gamification typically deal with games used as marketing devices, behavioral modifiers, pedagogical tools, and social experiments. Most proto-gamified tactics are predigital; if they do involve digitality, they are not networked. Music, art, business, and science have, at various points, deployed proto-gamification for learning, early marketing, and

thought experimentation (Fuchs, 2014b; Raczkowski, 2014). Utilizing games, game mechanics, and game theory to drive innovation in science and philosophy has a long history in scholarship, especially in the form of collective “thought experiments,” secret societies, grant/research competitions, and hacker communities that form and compete on the sidelines of “official” academic gatherings and events (Fuchs, 2014b; Huhtamo, 2012). In some cases, such as Foldit (a ludic protein-folding application) scientists use gamified tactics to encourage amateur and citizen science (Parslow, 2013). The examples are typically considered part of the growing trend of ludic activism and pedagogy. This chapter conceptualizes gamification by understanding both “life” and “work” as forms of play, or perhaps playbor. Particularly salient to this pursuit is examining gamification from the standpoint of ludology, or the social, biological, and philosophical interrogation of play. Throughout this chapter, I cover past ludological texts that imply all culture, including labor, stems from the desire to play (Huizinga, 1950; Spariosu, 1989). Additionally, I examine texts that question play's de facto “good” intentions by comparing it with war, mechanization, catharsis, and simulation (Baudrillard, 1979, 1998b; Baudrillard, 1981a, p. 174; Mumford, 1934). I develop a critical history of gamification by exploring how the concepts of work-as-play and life-as-play align with or deviate from standard definitions of games and play. First, I examine how gamification collides with and diverges from conventional notions of games and play as superfluous pursuits. Second, I include a general history of gamification as it stands today, utilized as a tool for management, marketing, and consumer surveillance. I also note a breakdown in the understanding of play, life, and labor brought about by location-based mobile games (LBMGs). I suggest that gamified applications are not necessarily a break from play; instead, they represent a change in the discursive formations that employ or deploy play and games. I suggest that play is ethically and ontologically elusive. It always exists between the discursive frames of power and progress (Sutton-Smith, 1997). Third, I explore the scholarly treatment of play itself, arguing that in order to undertake a severe examination of gamification and games,

play must be repositioned as a situational pursuit fraught with ambiguity. Finally, I suggest that examining gamification must be done on the level of cultural theory. Gamification is driven by surveillance capitalism, and it is rooted in monetizing the contingencies gaming produces socially and materially. Gamification represents a question of work-as-play, and life-asplay only as long as the concepts work life, and play remain separate and distinguishable from one another. Ironically, this separation is something that gamification seeks to obliterate. As a result, gamification brings about the terms for its obsolescence – since it relies on the boundaries between labor and play to exist, dissolving these boundaries leaves gamification with no actual use value. Gamification's discursive complexity, when framed in terms of play, contributes to the ongoing debate concerning games and labor covered in the previous chapter. This chapter considers this complexity from the standpoint of play as a discursive formation, rather than gameplay as a specific process of power and control. In this chapter, gamified design is reimagined as the “gaming of culture” (Boellstorff, 2006) – a set of ethically muddy practices that utilize playful practices, contingencies, and processes that are inevitably linked to the spread of computational networks and network protocol (Galloway, 2006). Without a set of networks to exploit, gamification would not be able to maintain its profitability as a mode of surveillance or mass behavioral technique. However, while gamification may need networks to produce a profit, it relies on playful engagement as a source of power.

Resituating Games and Play The first step in understanding how and why gamification has been considered a divisive set of practices in the last few years is examining how gaming and play have conceptually been treated in the past. Studying play is commonly referred to as “ludology,” or the study of play from an anthropological standpoint. Traditional ludology has two major players: Huizinga (1950) and Caillois (1961). Both espoused definitions of games as free-standing, rule-based, ritualized systems that result in play – behaviors set apart, at least

superficially, from more “serious” social pursuits (Juul, 2005; Salen & Zimmerman, 2003). Setting play “apart” is also the most common interpretation of games and put forth in early media and game studies. However, it is not the only approach. Other theorists, such as Baudrillard (1979) and Mumford (1934), viewed games as highly technical systems that support simulation, seduction, and mechanization. These lesser-known approaches were often overlooked in early media and game studies literature because they generally do not fall into the category of ludology or narratology – the primary stable of literature on which early game studies operated – and thus they were not covered as frequently. As we saw in Chapter 1, game studies are now embracing a definition of games and play that includes the possibility that they are, or can be, methods of control, instrumentality, and surveillance. However, when looking at gamification, a genealogy of past ideas needs to be excavated and read against modern and traditional ludological definitions. Doing this may clear up the dissonance between definitional accounts of gamification by providing alternate modes of examining play. So, I include accounts from a variety of disciplinary perspectives. It engages in the task of deconstructing the “magic circle” (Huizinga, 1950) that surrounds games and play. Also, I provide a multitude of perspectives that are frequently lost or overlooked in early studies of play. While I do not dismiss ludology and early game studies scholarship, I do question them as a definitive account. Doing so will unravel alternative definitions of play apart from games, definitions that do not place it on a pedestal. The Magic Circle and Types of Play Johan Huizinga (1950) is mostly noted for coining the term “magic circle,” something that has a mixed history in the study of games. He points out that the activities within the magic circle are directly carried over into “real life.” In other words, games are a form of cultural learning and expression ritualistically partitioned from nonludic processes. He discusses play as something happening outside ordinary life. Huizinga views play, and by extension, games, as a type of ritual activity that emerges through rules that are mostly

separate from everyday reality. Huizinga (1950, p. 13) states that play and games constitute a “free activity standing quite consciously outside ‘ordinary’ life as being ‘not serious,’ but at the same time absorbing the players intensely and utterly.” Huizinga was also interested in understanding how play, ensconced in the ritual space of games, is both an outlet for culture and a key component in cultural circulation. Oddly, for Huizinga, games and play are also activities connected with no material interests. They entail actions that gain no extrinsic profits. They also proceed within their proper boundaries of time and space according to fixed rules and in an orderly manner (they are intrinsic ). Huizinga's primary thesis is that play is a primogenitor of culture, and games are its vehicle. The order created in the ritual nature of games is a sort of laboratory for cultural pursuits ranging from law to sexuality to art. Huizinga's argument is not one that precludes a bounded space, but one that suggests all culture is a realm of networked spaces, of topographies, and play inhabits and influences many spaces at the same time. His primary goal is not to identify play as a set of practices existing within a culture or to define games as inhabiting their cultural milieu. He examines how all aspects of culture bears a resemblance to play and games. Games imply a cultural cycle – they are containers, or spaces of germination, for cultural possibility. Huizinga assumed that play was contained in a “magic circle” created by games. The magic circle has different temporal constraints, spatial boundaries, and sets of rules. He points out that the activities within the magic circle are directly carried over into “real life.” In other words, play is learning that is only superficially separated from culture at large. In reality, society functions alongside the rules that are “tested” in a playful environment first. Huizinga can be credited with drawing attention to games as an integral part of the social realm. Roger Caillois (1961) is most noted for categorizing the types of play that certain games produce. He analyzes different aspects of play in various cultures and then creates a “comprehensive review” of different play forms. He notes that there is considerable difficulty in defining play without first categorizing it. His conclusion is that play is characterized by six core characteristics. Play is never forced. It is separate from everyday activities. It occupies its own time and

space. Its results cannot be predetermined and thus requires special initiative from the player. It is ultimately not tied to capital in that it creates no wealth and it has a definite “end” and “beginning.” Play is acultural in that it revolves around rules that suspend normative laws and behaviors. Finally, play involves a process of imagination that allows players to confirm the imagined realities it produces. Caillois was primarily interested in games and play as social forces that exist alongside everyday activities while also providing a distinct, positive social influence. Caillois (1961) was highly critical of any games that involved chance. He associated games of chance with gambling and compulsion. Games of chance are “all games that are based on a decision independent of the player, an outcome over which he has no control, and in which winning is the result of fate rather than triumphing over an adversary” (Caillois, 1961, p. 17). In games of chance, Caillois (1961, p. 17) claims, “the player is entirely passive: he does not deploy his resources, skill, muscles, intelligence. All he need do is await, in hope and trembling, the cast of the die.” Chance “negates work, patience, experience, qualifications… It seems an insolent and sovereign insult to merit” (Caillois, 1961, p. 17). At the time, digital games were unheard of, and computers were in their nascent stage. Still, a computer shares a fair amount in common with cards or a slot machine – both are counting mechanisms, and their inner workings are opaque; that is, their fundamental mechanics are generated via chance, at least as the average user perceives them. Games of chance are pitted against more honorable games (e.g., chess) where there is no agency other than human dictating rules or outcomes. In the case of Kasparov vs Deep Blue , Baudrillard (2001) maintains that even chess is reduced to agon in the advent of simulation; he states that Deep Blue “has no adversary, it moves within the scope of its own programme…The computer…is condemned to play at the height of its capabilities” (p. 117). Baudrillard, who was reliant on Caillois' definition of play, implies that genuinely playing with a machine via simulation is an “impossible exchange.” Caillois' definition of play requires human actors to engage with one another. Whether engaged in solitary games that

require raw imagination, cooperative games that require players to help one another, or adversarial games in which wits and strategy prevail, games are a thoroughly human pursuit. In order for “healthy” play to occur, games must bring human actors together. For Caillois, gameplay that impartially generates resources or mechanics via a nonhuman system is designed to favor chance. These are games that are naturally compulsory and lead to undesirable behaviors in which the game masters the player, as opposed to the other way around. If we look at gamification as a design process that adds gaming mechanics to nongaming systems for “inviting” or “driving” engagement, it becomes highly suspect under both Caillois' (1961) and Huizinga's (1950) notions of ludic activity. Because gamified applications are primarily used to monitor and influence behavior within networked environments, they often involve chance, and they usually have positive reinforcement through points and rewards with real-world value. Gamified applications often reinforce “normal” or “desired” outcomes rather than disrupting them. Many of these gamified applications rely heavily on chance-based mechanics and positive reinforcement (some examples include Farmville , McDonalds' Monopoly, and Shopkick ). Gamified design is mainly about inspiring “fun” and “playfulness” in everyday situations (Zicherman & Linder, 2010) while also providing “loyalty-oriented” tools to the organization that seeks to benefit from it (Zicherman & Cunningham, 2011). So there seem to be some elements of gamification that fit the bill for traditional games (fun and playfulness) while also disrupting the idea that play is “free” or separate from more quotidian sectors like economics or government. Games, Mechanization, and Seduction While Huizinga (1950) and Caillois (1961) primarily link play and games with positive elements of cultural production, other theorists do not take the same path. Mumford (1934), in Technics and Civilization , links the evolution of games with the creation of a “technical society.” Baudrillard (1981a, 1998c) also frequently used the metaphor of games and gaming to illuminate consumerism and

simulation. Like Fink (1968, 1974) both authors were somewhat hesitant to extol ludic activity as a positive pursuit, metaphysical or otherwise. Jean Baudrillard and Lewis Mumford can both be considered “tertiary ludologists” because their interest in games is often nested in much larger social trends, pitting notions of games and play against economics, mechanization, and warfare. Mumford (1934) felt that games operate as “agents of mechanization” that reverse his romanticized “eotechnic” age. As games become increasingly technical, they present an illusion that “fair play” is obtainable. For instance, technology is often seen as the great leveler, and advances in technology are often accompanied with the caveat that they will create an equal society (Carey, 1989). Mumford argues that in reality, “win at any cost” becomes the standard operating procedure in a fully technicized society. Winning, in this case, is obtaining more time and resources for leisure by making more powerful machines. Mumford (1934, pp. 101–102) maintains that mechanized parts such as wheels, gears, and levers, are just “buckets and shovels dressed up for adults” and that games and play are infinitely caught between “consumptive pull and productive drive.” Civilization's advance toward “complete mechanization” is closely intertwined with the desire for leisure, namely the desire to save time and increase efficiency. Leisure activities birth technologies that focus on producing more leisure. Formerly nonpractical objects, like toys and models made of moving parts, eventually become larger and more powerful. Mumford (1934) notes that the gyroscope was initially a toy before it became a stabilization device for trains, airplanes, and carriages and existed in the miniature before it became widely used. Mechanization begins with the maximization of sensual pleasure and life itself. Unfortunately, mechanization ends in a hellish arena where the brutality of real life is inseparable from the games in which it was based (Mumford, 1934). In seeking a maximal, luxurious balance between leisure, play, and work, mechanization leads to an “upthrust in barbarism, aided by the very forces and interests which originally had been directed toward the …perfection of human nature” (Mumford, 1934, p. 154). This barbarism originates partly from the luxury of play transforming into a form of a bloodlust. Play, through

“mass-sport,” has degenerated into the worship of the productive “goddess” who values generativity above all else. He states: “Sport, then, in this mechanized society, is no longer a mere game empty of any rewards other than playing: it is a profitable business…” (Mumford, 1934, p. 307). Mumford maintains that in a mechanized society, play is at the mercy of capital. There are no longer rewards from play for play's sake. Every game must have a meaning, and play must produce calculable results. This prediction, in many ways, holds some similarities with gamification's play for-profit model. Mumford's presuppositions about the brutality of a technological society are heavy-handed. However, he envisions games as precursors to a situation where the desire for leisure results in leisure and labor becoming indistinguishable. Both signifiers collapse and become meaningless under the ambiguity of play. Mumford's take on games, toys, gadgets, and play is also premeditative of the later writings of Baudrillard (1981a, 1998b), who links games with simulation and the move toward hyperreality in technologized societies. Scholars maintain that, for Baudrillard, games and play are ambivalent experiences that suffuse the modern condition of being human (Coulter, 2007; Crogan, 2007). Similar to Huizinga's (1950) space of “social possibility,” Baudrillard (1981a) saw games as an exercise in the eradication of reality; perhaps more accurately, the increasing importance of games to simulation is a sign that reality is already eradicated. Play, for Baudrillard, is an act of seduction, or complicity with generating and living within an illusion, a world in which simulation has already triumphed (Galloway, 2007). Seduction is the ultimate metaphysical tromp d'oeil – a type of charade in which appearances move beyond the stable categories of production or consumption (Baudrillard, 1991a). For Baudrillard, all games represent the situational elements that allow simulation, fantasy, and seduction to infiltrate daily life at the most fundamental levels. Baudrillard holds that life, love, and work are not distinct entities separated from play. Rather, play itself is desire and desire gives rise to all manner of possible ills. One of which is the triumph of simulation over reality.

Baudrillard (1991a) states, “all appearances conspire to combat meaning, to uproot meaning, whether intentional or not, and to convert it into a game” (p. 153). He continues, “We seduce with weakness, never with strong powers and strong signs. In seduction, we enact this weakness, and through this weakness, seduction derives its power…Seduction makes use of weakness, makes a game of it, with its own rules” (p. 165). For Baudrillard, the advent of the information age is also the advent of appearances and signs – seduction is the type of force complicit with technologies of appearance and inscription (i.e., writing, visual art, screens, lenses, and mirrors). Gamified applications rely on channeling seduction through design. They are simulations that invite certain behaviors and utilize play as a form of desire to inspire actions that, in typical contexts, do not make sense. Behaviors like stopping to check in at a coffee shop, or driving to multiple store locations to collect tokens work because of a desire for rewards that often have no value outside the application. What ensues is an increasingly complex system of badges, avatars, titles, and points that form a web of objects linked to the performance of rituals in service to the gamified application's mechanics. Baudrillard (1981a) maintains that the proliferation of technological objects and their related codes are based on the assumption that nature, as we can perceive it is mechanistic and capable of being reproduced. In other words, technology improves upon nature on insomuch as nature itself is technological (Lane, 2008). Technology acts as a compensatory mode of being in a world that is increasingly automated. The transferal of human desire and agency to a system of replicable objects and processes fractured any naturalistic relationship between human actors and the world. In turn, the human subject no longer embodies a natural sense of “being” in the world. Rather, the world is populated by simulacra – objects, signs, and representations that human subjects actively observe. The seduced human subject is adrift in a simulative environment that replaces, or at worst obliterates, any notion of reality as a stable concept (Baudrillard, 1981a). Seduction is the active process of this obliteration, the slow and joyful transfer of agency to objects, signs, and signifiers.

Seduction and games are primarily simulative processes sustained by a myriad of technical networks; seduction serves to manipulate and direct the desires of humans. Baudrillard (1991a) maintains that seduction is essentially a mechanic embedded in “a game of simulation” that is being played. This game is not one that someone chooses to play; rather, the game of seduction “plays itself” and human actors are caught up in it. As such, Baudrillard viewed life and game as a mutated category, in which they infinitely refer to each other (Galloway, 2007). A Baudrillardian approach to games implies that “what we recognize as games (digital or otherwise) are merely old order distractions from the real game or perhaps the game of the real” (Simon, 2007b, p. 356). “The virtual is emphatically not the gamic for Baudrillard,” Galloway (2007) writes, “it is this world that is the game” (p. 378). Games and play are an order of “psychic complicity” with simulation, a complicity that finds its roots in the seductive system of objects (Galloway, 2007). Games and play here are indicative of a technological imbroglio, one born of rampant computerization and the rapid diffusion of media technologies throughout the developed world: They are indicative of a technologized world, rather than being mere parts. In Mumford (1934) and Baudrillard (1981a), we see a line of reasoning that postulates games and play as bloodthirsty, seductive forces that serve to direct and manipulate human agency. Seduction is the promise of pleasurable simulation; the idea that technologically supported leisure leads to more leisure, and that more leisure ensures more technology, which in turn ensures more pleasure. For both Baudrillard and Mumford, what ensues is a society in which all meaningful references to labor or leisure collapse, resulting in a world that resembles a game at all times. Labor and leisure become meaningless symbols, replaced by consumer-driven games of chance and luxury. From this standpoint, gamified design represents the epitome of a “game of seduction” in which seduction supplants the game. Seductive applications foreground simulated rewards and supplant free play for playbor's sake – forsaking creativity for efficiency. For Baudrillard, seduction conceptualizes games, play, consumerism, and desire as ubiquitous, directed processes in an increasingly simulated society.

A layman's definition of both games and play might situate them as fun, harmless, ebullient systems – they rise and fall in an ebb– flow cycle that dovetails with a set of fantastical, ritual, and material spaces. Humans, rather than automated systems, determine the rules, and these rules are agreed upon through a ritualistic pact that has no bearing on reality. However, Huizinga (1950) and Caillois (1961) both noted that games, while existing in a specific categorical space, are actually conjoined to social and material processes. In the works of Mumford (1934) and Baudrillard (1981a), games are a force that can be culturally harnessed and directed toward a variety of means and ends, including social and technological control. In the case of Baudrillard and Mumford, the “pact” inherent in games is always social and technological, and it should be closely examined. Mumford's obsession with games as “mass blood sport” and toys as miniature precursors to weapons – as well as Baudrillard’s (2005) assertion that economics are merely games played for the rich – identify the relations between games and dangerous or disruptive technologies as a key concern for both theorists. For Baudrillard (1994), games are complicit with simulation, consumption, and seduction. For Mumford, play objects such as toys are inherently tied to teleological mechanized processes. Each author's approach is illuminating because it provides a background for gamification's marooned status in early game studies and ludology: The ludic was often conceptualized by scholars as a black and white gaming universe. There was an ethical fault line where a “game” stops short of control and exploitation. The alternative concept, only now being explored in depth, is that games embody a possibly dangerous expansion of control as soon as they are initiated (Dyer-Witheford & de Peuter, 2009; Galloway, 2006, 2007; Rush, 2011). After some examination, ludology's take on both play and games is largely ambiguous; play can be used as a tool for freedom or regulation, for stability or disruption, and for leisure or labor. It is important to keep this in mind when approaching gamification. Games and Play as Metaphysics

Philosophers have also construed play as a vital part of human experience. Two key figures in ludological philosophy are Fink (1974), mentioned earlier, and Carse (1987). Fink contends that play was unfairly devalued in metaphysical tradition, and maintained that to understand the world as an ontological concept, play must first be interrogated (Elden, 2008). For Fink, play is a cosmological force that is not necessarily human in nature; rather, is both the cosmos and a symbol of the cosmos – it produces and realizes ontological difference (Elden, 2008). As Fink (1968) states, “the mode of play is that of spontaneous act, of vital impulse…Play is, as it were, existence centered in itself. But while seeming to be unrelated to our normal life, it relates to it in every meaningful way” (pp. 20–22). Play, in an illusory manner, produces the world around us, and it also produces the objects that we interact with in everyday life. Play is like a mirror, or a shadow, of a larger concept; it allows humans the ability to don and discard a variety of social, spiritual, and material possibilities. When playing, people willingly take on new identities, perform new rules and traditions, and create new tools. For Fink, “play always has to do with play objects. The play-thing alone is enough to assure us that play does not take place in pure subjectivity without any reference to the concrete world around us” (p. 27). Illusion and reality, the extant world and the world we perceive, are all processes of interplay and interpolation – all play produces a “play world” that mirrors and affects the real (Fink, 1968). In other words, social processes, such as language, music, and art, mirror the inherent mimicry that play requires to function – and from this mimesis flows a self-referentiality that defines existence. Similar to Huizinga's (1950) thesis, play and games are spaces of possibility. However, Fink (1968, 1974) takes Huizinga's conceptualizations one step forward: play is not only the primary source for the social, it is also a “basic existential phenomenon” which is “just as primordial and autonomous as death, love, work, and struggle for power” (p. 22). “We play at being serious,” Fink (1968) postulates, “we play truth, we play reality, we play work and struggle, we play love and death, and we even play play itself” (p. 22). For Fink (1968, 1974), play is the polarity of two extreme modes of existence – the clear “Apollonian” moment of self-determination

and the “dark Dionysian” moment of panic and self-abandonment. Both are procreative of the world as humans perceive it. Carse (1987) noted that play revolves around two different worldmaking technologies: finite and infinite games. Finite games are games that take place in a space – they are contests of power, ritual, and democracy. They are also voluntary and cannot be undertaken if compulsory (Carse, 1987). Infinite games, on the other hand, are games of life. They are games in which the only rules that exist are rules that ensure the continuation of play (Carse, 1987). While finite games are pursuits linked to distinct spatial and temporal boundaries, infinite games are games that transcend both space and time – infinite games play with boundaries. A finite game is a game of Marco Polo. An infinite game, hearkening back to Watts (1995), is a game played via consciousness – a game where the self's position in the context of reality is evolving. More concretely, infinite games are processes. Economics – with its emphasis on constant growth – could also be considered an infinite game – it effectively defines our place in the grand scheme of things. Carse maintains these two types of games mark the boundaries between the world of the social (finite games) and the realm of metaphysical truth (infinite games). He states the rules of an infinite game must change in the course of play. The rules are changed when the players of an infinite game agree that the play is imperiled by a finite outcome…The rules of an infinite game are changed to prevent anyone from winning the game and to bring as many persons as possible into the play (p. 9). Thus, finite games are interested in logistic outcomes, and infinite games involve a never-ending process. For Carse (1987), infinite games can be material or spiritual, social or solitary – but they are always productive. Games that involve destruction must inevitably end, thus making them finite. From the standpoint of gamification, both Carse (1987) and Fink (1968, 1974) reiterate the ideal notion of work as play. Gamification, indeed, holds many resemblances to infinite games. It relies on an

infinite loop of playful behavior that nobody can win. Ending a gamified application terminates intended behaviors and the data they produce. Additionally, like an infinite game, gamified applications are only useful when vast numbers of people play. However, unlike Carse's infinite and emancipatory gamespaces, gamification is mostly about the modulation of desire. Players are expected to desire finite outcomes for play, such as badges, gift cards, or avatars. These finite rewards, based in positive reinforcement, are at odds with the reality-shaking implications of Carse's infinite game. It is true that gamification's rules only exist to extend play infinitely; however, gamification's boundary play aims to conceal the compulsory rather than eradicating it. Furthermore, the aims of gamification tie to finite material and social outcomes. Thus, gamification lands squarely on the side of Fink's (1968) world of illusion and shadows. The rewards given for infinite play are decidedly finite, and often they do not “exist” at all, as in the cases of digital badges and titles. From a metaphysical standpoint, gamification's infinite game mirrors Dionysian self-abandonment: It does not replace or supersede work or life; it merely aims to persuade players to forget momentarily. Ambiguous Play Despite differences in conceptual approaches among gamification practitioners, ludologists and tertiary ludologists are interested in the power of games and play. The short history of gamification just presented brings this interest into direct focus – play is being used more than ever to observe and modulate behavior and cultural production on a large scale. However, defining just what play entails has been a messy discursive exercise. In this section, I move toward an understanding of play as an ambiguous act that does not necessarily connote a set ethical standpoint; rather, it is the discursive treatment of play as ethical that often creates a problem in “placing” or “defining” gamification. Gregory Bateson (1956), a biologist, suggests that play is a paradox because it is and is not what it seems to be. The playful “nip” of an animal at play is both a bite and not a bite; it “connotes a

bite but not what a bite connotes” (Sutton-Smith, 1997). Robert Fagen (1981), an animal play theorist, states: “The most irritating feature of play is not the perceptual incoherence, as such, but rather that play taunts us with its inaccessibility. We feel that something is behind it all, but we do not know, or have forgotten how to see it ” (as cited in Sutton-Smith, 1997, p. 2, emphasis mine). Play's ambiguity seems to be couched in its curious visibility: we can only define play by what happens during its course. Culturally, play manifests in an infinite spectrum that acts as a barrier to stable definitions. Brian Sutton-Smith (1997, pp. 6–7) states: …biologists, psychologists, educators, and sociologists tend to focus on how play is adaptive or contributes to growth, development, and socialization. Communication theorists tell us that play is a form of metacommunication far preceding language in evolution because it is also found in animals. 1 Sociologists say that play is an imperial social system that is typically manipulated by those with power for their own benefit. Mathematicians focus on war games and games of chance, important in turn because of the data they supply about strategy and probability…No discipline is, however, so homogeneous that all its members are funneled into only one such way of theorizing. Nevertheless, the diversity exists, and it makes reconciliation difficult. With all of these contingencies present, play appears to be a rather useless concept – it is rhetorically vague and theoretically ungrounded. Theorists and philosophers avoid the concept of “play”; a stable definition does not exist in non-Western discourse (Malaby, 2007). Play is so diffuse that its discursive boundaries seem to infuse everything from warfare to lovemaking to religion. Perhaps, then, it is best to focus on the ambiguity of play in the context of how it alters the discursive environments where it takes place. Play always seems to occupy a position that implies some mode of power or action is needed to activate, regulate, and direct it. The need to direct or define play as a clearly defined set of activities

links to the rhetorical framing of what play entails. Sutton-Smith (1997) points out that play exists between two diametric poles: progress and chaos. Ensconced within these two polarities are several subsets of statements made about play, two of which are particularly relevant to the idea of play in the context of both gaming and gamification: play as progress and play as power . The first discursive framework is play as progress. Sutton-Smith (1997) points out that progressive play is a biological approach, one that has, until recently, implied “the notion that animals and children, but not adults, adapt and develop through their play” (p. 9). This belief in play as progress is something of a scientific ideal, and it is often rooted in the epistemology of both biologists and educators. Play is a currency in children and animals that can be used to culturally imbue certain favorable aspects through the application of ludic rules and procedure. Sutton-Smith (1997) states that “most educators over the past two hundred years seem to have so needed to represent playful imitation as a form of children's socialization and moral, social, and cognitive growth that they have seen play as being primarily about development rather than enjoyment” (p. 10). What is interesting here is that this educational view of play is beginning to be transferred to the behavioral analysis of adults, especially in the workplace (Costea, Crump, & Holm, 2005). For example, the research enacted at the National Institute For Play (NIFP) under Stuart Brown (2009) and the psychological research of Mihaly Csikszentmihaly (1990), both approach play as a biological and psychic necessity for the continued growth and health of adult human beings. The change in conditionalities makes play as progress applicable to nonludic subjects and spaces. Play, or at least playful behavior, is a trigger for healthy lifestyles. In the case of Csikszentmihaly (1990), play is a rabbit hole to the realm of “flow” – a timeless space where mastery is the key to joy. For Brown & Vaughn (2009), mastery and instrumentality are keys to bodily health. Both of these researchers assume that play is a golden horizon to be sought out in the drudgery of day-to-day living; it is a key to biological wellness and mindful joy. Play is truly a generative process, in these cases, and it

is seen as a lifelong undertaking and part of the duty of every person to live a “good life.” Play as power is the second discursive framework play inhabits. Sutton-Smith (1997) points out that play as power is inherent in games of competition. Games pitting a human player against fate, chance, destiny, and the “will of the gods” are conduits for psychic, social, and material energies. Like Baudrillard's and Mumford's concerns about play's links to seduction, simulation, warfare, and techniques of domination, power, and play focus on play's homogenizing and unifying power – the power to supplant all previous modes of existence for a time. Play as power advocates “collectively held community values rather than individual experiences,” and as a rule, it denotes that play is a way to make things more real (Sutton-Smith, 1997). Sutton-Smith (1997, p. 10) states, “The rhetoric of play as power is about the use of play as the representation of conflict and as a way to fortify the status of those who control the play or are its heroes.” The view of play as power has its roots in psychological literature about excess energy similar to Bataille’s (1991) theory of “general economics” – play is a primitive mode of blowing off excess cultural energy when that energy can no longer be directed toward the expansion of the “economic organism.” The explosion of magic, games, sacrifice, and festivals in ancient economies is a way of transmitting power as catharsis or fulfillment (Sutton-Smith, 1997). Play, then, becomes the act that makes other acts bearable. Play as power also links back to two critical play theorists: Huizinga (1950) and Mihai Spariosu (1989). Huizinga viewed play as a catalyst for culture – the excess energy of play was redirected into spheres such as law, war, art, and even scholarship (scholars do compete with each other by “playing” with ideas and concepts). These connections between play and society are “morphological parallelisms,” in which the mastery of games is a catalyst for social hierarchies through the formation of communitas (Sutton-Smith, 1997). Interestingly, recent thinkers in biopolitics (see Esposito, 2011) have also pointed out that the potlatch style of playful excess is vital in the formation and regulation of community – the reciprocity of play is the glue that allows communities to form (Campbell, 2011).

However, Sparisou maintains that the ties that bind are also the ties that can dissolve (similar to the concept of reversibility in Baudrillard's account of seduction). He contends that play is as much about disorder as it is about order. In this manner, play and games act as disruptive agents just as much as they can be ordering principles. Sutton-Smith states, “there are two conflicting rhetorics about the play: One that says it is positive, as a mode of cultural origination, humanization, catharsis, or socialization, and another that says it is a site for power seeking, domination, and hegemony, or disorder, inversion, and resistance” (pp. 81–82). In short, gamification's definitional quandary lies in the complexity of play, and what it means in terms of individual behavior and the social. The unifying thread between power and progress is the question of ambiguity. That is to say, play links to the environments in which it occurs: It directs and is directed toward a number of possibilities. However, each possibility ties to the concepts of power and progress, two contingencies linked to a host of other social and material processes. In the context of gamification, both power and progress are at stake, yet both are linked directly to the generation of capital, data, and control. A quick look at the history of gamification will confirm this.

A (Brief) History of Gamification American pragmatist Mead (1934) situates games and play as key processes in learning how to objectify one's self and take the perspective of others. These acts must precede economics, language, and mathematics. For Mead, play is the original mode of transmission for language, economics, and culture. Mead, another tertiary ludologist, points out a pivotal point in historicizing gamification; games and play are the producers of social systems and ideologies. This revelation leads to another critical point: as long as there are game mechanics and logics that direct outcomes for playful behavior, there exists the possibility of gamification. Gamification presents a prime opportunity to examine emergent history, and it would be impossible to construct a total history of gamification at this point. 2 Instead of totality, a general history that

examines the material conditions through which gamification becomes visible proves more useful. Mathias Fuchs (2014a) states that gamification operates at the level of “ideology” – one that privileges soft power and gift-based economic exchange. Fuchs cites Mauss as one of the first authors to ideologically explore gamification by situating “gift economies” as alternatives to capitalist exchange. 3 Fuchs also cites Georges Bataille's 4 theory of general economics as a precursor to gamification's principle goal of seeing play supersede labor in a viable system of economics. However, Fuchs also notes that by replacing labor with leisure, gamification may bring about conditions where play itself becomes drudgery, thus bringing about its demise. In the end, Fuchs argues that the effort to combine play and labor through gamification has dire consequences. Because leisure and labor politics is where the primary conflict over gamification's legitimacy begins (deWinter & Kocurek, 2014), it is also where I begin its history. The idea of work as play may have first been explored by Watts (1995) and his Zen philosophy during a series of television broadcasts in the 1970s. Gray (2007), a leisure studies scholar, notes that this revolution ended the idea that leisure is a matter of having more “free time” – instead, as the globalized economy became computerized, work became “24/7,” inseparable from everyday life. Coonradt (2007) first proposed in 1984 that games may serve as a better framework for conducting business that follows standard business best practices. Reckoned the “grandfather of Gamification” by Forbes Magazine (Krogue, 2012), Coonradt points out that recreational games provided better motivation and feedback, stable rules of play, and efficient scorekeeping than traditional managerial methods, stating “in recreation participants feel they have a higher degree of choice…Part of the reason for liking a recreational activity is the freedom you have in doing it” (pp. 150–151). Other scholars note a ludic managerial turn. Costea et al. (2005) identify a “Dionysian turn” in the way that play is deployed in the workplace. Costea et al. point out that “play emerges as a managerial resource because it has an affinity with the increased weight placed upon ‘work’ as a site for the pursuit of collective and

individual ‘wellness’ and happiness as key dimensions of selfassertion” (p. 140). The biological and cultural trajectories of play in the workplace have combined. The authors state that the social manifestation of play embodies an “entitlement to happiness” and a “duty to be happy” as a form of managerial and biological self-work (Costea et al., 2005). Play, when trapped in the “work-as-play” conceptual webbing, is reframed as a duty in the workplace. Games, the chief modulators of playful behavior, become a form of technology that enables duty. Costea et al. (2005, pp. 143–147) state that The link between production, consumption, play, and wellness is most clearly evident…the logic here is that effective design of the consumer experience requires moving away from the rationalized logics of the market… results are the 21st century's fully-fledged consumption cultures in which the entitlement to happiness (through choice and consumption) and the “duty to be happy” as consumers and as workers are the new dimensions of “citizenship.” In the Dionysian turn, the work-as-play ideal operates as a biological imperative privileging wellness and the “adult” principle of generative labor. Like Dionysus, the god of wine and forgetfulness, the Dionysian turn aims to make workers forget they are working. What results is an ideological marketing and business ploy that exploits the boundaries between leisure, labor, and life. Marketing via a conflation of life/work/play has been utilized frequently in predigital forms (Fuchs, 2014b). Although, without networked computing, the scope of gamified projects was usually simple. New York University's Governance Lab has noted that in 1910, Cracker Jack is cited as utilizing the “first” predigital marketing ploy to involve gamification (Verhulst, 2013). Cracker Jack was the first to give away toys in a box. Similarly, frequent flier cards, loyalty rewards and points, and even sophisticated advertising campaigns like McDonalds' Monopoly (Zicherman & Cunningham, 2011;

Zicherman & Linder, 2010) are early examples of gamification in marketing. McDonald's Monopoly was a marketing scheme that placed game pieces onto specific items on the McDonald's menu. Styled after the board game, players had to collect matching pieces of color-coded property to win prizes. Certain items of the menu would have game pieces attached – for example, if you matched three pieces of purple-colored property, you would win a significant prize. Also, some game pieces offered free menu items, like burgers and cokes. The game was an enormous success and drove sales up for the McDonald's franchise, leading it to become a yearly offering (Marketer, 2011). McDonald's Monopoly effectively turned the network of franchise stores across cities into a game board, inspiring consumers to change their eating and shopping habits to participate in the game (Hulsey, 2015). For example, a player might buy an abnormal amount of french fries or extra-large drinks because they have more game pieces than other items on the menu. As evidenced by Monopoly , early marketing-based gamification was not always simple loyalty tricks, toys, or rewards. In some cases, predigital gamification was also extremely sophisticated, playing with collective labor and social identity. For example, the fictional character of “Betty Crocker” and her cookbook contests are examples of harnessing collective, ritualistic games that women play with themselves and each other (Horner, 2000; Rossi-Wilcox, 2006). Betty was initially envisioned as a fictional character – or perhaps a nonplayer character (NPC) – whose purpose was to answer consumer mail about home economics and domestic labor in the 1920s. Originally, “Betty Crocker” was all the women of the Home Service Department of the Washburn Crosby Company; however, in a Baudrillardian move, she was separated from her biological counterparts by General Mills to circulate as a signifier in the world of consumer objects (Marks, 2005). After appropriating the faces, voices, and talents of biological women, Betty Crocker won the title “The First Lady of Food” after being named the second most influential woman by Fortune magazine in 1945. 5 This honor was based on the (mostly free) collective labor of countless women – Betty was not even real.

Betty Crocker is one of the most sophisticated exercises in predigital, proto-gamification. Most approaches had to do with loyalty programs, punch cards, and reward programs. Gamification, in its predigital form, only had a few sets of design choices to play, and distribution was limited to the restraints of the time. The digitization of games and gamification expands the array of design practices used in addition to highlighting new modes of distribution, surveillance, and transmission (Whitson, 2013). The term gamification was not used until the implementation of networked computing. “Modern” Gamification Goes Viral In an interview with game journalist Andrzej Marczewski, Richard Bartle – an early proponent of networked gaming – claims to be one of the first computer scientists to use “to gamify” as a verb in the 1980s (Marczewski & Bartle, 2012). Bartle was working on the first ever multiuser dungeon (MUD) and “to gamify” meant to turn a simple text-based “virtual room” into a game. Of course, the intent of “gamifying” the virtual room was to motivate people to use the space. As such, the term “to gamify” originated alongside the first networked game. Bartle sees gamification as a stage in the evolution of a game. Bartle states: “I am a game designer. I want all gamification to take that last extra step and become a game. From that point of view, no example of gamification is done well!” (Marczewski & Bartle, 2012). For Bartle, gamification means to turn a quotidian networked space, which is not a game, into a game (Marczewski & Bartle, 2012). Modern usages of “to gamify” focus on the act of breaking games down into their design components and then strategically distributing them into nonludic environments, an inversion of Bartle's use of the word. The more modern take on “gamifying” is due in part to the theoretical work on play, learning, and user motivation done at Xerox's Palo Alto Research Center (Xerox PARC). “Motivation,” in this case, is an attempt to understand what makes things fun to learn and why people sustain engagement with particular environments and objects as opposed to others. The work on learning and

motivation through play is attributed to research done by Thomas Malone (1980). Malone noted that motivational approaches to software design and learning could be modular, a supposition that influenced distance education, where learning applications are referred to as “modules.” In the 2000s, Xerox PARC and its alumni made significant leaps in the sociology of digital play and the field of game studies, 6 including addressing the pressing question of how to make labor “fun” (Yee, 2006b). At the same time, the research that was done at the Xerox PARC lab also highlighted the differences between gamification and games by solidifying early definitions of gameplay, gamespace, and play styles. During the first decade of the twenty-first century, relationships between games and learning were primary focuses for ludic research. Additionally, mobile and location-based games also became popular as both art and leisure (de Souza e Silva & Hjorth, 2009). Fast forward to a few years later – “gamification” (a previously nonexistent term) has become, as Richard Bartle (2012) calls it, a “bandwagon.” Gamification went viral quickly in the first decade of the twentyfirst century (Economist, 2011; Liyakasa, 2012b; Raczkowski, 2014; Scofidio, 2012; Zicherman & Cunningham, 2011). In 2002, Nick Pelling created Conundra 7 – a company proclaiming that Moore's law determines all devices will become a game or gamelike in the twenty-first century. Conundra was the first to publicly use the term “gamification” in a business context. Pelling's Conundra website refers to hardware alteration, as opposed to manipulating software. While Conundra was “ahead of its time,” according to Pelling (2011), Bunchball , the first successful software-based gamification platform, launched in 2007. In 2010, the term “gamification” went viral. Jessie Schell's DICE Conference presentation, named “The Secret Mechanisms” described a world in which “gamification” and the “gameocolypse” conquer all (Schell, 2013). Since 2010 gamification has genuinely become a bandwagon. Three years ago, much-hyped gamification was predicted to plunge into the technological “trough of disillusionment” (Goad, 2011). In 2015, gamification drives market expansion in big data (Boyd & Crawford, 2012; Paharia, 2014), wearable health monitors and calorie counters and fitness programs like Fitbit (Walker, 2013a; Whitson, 2013), informational and

business services like Bunchball (Danforth, 2011), commuting like Waze (Lopez, 2012), location-based services and advertising like Foursquare (Zicherman & Cunningham, 2011), shopping applications like Shopkick (Rao, 2012), food applications like Open Kitchen (Van de Zant, 2012), experimental surveillance “games” like Google's Ingress (Hulsey & Reeves, 2014), and social “games” like Farmville (Luscombe, 2009). The trough has, thus far, not materialized. In 2013, the study of gamification was “standardized” with the development of Octalysis (Chou, 2013). Octalysis works as a sliding octagon, with point holding a different logic. As different mechanics work toward various outcomes, the shape (or the weight) of the octagon changes. Thus, different applications can be examined based on the game mechanics present to determine what aspects of gamification they utilize and how gamified they are on a comparative scale – gamification literally takes a shape. Octalysis solidifies gamification as a set of diverse design practices centered on intrinsic, playful and motivational game mechanics embedded into devices or applications. For Chou (2013), gamification's design is ethically fluid, and design choices separate into “Black Hat” and “White Hat” partitions (Chou, 2013). Black Hat 8 gamification, similar to the hacking moniker, plays with the compulsory side of game mechanics like scarcity and competition. White Hat 9 gamification, once again like the hacking moniker, consists of positive motivational reinforcement like achievements, digital property, customizability, and points. From Chou’s (2013) methodological perspective, gamified applications represent a somewhat ambiguous set of practices playing with both motivation and compulsion. Advergaming It is the distinction between motivation and compulsion that permeates the recent history, and controversy, surrounding gamification. However, advances in computing drive gamification as a viral set of design practices. While Coonradt (2007) proposed personal solutions for increasing productivity in the workplace and mitigating stress, recent technological trends promote that game

thinking can work as a collective solution to productivity and motivational issues on a truly massive scale (Byrne, 2012; Kim, 2012; Nicholson, 2012). Far from Watts' (1995) idealist conception of work as play as a way of becoming, gamification has widely been proposed as a business solution – it is this proposition that links back to gamification as a behaviorist technique altering daily practices. Although the word itself is new (Deterding, 2012; Fuchs, 2012; Liyakasa, 2012a; Mosca, 2012) the concept is at least two decades old. The current visibility of gamification comes on the heels of advertising and motivating through networked, social videogames (Clavio, Kraft, & Pedersen, 2009). Social media games, such as Farmville , exposed a new brand of consumer provisionally called the “cyberfarmer,” an ideal consumer whose loyalty is bought with virtual goods rather than expensive real-world loyalty rewards (Luscombe, 2009). Farmville led to the development of “advergaming,” or building games that showcased a product, location, or service using persuasive elements such as avatar customization driven by a “harvesting” mechanic (Bailey, Wise, & Bolls, 2009; Choi & Lee, 2012). Advergaming also had internal uses for the workplace – by attaching points and rewards to daily tasks, employers sought new ways to manage production and consumption within the workplace (Byrne, 2012; Liyakasa, 2012c). However, advergaming had inconclusive results in promoting consumer action; it produced affective responses to products and brands, but it did not drive extended cognitive or behavioral outcomes (van Reijmersdal, Rozendaal, & Buijzen, 2012; Sukoco & Wu, 2011). For example, players' retention of brand information was not revolutionary after playing a brand-related game (Sennott, 2005). The failure of gamebased marketing to produce extended engagement with a brand was because the advergames themselves were self-contained systems, that is, they produced motivational results solely within the context of the game and its rules (van Reijmersdal et al., 2012). When the game ended, so did the spike in engagement and retention. This problem harkens back to the difference between Carse’s (1987) finite and infinite games – to truly make money and later behavior for an extended period, advergaming needs to be infinite.

