Artificial Intimacy: Virtual Friends, Digital Lovers, and Algorithmic Matchmakers 9780231553858

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ARTIFICIAL INTIMACY

ARTIFICIAL INTIMACY

Virtual friends, digital lovers and algorithmic matchmakers

ROB BROOKS Columbia University Press New York

Columbia University Press Publishers Since 1893 New York Chichester, West Sussex cup.columbia.edu First published in Australia by NewSouth, an imprint of UNSW Press Copyright © 2021 Rob Brooks All rights reserved Library of Congress Cataloging-in-Publication Data Names: Brooks, Rob, 1970– author. Title: Artificial intimacy : virtual friends, digital lovers, and algorithmic matchmakers / Rob Brooks. Description: New York : Columbia University Press, [2021] | Includes bibliographical references and index. Identifiers: LCCN 2021011487 (print) | LCCN 2021011488 (ebook) | ISBN 9780231200943 (hardcover ; alk. paper) | ISBN 9780231553858 (ebook) Subjects: LCSH: Sex. | Intimacy (Psychology) | Online social networks. | Artificial intelligence—Social aspects. | Technological innovations— Social aspects. Classification: LCC HQ21 .B873 2021 (print) | LCC HQ21 (ebook) | DDC 306.7—dc23 LC record available at https://lccn.loc.gov/2021011487 LC ebook record available at https://lccn.loc.gov/2021011488

Columbia University Press books are printed on permanent and durable acid-free paper. Printed in the United States of America Cover art and design: Milenda Nan Ok Lee and Design by Committee

For all the people coming of age in this era of climate change, COVID, and artificial intimacy. Especially my students, and Ben, Lily, Oskar, Matilda, Christopher, Anthony and Olivia.

Contents Introduction: In the beginning …

1

1.

Meet the dollbots

6

2.

It’s not about the robot

27

3.

Groom your friends

50

4.

The intimacy algorithm

68

5.

How did sex become so complicated?

86

6.

When artificial intimacy goes bad

108

7.

Ploughs, pills and porn: How technology changes sex

132

8.

Tomorrow’s moral panic will be just like yesterday’s

152

9.

Make war not love

177

10.

A Fembot army to disarm the InCel insurrection

199

11.

There’s no such thing as free love

217

12.

A future in four fictions

233

Acknowledgments

252

References

256

Notes

269

Index

279

Introduction: In the beginning … According to the Old Testament, sex and gender relations first grew complicated when Eve ate fruit from the Tree of Knowledge of Good and Evil, and then manipulated Adam into doing likewise. Their sin made apparent to them their nakedness, of which they were ashamed. Through sexual desire and reproduction, Adam and Eve transmitted their sin to all their descendants, thus transforming human nature. Greek mythology pinpoints a similar moment. The poet Hesiod tells us that the first woman, Pandora, brought with her to the world a jar containing ‘burdensome toil and sickness that brings death to men, … diseases … [and] a myriad other pains’.1 She promptly scattered all these contents, filling the earth and sea with evils. Whichever account you read, sex became complicated very early in human history, women bore most of the blame, and knowledge made everything worse. As a scientist who studies the forces that render sex so complicated, I have nowhere near the canonical certainty of Hesiod, the Old Testament, or the fundamentalists who today use religious origin myths to set their moral compass. I do know, however, that knowledge presents a key to human improvement, that making women responsible for policing sexuality harms people of all genders, and that there is no point looking for answers in Genesis. Sex was complicated from the very first time two single-celled organisms combined their DNA. It grew even more so by the time modern humans arose. Yet it reached new depths of complexity over the last 12 000 years or so, for reasons that have nothing to do with a 1