Marketers assumed that game dynamics nested in advergames also needed to be divorced from the idea of “a game” to produce reliable results (Zicherman & Cunningham, 2011). Games are, by most standards, self-contained worlds with their timelines and sets or rules. If producing and consuming are 24/7 pursuits that rely on maintaining interest, efficiency, and overall motivation, then the idea of a single game would be insufficient to fulfill the dictum of work as play. Ideologically, marketers believed that game dynamics must be pulled from their ritualistic bubble and directly injected into everyday life. Alternate reality games (ARGs), like Majestic , released in 2001, had been successful in puncturing the thing divide between everyday life and gaming (Taylor & Kolko, 2003). Marketers sought the same hybridized effect. In order to drive engagement, the affective nature of gaming must become extrinsic, tied to real-time physical and economic events, and the mechanics and the logics behind the gamified application must be continuous. The smartphone and tablet computer provided the platform to test out a mode of attaching game dynamics to everyday behaviors and locations while ensuring the gamified system was always present (Keats, 2011). Trade journals noted that the mobile revolution would usher in a new era of customer interaction and workplace management (Clavio et al., 2009; Keats, 2011; Naughton, 2003; Qin, Rau, & Salvendy, 2009; Rizzo, 2008; Sennott, 2005). Industry blogs asserted that “what yesterday's science called Human-Computer Interaction (HCI) is today's art of playing” (Gopaladesikan, 2012). The success of this venture has been confirmed, with applications like Shopkick – a gamified that rewards players with points for entering stores and locating products – generating millions of users, check-ins and product views (Ha, 2011; Rao, 2012). From the “cyberfarmer” to the always-on amalgamate subject of employee/consumer/player, gamification's uses are just now beginning to be explored by researchers. However, the concepts behind gamification are quite old, and the money (and data) has been flowing in for quite some time. Gamification and LBMGs

The increasing flows of global data, risk, information, and capital become enabled by the “collapse” or, perhaps, contraction of space and time (Harvey, 1990, 2006). The contraction is due partly to cellular infrastructure, mobile devices, and, more specifically, “smart” devices that are location-aware (Bell & Dourish, 2007; Dourish & Bell, 2007, 2011). The abilities of networked and location-aware devices have led de Souza e Silva (2006) to propose the concept of “hybrid space.” Hybrid space hinges on the idea that mobile devices are not just modes of two-way communication; instead, they serve as microcomputers embedded in social space that connect data spaces to physical locations and social networks (de Souza e Silva, 2006). Hybrid spaces, then, “are mobile spaces, created by the constant movement of users who carry portable devices continuously connected to the Internet and to other users” (de Souza e Silva, 2006, p. 262). Hybrid space assumes that connected users are operating in a hybrid reality where a “mix of social practices… occur simultaneously in digital and in physical spaces, together with mobility…” (de Souza e Silva, 2006, p. 265). Because hybrid reality is co-produced through social uses of technology, spatiality, and infrastructure, removing data from space produce unalterable consequences. In other words, hybrid realities and their associated spaces are inextricable from the data, technology, and users embedded in them. de Souza e Silva (2006) encourages a reframing of what “physical” and “digital” spaces entail through her analysis of “mobile interfaces” (p. 273). These interfaces do not just translate between data spaces and lived everyday activities. They fuse the two in an amalgamation of location awareness, smart navigation, crowd-sourced locational information, visually represented social networks distributed across space and data feeds linked across multiple global networks, including mobile, hybrid gamespaces. Advergaming, which was highly localized, began its shift toward gamification and pervasive gaming when combined with LBMGs. Mobile gaming initiated a collapse between the perceptions of “physical” and “virtual” gamespaces (Chan, 2008; Hjorth, 2011; Richardson, 2011; de Souza e Silva, 2008). LBMGs share many aspects with pervasive games, games that “expand” the magic circle (Montola, Stenros, & Waern,

2009). However, LBMGs utilize very distinct technologies, such as location-aware devices. Montola et al. (2009, p. 503) state: A pervasive game is a game that has one or more salient features that expand the contractual magic circle of play spatially, temporally, or socially… The game no longer takes place in certain times or certain places, and the participants are no longer certain. Pervasive games pervade, bend, and blur the traditional boundaries of game, bleeding from the domain of the game to the domain of the ordinary. Pervasive games exist in the intersection of “phenomena such as city culture, mobile technology, network communication, reality fiction, and performing arts, combining bits and pieces from various contexts to produce new play experiences” (Montola et al., 2009). Perhaps the best examples of pervasive games are those that have a diffuse “space” in which they take place, such as some LBMGs that rely on pervasive techniques. However, pervasive games do not have to involve advanced or networked technologies. For instance, games like Assassins , where players stalk others with water guns over a series of days and weeks, and live-action roleplaying (LARP) are also considered pervasive even though they need not involve digital or mobile devices. Both types of games are open-ended and take place across diffuse spaces; they appropriate quotidian spaces and convert them into gamespaces. LBMGs, on the other, utilize mobile devices that constitute as “mobile interfaces” (de Souza e Silva, 2006). Mobile interfaces, de Souza e Silva (2006) states, combine “portability, social interactivity, connectivity, individuality, and context sensitivity.” These devices can network players together, enable communication, and transmit locational data. Early LBMGs such as Can You See Me Now? and Mogi revealed that a variety of unique behaviors related to location-based gameplay (de Souza e Silva & Hjorth, 2009; Licoppe & Inada, 2010). Mogi , a Japanese LBMG demonstrated that the networked display positional data (where the player's position can be marked and

commented on) also provides users with resources to recognize their co-proximity while not necessarily being co-present (Licoppe & Inada, 2010). Players used this information to simulate future encounters with other players and, as a result of gamified lateral surveillance, changed their spatial practice in a number of ways including seeking out new social encounters, avoidance, mediated pro-sociability, and, at worst, stalking-type behaviors (Licoppe & Inada, 2008, 2010). From the standpoint of play, these behaviors indicate players would, for an extended period, change their typical behaviors in favor of engaging with locations and other players via the LBMG. In Mogi , players altered their daily routines in order to meet or avoid other players in the city (Licoppe & Inada, 2010). Gordon and de Souza e Silva (2010) point out that “most LBMGs lack a predefined game structure; that is, they do not have a clear end and are always running as long as there are users connected. Most importantly, gameplay often converges with ‘real’ life” (p. 60). This convergence is what makes LBMGs pervasive, and it also is what gives gamified applications their ability to reach far outside of bounded-off gamespaces. Because LBMGs usually employ networked mobile interfaces, they can transmit continuous data concerning gameplay and location. This continuous transmission is necessary for gameplay, and also creates a unique environment for embedded surveillance of the type that gamification employs. However, LBMGs are also about producing new forms of play (de Souza e Silva, 2008). LBMGs introduced a new gaming logic that extricated gameplay from a set of highly redistricted spaces: They moved play from being confined to a screen or board to constant engagement with both physical and digital spaces (de Souza e Silva & Sutko, 2008). A vital example of this move is the formation of Baudelaire's flâneur into the “phoneur” (de Souza e Silva, 2008). The flâneur reframes the city through a series of playful actions that turn the city and its flows of power into a modern, observational game; the flâneur both participates and observes in an unaffected manner (de Souza e Silva & Hjorth, 2009). The flâneur observes, but the phoneur experiences and is experienced by others who are also embedded in hybrid gamespace. The phoneur, as a player, participates alongside

“intimate strangers that inevitably get caught up in the gameplay” while “the magic circle of the game automatically fades and is blurred with the order of various ‘flows’ – geographic, electronic, sociopolitical – of the context” (de Souza e Silva & Hjorth, 2009). LBMGs “take the phoneur away from… apanoptic mechanisms’” present in many mobile media practices and “place the phoneur in the pushing and pulling of play” (de Souza e Silva & Hjorth, 2009). For example, in the game Botfighters players would always alter their quotidian routines to engage with other players in combat, sometimes riding through the city until they came across an enemy combatant (de Souza e Silva, 2008). However, it is also important to note that phoneurism can also be networked into larger systems of surveillance while still using hybrid gamespace as a motivational apparatus – the development of gamification provides an example of how LBMGs have been instrumentalized into larger networks of control and capital. The development of LBMGs allowed advergaming to move beyond contained or localized gamespaces and into hybrid space. Thus, the tracking and surveillance capabilities embedded in hybrid gamespaces to advance play are also tools that can be used to collect profitable data. For gamification, this involves recording players and gauging their efficiency is performing desired behaviors. The behaviors of players, which mechanics seek to influence and harness, is key to gamespace – the players' bodies in space is the primary mode of generating data and profit. This is a crucial point in examining the history of interactions between LBMGs and gamification: the conversion of the quotidian space into the gamespace and the subsequent conversion of the player into profit. Location-based gamification emerges at the end of a few phases in the development of LBMGs. The research phase of LBMGs consisted of experiments and art projects such as those conducted by the research and art group Blast Theory – e.g., Can You See Me Now? (2001) and Uncle Roy All Around You (2003) – both of which have been covered extensively by research on LMBGs (Gordon & de Souza e Silva, 2010; de Souza e Silva, 2006, 2008; de Souza e Silva & Hjorth, 2009; Sutko & de Souza e Silva, 2008). This phase focused on the interactions between players and technology and the

feasibility of creating LBMGs. They were hampered by technological limitations, for example, players in Can You See Me Now? wore backpacks and carried GPS units. The second phase occurred as smartphones with built-in GPS began to come to market – this phase is the social networking phase. Early LBMGs, such as Mogi (2003), which was played in Tokyo, made heavy use of social networking. These types of games went from localized gamespaces to international sensation with the emergence of social networking platforms such as Foursquare (2009), which is covered extensively in later chapters. Foursquare provides a transition into the current phase, which combines social networking and LBMGs with advergaming – the gamified phase. This phase is currently occurring. The gamified phase is less interested in exploring the possibilities of play and more interested in using location-based play for profit. Foursquare makes its money off selling location-based ads and customer data. Ingress (2013), another gamified LBMG covered later, also profitably generates data. Both games focus on efficiency in collecting friends and navigating/exploring the city for social capital and titles (Foursquare ) or holding territory for points (Ingress ). This efficiency links to the movement of the body through space, and the constant surveillance of the body in regards to gameplay efficiency – in other words, efficiency is rewarded and recorded. These rewards and data apply to purposes outside the games itself – they are instrumentalized. This focus on surveilling and training the body toward efficiency in gameplay plays into discursive links between computation and behaviorism.

Gamification, Computation, and Behaviorism While gamification has only been “named” in the past two decades, it has its roots in the development and dispersal of networked computational devices. That is to say, gamification only exists through the networked media technologies it utilizes, technologies that began to proliferate as early as the 1970s (Leiner et al., 2009). The computer, with its hyper-logical simulative capabilities, was especially responsive to logistics derived from mathematical game theory (Halpern, 2003, 2007). Computing and simulation, much like

gaming, rely almost entirely on propositional statements expressed through a specific language or code. Alan Turing's universal machine, the building block for almost all computational systems, is based on a simulated “game” played with a set of tables (Turing, Post, & Davies, 2004). His universal machine is actually a series of simulated counting machines playing a recursive logic game. In modern terminology, this is “running a program.” Computers and computer programs are logic games; however, they are referred to by Turing as “simulations” because machines (currently) lack a biological predisposition toward play (Baudrillard, 2001; Turing, 2004). As many scholars have noted, the similarities between computational code and game theory are marked, as both derive from similar mathematical principles (By, 2012; Crookall, 2010; Klabbers, 2009). As such, games and play acted and modes of transmission for computing, and specifically networked computing; as early as 1963, game theory and games (which are visual expressions of game theory calculated by a computer) were used to demonstrate the use of computers as both logic machines and artificial intelligences (Jorgensen, 2009). As computers increasingly became necessary for monitoring the growing global economy, game logics were further integrated with computational systems and are present in many aspects of basic systems design (Halpern, 2003). Game logics, software design, and simulation from a computational standpoint are mutually constructive of one another. For example, all of Turing's computational tests, which are benchmarks for modern computing and artificial intelligence, were games (Turing, 2004). At its most basic level, computation involves simulation-based devices. Because games and simulations are very close, almost all early programming designs were tested and simulated via games and game dynamics. The mutuality of games and computation is what allows for computers to perform simulative calculations necessary for the basic functionality of software programming ranging from economics to basic locational applications like navigation services. They are also intrinsic to networking applications (Halpern, 2007). Games, from the standpoint of game theory, are built into the fabric of computational

protocol. Game theory, the theory of decision-making, probability, and contingency, played an essential role in the development of simulation, computer science, and economics. The decision-making paths of economic agents can be calculated, based on contingency, as branching trees related to possible gameplay scenarios, utilities, and choices (Hulsey & Reeves, 2014). Additionally, game theory has been used to explain evolutionary outcomes (Consalvo et al., 2010). While game theory is not necessarily a game, it uses games as ways of understanding the paths and possibilities that agents may take. Thus, game theory has also been used as a basis for creating algorithms and artificial intelligence. Most important, game theory is also unique in that it can map the transmission and formation of power – the relationships between actors as they move (Fuchs, 2010). In the study of gamification, games, game studies, and mass computing are circuitously connected. In the Mobius loop of a gamified environment, the data generated by players support more simulation, more monetization and, of course, more play. Their behaviors are mapped, and the environment is altered via mechanics to account for deviation or counterplay. All decisions must conform to the logics required in producing the needed data. Gamified design is the direct result of detaching game logics, game theory, and game design practices from the concept of a selfsufficient “game.” Most notable is the use of game mechanics , which aim at influencing user motivations when they engage with a product, brand, location, or social network (Deterding, 2012; Kim, 2012). Game logics encode the outcomes of player choices through algorithmic sequences and represent the rationale for the end-state of actions produced in the game (van Benthem, 2003). Game mechanics are the specific architectural qualities of game design – the formal or structural components that constitute rule systems, constraints, and pathways (Sicart, 2008). However, despite the addition of gamelike elements, gamification does not equate “turning something into a game.” Gamified design is mostly about creating an environment where certain types of behavior, namely compulsive play, are encouraged and monitored. Humans, it turns out, are compelled to play. Downplaying behaviorism in gamified design is a result of negatively typecasting

game mechanics as Pavlov-style experiments in making “fun” superficial, with play behaviors serving a much deeper purpose. Scholars often base their judgments of gamified environments on the ethical assumptions that games make things better, regardless of where and how they deploy. However, all software courts behaviorism; design, after all, is meant to facilitate behavior (Norman, 2008, 2011). Computation itself is noted as a doubleedged blade by scholars, who state that the transferal of behavioral agency to computers can have lasting effects on interpersonal and macro social spheres (Levy, 1997; Turkle, 2011). In the end, operating on simplistic ethical notions of games and play is not well suited to the processes and forms of gamification. Gamification of Culture Pressing issues concerning ontologies of play, the epistemological frameworks of gaming, and ideological issues plaguing the so-called separation of leisure and labor have led to a greater awareness that games and play exist as practices embedded in material culture. Material culture, here, refers to a distinct approach to cultural activity that emphasizes culture as a practical activity (Marx, 1997). In other words, culture is not a stable history of ideas or meta-narratives but rather a diverse collection of practices embedded in everyday activities (Lefebvre, 1991). Materialism holds that all cultural processes are, to some degree, material processes (Williams, 1989). They involve actual constraints that are the result of heterogeneous times and spaces (Massey, 1992). The ability to engage in cultural production is based on a wide array of problems and conditions: who is allowed to communicate; how are people communicating; what technologies are available to whom; how and why are these technologies available? This short list of issues does not do justice to the vast array of approaches and problems embedded in a materialist approach to culture. However, they serve as the groundwork for examining what many would claim is the primary goal in a cultural approach: examining the relationship between power and cultural production (Couldry, 2000). So, from a cultural standpoint, gaming works

“simultaneously as central nodes in the organization of contemporary leisure culture, computer-mediated interaction, visual culture, and information societies” (Simon, 2006, p. 64). When examined alongside these particular loci of concerns, gamification's version of play does not exclusively represent a black box marketing methodology aimed at behavioral modification and surveillance, but as sign and symptom of a media-saturated culture that has deep historical, cultural, and technological roots. Gamification, like games, also represents “critical locations for understanding the role of digital technologies in mediating and constituting the social interaction and organization of subjects in late modern information societies” (Simon, 2006, p. 66). For example, Boellstorff (2006, p. 33) states, “many games, and other forms of interactive media…that are less clearly game like, are taking on cultural forms in their own right… These cultures cannot be reduced to the platform; that is, the rules and programming encoded in the game engine.” Like gaming, gamification also encompasses the meanings created through individuals and groups playing from both a productive and consumptive standpoint. Malaby (2007) suggests that games are “dynamic and recursive” in that they reproduce their form over time and space, but also encode within themselves the pattern for change. Key here is that gameplay embeds the desire for control alongside the possibility for alternate, appropriated meanings. Malaby (2006) suggests that on the surface, games are a series of processes based on contrived contingencies ; outcomes that, theoretically, can be contained and constricted through the rules of play (or perhaps, the rules in play) but also rely on open-endedness and subjective interpretation. “Contingencies” represent “that which could have been otherwise” (Malaby, 2006, p. 106). As Huizinga (1950) suggests, games are germination spaces for perpetual cultural recalibration that operate through a series of external relationships. Games contain, according to Malaby (2006, p. 107), the “fundamental quality of multilayered contingency that allows them both to mimic and constitute everyday experience.” “Contrived” suggests that games are both ordered and disordered. Unlike bureaucratic rules and regulations, the contingencies created through ludic processes are not aimed to

“reduce unpredictability across cases” (Malaby, 2006, p. 105). Rather, ludic processes “are about contriving and calibrating multiple contingencies to produce a mix of predictable and unpredictable outcomes” (Malaby, 2006, p. 106). Malaby implies that gameplay, from the standpoint of intent, encourages exploration and pathfinding as much as they require a player to abide by rules. Gameplay embodies a fluid system of control that relies as much on innovation as it does compliance. He (2006, p. 106) claims: …the contrivance of these sources of unpredictability is achieved through various modes of control…these modes of control additionally include the architectural (encompassing the gamut of relatively non-negotiable and concrete constraints, from physical layout and landscape to the implicit code of online games), the cultural (the set of practices and expectations that are often implicit and taken for granted), and the economic (the familiar constraints of the market in all its forms). Games are distinctive in their achievement of a generative balance between the open-endedness of contingencies and the reproducibility of conditions for action. One key aspect of this open-ended approach to contingencies is that games promote multiple configurations across social and technological matrices. The multiplicity of outcomes and interpretations that games produce are subject to varied, culturally shared, meanings that are consistently decontextualized in the realm of practice. Thus games are a set of practice-based contingencies that are generative . Psychology describes generativity as a human “need, drive, concern, task and issue” that involves socially and environmentally transferring specific traits or characteristics from one generation to the next (McAdams & de St. Aubin, 1992). Jonathan Zittrain (2008) expands this definition to technology. He defines generativity in terms of software or technology-related “generations.” He states, “generativity is a system's capacity to produce unanticipated change through unfiltered contributions from broad

and varied audiences” (p. 70). Under Zittrain's definition, generativity results when technologies enable users to generate, create, or produce new content unique to that application. One key aspect of generativity is that content appears without additional input from the designers of the apparatus in question. Critical examples of generative technologies include open-source software and hardware, most video games, and the Internet (which allows users to produce and sustain a myriad of content via the World Wide Web). Generativity, according to Zittrain, requires both technological and social actors. For example, Molesworth and Denegri-Knott (2007) examine how gaming, and constructing meanings through play, is an act of consumption. However, rather than accumulating, hoarding, and territorializing resources, gaming operates through complex, liminal activities that occupy a culturally productive position that tethers the practical activity of using goods with a malleable digital sandbox. Meaning-making in-game culture blurs the lines between producer and consumer, occupying a liminal space that encourages change, performativity, and imagination (Molesworth & Denegri-Knott, 2007). Players adopt a “doing with” attitude, actively embodying both regulative, ritual-based contingencies and an imaginative “acting out” attitude that links the imaginative function of possibility with the practical function of “making real” (Molesworth & Denegri-Knott, 2007). This dynamism between consumption and production, the small and grand narratives of cultural performativity, accentuate both Malaby (2006) and Boellstorff’s (2006) claims that games may underline a renegotiation of the processes through which culture is coded and decoded in the digital age. Boellstorff (2006, p. 33) states that Most persons who participate in games and other interactive media…play more than one game…We are seeing the emergence of cultures of gaming on a range of spatial scales – some local, some national or regional, some global – shaped by a range of factors from language spoken to quality of Internet connection.

Gameplay, then, is interpreted as a broader set of meaningmaking practices that are conducive to the formation of a “game culture” shaping the landscape and definition of games. “Cultures of gaming” are the diverse and segmented practices embedded within an extensive cultural milieu tied to specific modes of play behaviors modulated by games and related technologies. The decentering of gameplay as a ritual practice set apart from more “serious” social processes has resulted in a growing interest in the “gaming of culture.” Boellstorff (2006) maintains that “As [gaming] gains in significance, [it] increasingly affects the whole panoply of interactive media, from television to movies to cell phones to the Internet in all its incarnations. Gaming also shapes physicalworld activities in unexpected ways, including the lives of those who do not play games or participate in interactive media” (p. 33). The gaming of culture is perhaps similar to what Baudrillard (1979, 1981a) envisioned when he proposed that seduction and gaming were part and parcel to the (de)programming of reality. Gaming culture has been linked to many “nongaming” practices. Key here are military research and simulation (Allen, 2011; Veen, Fenema, & Jongejan, 2012), ludic consumer practices as they relate to the expansion of neoliberalism (Dyer-Witheford & de Peuter, 2009), and the search for play-centric education, which has seen a vast surge of interest in exploiting the “learning power” nestled in games, particularly as a subset of a so-called “participatory culture” that is driven (in part) by the expansion of computer games and playful, gamified applications (Squire, 2011). It might be said that the study of gamification contributes to the “gaming of culture.” The culture around us is beginning to resemble a “play of the machinic unconscious” (Colman, 2012) or perhaps just machinic playgrounds : spaces where the datafication of everyday life incorporates game mechanics to feed, direct, and influence collective and individual desires on an increasingly micro scale. The ambiguity of play leads to ambiguity in games. Ambiguity is what often results in games being boxed into a magic circle that defies inherent ethical issues such as power or progress. However, the study of gamification demands that scholars dig between the polarities of power and progress. Gamification is about play, albeit a

strange interpretation of it, and it is about power and progress. In a way, it is about games, as well. It affirms that games/play and power/progress are just a few sides of the same cultural prism, a prism that projects no ethics, no play, and no games beyond the spaces where it resides. What our “gamified prism” reveals is a different spectrum of contingencies for each source of light, each room, and each experiment where it finds itself useful. Gamified design is comprised of embedding game logics and mechanics into nonludic environments to create and maintain engagement with a system or groups of systems. It ties the user to the interface and greases the wheels of surveillance capitalism, keeping workers in the data mine. As such, it is a set of practices concerned with producing material and social results not inherently concerned with play or playfulness as a free or spontaneous act. The idea that players are not necessarily in control of the system has been suggested multiple times, including by early ludologists (see Caillois, 1961 on “games of chance”). Gamification employs gamelike qualities in the form of mechanics and logics. It also does attempt to inspire playful behavior, channeling the desires of users, although it does not produce the type of play often associated with both digital and analog self-referential, or perhaps finite, games. The design choices that exist in many examples of gamification – such as points, progression, levels, customized avatars, and rewards – are gamelike elements. Gamification aims at making everyday tasks enjoyable in many cases. However, the intent behind these design choices means that gamified systems do not necessarily result in a self-contained game, nor does it exist entirely within the boundaries of game culture. Gamification distributes game logics and mechanics through systems that do not always have play in mind. Gamified environments do not focus on playfulness as a set of definite or selfreferential outcomes. Playful behavior, in this manner, is similar to a human resource. However, this “resource” is a state of being that can be directed toward decidedly nonplayful ends, such as efficiency and profitability in everyday life (faster work, healthier body, better navigation). In a gamified environment, there is rarely a prince or princess to rescue or a galaxy to save. There is no spontaneous yelling of “Tag,

you're it” or “Marco Polo!” Rather, the formal qualities of gamification operate alongside a meta-narrative of consumption and production, embedding any playful aspects produced by the gamified system into much larger circulations of labor and capital not directly related to the gaming industry or the purchase and use of self-contained “games.” This meta-narrative leads to two distinct possibilities. The first is the “indebted man,” or players whose everyday lives depend on a system of play for data, where gamified logics economize and indebt their datafied bodies (Lazzarato, 2012). The second possibility is that gamification is a system of “machinic enslavement” that modulates “pre-individual, pre-cognitive and pre-verbal components of subjectivity” (Lazzarato, 2006). In this case, the exploited preverbal and preindividual component is play – natural urges codified into application design. Most gamified applications generate revenue not through the distribution of the app, but through the data generated by its use. Similarly, gamification in design software is aimed at increasing the user-friendliness of the interface or the simulative capabilities of system – both lead to efficiency and, by extension, profitability. As such, the formal qualities of gamification do not produce gameplay in the sense that “players” engage with a “game.” Rather, gamification creates players who engage with gamified environments in the context of everyday activity. Gamification serves an overriding logic that does not always congeal with play as a free or open experience. Rather gamification serves the logic that pleasure is not happiness or healthiness in situ : pleasure keeps people happy and healthy no matter what their proximal or locational situation may be. Additonally, pleasure can be gained by ever-increasing efficiency, so long as that efficiency is achieved through play. As such, play is seen in a much different light when gamified – it is a force to be directed and controlled. Play, in the case of gamification, must be viewed as a form of power that affects the player's relations with the world around them and the game logics. Power through play is a series of relations that involve the game having power over the player, the player overpowering the game, and the relations between both redefining how the course of gameplay unfolds.

Because of this, gamification, in many respects, challenges some of the canonical conceptualizations of both play represented here. Gamified applications are not games, but rather collections of design practices that serve a rationale utilizing playful behavior as a power source. They do not necessarily follow genre formats, and many times are undetectable without expertise. Gamification does not necessarily present a “different” or “new” set of social or material concerns when it comes to playing; instead, it warps how play operates, and by extension destabilizes past definitions of what play actually might entail in the twenty-first century. Gamified design is theory. It concerns itself with how networked players work together, through seduction, to produce playful sets of contingencies not typically associated with “free,” “harmless,” or “ritualized” games as defined by Huizinga (1950) and Caillois (1961). Gamification's form of gameplay operates closer to the murky side of play – the ambiguous, Baudrillardian contract. It is seductive as much as it is ludic. It is consumerist, connective, and controlling. The types of gameplay produced by gamified applications are closer to instrumentality, where the subject naturalizes into a networked, monitored, and generative system. Gamification entails utilizing parts of a game – the mechanics, rules, and rewards – to increase the predictive capabilities and/or efficiency of much larger systems. It promotes repeated noncoerced engagement within a set protocol for a result outside of the gameplay itself. It records player actions for the profit of the designer and the continuation of engagement with the system and taps into the business of leisure and pleasure through harnessing playful desires (Zicherman & Cunningham, 2011; Zicherman & Linder, 2010). Different combinations of design choices, technology, and modes of deployment serve to meet each of these conditions.

Conclusion In this chapter, I have explored past interpretations of play and their relationship with gamification. I have focused on decentralizing play and games from their current moorings by suggesting that focus on games and play should be contextual rather than monolithic; both

should be treated differently in different contexts, especially in regards to power and control. I have also suggested that both games and play are ambiguous in their cultural outcomes and that gamification should be a set of cultural practices appropriating ludic activity. The scholarly focus on gaming and gamification has been one of the definitions and outcomes. Namely, my analysis has revolved around what role games and gamification play in culture at large and how gamification is used for one end or another. Following Baudrillard (1981a) and Fink (1968, 1974), games play with ethics, history, and life itself in increasingly ambiguous ways. Gamification is now far removed from Watts' (1995) Zen idealism, and as gamification becomes prevalent, it is time to focus on how everyday tasks and occurrences begin to resemble machinic playgrounds. Gamification plays with all boundaries: it expands across tasks, times, spaces, and even species. Games, gamification, and gameplay are all around us, hiding in places previously unseen. The next two chapters analyze the historical connections between games, game theory, simulation, and computation. Developments in game theory and simulation coincide with the current flood of data and modeling, commonly called “big data.” I trace the impact of game theory across multiple fields, setting up an argument for interdisciplinary approaches to gamification and paving the way for an examination of gamification links with early simulation. 1

This could be a reference to Huizinga (1950), Mead (1934), Goffman (1961) or all three. Total histories seek to define governing or formal principles to account for a cohesive or “meaningful” history in the context of age, epoch, or period. It also assumes homogenous networks of relations that imply causality. These relations are often arranged by the researcher in an arbitrarily ordered fashion that impart a cohesiveness to the subject matter (Dean, 1994). On the other hand, general histories are nontotalizing, with special interest in details and complexity. The key difference is general history's focus on “series, divisions, differences of temporality and level, forms of continuity and mutation, particular types of transitions and events” and relations of possibility (Dean, 1994, pp. 93–94). 3 Mauss (2000) explored the origin of potlatch style gatherings and festivals in various cultures. His analysis of gift-giving serves as a key reference point for the anthropological exploration of economic systems, which are based in symbolic, playful exchanges that are also deadly serious. 4 Bataille's (1991) theory of general economics explores art, magic, games, and festivals as “excess energy” burned off by the “economic organism.” Similar to Mauss (2000), Bataille situates “gift economies” as a predecessor to (and a cure for) capitalism. 2

5

She “lost” to Eleanor Roosevelt. Multiple gaming studies from XPARC were published, most notably: Ducheneaut, Moore, and Nickell (2007), Williams et al. (2006), Yee (2006a). 7 A cached copy of the original website is available for historical research (see Pelling, 2002). 8 Black hat hackers seek to disrupt security protocol, often for personal gain (Moore, 2005). Black Hat gamification usually deals with scarcity, competition, and compulsion. One example of “black hat” gamification is McDonalds' Monopoly , which uses chance and scarcity to drive harvesting behaviors. It is important to note that black hat and white hat hacking are two sides of the same coin; they merely embody different motivations. This is also true of black and white hat gamification, where applications can have white and black hat mechanics embedded. 9 White hat hackers seek to shore up and reinforce security protocol (Moore, 2005). White hat gamification seeks to reinforce behaviors with positive, rather than negative, feedback. One example of “white hat” gamification is Foursquare , which takes a less competitive and more collective approach to gamifying social spaces by positively reinforcing certain renditions of spatiality. However, Foursquare also contains competitive mechanics (e.g., the “mayor” function); most gamified applications have a variety of mechanisms that span both black and white hat mechanics. 6

Chapter 3

Gamespace, Simulation, and Gamification In 2016, Time Magazine 's online newsfeed claimed that a largescale mob in Taiwan “may have just shown us what the end of the world looks like” (Jenkins, 2016a). Reporting on a video posted from Taipei, reporter Nash Jenkins (2016a) states: “we see a mob pushing through an intersection…with the urgency and intensity one usually expects of marathons or attempts to escape alien invasions or terrorist attacks… Overcrowding is so intense, reports say, that the civil-defense brigade has had to be called in, along with police reinforcements from neighboring areas.” The video itself shows people acting collectively, like a swarm. The crowds are separate yet choreographed, like a hive of ants. They were playing the hit augmented reality game Pokémon Go with overlays of collectible creatures projected onto the locational maps provided, of course, by Google Maps (Sabin, 2017). Similar events have occurred in New York City's Central Park and even the Tual Sleng Genocide Museum in Cambodia (Jenkins, 2016b). When Pokémon Go first came out, it seemed many thought the world had lost its mind. However, an application like Pokémon Go has a long set of precedents, which we will explore in this chapter. Pokémon Go , according to Zuboff (2019), is a significant example of a technological “apparatus,” a large complex of technologies central to surveillance capitalism. While there are a variety of ways to describe the apparatus, there is “a consistent vision: the everywhere, always-on instrumentation, datafication,

connection, communication, and computation of all things” (Zuboff, 2019, p. 202). Pokémon Go , it turns out, is a data-fracking service, profiting off selling locational data and models to third parties, including Google and other agents in the “behavioral futures market” (Zuboff, 2019). It is far more than a simple game; it is gamified. All of the apparatus is geared toward prediction, and yet it relies on what Zuboff calls extraction and execution architectures . Extraction is meant to pull large-scale data sets from an application like Pokémon Go , while execution architectures aim to impose “hidden economic objectives” on the “vast and varied field of behavior” (p. 203). I argue that extraction is based at the level of the interface. Interface, here, refers to a collection of technologies that allow a user to interact with the digital or computational system (Gane & Beer, 2008). As a concept, “interface” is a collection of practices and technologies that enable or constrain new media usage. Interfaces include screens, peripheral devices like mice and keyboards, sensors, GUIs/HUDs, sprites/avatars, maps, and locational notations. They primarily assist in the navigational aspects of software usage, allowing users to connect with and explore the enablements and constraints embedded within a program's design. By exploring the historical evolution of interfaces, especially mobile ones like Pokémon Go , we can see why extractive architecture is a natural outgrowth of computation and gamification. While computer games require players to respond to minute haptic controls, gamification's “controls” consist of everyday activities – e.g., exercising, shopping, and pet care – mediated through a spatially oriented graphical user interface (GUI). In this chapter, GUI is used to refer to any visual, icon-based system for controlling software as opposed to a text-based command line interface (CLI). GUIs, in computer games, are commonly referred to as heads-up displays (HUDs) that contain menus, minimaps, inventories, and status bars. Sometimes a HUD is considered to contain all elements of a game's primary visual navigation/control system. However, in gamified applications, the term GUI is still used to describe the visual interface. This nomenclature is most likely a result in the discursive differences between games and gamification described in previous chapters. In order to simplify term usage, I refer to any icon-based

visual control system, whether it is production-oriented or ludic, as a GUI. Interfaces, on the other hand, are conceptualized as the connective tissue that holds users and digital space together – a tether that forms the base of the Stack and the source of profits for surveillance capitalism. Digital spaces are generated and sustained by computation. “Natural” laws, such as gravity, are simulated in digital spaces. For example, gravity in a digital space, along with everything else, is negotiated through digital code. However, digital spaces and computational code do not escape the long arm of materiality. For example, the electrons that arrange and transmit information on a hard drive have weight and light itself is the physical medium enabling all digital media (Kittler, 2010). Therefore, digital spaces are not mutually exclusive to physical space – there is no great divide. Physical space enables the perpetuation of coded digital spaces while coded digital spaces actively expand and alter the possibilities inherent in existent physical space (Kitchin & Dodge, 2011). Gamification utilizes spatial computing – which involves the digitization of spatial data via geographic information systems (GIS) – in combination with gamespaces designed for monetized surveillance. Gamification decontextualizes physical and digital spaces to drive monetized gamespaces that feel immersive, pleasurable, and natural. By doing this, gamification produces a vast set of living simulations enabled via mobile interfaces. Behaviors that were formerly modeled via mathematics are now performed by living beings in real time. Rather than using outright probability to predict behaviors, the data generated by players become the basis for simulation in real time. These data provide the capital that supports gamified environments and ensures the continued production of gamespace. The histories of technologies that currently inform gamification's developmental course – early games, GISs, and spatial simulation – provide it with specific characteristics. The respective genealogies of gamification and gaming, in the case of spatiality, splits at the point of computational simulation: While games are spatially selfreferential and thus simulative in nature, gamification uses game mechanics to feed player data into profitable, full-blown simulations

(Ruffino, 2014; Whitson, 2013). This chapter explores the gamified “ludic interface” (Fuchs, 2012) – a type of ludic interface that involves direct monetization of everyday activities – as extractive architecture centered on seductive spatiality. Fuchs (2012) states that ludic interfaces represent a subset of interface design. They comprise an interface that supports play and is applied to either digital or nondigital phenomena. For example, Gane and Beer (2008) state that, from the standpoint of new media theory, “the interface” is a concept linked to media usage rather than a collection of specific objects. The objects used to interact with new media are constantly changing and being remediated. Like Gain and Beer, Fuchs points out that the ludic interface is a conceptualization, and it includes anything that allows a player to visualize the rules of the game, navigate the gamespace, adjudicate possible actions, interact with the mechanics of the game, and understand their role within the game. The ludic interface is a broad concept that refers to the GUI/HUD, the haptic controls, and the medium or delivery mechanism of a game synchronizing with a player to advance play. The ludic interface supports the game content and narrative by facilitating player engagement. The “gamified ludic interface” is a ludic interface that capitalizes on the surveillance of everyday activities such as exercise, shopping, and pet care. Like the ludic interface, it is a concept that refers to a collection of objects and software that allows players to interact with a gamified environment. This chapter positions historical collusions of early game GUIs, GIS precursors such as radar, and early visual–spatial applications as linchpins in the development of modern gamification, and the creation of gamespaces where big data can thrive. I will (1) examine relationships between early GUIs, computer games, and gamification; (2) explore the relationships between radar technology, GIS, and gamification; and (3) trace links between early digital games, gamification, and spatial computing by analyzing modern gamified applications that rely on spatially situated game mechanics. Finally, I parse how gamification uses (or misuses) gamespace in order to embed seductive protocols within quotidian spaces via network architecture.

Analyses in this chapter cover early GIS technologies (e.g., radar) and the development of early computer games such as Nimbi , Pong , 1 and Spacewar. I examine these historical examples in juxtaposition with modern, location-aware gamified applications such as Strava , Pokémon Go, and Ingress , which is the Google-funded precursor to Pokémon Go . These analyses are used to construct a genealogical history of gamification from a spatial standpoint; they provide insights into gamification's alterations of everyday spatiality by examining how gamification borrows aspects, or signatures, of past technologies.

Gamification, Gamespace, and the GUIs Gamified applications that alter space use a combination of ludic interfaces, surveillance, and spatial simulation that expands the scope of gamespace to encompass everyday activities for the purposes of biopolitics, surveillance, and capital. Gamified spaces – and their monetization of players as they move through space – utilize approaches of early GIS such as radar by tracking both objects' and players' actions in space. Like radar, gamification spatially identifies and contextualizes the movements of players and related objects. As such, gamification is used to generate data for social and spatial simulations, producing a model of everyday activities on a massive scale (Whitson, 2013). In this respect, geolocative gamified applications are more like early GIS systems: rather than solely tracking player-generated, self-referential objects (like the path of a spell cast in the direction of a goblin), GIS and GPS seek to track, simulate, and contextualize actual objects – such as a ship, plane, or person – as they move through space. For example, Strava , a location-aware biking application, requires players to map their routes and competitively follow others' routes. It records performance and players can compete against past times on any given route by any given player. Players form clubs and compete for leaderboards. They also share their biking-related information, and they accrue social capital within the community by sharing this information. They also provide revenue to Strava (and other parties) via their playful behaviors. The outcome of Strava's

style of gamification is usually a very detailed map of a person's biking life as a variety of minigames, each with their rewards and motivations. In the case of Strava , players are cyclists, and their mode of social capital is interactive cartography. Their age, likes, dislikes, and social network is attached directly to their life as a cyclist. Strava is a data-driven apparatus which utilizes digital objects to ensure and track actual player movements. In turn, it also informs consumer predictions on the part of those consuming the data produced. Strava tracks a live spatial simulation, much like GIS systems; however, instead of computational models, biological actors become a living model used in a consumer-oriented simulation. Players participating and fueling spatial simulations that rely on digital and physical objects provide the basis of many location-aware mobile applications, including gamified ones like Strava . Gamified applications often combine the tracking capabilities of radar, the algorithm-centric concerns of spatial simulation, and the delight inherent in iconic, responsive GUIs to create seductive network architecture in spaces where there previously was none. These spaces, which are simulation-oriented gamespaces, work as data generating spaces that help to model futures by influencing and tracking play patterns. Gamified applications draw from several previous media technologies to generate profitable outcomes. Gamified applications, like all media, follow the process of remediation (Bolter & Grusin, 2000), its design architecture contains signatures of media systems that preceded it. Because they involve tracking and contextualizing movements through space, gamified applications refer back to previous media that involves representing spaces and manipulating spatialities, such as spatial simulations, radar, and early computer games. These media are precedents to gamification's spatial functionality, which is primarily the creation and maintenance of monetized gamespaces geared toward the surveillance of bodies and objects as they are in play. Part of examining gamification from a spatial standpoint requires examining early interfaces that informed the design and implementation of gamified environments.

Applications like Strava use gamelike GUIs to drive ludic interpretations of everyday spatiality. Gamespaces, analog or digital, are mediated by a variety of interfaces. Conceptually, interfaces can be several things, such as a haptic controller. However, in the case of digital games, the most recognizable interface is the GUI, which gives gamespaces an architectural structure 2 and an aesthetic, sensuous appeal. GUIs in games come in many different forms, and even those games that include minimal GUI elements use that absence to increase the overall quality of the architectural space – whether opaque or transparent, all games utilize GUI elements. These elements can include tools for manipulating and viewing maps, avatars, currencies, player characters, inventories, objects, and available actions. GUIs in digital games and gamification immediately respond to user input. They are visually arresting, and they control every aspect of how a player interacts with her or his environment. GUIs provide the contextual information needed for navigation and the seductive motivation to explore and perform tasks. As de Souza e Silva (2006, p. 262) states, “every shift in the meaning of an interface requires a reconceptualization of the type of social relationships and spaces it mediates.” It is especially true of the ludic interface, which is both the “driver and product” of games and gamification (Fuchs, 2012). The gamified ludic interface, while inspiring delight in the player, also serves the purposes of generating capital in the context of data used for sophisticated economic, biological, and social modeling. Like LBMGs, the GUI of a gamified application links to a mobile device, such as a cell phone and a location-based sensor. Many fitness applications combine a playful, responsive GUI with movement sensors and global positioning systems (GPS) to sustain the game logics that produce useful, monetized data concerning everyday activities. For example, when users of Fitocracy – a social workout application that is also a location-based network of fitness enthusiasts – check into locations and list their exercises and caloric burn, they are creating a playful “map” of their fitness routine that serves the interests of various consumer organizations. Gamified GUIs mediate monetized gamespaces by encouraging players to move in specific ways toward certain locations, much like a quest.

The GUI is what allows players to interact with the game mechanics on a visual level. This deep combination between space, user, and interface were first developed in LBMGs, which also utilized locationaware sensors to toy with players' practices concerning co-proximity, navigation, community, and sense of privacy (Licoppe & Inada, 2010; Sutko & de Souza e Silva, 2008). Spatialized gamification is mostly an instrumentalization of the mechanics and practices pioneered in the creation of experimental LBMGs. Gamified environments are a set of ludic and often mobile interfaces, which includes GUIs in addition to haptic interfaces such as controllers and touch screens, that utilize playful game mechanics to spatially situate and direct players in fueling spatial and social simulations. The GUI of gamified applications, when used with a mobile device, contextualizes everyday spaces into gamespaces by motivating player movement through physical space. Additionally, gamified applications employ the simulative, control-oriented qualities of digital games to monetize ludic spatiality in the form of data. For example, the rewards application Shopkick utilizes badges and points to direct the movements of shoppers to specific stores, offering rewards when shoppers check in at certain locations. It provides the mechanics needed to motivate certain types of monetized navigation; in turn, players give valuable information about what types of rewards will motivate consumers to alter their movements through space. Gamification relies on two methods to render its specific iteration of gamespace functional. The first method capitalizes on seduction and delight by using a ludic interface that architecturally “frames” spaces in favor of seduction; the second method involves monetizing reframed space by using gameplay actions to provide data for complex social, economic, and spatial simulations. The technologies that inform modern gamification and games are similar in the early years of spatial computation and interface development. Radar, like gamification, tracks physical objects by representing them digitally. Additionally, the radar screen (CRT monitor and oscilloscope) enabled computer games to display digital objects where there was formerly text – visual displays, like the CRT monitor, used icons for computing. Gamified applications also utilize digital objects and

icons, and often, as is the case with Pokémon Go's colorful world, the digital objects are embedded directly into physical spaces. Since both gamification and games produce gamespaces, their technological predecessors are similar. The first visual computers 3 – and by extension, the first GUIs – used en masse in the US, Canada, Europe, Russia, and Japan were arcade games and, later, home consoles (Donovan, 2010). For example, Tetris was invented in a Soviet research lab circa 1984; interestingly, Tetris went “mobile” for Gameboy in capitalist regions, but Russia (and the game's creator, Alexey Pajitnov) did not benefit until many years later (Johnson, 2009). As closed off as the Soviet Union was, good games always prove to be universal and mobile. Tetris is an infectious game, and it managed to transgress ideological, cultural, and economic iron curtains. However, suspicion followed it; some critics saw Tetris as a “plot” to distract American youth with useless mental exercises (Johnson, 2009), which reinforces the idea that games and play may be a transportation mechanism for contentious policies, habits, and technologies (Elllerbrok, 2011). Tetris is a prime example of how ludic interfaces spread, becoming mobile vectors for gaming culture. Over the years, the types of ludic interfaces have multiplied as visual computing has advanced. In order to clear up any overlap between terminologies, I should note that the term “heads-up display” (HUD) is often preferred when designing game GUIs to avoid confusion with production-oriented software; games represent some of the first icon-based control systems for digital computers (Donovan, 2010; Gere, 2006). As such, the visual aspects of ludic interfaces precede the modern, production-oriented GUI. Computer games used icon-based systems for controlling software that predated the Xerox STAR , the first widely available productivityrelated GUI released in 1981, by nearly four decades. For example, OXO , an adaptation of tic-tac-toe, was developed in 1952 (Donovan, 2010). The development of the GUI played a large part in the proliferation of personal computers (Gere, 2006). Before Macintosh's system of icons embedded with an operating system, domestic computer users had to go through the laborious process of learning thousands of textual commands. It is lesser known that the

ludic interface informed the creation of production-oriented GUIs based around a desktop metaphor. The development of the GUI actually overlaps with the advent of both computer games and personal computers – researchers and entrepreneurs observing the arcade craze, which began with Sega's electromechanical game called Periscope in 1966, saw how quickly the average person can learn and respond to a computer through gameplay (Donovan, 2010; Loftus & Loftus, 1983). Steve Jobs and Steve Wozniak, who worked for Atari during their formative years, were especially observant of how arcade game design (specifically the use of iconic visual cues) influenced how people used computers (Hanson, 2013). After leaving Atari, they developed the Lisa interface, one of the first fully functional GUIs designed for widespread consumption. While Lisa was a commercial and technical failure, Macintosh – Lisa's spiritual successor – was considered revolutionary. Games and the development of GUIs entwine at many different levels, a point often belabored by computer game historians. However, at the earliest stages of research, GUIs and games repeatedly collided. During the 1960s and 1970s the Xerox Palo Alto Research Center (Xerox PARC) – which developed the first productivity-oriented GUI in a research context – and Stanford's Augmentation Research Center (ARC) – which developed the haptic peripherals used to control GUIs such as the mouse and keyboard – both experimented with game-oriented research methods (Engelbart, 1968; Gere, 2006). In the case of ARC, this funding was provided partially by military institutions, which had been experimenting with using icon-based systems for computational controls since the advent of radar (see Engelbart, 1968). Like computer games, the GUI and its peripherals are the demilitarized “soft edge” (Levinson, 1997) that precluded the cultural appropriation of games, computers, and simulation (Crogan, 2011). In the case of modern gamification, the GUI serves as the seductive framework that mobilizes players within gamespace. While many early LBMGs were facilitated via text message, this predated the smartphone with a full graphic layout. In the case of Macintosh, computing became a playful interaction with a visual interface inspired by arcade games, which was

intended to make using the computer “fun.” GUIs and HUDs, whether playful or quotidian, are more than static representations. However, as many scholars of the interface have noted, it is increasingly difficult to separate a space from the interface that defines its use, because interfaces, and all optical media, also produce their own spaces (Gane & Beer, 2008; Kittler, 2010; Manovich, 2006). Within gamification, the interface determines what actions are taken in a (game)space and why those actions are beneficial. The interface includes the surveillance of spaces; who or what is monitored is embedded in the interface of all gamified applications and displayed by the corresponding GUI. For example, Strava draws attention to the routes and times other bikers take via its GUI, making competition on a route a primary focus of players who employ it as a biking application. This spatial monitoring links directly to early GIS technologies, namely radar and spatial simulation.

Radar Games: Spatial Monitoring and Spatial Play Radar is the precursor to both early games and early visual computing, including the GUI. There was no technology before radar that accounted for digital representations corresponding directly to physical objects. Each digital representation, in the case of radar, is moving through representational space. In turn, all spaces also corresponded to physical spaces. Before radar, some panoramas and stereoscopes could represent space and movement. However, these movement-oriented mediums were rudimentary projectionbased technologies that preceded television and cinema (Huhtamo, 2012, 2013). In other words, the representations in panoramas only corresponded to the narrative they served. They did not directly represent reality; they interpreted events via an artistic medium. The computer screen and everything represented on it, including this text and the GUI that enables me to write it, are not projections or physical objects – they are digital objects that correspond to the logic of the programs I use.