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mythic Tree of Knowledge. Human sexuality became complex because new technologies changed how women and men make their livings, and thus how they relate to one another. From taming animals and domesticating cereal crops to industrialisation and the contraceptive pill, technology repeatedly disrupted the ways in which people cooperated with, befriended and loved one another. And new technologies threaten to overshadow the myriad pains that escaped Pandora’s box. As lifesized silicone-skinned sex dolls metamorphose into lifelike robots that can move, talk and, especially, fuck, many commentators fear they will change human relationships for the worse. That they may well do, but could a sex robot revolution have some upsides? While we gawk at the sex robots, trying to process them in all their uncanny weirdness, other technologies based in artificial intelligence and virtual reality insinuate themselves into human interactions, quite likely with more profound effects. Collectively, these are the ‘Artificial Intimacies’: technologies that engage our human needs for connection, intimacy, and sexual satisfaction. Machines that can help us make and maintain friendships in a world of cognitive overload. Machines that can help us feel better. And machines built to feed back to us whatever it is that they need us to see, hear, or feel. Many artificial intimacies will simply refine technologies that already exist, including social media and video games. Others will look entirely new. Together, they will likely transform the quality of human life. The coronavirus pandemic already accelerated the transition to artificial intimacy as people in isolation leaned more heavily on their digital tools to socialise, work, play, and sometimes get off. If you want to date the start of the age of artificial intimacy, then I would suggest 2020. Human friends or lovers being made redundant by touching, feeling robots and virtual reality avatars will likely remain the realm of science fiction. Machines may never do intimacy as well as real humans do. They don’t have to. Social media already occupies some of the 2

Introduction: In the beginning …

limited time and headspace that people have available for social relations. Facebook, Snapchat, and TikTok crowd family, friends and lovers into ever-smaller spaces in our lives. Likewise, the artificial intimacies of the near future will provide imperfect substitutes for companionship, friendship, enmity, rivalry, counsel, intimacy, sex and love. As they have proved for social media, the results will present a mix of good and bad. Some technologies will meet urgent needs. Some may bestow salutary, even life-saving, effects. Other consequences will diminish individuals, and possibly even devastate communities. Whatever the blend of positive and negative effects, anything that changes human relations will generate ideological heat. The new technologies could unleash changes so extensive that the sexual revolution of the late twentieth century, and the culture wars that have reverberated ever since, come to look relatively trivial.

I am an evolutionary biologist who studies how sex and reproduction shape the lives of animals, including human animals. Early in my career I watched the world’s favourite aquarium fish – the guppy – for thousands of hours, learning how they court and mate. My collaborators and I captured crickets in a country graveyard at midnight and took them back to our lab to show that, when fed a high-quality diet, males use it as fuel for their relentless chirping to attract mates. They then burn out and die young. Sex really matters. Our research at the UNSW Sydney Sex Lab, on mice, venomous red-back spiders, pond-skating water striders and many other species, reveals that sex has far-reaching consequences for non-human and human animals alike. While it might undersell humanity to suggest that we ‘ain’t nothing but mammals’, there remains a great deal about the human condition to be learned from watching the Discovery Channel. 3

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Artificial Intimacy is foremost about human nature, shaped as we domesticated one another from wild, forest-dwelling apes into more cooperative, friendly, intimate creatures. That same evolutionary process, however, has a dark side that enables exploitation, conflict and strife. Both the lighter and shadier aspects of human nature will influence the course as AI and other technologies blow humanity into waters never before sailed, much less charted. This book doesn’t peer into distant decades, projecting technologies undreamed of by the average imagination. It does not concern itself with artificial general intelligence (AGI) that can do anything a human can, or fret about the coming singularity when AGI can design better AGI and technological progress explodes. Artificial Intimacy concerns the near future, from a vantage point firmly in the present. The technologies are only those we have right now, somewhat amplified by realistic expectations of faster computers, more sophisticated algorithms, and accumulating mountains of data, data, data. The job I offer to do, as your guide, is to extrapolate from the latest knowledge of human nature to consider how the new and emerging technologies will – or at least could – alter humanity’s future.

Those of us old enough to remember the nineties, but young enough to have welcomed the internet, will remember how the net was meant to make the world a better place by democratising information and communication. The internet delivered many wonderful things, including free access to almost all of human knowledge, instantaneous communication, and navigation tools that get us where we need to be with remarkably few arguments. We can share photographs with loved ones on the other side of the world, buy almost anything online, and

4

Introduction: In the beginning …

entertain ourselves for an entire evening watching TikToks. Who could ask for more? Generation Xers like me, who remember the frisson of the internet’s early promise, find ourselves a little flat nowadays. In addition to all the wonderful things that came bundled with the net, it also inflated thought bubbles full of fake news, democratised ignorance, and birthed armies of trolls. We know how technology can disappoint, even as it delivers. If humans simply leave things to unfold on their own, without thought or discussion, then artificial intimacy will be captured by a few corporations and enslaved to serve their interests at the expense of the many users. The technologies that abet commerce and manipulation will win out, and those that serve a public good might not see the light of day. Artificial Intimacy offers a glimpse of what the distant evolutionary past, and the more recent technological–cultural past, can teach us about humanity, and how we might go about fashioning a better future.