Digital objects, the basis of most computer games, HUDs and GUIs, are functions generated by computer programming – they are the simulacra that fuel simulations (Baudrillard, 1981a). The correspondence between a digital object and digital space is the primary way in which a GUI differs from a radar readout (Gere, 2006). Physical objects and spaces were tracked first while selfreferential digital representations came after. Before game developers could employ realistic game physics and real-time movements, technologies had to compute and represent actual physics. Gamification is unique because it combines two formerly separate approaches. Before gamification, physical objects were tracked by spatial technologies like radar. These technologies did not influence the movements of physical objects – i.e., they did not provide a purpose for movement, only a real-time record. Alternately, digital objects are self-referential – user input is the sole method of initiating movements and movements that only affect the embedded digital spaces. However, gamified design uses digital objects and spaces to influence, track, and represent physical objects moving through space – objects such as bodies and capital. The mobile technologies that facilitate gamification use GPSenabled devices to create objects, guide objects, and track objects (Gordon & de Souza e Silva, 2010). Gamification does more than just guide; it uses a screen filled with digital and physically represented objects to influence fundamental reasons for why movement occurs and the context for tracking this movement. It adds an extractive logic to movement, a collective mind to those following its cues. Like LBMGs, which create inject gamespaces into nonludic spaces, gamification also visually alters how space is represented using simulative process. By injecting digital objects and physical representations into the rhythms of everyday space via the screen or monitor, gamification draws heavily from both early computer games and spatial technologies like radar. The cathode ray tube (CRT) monitor of the radar allowed the visualization of early computer-based games, such as Pong, in addition to the eventual design and production-oriented GUIs (Gere, 2006; Lowood, 2009b). Gamification shares more ontological similarities with early GIS technologies and spatial simulations than it

does with early games and gaming technologies. Arcade and computer games took a self-referential, transmedial approach to computational aspects of play where players bought one unit (a game). Playing the game did not produce any profit; all actions taken during the game refer only to the game itself. In gamified environments, players become agents in an active, living simulative space. Tracking and predicting player actions through designed gamespaces is what creates data and capital. While the ludic interfaces of early gaming consoles and arcade machines are both drivers and products of the widespread cultural appropriation of computing as game devices (vs military uses), the visual–spatial aspects of computer games and their GUIs are also linked to radar technology. For example, the Cathode Ray Tube Amusement Device was a missile simulation game developed in 1947 based on radar technology – it electronically simulated tracking and destroying represented missiles (Donovan, 2010). Tennis for Two (c. 1958), Pong's predecessor, was created by modifying an oscilloscope, a radar-based CRT technology. However, instead of having the monitor track physical phenomena identified via sonar or radio frequency, researcher William Higinbotham decided to alter the machine to track virtual objects created and transmitted by a computer (Lowood, 2009b). In both Pong and Tennis for Two , the “ball” denoting the digital object was knocked back and forth with control knobs – it had no correspondent in physical space. The edges of the screen, which contain lines usually representing the location and frequency, were appropriated to represent “paddles” (Lowood, 2009b). They served as the sprites indicating the location of the player's game piece, the digital paddle. In this case, the iconic gamespaces and GUIs of Tennis for Two and Pong used a repurposed radar display (an oscilloscope) imbued with game mechanics. Tennis for Two was not created solely for amusement. Rather, it was a visual example used to inform the public about the power of computers. While computers were popularly considered arcane math or war machines, the game allowed the public to glimpse the power of digital representation and then interact with digital objects at a fundamental, playful level. Computers were not arcane machines or

harbingers of nuclear destruction; they could be fun . While it was not necessarily gamified, like most early games Tennis for Two was linked to marketing: It was funded by the US Department of Energy to promote atomic power and sway public opinion. Visually, Tennis for Two represented the fact that computers could be just about anything, including a gaming device. Also, the spatial focus of the radar screen translated quickly into a gamespace once imbued with a ludic interface. Today, the same stands true for spatial technologies; many locational tools such as Google Maps are being used to provide spatial data for both LBMGs and gamified applications. Increasingly, spatial technologies are being used to provide game-based public services. For example, Google purchased the gamified social navigation application Waze – which integrated with Maps – for over one billion dollars purchase price in 2013 (Wasserman, 2013). It turns out that complexity and newness mitigate surveillance with good old-fashioned fun and games. While early computer games emerge from radar display technology (via the CRT monitor and oscilloscope), games and radar technologies differ on a functional standpoint: Radar technology is meant to monitor and represent physical spaces and actual objects as they move, while computer games are meant to create spaces through which a player moves. In the case of gamification – which uses game objects to provide purposeful movements and then records these player movements through physical space – radar and early computer games' signatures are present. However, instead of creating spaces, gamification draws from radar's monitoring functionality to create and track objects in physical space. Digital objects such as badges, location markers, or obstacles are used to motivate players to move through physical space so that they are contextually tracked. Radar straddled the gap between analog and digital media (Gere, 2006). Before the 1960s, radar was based on analog radio transmissions and sonar visualized via an oscilloscope; it was mainly an electromechanical technology. Researchers such as Claude Shannon, who worked in computing, often worked with radar-based applications, as well. Shannon, who was also partially responsible for the first wearable computer, was integral to the development of

missile navigation systems and spatial simulation (Crampton, 2010). Shannon's interest lay in computing probability, 4 and his work with predictive radar guidance systems led to the combination of analog radar with computational technologies (Crampton, 2010). In part, Shannon's digitization of the (previously analog) radar led to the creation of modern GIS that enable the current state of interactive, mobile cartography such as Google Maps (Crampton, 2010). His work on radar guidance systems allowed for the real-time calculation of moving objects in space using radio frequencies and rapid computation. Shannon's work also changed the way radar worked: Now radar systems could also guide an object, rather than track a trajectory. This task required an on-the-spot computational model for rendering Tobler's (1970) first law of geography for the guidance of a highspeed object: “Everything is related to everything else, but near things are more related than distant things” (p. 236). 5 Shannon's work in virtualizing the radar and creating reactive navigational systems led to modern GIS systems that recognize signal-based inputs from a moving object, such as radio-frequency identification (RFID). These advances also allowed researchers to input virtual coordinates into a radar-based tracking system visual representation and mapping – and this system's basic idea was also employed to create the first iterations of Pong . The combined representational display and tracking abilities of both the radar and the computer contributed to the creation of LBMGs that also generate, guide, and display digital objects and objectives. GIS, in tandem with GPS, also facilitates most gamified mobile applications, including location-based social applications like Foursquare (de Souza e Silva & Frith, 2011) and Ingress (Hulsey & Reeves, 2014; McGonigal, 2011). As of now, most radars are virtualized – that is, the computer interprets sensors' data, rather than an actual, mechanical radar (Crampton, 2010). Almost all cell phones hold radar's remediated signature, as they allow for real-time tracking of objects' and users' locations in space. However, whereas digital games create digital spaces, gamification borrows from tactics employed by LBMGs, digitizing, and altering quotidian physical spaces while still monitoring the

movements of targeted physical objects through that space. Unlike LBMGs, gamification then feeds the gameplay directly back into extensive networks of capital and control. While Pong was selfreferential, gamified applications like Pokémon Go utilize Pong -like mechanics – namely the generation and manipulation of digital objects acquired by strategic movements. However, Pokémon Go tracks human bodies, not digital sprites. The result has been surveillance-oriented applications, which combine the seductive visual elements of game-oriented GUIs with tracking-oriented technologies. While gamified ludic interfaces hold the remediated signature of the radar and early playful GUIs, visual interfaces only represent one aspect of its profitability. The other end of gamification's popularity is its ability to contextualize the data it helps to create by tracking purposeful movement taken to achieve ludic objectives during gameplay. It does this by relying on spatial simulation and modeling, which also link back to early computer games and their iconic, visual representation of spatial information.

Mathematical Marketing: Simulation-based Spatial Software From the standpoint of early computing and computer games, radar's CRT monitor provided the computer with a way to visually represent coded objects through a spatial GUI. Visual aesthetics, specifically for gaming and simulation, created the epistemological conditions necessary for the social appropriation 6 of visual computing (Fichtner, 1999). The modified CRT monitor combined with the surveillance and tracking capabilities of radar technology allowed researchers to construct gamespace as coded space. Previous to the GUI, all interfaces were CLIs, which treated digital games as logical processes enabled by coded text. Early explorations of visually seductive computer games were created to test and market the capabilities of a computer's processing ability – gamespace as an aesthetic product was ignored in favor of creating advanced logical simulations. This line of research changed with Spacewar , a game that pioneered the use of a sophisticated,

striking, and interactive ludic interface to drive playful behavior. Key to this advance was the use of a visual interface that reacted to players, thus forcing moves, rather than merely representing movements. Players had to avoid or shoot incoming objects in order to progress. While there are many ways to win, some movement or action is required by the game mechanics. While Spacewar contained no true AI in the sense of a decision-making tree, the randomized movements of “enemies” in the game presented an immediacy that, up until that point, was lacking. The pace of Spacewar was frenetic, and movements on the part of players and the computer were nearly instantaneous. The speed at which Spacewar , the first “bullet-hell” game, forced players to react was hitherto unexperienced. By 1960, the Massachusetts Institute of Technology (MIT) was home to the Artificial Intelligence Laboratory (Donovan, 2010). The laboratory had a custom computer, the TX-0, which was somewhat smaller than a room-sized mainframe. The TX-0 was accessible to students and operated during off-peak hours (Donovan, 2010). The computer attracted an engineering undergrad organization called the Tech Model Railroad Club (TMRC). The TMRC referred to themselves as “hackers” rather than “hobbyists” or “researchers” (Moore, 2005). A “hack,” according to the TMRC, was an ingenious feat of design or programming ingenuity. The TMRC and other hackers spent their nights punching code into strips of paper to create programming tools, music, and gamelike AI routines (Donovan, 2010). What resulted was a visually seductive game – Spacewar – played between human and computer, with the computer providing the aesthetic and simulative aspects of play (interactive objects moving through space) while the human player provided the input necessary for the continuance of the game. Spacewar (c. 1962) was one of the first computer games to achieve national distribution. It was a test program on every PDP-1 computer sold. This version of Spacewar was created to test and display the functionality of a GUI through gameplay. By the end of the 1960s, Spacewar became a cult activity in university computer labs across the US, and it inspired researchers and students to further explore the complexities of visual human–computer

interaction (Donovan, 2010). Even though the hackers who created and modified Spacewar could sense computer gaming's commercial possibilities, the game could only run on hardware costing thousands of dollars (Donovan, 2010). As computer components fell in price, both Spacewar and Pong became harbingers of the first wave of game consoles in the US, Japan, and Europe. While Spacewar utilized its ludic interface to explore human– computer interaction in the form of a spatial game, Nimbi was an exploration in spatial probability and player simulation (Jorgensen, 2009). Nimbi is one of many Nim-playing computers created in the 1950s and 1960s. Nim is a mathematical strategy game that originated in China, and it is one of the oldest games in the world (Jorgensen, 2009). It involves two players taking turns removing objects from distinct heaps containing different amounts. On each turn, players must remove at least one object; however, they can remove as many as they want as long as they come from the same pile and whoever is the last to take an object wins. In a variation known as misère, the goal is to force the opponent to take the last remaining object. Nimbi was a public relations endeavor released in 1962; it was an attempt a creating an “indestructible” game, that is, no mathematician or player could “beat” its code via predictive calculation (Jorgensen, 2009). In short, it was an attempt at creating an unhackable, unbreakable set of coded protocol that imitated a human player. Nim, similar to chess, is considered a “mathematical game” – a game that produces useful algorithms – that was of particular interest to mathematicians and computer scientists (Jorgensen, 2009). Researchers such as Claude Shannon and Herbert Simon utilized mathematical games in their work to understand machinic and human intelligence. Chess was necessary; so much so that it was called the “Drosophila of AI” (Jorgensen, 2009). Uniquely, Nim is an impartial game. In impartial games, it is the space of the game that matters, and not the movements of players. In short, it makes the set of allowable moves dependent on the position of gamespace about players. Nim, as a mathematical entity, produces algorithms that redefine a “game” as a position taken between two players (Conway, 1976). It produces a locational

gamespace depending on the size of the piles from which objects are drawn. Many LBMGs mimic these mechanics – often, more than just the location of other players are required to play. Location-based games utilize the resources available at specific locations – i.e., the “size of the pile” – to drive the movements of players. 7 Of course, other players can also be a resource. Even still, if that is the case, it is the number of players present in space with will influence movement. Numerous Nim-playing machines were devised, and Nim itself accrued a long mathematical history (Jorgensen, 2009). Nim fell out of favor as chess dominated the field of “game-playing machines” (Jorgensen, 2009). Critics and historians dismissed Nim as a class of game that attempted to “devise algorithms which can be used to ensure a win,” and it was deemed “mathematically trivial” (Jorgenson, 2009, p. 46). Nimbi never generated the publicity it was meant to, but it did demonstrate that a computer could imitate an actual player, which changed the implementation of games – no longer did a human face off against the game (as in Solitaire) it was challenged by the computer. Nimbi demonstrated that the algorithms produced by Nim could be used to simulate a human opponent and it informed the evolutionary simulations conducted by mathematician John M. Conaway, a principal researcher in agent-based simulation (Jorgensen, 2009). Nimbi was a software program that simulated a second human player and played against the human rather than always choosing the optimal combination to win. Thus, it could not be “outwitted” and produced randomized results that simulated a human opponent. However, Nimbi only simulated the logistics of space as mathematical. Unlike Spacewar, it ignored the qualities of an interactive, seductive ludic interface. Instead of a CRT or oscilloscopic display, Nimbi used a textbased IBM console and a game board that represented the gamespace. Its failure has much to do with the fact that it did not provide the immediacy of games like Tennis for Two or Spacewar . Still, Nimbi embodied the search for a game that both defines and defies the basic precepts of computational simulation: It sought to simulate a logic game that defied further simulation, thus imitating a human player. However, Nimbi was also partially gamified: Like

Tennis for Two and Pong, it was deployed as a public relations apparatus to highlight the capabilities of computers. Advergaming entwines with the earliest examples of computing, including the reasoning for producing computers games. Beyond marketing, Nimbi also follows gamification's central proposition: in order for a digital game to produce capital via play, it must deny the trappings of finite games – the game cannot be “beaten.” Rather than an actual game, Nimbi was a game-based simulation used for research and marketing purposes. Its commercial failure rested on the fact that it was not visually stimulating, and as a result, it was not taken up by researchers or consumers. While Nimbi was a commercial failure, many early computers shipped with Nim-playing software based on its design (Jorgensen, 2009). These later computers added a GUI-enabled ludic interface to the game to motivate players to engage with Nimplaying software. While Nimbi itself is an interesting sidenote in computer game history, its primary importance lies in the fact that it preceded advanced cellular simulation – a precursor to agent-based modeling 8 used in almost all modern simulation-based games and gamebased simulations. As stated before, gamification seeks to unify these formerly separate categories. Evolutionary simulation games – including the groundbreaking Game of Life, which is covered in the next chapter – contain many of the same algorithms generated by a match of Nim – both generated gameplay via combinatorial game theory, or CGT, where moves are spatially represented by “game trees” (Pearl, 1984). Also, the spatially oriented “no win” tactics of Nim are similar to the infinite game mechanics used in gamification: like Nimbi , the computer always wins in a gamified environment by manipulating the space in which the game takes place rather than directly manipulating the location of players. For example, Niantic's Ingress is an experimental, gamified mathematical simulation that utilizes aspects of game theory and simulation (Hulsey & Reeves, 2014; Lewis, 2013). It was designed by Niantic, the same team that later produced Pokémon Go . While Pokémon Go “shares” data with Google, Ingress was funded and incubated by Google for a specific set of purposes. Ingress solves

difficult algorithmic problems with player data associated with directing pedestrian traffic and improving the efficiency of locationbased advertising (Gildea, 2012; Gold, 2012; Hindman, 2013; Hodson, 2012; Hulsey & Reeves, 2014; Kolb, 2013; Lewis, 2013; Roy, 2012). To solve issues of human movement from a computational standpoint, Ingress utilizes the “no win” tactics of Nim by creating spatial uncertainty – a sense of ignorance in terms of what resources are located in a space – where players track down, obtain, and defend resources that are generated on physical locations and displayed on a location-aware GUI. Live simulations like Ingress help to illuminate decision-based probability by using actual players, rather than theoretical actors who take a set course of action based on a predetermined model. Both Pokémon Go and Ingress generate resources in specific locations and then track the combined movements that players take to retrieve them. Eventually, patterns emerge that can help to predict future movements. Humans are unpredictable – by creating situations where spatial uncertainty is a primary game mechanic, gamified applications like Ingress can provide useful data on how humans get to and from certain physical points in real time.

Gamespace and Seductive Architectures Ludic interfaces and GUIs are designed to motivate engagement with games and software based on architectural principles (Aarseth, 1997, 2001; Fuchs, 2012; Kitchin & Dodge, 2011; Silver, 2009). They embody and direct the agency of players within their respective social spaces. Social space rearticulates the proposition space is not an abstract mathematical entity – it is socially constructed and consists of physical, social, and material relationships (Lefebvre, 1991; Soja, 1989). Theorists who deal with space advocate a variant approach to interpreting modernization, one that does not focus exclusively on connections and disruptions as they occurred in time ; rather, social processes occur through both space and time, with each affecting the other (Soja, 1989). Henri Lefebvre (1991, pp. 36– 37) states that even mathematical space was subject to the social understandings of people at a specific time in place: “If space is a

product, our knowledge of it must be expected to reproduce and expound the process of production. The ‘object’ of interest must be expected to shift from things in space to the actual production of space…” Space is integral to the circulation and reification of the capitalist system; specifically, space acts as a critical player in the circulation of power. He argues that “(social) space is a (social) product […] the space thus produced also serves as a tool of thought and of action […] in addition to being a means of production it is also a means of control, and hence of domination, of power” (Lefebvre, 1991, p. 26). Like social space, “social interfaces” enable spatial relations of production and power (de Souza e Silva & Frith, 2011). For example, Pokémon Go and Ingress are both game-driven locational applications; however, players must engage directly with the ludic interface of their respective applications in order to interact with each other via gameplay. Gameplay, in turn, drives outcomes and data that are of value to Niantic and Google. Because gamified ludic interfaces rely on finely tuned design choices to produce biological and spatial capital in the form of data, architectural analysis serves as a starting point in examining the construction of gamified environments. As we will see in later chapters, architectural theory is vital in the development of modern software and game design, and game design engines are equally contributing to revolutionary approaches in architecture (Cruz & Colletta, 2008; de Kerckhove, 2001; Levy, 1997; Paterson, 2007; Schmitt, 1999; Vella, 2007). For example, games utilize architectural principles to design levels while architecture uses game mechanics and gamelike systems based in CGT-based modeling to design and test 3D spaces before their construction (Paterson, 2007; Vella, 2007). Game engines, such as the Unreal engine, represent architectural spaces and then fill those spaces with active agents; they are ideal for testing structures out as “games” before construction commences (Vella, 2007). One might say architecture itself is being gamified from the inside out – it relies on the ludic properties of game engines and mechanics to generate and test designs used for nonludic outcomes. The emergence of digital, “deconstructive” architecture in the form of spatialized interfaces is paramount to the creation of

heterogeneous spaces (Johnson-Eidola, 2005a). In other words, digital architecture – via game engines and mechanics in addition to quotidian software – determines the spatial strategies implemented. Architecture and spatial arrangements are frequently designed around technology, rather than the other way around. Additionally, spatiality is increasingly mediated and influenced via the presence of digital applications that coincide with the spaces inhabited – a process known as “net locality” (Gordon & Manosevitch, 2010; Gordon, Schirra, & Hollander, 2011; Gordon & de Souza e Silva, 2010). These digital–physical spaces, known as “hybrid spaces,” are created when the digital, social, and physical aspects of a space entwine so that they cannot be separated (de Souza e Silva, 2006). If they are altered, then the space itself is altered, as well. Interfaces, especially GUIs, are the architectural framing techniques of digital and hybrid spaces (Silver, 2009; de Souza e Silva, 2006). Framing involves altering code within a space – designed structures “frame” spatial perceptions. The architecture of a space tells the “narrative” of that space, and in the case of physical structures, we read these frames as spatial texts (Dovey, 1999). The literal and figurative meanings of architecture converge in the concept of framing. As a noun, a “frame” is an established structure or order. As a verb, “to frame” denotes creating borders, striations, and ways of seeing. Framing is a concretization of spatial identity; however, framing also implies the alteration of coded structures within a space. Framing through design physically alters space, spatial perception, and any movements, digital or physical, through spatiality. Architectural framing is a way of altering all structure-oriented spatial codes, whether that code is physical, digital, or hybrid. For architecture, designed structures channel power through framing . Like architecture, interfaces territorialize digital spaces physically, digitally, and discursively (Dovey, 1999; Johnson-Eidola, 2005b). In all design-related disciplines, architecture serves as a metadiscipline – it plays a significant role in producing and modulating rhythms in the everyday lives of individuals (Lefevbre, 2004). Its reach extends to the design of software, specifically software that represents or embodies space, such as GUIs and HUDs. As noted in

previous chapters, everyday life increasingly involves a collision and collusion between ludic, digital, and physical spaces (de Souza e Silva, 2008; de Souza e Silva & Hjorth, 2009). However, physical space is increasingly dependent on software for implementation, support, and general use value (Dourish & Bell, 2007, 2011). Space and code are increasingly inseparable (Kitchin & Dodge, 2011), and this is the rule rather than the exception in gamified environments – the architectural qualities of a gamified ludic interface determines what connections players can make within a gamespace. Issues concerning the role of design are relevant in understanding why individual iterations of gamification are successful while others are not. The extractive architecture of a gamified space determines how, when, and where a player is allowed to circulate within a given space. Mechanics – which provide affordances and constraints that encourage and reward efficiency – act like walls, corridors, and doors. They herd the player toward sets of goals and provide choices on how to reach it. Like architecture, gamespaces have an odd relationship with power – they run parallel to the realm of disciplinary power structures, yet they actively engage in the form of procedural control. Gamification occupies the same positions as architecture when it comes to the circulation of power – “power through” rather than “power over.” “Power through” is an exercise in control that uses design to produce spatial frames simulating freedom of choice (Dovey, 1999). “Power over” is typically the most widely studied form of power in sociology. Power over includes “force” and “coercion” (Dovey, 1999). Force implies the overt use of power to strip a subject of any means of noncompliance. In the case of physical structures, force manifests itself as either confining structures (prisons, asylums, and refugee camps) or exclusive structures (fortresses and gated communities). However, in the context of architectural design, it is people who exert power over others through architecture. Similarly, coercion is defined as the threat or possibility of force to ensure compliance (Dovey, 1999). There are also more subtle forms of spatial coercion linked to the Latin coercere, which means “to surround” (Dovey, 1999, p. 10). In this manner, observing space is a form of coercion. Still, when designing for spatial coercion through

surveillance, surveillance is the primary coercive mechanism. Architecture supports surveillance, again granting “power through” rather than exerting “power over.” One key conceptualization of “power through” is seduction : the “highly sophisticated” mode of sublimating the desires and interests of the subject with regards to control (Dovey, 1999). It is most often associated with advertising spaces (Baudrillard, 1981b) and gamespaces (Galloway, 2007). Perhaps because of its gamelike nature and ambiguous morality, seduction is viewed negatively by many architectural critics. K. Dovey (1999) employs a quote by cultural critic Steven Lukes (1974, p. 28) to excoriate seductive power: Is it not the supreme and most insidious exercise of power to prevent people, to whatever degree, from having grievances by shaping their perceptions, cognitions and preferences in such a way that they accept their role in the existing order of things, either because they can see or imagine no alternative, or because they see it as natural… Seduction operates by channeling desire as a “natural” resource. Seduction is about longing for beauty; however, like Narcissus' myth implies, seduction is also about transferal of human agency and (eventually) life to a series of objects and simulations that affirm our perceptions (McLuhan, 2003). Objects and structures often frame life and beauty, holding them in evaluative stasis even as “the original” fades; thus, all design enforces seductive potential. Seductive power modulates through the Utilitas (commodity) and Venustas (delight), two canons of architecture laid out by the Roman architect Vitruvius (Bruegmann, 1985). Commodity deals with how structures meet their designer's ends. However, structures are also judged based on the values of the ends themselves. For example, while Auschwitz may have been a triumph of design efficiency, it will never be considered a triumph of Utilitas . Bruegmann (1985) states that one aspect of a commodity implies functionality, while the other implies moral and conceptual formations: “both spring, and spring inevitably, from the link which architecture has with life” (pp. 3–4).

However, the most potent and intangible architectural link to seduction is Venustas – the element of “delight.” Delight and seduction, in this context, are positive forces that are attuned to affect, play, and sensuality (Grosz, 2008). Delight is playful – it is a world-building activity that does not rely on coercion. Seduction and delight are also commensurate with desire or generative power without force. For example, Bruegmann associates Venustas with desire and a search for beauty. The productive tensions embedded in Utilitas and Venustas illuminate the spatial aspects of Baudrillard's (1979) concept of both seduction and simulation as dovetailing concepts: Seduction and simulation occupy the same cultural “space.” Both are rooted in desire: simulation in a desire to know the future and seduction is a desire to live the present. Like simulation, seduction has no stable form; rather, it inexplicably works with or against established order based on its logic. Deduction and desire act as a gatekeeper of possibility. They borrow from commodity to obscure or illuminate what is possible. However, seduction is also actively modulated, directed, and actualized through the commodification of possibilities. Seduction is self-referential and steeped in the human urge to be pulled in and guided by the signification of beauty and completion (Baudrillard, 1979). It neglects force – desire is necessary for seduction, simulation, reproduction, and play. Gamified hybrid spaces and ludic interfaces leverage both commodity and delight for control, rather than force or discipline. The ludic framing of everyday spaces generates gamespaces that require architectures of choice, or mechanics, to operate – in turn, mechanics must have players. Jacques Derrida (1966) points out that playful qualities of language allow the formation of “the event,” and that events themselves require play to maintain any meaning. Linguistic aspects of culture, then, are a series of meaningful social and mental games. This same viewpoint is echoed for spatial formations, which embody structural agency, by architectural theorists like Brian Tschumi (1996), who points out that architecture is the physical embodiment of the event – the extractive architecture informs and frames the physical, nondiscursive aspects of designed spaces. It is the architectural qualities of games, and thus the architectural qualities

of desire, that frame play. The design of games also allows us to reject the actual in favor of what is possible and vice versa. For example, Huizinga (1950) states games act as ritualistic explorations of cultural possibilities that appear to be “outside” of culture. However, a better term would be “parallel to culture.” Games explore and channel play, and the possibilities it contains, as a sort of cultural laboratory. Play and desire are always generative; thus, desire and play naturally beget more structures, more games, more objects, and inevitably, more complexity. More complexity, in this case, is not always synonymous with more freedom. However, as Hays (2009) points out, architectural freedom (like “freedom” in a gamified environment) is a matter of perception. Seductive design choices are aimed to create delight as expressed through spatial arrangement, and thus it commoditizes and controls spatiality via sleight of hand. In other words, seduction obscures commodity with delight, while channeling delight to produce new forms of commodity. Seduction, which is epigenetic, is based on the transformative process of channeled desire. For example, once an Ingress player completes and goal, new goals are created based on that completion. As the player progresses, the levels and goals of Ingress change to meet her progression, providing a never-ending negotiation of prolonged desire. Over time, the physical spaces will change to support this negotiation, and alter the user's perceptions of these spaces, as well. Dourish and Bell (2007) points out, one aspect of ubiquitous computing is the tendency of physical paces to mold themselves in support of informational infrastructure, rather than the other way around. Seduction, whether inscribed through a ludic interface or a building, always implies that a game can be played . However, seduction stops at an implication. Seduction is not the game; it only signifies the possibility of a game (Baudrillard, 1979). The free will of players is the key to seeing seduction through to its endpoint. So, gamified applications must keep players in action. Seduction suggests that almost any space can become a gamespace if the right frames are applied. The ludic interface, as it applies to gaming and gamification, always contains some form of seductive architecture – after all, playful protocol always generates more

playful protocol (Galloway, 2006). Seductive architecture drives the design of the GUI and the creation of the hybrid (game)space; it also the sustains game mechanics embedded within the space, thus ensuring the space's continued existence. Players, if they are to remain, players, must be able to engage with game mechanics and serve the logic they represent – all player activities must embody the game via instrumentality. Without mechanics, gamified spaces are merely quotidian spaces, and gamified apps are reduced to services. In this situation, players become users, and gamified hybrid space ceases to exist. Gamification must produce play, and play is necessary to support “players” as a subject category. Because players are the primary means of producing capital and data, seductive mechanics must always be present to draw players into the gamespace and reward them for participating – players must desire to become instruments of the game. Gamified applications use seduction to create a gameplay where there previously was none, and this is the key: Humans, in the end, are always for play. Gamified design's use of seductive architecture seeks to give people more of what they want. As opposed to drudgery, gamification presents an altered version of everyday life. However, gamification is fragile: without mechanics, it does not exist. In this manner, seductive architecture, operating via the gamified interface, always embeds the potential to alter an environment in favor of play. Pokémon Go and Ingress players can just as easily navigate spaces for quotidian rewards; however, they choose instead to use gamification to transcend the ordinary, to alter and upend quotidian spaces. The answer to why this extraneous layer is needed has vexed biologists, metaphysicians, and social scientists: why play? Gamified design and the resulting applications embody this question because they attempt to harness ambiguity for clarity and promote desire for control. Gamified design uses ambiguity in order to drive its living simulations. Because of seduction's complicit relationship with playful desire, seductive ludic interfaces induce the evolution of gamespace. Without seductive frames, the mechanics of Ingress and Pokémon Go hold no power. The usefulness of gamified design relies on its ability to suspend players in a playful, behavioral, and spatial loop, to keep bodies in motion within space.

Gamespace: Desire, Space, and Simulation Collide Gamespaces always inhabit the liminal spaces between what is actual and virtual – there is constant tension produced via the player discovering what alterations within a space. Gamification relies on playful actualization as its business model – it produces capital by mapping players' collective behaviors by converting everyday spaces into spaces where simulation is a foregone conclusion. Thus, gamified spaces are gamespaces, albeit modified ones. Gamified environments host gamespaces that tend toward complete monetization and full-blown simulation using live actors. Interface and mechanics determine a gamespace, not ethics. The primary difference between gamified spaces and traditional gamespaces is simple: gamified spaces always seek to alter existing spaces by modifying possibilities, while traditional gamespaces create new spaces and possibilities . For example, a utilitarian social space like a dog park exists before Ingress ; however, gamified applications grant new, gameplay-oriented contexts to these spaces for monetized simulation. While an LBMG might also alter the dog park, the park takes on an entirely new meaning distinctly related to the game. Ingress , beyond gameplay, produces useable data. Ingress makes the park a central resource node, a space that hosts embedded mechanics that identify the space as gamespace. Rather than being layered onto the park, Ingress decontextualizes the park itself for players, who may or may not be there to walk their dog – but it does this to complete a goal beyond that of a game. Games are self-referential in their use of seductive architecture; Spacewar and Pong both aid in producing new spaces that only have meaning in the context of gameplay. However, the seductive architecture in the gamified environments of Ingress , Strava, and Pokémon Go transforms quotidian spaces into playful ones by way of motivating playful behavior. These applications do not have their own spaces outright; they merely alter the purpose that each player has within their previous space. While the physical context of the space still exists, that space cannot sustain players without embedded game mechanics.

In reality, gamespaces are spaces where the possibility of gamification exists. Because play can take many forms, it stands to reason that at any point, it can be monetized as a motivationoriented resource. Ingress , for example, is very close to a game. Without surveillance and locational data mining for simulation, it would merely be a gamespace. Locations, like the dog park, would be decontextualized in the service of self-referential play. However, Google's aims exceed self-referentiality – the spaces where nodes are placed are strategic. They are monetized, surveilled, and interface-oriented. Gamespaces expand and shape extractive architectures where ludic connections are formed. Gamification (re)actualizes already existing connections in favor of play – i.e., space is converted and then expanded upon in favor of playful interactions. Ingress and Pokémon Go both convert everyday social interactions and movements into context-driven actions. The new contexts in spaces that host gamified mechanics are gameplayoriented, such as collecting resources or competing with friends for check-ins and badges. However, gamification also channels play toward nonludic outcomes – in short, gamified applications continually use data generated through gameplay to produce capital and inform real-world decision making. The game mechanics that harness play as a state of being (e.g., surveillance) are also spatial mechanics that aid in reworking quotidian space into gamespace. Strava, for example, is a social biking gamified application that relies on aesthetic, simulated space to thrive. Its playful interface aggressively reframes the player's riding experience via seduction and ludic framing. Trevor Ward (2014), a cycling blogger and selfidentified “Strava cycling addict,” states gamification irrevocably altered his cycling experience via game mechanics. Ward (2014) states, I discovered one of Strava's many clubs. I could join and compare my performance against other members. I should have just ignored it, and continued as before. Stupidly, I didn't, and too late I realized (sic) that my regular, innocent fix of data about my day's bike ride had actually been a gateway drug to something far more

addictive – a big, shiny league table in which the position of your name is determined by how many miles you've logged. Usually as competitive as a cabbage, I suddenly wanted to be top of the league. Now, instead of merely uploading my data, comparing it with the previous day's and then logging off until my next ride, I have become obsessed not just with my own performance, but those of the other 60-plus members of the club. Specifically, Ward cites mapping his actions in coordination with others led to a new perspective on his hobby. He was able to track his progress by monitoring other players' times via lateral surveillance. This live mapping process encourages riders to modulate their behavior based on the location-based digital information tagged by other players. Players also create narratives based on the frames generated by locational information, which is, in turn, generated via play (Dovey & Kennedy, 2006). Both perception and narrative contribute to the overall design of Strava , a crucial example of why symbiotic architecture is necessary for gamification. Without gamespace, Strava and its hybrid riding spaces cannot exist. Playful, competitive hybridization changes both the act of cycling and the everyday spaces in which cycling occurs via recorded movement through gamespace. Like all gamified hybrid spaces, Strava embodies the possibilities inherent in gameplay by leveraging space. As a gamespace, it also models how capital is produced via playful mobility. Strava straddles both simulation and gaming in a manner that utilizes space, self-archival, digital rewards, predictive mechanics, and competition to produce a wealth of information about biking cultures across the globe. Inevitably, Strava also increases the predictive capacity of consumer simulation based on spatial data: Where people bike, what groups of people bikes together, the demographic stratification of these groups, the equipment they share with the app, and the general daily social habits that identify Strava players as “bikers” are all integrated into a massive database. Some of these data are fed back to bikers, allowing them to monitor themselves and others, but most of it is used to improve the

predictive capabilities of the system. Updates and patches may be internal (for instance, providing new mechanics based on users' usage patterns), but they also can reach much further than the application itself – patches alter both social behaviors and spaces. Like other gamified applications mentioned, Strava can provide a wealth of targeted locational and personal data on individual bikers and small, location-bound groups. In turn, Strava also creates and manipulates the social mechanisms these groups operate by bringing Strava to the forefront. Thus, it also retains the capacity to change the spatiality of these groups by altering the use of the software and how space is represented digitally and physically. For Strava , Pokémon Go , and Ingress , location is inseparable from identity – in the collective map created by these applications players embody a ludic, monetized social space. Without players actively creating, exploring, and differentiating gamespaces, games and gamification cannot exist. One significant ideological aspect of gamification is that play should be an “everyday” state of being – people construct gamespaces and their identities within them as they go about everyday life. Everyday spatiality is a vital component of gamification's use value – the charted movement of virtual–actual bodies and entities through space-time serves as the basis for biopower (Foucault, 2007b), simulation (Pias, 2011) and the “uneven spread” of capitalism itself (Harvey, 2006). Gamified spaces like Strava have modified gamespaces – they are spaces in which play has the possibility of occurring. Also, like gamespaces, they are spaces in which play is actualized. If we apply this to gamification's conceptual grounding, “life-as-play,” then all spaces are possibly digital gamespaces, and all digital gamespaces support (possible) monetization schemes. Gamification and games both have a part to play in reframing everyday spaces. Both rely on gamespace, and gamespace relies on the contextual actions of players. However, while games can be free, gamification requires that gamespaces produce constant capital through play. Gamespaces converted from quotidian spaces are the result of gamification's efforts to spatially harness desire, design, and simulation. It is the conventional mortar that holds the bricks of mechanics, logics, and players together. Players rely on mechanics.

Mechanics, in turn, rely on the continuity of gamespace. For example, Ingress augments quotidian city space with resource nodes, which must be controlled by players. These nodes previously existed in physical space: they are monuments, statues, restaurants, and dog parks. However, their quotidian meanings are altered by Ingress' mechanics, which subsumes locations into a battle for resource control. Ingress' seductive architecture creates a social space where players find context in movements and actions contextualized by the ludic interface. In turn, these contextual movements fuel Google's advanced simulation, which creates capital. Gamespaces rely on seduction to motivate players, forcing them to adjust to constant changes in the gamified environment. The more players adjust, the easier it is to predict how adaptation is possible. Like Nimbi , gamification seeks to create an unbeatable game out of everyday life, one in which the context and results are forgone conclusions. The drudgery of play in this manner is not apparent to players, who experience something new with each play session; however, to those with the ability to see the bigger picture, gamespaces produce fertile grounds for seductive, productive, and profitable extractive architecture. However, games are also selfreferential in their future-mindedness. Once a finite game ends, the process resets. Gamification does bank on finite manufactured futures; it strives to create a reality that accounts for any possible future enacted through gameplay. In a counter-logical fashion, gamification uses game mechanics to divest movements and spaces from quotidian origins to better predict the paths that everyday life produces. Ingress , after all, is an exploration in predicting how and why pedestrians move in the ways that they do, and Strava seeks to account for the collective behaviors of bikers.

Conclusion This chapter explored how gamification alters, frames, and constructs gamespace through extractive and seductive architecture. It also proposed that gamification creates a living, monetized gamespace that works to harvest and monetize data. It utilizes two

primary methods: seductive delight imbued via the gamified interface and dataveillance of gamespace. It also draws from movementoriented games like Spacewar. Because of its focus on producing capital, gamification is a sly extractive interface. Gamification's debt to delight and aesthetics is skin-deep. Using an interface to embed game mechanics into everyday spaces motivates players in performing certain behaviors. At its core, gamification uses a GUI to help guide living players into active points of data. Rather than stubborn interiority, the hallmark of finite games like Spacewar , gamification generates knowledge and power by altering everyday spaces into gamespace. Gamification's ability to colonize quotidian space in favor of data marks it as a possibly dangerous technology; at the same time, the discourse surrounding gamification rejects force and domination. One thing is clear: Gamification only survives via the movements of players. In the next chapter, we will look at the shared techno-centric philosophies that drive gamification and surveillance capitalism. While this chapter has been focused on the extractive architecture of the interface, we will delve into the history of execution architecture – game theory, computation, and simulation. Gamification's logics are found in the general mandate of game theory, that a universal set of formulas (or algorithms) can standardize analysis of human behavior. 1

Pong is a generalized term I will use to refer to a number of early ball-and-paddle games created for cathode ray tube (CRT) monitors, not just the popular Atari console version of the game, which used a TV as a replacement for a CRT monitor/oscilloscope. The first iteration of a Pong-type game, called Tennis for Two , was created in 1958 by William Higinbotham (Donovan, 2010). It was created as a marketing ploy for the US Department of Energy. 2 Similarities between games studies and architectural studies have been noted. Aarseth (2001), in his essay Game Studies, Year One , states “Like architecture, which contains but cannot be reduced to art history, game studies should contain media studies, aesthetics, sociology etc. But it should exist as an independent academic structure, because it cannot be reduced to any of the above”. 3 Visual computing refers to any type of computer that uses nontextual visuals to relate information (Fichtner, 1999). Visual computers include any computational device that has a visual readout that can display more than text or code. 4 For example, his interest in gaming led him to help produce a portable computer that predicts roulette outcomes and his research into artificial intelligence involves chess

(Jorgensen, 2009). 5 Shannon's research actually precedes and informs Tobler's law. Tobler (1970) developed the law in 1970, while using computational simulation to predict the population growth of Detroit. It was Shannon's work on missile guidance systems that enabled modern geographic studies, which makes heavy use of GIS/GPS. 6 Appropriation, in this context, simply implies that while the overarching category of “computers” stays the same, their social uses vastly differ from scientific and military uses (Fichtner, 1999). 7 Ingress is a key example of these mechanics – players move based on the distribution of nodes in their area. They attempt to triangulate connections between nodes that will harvest the most resources for their faction. 8 Agent-based modeling involves imbuing cells, or cellular automata, with certain properties and then observing how the CA navigate and interact within a simulated space (Gilbert, 2008). It is the precursor to advanced geosimulation tactics (Itzhak & Torrens, 2004), game design (Gilbert, 2008), and modern, digital architectural design (Parisi, 2009).

Chapter 4

Histories of Gaming and Computation A young scholar named Herbert Simon was working for the International City Manager's Association in Chicago, studying for a career in systems and administrative management. It was the 1930s, and he was concerned that, despite the superior organization structure of governance, people's behavior was “messy” and against self-interest (Heyck, 2008a). The people of Chicago kept electing mayor Edward “Boss” Kelly, whose government was “maximally corrupt” (Heyck, 2008a, p. 45). It was a problem that intrigued him: Why did seemingly well-designed social systems and institutions fail to produce good results? Why did the actors within these systems work against their own interests? Simon's dogged pursuit of practical problems of governance and reform eventually led him to an even more profound paradox: how can we create orderly systems of control while also respecting individuality and freedom of choice? At the time, efficiency experts believed the issue was a crisis of rationality. The answer was to seek out and instill a universal theory of rationality that could “judge” the decisions of human actors (Heyck, 2008a). Human beings are inherently rational actors and, given a chance, will always make good choices in their own interest: a corner pillar of midcentury capitalist economic theory. Simon, however, saw it differently. Rather than sticking doggedly to the idea of universal rationality (especially regarding self-interest), he aligned himself with the emerging field of sociology, specifically a young sociologist named Talcott Parsons (Heyck, 2008a). Parsons

believed that a “voluntaristic theory of social action” was needed to explain how social systems and institutions shaped the values and choices of their collective actors (Parsons, 1954, 1999). For a system or institution to succeed, people had to give up some autonomy willingly. In turn, the system also needed to inspire confidence in a positive outcome – people need a controlled environment that encourages mutual values and desires. Inspired by this insight, Simon proposed that rationality and decision-making were bound to the amount of information available. The ability to process this information sets the bounds on decisions. Simon (1947, p. 79) writes, “It is impossible for the behavior of a single, rational individual to reach any high degree of rationality…Individual choice takes place in an environment of ‘givens’ – premises that are accepted by the subject…behavior is adaptive only within limits.” What results is a sense of “bounded rationality.” The novel idea that humans need complex systems (and effective design) to aid in making rational choices drove Shannon into the abstract territory of artificial intelligence (AI) and behavioral simulation. Later in life, Simon would become a pioneer in cybernetics. With Alan Newell, he developed a theorem for simulating human problemsolving behavior (Simon & Newell, 1970). Alongside Alan Turning, Claude Shannon, and Norbert Weiner, Simon's work marked the beginnings of our current obsession with simulation and modeling. Oddly, Simon had no background in computation. How did he make the jump from studying human behavior to machine cognition? The answer lies in difficulties of designing for optimal control. The best way to ensure a theoretical system works is to test it. Proper test design protocol for social behavior is to use a trial with actual subjects. However, this is impossible with large-scale social or economic institutions. The best way to ensure that the contingencies work, Simon determined, was to simulate the human subjects (Simon, 1969; Simon & Newell, 1970). That way, all design factors were known before the protocol “went live.” For that to occur, the computers needed to think and learn on a human level. Today, the paradox between control, freedom, and behavior continues. Game and software design teeter between enablement and constraint, setting up contingencies and choices that lead to

desired outcomes. They do this because they act as interfaces, the connection between users and much larger technical systems. Games, uniquely, also respect the ability of a player to make choices. The early philosophies of cybernetics, tensions between control and freedom, still drive gamification's design ideology: how do we ensure voluntary submission to widespread extractive architectures? Thus, providing choice architectures that herd and nudge users toward desired (and predicted) end-states ensure better outcomes. Simon's belief that modeling collective behavior is necessary for a stable society drives the logic of surveillance capitalism. After all, correct predictions are the best outcomes in the “behavioral futures” market. The histories of computation, simulation, and AI have been wellcovered, and this chapter will not retread that ground. I focus on how the theories and ideologies that drove early work in computation also form the basis for gamification. The last chapter explored the material history of gamification, such as radar and the CRT monitor. This chapter focuses on gamification and computation's shared theory and ideology. The chapter begins with exploring social theory surrounding simulation, and how that theory closely aligns with the current status of our “algorithmic culture.” Then, it excavates the oftoverlooked roles that games played for the technical advances in early cybernetics. I examine game theory's “dream” of a unified theory of human behavior. The collapse of this dream is essential, as it introduced the need for evolutionary simulations like Game of Life. Finally, the chapter shows how evolutionary game theory gave way to living simulation, which requires the constant surveillance of everyday life. I explore the links and similarities between current gamified applications (e.g., Pokémon Go ) and simulations like Game of Life . First, we will begin exploring the roots of algorithmic culture and the precedent of simulative control, one that uniquely fits gamification's primary aim.

Simulation and the Algorithmic Sublime Herbert Simon's use of bounded reason to propose that technology could sustain humane systems of governance that provided a

balance between control and freedom. A deep fascination with simulation marked his interests. During his most active years in cybernetics research, simulation had also caught the eye of historians, sociologists, and psychologists (Cubitt, 2001). These parallels between early simulation theory and the current state of surveillance capitalism are of note. Both technologists and their critics focused on games and play as aspects and advances in modeling and simulation. Sean Cubitt (2001), who wrote one of the only histories of simulation theory, points out that play and games play perform a role in the work of simulation theorists such a Jean Baudrillard because of their role in bourgeoning systems of prediction and modeling (Cubitt, 2001, p. 133). Excavating these relationships will illuminate why gamification is a natural result of computation: it moves simulation from the abstract to the everyday through seductive game mechanics. Gamification is one result of the shift in values that occurred during the midcentury boom in cybernetics research. This shift primarily comprised the growth of information technologies and their large-scale effects across all social and economic arenas. In 1951, as computers moved from war-based tools to research instruments, a Canadian historian named Harold A. Innis proposed a radical new view of human history. Innis proposed that society, economics, power, and culture were all determined by information. Communication technologies and flows of information could provide an account of human history. Innis focuses his analysis on “mediums” of communication. For Innis, society progresses through the transportation of information shared and stored. He states, “A medium of communication has an important influence on the dissemination of knowledge over space and time…We can perhaps assume that the use of a medium of communication over a long period will to some extent determine the character of the knowledge to be communicated” (Innis, 1951, pp. 33–34). Information, in turn, creates a “pervasive influence” that will “create a civilization in which life and flexibility will become exceedingly difficult to maintain” (Innis, 1951, p. 34). Innis argues a medium of communication (e.g., the move from oral cultures to written cultures) has a profound psychological and social effect on people; the resulting changes in a

culture increasingly shift the social burden onto technological mediums. In turn, societies become increasingly immersed in a realm of abstraction and information. He saw this move away from grounded, natural communities as a weakness, noting that is everything becomes datafied, reality become increasingly negotiable (Cubitt, 2001). 1 Innis' focus on communication and technology as determining factors of social conditions would spark a range of other theorists to explore the impact of information technologies on Western culture. At roughly the same time as Innis, Claude Shannon (mentioned in the previous chapter) was also delving into the meaning of information as an operational function of both computers and society. Like Simon, he believed that improvements in technology could bring about improvements in society. However, he was primarily interested like information: what constitutes information, why and how is it transferred, and to what degree does the mode of transferal effect its impact? While working at Bell Labs in electrical engineering, Shannon was attempting to solve a vexing problem. Shannon has just finished his research on applying the symbolic algebra of mathematician George Boole to network architecture and switches within those networks. Shannon's calculations would be the first iteration of Boolean logic in a network-oriented setting. The use of telephones had rapidly expanded in the postwar years, and human switchboard operators were overwhelmed. Shannon had figured a way to build a more functional and efficient network, but there was one problem, a decidedly human problem. Bell could not hire enough of switchboard operators – people were just too expensive. In 1949, Shannon and his research partner Warren Weaver created a mathematical theory of communication, one that would allow them to automate Bell's network and make human operators obsolete. Later, this same functional theory of information would also open the gates for modern computer networks, as it also forms the basis for the logic switches gates of contemporary computers (Cubitt, 2001). However, it is doubtful that Shannon foresaw the impact that his theory of communication would have on nontechnical fields. The theory developed a vocabulary widely used today to describe information transfer: sender, encoding, signal, channel (or

medium), receiver, decoding, and noise (Shannon & Weaver, 1949). Shannon and Weaver (1949) argued that the nature of the channel did not matter so much as the signal-to-noise ratio that the channel provided. The lesser the noise, the more precise and powerful the signal. If a signal is optimized, there is less need for “redundant” elements (Shannon & Weaver, 1949). The social impacts of such a theory were immediate: humans became redundant in telephonic networks. As fallible agents, humans were the source of the noise. Shannon saw his theory as a practical problem, just like Simon. However, the idea that information can be measured, evaluated, and optimized has permeated the thinking of fields well beyond the purview of electrical engineering. For example, his theory of information influenced cognitive psychology, where the mind was reduced to a mechanism of informational transfer signaling the end of phenomenological approaches to the human experience (Cubitt, 2001; Gleick, 2012). This proposal that the mind is an organic computer still lives on in modern neuroscience, alongside the theory that the mind can one day be subsumed into a computer. Shannon and his contemporary Norbert Weiner can be seen as a starting point of “the information age,” when everything – our biology, our environment, and our culture – can be converted to information and, as a result, be modeled and manipulated (Gleick, 2012). Of course, as Shannon also noted, information can always be optimized. It was this idea of infinite “optimization,” and its consequences, that caught the eye of historians and social theorists because it disrupted the traditional Marxian analysis of capital. As computers rapidly advanced, thanks to the field of cybernetics and information theory, more scholars begin to note the possible fallout of computation and automation. The first change noted was how the human pattern of buying and selling changed. As production became a question of technology, the concept of a “commodity” also shifted. Marx (2000) originally defined a commodity as an object whose value was determined by the labor market. In the classic model, the amount of human labor determines the value of the commodity. He believed that production and consumption formed the foundations of capitalism. Of these two processes, production has traditionally been the most studied. However, as automation becomes the primary

mode of production, commodity and value also take a second form focused on consumption and expenditure (Bataille, 1991). As natural resources dwindle, the traditional commodity-based economy described by Marx becomes problematic. Value gets caught up in a “general” economy, which includes not just humans, but the availability of energy (Bataille, 1991). These relatively recent changes shift cultural focus from production to consumption. More importantly, human populations are reconceived as consumers rather than laborers. This concern with consumption also begets an interest in guiding and controlling commodity. As computation and AI handle the logistic ends of production, systems of control become focused on consumer behavior (Baudrillard, 1981b). Modern technology reduces the amount of human labor that goes into creating commodities, so our culture becomes driven by the second form of commodity value: playful expenditure, waste, and destruction (Cubitt, 2001). This realization marks the core of simulation theory: the circulation of information and objects form the basis of our society and social relationships. It is here that simulation theory becomes unique in its own right, thanks to Jean Baudrillard, who also felt that links between commodity, consumption, and information lay at the heart of new technological developments (Cubitt, 2001). He notes that postcomputation, information had become a commodity as opposed to an abstraction. Baudrillard writes that, as our society becomes more and more obsessed with collecting, arranging, and valuating information technologies, it becomes a series of “ludic and combinatorial” practices (Baudrillard, 1991b, p. 108). What used to be spontaneous social exchanges become increasingly surveilled and codified, resulting in a society that relies almost exclusively on technology to drive its culture. The Consumer Society , written in 1970, theorizes culture itself increasingly becomes a recursive “play on forms and technology” which replaces more stable modes of interpersonal sociability and cultural creativity (Baudrillard, 1991b, p. 102). Play is essential because it provides a way for people to make sense of all the information and objects thrown at them while still maintaining the possibility of resistance, a point which comes up in later chapters. Baudrillard believed that computer code is a language

devoid of poetics or aesthetics, a set of protocol arranged around efficiency and functionality. He states that play, because of its arbitrary nature, is the only mode of resistance to the “universal programming of language” (Baudrillard, 1996a, p. 93). Play sits at the center of the consumer society as an arbitrary force, one that can promote servitude or resistance. The move from production to consumption set into motion a domino effect of technologization, causing a social and cultural obsession with computation and media. Systems of consumption accompany increased reliance on technological objects and computation. As such, the society becomes reliant on code – a set of predetermined functions and forms that ensure no unknowns exist (Cubitt, 2001, pp. 43–44). Baudrillard points out “no revolution is possible at the level of a code…” (Baudrillard, 1991b, p. 94). Everything must adhere to a predetermined model. In short, a technological society is one where simulation is no longer optional, one that must index and predict all possible outcomes to create a standard set of cultural forms. Baudrillard (1996b) states, “As directly experienced, the project of a technological society implies putting the very idea of genesis into question and omitting all the origins, received meanings and ‘essences’…it implies practical computation and conceptualization on the basis of a total abstraction, the notion of a world no longer given but instead produced – mastered, manipulated, inventoried, controlled: a world, in short, that has to be constructed” (p. 28). He saw this obsession with building data inventories and automated systems of control as a paradox: as our objects become smarter, we become more reliant on their construction of our reality. Baudrillard (1996b) argues that automated systems degrade our humans' ability to interact with one another; rather, the social sphere becomes replaced by a “system of objects” that serve to grant us identity, meaning, and language – things that used to rooted in our relationships with others. Automation and computation operate through logics of functionality: so long as the object functions, its existence is justified. Baudrillard argues that functionalism breeds systematization. New objects create new issues; new issues need new objects. Thus, the system of objects obeys is self-propagating. Whereas an organic

society orients itself around people, functionalist societies orient around instrumentality, technicity, and efficiency. Baudrillard notes that “functional mythologies” concerning automation are negatively depicted in a dystopian light (e.g., science fiction's trope of robotic rebellions). Despite these myths, we still submit to functionalism. He states, “the machine, so far from being a sign in our present civilization of human power and order, is often an indication of ineptitude and social paralysis” (Baudrillard, 1996b, p. 126). As computation and functionalism intertwine, we risk more and more of our social agency. Furthermore, a technocratic civilization is “at once systematized and fragile” (Baudrillard, 1996b, p. 132). A single catastrophic failure in one sector could cause a total collapse. Accusations of dramaticism always follow Baudrillard. Still, his fears were partially realized in the 2008 global financial implosion. A wave of disaster unhinged the Western economic and social machine; it was an implosion driven in equal parts by greed and blind spots within the models generated by complex economic simulations. Baudrillard wrote The Consumer Society and The System of Objects when computation only applied to scientific and business applications. They are remarkably prescient and formed the basis of his later work on simulation. During the 1980s, as home PCs and game consoles spread across Western households, Baudrillard (1983) issued one of his most famous (and misunderstood) warnings: “Reality no longer has the time to take on the appearance of reality. It no longer even surpasses fiction: it captures every dream even before it takes on the appearance of a dream” (p. 53). In Simulacra and Simulation (Baudrillard, 1981c), he made a broad statement that simulation had, at some point, “replaced” reality with a type of “hyperreality.” Our culture was becoming obsessed with fantasies and possibilities while ignoring mounting problems. As culture becomes immersed in the repetitive forms of media and code, it is increasingly unable to determine actuality versus fictionality. Baudrillard's definition of simulation noted that the decaying state of our world was of less interest than media; we would instead map and recreate different versions of ourselves and our environments than deal with physical and social realities. He

sums this up by stating “the territory no longer precedes the map, nor does it survive it. It is, nevertheless, the map that precedes the territory” (Baudrillard, 1981c, p. 1). The focus on information encourages a world where there was no interest in present actuality. We focus instead on representations of actualities and, like a predictive map, indexes of possibilities. Our technological society has morphed into a simulated one, where “there is more and more information and less and less meaning” (Baudrillard, 1981c, p. 79). Baudrillard's take of simulation is compelling, and play's sense of irreality and impermanence stood at the center of his analysis. However, Baudrillard also failed to operationalize his theories with clear definitions, relying on wordplay and aphoristic writing. Those scholars working alongside him, specifically Gilles Deleuze, would bring simulation theory a set of clear definitions and examples. One key issue with Baudrillard's take on simulation is that he fails to define reality . As such, he is often mistaken for a Platonist, believing that there is an idea, absolute reality, and media technologies are somehow ruining it. I assume that Baudrillard, who pulls from Innis, refers to “reality” as a spectrum. On one end is the total reality of the animal and prelanguage human, who cannot express abstract concepts like “the self” or “the past and future.” In the middle is the “literate human” who can engage in abstraction as a mode of thought and language. Finally, there is the “technological human” where technologies generate abstractions. Still, these lacking definitions are troubling. Gilles Deleuze, who worked in the same period as Baudrillard and was familiar with his work, offered up a more operationalized definition of simulation in a social and metaphysical context. As such, when I refer to “simulation” as a concept, I am predominately working on Deleuze's interpretation. Deleuze wished to overcome the Platonic trope of original versus copy, a hallmark of essentialism and representationalism. 2 Deleuze suggests that simulation does not question what is real, but rather the simulacrum “is not merely a copy or a false copy…it calls into question the very notion of the copy…and of the model” (Deleuze, 1990, p.294). Plato distinguished between “copies” and “simulacra,” stating that copies are well-grounded close to the real, while simulacra are false copies (Smith, 2006). 3 Deleuze rejects that

simulation is a falsehood opposed to pure reality. Instead, he argues that simulation represents a category of being, unique from representation (Smith, 2006). Rather, simulacra are based on difference. Rather than being a lesser representation based in sameness, “simulacra are those systems in which the different relates by means of using difference itself” (Deleuze, 1994, p. 299). Deleuze states that, in simulation, there is no “prior identity and internal resemblance” to an original reality (Deleuze, 1994). Simulations are real in their own sense, based in the tension between what is possible and what is actual. In other words, simulacra are locked in a cycle of differential tension between what could be and what is. They attempt fidelity, sameness, and truthfulness concerning their “origin”; however, unlike copies, they “internalize difference.” Simulations are moving, changing, and growing (Deleuze, 1994). Humans, because of limited vision, note outward simulacra's similarities to the “real” thing or process but simulacra have their singular internal logics, giving a differentiated state. Simulations plumb processes so massive that humans cannot maintain perspective; simulacra use repetition to model the impossible and to see whether ideas and processes may become possible. In this way, they are “superior forms” that make sense of a chaotic world: “the difficulty facing everything is to become its own simulacrum” (Deleuze, 1994, p. 67). Simulacra, for Deleuze, are iterations of the virtual and the actual . The virtual is untamed potential and desire (Deleuze, 1994). Reality is not a stable or homogenous entity which can clearly be distinguished. It is embodied by differences that repeat over time, creating new iterations of the world. The “world,” in this sense, is imminent: a never-ending repetition of “potential” realities and “actual” realities (de Souza e Silva & Sutko, 2011). The fact that ideas and systems can become reality shows the predictive capacity of the virtual to influence and determine new aspects of reality over time. The actualization of virtuality is a process of differentiating potentials into multiple instances. For example, in their exploration of mobile and augmented reality application, De Souza and Sutko (2011) point out that mobile technologies are prime examples of the virtual-actual cycle. Data-oriented spaces and simulated systems are

embedded in the realities of users as “location-aware technologies can be perceived as manifestations of potential structures” (de Souza e Silva & Sutko, 2011, p. 33). For a more specific example, let us say we are using Google Maps to find our way across an unknown city. Maps aggregates locational data pulled from a variety of sources to provide a simulation of the city's highways and byways. Through Maps' interface we see roads, traffic, and landmarks, all of which we must trust exist in carne . Trust in the simulation based in our desire to get to our destination, as we cannot just “think” ourselves to the spot – we have to move our bodies through space, thus actualizing our desire. So, our idea to take the fastest route out of multiple options (possibilities) motivates us to access a structured iteration of the virtual via simulation. We choose one possible route out of the many that Maps differentiates for us, and then act on the decision, navigating to our destination. Of course, Google also has its own set of desires; as you drive, they collect your data (virtualizing your trip) to add to their collective simulation of all vehicles moving through the city. Maps is an easy example of how Simulations works as an active segment of virtuality. It is, of course, simulation's influence on the world around that concerns simulation theorists. Deleuze (1995) also noted that with the advent of computation, the world was shifting increasingly toward “control” of rendered possibilities, warning against “ultrarapid” and “free-floating” forms of control that impinge on everyday life. The philosophical history of simulation as a concept flows directly into the ideas proposed by Simon and Shannon, new forms of “humane” control providing an effective simulation of free choice, all while driving toward absolute efficiency. Despite the concerns of twentieth-century thinkers like Innis, Baudrillard, and Deleuze, computation continued to expand beyond the war machines, laboratories, and business mainframes into the homes and, eventually, hands of individuals. However, their concerns remain valid: how can we, as a culture, stay committed to free will and personal development if we increasingly rely on objects and computational processes to shape and guide us? What was once an abstract concern of theorists is now a pressing concern; almost all of our environments are now simulative to some degree.

While arbiters of reality and truth used to be institutions, we now are experiencing interface creep. Our everyday understandings are rooted in the applications we use. Gamification, as it were, is the spoonful of sugar, the pleasurable submission to the instrumentality of surveillance capitalism and the control society.

Simulative Dataveillance Simulation theory, especially the Deleuzian variety, notes that behind all visible, physical processes there are internal inconsistencies and differences – a homogenous exterior does not belie an orderly, systematic interior. There are vast networks of informational processes linking together as the social, technical, and biological level. Simulation is unique among these practices because it provides glimpses at the possibilities inherent in these heterogeneous assemblages. These glimpses formulate their own set of realities, ones that can (perhaps) be actualized. Dataveillance and algorithmic culture lie at the crux of this transition from possible to actual. They provide the data needed to design systems that can nudge simulations into actualities. My earlier example of Google Maps, in which a simulation of highways helps to actualize a person's route, is a simplified example. We must think beyond simple applications to a complex of extractive ecologies. Bratton (2015) notes that the Stack is rife with connection points between the user, the simulative interface, and the world. All of them serve to expand the influence of the technical assemblage making up the Stack, itself. Users make up the base layer of the Stack, living beings caught up in the increasing flood of information. However, as Bratton (2015) points out, users are not born – they are actively formulated by design. Bratton uses Foucault's genealogies to illustrate the process: the human body is abstracted, labeled, and then a system is produced to optimize that body's productiveness (Bratton, 2015). So, while users may form the base layer of the Stack, they are living beings needing to be progressively labeled and optimized. This optimization starts at the interfacial layer: “an interface necessarily limits the full range of possible interactions in a specific and arbitrary

way. Any interface…must eliminate or make invisible a whole range of other equally valid possible interactions” (Bratton, 2015, p. 221). While Foucault (1977) noted the large institutions (for example, the church and the state) employed techniques of discipline to optimize the bodies and lives of individuals, the advent of the simulation society places that burden on the interface, which serves to wield information as a loose but effective form of governmentality. Baudrillard's grand statement that the map precedes the territory is only partially accurate. In our current age, the information precedes the action. For interfacial layers to effectively herd, nudge, and seduce users, there must be some sense of internal logic to their design. Jean-François Lyotard (1979) called it the logic of performativity – or the precedence of data. Lyotard (1979) is perhaps best known for coining the term “postmodern condition,” which argues that science, knowledge, and truth are increasingly the product of “language games.” For whatever reason, scholars often overlook him in the study of technology and media (Gane, 2003). Lyotard contributes a great deal to simulation theory. He contends that computation or any related informational system breeds a dangerous obsession with optimization. The danger grounded in the sciences move toward social control. Lyotard asserts that “the true goal of the system, the reason it programs itself like a computer, is the optimization of the global relationship between input and output – in other words, performativity” (p. 11). In short, what is legitimate is optimized, and what is optimized is also legitimate – a Moebius loop of truth. Performativity is the wanton commitment to reduce systemic entropy by inputting the least energy for the highest return; in other words, “optimization” (pp. 11–12). So, an action is not worth taking if the simulative data say otherwise. Lyotard argues that performativity is a cultural technique of power resulting from our current sociotechnical infrastructure, which (almost) exclusively relies on technology to advance legitimation and efficiency: By reinforcing technology, one “reinforces” reality, and one's chances of being just and right increase accordingly. Reciprocally, technology is reinforced all the more

effectively if one has access to scientific knowledge and decision-making authority. […] Thus the growth of power, and its self-legitimation, are now taking the route of data storage and accessibility, and the operativity of information (Lyotard, 1979, p. 47). For Latour, information technology mobilizes the production of power and legitimation; restructuring the deployment of troves of data serving as the vanguards of techno-legitimate truths. Performativity notes that data determines action and not the other way around. Because there are data, and therefore potential optimization, there is value and meaning. In the information age, everything must perform . If we explore modern concerns with algorithmic culture, we can see that “truths” are performative – operationalized and the fed back to users, resulting in the creation of a society and culture driven by algorithms.

Algorithmic Cultures The terms “algorithm” and “algorithmic culture” have shown up a few times in this chapter, and I have yet to operationalize them. Historically, simulation theory has focused on broader terms such as “computation” and “information.” For modern thinkers, algorithms have become a primary focus on how users navigate their sea of interfaces. The key concerns are (1) what cultural functions algorithms perform and (2) how do these functions embed systems of social or cultural control? We should start by explaining what algorithms are. Ed Finn (2017, p. 15) points out that “algorithms are everywhere…They already dominate the stock market, compose music, drive cars, write news articles, and author long mathematical proofs – and their powers of creative authorship are just beginning to take shape.” They revolve around computation's ability to operationalize, optimize, and arrange information based on user inputs, a process of “programmability” (Chun, 2011). However, algorithms go beyond mere inputs or commands, they represent a system of automation – a driving force behind simulacra. Finn (2017, p. 17) states: “An algorithm is a recipe, an instruction set, a

sequence of tasks to achieve a particular calculation or result, like the steps needed to calculate a square root or tabulate the Fibonacci sequence.” For computer scientists, algorithms are an innate logic of computing; for mathematicians, algorithms are the logical steps from getting from point A to point B (Finn, 2017). But what about for social theorists? The implementation of an algorithm is “never just code: a method for solving a problem inevitably involves all sorts of technical and intellectual inferences, interventions, and filters” (Finn, 2017). The inferences and filters are not apolitical, as “many of the most powerful corporations in existence today are essentially cultural wrappers for sophisticated algorithms” (Finn, 2017, p. 20). Algorithms encompass a world view, one where all things can be “in place.” In an algorithmic world, a human must use “tacit” negotiating tactics to navigate algorithmic systems; we change the ways we speak, write, travel, and interact (Gillespie, 2014). However, at the core of these changes is the sense that algorithms lead to unbiased, machine-aided decisions. To return to our Maps example, perhaps we already know a shortcut that bypasses traffic, a way not included in the simulated routes presented by Google. Would we second guess ourselves, assuming that Maps presents a more unbiased opinion based on information to which we do not have access? The act of getting from one place to another becomes a process of second-guessing ourselves in the face of algorithmic truth; our lives become performative, always oriented around the possibilities extracted from data. Maps has the option for you to program and upload your secret route, extracting knowledge to add to its own. Finn (2017) notes that this situation, the “cathedral of abstractions and embedded systems” follows a computational history based not in rationality, but desire : the desires of technologists to arrange and optimize the informatics of life into a nonbiased, machinic system and the desire of users to make life a little less chaotic. We want the answers ; we want everything to be accessible, fun, and interactive. The principle of design is to make everything more user-oriented, more connective. By extension, of course, we must become users. This twofold set of desires is the basis of “algorithmic culture,” a natural outgrowth of performativity and simulation. Ted Striphas

(2015) notes that algorithmic culture is the process of offload social, material, and emotional tasks onto technology, changing the most basic definitions of what defines “culture.” It is the combination of what Gillespie (2014) calls “sociotechnical” assemblages aimed at optimizing and automating everyday life. Of course, algorithmic culture begins with (and continues to revolve around) games. It is no secret that the mass public's first taste of “the interface” was the computer game. Alexander Galloway (2006) notes that games and gaming are harbingers of our present “algorithmic culture.” Gaming comprised a two-fold wish to be in control of certain things while also eschewing actual consequences. Possibilities are much more fun when their actualities do not get us killed. In games, I can freely act on the contingencies presented to me. I will not die. I have to, in gamer slang, “get gud.” Soon I will be fully instrumental in the ludic system, a master of contingencies. Galloway (2006) states, “We were born here and love it. Short attention spans, cultural fragmentation, the speeding up of life, identifying change in every nook and cranny – these are neuroses in the imagination of the doctor, not the life of the patient” (p. xii). Gaming centers on the redefinition of social realism from representation to action, a process of playing meanings rather playing with meanings. Galloway (2006) points out that formerly, information, text, and visual arts required users to “perform the act of looking” while video games (and all digital media) seduce the user into “performing acts.” These new relationships with information, knowledge, and meaning also present new forms of control, which lies at the center of both user's and designer's desires. Games present us with a model of control that is difficult to resist: if we internalize the logic of the system, then we can achieve more, do more and, inevitably obtain more freedom. I have spent many years playing games, and the higher my power level, the more I can accomplish. Levels that were locked away become available, plot points are unveiled that bring new understandings. The more I internalize the logic on the game, the more I can accomplish. It is a process of faux self-actualization – a personal simulation of the top point of Maslow's pyramid of needs. Galloway (2006) argues that games present an “allegory of control,” one that involves “playing the

algorithm” (p. 95). In gaming, the first form of control is learning to navigate and acknowledge contingencies; the second is internalizing them so that you can expand your actions. This push–pull cycle is the center of gameplay. Games offer a control allegory that favors expansion over confinement. Deleuze (1998) states, “A control is not a discipline…you do not enclose people but instead, multiply the means of control” (p. 18). Moreover, so, we see how games can operate as valid control systems: they merely multiply the contingencies available (the means of control) to simulate freedom of choice. Freedom through control is the root of gamification's impact on social and cultural processes. In the last chapter, we saw how games quickly followed material advances in computing such as radar, missile defense systems, and the CRT monitor. Games also formulate the precedents of modern computing. If simulation, performativity, and optimization are the hallmarks of our current society, then games – or more accurately, game theory – illustrate their direct antecedents. Game theory sprang from mathematicians' and cyberneticists' collective desire to create optimized functions that predict and simulate human and nonhuman behavior at the algorithmic scale – from precomputation to the advent of the personal computer, their focus honed in on allegories of control.

Game Theory's Universal Player In this section, we catch back up with Herbert Simon, who moved from Chicago to the Carnegie Institute of Technology (Heyck, 2008b). It was the 1950s, and he had begun to work on combining two formerly distinct fields: the science of choice (game theory) and the science of control (systems theory). However, while social science was interested in how to design human systems of control, the science of computation had also moved forward significantly. Part of this expansion was systems design; which solved problems of networking and communication within massive technical assemblages (e.g., Shannon's work with network switches at Bell Labs). As machinery morphed in computational componentry, thinkers in both electrical engineering, biology, and psychology

suggested the human brain and the computer were not just similar but could become interchangeable. Simon believed that this combination formed vital concepts at the beginning of the cybernetics boom: (1) organisms and computers are both behavioral systems that shared a “functional language” and (2) system behavior, like social behavior, is driven by choosing alternatives within a given set of contingencies (Heyck, 2008b, p. 54). This allegory would have far-reaching consequences for both Simon and society as a whole. In the last few chapters, we explored the material advances of computation and the impact of games on their development. In this section, we will explore how these two critical concepts outlined by Simon collided with games to birth the living simulations of surveillance capitalism. Years earlier, in 1944, a book was authored by John von Neumann and Oskar Morgenstern called Theory of Games and Economic Behavior . The New York Times “blandly” introduced it as “a mathematical investigation of economic theory, social organization, and games” (Erickson, 2015). However, the reviews failed to capture the ideal behind von Neumann and Morgenstern's work: they believed that their idea, named “game theory,” could provide a universal set of formulas for the study of human choice and behavior at the micro- and macroscale. Both believed that game theory was a “triumph of mathematical science” which “might bring the study of society out of its present dark age and into a truly scientific future” (Erickson, 2015, pp. 1–2). Their ideas were grounded in social science; they were also formulaic and algorithmic, “fluent in the language of computers, man-machine systems… manifestations of Cold War high technology” (Erickson, 2015, p. 2). Game theory, at the time, was envisioned as a “new enlightenment” on how society could think and act rationally; it rapidly infected techno-corporations, universities, and the military (Erickson, 2015). Its creators intended it to be the final solution to problems of choice and organization in the social realm. In 1944, they could not have imagined its impact on computation and simulation. However, the signs were there all along. Game theory was born from “set theory” and axiomatics – both areas of mathematics also inspired and enabled the first computation

systems, imaginary devices such as Charles Babbage and Ada Lovelace's “analytical machine” (Gleick, 2012). Specifically, set theory focused on board games, such as chess, and how to obtain winning positions in a finite set of moves, allowing a player to “force” a win (Erickson, 2015, p. 35). Von Neumann sought to model all possible outcomes of a game while also forcing the best possible outcome given the circumstances. He noted that the psychological state of the player was of no consequence, nor did it matter what player was better: the game was indifferent to both (Erickson, 2015). Rather, what was important was managing chance, which would always make a “spontaneous appearance” (Erickson, 2015). He notes that chance in an intrinsic part of the game and “life itself” (Erickson, 2015). Managing it would bring about a revolution in systems of choice and control. Game theory's philosophical aim to chart all possibilities while ensuring optimized outcomes made it attractive to military research institutions, most notably RAND (Research And Development), a think tank formed by Douglas Aircraft to aid the United States Armed Forces (USAF). By the late 1940s, a large percentage of the staff consisted of game theorists (Erickson, 2015). Simon found his way to RAND's Systems Research Laboratory in 1951, where he caught his first glimpse at the combination of computation and simulation. Game theory advanced considerably while Simon was there, primarily focusing on utilizing game theory to determine “Military Worth” (Erickson, 2015). It is worth noting that Weaver was also at RAND during this period and helped perfect systems theory for the USAF based on game theory. The seemingly otherworldly convention of primary cybernetics thinkers at RAND revolved around the problems RAND was working on: “the interrelationships between power, trust, and knowledge in social interactions – seemingly overcome in the theory of the two-person zero-sum game – would emerge persistently” (Erickson, 2015, p. 113). For example, the first known example of “programming” emerged in the context of machinic systems. In the 1940s, Air Force budgeting was a “daunting” task involving vast bureaucratic systems which seemed unmanageable with purely analog technology (Erickson, 2015). The budgeting process needed to be optimized and automated using

punch-card programming based on game theory. Mathematical models captured the functional processes needed to calculate and enact an optimized budget (Erickson, 2015). The calculations were carried out by early computer mainframes, and this contact with computers and games led to an explosion of activity by cyberneticists, engineers, and mathematicians. Von Neuman helped to link the issues of budgeting and the process of games, suggesting that the two issues were “analogous” (Erickson, 2015, p. 97). Shannon, meanwhile, worked on radar and missile defense systems, using game theory to aid in target acquisition and threat analysis (see Chapter 3). At the same time, Simon was interested in the interactions between “human–machine” systems designed to enable “experimental investigations into the nature of communications and decisions-making.” He explored interactions assemblages of humans and computers (Heyck, 2008b, p. 55). Simon wrote, “The secret weapon that…I had access to a digital computer, and an idea – derived from contact with computers – that it could be used as a general processor of symbols” (Simon, 1991, p. 111). These collective research studies aided Simon's conclusion that the mind, the organization, and the computer had all become collective “behavioral systems that processed information to solve problems” (Heyck, 2008b, p. 50). This basic idealism persisted throughout the 1950s, as evidenced by cybernetic literature. Humans and computers were the same; the human mind was a biological computer than was capable of melding completely with a machinic system (Cubitt, 2001; Gleick, 2012). This set of beliefs was propped up by the rigid bureaucracy of the USAF and the initial mathematical success of game theory. Trouble was on the horizon. The absolutist claims of game theory failed to live up to expectations when applied to everyday processes. Economics was the first of the social sciences to attach itself to the dream of Game theory; its basic tenet, that all actors are rational actors formulated the basis of Rational Market Theory, based on Simon's concept of bounded rationality and Game theory. It held sway in economics until the 1990s, crumbling over repeated and unexpected market crashes (Fox, 2009). Simon's vision of a control system based on computation-aided rationality would prove

impossible to achieve. However, another branch of the social sciences also latched onto the promises of gamic logic and gamebased analysis: social networking. Here, our focus on Simon and cybernetics ends, and the focus on true gamification begins. In cybernetics literature, scholars like Norbert Weiner and Claude Shannon focused on cybernetics as a system of information exchange, feedback, and networks of knowledge and decisionmaking both human and technological (Erickson, 2015). However, von Neumann saw a more nuanced picture of game theory and cybernetics that connected to social exchanges and strategy, driven by a priori rational actors. In 1952, RAND started up a specific program to explore “behavioral sciences” called Program V (Erickson, 2015). In its six-year existence, it made an indelible mark on the future study of social interaction. At MIT, Kurt Lewin established mathematical models of social interaction based on topographical formations: closeness, space, shape, and living spaces (Erickson, 2015). These theories of social interaction and group behavior would be rooted in set theory, a branch that heavily informed game theory. Lewin's work inspired Duncan Luce, a young graduate student, to become interested in mathematical solutions to social formations in 1953. Luce was one of the first scholars who would start viewing the mathematical variations of social networking, specifically the communication patterns in small groups, research funded by RAND (Erickson, 2015). The goal, eventually, was to produce behavioral models that could predict possible networking patterns that form through social groups. To do this, he had to abandon traditional formulations of game theory required rational actors; the higher the complexity of the group, the more rationality broke down. At MIT, Howard Raiffa adopted Luce's research; their work became theoretical, but it did provide a blueprint for later, largescale behavior modeling programs and shows an early symbiosis of game theory, games, and social networks in regard to simulation and modeling (Erickson, 2015). Games and Decisions , Luce and Raiffa's book, determined that traditional models of game theory were inaccurate at modeling complex social behavior. They influenced Herbert Simon, who agreed that game theory's rational actor could not account for complex social behavior (Erickson, 2015; Simon,

1958). Simon shared Luce and Raiffa's pessimism on the traditional game theory to contribute to a complete “theory of human economic and social behavior” (Erickson, 2015, p. 160). Simon (1958, p. 343) states that Luce and Raiffa correctly demonstrate game theory's difficulty with significant social and behavioral models; he states “my own hypothesis is that the theory rests on a fundamentally wrong view of the human decision-making organism and the nature of rational choice.” Simon, as we know, believed that decision-making was embedded in the psychological conditions of the information environment. After Games and Decisions , game theory emerged from theoretical confines to laboratory settings in an attempt to solve the issues with so-called rational actors.

The Collapse of Rationality Simon's work in behavioral simulation and cybernetics was unique. He believed, along with other scholars like Luce and Raiffa, that traditional game theory would need to be altered and optimized to provide an accurate model of complex social behavior. He believed that behavioral modifications would need to be environmentally based on access to information and choices (Simon, 1969). Optimal human behavior and decision-making could only be simulated or actualized through designing the proper control system. Simon believed that the mind was an “information processing machine” not unlike a computer, and as such it could be, in a sense, programmed to respond appropriately to optimization through environmental conditions (Simon, 1969). His 1969 work, The Sciences of the Artificial , completed his work in cybernetics. He took his experiences with Newell in behavioral simulation and applied them to design. Specifically, Simon noted that the evolution and behavior of animals involved structured tasks over time, which led him to note that designing behavioral systems (simulated or otherwise) is like computer programming, a set of hierarchical tasks. This emphasis on examining animals and precursors to human behavior is unique in early cybernetics literature, but also decisive. By the 1960s, the concept of a priori rationality had fallen apart: what looked good in theory did not translate to practice. This insight came from observing

human gameplay. Perhaps rationality in humans was “bounded,” as Simon suggested, and could express itself in the right environment. The Cold War's distinct irrationality influenced behavioral research in the 1960s. Scientists were intrigued by the strategic moves made by the United States and the Soviet Union; the Cold War was undoubtedly a series of “games.” However, neither actor seemed rational. Strategically, both parties were caught in the Prisoner's Dilemma, where they seemed to be betraying their selfinterests by not cooperating or seeking equilibrium. Furthermore, both nations were also playing games of Chicken , in which one steered on a collision course with the other, seeing who would jump out of the way first. Could game theory's concept of rationality be tweaked to provide a template for world peace? The answer lay in how groups of people (not individual actors) navigated the rules of a game. Scientists decided that the best course would be to observe group behavior to produce models, rather than rely solely on mathematical theory. During the late 1950s, at the University of Michigan, Anatol Rapoport began to test how groups played and responded to different games – a set of observations that led to applying game theory, decision-making, and social network analysis (Erickson, 2015). His work followed Simon's presumption that groups symbiotically learned to navigate rules by forming internal structures. The human experiments by Rapoport echoed early AI tests by Claude Shannon, who had built a maze and a small rat-like robot. Shannon wanted to determine if machines could learn rules like an animal, echoing the behaviorist tests of Pavlov and Skinner. The rat seemed to be able to “remember” and “learn” from the maze, which had a series of electrical relays that told the rat where it was (Gleick, 2012, p. 250). As noted later, it was not the rat that was learning where the maze was, but rather the maze was learning where the rat was. The environment was ushering the rat along, providing information at crucial points (Gleick, 2012, p. 252). In short, Rapoport wanted to test how group decisions faired in a series of changing games (like a maze, games also form pathways of branching contingencies). Rapoport noted that living organisms form group structure not just around a set of rules, but also through effort and mutual satisfaction from working with one another (Erickson,

2015). In other words, behavior was a matter of navigating internal social structures as much as external rules. Rapoport's experiments were funded by the Air Force, who were interested in optimizing the “performance” of groups under external stress (Erickson, 2015). He created a game based on the prisoner’ s dilemma with discrete moves and payoffs, then hooked group subjects up to the “Sympar” machine that noted biological signs of stress during gameplay (Erickson, 2015). While results were disappointing, Rapoport noted that observing gameplay presented a new take on game theory; what was useful in observation of the absence of mathematical theory and the presence of human dynamics (Erickson, 2015). His early work on group dynamics, structures, and environments would pave the way for more psychological research using gameplay as a primary testing model well into the 1960s. However, these approaches would prove disappointing, once again buckling under the specter of “rationality” and decision-making (Erickson, 2015). However, game theory had proven a major point: rationality in individuals and groups is far more complex than external or internal environments. Chaos and complexity, it seemed, always rose its ugly head. It seemed that game theory and observations of gameplay showed how irrational humans are, opposite the core tenant of game theory itself. Rapoport's findings revealed that theoretical models and simulations using game theory were, at their core, inaccurate. Yet game theory was gaining traction in another area: biology. This new application was not game theory based on observations of human behavior and rationality. It returned to the production of simulation and models. Rather than simulating rational models, game theory (as Simon surmised) was a key to looking at animal behavior and evolution (Erickson, 2015). If game theory's concept of rationality failed, then why not remove it as a variable, instead of setting up a system of “natural” rules and allowing the players to “evolve”? Rather than focus solely on optimized actualization of positive outcomes, why not focus on possibilities? Why not remove rationality, a central part of game theory, from the model? Game theory without rationality abandoned an essential set of philosophical foundations that anchored early theory. Von Neumann

and Morgenstern's original theory stressed that rational decision is a necessary concept. However, results were not playing out in actual human testing. No design technique or environmental variable seemed to support rational decision-making, bounded or not. However, some of the first biologists begin exploring game theory and simulation to model animal behavior and evolution on a large scale by removing rationality. Erickson notes that, in 1973, “a war unfolded on the pages of the journal Nature .” The war was a simulated evolutionary environment between simulated combatants: “Hawks” pursued a strategy of “total war,” fighting tooth and nail against all challengers. Other combatants adopted more nuanced strategies of “limited war”…the outcome seemed decisive if counterintuitive: the practitioners of “limited war” had survived as the fittest. The Cold War had been fought in nature, and the Hawks had lost (p. 204). The article, “The Logic of Animal Conflict” was the starting point in nonrational game theory: deemed “evolutionary” game theory (p. 204). It led to a surge of interest in how computer shed light onto how animals, based on behavior alone, interacted with one another and their environment. There was no philosophical bent to evolutionary game theory, just simulated animal behavior. Without Descartian baggage, game theory found a new life, one that would heavily impact our current algorithmic culture. What was of interest to biologists was “population” and how animals seemed to find a natural equilibrium without the assumed “benefit” of rational decisionmaking. Erickson (2015, p. 216) states: “For a biologist who focused on analysis of population…it problematic to talk about ‘choice’ and ‘rationality’ in individual (nonhuman) populations.” Interesting philosophical questions arose: who were the “players” in the game of life and death? Can they make choices regarding their social structures, and can they exhibit preference and strategy? Under this guise, the language of “games” retreated and gave way to “optimization,” “programming,” and “regulation” (Erickson, 2015, p.

217). The removal of games and rationality from simulation also formed the primary language of algorithms we have currently. With the advent of evolutionary game theory came a new focus in computing, one that aimed to chart all possible direction life could take. This new mode of simulation inevitably embraced the metaphor genetics: breaking coded anomalies down to their most basic rules and observing them create new structures. Erickson notes that this new emphasis on optimization and programming is the root of game theory spreading back into the social sciences after the failures in testing human subjects. However, it is also important because it reveals the beginnings of Deleuze's (1995) control society: the rationality of logic is no longer a focus. We create enclosures that are “analogical” – control mechanisms become numerical, employed at the level of code, and are focused on “modulation” of environments “like a self-deforming cast that will change from one moment to another” (Deleuze, 1995, p. 4). In societies of control, individuals no longer matter, what matters is the self-replicating code. The birth of the evolutionary game theory is also the beginnings of distributed machine learning: learning based on the constant observation of human language and behavior, to create an ever-changing informational enclosure: a “digital enclosure” (Adrejevic, 2007). It also serves to create new individuals immersed in their own place within the evolutionary algorithm; internalize the rules and contingencies to be an “algorithmic person” which is “defined by a distribution of data, patterns, and interactions scattered across many interfaces.” Much like the Hawks of the first evolutionary simulation, we must adapt tactics and strategies generated through game-like contingencies. Herbert Simon hoped that game theory and cybernetics would provide an enlightened system of governance based on human rationality; however, we seem to be increasingly immersed in gamified enclosures focused on surveillance and manipulation. Games did not necessarily provide a window into beneficent governmentality. Rather, they became computational modes of control. It is ironic, then, that one of the most critical evolutionary simulations to emerge in the 1970s is called the Game of Life . The current state of our algorithmic society creates enclosures where

human experience and choice exist only within “the boundary of effective computability.” Game of Life sought to model the processes of life in simulation: the “spontaneous generation of information, or seemingly living or self-perpetuating patterns” that emerge when contingencies are applied to “living” actors. This new mode of evolutionary computation would spread far beyond the confines of biology. After all, it embodies the goal of cybernetics. As Norbert Wiener (1949, p. 8) states: “To live effectively is to live with adequate information. Thus, communication and control belong to the essence of man's inner life, even as they belong to his life in society.” The crucial goal of cybernetics was tapping the virtual to optimize and control decisions. For cybernetics (and game theory), computation and control would become the lens through which “biological systems, social structure, and physics could be united” (Wiener, 1949) – exploring how humans got caught up in this living game means exploring how the early cybernetic game of life played out and how it directly informs the gamified environments of today.

Game of Life and the Living Simulation If you type “Conway's Game of Life” into your Google search engine, you will a small group of blue cells begin to multiply in the corner of your screen. Over time, they will take over the page, filling it with simulated life forms. Pinwheels, gliders, and guns will live out their digital lives until you exit the page. That Google pays such deep respect to the Game of Life is a testament to how important it is. It is the beginning of evolutionary play in computation, later leading to the same types of machine learning and algorithmic acrobatics that make Google's search engine work so well. However, evolutionary games are not just limited to search engines. They also drive the data-farming and content generation of Facebook, YouTube, and Instagram. Just about every major social network and content provider utilizes some form of evolutionary algorithms and machine learning to predict what user want before they want it. In the last chapter, I noted that material advancements in computing, such as the CRT monitor, allowed visual ludic interfaces such as Spacewar and Tennis for Two. However, these visual

advancements also supported complex simulations. The growth of game theory from mathematics to systems of control was relatively unsuccessful. However, when game theory was combined with evolutionary theory, a whole new mode of simulation emerged, one that focused on the observation and control of spontaneous environments generated by virtual actors. Of particular interest is the Game of Life , a significant precursor to all current modeling simulations, large-scale gamified applications and simulation-based games such as Civilization , SimCity , and The Sims (Aarseth, 1997; Galloway, 2006). Hackers at the TMRC were interested in how humans could interact with software via ludic interfaces. Researchers who created Nimbi were primarily interested in how computers could simulate human players in uncertain spaces, where there are constant choices to make and paths to be considered. However, some mathematicians saw in video games the ability to visualize and predict advanced evolutionary simulations. One such researcher was John H. Conway, who created the Game of Life in 1970 (Itzhak & Torrens, 2004a). As we saw in Chapter 3, AI was a hot topic in the 1950s with Alan Turing and Herbert Simon furiously attempting to impart some degree of intelligent processing to computers by experimenting with mathematical games. Combinatorial game theory, when mixed with the desire to simulate human behavior, resulted in the creation of cellular automata , which acted of their own accord based on rules and contingencies set up by the researchers (Itzhak & Torrens, 2004a). The creation of cellular automata was the first real exploration of spatial simulation, in which computers were used to determine a future reality by exploring combinations of evolutionary events via sets of game mechanics. Hardware capabilities and prohibitive costs bottlenecked research during the 1960s, and public interest in cellular automata declined (Itzhak & Torrens, 2004a). A revival of interest happened in the 1970s, starting with the presentation of the computerized version of Game of Life (Itzhak & Torrens, 2004a). The game, which visualizes self-reproducing, recursive “life” via simple game mechanics, was originally a simple set of rules used to study the spatial dynamics of populations (Itzhak & Torrens, 2004a). Conway used simple rules because the game was initially played via pen and

paper. He settled on two end-states for the simulated cells – alive or dead. Life or death occurred according to three distinct rules based in the spatial arrangement: Cells lived, died, or were reincarnated based on their proximity to living or dead neighbors. For “survival,” the cells had to position themselves between two living neighbors. To be “born,” a dead cell must be surrounded with at least three living cells. “Death” can occur with either overcrowding or loneliness; a live cell can be crowded out by dead or dying neighbors, or it can die because it has no neighbors at all. The simulation game was simple because computational power in the 1970s was minimal compared to today. However, as computation increased, the cells could be imbued with ever-increasing functions and layered with other cells representing different functions. These functions can be abstract (such as “cell type n only ‘lives’ when next to cells of x ‘color’ in sector 12”) or complex (such as “cell type n only ‘buys’ ‘shirts’ of x ‘color’ within y radius of sector 12”). The first rules only have to do with how/when a cell lives or dies within a location. The second rules seek to simulate a location-bound purchase. Pure functions are used to guide the game-like portion of Game of Life ; in other words, they are used to render precise results like shapes and patterns. Complex functions are used to represent realworld social or economic actors, such as an individual with certain traits buying a shirt in a particular area. The digital organisms followed an evolutionary algorithm based partially on game theory similar to Nim (Conway, 1976). 4 The simple rules produced population dynamics that were complex, unpredictable, and often unexpected (Aarseth, 1997). The position and rules attached to the initial cells determine the outcome of the cellular formation, similar to stem cells. However, as each generation forms, the ability of the researcher to predict what life forms will appear gets more accurate, not less. In other words, the model becomes more predictive – even though new behaviors are continually occurring – as the simulation portion of the game becomes complex. Researchers and player can tweak the rules of Game of Life to account for complicated “hard” and “soft” agents. Hard agents represent stable structural agents (such as a building) while soft agents are more unpredictable biological agents (such as humans,

insects, or animals). Both are imbued with particular properties and then “set free” to trace a multitude of interactional possibilities. The purpose of agents is to evoke an emulation of life and death through imbuing a system with agential properties and allowing it to play itself – with the results of the game recorded and then sublimated to actualized physical-spatial designs. Game of Life became a spatial simulation that plays itself with some input from the user. It demonstrated that replicating and predicting unique forms of life formed from cells following simple sets of game mechanics was possible and practical. By watching larger patterns as they coalesce over different generations, each cellular construct in Game of Life can be accounted for before it forms . In other words, games produce predictable results, even when the agents themselves are unpredictable. Gamic interaction is the basis for agent-based modeling. Making sense of big data is dependent on game mechanics and the algorithms they produce – the algorithms produced by combinatorial games are the basis for heuristics, which inform all model-based simulations (Gilbert, 2008; Pearl, 1984). Rather than utilize simulated cells, gamification uses the basic predictive concept of Game of Life and applies it to living players. For example, Strava , Pokémon Go, and Ingress utilize player data to predict where and how users will move in any given situation. They do this by providing hard structural agents, such as the location of resources and Pokémon, and then monitoring how players move to obtain these resources. Following in the footsteps of Nimbi and Game of Life , gamified apps like Pokémon Go seek to create a living set of cellular automata made of players. By recording and tracking player movements, Google and Niantic will eventually be able to better predict human motivation, pedestrian traffic, and customer responses to location-based advertising. This predictive model becomes more accurate as the player base increases, despite the game seeming chaotic. The automata in Game of Life and other spatial simulations form multiagent systems , which deploy variable functions into a simulated space to present the “soft” components of space – i.e., its population of players as represented by cellular automata. Human individuals are represented in multiagent system models as “free agents” that

carry within the function differentiated algorithms that “carry the economic and cultural properties of human individuals” (Itzhak & Torrens, 2004b). Gamification borrows from multiagent systems and cellular automata; however, instead of “cells” imbued with behavioral properties, gamification introduces living players into the altered gamespace of everyday life and then tracks their reactions and movements: Rather than simulating model humans via cells, gamification utilizes actual humans (and their bodies) in a vast, living simulation aimed at producing and predicting protocol. Not only do gamified applications provide the protocol for behavioral efficiency (such as coordinated navigation in the case of Pokémon Go ), as players perform these actions the game is better able to predict future actions based on the same set of mechanics. While Game of Life shares an ontological background with computer games, it does not represent the same ideological or epistemic concerns as computer games (Aarseth, 1997). Game of Life is an example of ergodic literature that requires nontrivial effort to traverse or navigate that text (Aarseth, 1997). Game of Life is a primary example of Aarseth's (1997) notion of “story-living,” a narrative that is somewhat self-perpetuating. While Game of Life will operate by itself once set in motion, it requires the player to define the rules by which the simulation runs – tweaking these rules results in different generations of life forms and ecosystems generated throughout gameplay. Game of Life represents the thin line between simulations and games. In Game of Life , one plays with the simulation, rather than engaging in the simulative process itself. Both simulations and games are referred to as “fictionings of the future” by Crogan (2011). Galloway (2006) refers to historical simulation-based games as algorithmic reformulations of the past. In all cases, simulations and games are only slightly different – one is “serious” and the other “playful.” A game requires constant input in order to create a narrative, while a simulation only needs rules to project probable outcomes. Gamification lies somewhere between the two. The visual and ludic aspects of simulative environments take the forefront of modern design – colorful and playful arrangements make apps more appealing. However, most simulations are not focused on whimsy. They aim to produce accurate results. Conway's game is

not beautiful; it is there to demonstrate mathematical principles. The differences between Game of Life and a traditional game show that games are inherently different from simulations, which are always game-like but do not involve extrinsic and quotidian rewards for play (Myers, 1999). For example, Game of Life was a research vehicle, used to explore beneficial synergies between computation and mathematics. Researchers might be “playing,” but the rewards are not limited to the game itself. Like Game of Life , gamification utilizes recursive evolutionary modeling to harness the predictive capacity of game-based algorithms. It also puts these algorithms to work extrinsically. However, gamified apps are also colorful, playful, and seductive. This includes simulation-type games like SimCity , which tell an algorithmic narrative that is controlled and tweaked by the player. For example, automata-based design methods are often used in historical simulation games like Civilization and city planning games like SimCity . The Sims – a popular cellular automata-based game that involves managing the lives, spaces, and social interactions of simulated humans – has been utilizing mechanics derived from the Game of Life and other explorations of evolutionary AI since its inception at the turn of the twenty-first century. In many regards, the gamification of everyday life reflects the situation of The Sims . Entities that design and implement gamified spaces aim to observe how users, who are living Sims , react in different situations. Living players, who replace the part of cellular automata, are invited to explore and use a gamespace to reap the rewards such as points, badges, content, and levels. Gameplay, facilitated by a ludic interface, is the primary mode of motivation for the cells (i.e., players) to move about in the created gamespace. If enough cells are active, then the formation of new players and their future actions within the gamespace can be predicted over time. Increasingly, gamification is utilizing rule-based environments combined with simulative environments to explore what people are willing to do behavior-wise. Like the Sims, users occupy a clear-cut environment and then, based on directives, perform behaviors. Over time, one can “learn” how the Sims works and get the same result from every game. Game of Life is also the same: when researchers

can learn and modify the rules, they can get the cells to build a variety of structures. The link between Game of Life , evolutionary game theory, and gamification involves designers using gamified applications to learn how human behavior evolves continually within a preset of mechanics. After a while, the human futures market transforms from chaos to predictability – the set of “moves” available leads to predicted social and economic outcomes. In other words, users become the evolutionary cells used to predict and mold future patterns – a living simulation.