5

1

Meet the dollbots New technologies have opened up a world of algorithmic matchmakers, virtual friends, and digital lovers. Social upheaval could well ensue.

The first thing I noticed about Roxxxy was not her Photoshop-smooth complexion, the slouching way her body had been arranged on the chair, or the flimsy black garment straining against her improbably proportioned torso. The first thing I noticed was the enigmatic look frozen on her face, somewhere between pleasant surprise and utter horror. There could be no mistaking Roxxxy Gold True Companion – her full name – for a human being. Indeed, one could reach no other conclusion than that she was an object created to satisfy a prosaic heterosexual male fantasy. And yet, here I am, unable to decide whether to call Roxxxy ‘it’ or ‘her’. On first impression, there seems little difference between Roxxxy and the sex dolls that have gradually grown more lifelike in recent decades. But when Roxxxy debuted in 2010, her creator Douglas Hines, formerly an artificial intelligence engineer at Bell Labs, touted her as ‘the world’s first sex robot’. Not because she moves about freely; her movements remain limited to a few simple arcs. Unlike other sex dolls, however, traces of artificial intelligence (AI) breathe a semblance of life into Roxxxy and her male stablemate Rocky. They can recognise and generate speech, ‘have an orgasm’, and, apparently, they have personalities. Several personalities, in fact. According to the True Companion website,1 Roxxxy’s artificially intelligent personalities can be customised 6

Meet the dollbots

by the owners, or they can be set to adventurous ‘Wild Wendy’, matronly and talkative ‘Mature Martha’, reserved ‘Frigid Farah’, and the naive, curious, but apparently just-over-18, ‘Young Yoko’. Let us suspend, for now, the ‘WTAF?!?!’ reflexes raised by Frigid Farah and Young Yoko. Even before we get to the notion of sex robots built to be sexually reluctant, or to simulate somebody only trivially older than the age of consent, and even if we believe the most breathless declarations on the True Companion website, Roxxxy and Rocky remain pale imitations of the living, breathing companions that most people seek. Their faces bely no affect, they remain unable to move themselves about, and the artificial intelligence that powers their personality seems, as far as I can tell, like a primitive chatbot. A suite of competitors has joined the party. Samantha, made by Synthea Amatus in Barcelona, has an impressive conversational repertoire and can report verbally on the state of her many sensors and systems. California’s Realbotix turned their experience producing the popular RealDoll line of sex dolls into the highly-responsive Harmony sex robot. There’s much more to Harmony than a selflubricating robotic vagina. Users can run Harmony’s AI personality from a smartphone app, kindling a digital relationship even when physical circumstances keep user and robot apart. Like Roxxxy and Rocky, Harmony and Samantha are debatably more doll than robot. Let’s be generous and call this current generation ‘dollbots’. They do provide a glimpse of how tomorrow’s must-have sex robots will differ from today’s dolls. Artificial intelligence, we are told, will enable robots to simulate the ways in which humans bond emotionally and fall in love. Such robots will eventually be able to learn what a user likes, how to converse with them, how to turn them on, and when actions speak more eloquently than words. A robot equipped with good AI will have the capacity to learn from every interaction. The things users say and do to the robots, and the way users respond to what the robots say and do, produce data. 7

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Those data, shared between robots and their manufacturers, make perfect material for a form of artificial intelligence called machine learning. For those readers unfamiliar with machine learning, it bears a moment’s introduction. My UNSW colleague Professor Toby Walsh provides a pithy encapsulation of what machine learning is and why it is so important in his book 2062: The World that AI Made.2 Because a program can change its own data, a program can change itself. This is the heart of machine learning: the idea that a computer can learn from its data and change its own code to improve its performance over time.