Gamification, the Living Simulation In the previous chapter, gamified spatial applications like Pokémon Go work in concert with a seductive, extractive interface to aid in mapping gamespace through rule-oriented movements. The contextual data of tracking player movements through space can also be manipulated via game mechanics, as we see in Game of Life . It represents the opposite end of the cybernetic loop that began by interactive interfaces and surveillance-oriented systems – it is a simulation that produces predictability on a large scale, but on a smaller, cellular level it relies on seemingly random combinations guided by choice. For example, when a player zooms into a small section of Game of Life , the interactions between cellular automata seem frenetic and unpredictable. However, when zooming out, one can see that it almost always produces a predictable pattern on a large scale. Game theory's evolutionary algorithms are what make gamified applications useful to marketers and researchers who collect data from applications like Pokémon Go and make sense of the vast data sets. Gamification relies on seductive mechanics mediated by applications to project randomness to players, thus motivating them to produce the data that, on a large scale, is predictable. For example, players who log into Pokémon Go will see new resources, new players, and new obstacles. The seemingly randomized logic behind cellular behavior in Game of Life represents a direct link to the evolutionary algorithms. Those algorithms, through procedural generation, maintain a ludic simulative environment by channeling

desire and modifying behavior. Game of Life instantiates a visual multiagent system via a ludic interface – an architecture of “choice” and contingency that cellular automata navigate. Collectively, the cells build a dynamic information environment built about a few simple rules. It is a precursor to the “life hacking” techniques embedded in modern gamified architectures such as fitness monitors – it aims to explore and display all options users can take before they become actions. In short, the “algorithmic person” described by Finn (2017) starts with playful virtualities. Games and gamification cannot exist without the biological principle of play; simulation, on the other hand, utilizes game theory and mechanics but exists without play. Rather, simulation focuses on interplay – or the interactions between agents. For example, in Game of Life , game mechanics themselves drive simulative functions of the system. Once set in motion, cellular automata do not stop until they either die out or reach a state of inertia. Humans are not quite as tenacious as automata; they require a reason to interact with hard agents such as game mechanics and software systems. Game of Life is technically a simulation: after the rules are set in motion, the automated cells live and die by contingency. However, gamification relies on the movements and motivations of living users to sustain and change the life of the application's environment through their activities. The generativity of ludic environments is why gamification requires a seductive interface supplemented by tracking mechanisms provided by GIS. Players must be motivated by self-contextualization through play while also providing structured spatial data to the parties funding the gamified system. The recorded results of play in gamespaces often have the same usefulness as a simulation – they contribute to increasingly accurate models of playful possibility. Simulative practices linked to gamification lack outright force in the transmission of knowledge and the modulation of power (Galloway, 2006; Galloway & Thacker, 2007). While coercion may still be present in some forms of control by setting limits on possible behavior, as both Huizinga (1950) and Caillois (1961) have noted, coercion cannot coexist with play. A correctly implemented simulation must freely model all possible futures; coercing variables

in simulation erases the use value of that simulation since it presents a biased view of what might happen in a given time and space (Pias, 2011). Similarly, you cannot force a player to play a game because play cannot survive under coercion. While some games are useful , such as those employed in education, they do not naturally result in play. Force erases ludic action by removing the contingencies needed for playful exploration and free will; force subsequently terminates gamespace, as well. Gamified environments are forceless, affective, and protocological spaces of control, whose result is the production of data for successful modeling. All gamespaces rely on both simulative properties and seduction as modes of noncoercive power, primarily via the architectural processes involved in seduction . Pias (2011) notes that, ironically, the more divested from reality simulations are, the broader and more accurate their models of the “real” become. Simulation needs to be divested from reality to produce a more realistic model because they process reality as integral (Pias, 2011). Gamespaces embody this function; they consistently harvest data that can be converted into future capital. From an evolutionary standpoint, Stephen J. Gould (1996, p. 44) states that simulations, plays, and games are valuable because: Evolutionary potential for creative responses requires that organisms possess an opposite set of characteristics usually devalued in our culture: sloppiness, broad potential, quirkiness, unpredictability, and, above all, massive redundancy. The key is flexibility, not admirable precision. Gamification, through its use of gamespace, thrives on creating abnormal, creative, redundant, and unpredictable actions. It relies on quirky redundancy to track and trace the evolutionary paths of players as they proceed with individuation via gameplay. Altering spaces in favor of desire produces behaviors, but the behaviors are only useful when there is a collective space to contain and contextualize them.

Conclusion The process of creating monetized gamespaces that double as living simulations lies between the seduction of gameplay and simulationoriented modeling and surveillance. Gamespace can produce a myriad of rapid, procedural experiences and affective qualities that make simulations inherently ludic – a Pokémon Go user must find the quickest routes to Pokémon, routes that change depending on the locations and actions of other players. Tactics can be repeated based on the player's mental model of Pokémon Go's map, but even master players do not yield precisely the same results on subsequent attempts to find and link nodes. Gamespaces evoke a preoccupation with the immediate consequences of future actions. Play results general states of being that are attuned to possibility (Dovey & Kennedy, 2006; Sutton-Smith, 1997). Thinking ahead is a requirement for all games, the human players must always be in the process of simulating possible outcomes in order to make a move – not inferring the future probability of an enemy player's movements usually results in a “Game Over” screen. This future-mindedness is the progenitor and result of simulations and games (Baudrillard, 1979). In turn, it also begins to answer the question posed earlier, “why play?” Why use an ambiguous act, so divested from control, for control? The short answer is that play, when harnessed and directed by games, produces useful algorithms (or mathematical functions that use probability to solve problems). Algorithms inform the development of code on computational and evolutionary levels; they power Google searches and control how DNA combine. They form the basis for any successful simulation. Because play produces a beautiful array of algorithms when parsed through game mechanics, it is a perfect technique for driving a living simulation, with players and users acting as models. Living simulations provide a method for gamified app developers to “solve” a problem using gameplay. Essentially, gamification is game theory removed from “theory” and inserted into everyday life. Gamespace provides the context for how and why these algorithms produce behaviors.

In gamified environments, players walk a fine line between simulation and gameplay – a line that gamified applications gleefully appropriate for capital. Baudrillard (2001) saw Kasparov vs. Deep Blue , the famed matches between a human chess master and a machinic opponent, as an exploration into the troubling connections between play and simulation, with the computer opponent doomed to play at the best of its simulative abilities: It could only move based on the best possible future. Similarly, as humans are forced into increasingly data-driven frameworks, life itself becomes a negotiation of extremes used to yield a set of probable futures into the “better” actualities, co-opting the virtual to support the Stack's unique form of governmentality. This chapter closes out the first part of this book, which serves as a history on which to build a deeper analysis of gamification. In the next section, we will begin to explore how gamification plays out in a variety of different settings. The next chapter looks out how people adapt when their environments are suddenly infused with game mechanics, and how gamified environments also look for a sort of evolutionary space that molds everyday life into the flows of surveillance capitalism. 1

It is important to note that “natural” simply refers to preoral existence. Similar to animals, prelanguage humans were connected to and entirely reliant on the natural cycles and the land they lived on. There was no capacity for abstraction, only immediacy of experience. 2 Essentialism assumes that everything has an “essence” or perfect form. Representationalism assumes that all forms of communication are “representations” of a perfect form. I thoroughly reject both. We are our own reality, and our language is our own. Both are always imperfect. Any representationalist analysis is bound to slide into utopianism, dystopianism, or essentialism. This work rejects all three categories. 3 Simulacra is the plural of simulacrum. Plato originally stated that a simulacrum is the “representation” of an idea, object, process, or reality which can pursue either abstraction and distortion or faithfulness and fidelity (Plato, 2015). Simulation, on the other hand, is the task of creating and interacting with one or more simulacra. 4 See Chapter 3.

Chapter 5

Gamification, Power, and Networks Gamification plays with boundaries, especially those drawn between user and interface. It recreates quotidian life, redefining and solidifying ludic experience. The expansion of gameplay from distinct ritual spaces into a seductive context is one aspect of gamification's built-in ambiguity – infinite games, pervasive games, and locationbased mobile games, all seek to rupture the ritualized bubble proposed by Huizinga (1950) through a combination of rules, gamespaces, and technology that diffuse beyond the boundaries of life, education, work, economics, and spaces previously untouched by game logic (Montola, Stenros, & Waern, 2009; Petridis et al., 2011; Stenros, Waern, & Montola, 2012; Taylor & Kolko, 2003; Thomas, 2006). Virality is an aspect of environments incorporating gamified systems – they infect adjacent areas via instrumentality. Perhaps this virality is the use value making gamification a primary technique in surveillance capitalism. Also, by redesigning the relations between user and interface, gameplay lubricates information moving up and down the layers of the Stack. In a sense, gameplay has always been about expansion. Games may be contrived contingencies (Malaby, 2007), but part of the contrivance is that the outcomes of gameplay must be open-ended in the sense that they can travel across boundaries. Many successful games in the twenty-first century are “persistent,” meaning that they combine elements of continuous virtual worlds with external media, including material products, social media, and locational media

(Castronova, 2005; Lopes & Bidarra, 2011; Malaby, 2006). For gamification to work as a surveillance mechanism, a managerial apparatus, or a generative mode, it must be expansive and adaptive – it must be ecological (Fuller, 2005). Gamification, as part of media ecology, implies that it exists alongside many contributing processes and networks which coadapt to one another. This chapter performs two main purposes: it grounds a variety of terms utilized in the next chapters, and it concretizes them with a current example of gamification when deployed in the environment surrounding pets and pet ownership. Covered here are several propositions about the excavation of gamification: that gamification engages directly in relationships concerning power/knowledge, that gamified applications are networks with distinct structures that determine their use and identity, that these networks exist within an ecology of subjects, spaces, and objects, and that gamified design harnesses an evolutionary process spurred on by the desire to play. Each of these insights provides pieces of the framework used to guide the archaeological portions of this project – conducted in the following chapter. As with most insights into gamification, this chapter begins with observations on how recent computer games paved the way for current deployments of gamification. Advancements in computation allow for hyperadaptive virtual worlds (Lopes & Bidarra, 2011). In adaptive environments, designers inject game mechanics into a previously existing environment. Also, rule systems and technologies are responsive, portable, and connective. The shift toward mobile computing has provided marketers and managers with a platform for perforating formerly restrictive spaces. However, the social expansion of gameplay, and leisure, in general, is historically linked with the proliferation of technology (Baudrillard, 1998b, 2005; Debord, 1995). One aspect of modern technoculture is the proliferation of machines that reproduce and combine simulacra and ludic machinations with everyday life (Giddings, 2007a). Seth Giddings (2007b, p. 393) states, The ambivalence of play and games has always entailed their machinations in the persistence and reproduction of social orders and hierarchies…as well as in their

subversion or transformation. The symbolic, the authentic, and play can also be cruel and conservative. It has been argued that the magic circles circumscribing play, separating it from other everyday realities, have been thoroughly effaced in consumer society. Gameplay becomes a commoditized “form of productivity...productive of enormous wealth” (Dovey & Kennedy, 2006, p. 101). Productivity and generativity are two sides of the same coin, a coin that gamification frequently flips. Part of defining a theoretical framework for examining gamification, and the gamified environments it creates, involves a radical shift from stable conceptualizations involving players, gamespaces, and the gaming of culture. Tracing how technology reshapes play requires rethinking how we view ludic activities as positive ethical pursuits. It also forces us to deal with technologies that serve as tools of coding and transmission. Instead of being self-contained systems, applications become adaptive, hybrid “code/spaces” that permeate everyday life (Kitchin & Dodge, 2011). 1 I begin with a consideration of three gamified applications: Games for Cats , Whistle , and Petcube . Next, I examine gamification as a series of procedures that are inherently rooted in knowledge/power dichotomies and biopolitics. We have looked at how gamification acts as seductive and extractive architecture; now, we will see how architecture alters networks of power. Gamified design is part of larger discursive frameworks about space, leisure, materiality, capital, games, and play. I then go on to suggest that gamified applications are situational. As an arrangement of material, digital, and social entities, their form ties to the changeable structure of distributed networks. These networks, be they arranged between pets and their owners' technology or humans and their digital games, adapt to the ways game logics and mechanics reify or disrupt connections between people, technologies, environments, and tasks. Identifying and analyzing a gamified system, or any digital assemblage is an “ecological” pursuit (Fuller, 2005). Media ecology involves tracing the shifting connections between human and nonhuman actors as they modify their trajectories. Fuller (2005, pp.

2–3) states that the term “ecology” is used to refer to media systems “because it is one of the most expressive [terms] language currently has to indicate the massive and dynamic interrelation of processes and objects, beings and things, patterns, and matter.” Media and information – it is questionable if one is truly separable from the other – are vast collections of intensities in which viewers/users/players invest. Media are material and immaterial, ordering, and disordering. In this manner, as the channels through which culture distributes, media in the twenty-first century truly represent a vast, contentious plane of mutually inclusive (although not always harmonious) environments (Fuller, 2005). As a form of design deployed via media, gamification represents a constantly evolving technical pursuit that dovetails directly with the evolution of technical objects, systems, and environments. In the end, gamification's primary concern is the constant alteration of environments in favor of seductive play. Environmental alteration is especially true in the case of gamified pet care technologies, which represent how gamification perpetuates its existence by altering even nonhuman networks for play and profit.

It's Gaming Cats and Dogs The primary purpose of exploring interspecies gamification is to note that any relationship or environment can be gamified. Interspecies gamification also provides a concrete example of just how viral gamification is. Finally, it serves as an empirical grounding point as I develop the theoretical framework around gamification. Humans sometimes forget that play is, as Fink (1968) points out, a primordial pursuit. Play is ambiguous, and it is not relegated to one species alone (Brown & Vaughan, 2009). As a cultural set of practices Fink's “play world” is not tied to the human realm – it is a mode of experience related to raw existence (Elden, 2008). From a biological perspective, play is a world-building activity for almost every mammalian and avian species – animals play to learn, play to build, and play to socialize (Bateson, 1956; Fagen, 1981). Play, for animals, is just as much a social activity as it is for humans. It stands to reason that animals are just as susceptible to gamification as their

human counterparts, with pets being a prime example. Pets can be both players and play pieces. The distinction becomes meaningless when we examine pets as a sort of liminal being on the outskirts of culture – the form and function of pets is a subject category always in play. Baudrillard (2005) states that pets are an “intermediate category between human beings and objects” – they are living objects subjected to a “serial game,” a system of possession that reifies the notion that “everything that cannot be invested in human relationships can be invested in objects” (pp. 95–97). For example, dog and cat breeds are prototypes of modern genetic engineering – selectively bred for aesthetics and utility; breeds are a collectible “series” of animals. More importantly, breeds are also a collection of changeable traits, thus functionalizing the dog into a metamorphic series of parts that can be used. Pets are both tools and companions. Haraway (2003), in her Companion Species Manifesto , points out that in this relationship, pets also alter their humans in a myriad of ways. Despite relationships being reciprocal, pets often receive the short end of the proverbial stick. They are unknowing, and sometimes unwilling, denizens in our structured human environments; they are slaves, antagonists, and collaborators when it comes to humanity. Pets fit into society without ever quite acquiring human capacities. They can be trained, punished, neutralized, and annihilated depending on their ability to integrate into our society. Increasingly, pets are consumers of technology and technologized play – they are both objects of technological domination and users of technological objects. Shock leashes, automatic feeders, Astroturf indoor bathrooms, and automated toys are everyday realities for many companion animals. The expansion of technical gameplay into the animal realm is evidence of the viral nature of gameplay and gamification – pets are generative of data and capital, same as humans. They are also potential users and playthings, a distinction that gets muddied when dealing with gamification. Games for Cats, Whistle and Petcube

It took me aback to realize that my cat enjoyed playing computer games. It was 2011, and I had downloaded the Friskies Games for Cats (now called Cat's Play ) applications to see how well they worked. As my cat played her feline-centric game (which involved swatting at moving objects on my tablet and collecting points), I was surprised that she showed interest in the computer, something she usually ignored studiously. I realized that her life was, for the most part, better for the games. My tablet is equipped with a bright, color screen and haptic responses, enabling her to exercise a repressed part of her being taken from her by (semi)domestication. Long days in the same house must have taken a toll on her, judging from the zeal with which she threw herself at the colorful fish interface of the Games for Cats . What I interpret as “joy” in my cat is one side of the proverbial gaming coin: games are fun, relaxing, and stress relieving. Play is often considered sacred – a safe (if sometimes mischievous) and self-contained exercise of creative, social, and analytical skills. Games for Cats, released in 2011, was a mixture of games designed for a cat's natural hunting instincts (Lacy, 2013). “As we started to see the surge of technology and play and a couple of early videos on YouTube [of cats swatting] after the first iPad launched,” Alison Colburn, assistant brand manager for Friskies, stated: “It dawned on us that it could be great synergy for what our brand celebrates and cats' natural behavior” (Lacy, 2013). Friskies' Games for Cats has spawned hundreds, perhaps thousands, of usersubmitted videos and tens of thousands of downloads (Lacy, 2013). People genuinely like to watch cats play, judging from the amount of cat-related content online. However, animal enjoyment aside, there are deep-rooted questions that arise when we stop assuming gamification is only relegated to a bounded discursive framework, such as the notion it only applies to humans. Channeling Donna Haraway (2003), issues of my cat's “significant otherness” are called into question by gamification. Haraway (2003) approaches relationships with companion species as co-conditioning – one that mediates similarities and differences via a slew of cultural and technological matrices. Through technology, namely a computer game, I have a glimpse into the commonalities of “being together” with my cat. However, those

commonalities rupture when data come into play: the data trawling in Games for Cats net both of us, but only I produce capital, informational and otherwise, for Friskies. Gamification has a way of retooling relationships, making new ludic experiences the focus of the user–interface interaction. The bizarre consumer surveillance of the “cat vs game” scenario becomes ridiculous when I notice that my cat was winning points by playing – as she swatted she accrued a codified, mathematical system of virtual currency she had no way of understanding. However, if she wanted to, she could post her scores online and compete with cats all around the nation. If she were a prodigy, I might have posted them for her. If I wanted to, I could also compete with my cat's lightning reflexes and see how our scores compare. Either way, she wanted the fish – a simulated, hyperreal fish that she will never catch; one that never belonged to her in the first place. I was the one suddenly interested in points and progression, a common hook on gamified design. I also began to notice something strange about Games for Cats . When I downloaded the application, it needed “access to my phone” and wanted to “integrate” with my social networking profiles. At the time, it allowed me to share scores on my cat's behalf. While Friskies promised not to share my information with anyone, they never quite say what they are doing with the data or just how much of it they have. Once a private matter, my cat's playtime became integrated into a network of other information, information about me, my life, and my pet. This information might have allowed Friskies to better understand, through so-called “metadata,” what my consumer identity might be. Potential access to what sites I visit, what products I like, what I browse for, and who my friends are is the price that I pay for my cat's free application. Games for Cats was more than just a game – if it was ever a game, at all. Dogs are also included in the gamified environment. Whistle , a dog activity tracker that attaches to the dog's collar, is also a location-based gamified application for managing human–pet relations (Empson, 2014). As pointed out by Sutko and de Souza e Silva (2008), surveillance often embeds into location-based applications – Whistle is no exception. Currently, Whistle remotely

monitors dogs' activities, allowing owners to check on their pets and map when their dog is active (Empson, 2014). However, the collar attachment's functionality allows for a variety of features, including geolocational services, social networking functionality, and locationbased games. The mechanics of self-archival, goals and points, all associated with gamification, are present. Pet owners can turn their dog's daily life into a series of points, goals, and levels through activity monitoring. Gamified remote access to pet behavior goes further than just activity tracking. Petcube , successfully funded by a Kickstarter campaign, is a cube equipped with a wide-angle video camera, microphones, speakers, a laser pointer, and network connectivity (Brooke, 2013). The cube essentially turns the dwelling place into a pet panopticon; owners can use their mobile device to speak to their pet, activate the camera to observe their pet, and use a gamelike interface with touch screen haptic controls to play laser games with their companion animal. Petcube integrates with products like Whi stle and even Facebook , allowing owners to stream their pet's life and ping their location. Petcube also provides an open API for game and app developers to develop third-party devices and programs with the cube in mind (Brooke, 2013). Once again, as with almost all gamified devices, the Petcube features social connectivity, points, and archival mechanics, allowing owners to record, share, and even compete across social networks. The primary mechanics used by gamified devices and applications – points, archival tools, avatars, leaderboards, social connectivity, location-based features, targeted rewards systems, and network connectivity – are showing up almost everywhere, and they aim to integrate human and nonhuman subjects into ludic, networked, generative spaces influenced by gaming logics. Watching my cat swat at a screen, trying to capture a digital fish for hours is eerily reminiscent of the common scenes of moral panic associated with humanity's complex love for games. Gamified petcare is a far cry from simple radar-based games. It is a common dichotomy, and a false one, to assume digital gaming is a harbinger of either Ray Bradbury's Fahrenheit 451 or Aldous Huxley's Brave New World . Both are two different routes to

the apocalypse, or “gameocolypse,” as game designer Jesse Schell (2010) terms it. We are either numbed beyond oblivion by simulations or too happy to care about consequences. It remains unknown how dangerous gamification can become, given that gameplay is such an arbitrary act. Utopian or dystopian visions aside, the anecdotal kernel embedded in the practice of gaming cats and dogs highlights the paradoxical relationships between player/user, pleasure/compulsion, and production/consumption. Primarily, gamification points to the fact that the expansiveness of play links all beings to structures of power, capital, and surveillance. Life and space have always been harnessed and integrated into disciplinary, social, or political networks. However, game dynamics appear to provide the motivational force needed for populations to engage with surveillance capitalism willingly. Ludic seduction is what makes gamification a desirable outcome for any party seeking to influence, monitor, or categorize populations of coexisting users and players .

Gamification and Biopolitics The first steps in constructing a framework for examining gamified applications like Games for Cats , Whistle , and Petcube , and others are understanding the conditions of their use: the production and modulation of both knowledge and power. Biopolitical networks integrate life, human or otherwise, and space into a set of categorized populations meant to be herded and controlled (Foucault, 1977, 1980, 2007b). However, games appear to provide the motivational force needed for mass engagement with digital biopolitics, beginning with the interactions between users and interfaces. This ludic seduction is what makes gamification a desirable outcome for any party seeking to influence, monitor, or categorize populations of users based on their activities within a gamified space. Gamification works toward the generation of biopower via surveillance that produces modulations of power and knowledge. Biopower is defined as a collection of technologies aimed at managing humans as populations rather than as individuals.

Foucault (1998, p. 140) described biopower as “numerous and diverse techniques for achieving the subjugation of bodies and the control of populations.” Foucault (2007b, p. 1) expands this definition in Security, Territory, and Population : “By [biopower] I mean a number of phenomena that seem…significant, namely, the set of mechanisms through which the basic biological features of the human species became the object of a political strategy…” Surveillance is the primary method used for producing biopower. Biopower fosters life or disallows it to the point of death by controlling knowledge about the body, distributing bodies through spaces, and technologizing bodily functions (Foucault, 2002). The mechanisms used to supervise and control the individuals' bodies rely on discursive formations of the human body as a complex machine. Rather than directly controlling, repressing, or concealing workings of bodies, biopolitical mechanisms strive to constitute and structure perceptual grids and physical routines into bodies by “mapping” them into “place.” Traditionally, mapping occurs through the tactical deployment of surveillance mechanisms such as the “spying” conducted by various governmental departments or, even more mundane, the use of census taking. However, technological trends such as data mining, ubiquitous computing, and social networking have moved surveillance trends away from centralized methods of information extraction to individualized methods of lateral and self-surveillance, or watching others and watching one's self, respectively (Andrejevic, 2002; Whitson, 2013). The digital enclosure measures the bounds by which we are controlled and watched. Gamified environments embed lateral and self-surveillance; however, at the heart of gamification lies the deciding factor of play, which differentiates “player” as a unique subject category. However, extractive architectures rupture the idea that players are innately aware of the rules and can master them. In a gamified environment, players become recategorized as users, creating a split subject category. Knowledge about why users play in a certain way embeds into the mechanics of a gamified application from its inception, and seductive motivational prompts are what lead to knowledge about them.

For Michel Foucault (1977), defining knowledge is largely about defining the power relationships that sustain and embody its various forms. Consequentially, knowledge is what allows us to define and manipulate different forms of power (Foucault, 1977). The power source for gamification, in this case, is the drive to play games – the desire to interact with a responsive system of challenges and rewards, hierarchies, rules, and options. Foucault (2003, p. 139) states that power can only be exercised over “collective subjects who are faced with a field of possibilities in which several kinds of conduct, several ways of reacting and modes of behavior are available.” “In this game,” he continues, “freedom may well appear to as the condition for the exercise of power” (Foucault, 2003, p. 139). An arrangement of “prompts” that alternately steer and interpret user actions, or gameplay, modulates the transition from raw data to knowledge. What forms is a cyclical relationship between playful behavior channeled, in part, via software (power) and the types of information produced and categorized by the users (knowledge). This “knowledge/power dichotomy” is the foundation for a biopolitical mode of governance (Lemke, 2011). By examining the relationships between bodies, social systems, technology, and governmentality, Michel Foucault (2010) argued that scholars could trace, or perhaps excavate, a genealogical history of objects or processes (such as gamification) as they relate to the production of knowledge and power. Gamification has been categorized as an example of governmentality (Schrape, 2014). However, gamification itself does not operate as a distinct material or ideological element; rather, it exists through a series of media-based relationships that contribute to the production of certain types of knowledge and power. Archaeology and genealogy dovetail as methods to explore multiple points of convergence as gamification and related technologies become increasingly visible. As Foucault (1982, p. 219) states, “something called Power…which is assumed to exist universally… does not exist. Power exists only when it is put into action.” For him, power “is not a renunciation of freedom, a transference of rights, the power of each and all delegated to a few” (p. 220). As such, power is positive and it exists only through the applied actions of agents. “A

power relationship can only be articulated on the basis of two elements which are each indispensable,” Foucault (1982, p. 220) states; “the other” is actually “recognized and maintained to the very end as a person who acts.” Power is generative; it does not necessarily dominate or negate: “faced with a relationship of power, a whole field of responses, reactions, results, and possible inventions may open up” (Foucault, 1982, p. 220). For Foucault, power is expansive and universal; for humans, it constitutes domains of objects and discursive truths (Smart, 2000). Power is relative to knowledge; they inform each other. Put simply, power determines what types of knowledge or truths are allowed to exist within a given spatiotemporal point. However, power is not necessarily determinant of knowledge – they co-constitute each other. While power produces certain forms of knowledge, knowledge conditions what forms of power are deployed. For example, Friskies uses knowledge about cat behavior to design and employ their Games for Cats . The games themselves operate as power – a productive force that encourages behavioral results (in this case, play). The power of the game is supported by a variety of techniques, or localized technologies through which power is harnessed, transmitted, or altered (Taylor, 2011). Techniques, 2 in this case, are the materials composing my touchscreen tablet, the code used to create the game, the visual and haptic interfaces through which code is implemented, and so on. Foucault (1993, p. 203) states, One can distinguish three major types of technique: the techniques that permit one to produce, to transform, to manipulate things; the techniques that permit one to use sign systems; and finally, the techniques that permit one to determine the conduct of individuals, to impose certain ends or objectives. That is to say, techniques of production, techniques of signification or communication, and techniques of domination. While technologies such as mobile devices or computers certainly impinge on each of these categories, techniques

conceptually imply many different forms of dissemination such as governmental institutions, laws, personal habits, language, and art. Of course, the example becomes more complex when we expand the picture. Assumptions, or “knowledge,” about cat behaviors are linked to a vast array of institutions that produce scientific “knowing” in different ways. Within these institutions, such as a school of veterinary medicine, power is also present in complex forms – it further conditions what types of knowledge about cat behavior become instantiated as truth and, by extension, what behaviors are eventually targeted by the game mechanics. It also may be the case that the media, which often personify pet behavior in inaccurate ways, also conditions my understanding of cat behavior, leading me to believe that she is “playing” with the application. She may be trying to kill it. In the extreme, killing may be a primary form of play for cats. In any case, my cat's so-called playfulness also produces knowledge about me through the surveillance mechanisms embedded in the application's design. Thus we see that power distributes through a vast array of institutions, people, and technology. It is not reserved for the state, the government, or other “powerful entities,” per se. Power is inherent in a multiplicity of force relations between things, people, structures, and ideas. Foucault (1980, p. 92) states that the analysis of power “must not assume that the sovereignty of the state, the form of law, or the overall unity of a domination are given at the outset; rather these are only the terminal forms of power.” Power relations are exercised over and through human and nonhuman subjects, alike. Power is circulative with knowledge: Truth is a variable sociocultural system of ordered procedures that produces power relations while also guiding and distributing them. In this manner, any iteration of power is an epistemological position. Gamified applications like Games for Cats channels power via networks; however, gamification itself rarely builds a “new” network. Gamified applications represent a reconfiguration of power; they alter networks by changing their form and function in favor of play, or at least playful behavior. Defining certain aspects of gamified applications involves identifying their abstract formal qualities,

charting the relationships they engender, and mapping “surfaces of emergence” (Foucault, 2010) that allow institutions to identify them. Charting emergence requires a search for contingencies rather than causes (Kendall & Wickham, 1999). Gamified applications like Whistle represent a reconfiguration of emergent power, one that is currently unfolding with unknown consequences. From the standpoint of the individual, it presents a biopolitical challenge. Spatially, the surveillance mechanisms embedded in gamified applications like Petcube , with its ever watchful cameras and laser projection capabilities, suggests that the particular reconfiguration of power represented by gamified design is architectural – gamification alters the structure of networks in favor of play.

Gamification and Network Architecture When examining gamified applications and their effect on the production of knowledge and power, it is important to recognize that they do not exist within a vacuum. Gamified applications exist as networks, and each has a certain structural quality that determines its specific use. A gamified application's structural qualities influence how biopower is produced. They exist at the level of architecture . Architecture is typically thought of as the design and implementation of physical structures such as buildings. This is partially correct; however, architecture is also constitutive of networks, and more importantly, their structural qualities. Manuel Castells (2009a, 2009b) states that a “network” is not a metaphor for new social arrangements; it is a distinct spatial form that is defined by the connections it forges between different physical nodes or places. These connections comprise protocols that operate along with the points of interface between different networks. Latour (2005, p. 129) critiques this interpretation, pointing out that “…network does not designate a thing out there that would have roughly the shape of interconnected points, much like a telephone, a freeway, or a sewage ‘network’… It qualifies its objectivity, that is, the ability of each actor to make other actors do unexpected things.” Key here is that networks are not just material or spatial; they have emergent forms that embody connectivity and change. These forms

contain a variety of actors and relationships that are social, physical, and ideological. To be clear, “network” is not a single structural form; in practice networks may have quite different architectures or topologies. In this case, quite literally, network architecture is the formation of different, interconnected spaces. In this context, architecture is also constitutive of different forms of power as it circulates through networked space. Foucault (1977, p. 172) states that at its root, architecture serves “to act on those it shelters, to provide a hold on their conduct, to carry the effects of power right to them, to make it possible to know them, to alter them.” In the context of media technologies and networks, architecture is a form of coded control (Levy, 1997). Thus, architecture, and by extent network architecture , is the totality of structural components, social and material, that constitute networks (Lessig, 2006). Network architecture comprises the formation of networks in both the digital and physical sense. Emphasizing the structural components of gamification as part of network architecture also emphasizes what game mechanics are used and why. Specifically, network architecture is a constellation of agencies, each one supporting, connecting, pressuring, puncturing, undermining, or stabilizing a set of structures. Like a building, network architectures shed and regain identities as time wears on them. Also like buildings they decay and endure, simultaneously. They are modified, added to, and appropriated – they contain everyday life and, concurrently, are contained. These statements may sound abstract, but Latour (2005) frames “network” as a mode of transportation, the movement of meanings that, in turn, creates connections. Networks, therefore, exist as active structural components that objectify themselves through constant movement. Latour (2005, pp. 131–132) states, network is an expression to check how much energy, movement, and specificity our own reports are able to capture. Network is a concept, not a thing out there. It is a tool to help describe something, not what is being described. It has the same relationship with the topic at hand as a perspective grid… we need something to

designate flows of translations. Why not use the word network? The term “network architecture,” when describing gamified applications, should not be pinned down as a single set of things that constitute an object of research or a stable set of statements and actions. It is simply a term to denote the arrangement of structural components within a network. Everything has an architecture, but architectural design and theory figures prominently in games and gamelike structures as the arrangements of gamespace (Aarseth, 1997, 2001; Elverdam & Aarseth, 2007). There is a network, and then there are the structural qualities of the network that take form and, from that, function. Those structural qualities are a network's architecture – their arrangement determines the identity of the network. For example, gamified applications represent a multitude of approaches that share some similar formal qualities. These structural qualities often determine the identity of the application and its resulting use. To explain this more clearly, I return to the example of Games for Cats . We can ask, “What is the architecture of the cat-tablet-gameinstitution network?” There is an immediate list of nodes: the cat, the tablet, the game, the code, the interface, Friskies, and myself. There are also actions: tapping the tablet's surface to catch the fish, plugging in the power cord to power the tablet, coding the application, designing the interface and, perhaps most importantly, laughing at (or maybe with?) the cat. However, in looking at how these all work together, there are some issues. Namely, there are multiple network architectures, and each one implies interconnection with even more networks. The tablet is powered by a complex system of power grids, which links to private/public enterprises, and its components are a collection of high-tech modules created by scientific practice and assembled in various countries. Each of these contingencies contains different power relations, different visibilities, and different surfaces of emergence. Any “master–pet” relationship is a complex one with a unique power dynamic that comes from interspecies relations. While there is no clear network architecture for the multitude of relations that

encompass my cat's playtime, focusing on a single set of repetitions may yield empirical results. When viewed at grand distances, the complexity of a network-oriented approach can be overwhelming. Latour (2005) notes that studying networks is “myopic”; it works best on a small scale, focusing on detail to discern emergent structures. Examining the network architecture of Games for Cats starts with the game and the cat's interactions with it; then we begin to see a clearer picture. In short, the game has a set of game logics – rationales for designing certain contingencies – that rest on the arrangement of individual game mechanics. For example, one logic is to encourage the cat's engagement with the tablet by stimulating the cat's instinct to hunt. The mechanic is a randomly moving object in colors the cat can see. The repetition of action, literally programming behavioral results through the cat-code-game interface reveals a pattern of interactions that highlight the structure of play (i.e., tapping the screen to “catch” a fish) and the underlying contingencies of the situated act produced by a set of mechanics. The design of Games for Cats must follow a set of conditions that allow a game for cats to be made and used by cats. It requires a unique set of mechanics and contingencies based on the instinctual behavior of the cat. The possible contingencies illuminated by the cat's behaviors also reveal a second set of conditions that influence the underlying architecture of the application: Cats may understand games, but they do not fully understand complex technologies. By adding competitive mechanics like scoreboards and versus play, there are also logics and mechanics that aim to engage pet owners. Both of these logics, play for owners and pets, contribute to the overall network architecture of the Games for Cats application, which exploits several heterogeneous motivations and activities to produce pet-based profit through surveillance mechanisms.

Gamified Ecology Identifying the network architecture of an application is only one step in a framework for analyzing gamified applications. It examines the internal structures of the application but excludes the exterior relations with which the application interacts. These external

relations give the application its identity. Gamified applications like Games for Cats exist within a larger environment; they are part of an ecology of subjects, relations, technologies, and beliefs. These ecological interactions produce a wide set of affects, or disturbances, that identify the presence of gamified design when it inserts into a previously existing environment. Myopic scholarship can be effective, but only focusing on minute examples of network architecture – like certain aspects of Games for Cats – leads to an issue of scale. How can we make any generalizations about gamification if we can only look at it as a patchwork series of loosely bound relationships? Gamification – as either life-as-play or a set of design practices aimed at control – has existed for quite some time . However, only now we are viewing its attendant disturbances, such as new modes of surveillance and new ways of enforcing efficiency and control outside of coercion. These disturbances are most apparent when one looks at surfaces of emergence rather than the resulting artifacts. In terms of the artifacts themselves, they are part of an overarching set of relationships. Fuller (2005, p. 2) uses the term “ecology” to refer to this set of “dynamic interrelation[s] of processes and objects, beings and things, patterns and matter.” From the standpoint of media, Fuller states that the relationship between materiality and information has been redefined. What is left is a media ecology that is inseparable from processes such as culture, capitalism, and nature itself. The disturbance in everyday life linked to gamification are ecological processes that represent emerging trends in surveillance and gameplay. Key to the idea of “ecology” is the idea that human and nonhuman actors contribute to an ecology of processes that evolve together (Fuller, 2005). Ecology, in this case, is used according to the most basic definition: the interactions between actors and their environments. Ecology is useful “at a time when objects have explicitly become informational as much as physical but without losing any of their fundamental materiality” (Fuller, 2005, p. 2). It connotes that all components of networks operate with the creation, preservation, and eventual destabilization of an environment, designed or otherwise. These components constitute a material

generativity and affective capacity for the storage, use, and eventual disposal of increasingly large amounts of information. Gamification, as many scholars (Ruffino, 2014; Whitson, 2013) have suggested, directs and controls certain social and spatial practices, but it cannot be viewed as solely structural-functional at the expense of recognizing its complexity. Rather, the architecture of gamification exists through (and helps generate) gamified environments with varying ecological conditions. These conditions are due, in part, to constant remediation (Bolter & Grusin, 2000), in which “new” technologies always contain the residual traits of previous media. Games for Cats, for example, is not a new idea; it has only modified preexisting conditions of human–cat relationships via media technologies. Humans have been playing certain types of games with cats for a long time. If we take institutional knowledge about cats into account, adult feline play is relatively rare in feral cats (Beaver, 2003). Play behaviors are most often associated with kittens, and they contribute directly to learning social skills and hunting tactics (Beaver, 2003). However, housecat play is unique because the relationship between “owner” and “companion species” in the case of felines centers on keeping cats in a social, kitten-like phase for their adult lives (Beaver, 2003). Keeping my cat playful is largely a practice of keeping her indoors, thus ensuring that most of her hunting behaviors are relegated to household objects. My cat has an environment that produces within her an innate knowledge of what to do in situations that she understands. Playing with housecats is only possible through a tightly controlled environment, a technique of ownership that controls the network architecture of the cat's environment – for example, keeping the cat in a hibernative state of kittenhood. I also have beliefs and practices that result from the environments shaping what constitutes a “good” pet owner. I somewhat instinctively treat my cat a certain way. Feline Behavior: A Guide for Veterinarians (Beaver, 2003) even has a subject position for me: The “strong attachment owner,” of which I fall into the first subcategory – the “quality or status conscious owner,” an owner who feels their cat “is an expression of how this owner views himself or herself and reflects his or her good taste, as would other material

possessions.” These owners feel that “the cat depends on them for love, affection, and care, and as a result, the animal is well groomed and only reluctantly left alone” (p. 6). I like my cat, and I treat her well because if I didn't I would be a bad person – at least by my own standards. The environment in which I was raised imparted this to me, and I am only rarely conscious of my actions toward the cat. I am just nice because I would never knowingly be unkind. Part of owning her is playing with her. I would never think of it otherwise. This unknowingness is our collective social network; my cat's environment and my own impinge on each other – they are usually synchronous. Games for Cats , in a way, ruptures this unknowing relationship. It leveled the playing field and, in an odd way, made me more aware that we are simultaneously players and users in a rather seductive game aimed at capitalizing on our reformulated relationship. Technologies of play have evolved much in the same ways for cats as they have for humans. Lewis Mumford (1934) noted in Technics and Civilization that the development of games with the intent of automating play had a distinct role in mechanization, namely creating games that involved interchangeable parts. Cat toys are no different. Toys have evolved from the simple “object attached to a stick” to a hand operated laser pointer. Automation of that resulted in the robotic laser pointer. Evidence of previous technologies and processes are present via skeuomorphs , or “details that were previously functional but have lost their functionality in a new technical ensemble” (Hayles, 2012). The “object” being chased is only present through concentrated light reflecting off surfaces, and the “stick” has been replaced with a more advanced technological ensemble (an automated, randomized machine controlled by a simple computer program). However, many laser pointers still retain the signifying shape of a mouse, the same mouse that used to be attached to the end of the string. Despite skeuomorphism, the automated laser pointer is different because the function no longer requires direct human agency to move the laser. In fact, many models are timer or motion sensor operated, coded to react in the presence of the cat or turning on at a designated interval. Gradually, humans adapt to the implementation

of consistently automated functionality – as long as that functionality still retains similarities with past iterations of pet ownership. Similarly, humans are better able to deal with changing processes and ecologies as long as some internal consistencies remain the same. Technology and life work together, in the case of Games for Cats , within a complex social set of relations that span and connect many divides. However, at each point in the network that constitutes playing with my cat, power and knowledge are generated and exchanged. Superficially, gamified applications like Games for Cats , Whistle, and Petcube do not represent a radical or revolutionary change in either games or pet care. From the standpoint of the human–pet–technology network, interspecies gamification represents a growing interest with automating pet technology. However, when we move outside of this smaller network, we begin to see a change in the overall ecological conditions of pet ownership. In the case of Petcube , owner–pet proximity is changed. In the case of Whistle , which reduces the dog's daily life to a series points, goals, and competitions, the dog's actions become points that denote healthy activity. In the case of Games for Cats , my cat's mental acuity is tested while my information is added to the growing pile of big data. Each change is linked to larger movements for connectivity across the globe. Gamified applications like Games for Cats represent a certain modulation of power within the larger scope of these changes, one that subtly alters ecologies and networks in favor of play.

Gamification and Technogenesis The ecological processes by which gamified applications gain identity, including gameplay, surveillance, and seduction, also sustain their ever-changing uses and forms. The final step in this framework for analyzing of gamification involves acknowledging that knowledge/power, network architecture, and ecological relationships are co-agential in a larger process of change, or perhaps evolution. Media ecology sustains an evolutionary drive that depends as much on the social environment as it does the technological objects that support it. Media is the product of societal and technological

changes, but it also causes them. In other words, media causes and stabilizes disturbances in everyday life. Society must absorb the disturbances of media, and they do this by appropriating and utilizing more media to negate or offset disruptive effects. Doing so, of course, creates more ripple effects which require, inevitably, more media. The co-expansion of media and culture is a result of technogenesis, or “a theoretical framework in which technical objects are also seen in evolutionary terms as repositories of change” (Hayles, 2012, p. 85). The capacity for change is inherent in technological objects themselves. Technogenesis assumes that human attentional and sensorial capacities form via technological environments (a process called “epigenesis”). In turn, epigenesis produces new possibilities for the emergence of “technical beings” through concretization of technical objects and ensembles (Hayles, 2012). Hayles (2012, p. 86) states that “technical objects embody complex temporalities enfolding past into present, present into future. An essential component of this approach is a shift from seeing technical objects as static entities to conceptualizing them as temporary coalescences in fields of conflicting and cooperating forces.” Concretization involves innovations that resolve conflicting requirements within an environment. So, the technics of surveillance capitalism causes disruptions that only new technology can solve. Additionally, as gamification entrenches in everyday life, people will adapt and appropriate it, forcing changes in the design and deployment of gamification itself. Technological environments “produce” humans (and users) in the same manner that humans produce tools. According to Gilbert Simondon (1992, 2007), the tendency to become a single unit is always interrupted as it moves toward an indivisible state. The individual subject is never an a priori supposition. Simondon believes that technics produce individuals. However, this mode of production does not cease; individuation seeks more connections over sets, series, and combinatorial forms. The individual is a repository of potentiality for change – it coagulates fluidities, borrowing from other individuals or sets in the course of an ongoing process (Simondon, 1992). Individuation means that there is no preformed subject or

individual, just a set of potentials that can unfold into a variety of possible forms, networks, or technical systems. So, as much as gamification may produce efficient users and players, these individuals will also alter and change the gamified systems that they inhabit – as potentials unfold, they create new sets of potentials. Individuals do not attain any coded form except in the actual process of unfolding – individuation is this process. An individual is never finalized; within each unit or set, there are always untapped reservoirs of potential for change, alteration, and requirements for unlocking potential. These requirements can be temporospatial, social, technical, symbolic, or (usually) a combination of all factors. Hayles (2012, pp. 88–89) states that concretization: Integrates conflicting requirements into multipurpose solutions that enfold them together into intrinsic and necessary circular causalities… Detaching a technical element from one individual – for example, a transistor from a computer – and embedding it in a new technical ensemble or individual – for example, importing it into a radio, cell phone, or microwave – requires solutions that move the new milieu toward greater concretization… technical objects are always on the move toward new configurations, new milieu, and new kinds of technical ensembles. Technical ensembles…create technical individuals; they are also called into existence by technical individuals. Gamification directly relates to this process, except it uses game mechanics as the primary means of altering the technical ensemble. For example, instead of removing a technical element from an ensemble – like removing a transistor from a computer – gamification removes a game mechanic from a game . Replacing the technical element into a new “technical object” – like placing the removed transistor into a keyboard – would be, in the case of gamification, adding the individual game mechanic to a formerly nonludic network architecture (i.e., pet maintenance). This initiates a

contextual change in the network by introducing game logics into the receiving network. The gamified technical ensemble that results from combining game mechanics and nonludic networks is a gamified environment . Like other technical environments, a gamified environment produces distinct technical individuals. Gamified applications produce users that operate within a specific set of ecological contingencies. Technical individuals also help to produce their environments by altering technical ensembles to suit individual needs. However, the technical individuals also change to fit their new roles within the ensemble. Thus, individuals alternately call into being and are called into being by their environment. While technical individuals can be objects or applications, perhaps the best example of technical individuation is the creation of a “player” that is also a “user.” The tension between these two subject categories is evident in how gamification is treated by ludic scholars. A player is a knowing and willing participant, while a user is decidedly less romanticized. Players are very similar to Simondon's (1992) conceptualization of the transformation of “dividuals” into “individuals.” In different gamespaces players are different characters, objects, and affective forces – still, they (mostly) commit to engaging the required mechanics in order to generate directed, favorable outcomes within the context of the game they are playing. The “being that plays” holds the primary value for exploitation by seductive architecture. Players are the only individuals who can bring “a game” into being. They generate and sustain the logics of a game by playing it. They are evolving with the game while also submitting and diverging from the ludic contingencies. Players are always under construction in ludic environments – their mutually initiated, short-lived identities are only visible during the process of play, itself an endless process of becoming. Players are dependent on the ludic ecology to sustain their identities, and they inevitably evolve within the gamespace. However, unlike an intrinsically oriented game, the player in gamification is linked to a vast number of ancillary networks. The links to these networks must be maintained indefinitely – the gamified player cannot stop playing. The gamified formula becomes a curse: if life is play, then play only ends when life ceases. My

axiom is an extreme example, but it serves to illustrate that as gamification creates new environments geared toward play that embraces the constricted category of a “user” while promising the freedom of becoming a “player.” This tension recreates quotidian environments and subjects in a cycle of technogenesis. Petcube , for example, redirects the idea of pet care away from locational presence, creating a new environment for both the pet and the owner. Former technical ensembles used for pet maintenance may have been a ball or a chew toy deployed in a distinct geographic area. Petcube simulates former “pet toys,” thus creating a new technical ensemble of play. The alteration has direct consequences on the evolution of the pet–owner relationship. Pets may be drawn to the cube because of the stimulus; however, it is difficult to imagine that they relate the cube with their owner. Thus the object alters their former play environment. Owners, as long as they are engaged in play via the Petcube , extend their ability to play in spaces outside the immediate vicinity of the pet. This shift in ecology from immediate to mediated produces effects on both the owner and the pet, shifting the relationships both parties have with one another. Inserting new technics into a media ecology changes that environment and the relationships that exist within it. For example, owners using Whistle may change their behavior toward a dog based on the point-based activity goals in the application. These altered relationships produce further dynamics – the process of epigenesis tied to technics eventually results in altered individuals, though the process takes time. In other words, both individuals and ensembles inform and modulate a series of unfolding potentials where constant evolution sustains the technical process. Skeuomorphic elements, or reassuring aesthetics, cushion any form of future shock related to the unfolding potentialities, yet they only conceal the fact that pet care becomes mired in an extractive web. In Games for Cats , in order to have a critical point of entry for the gamified epigenesis of the cat-play ecology, we should consider a few major technical developments: networked computers, databases, and virtual interfaces. First, Friskies' Games for Cats, as with most gamified applications, is aimed at generating profit. However, rather than shipping individual units, or playthings such as

the traditional laser pointer, Friskies profits through circulating data, namely information about the pet-owning subject. The game collects data through a network and then stores it in a database. So while the game is supposedly free, the gamified environment generates profit via play. One of the key reasons why Games for Cats exists is that it evolves via a technological and social environment that accepts computers and games as “natural.” I never consciously asked what the function of the virtual fish, an obvious skeuomorph, was. The technological ensemble of Games for Cats , itself a gamelike apparatus, was concretized enough so that I had no issue understanding it. To me, the coding was only slightly different from what I do for leisure normally; it was something easily accepted – why would my cat be any different from me? The “object” was on the space of the screen, a simulacrum, but it was still “there” for the cat to play with. However, the extent to which Friskies was data mining my cat's playtime indicates the network architecture differs greatly from the analog model of playing with a cat. In the future, platforms like Petcube and software like Whistle might also evolve into different dog-and-cat-oriented ecologies, each one with different modulations of play and ownership.

Conclusion Pets, so close to us yet so different from ourselves, engage in play much the same as we do. Like our play, their play is ethically variable, situational, and most importantly, economically and socially generative. Pets are monitored and integrated into a networked environment where play behaviors become a form of currency. Activity, engagement, and docility are commended, recorded, archived, and displayed. Houses in which privileged pets and humans share a habitus are machinic playgrounds for humans and owned non-human companions. All ecological changes wrought by gamification alter existing network architectures in a process of technogenesis. Meanwhile, subject positions of both pets and humans are also recast in the process of ludic individuation, enmeshing them in new relations of digitalized biopower.

This chapter explored theoretical concepts behind the changes gamification brings to identities, environments, and circulations of power. In short, gamification offers slightly different opportunities in spaces and subjects, revealing the possibility of different forms of play and players. In turn, play offers an altered set of interactions with our world. Play changes individuals, and in doing so, it creates new ensembles, driving the evolution of environments where it is situated. Gamification utilizes play to set new subjects and ecological conditions. It is important to note that only a select and privileged population of pets will ever experience Petcube or Whistle . While some animals are players by default, others never have entry to the game. Different socioeconomic situations and cultural values can block pets from “playing” in gamified environments. More importantly, pets must produce some type of capital to sustain gamification. While games are expansive, they are also selective. They serve to create series, teams, levels, and rule-bound spaces. Game mechanics are not always inclusive or free, and game logics almost always work toward the goal of clearly defining groups of people for orderly play. While there are always chances for disruption and resistance, being a “good sport” often means playing by the rules for the good of the team, whatever that may entail. The creation and surveillance of players and users make gamification useful and profitable, and technological advances can make gamespaces out of almost any space, object, or being. Play, it seems, is a biopolitical process and gamification makes full use of its governing possibilities in a myriad of ways. These models of selection are rooted in the sorting and governance of populations and, more importantly, bodies. In the next chapter, I argue that gamification seeks a form of governance over bodies that do not play out in a disciplinary fashion. Gamified applications are part of seductive, ludic biopolitics that focuses more on distributed control of players as variable individuals rather than maintaining stable, disciplined subject categories. It changes the game of surveillance and governmentality, shifting the dial away from traditional, centralized governmentality toward seductive protocols. I explore the development of gamified healthcare applications and the protocol that enables them. From the

development of international health protocol, aerobics, and physical education to the wearable networked devices that purport to make players healthier, gamification reveals that epigenesis first requires bodily transformation. In order for individuation to occur, gamification must first stake a claim in the biopolitical governance of bodies. In the next chapter, I examine how the body of the player becomes the focus of gamified surveillance through a modern history of wearable tech. The body, as it engages with a productive negotiation with game mechanics, is the primary generator of gamespace. In the case of gamification, the gamespace houses the network architecture of seductive surveillance and profitable classification. The inner working of the player's body, driven toward progressive efficiency, becomes the primary producer of gamified capital and the primary target for control. 1

Coded spaces are spaces where code is augmenting the space but does not define it; code/space, similar to hybrid space, is a space where removing the code eliminates the existence of the space itself (Kitchin & Dodge, 2011). Hybrid spaces may contain both coded spaces and code/space. 2 Foucault (1993) identifies techniques as technological modes of dispersing or implementing power. Techniques are linked to the Greek techne , or ways of seeing or knowing.

Chapter 6

Gamified Health and Bodies In 2019, wearable tech became a hot topic, as mobile devices added a new component to their ecosystem. Small digital trackers morphed in form and functionality, becoming “smartwatches.” Apple, Fitbit, Samsung, and Google all have fully integrated “smart” ecologies that track the wearer's every move and even heartbeat. This chapter looks at the modern history of these devices, from their military and cybernetic roots to the explosion of self-tracking devices in the mid2000s. As mobile devices grow smaller and more connected, the interface and user levels of the Stack become inevitably blurred, and surveillance capitalism gains access to always-on surveillance of the internal rhythms of human bodies. In this chapter, I explore the synergy between biopower, health protocol, and wearable technologies – specifically health tracking devices – associated with gamification on an individual scale. Biopolitics and gamification work together toward a “quantified self” (Whitson, 2013). I start with an analysis of gamified fitness applications to explore the historical convergence of wearable computing, games, and health protocol. In this first section, I provide a historical overview of wearable computers, fitness protocol, the development of international health protocol, and the use of games in physical education. I suggest that we are witnessing a shift in the ways that bodies are managed, from “massified” bodily fitness to individual digital enclosures that encourage users to monitor themselves for the sake of prizes, points, and rewards. In turn, data are distributed and used by a wide array of parties. Second, I look at

the “Quantified Self” movement and proceed to examine how quantified living, a practice enabled via data-driven health protocol, serves to further biopolitical interests. I explain how movements like “Quantified Living” serve to further ideological support for control on the individual level. Finally, I analyze how gamified technologies and applications enable the player to exist within the event of the game being played, utilizing their own body as a play piece and kinesthetic or biological activity as currency. I argue that the “healthy subject,” formerly a stable part of a population defined by the state, is now a docile body, subject to gamified techniques that bring it into being. I also argue that play, in this case, operates as a mode of technological transferal that aids in the adoption of otherwise contentious technologies largely dealing with surveillance (Elllerbrok, 2011). Most recently, the digital enclosure – an ever-widening range of smart devices with built-in surveillance – is the primary means of extracting useful data from technology usage (Andrejevic, 2007). In this model, top-down surveillance by state organizations is supplemented by lateral surveillance and market research conducted by private organizations. To some degree, denizens of the digital enclosure do the work of watching themselves and others rather than a centralized governmental authority. Nowhere is trend more apparent than the quantified life movement and its catalyst, gamification. While gamification biopolitically operates across many levels, I have singled out the field of health monitors and wearable technology as the most visible examples of biopolitical gamification. Wearable technology is rapidly being cast as the harbinger of an “always on” society, where human bodies and perceptions are constantly monitoring and being monitored by technology (Adrejevic, 2007; Turkle, 2011). The idea of “the self” is posthumanized as the body becomes a functionalized set of pieces or parts (Katz & Marshall, 2004) that can be technologically objectified, modified, modulated, and monitored. Meanwhile, physical education and wearable technologies have respective histories that are intertwined with games and play; however, the standards by which the body is monitored are direct results of decidedly nonludic international health protocol. All of these diverse approaches to biological monitoring

combine in gamified health monitors to produce the ideal “healthy player” and individual whose digitized body and movements feed into a much larger framework of health.

Wearable Technology, Health Protocol, and Games Gamification begins with the creation and maintenance of players as users. However, players in a gamified environment contribute to a much larger set of processes that include nonludic outcomes. One of these processes is the collection and use of data to create more effective customer models for a variety of social and economic simulations (Pias, 2011). Games innately quantify and contextualize players' actions within a (game)space. However, gamified systems utilize the contextualizing mechanics to quantify players' behaviors in a variety of spaces and for a multitude of purposes, including the production of capital. Each “player” in a gamified environment contributes to an ongoing, living social simulation driven by big data. Big data, when applied to the customers, products, and services, centers on the data produced via “everyday life” (Boyd & Crawford, 2012). It is grounded in the idea that more is better and even seemingly extraneous data can be useful in a large context. In this case, everyday life entails basic actions that previously were not subject to intensive surveillance such as spatiality, hygiene, sleep habits, domestic life, family interactions, media consumption, consumer decisions, and daily fitness/health. These are only a few examples. On the individual level, many bodily processes can be gamified, contextualized, monitored, and monetized. Most gamified applications are geared toward monitoring individuals' bodies on a massive scale, and the collection of metadata often targets health. For example, Clue , a reproductive tracker, is an app that tracks women's reproductive health practices, including birth control, mood, and menstrual cycles. Reproductive trackers account for some of the “most used” applications on mobile phones (Steel & Dembosky, 2013), and they usually contain gamified elements. Clue , for instance, offers self-monitoring as a reward mechanic. Self-archival,

in the form of player dossiers, achievements, and inventories, has been cited as effective game mechanics even though they do not constitute or even directly support gameplay (Medler, 2011). Ben Medler (2009) states, “player dossiers should present gameplay data in context to gameplay and provide an interactive system for players to gain insight or enjoyment from analyzing the data…In order for a player dossier system to validate motivations using gameplay data, it must present that data to players in a coherent and meaningful way.” Player dossiers are forms of self-archival that relate personally generated gameplay data back to the user using statistical visualization methods. While some player dossiers only list achievements, showing detailed play data also validates play as a connected series of persistent and meaningful actions. Similar to tallying points to determine a winner, self-archival mechanics push players beyond gameplay in situ . Data persist after games are completed, and contextualize the actions taken after a play session or game is done. In this manner, gameplay data create a persistent, playful presence over many games and play sessions. On trackers like Clue , women can record moods, meals, and notes, and many reproductive trackers also double as fertility monitors. Period trackers involve interactive interfaces, and some also contain a social element. Many reproductive trackers have colorful avatars, emoji-style visual representations, and detailed, colorful interfaces. However, Clue has been praised by users for its no-frills modern interface, which operates more like a playful inventory menu than a young girl's secret diary. Regardless of what design is utilized in creating the “feel” of the application, they are all designed to motivate use: All of the reproductive trackers, Clue included, provide a colorful, longitudinal history of an individual woman's everyday reproductive experiences. They promote selfdriven contextualization via mechanical objectivity. Each reproductive tracker is, superficially, a gamified selfsurveillance mechanism. However, surveillance operates on different levels, and gamification touches on almost all of them. Games naturally involve self-surveillance and archival; however, multiplayer games represent lateral surveillance mechanisms, and the data collected via gamification represent the digital enclosure (Whitson,

2013). Women watch themselves and compare themselves to a normalized model of the reproductive practice, but their data are not their own. Who else does the data go to? Clue , to their credit, acknowledges that the data go toward research at the Max Planck and Kensey Institutes, and Stanford , Oxford and Columbia Universities. Similar to gamified applications like Lumosity , Clue claims to provide some of the largest data sets available for studying women's sexual health and reproductive cycles (Druet, 2018). However, it also reserves the right to share data with any other “third parties,” or what their true profit model entails. According to a study undertaken by the Financial Times , it goes to countless third parties, including insurance companies and cottage-industry “data brokers” whose sole purpose is to collect and market metadata (Steel & Dembosky, 2013). The study showed that almost all of the major health applications, including reproductive trackers, reported data to varied third parties. As Steel and Dembosky (2013) state, “iPeriod will soon have the capability to target ads at a very fine level. So a woman who records in the app that she gets headaches before her period could soon receive an ad for a pain reliever at just the right time of the month.” Other beneficiaries include insurance companies who could use data against people to charge more for coverage of “abnormal” women (Steel & Dembosky, 2013). Women can also participate in social media via some reproductive trackers, and in doing so, they are contributing to the creation of a finely tuned simulation comprised of many women's collective reproductive experiences by also submitting the extraneous social information embedded in their existing profiles. The sample size provided women using reproductive trackers is much larger than any health protocol produced prior to big data. A primary function of health monitors is to supposedly provide a much larger model of health, including women's reproductive cycles (Steel & Dembosky, 2013). Health tracking is generating a large amount of data for many companies so much so that it has spawned a cottage industry of companies to deal with it (Steel & Dembosky, 2013). What is key, however, is how and why people are motivated to participate in the digital enclosure. The answer, in part, is play and

its empowering, surveillance-oriented contextualization of events and choices. Health applications like reproductive trackers contain game mechanics that promise a degree of playful self-actualization. However, this self-actualization is based on previously established standards of normalcy based on internationally recognized health protocol and the use of games in skill-based learning. Exploring both in the context of wearable technologies provides clues to the current configuration of applications like Clue .

A Playful History of Wearable Technologies Mobile health applications like Clue can be analyzed from the convergence of wearable technology and gamified health protocol. Both wearable computers and fitness protocol have roots in the 1960s. However, the popularity of gamified fitness has only gained traction in recent years with the uptick to the wearable technologies market. The development and expansion of the wearable technology market are in turn driven largely by the gaming and fitness sectors. This market turn is no accident. By way of targeting aids and onbody surveillance equipment, wearable technologies like headmounted displays (HMDs) were first funded and researched for predominately military-oriented technologies, an institute with a marked interest in game theory and physical fitness. For example, in 1967, Bell Helicopter experimented with HMDs with input from servo-controlled cameras as part of tests for several early camera-based augmented-reality systems. In one, the HMD coupled with an infrared camera that would give military helicopter pilots the ability to land at night in rough terrain. An infrared camera, which moved as the pilot's head moved, was mounted on the bottom of a helicopter, making the pilot's field of view that of the cameras – in short, the display simulated the helicopter's multi-angled point of view allowing a human to simulate “being” the technology he or she is intended to use (Sennerston, 2010). Fascination with simulated points of view and mobile computation also combined with expanded, external memory enhancements. Vannevar Bush (1945) is the first person documented to mention the serious possibility of augmented memory. “Consider a future device for individual use,

which is a sort of mechanized private file and library,” Bush wrote, “It needs a name, and to coin one at random, ‘memex’ will do. A memex is a device in which an individual stores all his books, records, and communications, and which is mechanized so that it may be consulted with exceeding speed and flexibility. It is an enlarged intimate supplement to his memory.” Wearable cybernetic systems and external memory both provided a technological imaginary that lead toward ever-smaller computational devices. The connection between games, simulation, and the military has been mentioned numerous times (Allen, 2011; Donovan, 2010; DyerWitheford & de Peuter, 2009; Murphy, 2008; Payne, 2012; Smith, 2010; Veen, Fenema, & Jongejan, 2012). Since aviator Alberto Santos-Dumont, inventor of the fixed-wing aircraft, commissioned the first wristwatch in 1907, wearable technology developed from simple chronology to trace the internal and external rhythms of everyday life. Wearable computing devices that aid in both selfquantification and temporospatial tracking generated revenue of over $110 million in 2012 (Walker, 2013). In 2015, the end-of-year projected sales were $1.8 billion for health wearables and $3.1 billion for smartwatches, a new trend that shows a 474% increase over 2014 (CEA, 2015). As these devices became remediated in the form of smartwatches, the sales raised to $5 billion in 2018, with Apple, Samsung, and Fitbit leading sales (Jansen, 2019). The sales are projected to rise even higher as Google also enters the fray. While smartwatches seem to be a new trend, we have been making memory transference, and storage business since Bush (1945) proposed the idea of a desk-sized “Memex” in his article “As We May Think.” Almost inevitably, it seems the history of wearable technology and surveillance collides with gaming at an early stage. In 1966 Claude Shannon, computer scientist and foundational scholar in the field of communication, and Ed Thorpe, economist, mathematician, and game theorist, revealed the first truly wearable computer – a small, hand-controlled input device with an attached hearing aid designed to game the system while playing Roulette. The system was a cigarette-pack-sized analog computer with four pushbuttons. A player used the buttons to indicate the speed of the roulette wheel,

and the computer then sent tones via radio to the attached hearing aid (Thorpe, 1969). Since then, wearable technology, with a variety of metrics for self, lateral, and top-down surveillance, has become a major market player. Cybernetic implants, while still on the research level, have already been pioneered by researchers like Steve Mann (2001), who uses visual implants to augment his vision while also performing individual countersurveillance of his surroundings by recording and even altering them through coded optical inputs that can toy with the UV spectrum. Problems concerning wearable technology where surveillance is rebounded back at traditionally panoptic entities (e.g., corporations, law enforcement agencies, and governments) – a practice known as “sousveillance” – have manifested multiple times in Mann's life. In 2002 his cybernetic gear was ripped out at a Canadian airport, causing him to soil himself (Guernsey, 2002). In a Paris McDonald's, he was reportedly attacked by employees who did not believe that his implants were attached (Biggs, 2012). Once again, his implants were ripped out coining the term “McVeillance” – surveillance policies where people do not have the same right to use monitoring technologies as large corporate or governmental entities (Mann, 2012). Despite Mann's research, industry drivers before the wearable technology consumer boom were mostly gaming, health, and military related (Walker, 2013). Smart clothing, hand-worn terminals, and heads-up displays have been researched since the 1960s. In healthcare, wearable monitors have been in development even longer. The primary difference between older renditions of wearable technology and new “smart” technologies is network connectivity, interactivity, and location awareness. Developing wearable products for the consumer market is an expansion of mechanical objectivity into the biological and spatial realm. In short, the development of new metrics and equipment, such as multisensor combinations, improved batteries, and low energy data transmission (e.g., Bluetooth) has mapped and modulated the schematized internal systems of the body as it moves through space. Soon, harvesting human energy to power devices means the market has room to grow

(Walker, 2013; Xu, Yang, Zhou, & Liu, 2013). In other words, our devices will not only harvest data, but also the body's energy. The mid-2000s jump in wearable technology was due to the original market drivers for the wearable market. These markets were telehealth life monitors and consumer medical devices aimed at geriatric care; scalable sports and fitness monitors aimed at athletes and augmented reality games. Also, funding poured in for industrial HUDs and a host of military applications including the so-called “Future Force Warrior” program which sought to provide “smart” exoskeletons, including fully connective monitoring systems and real-time heads-up displays, to soldiers by 2032 (Walker, 2013). One of the primary market drivers for visualization-based augmentation, or “smart” headgear, is gaming (Walker, 2013). Gamers, or people who game frequently, also have a reputation for early adoption and large install bases. The Oculus Rift , a virtual-reality HMD, is currently available to the public and has seen reasonable crossconsumption between gaming and industrial markets (Walker, 2013). However, the most conspicuous wearable market for the average consumer was healthcare-related, and the most popular devices were gamified. From a historical standpoint, it makes sense – gamers have always been early adopters when it comes to wearable gear. Gaming culture has a long and tenuous romance with wearables. Apart from Shannon and Thorpe's “gaming machine” designed to cheat at Roulette, home consoles have spawned a variety of wearable peripherals. The Switch , Nintendo's current console, features a host of freestanding haptic peripherals such as wireless steering wheels, infrared targeting guns. Before it, the Wii had body sensors such as the Wii Fit sensor board, which measures inertia, weight, and body position for fitness purposes. Nintendo has engaged in creating, promoting, or licensing a long line of wearable products for gaming. The Power Glove , a notorious example of a wearable technology released in 1989, was supposed to serve as a type of data glove that allowed for three-dimensional controls based on hand movements. The Power Glove represents a large collection of wearable, cyborg-esque gaming peripherals developed during the height of eight- and sixteen-bit consoles (e.g., the NES and the Sega

Genesis) such as head-mounted infrared targeting displays and weight-sensitive mats. While Steve Mann may have pioneered the first integrated cyborg headsets for research purposes, gaming culture in the 1980s paved the way for nonintegrated technology that resembles and mimics embedded research prototypes. In the wake of wearable gaming peripherals and the rise of transmission technology like Bluetooth, the market flooded with wearable, gamified products that did not market themselves as “a game.” Nike+ was Nike's move to enter the wearable technology market and represents a complete ecosystem for tracking physical activity through space. A sensor for shoes and sensor-laden wristbands connected to the phones or iPods via Bluetooth. Motion, location, steps, and general caloric burn are measured and logged through a series of algorithms and then translated into activity-based currency. Players set goals, tracked progress, and shared their personal archives. The information was displayed in a personalized mobile panel, hosted on the cloud, which allowed for social connectivity, group challenges, and remote or direct competition. The Fuelband , Nike's tracking bracelet, even included a basic mood tracker (Shu, 2014). Fitbit , another company to create a wearable bracelet, took a similar approach. Accelerometers and gyroscopes embedded in a pod or bracelet calculated caloric burn, steps taken, and physical activity based on how the wrists, shoe, or torso move through space during kinesthetic activity. Fitbit billed itself as the everyman's approach to wearable fitness technology, with a standalone platform in the form of a bracelet or clip-on sensor that communicates with a phone or desktop computer via a dashboard application. While bangles and bracelets were the fads in the mid2000s, the market was already moving toward always-on technologies like watches. In 2011, the TomTom Multisport became one of the first smartwatches with GPS, heart rate monitor, and accelerometer, which tracked the internal rhythms of the body in addition to movements through space. Each one of these devices provides the substance for a variety of game mechanics, and their connective nature allows for social competition and cooperation. The plethora of gamified fitness applications has led Apple to create an integrated

health dashboard for all of the mobile fitness products that display the information from various applications and sensors on either a wearable smartwatch, an iPhone, or both (Prigg, 2014). The Android operating system soon followed suit, creating a dense web of interactive matrices for self-tracking and sharing. What all gamified fitness apps do is create a set of contingencies based on pre-established fitness protocol. Contingencies are possibilities created through games that postulate a series of play outcomes. For example, in the case of Fitocracy – a popular gamified workout tracking application – social expression, community, and conspicuous consumption of fitness as a product work to maintain a key balance between self-quantification, spectacle, and surveillance. Fitocracy allows players to play their workout routines as a character they create, converting their body into an avatar that can gain levels, powers, and costumes based on inputting their gym routines. These routines convert into quests and narratives. Players can also form social groups and compete with one another to complete workout-related quests. Player communities in Fitocracy , especially when it comes to cooperative or competitive sharing, are the key to continued engagement and application popularity – in this case, over a million users (Crook, 2013). While applications, devices, and technological convergences drive the market, the end-use of wearable tech is increasingly gamelike for two primary reasons. One is the usefulness of motivational mechanics, and the other is a historical propensity toward gamelike series and structures embedded in the discourse of healthcare itself.

Fitness Protocol and the Denial of Pleasure It is important to remember that the summation of gamified healthcare is not necessarily the materials, such as sensors and hardware, but rather the social mechanics that are needed to create a set of contingencies that facilitate convergence. Whatever information sensors or users generate becomes a common community language and currency – self-quantification operates as a form of social capital and conspicuous consumption. Players cultivate fidelity with the gaming event by mastering themselves as

part of a “game” that is billed as productivity monitor. Be it heart rate, miles, steps, or even moods (Shu, 2014); if it can be measured and integrated into a network, then it can be converted into points and rewards for adhering to the expected contingencies. Each of these devices is almost exactly the same with a few unique design considerations. Each also has a similar logic – the individual body, as a gamified network, becomes the instrument of play, and the boundaries of the network become gamespace. Conspicuous play, enabled through “leaderboard”-style mechanics, serves as a motivator for collecting data through activity. Usually, data collection involves a gamified body generating “healthy” protocol via devices that monitor and prompt activities based on the individual player's actions. However, not all protocol is good protocol – in a way, the data generated by players are only as good as the metrics used to interpret data, and inaccuracy has been documented by several consumer groups (Bilton, 2014). This inaccuracy largely attributes to how metrics used for current gamified health applications are nearly five decades old – the metrics used to sustain the game mechanics utilized in applications like Fitbit are the same used to create the first scalar fitness system. 1 Gamification has not created any new metrics; rather it has altered existing metrics and brought the concept of play back into the realm of fitness. As such, the data's usability concerning widely used metrics has not been altered in surveillance capitalism, but the mode of generating the data has. In the case of fitness and wearable tech, the historical convergences began in the 1960s – the dawn of the then-burgeoning “network society” (Castells, 2009a). Kenneth Cooper, in 1968, created the first variable fitness program with his book, Aerobics – a scientifically formulated set of series that any person could supposedly alter for his or her bodily niche (Markula & Pringle, 2006). The concept of modular, scalable fitness links to supporting the aims of governmental organizations to better the health of entire population segments – such a large undertaking must have a way of sorting data while also predicting what sort of data will need to be sorted. In order to accurately gauge the health of populations, certain standard measurements, such as heart rate and caloric burn, were

established. The 1990 Conference on Exercise, Fitness, and Health, an enormous gathering of health professionals, scholars, and governmental representatives, did just this with the “objective” formalization of the “complex” relationship between fitness and health (Bouchard, 1990). Over 62 papers from the conference were published, as well as multiple guides. As a whole, researchers sought to standardize practices concerning fitness-related education. Linking fitness to cardiovascular health was established as a primary objective for the health of all population segments. It also established the link between fitness and epidemiology, while officially classifying obesity and cardiovascular as primary risk factors in the ongoing stability of society, at large (Dishman, Heath, & Lee, 2010). The conference also led to the Second International Consensus Symposium on Physical Activity in 1992, classifying obesity as an epidemic (Dishman et al., 2010). As a result of a variety of measures enacted by institutional forces, the relationship between fitness and health was “expressed as positive, direct and logical: increased physical activity leads to improved health” (Markula & Pringle, 2006). However, protocol also washes over individual differences and forces people into categorical sets, effectively decoupling fitness from play or sports. However, removing pleasure and individuality from the fitness equation has largely led to a decline in fitness in the US, despite constant programs aimed at promoting scalar fitness protocol as an “easy” way to monitor health. The simplicity of variable scales put forward by international academic organizations are off-putting, with 150–300 minutes of “moderate intensity activity” or 75 minutes of “vigorous-intensity” exercise being recommended per day as a “medium” level of physical activity with “substantial health benefits” (Dishman et al., 2010) – metrics that almost all wristbands, smart devices, applications, and fitness trackers operate from. The simplicity and scalability of fitness protocol also sustain their virality and adaptability: they are easily converted into levels, series, and points that can be contextualized depending on the desired contingencies and logics. It is for these reasons also that the international “standard” of fitness is directly connected to countries (specifically, the US) that have a history of actively promoting liberal governance,

biopolitics, and computing. Michel Foucault's (1989) la clinique , as it were, is next door. At any rate, the metrics by which gamified monitors operate are adopted from the standardized protocol from government agencies. However, protocol cannot be implemented without people behaving protocologically; it is always behavior that sustains and implements affective protocol (Galloway, 2004). So, while fitness protocol was intended to make health easier to monitor, it did not provide any intrinsic motivation for people other than getting “fit,” which is a rather vague standard. International health protocol led to individualized healthcare practices. 2 However, by making fitness a state-encouraged individual pursuit, health protocol also strips the activity of its affective relationship with pleasure, play, and community. 3 Healthrelated fitness separated from so-called “skill-related” fitness, to disassociate “fitness” from the concept of games and sports (Markula & Pringle, 2006; Werner, Thorpe, & Bunker, 1996). Health protocol also aimed at making quantification of health the duty of the exerciser, rather than the physician, trainer, or coach. Thus, fitness since the 1960s, as sovereign powers see it, is a regulated individual pursuit in which “average” people utilize the metrics provided to pursue and predict their bodily data based on a modular scale (Markula & Pringle, 2006). These modular scales mark the beginning of fitness activities as a series of individual goals based on numerical sets of activities. As such, they mark the building blocks for gamifying fitness. Modular, scalable fitness series predominately started as a means for controlling the cost of healthcare, with the idea that citizens falling into a certain bracket of activity are risks to the wellbeing of the state. In the case of fitness, skill and health are synonymous, with health defined as “being alive with no major health problem” (Markula & Pringle, 2006). However, removing mastery and skill from exercise also removes a certain amount of motivation. Since the creation of fitness protocol, sedentarism in highly mechanized societies has increased dramatically – in fact, without suggesting causation, sedentarism has been on the rise since the 1960s, the same decade nonludic health protocols were put into practice (Brownson & Boehmer, 2005). While work conditions and

the built environment both have something to do with the “epidemic” (Brownson & Boehmer, 2005), it could also be postulated that removing the direct rewards from physical activity, like winning or losing, and replacing it with vague missives about possible fitness does not necessarily account for motivation. Prior to the 1960s, “fitness” was not even an applicable concept (Markula & Pringle, 2006) – sport was undertaken for pleasure. Interestingly, in response to decoupling fitness from play and pleasure, health education has been exploring how skill-based fitness through gameplay can be accounted for in the confines of modern, scientized health protocol (Mortazavi et al., 2014; Werner et al., 1996). Since fitness protocol became standardized, games have become more important for teaching fitness-related skills, while also imparting the sense that fitness can and should apply to individualized and collective “fun.”

Games for Understanding Education has a long history of studying play and games as a mode of embedding social structures, knowledge, and skills. In Latin, “ludus ” refers to games/festivals/sports/play (Bonner, 1977). Stretching back to ancient Rome, “a ludus ” was used to refer to a training school for elementary school–aged children (Bonner, 1977). Additionally, a ludus was a school for gladiators – a training ground for physically conditioning warrior-class slaves for the brutal games they were required to take part in if they wanted freedom (Kyle, 2007). The schematized concept that play is required for skill-based knowledge can be largely attributed to advances in physical education research, and its interest in ludology, occurring during the 1980s (Werner et al., 1996). One result has been “exergaming,” an “expanding option” for physical education and fitness in which the scalable algorithms developed for fitness are combined with skillbased challenges and minigames (Mortazavi et al., 2014). Currently, the algorithms used to predict fitness outcomes in exergaming are still directly tied to the fitness-based directives adopted by the ACSM in 1975 (Markula & Pringle, 2006), utilizing heart rate and mileage as the benchmarks for a successful workout (Mortazavi et al., 2014).

The development of exergaming is a primary example of how research into games for health eventually gives birth to gamified applications promoting a ludic version of biopower. The result has been the creation of a popular educational model, Teaching Games for Understanding (TGfU). In physical education, the body and kinesthetic activity are viewed as the primary means of gaining knowledge about the physical world (Werner et al., 1996). In 1982, with the obesity epidemic just beginning to gain attention in the US media, Bunker and Thorpe (1982) proposed a “tactical” model for teaching fitness and sports in secondary school. The model proposed that life skills, kinesthetic activity, and play are progressively and positively linked. TGfU assumes that “the games teaching emphasis be placed on understanding the logic of play imposed by the rules of the game, and that appreciation of the tactical structure of play be learnt before highly structured technique teaching was proposed” (Stolz & Pill, 2013, p. 38). Stolz and Pill (2013, p. 36) state: Since its inception as a model, the TGfU approach has been the subject of significant attention from theoretical research, advocacy and practical perspectives…the TGfU model has been the catalyst for a global movement involving games teaching that has spawned a diverse array of derivations around the world. In TGfU, students are exposed to progressively more difficult “minigames,” which are then followed by tactical quantification of possible outcomes (Turner & Martinek, 1999). Gameplay, in this case, is viewed as a primary mode of motivation for implementing and concretizing various kinesthetic and cognitive toolsets. Like earlier fitness directives, it used games on a sliding scale based on age and gender, primarily. Different games were viewed as having value for different populations of subjects depending on social norms. Girls and boys are frequently separated and have differential scales applied to the skill sets that are deemed appropriate for different genders, and age groups within those genders 4 (Kennard, 1977). However, the concept of the sensor-

based “minigame” as fitness protocol is recent – full-body motionbased ludic systems explored by gaming companies (e.g., Nintendo's Wii Fit ). The application (and market) for immersive motion-based gaming has only grown with the spread of virtual reality headsets and controllers. Mastery of game mechanics in physical education is the primary mode of motivated skill-based competency according to TGfU, and it also is key in the development of a properly “educated” subject. Stolz and Pill (2006) note that since 1969, true “physical education” is not just linked to sets of movement; rather, the student must understand how they, as a player, work within the game of fitness. Mauldon and Redfern (1969) suggested that physical educators “should not call a person educated who has simply mastered a skill and presented a new approach for games teaching” (Stolz & Pill, 2006). According to Stolz and Pill (2006, p. 38), the “new” approach to fitness education contained three elements: “(1) game categories to group games of similar nature so that teaching for conceptual and skill transfer between similar games could occur; (2) game analysis by players so that players were prompted to develop game appreciation and understanding; and (3) structured situations for player experimentation and problem solving.” Each one of these criteria can also be applied to the gamified applications currently flooding the market. Applications must involve categorically applied mechanics, and mechanics must encourage self-analysis in the context of play and the creation of novel situations that keep the gamified system interesting and the players motivated. Increasingly, gamified applications involve an ecosystem of devices and software that communicate with one another. Games, points, and categorized data flow seamlessly between devices, games, and players. Gaming, then, should be seen as a viable set of fitness technologies since the 1960s. “Universal” fitness protocol, made exclusively for producing and computing data that lead to the categorization of populations, also finds its roots in the 1960s, as do wearable computers. All of these networks have been in constant codevelopment: TGfU is a motivation-oriented educational technique; fitness protocol is a technique for measuring and predicting fitness over large swaths

of bodies and territory; and wearable computing is a technique of observation, quantification, and prediction. All three are inherently biopolitical techniques. When techniques serve similar logics, they tend to converge (Foucault, 2007b). Gamified health apps, which combine the surveillance of wearable devices, scalar fitness directives, and progressive and pervasive game mechanics, are evidence of this convergence. Gamified applications such as Fitocracy , Apple Health , and Fitbit stand at the forefront of motivating people to engage in monitored protocological behavior for biopolitical purposes. In the end, health protocol's matrix-like sets of fitness goals translated easily into the gamelike functions utilized in most gamified health apps. When using semi-accurate caloric deficits and possible health outcomes, the deficits become the points while the possible outcomes become goals and levels. Tracking through data provides the mechanics for gameplay, with different tasks representing different “levels” of fitness activities. For example, Fitocracy players can gain levels by performing the most efficient number of exercises in a “correct” progression. Efficiency is the primary goal for both health protocol and gamified health applications. Ubiquitous computing and protocol-oriented fitness programs began at the forefront of the information revolution. Consequentially, we see them both converging in the form of gamified health applications. However, chronological coincidence does not always mean there is a direct causal link between games, fitness, ubiquitous computing, and, now, gamified wearables. Understanding how monitors, health protocol, and games work to produce subjects lies at the heart of exploring links between gamification and biopower. Convergence has as much to do with discourse as chronology. As a discursive formation, gamification (fitness related or otherwise) shares many similarities with the “quantified life” movement, which values an arrangement of data-centric surveillance to produce a participatory digital enclosure, one that actively works to map the kinetic potential of bodies into a much larger, data-driven framework.

The Quantified Subject

The so-called “Quantified Life” movement – a “way of life” where practitioners use technology to monitor their body and daily tasks on a biological, temporal, and spatial scale – holds many similarities with gamification (Whitson, 2013). Quantified living largely stems from the ongoing “big data” revolution (Bradley, 2013), as everyday life becomes increasingly networked and technologized (Hansen, 2004). The major advances in storing and transmitting data through wired and wireless networks in the first decade of the twenty-first century have led to a surplus of meaningful, meaningless, and attention-starved data. The “attention economy” (Simon, 1971) is an information-rich economy where the amount of data produced exceeds the collective parsing capacity of those who produce it. Herbert Simon (1971, pp. 40–41) states, “in an information-rich world, the wealth of information means a dearth of something else: a scarcity of whatever it is that information consumes. What information consumes is rather obvious: it consumes the attention of its recipients. Hence, a wealth of information creates a poverty of attention” that can overwhelm the average user. Gamified health applications claim to make fitness easy to understand by calculating and displaying the “correct” sets of data for the consumer. However, they also serve to mitigate “useless” data for data brokers, as well. A centralized route to processing these data is extremely difficult, as the US National Security Agency (NSA) has found in their increasingly expensive mission of keeping the global population's metadata stored for “safekeeping.” For instance, the NSA data center in Utah has been a collective focal point for both ire and admiration (Bamford, 2012a), with Greenpeace even stationing a large blimp over the facility stating: “Illegal Spying Below” (Mullin, 2014). The organization needs several thousand “zettabytes” of storage to process multiple “yottabytes” – a septillion bytes, the highest magnitude of bytes yet coined – of information at a budget of $10.8 billion per year (Bamford, 2012b; Sandvik, 2013). Even then, officials note it is hard to “find” an individual, leading leaders to question the efficiency of the operation (Angwin, 2013). Like early work in fitness and health, modular sets, based on clear-cut activities and goals, can serve as preventative measures against more action and information with less meaning. Gaming provides direction and

operates on mechanics that set immediately contextualized player activities. As we saw in previous chapters, games have frequently been used as an antidote to chaos. So, games seem to be a natural “sorting mechanism” for monitored activities, one that can help herd users into a set of meaningful behaviors. Game mechanics help with a variety of issues with mass surveillance. One problem is that the data are often not contextualized as they are transferred. Gamification helps alleviate this issue by acting as a ludic parsing agent, inviting and seducing players to categorize and parse their data for consumption, such as women who use reproductive trackers. This is not to say that gamification leads to NSA surveillance, but it does provide a solution for the anger and suspicion that accompany many attempts at widespread surveillance. If an organization “takes” data, it creates a coercive and hostile atmosphere. However, if the techniques for surveillance are built into an application as game mechanics, it helps to alleviate suspicion by giving players the illusion of choice – if they choose to play, then surveillance is simply part of the game. Gamification acts as an active sorting mechanism for quantified life; it is a way to shift the datatified management of our everyday life to the level of individual computing: We, the users and players, do and report most of the work in watching ourselves (Hulsey & Reeves, 2014). The health applications described above turn health into a game of self-management. The sorters of data are the producers – the players who start a game of fitness. Nike+ and Fitbit both require a large amount of player effort in tracking, arranging, and posting the data generated. Web portals host the data for personal archival and public display. These presorted data are ripe for plunder, and players have already contextualized them. A form of distributed labor, known as “techsourcing” (Jacobs, 2012), turns humans into motivated data sorters. Data-driven motivation, promoters of quantified living suggest, will make everyday life more rewarding, healthy, and fulfilling. Gary Wolf (2010), considered a major proponent of quantified living, states: We step on a scale and record our weight. We balance a checkbook. We count calories. But when the familiar pen-

and-paper methods of self-analysis are enhanced by sensors that monitor our behaviour automatically, the process of self-tracking becomes both more alluring and more meaningful. Automated sensors do more than give us facts; they also remind us that our ordinary behaviour contains obscure quantitative signals that can be used to inform our behaviour, once we learn to read them. Quantified living is basically about making good on the promise of cybernetics, a true co-generative relationship with technology on a close individual and collective basis. The primary goal of quantified life is to use technology – particularly the affective, reflective, and mnemotechnic aspects of ubiquitous computing – to apply the lenses of “mechanical objectivity” (Datson & Galison, 2007) to everyday life in increasingly minute scales. Mechanical objectivity is the set of dovetailing scientific apparatuses and technologies, like the microscope or the Doppler radar, that aim to scientifically and “objectively” visualize the natural and social worlds (Datson & Galison, 2007). For example, Pantzar and Shove (2005, p. 5) point out that heart monitors allow people to see themselves differently: They allow us to “see” our own heart…and in seeing, allow us to make adjustments in what we do: They allow us to quite literally tune our own engine. The results are made evident through longer-term record keeping – a personalizing of the medical record. As such heart rate meters have the potential to redefine the meaning of being well. With the help of sensors, quantified living attempts to modulate life in concert with the digital feedback our body produces as it moves through space and time. These data represent the seductive element of objectifying one's self through mechanical, or, in this case, digital objectivity. Deborah Lupton (2016, pp. 116–117) points out that “lively data” often “involve the rendering of bodily attributes and dispositions into digital data. They produce value in terms of the

intimate biodigital knowledges that they generate from individuals, and therefore self-tracking practices may be described as generating digital biocapital.” Digital biocapital revolves around digitally objectifying the user's or player's body. Objectification, in one sense, concerns attempting to deduce an “objective” examination of the body's internal rhythms by displaying them to the user. In the other sense, the internal rhythms of the individual body are realized as digital objects, which can be displayed and used for gaming, competition, social capital, and varied modes of surveillance. Many fitness trackers did just this. For example, Basis Peak health trackers were outfitted with built-in sensors for temperature and strategically placed pressure points for measuring pulse, which also leads to accurate sleep tracking down to the amount of time spent in deep sleep (Phillips, 2014). All activities recorded on the Peak health bands were quantified as “habits,” which constitute the point-based rewards system (Phillips, 2014). Bands like the Basis Peak included sensors that track galvanic skin responses, electromagnetic signals, light-based 3D movement sensors that reveal external and internal movement (for heart rate and a 3D picture of kinesthetic activities) and sweat composition (Ghose, 2015). Ironically, the Peak was recalled in 2016 for health hazards, in which they would overheat and cause burns (Cooper, 2016). Still, the Peak was the most intensive monitoring device on the market at the time. In 2014, the Atlas Sensor , which combined light-based sensors with biological monitoring, initiated the Motion Genome Project (MGP), which aimed to anonymously track the movements of thousands, or possibly millions, of fitness devotees to build a living map of fitness practices (Cheredar, 2014). Users attached their devices to their arms or legs. The devices measured sweat, repetitions, and even the type of exercises done. These data linked to age, gender, goals, and so on. The “fitness DNA” of players was then bracketed with their location, age, and even the types of exercise they are performing. These data are then stored and analyzed to create a predictive set of algorithms to guide others on how to reach their desired level of fitness. The Atlas website claims the MGP aims to “constant improve our algorithm” in tracking the

body and predicting the effects of certain motions. In short, since the advent of wearable computing, humans are approaching a technological state in which even the most minute bodily functions – such as eye movements, heart rates, and galvanic skin responses – can be recorded and displayed.