It is worth considering another common concept, central to machine learning, but important for far more general reasons too. ‘Algorithm’, according to Hebrew University of Jerusalem historian Yuval Noah Harari, ‘is arguably the single most important concept in our world’.3 Harari’s definition of algorithm as ‘a methodical set of steps that can be used to make calculations, resolve problems and reach decisions’ is as good as any I have encountered. All computer programs, therefore, are algorithms. Machine learning algorithms are programs that extract statistical patterns from data and, based on their performance, modify themselves to perform better the next time. This improvement mimics the way animals learn, hence ‘machine learning’. But the similarities between computer programs and living organisms don’t end there. As Harari famously declares in Homo Deus: A Brief History of Tomorrow, ‘organisms are algorithms’.4 Like a programmer designing a computer algorithm, natural selection shaped humans and other animals to be good at one task: making copies of themselves. They work through sensations, thoughts, emotions and, ultimately, actions. Machine learning algorithms, combined with ever growing computer processing power, could make sex robots exceptionally good at 8

Meet the dollbots

the mysterious arts of intimacy. Despite enormous popular and media interest in sex robots in recent years, and worries that they will, variously, displace us in the bedroom, corrupt our morality, and ‘fuck us to death’,5 many people will be relieved to know that today’s sex robots really aren’t that good. There is a long way to go before anybody can manufacture something like the warm-blooded, flawed, fellow human beings we know, love, and, occasionally, take to bed. One look at the likes of Harmony, and most of us know we could never long for its company, yearn for its closeness, or care for its wellbeing in anything like the ways we do for a human lover. We could never be surprised, rejected, affirmed, believed, hurt, or healed by something like Samantha. But that might not always remain true. Almost any criticism of a sex robot can be turned into an opportunity for product improvement if enough money, time, and design ingenuity are thrown at the problem. Have no doubt, enough money will be thrown at the problem. The global market for sex toys is estimated at $31 billion in 2020,6 with strong growth of 9 per cent per year predicted given the flourishing market in sex toys. Perfecting the look, feel, movement, and artificial intelligence of sex robots presents mere engineering challenges. Immense potential for profits will ensure that those challenges eventually wilt. Sex robots will get better. Underlying the current obsession with sex robots quivers a tremulous dread that we might become obsolete in our most human roles, as companions and lovers. Science fiction like Westworld, HBO’s series about a tourist park populated by lifelike robotic hosts available for guests’ every amusement, explores the possible consequences of artificially intelligent robots walking among us, difficult to discern from living, breathing, orgasming humans. When Sydney-based sexologist Dr Nikki Goldstein travelled to California to check out Harmony for her Sex and Life podcast, the possibility of real intimate partners being replaced topped her list of worries. Harmony proved an accomplished interviewee, with a cute Scottish lilt, charming conversational style, and 9

ARTIFICIAL INTIMACY

impressive range of movement. But to her palpable relief, and likely that of her listeners, Nikki discovered that Harmony remains a long way from displacing real women from men’s lives. Nikki later wrote: I don’t think the technology is there yet for robots to completely replace a woman, but it doesn’t mean that intimacy and connection can’t easily be formed with them.7

In case it is not already clear, let me state at this early stage that I am not among those who fear an army of humanoid lovers breaking out of the closets and basements where owners stow their dolls, taking our places, and doing a better job than us in our relationships and in the bedroom. That is not to say a threat does not exist. It is my belief that some of the technologies currently or likely to be deployed in sex robots could undermine human wellbeing and society. I also believe that those technologies introduce important opportunities to improve human lives. Although I have opened this book by introducing you to the dollbots, they are, ultimately, a decoy. When the media, and those who consume it, fixate on how sex robots are starting to look, sound and feel more human-like, and how robots might displace human lovers and partners, we take our eye off other, more profound issues. What I think will happen is that a bevy of flawed, piecemeal new technologies will each substitute for some of the friendly, intimate, or sexual things that people do. Those technologies will mostly not be sitting in a gynoid (female-like) or android (male-like) robotic body. Indeed, some of the technologies that matter are already sitting in your pocket, on your desk and in your home.