Life, Play, and Protocol The archival and display of human bodily functions requires a market environment that sustains the purchase and use of surveillanceoriented devices and applications. Rajat Paharia (2014), founder of Bunchball , a gamified workflow management system, states that the new economic model addressed by gamified design is one of attention. What grabs and holds attention in this economic model is data, and “if big data and motivation had a lovechild it would be gamification” (Paharia, 2014). For Paharia (2014), gamification represents a way of “architecting virality” – insuring that information and engagement, the two primary tools of quantified living, “spreads” evenly over a variety of economic and social sectors. Gamification, in short, provides the seductive motivational apparatus for surveillance and datafication at the level of the individual. Gamification is more than a vast collection of networks. As I stated in the previous chapter, a variable scale is a key aspect of gamified environments. For instance, a gamified environment can span an entire city, a shopping mall, or simply the length of the body. The networks that gamified applications alter can be as small as the wrist moving in conjunction with a gyroscope and digital counter, which then quantifies and displays the resulting mobile data to a variety of devices. The architecture of a gamified environment, much like a game, must be able to produce variable scales and series. It also must be able to produce an environment that requires constant evolution, a never-ending teleology that shifts according to the mechanics. Part of the genesis involved in sustaining a gamified environment involves creating players, a distinct subject category. The player as subject is an individual subject position that is inhabited by anyone who enters into a ludic space. Players become ethically entwined

and responsive to the contingencies put forward by the logics and mechanics of the game (Sicart, 2009). For Miguel Sicart (2009), games are an “encounter” (Goffman, 1961) in which players don a changeable ethical “skin,” one that requires a certain mode of “fidelity” with the system of rules that the event proposes. This ethical skin works as a coat of many colors, a costume that allows a single body to become a multitude of subjects depending on what game is being played (Sicart, 2009). In short, the player is many different individuated subject positions – a multitude of ethical “players” embodied in one person who engages in a multitude of rule systems. Depending on what these rule systems require, the player almost always seeks fidelity and eventual mastery of the system. The motivation for occupying the complex subject position of a player is simple – the pleasure arises from what T. L. Taylor (2006b) describes as the “joys of instrumentality,” a process of becoming an embodied tool for progression through the game's mechanics. The instrumentality of being a player allows bodies to adapt to new events, game-related or social. When it comes to surveillance and managerialism, play acts as the “soft edge” of surveillance technologies (Elllerbrok, 2011), allowing them to colonize social structures and communities without friction. This soft edge results in a quantified self, a subject position born out of play and materialized through data and networks. The quantified self is both the logic of gamification and its primary selling point as a mode of data processing (Bradley, 2013; Hesse, 2008; Singer, 2011; Whitson, 2013). In the context of creating quantified populations, gamification creates only semi-stable subject categories. When quantifying the self in the context of gaming, the “event” or “encounter” that embeds the contingencies of gameplay is always shifting. For example, points comprise a set of levels in Fitbit ; these levels represent a different part in a series, one which the body plays an integral role in producing the data needed to advance each series. Each shift produces data, and the data produced by players as they log their information identify them as active, unstable subjects who evolve alongside technology while publicly documenting and displaying their ongoing epigenesis. In short, gamified applications are the primary examples of the global shift toward digitally managing populations on

a bodily level, rather than as large, stable categories. For example, Clue uses technics on a ludic level to digitize reproductive subjects (i.e., women) in terms of their capacity, behavior, and so-called “normalcy.” A distinctly nonplayful approach is needed to get these normed categories of subjects. Lupton also points out the tracking has become increasingly “required.” She states, “there are various ways in which self-tracking is being encouraged, or even enforced on people, predominantly so that the objectives of others are met; and such ways raise the question of exactly how voluntary self-tracking may be in these contexts. People are now frequently encouraged, ‘nudged’, obliged or coerced into monitoring aspects of their lives so as to produce personal data that can then also be used for the purposes of others” (Lupton, 2016, pp. 2–3). Health apps have been used to create risk databases “of people who have been sexually assaulted, diagnosed with a mental health condition or a sexually transmitted disease, designated as impulse buyers or credit risks, or accused of wrongdoing. These lists are sold to marketers, financial institutions and potential employers” (Lupton, 2016, p. 118). In these cases, the façade of “play” gives way to extractive architectures of surveillance capitalism. However, by gamifiying self-tracking, people rarely peak behind the curtain, choosing to find comfort in the ludic interface set forward by designers. Quantified life techniques, when deployed playfully, hasten the epistemic changes already upon us where the player's body is a vessel for norming good health outcomes, thus hastening the adoption of formerly contentious technologies (Ellerbrok, 2011). However, because these changes are packaged as a game, players are less likely to seriously interrogate their experiences. Already, ingame monitoring and research raise ethical questions on ludic modes of surveillance (Taylor, 2008), and players are often not aware of what rights they are signing away when they accept enduser license agreements, or EULAs (Chee, Taylor, & De Castell, 2012). Social protocol creates an openness toward activities and technology that, in a logical sense, are unsavory and dangerous. The openness toward wearable sensors and smartwatches – and the openness toward technology being with, on, and even in one's

body and at all times – must be present in order for one to submit to complete self-quantification, whatever that open-ended state may be. Self-quantification is a game we play with ourselves, one that we are aware of as we play it. How our play interacts with other entities should be the primary places of interest. Acceptance must have a motivational force behind it. In order for the acceptance of any protocol, it must first be practiced (Galloway, 2004). So, it makes sense that the first sets of protocols introduced in surveillance capitalism seem to be playful. Galloway (2004) points out that “protocol is a result of protocological behavior, not the cause of it.” In this manner, the ambiguity of play and the logic of games combine into a fuzzy network with its built-in motivational apparatus – whether sad, frightening, whimsical, dangerous, violent, or funny. Games are always engaging and arousing. The network of play is more than game culture, it is also the environment, technical or otherwise, in which play occurs. It was the heart rate monitor, which was colonized by game dynamics and not the other way around. In the context of gameplay, a heart rate monitor is just another type of controller or feedback mechanism. It is the monitors themselves that allow players to “see” themselves within the contingencies of the game, yet often the monitors and controllers are the invisible support for any gamified environment. It is this invisible support mechanism, however, that does most of the work as a technology of the self and a technology of self-subjugation.

Healthy Players and Healthy Subjects The combination of games, fitness, and big data in the twenty-first century has less to do with chronology or linearity and more to do with affective relationships: Games, wearable technologies, and fitness protocol all aim to create docile bodies in one way or another. Foucault (1977, p. 136), in Discipline and Punish , describes a docile body as one “that can be subjected, used, transferred, and improved.” The relationship between movement, transference, and alteration stems from techniques and disciplinary methods: “These methods, which made possible the meticulous control of the

operations of the body, which assured the constant subjection of its forces and imposed upon them a relation of docility-utility, might be called disciplines” (Foucault, 1977, p. 138). In the case of gamified wearables, it is the creation of players that is the primary directive. However, the player as subject is a changeable one, and the docile bodies produced by games are always incomplete. Rather than the terminal state of “subject,” players are individuated units. Individuation is, according to Gilbert Simondon (2007), the effect rather than the cause of subjectification, or the formation of an individual subject. This viewpoint suggests that it is not the form of a subject that is important, but rather the process by which that subject forms that is of utmost importance. Simondon (1992) states that individuation is the attempt to place “the individual” at the level of the individuating process rather than “the process of individuation by means of the individual.” So, we must look at the protocols driving individuation, rather than the individuals. In short, like protocol, individuation is a process of unfolding – it is open, connective, and mutable. The player's body, subjected to protocological technique, becomes a subject of discourse, something that can be “altered, used, transferred and improved” (Foucault, 1977). However, players inhabit multiple bodies – they are a repository of potentiality for change and emergence. Emergence means that, before a gamified application, there is no preformed subject, just a set of potentials that can unfold into a variety of possible forms through gameplay. The creation of players, sometimes many players with one body (or one body with many “skins”), is the primary goal of gamified applications – players are a population willing to produce, sort, and submit data so long as there is the presence of a game. For surveillance in gamified health applications, players do not attain any coded form except in the actual process of unfolding through gameplay – it is procedural. Procedurality means a player is never finalized; within each unit or set, there are always untapped reservoirs of potential for change and alteration. In the context of different gamified applications, players are different things – still, they (mostly) commit to willingly engage the required mechanics in order to generate directed, favorable outcomes within the context of the

game in which they are engaged. In any game, there is no one way to skin a cat. Players navigate contingencies of their own accord, in unique patterns, toward a mutually desired (and officially designated) reality with little to no oversight. From a control-based perspective, that level of collective engagement is a managerial dream – one that has not gone unnoticed by both gurus of the quantified self and the governors of the quantified masses. It is the player, the bodily actor within a gamified environment, who holds the primary value for exploitation via biopower. The player's actions, via gameplay, are the primary means of sustaining the (game)space where surveillance occurs. As stated in Chapter 1, the body of the player is the only agent who can ensure that seductive power, and control, contuse. The player, through gameplay, is the only one who can bring the protocol of “a game” into being. For example, the data generated by players using Fitbit applications are only useful so long as they (somewhat) willingly engage with the mechanics. Players, quite literally, generate and sustain the protocol of a gamified application by playing it. In this manner, play can be a continuous set of actions over a series of games or gamified applications – play as a sustained state of doing, since players are always “in play,” aids in the production of gamified ecologies. Players will always respond to the gamespace as long as they still want to play – it is only a matter of negotiating what outcomes are generated via mutually adopted sets of protocol. So, play and gamification are primary catalysts in the self-managerial revolution and the key mode for making a profit through surveillance: They are the gateway to the docile body, the body that can consistently be optimized to produce performative data. As a population, they are customizable, observable, and mostly cooperative. Foucault (1977) recognizes that technology, in a myriad of forms, aids in the production of individuals and docile bodies. In the case of gamification, both technologies and techniques help those bodies acquire an identity, a coded structure, and a playful ethical subject position through the use of game mechanics and protocol. According to Foucault (1980), any technique or technology that abets selftransformation in terms of identity within a certain form of power,

discursive or otherwise, is a “technology of the self.” Foucault (1988, p. 18) states that technologies of the self are any methods that “permit individuals to effect by their own means or with the help of others a certain number of operations on their own bodies and souls, thoughts conduct, and way of being, so as to transform themselves in order to attain a certain state of happiness, purity, wisdom, perfection or immortality.” It is important to note that technologies of the self are not practices that transform discursive structures or technical systems, rather, they allow individuals with these formations to make an ethical choice about how they operate within the confines of the agreed-upon (or forced) set of contingencies provided. If play is the preindividuated reservoir from which the player springs, then games are the technologies that players use to modulate their ethical positions, or “skins” (Sicart, 2009), within the context of play. Users of applications like Fitocracy , for example, utilize the mechanics of the game, which encourage community-based fitness, to redefine their fitness projects in concert with the actions of others. They recontextualize their workout as quests and their physical progression as leveling. Besides, Fitocracy contains RPG-like mechanics that focus on leveling – tracking and rewarding a player for constant self-transformation. Players gain perks, abilities, and points as they work out, complete exercises, or encourage other players. Displaying triumphs to the community as they complete their workout becomes a motivational force. Players become a hero, completing a necessary role in their gameworld. However, their actions directly link to outcomes situated in the everyday task of monitoring and maintaining their health. They are not playing a character; they are playing themselves as a multitude of characters across a wide ecology of gamified applications. Another primary example, and one that has been covered in depth, is exercise. Foucault (1977, p. 161) states that at the center of any serialization of time (or space): One finds… ‘exercise.’ Exercise is that technique by which one imposes on the body tasks that are both repetitive and different, but always graduated. By bending behavior

toward a terminal state, exercise…assures, in the form of continuity and constraint, a growth, an observation, a qualification. Serialized repetition, scalable modes of engagement, and segmented levels are all forms of exercise, and whether they aim at fitness, play, or both, they ultimately operate as technologies through which self-transformation occurs without necessarily altering the system. In this manner, play is a form of exercise, and it also encourages individuation. Like exercise, play is skill-based, it requires mastery, and if it is done correctly, it also has embedded within it self-referential motivational apparatuses. Health may be one of these motivational sources, but the other, more effective sources, stem from the arrangement of protocol. Openness toward accepting new protocol while still maintaining a specific state of doing has other, problematic, advantages beyond the creation of players for biocapitalistic purposes. Play is a cultural “practice and public legitimation tool that encourages the acceptance of otherwise contentious technologies” (Elllerbrok, 2011). Jennifer Whitson (2013) points out that gamification, fitness, and wearable computing, as a set of affective technologies, serve the purposes of self-quantification on a massive scale. Whitson (2013, pp. 165–166) states: What is important about digital games is that the rules are not only formalized, they are completely hidden from players by the black box of the game software… the work involved in interpreting and maintaining the rules (and thus the system of social order) is taken entirely out of the players' hands and is instead reliant on algorithms. For Whitson (2013), one thing that separates gamification from games is the apparent lack of negotiation when it comes to protocol. Like fitness and health, scalable series allow for increased flexibility when it comes to quantification, but decreased flexibility concerning the power subjects have to alter the protocol they are producing.

Players (or ludic exercisers, perhaps) must adhere to the standards by which they are judged if they wish to succeed on any level. However, game mechanics can easily be overwritten, modified, or ignored. For example, people can cheat by playing against the game or exploiting certain mechanics for personal gain or, in some cases, to push the gameplay forward into a new phase (Kücklich, 2009a). For example, shaking a FitBit watch will cause the sensor to assume the player is walking when, in reality, they are simply moving their hand back and forth. Publicly, their profile shows a large amount of activity for which the player is rewarded. In reality, they are overriding protocol by exploiting the abilities of the sensor for accruing social capital and rewards. Still, what cannot be overwritten is the desire to play and the seductive promise of mastery and instrumentality that comes from playful behaviors. These seductive motivations, driven by mechanics, provide the ideological backdrop for the increasing penetration of gamified applications.

Conclusion In this chapter, I identified gamification's biopolitical leanings. Gamification shares a history with other biopolitical endeavors, including national fitness endeavors, fitness protocol, and healthrelated pedantry and education. At the same time, it also shares a concurrent history with the development of wearable technology. Each of these categories also shares a history with games and gaming. The failure of nonludic health protocol results in wearable, gamified technologies, and application becoming a market driver for the adoption of formerly contentious surveillance technologies. These technologies, via gamification, provide self-archival tools and aid in the large-scale monitoring of fitness and activity. If play acts as a harbinger for contentious technologies, then play also disguises what these technologies might be. Game algorithms are easily discernible to players who master the game itself. Reeves and Reid (2009) point out that game interfaces do indeed “sharpen” behavior within a certain context, meaning that players are efficient, but this sharpness is what allows players to master and discard gaming protocol in favor of new experiences. In essence, what

Whitson (2013) is worried about – the “hidden” protocol of play – is the primary weapon used to combat or alter protocol. Mastery, in the case of gaming, often leads to actions that change the game – actions such as modding (Owens, 2011; Simon, 2007a; Sotamaa, 2010) and cheating (Kücklich, 2009a). The same is the case in fitness, with those who “master” exercise routines choosing to “hack” or “mod” their bodies with diets, supplements, and altered fitness programs and goals (Wolf, 2010). These mastery-based behaviors alter and add to protocol rather than succumb to it. What is less discernible, and more ominous, is the affective relationships that gaming “algorithms” have with supporting technologies, such as sensors. The issue is that players are often hyperaware of the mechanics they are engaging in while playing, but less aware of the technological implementations (like controllers, monitors, and sensors) that allow them to become players (Kirkpatrick, 2009). While this is untrue in many aspects of gameplay (i.e., hardcore or competitive play), it should be noted that in gamified design the interface is specifically designed to become invisible (Zicherman & Cunningham, 2011). In order for bodies to become digitally contextualized via gamified ecologies, designers must alter spaces where bodies move. The redesign of entire environments is a primary object of gamification's ideological desire: All bodies must become players, and all spaces must superficially be spaces where a game can be played. Ludic ecologies bring gamification in direct contact with the bodies and spaces it alters and the spatiality of players who exist through gamified environments. Players cannot exist without protocol, and gamification must create protocols that permeate everyday life in order to profit. However, it is not solely a player's body that produces data: it is their everyday life and labor. Moving forward, I will catalog and critique gamification's influence on the spaces where people conduct their daily activities. In the final chapter, we will be looking at how gamification influences the workplace and the social realm by examining playbor, productivity apps, and social media. 1

Aerobics is perhaps the most common example. Invented in 1968, aerobics was one of the first programs that converted physical health into an algorithm (Markula & Pringle,

2006), For example, if a person of a certain age, sex, and height does a requisite amount of activities, that person can be deemed “fit.” 2 Individualized practices are part of an algorithmic system aimed at individuals tracking their own activities and plugging those activities into a functional matrix that determines activity levels. Aerobics is a key example – it places the onus of health on a single subject's adherence to a set of standardized protocol. 3 Theorists George Herbert Mead and Marcel Mauss both claim that ritual play precedes exchange, and therefore is a precursor to any type of community. Gamified applications like Fitocracy encourage and sustain fitness communities via play (Crook, 2013). They also promote international protocol, thus restoring the playful, communal aspect of fitness. 4 Even with the shift toward individualized digital fitness, this still holds true, with a host of wearable monitors directly targeted at “active” women (Rao, 2014).

Chapter 7

The Labors of Play As someone who has played games for most of my life, from my parents' old Atari system to the first Nintendo to building my first computer with my father, gaming has been a constant presence. Ask anyone who is a gamer, and they will tell you that gaming is hard work, and it is even harder to “gitgud.” It takes effort to learn the intricacies of top-level gameplay, and for a noncasual game to survive, it needs an active community. Scholars have noted this phenomenon, known as “playbor,” in which players exist somewhere between labor and leisure (Kücklich, 2005). Playbor can apply to many of the tasks dedicated gamers perform: modding games, moderating and contributing to forums or subreddits, organizing events, running game servers, and editing game wikis. Most of these tasks are considered part of the “metagame,” or the community maintenance and learning that goes on around the game. These tasks can be monotonous and unrewarding, yet we do it for the love of play, or at least we tell ourselves this. Games have a unique ability to make seemingly repetitive activities engaging through play. Soccer, to be blunt, is a swarm of people running back and forth, chasing a ball for hours. It is also the most popular game in the world. Nick Yee (p. 70) states that the purpose of games is “to train a player to work harder while still enjoying it. And most games…employ elaborate designs that derive from principles in behavioral conditioning.” Games rely heavily on willing instrumentalism, so that “the same way that TiVO trains us to become better TV watchers, video games train us to become more

industrious game workers” through the “timing and layering of reward mechanisms” (2006b). Engagement is playful, born of the desire to transcend and progress, and it is why companies are fracking game design for mechanics that make terrible or unprofitable tasks more rewarding for users and traditional employees. Digital labor is any task that takes place within a computational context, and it has upended predigital notions of work, play, and labor. Digital labor is a complex subject, since it does not just take place at a workplace. Digital laborers are often not employees in the traditional sense. Internet culture, a project of love constructed by billions of people, is also labor, a playful “factory” of content, data, and experiences (Scholz, 2013). Social media entrepreneurs seek and accumulate followers by the millions, carefully tailoring their entire lives around likes, retweets, and shares. Do these activities count as labor? Crowdsourced “microtasking” sites employ millions, and they focus on using unskilled workers for manual labor and sorting, annotating, and contextualizing data fed to databases, algorithms, and machine learning programs. The tasks are small, discrete, onerous and do not pay very much (Crockett, 2019). Yet, digital laborers work for hours and achieve play-like “flow states” through seductive and often gamified interfaces (Bucher & Fieseler, 2017). Crowdsourcing and social media companies do not “employ” these laborers, but their users do not “work for themselves” in the sense that they control their wages or choice of tasks. They are the denizens of the “gig” economy, based around discrete, distributed labor and the creation and consumption of data. Social media and productivity applications are increasingly gamified, and all of these tasks can involve social media scheming, livestreaming for tips, tweeting and retweeting, tagging photos, transcribing snippets of voice or video, annotating data, captioning pictures, and bidding for work through apps. Collectively, the data produced forms the primary aspect of artificial intelligence's and algorithms' seeming ability to “make decisions” for users and companies, alike (Lanier, 2013). Our algorithmic culture relies on an infinite procession of paid and unpaid tasks driven solely through motivation and engagement, a thin veneer of “play.” Perhaps this is why Alexander Galloway (2006) first chose to explore the

burgeoning algorithmic culture of the mid-2000s through video games. Playbor, which used to constitute a unique aspect of gaming culture, has spread like wildfire, encompassing multiple levels of digital play, work, and labor. Christian Fuchs (2015), drawing from Marx, points out that there is a difference between work and labor. Work is the direct interaction of humans with a set of tools, which produces use value. From the standpoint of gaming, we could say that doing “work” would be interacting with the modding software or community forum directly. For instance, I ran a server for the original Counter-Strike game back in 2002; I worked on modifying an old computer into a server and then listed the server so that others could play on it. The direct use value of working with these tools is that I was able to play with others using my own server rules. In this case, the interface and application became a tool that produced direct value for myself and the community. Fuchs (2015, p. 255) states that “new meanings and (the creation or maintenance of) social relations are the use values of communicative work. Cooperative digital work organizes human experiences that are given in the form of human thought, online information or joint meanings, and existing social relations.” Digital work, then, involves creating a new product or experience through manipulating media technologies. To improve at a game or support the community, many players do work within the context of ludic activities, just as musicians “play” instruments while simultaneously working to improve skillsets. In this case, work does not necessarily entail monetary value. It is simply the process of creating something with use value to the player or worker. So, if we look back at some of the gamified activities covered in past chapters – navigation, pet care, and self-tracking – users and players are technically working to produce data that alters their environments and relationships via technogenesis. For a woman using a smartwatch to track her health, the data does have a use value for her. So, she has a modicum of personal connection to the product. As she completes goals, she perceives the use value of the application. Labor, however, is a more abstract process rooted in power and control.

Labor is rooted in “alienation,” so while work and play have intrinsic use value, labor abstracts the process of work toward market value and commodification. In earlier chapters, I noted that consumption is what drives automation, which in turn creates a disconnection from production. However, digital labor comes fullcircle because users and players often occupy the role of producers and consumers (Piccinini, Gregory, & Kolbe, 2015). While we work and play in the digital ecologies of the Stack, we strike a Faustian bargain: “the social web appears to be free for us to use, but there are hefty social costs; oligarchs capture and financialize our productive expression and take flight with our data. We, the “users,” are sold as the product (Scholz, 2013, p. 2). So, while we produce content, we also become the product. Fuchs (2005) points out that digital labor has a fourfold process of alienation: alienation from labor power, alienation from the product and tools of labor and a final alienation from the objects of labor. Alienation from labor power implies that power becomes removed from the laborer and transferred to an institution; it renegotiates an identity of working for one's self and toward an “employee” with fewer rights and privileges. In the context of digital media, this alienation produces negative social and economic consequences if an individual no longer wants to use an application. For example, jobs initiate required on-site, data-driven surveillance where employees must submit or lose their job (Van Oort, 2018). However, this alienation also occurs with “optional” applications like Facebook . While users are not required to use Facebook , they will also miss out on a variety of connections and benefits if they decline access (Fuchs, 2015). Alienation from the product means that users do not receive direct benefits from the things they produce. Facebook users do not receive any payment or benefit from the reams of data they generate, even though that is Facebook 's primary mode of capital. They have no private control over the profits big data produces. In the case of crowdsourcing applications, users can exercise some control over tasks, but they cannot set the prices for their labor or control the algorithms that rank their effort.

Finally, alienation from the tools and objects of labor mean that laborers no longer own data in production: companies and developers control the user interface level of the Stack. Also, users and players no longer own their own experiences, as all data produced through the game's or application's interface belongs to the designing entity (Fuchs, 2015). Looking back at the work that players do in the metagame, where they do not own assets or profit from what they write or build, we can see how labor, work, and play begin to fade into one another. The same equation applies to user– player hybrids employing gamified applications; they are producers, products, and human resources. The existence of playbor results from the tension between digital play, work, and labor. As David Myers (2017) suggests, just like play, the power of games is ensconced in their liminal and paradoxical nature. As we saw in Chapter 2, gameplay is not-quite exploitation, but it also is not symmetrical in terms of power relations. Looking at playbor through the lens of gaming, the process of labor becomes muddled. On one hand, players intrinsically benefit from their gameplay and contributions to the metagame. For example, Twitch streamers are mostly supported by the gaming community rather than the game developers. On the other hand, players do not own the games or control profits related to their play within the game itself. Modders who create new experiences based on the resources provided by a development studio do not control or profit from the mod they created (Kücklich, 2005). Their labor is remade as play. Playbor, then, is a type of recontextualized alienation where the playborer draws intrinsic value from the context of play, which conceals or lessens the sense of separation from the product or means of production. In this chapter, I will explore the intersections of surveillance, informational, and platform capitalism, and how labor changes in the digital economies of the Stack. I suggest that, while extractive architectures seek to lift and contextualize data, gamified playbor serves as the cutting edge of execution architectures – protocols that seek to bend human behavior directly for profit and efficiency. If playful gamified applications provide a “nudge,” then introducing gamification into a wider context of life and work, where it is no

longer optional, is a hard push over the cliff. My analysis revolves around gamified social media, crowdsourcing, and productivity applications. First, I examine playbor in social media, and what happens when an application is “degamified.” Then, I move onto platform capitalism and the digital economy. I look at how seductive architectures produce dedicated playborers by adding a lusory context to unrewarding labor. Finally, I explore the key aspects of gaming that translate into the gray areas of playbor and labor by exploring the meritocratic systems of gaming and “the grind,” or the repetitive advancement of gameplay. In the past, play and labor have often been considered opposites. When immersed into gamified ecologies, they collide through strategic implementation of seemingly-simple game mechanics.

Watch Me Playbor As we have seen throughout this book, the Stack's base layer involves building up seductive architectures around people, altering them into users and players. This alteration of subject–positions and identities is also what fuels the profit mechanisms of surveillance capitalism. In the past chapters, I have focused primarily on the extractive architecture of gamification. However, seduction is an active process, one that directs and fuels desire. Gamification and games rely on what is known as a “nudge,” a behavioral push toward playbor through seductive architecture. Thaler and Sunstein (2008, p. 6) state: “A nudge, as we will use the term, is any aspect of the choice architecture that alters people's behavior in a predictable way without forbidding any options or significantly changing their economic incentives. To count as a mere nudge, the intervention must be easy and cheap to avoid.” In short, nudges are behavioral incentives built into design architecture that do not rely on discipline and punishment. Rather, they present a seductive brand of choice architecture. Nudges are an example of what Zuboff (2019) calls “execution architecture,” or the design of rigged choices to control and direct behavior. The cycle of execution architecture is simple: large amounts of data on behavior are collected and charted via extractive

architecture. Then, positive or optimized outcomes are modeled and a design is created or altered to provide contingencies that promote the “correct” behavior (Zuboff, 2019). The process is clear in-game design, where developers closely watch in-game protocols and game moderators (or GMs) patrol the gameworld, mediating complaints, and doling out justice (Kerr, De Paoli, & Keatinge, 2014). Moderators of guilds and forums mediate cultural norms within a game community, where speech and opinion are constrained and steered by ranks or voting systems (Collister, 2014). Every player's gameplay is recorded, but the digital labor of the community in the metagame is also monitored; developers watch what players think, say, and do. Then, rounds of “patches” are applied to adjust gameplay and retain optimum measures of gameplay, profit, and playtime. Facebook also follows the same game management method on a massive scale. It closely watches views, links, and upvotes. Then “populations” of users are identified, and smart algorithms sort and distribute content to those populations to keep them engaged (Vaidhyanathan, 2018). The populations are carefully controlled and mediated through “moderators” who trawl user data for unsavory content; their moderation queues are fed by bots and algorithms searching for rogue elements that might disrupt or break user engagement (Gillespie, 2018). Choice architectures and gamic ecologies, once the hallmark of early cybernetics and game theorists like Herbert Simon and John Conway, have been applied in farreaching applications. As I noted previously, The Game of Life is being rendered true in a very real way, with millions of living automata building monetized social and informational environments to the tune of simple mechanics. Playbor, rooted in the seductive nudge, is the new norm for almost all online social interaction and the power source of everyday life in the Stack. All social media platforms encourage some form of playbor, from YouTube (Postigo, 2016) to, more obviously, Twitch , Siva Vaidhyanathan (2018) likens the mechanics of Facebook and other social media “junk food.” There is a finely tuned recipe behind the use of game mechanics so that use is pleasurable, but it also is unfulfilling, so we continue to come back. The mechanics are simple,

and they recontextualize what we do, where we are, and whom we know. He recounts the coach section of a plane on a transatlantic flight, cramped and uncomfortable, yet everyone seemed to play Candy Crush (Vaidhyanathan, 2018). He states, “the scene was so odd. On mobile devices – phones and tablets – these fifty passengers were all playing Candy Crush Saga , the most popular game ever launched on the Facebook platform” (p. 31). The passengers focused on the application rather than their surroundings, “they weren't exactly happy, but they were not uncomfortable. In fact, the Candy Crush Saga players seemed to have adjusted to the indignities of coach air travel better than those of us who chose books or movies” (Vaidhyanathan, 2018, p. 32). These passengers represent how gamification contextualizes a bad situation; they can never beat Candy Crush , but they can mitigate the discomforts of air travel. Players can let the seductive architecture lead their attentions and bodies elsewhere. Through the lens of play, desire becomes active and directed. Like Candy Crush , which is an obviously gamified application housed with a hidden gamified application, Facebook's connective mechanics also direct our desire: Facebook wants us to remain engaged with Facebook as deeply and for as much time as possible… [it] has developed techniques that it hopes measure our relative happiness or satisfaction with aspects of the service. Facebook researchers have been trying to identify and thus maximize exposure to the things that push us to be happier and minimize exposure to things that cause us anxiety or unhappiness (Vaidhyanathan, 2018, pp. 33– 34). While Vaidhyanathan describes Facebook as a “Skinner box,” and I do not entirely disagree, I think it is also one of the largest and most complex social playgrounds ever created. Playgrounds are wild, and, without supervision, they can be dangerous. However, playground games are finite games; they begin and end.

Facebook is an infinite game, and endlessness is what makes gamified playbor dangerous. People tire of the obvious, disciplinary strategies of control in their everyday lives. How many mentally check out for an endless, playful sequence of content? It is not an unwise tactic; after all, play is pleasurable. But exactly how much of our nonludic lives do we miss in a given day, and what benefits do we receive from playbor? Research shows that we do not get many benefits, at all; in fact, social media usage makes users more anxious and depressed (Hunt, Marx, Lipson, & Young, 2018) and can amplify cruelty in ways never before imaginable (Boyd, 2014). Games can also breed anxiety, social disjunction, and toxicity (Euteneuer, 2019). 1 Gamification, it seems, can do the same. As we will see later, both games and gamification rely on the same mechanics, so it makes no sense to assume they might produce differing effects. Muddying digital play with digital labor may switch out discipline for ludic contexts and contingencies, but it does not solve the alienation of labor or the anxieties associated with alienation. Greg Goldberg (2018, p. 14) states that, in a digital context, anxiety is more than a feeling: it is “a particular way of seeing/feeling but also of intervening, of attempting to resolve the underlying cause of anxiety by producing a subject invested in or attached to desired objects in particular ways.” Anxiety and desire are both active in digital media. They involve compulsively using applications to fix problems and produce pleasure. Playbor mitigates boredom, loneliness, unemployment, and many other pests of modern life. The antidote to numbness is often pleasure, and the types of playbor social media produce are often “pleasurably embraced” by players and users (Terranova, 2000). This idea of pleasurable exploitation lies at the center of playbor's paradox. However, defining playful exploitation is also a central weakness in trying to define playbor (Goldberg, 2018). Goldberg points out that “redescriptions” such as “play as work” or “leisure as labor” become too broad when viewed through our shared media ecologies. Overall, “playbor” literature often does not target pleasures that are paid for (such as buying, playing, and beating a finite game). It only seems to criticize activities paid for in time and attention, such

as the infinite games of social media (Goldberg, 2018). Furthermore, there seem to be two different criticisms of playbor. The first deals with digital “exploitation” scholarship that attempts to devalue certain forms of pleasurable or playful labor; the onus is placed on the user since they are authors of their own exploitation. Goldberg (2018, p. 46) states that “these forms of leisure are understood as having little to do with the collective, communal, responsible forms of relationality valued by critics, whether because devalued forms are understood as escapist or as otherwise detrimental to valued relational bonds.” As I stated earlier, play and games are often denigrated or ignored by scholars of culture. Goldberg (2018, p. 47) intimates the denigration of play comes from the digital's siege on “forms of relationality valued by critics” – their anxiety stems from a perceived threat to a utopian version “the social.” The other problematic brand of criticism focuses on corporations, developers, and designers who attempt to retain monopolies on the profits of digital labor (Goldberg, 2018). In this model, players and users are not blamed for the pleasures of playbor; the issue lies with our digital culture not valuing shared or collective ownership (Goldberg, 2018). These critics do not target play or leisure as an issue, but the onus of blame still lies on the user. Goldberg (2018, p. 55) states that, in this vein of criticism, “users need to be made responsible, whether because collective ownership and control are responsible endeavors, or because the kinds of cultural content produced through collective ownership and control are assumed to be aligned with users' “best” – that is, collective – interests.” In the end, both forms of critiques fall short in devaluing playbor for lacking social value. I would agree with Goldberg's analysis: I enjoy the current “playbors of love” I do for my game communities, just as I enjoyed running a Counter-Strike server. I never felt exploited, even though I neither owned nor profited from the games (nor did the modders who created the Counterstrike mods my server supported). Attacks on playbor “surrounding the transformation of leisure into work thus aims to reestablish a boundary, not between labor and leisure, but between responsible and irresponsible forms of relationality” (Goldberg, 2018, p. 55). I question that placing boundaries on “good”

and “bad” playbor is a tenable process. Play and pleasure are both in the interest of playborer. Still, if playbor is not necessarily exploitative, then what is it? My primary answer goes back to seductive architecture and gamification' slusory modes of remediation and recontextualization. All voluntary digital labor involves work, the sense that you are doing something valuable and contributing ideas, experiences, and content for others. We cannot ignore the alienations inherited from traditional labor, either. The choice architectures of Facebook , Instagram , and Twitter are extractive. They also value the “nudge” or the combined “dopamine hit” of game mechanics to reinforce pleasure and desire (Lanier, 2013; Vaidhyanathan, 2018). Playbor, then, is rooted in both users and designers recontextualizing alienation: making it less visible and problematic. It is not necessarily the alteration of labor into leisure or work into play; it is a ludic alteration of the spaces and contexts in which these processes occur. Technogenesis involves the creation of new assemblages, new techniques, and new technical ensembles. Gamification is a new set of technics, a repository of changes driven by playful mechanics; in a sense, playbor is the evolutionary outcome of ludic, simulative design. Like games, its power rests in the liminalities it inhabits, somewhere between exploitation, affectation, and play.

Quixotic Playbor To understand playbor, we must first analyze the levels of “intentionality” in using game mechanics as design tools. We do know that, like all subject categories, a “player” is simultaneously produced by play, game, and designer. Are designers exploiting players? Are we mere puppets of design intentions? The answer is complex. Games communicate through subverting authoritative structures; for gameplay, it is imperative that the player is not “guided” or forced (Myers, 2017). This is why true exploitation, the application of disciplinary techniques, is not possible under seductive architecture. Playbor, like gaming, is an inherently self-reflective experience; within a limited context, it is also self-guided. In terms of technogenesis, we should assume playbor is an evolutionary

outcome of new, ludic media ecologies. It is neither good nor bad; it skirts the edges of coercion and exploitation without surrendering. Rather, I argue, playbor is a necessity for simulation and control societies. To survive surveillance capitalism and its alienations, we have to create new, playful tactics for navigating everyday life in the Stack. Playbor is natural in a digital ecology because play is innate to computing, itself. Games, in a way, come prepackaged with computation. The history of computers is a shared history with games, game theory, and simulation. Technologies of control increasingly incorporate themselves into our daily lives, seamlessly infusing our environments with strategic protocol, nudges, and choice architectures – all techniques stemming from the study of human choices spearheaded by game theory. However, I also think play is inherent in computing – it is inescapable. Miguel Sicart (2018) notes that humans engage in a form of “quixotic play” with computers. He argues that playful elements exist in all modes of computation, and users experience play as either submission or resistance to computational protocol. Computation is a process of “transforming information” through “generative structures” of computational protocol (Denning & Martell, 2015). Generativity is a keyword because it denotes what computers do with information; they create and combine ontological categories. Sicart (2018, p. 250) points out that “computers can be understood as instruments for playful production and consumption. User interfaces, feedback systems, and entertainment forms based on play are taking over the computing machine to envelop its powers in a friendly, playful discourse.” We increasingly “delegate tasks to computers, and the interfaces to these machines have become more and more interactively and aesthetically playful” (Sicart, 2018, p. 250). Understanding how play embeds into computing can help us understand why playbor exists, and why it is important as a simultaneous source of submission and resistance. Play is the innate act of world-making, a step in creating new ways of seeing and doing (Goffman, 1961). It is a desire to rearrange our social and material environments – the drive to learn, change, and then relearn. Interestingly, the root word techne also means a

way of seeing and doing. So play is a techne , or technique, for reontologizing our environments for better or worse – remaking our internal and external worlds. Computing also involves reontologization, which is, as philosopher Luciano Floridi (2013, p. 6) notes, “a very radical form of reengineering, one that not only design, constructs, or structures a system…but one that fundamentally transforms its intrinsic nature.” In short, humans increasingly understand the world and their internal being as an informational assemblage; so, because computation affects and transforms information, it also transforms human perceptions, as well. Unlike cybernetics, which sees humans as biological creatures engaging in a Skinnerian “loop” with technology, reontologization imagines humans as informational beings moving in an evolutionary loop with computational technologies. It fits well with the concepts of technogenesis and seduction because both require active participation from humans and technologies. So, computation and play share capacities for reontologization; however, the humans caught in the midst of technogenesis are unstable individuals, always undergoing change, similar to the subject–position of a “player.” It makes sense, then, that playbor is one form of “anxious labor” to stabilize our identities within ever-shifting networked environments (Goldberg, 2018). Both Sicart (2018) and Galloway (2006) note that play is a relational strategy helping to stabilize and connect human sociality in the context of protocological–algorithmic control; it is a tactic used to adapt. So, playbor is not exploitation, but a reaction to possible changes wrought by the digital economy. It is a mode of reontologizing digital labor into something playful, an acceptable compromise between a gamified application's designers and playborers. Sicart (2018, p. 260) writes that computational play is “Quixotean play” – Don Quixote lived in a world of fantasy, but it is not “his world of fantasy, it is not his construction, his settings, his desires driving that world.” His playful reontologization of his environment is a response to the boredom of quotidian life. Quixote's madness is a constructive pleasure that “thrives in the clash between reality and the imaginative recreation of it” (Sicart, 2018, p. 260). So Quixotean play is a negotiation tactic: “play capable of engaging with and

appropriating reality” even while reality “resists such appropriation” (p. 260). Play and playbor, in the context of computation, is simultaneously a submission to protocol and resistance to being controlled completely. Sicart (2018, pp. 261–262) states: to play with computers is to establish a relationship of submission and resistance – submission to the ontologizing process enforced by computation (the world created and upheld by the computer), and resistance to it (by developing new rules, interpretations, and contextual appropriations of that very reality allowed by the computer). As Goldberg (2018) notes, playbor is not necessarily “good,” it is still a reaction to anxieties and alienations. However, it is also not simply foisted on users by designer intent. Users and players welcome the seductive architectures of both games and gamification. The widespread use of game mechanics is proof that they work, at least to a certain degree. They provide an olive branch between people and protocol, a point of connection between technology and more human activities. If users were not willing to playbor, they would not agree to the lusory contract. In the face of grand uncertainties in the world, in the rapid reontologizations of technogenesis, play is a very human act. To understand just how important playful design is for applications, I will use an example of what happens when social media undergoes “degamification.”

Degamifying Foursquare Foursquare , in its original format, was a gamified location-based application. In it, players could publicly check-in at locations and add users who also frequent the same locations. Players could get badges for discovering new places and receive reports on how many times they visited a location. They could also compete with friends for check-ins and badges. Additionally, players who spent time in specific locations can be crowned “Mayor,” creating friendly competition. The Foursquare API also drove other gamified

applications such as Cashsquare , a Monopoly-like game that allows players to “buy” real-world locations and then generate digital cash based on check-ins at those locations. Interestingly, Foursquare abandoned many of its core game mechanics and split into two separate applications with disastrous results. In a massive 2014 update, Foursquare's development team changed the gamelike aspects of the app. They created a new social application called Swarm to appeal to people's playful impulses. This left Foursquare to become more focused on location-based advertising and searches. Gutting the social game mechanics of Foursquare turned out to be a mistake. Users abandoned the application in droves. Interestingly, the lack of game mechanics in the “new” Foursquare reduced the motivation to use it (Hu, 2014). The benefits that seductive architecture offers social media becomes starkly apparent when developers attempt to abandon gamification and playbor. In the original Foursquare , nobody won; the mechanics aimed to continually drive playful traffic. Originally, Foursquare facilitated playful social networking across urban spaces. Them, the application split into two. Foursquare shifted its ludic mechanics to Swarm , an entirely different application. The result decontextualized Foursquare and broke the spell of playbor. While a Foursquare user and a Swarm player might be the same biological individual, and the spaces inhabit might overlap, they become radically different agents. Someone using degamified Foursquare is simply a user building up informational space. Swarm users are also networking, but their actions are playbor. The network architecture of each interface creates separate identities that may cohabitate but never coexist: the player is motivated by play, the user is not. Without gamification, there is no longer the hybrid user–player subject position needed to motivate playbor. Foursquare , after it abandoned its cherished game mechanics, no longer provides ludic framing – the lusory reontologization of users' spatialities. Digital labor is present in the new Foursquare , but seductive delight is absent. The result is a decrease in user motivation to engage in social and spatial actions through the application. The playful, seductive, and profitable world Foursquare

once gifted to its users had become decidedly quotidian. Foursquare was in danger of losing its primary meaning without play. Journalist Dickson Otieno (2014) bemoaned the changes: You remember the days when you always wanted to check in somewhere new, beat your friends and become Mayor of your hostel, school or the cafeteria nearby? Well, they're gone totally. Foursquare decided to split earlier in the year to two apps: Swarm (some yellow thing) and Foursquare (a different nonsensical app). Swarm tries to maintain the good old original Foursquare but no one seems interested. By degamifying, Foursquare broke the lusory contract of playbor. People suddenly wondered why they were using the application, at all. Blogger David Weekly (2014) wrote a breakup letter to Foursquare, stating: “you've failed at everything you were once good at. You didn't stay true to your roots.” The original Foursquare did not identify itself as a game; rather, it was a location-based social application. Still, there were numerous gamelike elements in Foursquare – ones that utilize seduction to circumvent the quotidian nature of social apps while still marinating nongame status – adding numeric values to friends, adding titles and progression to the player's account, and adding the use of avatars and icons all smack of game mechanics. Foursquare provided the possibility of play to its fans while removing itself from the ideological aspects of gaming. Users were playboring, but they were also networking and exploring their urban environments. It utilized seductive design as a potentiality, not an ultimatum – the mobilization of playbor was the primary goal of its mechanics. The user–player acted on their desire to continue the ludic negation of spatiality, to contextualize, consume, and commoditize their spaces. Through the original Foursquare , they were enabled to reontologize their everyday spatiality into a playful mobility (de Souza e Silva, 2008; de Souza e Silva & Frith, 2010). Motivation and desire, in the case of gamified environments, is more than just a marketing goal or

a cognitive clind'oeil : it is a necessity for actualizing the potential of seduction on a spatial level via the ludic interface. In the previous version of Foursquare, players could compete for expertise on a specific location (a “mayor” is a person who has checked into a space more than others). The social capital imbued by a mayoral badge only pertains to other players of Foursquare . The social capital and game capital accrued by players in the battle for mayorship was the primary seductive mechanic that encouraged multiple visits to a location. The badge signified expertise, and it also signified that a user was an expert on a specific location. The mechanic aimed to direct social interactions. Other players could seek information from the “Mayor” of a location, and thus increased the rate at which a Foursquare player could create new connections. The mayoral badge was an integral part of Foursquare's former gamified ludic interface – it directly tied users to both the ludic interface of Foursquare and its spatial game mechanics. By embedding a badge-oriented mechanic into locations, Foursquare created a separate context for visits to that location. What was once a coffee shop or museum became a node for accumulating points. Points translate into economic capital for the designers of Foursquare and its users. The mayor badge is just one example of how gamification produces playbor; it pulls , rather than pushes, people into action. Foursquare's changes and subsequent decline are a stark representation of how a gamespace is not able to survive once seduction ceases to exist. Utility, it appears, is not enough. The lusory context of playbor was absent, and it was playbor that users loved: checking to compete with friends and strangers. Weekly (2014) states: Every once in a blue moon, when the gods of your mystical gatekeepers permitted, I could steal a date with the old Foursquare and succeed in checking in at a place. But then most of the time, I would get the bizarre notice: “You can't check in via Foursquare. You must use Swarm.” A product that willfully refused to perform its core task. A pencil unwilling to write.

The metaphor of a degamified social application becoming “a pencil unable to write” is telling; it is a tool that no longer serves a purpose for users. A primary mechanism is missing from the technical ensemble. Without play to mitigate the anxiety and alienation of digital labor, working within the constraints of these applications become devalued for users. Play oils the gears of extractive architectures, but it also is the guiding principle behind the success of execution architectures, as well. We need playbor more than we need labor; we need it to make sense of the time we spend on apps like Facebook , Foursquare , Reddit , and Twitter . Upvotes, retweets, friend lists, personal profiles, check-ins, karma – all of it helps us negotiate our relationship with protocol and control. Perhaps this is why critics of gamification and playbor find the combination so vile: they see it as the rose-colored glasses that drive surveillance capitalism and all of its ills. Still, playbor is not a technique of force; users and players willingly employ playbor to make sense of a world where “checking out” of the digital economy has severe consequences.

Platform Capitalism and the New Labor Market Shoshanna Zuboff (2019) notes that surveillance capitalism claims to require “freedom for ignorance.” In other words, people need to be free to ignore the extractive and execution architectures surrounding them. The adage goes back to the myths of the free market, something so complex that it comprises an “unsurveyable pattern” (Zuboff, 2019, p. 497). In the bounds of economic complexity, people must make choices with limited information, which harkens back to Herbert Simon's conjecture that people need a guiding structure to make decisions in their self-interest. Thus, the old dream of cybernetics: computation used as beneficent control, not exploitation. So long as choice is present, freedom remains. However, things are never that simple. Zuboff (2019, p. 497) points out that “surveillance capitalists produce the compulsion toward totality. Total information tends toward certainty and the promise of guaranteed outcomes. These operations mean that the supply and demand of behavioral futures

markets are rendered in infinite detail. Surveillance capitalism thus replaces mystery with certainty.” Seductive architecture works both ways: encouraging playbor ensures that the digital economy remains stable by keeping its users stable. Surveillance capitalism does not simply allow play; it relies on it. The digital labor market is changing drastically, and playbor is no longer just for gamers and the hybrid user–players of social media. Participation is the “oil” of the digital economy, and it becomes increasingly difficult to tell the difference between what constitutes paid labor and labors of love, so to speak (Bigge, 2010). In the Stack, human-interface interactions support the datafication of all aspects of human life, and gamification's mode of playbor provides a negotiation tactic that encourages participation. Users and players are crafted subjectivities, applied through the seductive design and protocol. The same stands, of course, for all digital laborers – diligent producers are made, not born. A gamified technogenesis spreads, it becomes difficult to pin down where the player ends, and the user begins. Nick Srnicek (2017) suggests that the digital economy is more far-reaching that tech companies and stocks. Its growth is based on the limits of physical capital, when resources and traditional labor begin to dry up, resulting in a shift away from production. He states “with a long decline in manufacturing profitability, capitalism has turned to data as one way to maintain economic growth and vitality in the face of a sluggish production sector” (p. 6). David Harvey's (2006) “uneven geographic development” of capital effects even the Stack, as disruption in the flows of information and labor have farreaching consequences: if one layer shrinks, the whole structure could topple. So, production must continue, and producers must be willing. The digital economy drives major changes in the way production works: “collective cooperation and knowledge” become valuable, traditional workers become “knowledge workers,” the labor process becomes immaterial, and the resulting commodities become immaterial – a sea of content, knowledge, affects, and services (Srnicek, 2017). In turn, the economy becomes focused on production and ownership of information. The Stack, as a system of governance, works as a megastructure of connected layers ferrying

and transforming information. Capitalism, then, becomes reliant on sustained surveillance and the platforms that perpetuate it. Platforms are “digital infrastructures that enable two or more groups to interact” and form “intermediaries that bring together different users: customers, advertisers, service providers, producer, suppliers, and even physical objects” (Srnicek, 2017, p. 43). Platforms also produce and are reliant on “network effects,” which boil down to a simple equation: more users equals more value. Platforms work via a domino effect, “more users beget more users,” and they are designed to be seductive intermediaries between the layers of the Stack: “in their position as an intermediary, platforms gain not only access to more data but also control and governance over the rules of the game” (Srnicek, 2017, p. 47). Part of this game is making production as “lean” as possible. Srnicek (2017, p. 76) states that “lean platforms operate through a hyper-outsourced model, whereby workers are outsourced, fixed capital is outsourced, maintenance costs are outsourced, and training is outsourced. All that remains is a bare extractive minimum – control over the platform.” In this model, digital laborers need to be interchangeable, malleable subjects. As soon as a “gig” opens up, it needs to be filled. Every platform needs more bodies and minds to generate and sort data. The role of a digital laborer resembles the unenviable position of unskilled “day laborer” rather than the old idea of an “employee.” Srnicek (2017, p. 78) points out that “the gig economy simply moves these sites online and adds a layer of pervasive surveillance.” Digital laborers must have the capacity for rapid change, as platforms force constant individuation. As we explored earlier, players are innately willing don new identities and skill sets depending on the game. They are the ideal “individual” for the shifting protocols of platform capitalism. Thus, the labor market is increasingly becoming a playbor market as the gig economy becomes gamified. Online work programs like Figure Eight (formerly Crowdflower ) and Amazon's Mechanical Turk (nicknamed MTurk ), specializes in crowdsourcing: using remote laborers performing discreet tasks for which automation has yet to provide a solution. Jeff Bezo's jokingly called it “artificial artificial intelligence,” referring to the system's namesake, a fake chess-playing “robot” that was a hidden human

puppeteer (Crockett, 2019). Figure Eight specializes in data annotation, while MTurk provides the “human-cultured” data fed to research algorithms. Jaron Lanier (2013, p. xxii) notes that this new labor market, born of big data, is one the underlying structures of the “AI myth:” machine learning and AI are “repackaged” human effort. To maintain the illusion that algorithms are truly “smart,” companies need humans to provide and contextualize data on a massive scale (Lanier, 2013). Big data and dataveillance form the primary reasons for gamification's attempts at creating a “living simulation” that can produce better, more contextual data patterns. In this market, each unit of labor is designated according to time and tasks performed. Digital surveillance of tasks is necessary for payment, and workers submit to tight time restraints for a menial reward. One of the primary issues, of course, is keeping up motivation for repetitive and meaningless tasks. It is very difficult to make any viable cash using MTurk, with the most successful “Turkers” building mods and scripts that alert them to well-paying “human intelligence tasks” (called HITs); only a few workers can summon the interest or time to earn more than $2 an hour (Crockett, 2019). MTurk's interface is no-nonsense, clearly the optimized vision of a programmer. Gamification, of course, was proposed to be a solution to motivational problems on these sites. In one experiment, researchers used a different, gamified interface for work on CrowdFlower (now Figure Eight ) and the results were telling: task completion rose from internal incentives such as points, badges, and leaderboards, with no further monetary rewards (Feyisetan, Simperl, Kleek, & Shadbolt, 2015). Shortly after CrowdFlower became Figure Eight , it began offering Dedicated , a data management package with gamified workforce management tools complete with points and leaderboards (“Figure Eight Dedicated,” 2019). The more repetitive the task, it seems, the more likely it is that gamification will be implemented. The Quixotean brand of playbor that gamification allows seems to work for both playborers and platforms. Gamification' slusory contract might be sustainable, but is it fair?