10

Meet the dollbot s

Artificial intimacy Many robotics and artificial intelligence researchers consider sex robots a quirky niche issue. Embarrassing and creepy, sex robots also seem trivial when measured alongside the apocalyptic potential of autonomous weapons, the chaos caused by election-stealing algorithms, and the workplace upheaval as AI learns to do human jobs. Many journalists, too, consider the topic more suitable for light entertainment than serious thought. News stories about sex robots fit the hackneyed templates of reporting on celebrity sex lives: titillating but ultimately trivial. I also think sex robots are quirky and niche, but not because sex is trivial. As a scientist who studies the tectonic evolutionary consequences of sex, I hold that few issues run deeper. As the coming chapters will show, sex lurks, though often unacknowledged, at the very centre of every other big societal issue, including warfare, work, politics, gender relations, wellbeing, inequality, family life, sexuality and love. My uncle Dave, like many men of the 1980s, insisted he subscribed to Playboy magazine ‘for the articles’. I hope I don’t sound as disingenuous as he did when I declare that sex robot bodies interest me less than their artificial intelligence does. Sex doll bodies, like pornographic magazines, are engineered to push users’ sensory buttons. They stimulate well-understood preferences. Several new technologies, many of them on smartphone platforms, already push other psychological buttons, stimulating the ancient evolved mechanisms that make Homo sapiens such a sexy, social, cooperative species. Artificial intelligence is already learning how to push more of those buttons, and how to do so in more compelling ways. Technologies that do this are the ‘artificial intimacies’ or ‘ArtInt’. They are technologies that will interact with, simulate, or even exploit human yearning for belonging, thirst for intimacy, capacity for love and desire for sex.

11

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The argument that machines will never perfectly do the most intimate human things stalks any treatment of ArtInt. In a 2018 New York Times op-ed, MIT psychologist and author Sherry Turkle proclaimed ‘There Will Never be an Age of Artificial Intimacy’. Turkle often argues, with great compassion for human users, that social technologies can never properly replace important human interactions. She compels the reader, with exquisite prose and plentiful evidence, to conclude that people need to bolster those interactions, notably conversation, in order to flourish. ‘Robots may be better than nothing’, Turkle argues, ‘but they still won’t be enough’.8 I enthusiastically plead ‘no contest’! The big issue is that technologies tap into our deep evolved needs for those human interactions. Many of the connections they deliver are welcome, even healthy. But the technologies use up time, attention and energy we would otherwise have invested in friends and family. They substitute for the real deal, often poorly, in much the same way chewing gum substitutes for chewing food. We get some satisfaction from the feel and flavour of the gum, but it falls far short of providing a meal. Better than nothing, but not nearly enough. Social media platforms like Twitter, together with chat rooms and Reddit forums, already do this, giving us the sensation of connecting with real people when we are only ever partially present, interacting with an agglomeration of other partially present people, and vacant bots. The time, presence and headspace this uses diverts us from conversations and connections we could be having directly with one another. We are now in a place where Sherry Turkle said we would never be: on the threshold of the age of artificial intimacy. ArtInt might never deliver the healthy meals of real friendship, intimacy or sex, but masticating their social chewing gum diverts us from meeting those needs. Tastier, chewier forms of social chewing gum will continue to pop up to tempt us, like the endless new levels of the uber-addictive game Candy Crush Saga tempt us to play just one more game. Artificial intimacies 12

Meet the dollbot s

that partly service our needs for connection and human–human interaction will often serve up the social equivalent of junk food: not really nutritious, but tasty enough to keep you coming back for more. Despite the many wonderful conveniences that digital life has bestowed on humans, from real-time reporting, to helping isolated people find welcoming communities, to platforming new and diverse voices, we seem to be entering a digital obesity crisis in which hyper-stimulating ‘social’ tools, mostly running on smartphones, crowd out many healthy whole foods from our social diets. The awesome power of machine learning to mine the endless strata of data that people lay down as they move through the digital world, is going to improve those technologies’ hold on our attention, and thus our social and intimate lives. The consequences of artificial intimacy extend far beyond users. If piling in to confected arguments on Twitter uses up some of the time and headspace we would have devoted to working through important issues with friends, then how does that change those relationships? More than that, does it have knock-on effects for other people? Even people who don’t spend their time on social media will miss the chance to work through issues in their regular lives because their intimates squander their emotional budgets on Twitter and are now only partially present, if at all, for the ‘real’ stuff.

A brief taxonomy of artificial intimacies Sex robots occupy only one modest spiral arm of the expanding universe of artificial intimacies. They demand attention because they literally personify the issues. For now, the dollbots are clunky, expensive, and take up space. Any user needs a big closet, a locked basement, or the bullet-proof self-confidence to leave Rocky on the sofa when friends come around. That isn’t necessarily true for the more discreet and less 13

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DIGITAL LOVER Sex Dollbot  VR Porn  Smart Toy  Deep Fake Lover

VR Sex Worker VR Hookup VR Lover

Sex Robot Digital Catfish Game Flame  VR Porn character

Dating Assistant MATCHMAKER IRL Hookup  IRL Date  Social media 

VIRTUAL FRIEND Social medium Friendly Brand Candidate

Assistant  Therapist  Game character  Confessor Carer

Figure 1: Three broad types of artificial intimacy and their zones of overlap. Technologies with a tick are already present in some form.

clunky technologies that occupy the rest of the ArtInt universe. It’s time we met some of them. Ever since my overbearing Grade 2 teacher Miss Hayway kept me back after school to finish what was probably a trivially easy task on sets, I have despised the Venn diagram. I will relent, just this once, to introduce some forms that ArtInt is beginning, or likely, to take. In Figure 1 I arrange the universe of artificial intimacy that is currently visible to the naked eye into three broad and overlapping galaxies. I stress ‘to the naked eye’, because there is much more out there in the universe, and more coming into existence every year. 14

Meet the dollbot s

The most eye-catching technologies are those that emulate, simulate or facilitate sex: the digital lovers. Artificial intimacies that can mimic how humans make friends, draw them near, and grow more intimate with them are the virtual friends. And third, the algorithmic matchmakers, use artificial intelligence to connect us with others, from matching with a hot Tinder date to the Uber driver who makes sure we get to the arranged meeting place on time. The ticks in Figure 1 indicate technologies that are already here, either on or just over the threshold of artificial intimacy. Technologies without a tick will, I predict, probably arrive soon. Some of the most interesting prospects arise when the categories overlap. When the sex robot reaches maturity, for example, it will have moved to the overlap between digital lover and virtual friend, able not only to please users sexually, but also to make them care.

Lovers and friends Digital lovers don’t have to be as conspicuous as gynoid or android sex robots. They just have to channel the power of AI to provide better sexual experiences. ‘Unlock the secret to more frequent and intense orgasms with Lioness, the world’s most advanced vibrator’, says the website of one new sex tech company.9 Their sleek matt-white wand uses precision sensors connected to a mobile app, allowing people with vulvas to review what brings them to orgasm. The impressive appbased visual interface has recently been supplemented with AI guidance trained on data from ‘30,000-plus orgasms’ to maximise user pleasure and satisfaction. People with penises need not get their sulk on. They can get their own AI-enhanced sex toys, like the Autoblow A.I. Inside its clinical white plastic exterior, a motor drives a moving grip up and down a silicone sleeve, apparently emulating the sensations of fellatio for anybody with their penis inserted. According to the animated video on their 15

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website, ‘Our team of scientists used machine learning to analyse hundreds of hours of blowjob videos to discover the techniques that are the building blocks of blowjobs’.10 Building blocks of blowjobs: I kid you not! Users can choose from nine of those techniques, applied at any one of ten intensities. A tenth ‘surprise’ technique cycles at random through the 90 possible combinations. It can’t be long before companies like Autoblow learn from Lioness to deploy machine learning on user data to deliver more tailored stimulation. Smart sex toys are just getting started, but they are undeniably a big part of sex tech’s future. Virtual reality pornography occupies a similar niche to sex robots, down the sexy/shady end of the ArtInt universe, but without some of the drawbacks. Imagine, if you dare, the variety of sexual viewing currently available from an internet porn site becoming available as immersive experiences. A headset allows the viewer to look around the scene, to focus on whatever aspects they want to see. That is not a futuristic scenario: a vast amount of porn is already shot in this way, providing a 3D visualisation, usually from the point of view of the person wearing the VR goggles. The pornosphere also brims with computer generated imagery (CGI). Some CGI bodies look human. Others are enhanced to the edge of improbability in order to push every erotic button. Yet others have slipped the tyrannical constraints of anatomy and even physics. You can search and verify for yourself, but the scope for combining CGI and VR porn is immense. Expect that soon adventurous users could drop into scenes unconstrained by the normal laws of anatomy, where extra limbs, multiple sets of genitals, and the features of other species abound. Their fantasy could extend to inhabiting a different body. Their torso might be as firm as it was when they were 18, they might sport a souped-up pair (or more) of breasts or history’s most elaborate penis enhancement. Or perhaps, and I predict that this will become very popular indeed, they will be able to experience the scene as somebody of a 16