The Asymmetries of Playbor

Multiple new crowdsourcing companies have picked up the gamification mantle, investing in the reontologization of playbor. When digital labor entails hours of repetitive tasks with no personal attachment or gain, gamification can help add intrinsic value. Playbor, once again, is instituted as a shared mechanism of survival: it invests platforms with repeat users and simultaneously provides these users with purpose and context. Both Uber and Lyft , the dominant ridesharing platforms, use labor-side gamification to encourage driver participation. Looking at Uber , which has “undertaken an extraordinary experiment in behavioral science to subtly entice an independent work force to maximize its growth,” we can see how gamification can butter both sides of platform capitalism's proverbial bread: both the drivers and passengers are immersed in a gamified environment (Scheiber, 2017). On the passenger side, users have interactive maps, profiles, ratings, and rewards. However, in 2017, Uber implemented a large update for drivers introducing gamification. Uber employs “ludic loops” such as badges, ratings, and something called a “forward dispatch” that encourages “binge driving” (Olyslager, 2017). Journalist Paul Scheiber (2017) notes “to keep drivers on the road, the company has exploited some people's tendency to set earnings goals – alerting them that they are ever so close to hitting a precious target when they try to log off. It has even concocted an algorithm similar to a Netflix feature that automatically loads the next program, which many experts believe encourages binge-watching.” All of this was done “without giving off a whiff of coercion,” after Uber was losing too many drivers (Scheiber, 2017). The system was so effective that Uber had to integrate a “pause” button to prevent drivers from playboring too long (Olyslager, 2017). The need for a failsafe in gamified design highlights an odd consequence of gamification in the ridesharing economy. While truckers, who are traditional employees, regularly drive for over 15 hours, this traditional job has no true limits on the exploitation of labor. Disciplinary surveillance measures are often used to keep truck drivers in line, with sensors implanted in the truck to ensure that drivers are efficient as possible (Baranuik, 2018). However, Uber drivers (and most other crowdsourced labor) are not

bound by any contract. Uber had to build an addictive, gamified ecology to keep drivers hooked into their loop. In an online piece for The Guardian , former Lyft driver Sarah Mason (2018) notes that she was “weirdly drawn in” to the gamelike gig of driving. Lyft, in addition to using points and badges, also archives driver performance in the form of a “Weekly Feedback Summary” that aggregates passenger ratings. Mason's score dropped from “a 4.91 (‘Awesome’) to a 4.79 (‘OK’), without comment” and she immediately changed her tactics to match the non-transparent score sent by Lyft : For the next several weeks, I deliberately avoided opening my feedback summaries. I stocked my vehicle with water bottles, breakfast bars and miscellaneous mini candies to inspire riders to smash that fifth star. I developed a borderline-obsessive vacuuming habit and upped my carwash game from twice a week to every other day. I experimented with different air-fresheners and radio stations. I drove and I drove and I drove. Mason points out that “the language of choice, freedom, and autonomy saturate discussions of ride hailing,” yet the supposed freedom, imparted to drivers through game mechanics, is suspect. The use of seductive architectures to drive labor in the digital economy pulls pages directly from the early research in cybernetics, proposing that illusory choice provides an environment where the “right decision” is bound to information parsed and served by game mechanics. Mason (2018) points out that the “apparent freedom poses a unique challenge to the platforms' need to provide reliable, ‘on demand’ service to their riders – and so a driver's freedom has to be aggressively, if subtly, managed.” The results are often too effective. She states: The battle to beat the quota also transformed a monotonous, soul-crushing job into an exciting outlet for workers to exercise their creativity, speed and skill. Workers attached notions of status and prestige to their

output, and the game presented them with a series of choices throughout the day, affording them a sense of relative autonomy and control. It tapped into a worker's desire for self-determination and self-expression. Then, it directed that desire towards the production of profit for their employer. The affective capacities of playbor hearken back to the idea that play must be self-guided, while games impart structure. Internal feedback mechanisms have to allow playborers to contextualize their own lives and desires as they carry out tasks. Yet, profit-based algorithms propel the “rules” of the Lyft's gamified platform. Mason claims that Lyft uses vast amounts of data, generated from the application use from drivers and users, to inform real-time game mechanics and scores. The “carrot” is based on “informational asymmetries,” in which the platform has a direct advantage over the driver, using design to inculcate low-cost labor (Rosenblat & Stark, 2016). In their study of Uber drivers, Rosenblat and Stark (2016, p. 3758) note that “the information and power asymmetries produced by the Uber application are fundamental to its ability to structure control over its workers; second, the rhetorical invocations of digital technology and algorithms are used to structure asymmetric corporate relationships to labor, which favor the former.” These asymmetries can help digital laborers enter a lusory contract on lean platforms like Uber and Lyft , but the playing cards are inherently stacked against them. In her study mechanics employed by gambling and casino game designers, Natasha Dow Schüll (2012, p. 76) calls the fraught relationship between gamblers and games a type of “asymmetric collusion,” which occurs between the design techniques and the users. The ludic relationship between the two is “forged not through coercion, but through a kind of collusion between the structures and functions of the machine and the cognitive, affective, and bodily capacities of the gambler.” The mechanics require willing participation, and turning from “from coercion to collusion” fits with Deleuze's concept of a control society, “a ‘mutation of capitalism’ in which a logic of discipline and restriction has given way to a logic of

control whose protocol is the regulation of continuous and flowing movement of bodies, affects, and capital” (Dow Schüll, 2012, p. 76). In truth, gamified design holds many similarities with gambling. Keeping up “addiction by design” requires constant action on the part of the user, this action is measured for performativity, and minute to minute changes require a constant feed of “live data” (Dow Schüll, 2012). Also, as in gambling, the algorithms in place to keep players playing are opaque. As Mason (2018) pointed out, the algorithms generating drivers' scores and badges can change at any time, leaving playborers scrambling for higher scores, not necessarily higher profits (for them, anyway). As with earlier gamified apps like Ingress, there are innate imbalances between applications and the player communities that form around them (Hulsey & Reeves, 2014). So, imbalances in information lead to an imbalanced form of collusion between platform and user, player and playborer. Wired magazine's look at TaskRabbit , a crowdsourcing platform where “runners” cast bids for manual labor tasks, reveals that “to keep the rabbits scampering, the site employs some serious game mechanics” (Tsotsis, 2011). The runners see a “videogame-style progress bar” logging points that are needed for them to level up. The points are awarded for accurate bids in labor price, bidding on a task quickly, recruiting other users, and other activities beneficial to TaskRabbit (Tsotsis, 2011). According to journalist Alexia Tsotsis (2011), the points needed to advance stack exponentially and “its competitive dynamics – the bidding, the points, the reviews – have created an elite cadre of runners who tend to fit a very particular personality type.” By setting workers against one another in pursuit of points and leaderboard positions, TaskRabbit encourages them to underbid prices for labor, where the runners drive down total prices in pursuit of points (Tsotsis, 2011). Once again, the point system can easily be tweaked by TaskRabbit to benefit their cut of the runners' labor, potentially driving prices to almost nothing. While playbor may be useful in reontologizing labor into playbor, it does not abandon the most prevalent alienations within surveillance capitalism – and, as seductive architecture proves its worth, more and more environments become colonized by gamification.

Playbor is not just present in social media or the gig economies of crowdsourced labor. It also infects the workplace. Trello is a popular project management tool, and it is widely accepted by multiple industries, including software design, IT services, education, retail, management, and health care (“Trello,” 2019). It allows managers and teams to set up their own goals, points systems, and milestones to move projects along quickly. On the Trello blog, Benjamin Brandall (2016) writes, “you get more done when you gamify your life” because “difficulty doesn't put you off if it's supplemented with rewards.” Brandall's system boils gamification down to a few steps such as: “indications of incremental progress (experience bars); multiple long and short term aims (main quests and side quests); rewards for effort (gold, loot, and experience); rapid, frequent, and clear feedback (activity explained on screen – “level up!”); Uncertainty (rare loot and bonus gold)” and “other people (multiplayer online games).” These are common mechanics used in other gamified applications aimed at labor management at traditional companies. Badgeville and Bunchball , two other consulting firms that provide user and employee management systems, use similar ludic loops. However, as we have seen, gamification emerges from a long history of research into technology's role in human choice and motivation. A key aspect of gamified platforms like Lyft , TaskRabbit , and Trello is that users enjoy them. This paradox is equally true of social media platforms like Facebook , Instagram , Twitch, and Twitter, all of which are gamified. Gamification requires a deep system of built-in choice and validation, a sense that playbor is paying off and players, users, or employees are advancing. It also requires the illusory nature of quixotic play, the sense that users are somehow advancing by resisting domination. To accomplish reontologization, seductive architectures borrow from one of the most engaging and problematics aspects of game design, a process that I call the meritocracies of the grind .

Meritocracy, Games, and the Grind

Meritocracies of the grind combine two gameplay processes: ranking and progression. These mechanics may seem like a simple and obvious combination, but both design tropes present one of the most powerful draws for gaming. Almost every major game sold combines both, to the point where indie games like Journey and Flower , which eschewed meritocratic grinds, were considered revolutionary. As we saw in previous chapters, game theory primarily dealt with games where there were winners, losers, and ranked outcomes. Gamification follows suit, building up complex, opaque systems of competition and ranking that drive playbor. Meritocracies in gaming have always been problematic, largely because they spawn toxicity and obsession. Christopher A. Paul (2018) notes that meritocracies create inherent inequalities between people while claiming to promote skill and dedication. “Meritocracy is blind to context,” Paul states, “meritocracy shelters us, individualizes us, and strips out the larger context in which we exist. For people… who were gifted head starts, meritocracy instructs us that we have earned our place and deserve to have more than those lesser people who are unable to reach our heights” (pp. 29–30). Meritocracies in games thrive on two elements: effort and skill. Out of the two, however, skill is often the more valued. Paul (2018, p. 37) writes “in the language of meritocracy, competitive mode is absolutely designed in a manner that ensures toxicity as an inevitable by-product because it is based on a system where players are boiled down to their net worth through the creation of a set of numbers that are supposed to represent their true skill. Skill is seductive and enticing.” The toxicity boils down to punishing “weaker” players regardless of context. Players focus on forming elite cadres, demanding and receiving respect from their communities. Looking at the “elite” users of Mturk and TaskRabbit , we can see how meritocracies become a tool of production: “ranking systems, from games to businesses, tend to obscure the logic of their judgments and become self-insulating under the premise that those at the top are the best and most talented, and have earned their rewards” which includes the validation that they have earned their place and are able to “pass judgment on their lesser” (Paul, 2018, p.

37). In past chapters, I have noted that player and user dossiers are considered powerful game mechanics, and the reasons link to meritocratic protocol. The personal archive of player shows, through statistics, their overall worth. Because their worth is generated by gamic measurements, failures and successes in a game become personalized at the structural level. To be blunt, self-worth becomes algorithmic. In-game design, ranking mechanics are often opaque, generated by a “secret formula” that paces certain players over others with no regard to the structural inequalities of the system. Ludic meritocracies thrive on asymmetric collusion, driven by arcane mechanics that personalize winning and losing and demand fierce competition for personal worth. However, in the context of playbor, meritocracy only works in there is something visible to be gained, and thus we come to another key point of how gamification ensures production – an element known as “the grind.” The study of the grind has been a primary interest in the intersection between play, productivity, and labor. The grind comprises sets of ritualized, repetitive actions by players in pursuit of in-game (and metagame) capital and progress. The grind, and related practices such as gold farming, highlight how gameplay and gamespace intersect with playbor. In gaming, production is a concept that links closely with power but focuses on how power plays out in the actions of players as they navigate gamespace. Grinding is an innate part of gaming that involves repetitive, ritualistic actions by players to advance or progress through the game's mechanics. The grind, then, is the “playbor” aspect of gameplay. The grind is also the mechanism by which players exercise power within the confines of game mechanics, and then develop and make meaning concerning their gameplay. If we liken games to a maze, grinding is the navigation of twists, turns, challenges, and eventual rewards. Therefore, the grind encompasses gaming's productive relations between capital, ritual, meaning, and playbor. When combined with meritocracy, the grind ritualizes worth, ensconcing labor into an easily swallowed pill that shows “how far you have come” from where you started and how you compare to others. When combined with platform capitalism, it produces maximum engagement even as rankings and progression are dealt out by

mysterious algorithms and mechanics. What results is the creation of false intensity, a self-inflicted obsession with advancement at all costs. Graeme Kirkpatrick (2015) outlines the effects of “ludefaction,” or the negative side effects of applying games and game mechanics to labor practices by targeting applications that turn workdays into a series of points, levels, and feedback mechanisms. The mechanics are frequently used by applications like Trello , Badgeville, and Bunchball and other gamified apps that provide customized project and workforce management solutions. As stated earlier, commonlyutilized design tropes are goal-setting mechanics, real-time feedback, positive rewards and progression to make workforces engaged on the job or keep consumers engaged with the brand (Mintz, 2011; Zhang & Fung, 2013). “Work comes to seem more attractive even as it makes more intense and invasive demands on its human subject,” Kirkpatrick writes. “Beyond this, however, ludefaction grasps the way in which gamification intensifies exploitation in the, probably unprecedented, development of allowing power to tap into the radical imaginary, that is, the facility we have for creating an alternative, better world” (p. 1). With applications like Trello , the body of the playborer is reduced to a series of points and levels determined by the amount of time they spend doing certain actions: checking and responding to e-mail, completing tasks and attending meetings, and other actions categorized and rewarded. All the while, the entire team or company is aware of each person's position within the grind, keeping those who fall behind in a state of constant activity as they alter their tactics to advance. The technologized body, rooted in the meritocratic grind, becomes the generative mechanism for gameplay. Kirkpatrick's take on gamification identifies it as an “ambivalent” practice, one without clear benefits and more than a few dangers. However, gamification's rapid colonization of the digital economy depends on whether play can continue to mitigate the downsides of digital labor through game mechanics. The best way to examine why meritocratic grinding is so prevalent is to examine it in its native context of gaming. The grind is the process by which players produce intrinsic capital within games and how this capital is instrumentalized for

extrinsic uses in the broader economy (Dyer-Witheford & de Peuter, 2009; Steinkuehler, 2006). Traditionally, grinding involves working through content and ranking systems for social and in-game currency. Another, more controversial, mode of grinding is “gold farming,” which involves grinding and selling in-game currencies and objects for cash. Both are modes of playbor within games. In the context of gaming, meritocratic grinds involve the use of playbor to build intrinsic meaning into in-game player economies. The grind is primarily the use of repetitive mechanics to create ritualistic behavior. Grinding involves collecting objects, points, and other positive reinforcements via gameplay and it shows up in games and gamification. For example, players in gamified “brain training” apps like Lumosity must play in increasingly efficient ways to collect, or grind for, “Lumosity Points” that supposedly represent their “intelligence.” Then they are ranked next to others in their demographic group, encouraging them to get “smarter.” Similarly, TaskRabbit pits runners against one another to level up through underbidding, driving down the worth of their labor but increasing their worth in the app's meritocratic grind. Designing successful grinds has been perfected over many years by games, from leaderboards in arcades to vast, collective systems of ranking for millions of players. In large multiplayer games like World of Warcraft , the grind drives the player capital, social and economic – users must collect and craft items to sell on auction houses. The scarcity of items and the benefits that items provide influence the price they bring on the auction, garnering them rank and position within their guild and granting them access to better gear. Grinding is time-consuming and exists to place boundaries on player ranking and game economies, gatekeeping content and preventing the deflation of goods. It is a primary cause of collisions between social capital, game economies, and everyday economies (Dyer-Witheford & de Peuter, 2009; Steinkuehler, 2006). Julian Kücklich (2009b) highlights the process of gold farming as exploiting the grind for money and bypassing – or “creatively interpreting” – game economies in order to accrue fiat currency. Like real-world economies, resources in games gain value through scarcity. Some resources are easy to find, and some are hard. Like cheating,

goldfarming, and real-money trading (RMT) address scarcity through a “shadow economy” of labor that provides game goods for either real money or paid labor (Harambam, Aupers, & Houtman, 2011). Steinkuehler (2006, p. 203) gives an example of gold farming where individuals are hired by a virtual currency selling company to spend long hours in-game to cultivate currency (in this case called “adena”) or resources which illegally are sold online: As best as I can piece together, Chinese adena farmers normally work 12-hour shifts…with two people to each computer so that the in-game character they share is always online. Typically, they must collect 300,000 adena per shift in exchange for their daily wage of about US$3. It may not sound like much, but compared to China's average yearly income of US$316, it's rather lucrative work. Like everyday economies respond to black markets, an in-game economy must respond to counterplay such as RMT and gold farming. Designers do this by altering regulations, laws, and rules. Alternatively, a developer could embrace the practice. Increasingly game rules and regulations include deliberate crossovers between global economies and game economies. For example, Blizzard's Diablo III provided players with a real-time auction house where ingame currency can be converted to dollars via a fluctuating rate. Like fiat currencies, the price of in-game gold and items fluctuate based on scarcity and the strength of the currency in question. 2 Also, many games are criticized for microtransaction, linking in-game assets to cash. As Dyer-Witheford and de Peuter (2009) point out, gaming is not separated from the larger flows of capital – it merely participates in these flows via unique circulations of gameplay in recursive, imaginary spaces. Gold farming and RMT exist because the grind can be timeconsuming and unpleasant, problems that are often designed around by introducing competitive meritocracies. Both mechanics become ensconced in the player's vision of his or herself within the context of gameplay. Scholars point out that the reason for the grind is the

“joys” of ritual in the process of meaning-making (Burroughs, 2014; Gazzard & Peacock, 2011). In other words, meritocratic accrual in gamespaces embodies more than just raw economics and money. Beyond the obvious economic market – where game development companies make money from individual games – the players engage in a larger, less tangible economy of social capital, and personal meaning accrued through gameplay. Games involve repetition and rules that contribute to both ingame economics and external economics, but there is also a social realm to the grind: the creation of ritual logic through recurrence and repetition that then links to a general sense of player well-being and transformation. Gazzard and Peacock (2011) maintain that there are two meanings to the repeated actions that constitute the grind. One involves the function of the game itself (the actions are needed to make the game work). The other is the creation of a ritual, the “conscious awareness” of repeated actions and the “deliberate execution of them to make a special meaning…These recurrent actions are characterized by being mainly reactions and responses, and may be seen as being ‘automatic’ in their operation and awareness as these are the thrills and pleasures of being immersed in the game” (Gazzard & Peacock, 2011, p. 505). These two meanings combine to form a “ritual logic” to the grind, an innate understanding of how and why the grind moves the game forward. Gazzard and Peacock explain, “ritual logic is about the way ideas of ritual move through the culture and its artifacts, and inhabits the minds of the members of the culture…[it] is about the way a videogame player understands what ritual is, what it does, and how it operates” (p. 501). When combined with meritocratic grinding, ritual logics are the transformative process from repetitively collecting and arranging items in service of meaning and personal worth. In this manner, the grind instills some sense of innate accomplishment to gameplay. At the same time, through meritocracy, it also encourages personal measures of worth attached to the methodical and recursive actions sustaining gameplay. The transformation of repetition into ritual is an important aspect of gaming because it reveals the deep pleasures of instrumentality inherent in gameplay. It is the root of games as technologies of the self, allowing players to

construct their own identity throughout play. Instrumentalizing the logic of repetition gives meaning to the broader impact of the metagame, and the systems of capital that motivate players to advance and compete. Meritocratic grinding is a collective way of making meaning on a broader scale. Players, as a collective, dedicate their time and efforts to solving problems in-game. Neil B. Niman (2013, p. 38) states that “righting a wrong…or making the world a safer place are all examples where multiple individuals have contributed to a single problem…Because the problem is so large and the solution requires the help of many, working toward a solution confers great honor.” Recognition of the meritocratic grind between players provides games with their allure. The pleasure of defeating a boss or defending a kingdom is enhanced by the grind that precludes it. The grind, and gameplay in general, is considered socially collective, providing both intrinsic and extrinsic rewards. In-game, players cultivate a ritual logic via the grind. On a broader scale, there is a sense that through gameplay, many players are collectively working toward the goal of problem-solving for specific games. Collecting social capital through grinding is most obvious in multiplayer games; however, single-player games often develop communities that explicate problems through walkthroughs and “Let's Plays” (LPs), where play sessions are shared via gamified platforms like Twitch and YouTube . LPs are, in their own right, an exercise in playbor since the hosting sites and the streamers themselves collect capital from the advertisements and views of their recorded sessions (Postigo, 2016). Thus, playbor often falls under the shroud of “informational capitalism,” which extends the bounds of class and capital beyond the scope of material or economic labor and forms the basis of platform and surveillance capitalism (Behrenshausen, 2007; Fernández-Vara, 2009). Informational capitalism exploits the labor of anyone who creates or recreates informational content in digital spaces such as social media sites and message boards – under informational capitalism, even creativity and play taking place in open public can be harnessed and extracted (Behrenshausen, 2007). Informational capitalism and playbor tie to the socio-economic transactions between players, and game

companies within gamespace. These transactions, or course, are tracked and manipulated through the design and redesign of the game. They form, alongside surveillance, the basis of profit in gamified environments. Players produce capital by grinding for micro-transactions and also by producing data through their grinding activities. Players' collective grinding activities in gamespace can be extracted and harnessed by the gaming industry itself. In China, there is a “secondary industry” centered around the socio-economic activities of the largest Chinese guilds in multiplayer games (Gazzard & Peacock, 2012). Zhang and Fung (2013, p. 38) point out that “as the secondary industry has evolved…This changing regime of value has given rise to bio-political control of consumer labor and, along with state control, is drawing gamers into the tug-of-war between entrepreneurial invention and labor exploitation.” Informational capitalism's rendition of the grind is often practiced between players. As noted by Molesworth (2007), nonviolent and trade-oriented players of the space exploration game EVE Online , known as “industrialists,” are targeted by other players. EVE Online's developer condoned the attacks against nonviolent players who engage in resource-harvesting and trading, because the raiding helps drive the economy and social interaction. The industrialists' deep knowledge and informational labor in the economy of EVE Online designated them as sources of exploitation to others, creating an in-game microcosm of information capital in a grind-based meritocracy. Players in EVE Online were watching one another's progress and using that information to turn the grind to their advantage, strategically manipulating trade prices using lateral surveillance. Examples like this one reveal that, in self-referential gamespaces, playbor still suffers from the same tensions as platform and surveillance capitalist processes. This complex model of playbor and meritocratic grinds in gaming also sheds light on the conditions of gamification and its modes of production. When gamified, the grind cultivates ritual behavior via gamified play. It also produces valuable data and valuable behaviors. However, the ritual logic behind repetitive actions also creates a larger, goal-based community around the gamified application that

aids in providing unique motivations in extending gameplay. This effect is accomplished by folding ritual-inducing behaviors and social rewards into the game's architecture. Farmville , an application that involves running a socially-linked farm through Facebook , is an example of a gamification that combines the grind with social motivations. Data from gameplay is harvested through Facebook , which hosts the game, revealing both interpersonal networks and behavioral patterns ensconced in Farmville 's ritual logic. Burroughs (2014) points out that Farmville 's ritual logic involves playbor that leads to a “feeling of contribution.” Burroughs explains the grind as a “digital ritual” that gives meaning to the recursive actions of players and creates a sense of community. For Burroughs, the grind is largely a question of design. In a sense, the grind and the resulting rituals enhance the “architectural structure” of the game. The pleasure of the grind results from a shared sense of agency within the context of game mechanics dispersed through the seductive design. Burroughs (2014) states that Farmville players derive “a great deal of pleasure” from the grind. Players collect and farm seeds, but they also collect friends who will help with farming their crops. This creates a favor economy linked to social capital. The addition of friends is a social grind that directly impacts the mechanic-driven grind of farming and selling crops. Additionally, they derive social pleasure that is “architecturally driven” into the gamespace. The gamified grind and its resulting extrinsic social pleasures occupy a “liminoid phase” where subjective identities are blurred – they become “malleable” (Burroughs, 2014). In other words, the identity of the user–player becomes indistinct and able to take on multiple successive roles and identities. This malleable subject exists between “play” and “labor.” Playbor inhabits an “in-between space” that is “meaningful for stepping outside the structures of power and constructing social bonds” (p. 162). Burroughs suggests that these liminal spaces are useful for producing labor-like behaviors without the onus of labor. However, as Kirkpatrick (2015) argues, ludefaction – the “fracking” of the radical imaginary concerning play and labor – may result in increasing demands on the playborer such as longer work hours, faster tasks, and more speedy interactions. These

demands are hidden behind the curtain of gameplay, where user perceptions of abuse and coercion are reduced to a manageable, lusory status.

Conclusion This chapter sought to reconcile the extractive and execution architectures of gamification with the concept of play and labor. While asymetries exist in playbor, it also presents a type of relational management between computational protocol and everday life. While seductive architecture eschew coercion, it still relies on asymmetric collusion between the player and the application, using informational advantages to drive increased rates playbor across multiple platforms and industries. While many scholars criticize playbor as the product of digital exploitation, I argue that playbor is a result of the quixotic play based in human-computer interactions. As such, playbor seems to be a necessary negotiation tactic within the increasingly tight boundaries of surveillance capitalism. Gamification's asymmetric collusion does resemble exploitative relationships between gambler and game, and it is based on meritocratic grinds that promote toxicity and intra-user competition. However, it also imparts some benefits to the user or player. Research also shows that injecting playbor into everyday labor reduces stress and heightens enjoyment – when skillfully designed in certain contexts (Herodotou, Winters, & Kambouri, 2015; Whitton & Moseley, 2014). Perhaps it is heightened enjoyment and reduced stress that are hallmarks of seductive power when deployed for production. While users and players certainly find some joy in the grind, that does not remove it from the circulation of power and control in gameplay. Playbor may be collaborative, but this does not mean that the meritocracies of the grind are fair. Moreover, this last section ends with the same question introduced in the first: is playbor exploitation, and if so, where is blame to be laid? It is clear that developer and designers craft finely tuned choice architectures aimed at transferring most profit to themselves. However, without seductive architecture, the digital enclosure would need to rely on disciplinary

techniques based in outright coercion. The concern with exploitation seems to be the core question when it comes to power and production in both games and gamification: what is the cumulative effect of seduction, surveillance, and meritocracy if they are deployed in the name of play? Does the fact that play is involved lessen the ethical impact, or make exploitation and control all the more heinous? In the final pages of this book, I will explore the problems inherent in attempting to control and direct play as a type of resource. 1

All games, not just digital ones, are powered by play. Play, as we have seen, is ambiguous; it can be beneficial or it can be dangerous and dark. Toxicity and rage are not unique to gaming culture. Sports and fan cultures can also produce violent outcomes. It is safe to assume that toxicity is present is nonludic cultural contexts, as well. 2 The RMT system in Diablo III was disastrous, causing many players to quit. Blizzard quickly removed the RMT auction house in subsequent updates. A clear example that linking the grind to fiat currency has to be done carefully.

Conclusion Gamification's ability to colonize quotidian space in favor of simulation marks it as a possibly dangerous technology; at the same time, the discourse surrounding gamification rejects force and domination. One thing is clear: Gamification only survives via the collective activities of users and players. These users, like cells in Game of Life , create and sustain monetized gamespaces that drive surveillance capital in the Stack. The question remains, still: “Why play?” Play is rather difficult to pin down; it inherently resists coercion but, when channeled through games, it entails an engaging form of submission – something I call seduction . Gamification, as noted in the introduction, attempts to nullify play's innate resistance to disciplinary techniques by using “antigaming logics.” Will these measures be enough to sustain a game that is not quite a game? Here, I address what the future of gamification might be. While gamespaces can be profitable, they are also inherently unstable. Gamification shies away from acknowledging itself as a game. Rather, it only uses small components, strategically placed, to nudge at optimal behaviors. At the same time, when play becomes an outcome, ambiguity and unpredictability will ensue. How gamification deals with ambiguity will determine its future as a set of effective design practices; however, the philosophy behind the design is rooted in certain discursive regimes concerning power, knowledge, and computation. This book answered four key questions about gamification: (1)

What place does gamification hold concerning games and play? Gamification borrows from games in an attempt to be a ludic technology of the self, a mode of using seduction to form “user–player” hybrid subject positions. It converts play into

playbor, a mode of digital labor that eschews coercion, but still engages in surveillance and behavioral modification. (2) What are the historical precedents to gamified applications and gamification? Gamification, like games, is born from attempts to create systems of simulative governance in game theory, cybernetics, and computation. (3) What are the conditions of knowledge and power that enable gamification? Gamification is a seductive technique directly linked to surveillance capitalism, aiming to use extractive and execution architectures to link all users in the Stack to repositories for raw data aimed at simulating and modeling behavioral futures. (4) How is gamification materially and socially instantiated, and what type of control does it entail? Gamification closely links to mobile applications and spatial surveillance. It relies heavily on the playbor of its users and players to harvest and convert data in a mode of environmental technogenesis. It entails a form of seductive control, rooted in channeling quixotic play as a lusory form of relationality with protocol. Each of these questions lead to a much larger one: “What is gamification, and why is play singled out as a technique for control?” To answer this, I proposed that gamification is a new take on everyday life, one that embraces playful-but-serious surveillance and introduces new protocol seeking to influence the categorical positions of both “user” and “player” as commoditized subjects that both relish and resist control. Gamification seeks to instantiate nondisciplinary protocol by introducing game mechanics into nonludic environments. Each chapter has covered a “lens” by which gamification can be magnified. I examine the discursive formation of gamification in relation to games and play (Chapters 1 and 2), the historical roots of gamification (Chapters 3 and 4), how gamification infects environments and evolves coopting bodies and turns them into hybrid user–players (Chapters 5 and 6), and how gamification reontologizes digital labor into playbor using monetized, meritocratic grinding (Chapter 7). Currently, almost all research on gamification

has focused on its definitional, practical, or ethical concerns. However, scholars and practitioners know relatively little about the possible effects or consequences of gamification. Apart from a few attempts to historicize gamification research has yet to produce a definitive account of a practice that is anything but “new.” This project takes a big step toward envisioning gamification as a valid theoretical term with roots in game design. Still, designing, defining, and criticizing gamified applications are only one side of the equation. The other side of gamification involves play , a subject that is often tiptoed around due to its complexity. Play is, in many respects, an ambiguous black box. In practitioneroriented research, play is treated as fuel – the motivational force that drives players to generate data. In Utopian ethical accounts, it is a pure and positive force that is being perverted by surveillance and platform capitalism. However, I think play is far from being exclusively positive or motivational. Play embodies the epigenetic change, the animistic desire to build, change, raze, and rebuild. Looking at how play can disrupt, decontextualize, reontologize, and even destroy systems bent on control is paramount to understanding the abilities of gamification, but it is also indicative of the limitations. Harnessing play is rather like controlling lightning – it can be done, but not without risk. Gamification's industry experts note that play is an unstable resource that requires expert design to direct. At every turn there are opportunities for users and player to exploit, counterplay, cheat, and generally implode the carefully balanced control protocols. In this book, each chapter worked to examine gamification through specific lens in order to divine why play is used to skirt disciplinary boundaries. With this in mind, I sought to unify the current disjointed atmosphere concerning gamification and play by solidifying it as a theoretical term. I do this by clarifying misconceptions about gamification's relationship with games and play, situating gamification as a design technique that relies on seduction and control via playful technogenesis, and suggesting that gamification involves the application of seductive architecture, the primary factor in altering subjects and environments in favor of

surveillance capitalism. I do not, however, suggest that gamification is exploitative, at least not to the degree of disciplinary applications employing surveillance-based protocol. It seems that gamification's primary product is playbor, a form of quixotic play that negotiates the boundaries of control between user and interface.

The Problem with Play Gamification is primarily able to monetize the movements of the body via spatial surveillance and control behavior through seductive architecture. In the case of health and fitness monitors, it is the movement of the body through space that generates data. In the case of behavior, there is a ludic negotiation between users and the app that serves to mitigate the anxieties and alienations inherent in the digital economy. The seductive contingencies embedded in a gamified environment direct desire, pushing the body toward an optimized set of lusory negotiations and contracts. Gamification's contingencies are always embedded within a technogenetic gamespace. Like games, its primary method of operation is productive gameplay twisted into playbor. However, playbor is not localized – it networks into the wider assemblages of everyday life. In applications like Pokémon Go , Ingress , Strava , TaskRabbit, and Facebook gamified interfaces utilize the networked nature of hybrid space to collapse boundaries between quotidian and ludic practices and linking the resulting gameplay back into wider networks of capital. This leads to the creation of new liminal spaces, ones where gameplay, surveillance, and seductive control overlap for the purposes of production. Ludological theorists point out that if life is to become the embodiment of play, then we humans must admit that all we have ever achieved in our short history as a self-aware species is a series of ever more complex finite games in service of the infinite one. This is the human mystery, an existence that freely and frequently alters its own modes of being and becoming. What play requires seems to be the opposite of what gamification seeks to accomplish. In its undirected form, play is a release from control, not a renegotiation of

it. In hitching itself to the ambiguity of play, gamification has most likely committed a fatal error: it has built its own obsolescence. Technogenesis and computation require sustained playfulness: both need the seeking, chaotic desired of humans to initiate changes and reactions. Yet true playfulness will engage every possible contingency, not just the ones considered optimal. If playbor is a negotiation, what happens when it breaks down? For example, Ingress needs its hybrid user–players to act with the ludic interface in order to create meaningful data. In turn, if players react against it, even slightly performing outside the boundaries set by Google and Niantic, they ruin the data's context. Because gamification sets narrow boundaries for players, it will always encounter the reactive end of epigenesis: it will need to change its mechanics. However, constantly changing or updating mechanics is not a long-term option. Players learn quickly; after all, they are inherently unstable subjects. Issuing new mechanics and failsafes that serve as “antigaming logics” will not change the tide of players who refuse the “user” category, and push against nudges and execution architectures to see where “capitalist games” break down. When these control tactics are exhausted, apps like Ingress will cease to be a tool for surveillance capitalism. Ingress will either be eliminated or evolve into what it was meant to be all along – a game. In the end, all future seductive architecture will increasingly have to account for the chaos of play. Sooner or later, seduction has to end. While gamified technologies may alter environments and practices, they also must deal with the chaotic players. Designers and developers will need to change mechanics constantly to account for shifts in the conditions needed to support playbor. When mechanics change, so do their logical outcomes. Gamification is in a precarious epigenetic dance with play, one that it will inevitably lose. While play seems to be many things, both strategies and tactics, any game cannot exit without the players' consent. Small acts of resistance and counterplay can damage, disrupt, and perhaps change the way surveillance capital currently works, and as a result, change the base structure of the Stack itself. Small acts of counterplay by large amounts of people can cause deep ripples in to the modeling and algorithmic processes, which corporations and

data-mongers use to influence us. It simply requires enough people refusing to play correctly, and finding the exploits. We have already seen the simple use of spamming and bots throw large institutions like Google into a tailspin. Oddly enough, we players have the right cheat, to test the game boundaries, and to push them so thin that they break. After all, this is our magic circle and our playbor. We can easily move from using playbor as a negotiated shelter from the strictures of surveillance capital to using gameplay an all-out attack on its darker, Pavlovian center. We just need to start thinking like players, not users. We can be players who will exploit the game to beat it, rather than submit to suspending the infinite game's rules forever.

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Index Advergaming, 54 – 55 Aerobics , 144 , 145 Algorithmic cultures, 24 , 92 , 99 , 101 – 103 , 162 Algorithmic protocol, 4 Alienation, 163 , 170 , 189 Ambiguous play, 46 – 49 Apple, 137 , 143 Apple Health , 149 Archaeology, 12 Architecture, 126 execution, 165 network, 126 – 128 seductive, 81 – 86 , 173 Artificial intelligence (AI), 92 , 95 Automation, 95 , 96 algorithms, 101 robotic laser pointer, 130 Betty Crocker, 51 Big data, 2 , 138 Big picture, 5 Biopolitics, 123 – 126 , 137 Biopower, 123 , 126 , 147 Bluetooth, 143 Bounded rationality, 91 Bunchball , 152 Candy Crush , 165 , 166 Candy Crush Saga , 165 Capitalism, 30 , 174

informational, 183 platform, 173 – 175 surveillance, 2 , 21 , 68 Cashsquare , 170 Civilization, 41 , 110 , 113 Clue , 139 , 140 , 153 Coded spaces, 118 Cold War, 107 Colonizing attempt, 17 Commodity, 95 Comprehensive review, 39 Computation, 92 , 96 , 168 gamification, 93 hyperadaptive virtual worlds, 118 logistic ends of production, 95 Concretization, 131 Conspicuous play, 144 Consumption, 96 Convergence, 3 , 140 , 149 CrowdFlower , 175 Crowdsourcing, 162 “Cultivation of ludus”, 17 Cultures of gaming, 63 Cybernetics, 92 , 95 , 106 , 109 , 169 Dataveillance, 99 – 101 Decision-making, 91 , 107 rational, 108 theory, 59 Desire, 86 – 89 Digital games, 2 Digital labor, 161 Digital spaces, 68 Digital surveillance, 174 Doppler radar, 151

Ecology, 128 – 131 Environmental alteration, 119 Epigenesis, 131 Essentialism, 97 EVE Online , 183 , 184 Execution architecture, 165 Facebook , 2 , 110 , 122 , 163 , 165 Farmville , 184 Figure Eight , 175 Fitbit , 137 , 143 , 149 , 153 Fitness protocol, 144 – 147 Fitocracy , 143 , 144 , 149 , 156 Foursquare , 170 – 172 Freedom, 92 , 93 , 103 Freedom for ignorance, 173 “Future Force Warrior” program, 142 Game cultures, 3 , 63 , 64 , 154 Game industries, 2 Game of Life , 92 , 109 , 110 – 113 , 165 , 187 Gameplay, 26 – 30 , 117 , 118 , 120 , 155 Gamer culture, 1 Games, 22 – 25 ambiguous play, 46 – 49 magic circle, 39 – 41 mechanization, 41 – 44 metaphysics, 44 – 46 seduction, 41 – 44 types of play, 39 – 41 Games and Decisions , 106 Games for Cats , 120 – 122 , 124 , 126 , 127 , 129 , 134 Games of truth, 30 Gamespace, 30 – 33 , 86 – 89 desire, 86 – 89

gamification, 70 – 74 GUIs, 70 – 74 seductive architectures, 81 – 86 simulation collide, 86 – 89 Game theory, 4 , 103 – 106 , 108 developments, 66 growth, 110 visual expressions, 59 Gamic interaction, 112 Gamification, 2 , 6 – 7 , 93 , 114 – 115 biopolitics, 123 – 126 , 138 cellular automata, 112 computation, 59 – 60 culture, 60 – 65 definition, 35 – 66 ecology, 128 – 131 epistemological contingencies, 13 gamespace, 70 – 74 gamified applications, 8 gaming cats and dogs, 119 – 122 genealogy, 11 – 12 genetics, 21 – 22 history, 49 – 52 multiagent systems, 112 network architecture, 126 – 128 proto-gamification, 12 researching gamification, 9 – 11 rule-based environments, 113 technogenesis, 131 – 134 virality, 117 visibilities, 13 Gamified applications, 2 , 5 , 8 , 10 , 65 Apple Health , 149 Fitocracy , 149 Fitbit , 149 gameplay, 15 implementation, 11

Games for Cats , 126 Ingress , 69 Pokémon Go , 69 Strava , 69 Whistle , 126 Gamified design, 60 , 64 , 65 , 118 Gamified ecology, 128 – 131 Gamified health and bodies fitness protocol, 144 – 147 health protocol, 138 – 140 healthy players, 155 – 158 healthy subjects, 155 – 158 quantified subject, 149 – 152 understanding, 147 – 149 wearable technology, 138 – 140 Generativity, 168 Gold farming, 181 , 182 Google Maps , 99 Governmentality, 124 Graphical user interface (GUI), 68 Grinding, 178 – 185 Head-mounted displays (HMDs), 140 Heads-up displays (HUDs), 68 Health tracking, 140 Healthy players, 155 – 158 Healthy subjects, 155 – 158 Huizinga’s primary thesis, 39 Human Cognition Project, 24 Human intelligence tasks (HITs), 175 Hyperadaptive virtual worlds, 118 Hyperreality, 97 Individuation, 132 , 155 Information theory, 95 Ingress , 190

Instagram , 2 , 110 , 168 Instrumentality, 21 Interfaces, 4 Internalize difference, 98 International health protocol, 146 Internet culture, 161 Knowledge, 2 Labors, 161 – 185 Language games, 30 Life-as-play, 35 Living simulation, 110 – 113 Location-based gamification, 58 Location-based mobile games (LBMGs), 55 – 59 Loyalty 3.0 , 19 Ludefication, 23 Ludic interface, 69 Luminosity , 29 Lumosity , 24 , 181 Lyft , 175 , 177 Magic circle, 30 Mass-sport, 41 Material culture, 60 Mathematical marketing, 78 – 81 Mathematical theory of communication, 94 McVeillance, 142 Mechanical objectivity, 151 Media ecology, 119 Medium of communication, 93 Meritocracy, 178 – 185 Metadata, 121 Metaphysics, 44 – 46 Mobile interfaces, 57

Modern gamification, 52 – 54 Motion Genome Project (MGP), 152 MTurk , 174 , 179 Multiplayer Online Battle Arenas (MOBAS), 27 Netflix , 175 Network architecture, 126 – 128 New labor market, 173 – 175 Niantic, 190 Nike, 143 Nimbi , 110 , 112 Nonplayer character (NPC), 51 Nonrational game theory, 108 Nudges, 164 , 165 Oculus Rift , 142 Optimization, 94 , 100 , 108 Peak , 152 Performativity, 100 , 101 Pervasive games, 56 Pervasive influence, 93 Petcube , 122 , 126 , 133 Platform capitalism, 173 – 175 Platforms, 174 Playbor, 161 , 162 , 164 – 168 asymmetries, 175 – 178 quixotic, 168 – 170 Player/game dichotomy, 25 – 26 Pokémon Go , 112 , 114 Pong , 69 Posthuman scholarship, 10 Postmodern condition, 100 Power, 22 – 25 , 124 , 125 gameplay, 26 – 30

rules, 26 – 30 Power Glove , 143 Power-ups, 1 Programmability, 101 Programming, 104 , 106 , 108 Program V, 105 Proto-gamification, 12 Quantified living, 137 , 149 , 151 Quantified self, 137 Quantified subject, 149 – 152 Quixotic playbor, 168 – 170 Radar games, 74 – 77 RAND (Research And Development), 104 Rationality, 91 collapse, 106 – 109 crisis, 91 universal, 91 Reality, 97 Real-money trading (RMT), 181 , 182 Reproductive trackers, 139 Researching gamification, 9 – 11 Rethinking gamification, 19 Rules, 26 – 30 Samsung, 137 Seduction, 3 – 4 Seductive architectures, 81 – 86 Seductive control, 2 Seductive design, 7 – 9 Self-actualization, 140 Self-contextualization, 114 Self-surveillance, 139 SimCity , 110 , 113

The Sims , 110 , 113 Simulacra, 98 , 101 Simulation-based spatial software, 78 – 81 Simulation collide, 86 – 89 Simulation theory, 92 , 93 – 99 Simulative dataveillance, 99 – 101 Skeuomorphism, 130 “Skill-related” fitness, 146 Smartwatches, 137 , 143 Social media, 161 , 162 , 167 Social media games, 54 Social possibility, 42 Sousveillance, 142 Spatial monitoring, 74 – 77 Spatial play, 74 – 77 Stack, 3 – 4 Strava , 112 Surveillance capitalism, 2 , 93 , 173 Swarm , 170 , 171 Switch , 142 TaskRabbit , 177 , 179 Teaching Games for Understanding (TGfU), 147 , 148 Technical individuation, 133 Technical society, 41 Technics and Civilization , 130 Technogenesis, 131 – 134 Techsourcing, 150 Theoretical process, 3 Thingification, 20 TomTom Multisport , 143 Trello , 178 Truth, 125 Twitch , 164 , 165

Twitter , 2 , 168 Uber , 175 , 177 United States Armed Forces (USAF), 104 Universal programming of language, 95 Universal rationality, 91 Vexing problem, 94 Virality, 117 Voluntaristic theory of social action, 91 Wearable technology, 138 – 140 playful history, 140 – 144 Whistle , 121 , 126 , 133 Work-as-play, 35 World of Warcraft , 181 Xerox’s Palo Alto Research Center (Xerox PARC), 52 YouTube , 110 , 120 , 165