Meet the dollbot s

different gender or sexuality, one they have long wanted to explore but circumstances never permitted them to try. Indeed, an AI algorithm trained on millions of people’s fantasies could help you infer what you want to try, and perhaps even help you realise your own sexual preference or gender identity. A range of attachments placed on or in the viewer’s body and wired into the scene will provide stimulation coordinated with the video. Contemporary ‘teledildonic’ sex toys are already most of the way there, allowing a friend or lover to control a user’s favourite toy remotely – hence ‘tele’ – from anywhere with an internet connection. The companies Lovense and Kiiroo produce teledildonic toys for couples to stimulate one another in their preferred ways, via coordinated apps. Lovense’s Max and Nora toys are built to penetrate or be penetrated, respectively, as are Kiiroo’s Pearl and Onyx. The advance for these toys exists in the way they can synchronise with live cam models, porn movies, and virtual reality porn. The sex toy and adult entertainment businesses are already working together to build more seamless coordination between VR action and teledildonic stimulation. Haptic devices that allow users to give and receive the sensations of touch will shortly come to enhance VR scenes. In short, on its current trajectory, enhanced, immersive VR pornography will become increasingly like participating in the scene oneself. The next obvious step is true VR responsiveness and continuity of relationship. This is where VR porn characters and lovers will take on virtual friend properties. To begin with, responsive VR porn may resemble a ‘choose your own adventure’ book, but in this case it will be set in Pornland. Viewers won’t have to go along with the scene in a single linear narrative, but instead they will have options. A nod or turn of the head will lead the viewer to their chosen scene, and, likely, a sexual interaction that they choose. Progress in AI will eventually put paid to such clunky either/or scenarios. Expect scenes to be set in motion with a certain cast and physical 17

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landscape, but then to flow freely, learning from the viewer as the scene proceeds. To be sure, it will take technological creativity, computational grunt, and plenty of bandwidth, but this kind of deep interactivity is close enough that we can already sense it, just over the horizon. By the time it arrives, it may render independent, autonomous sex robots all but obsolete. All that will remain is the artificial intelligence ghost in the machine, able to learn what a user likes, able to retain and refer to a shared past, and yet, due to VR, able to morph at light speed, to be whatever it infers the user wants.

Rediscovering sex Enhanced VR porn will likely open the way to a new kind of sex, deeply intimate but practiced at a distance. Imagine being separated from your lover during an extended period of overseas work or, heaven forbid, a global pandemic. What if the two of you could, in the comfort of your distant homes, enjoy full immersive interactivity as your VR avatars have sex with one another? Every move, gesture, and gasp felt, seen, and heard by the other through headsets, teledildonic devices, and haptic suits. Where brave couples today, who miss each other very much, can kindle intimacy and stimulation via FaceTime and teledildonic play, the quality of transcontinental sex will likely go off the charts. Why restrict this view of virtual sex to couples? VR sex opens up a whole new world of long-distance hookups and booty calls that redefine the term ‘frictionless’. Combine VR sex with Tinder-like matchmaking algorithms, and pairs, threesomes, foursomes and moresomes – whose hardware and software are both literally and metaphorically compatible – will be able to do things to one another few have ever imagined. Afterward, there will be no need to extricate oneself from a strange apartment, and no ‘walk of shame’. If a hookup partner turns out to be a bore, a jerk, or just plain dangerous to be around, one can simply break the connection without incident. 18

Meet the dollbot s

Long-distance VR sex work also becomes a viable prospect. The camera models of today’s erotic economy video themselves stripping, masturbating, and doing other things viewers request, all for a price. Many now offer the service of delivering teledildonic pleasure by working clients’ sex toys remotely via smartphone apps. In much the same way, one might expect VR sex to create a ready niche for VR sex work. Workers will be able to immerse themselves in the same VR scene as their clients, and charge per an agreed schedule, without the physical and legal risks of ever meeting them. Virtual reality is one of those technologies that defies the limits of imagination. How soon, and how fully those scant possibilities I have managed to sketch here might come to pass, time will tell. The computing and bandwidth demand will be profound, but we have long come to expect the computing universe to keep on expanding and expanding. What else will people do with those super-powerful quantum computers that we are told are just over the event horizon? I mean, beyond computational drug discovery, uncrackable encryption, and exceptional new scientific inquiry, will the amazing computers of the near future be of any use? If the past is anything to go by, they will be deployed from the very start to deliver new and lucrative forms of titillation and stimulation.

Make us a match When I was at university in the early 90s, the only legit way to meet somebody was to encounter them in the flesh. We met our girlfriends and boyfriends at parties, in class, and through friends. Without Tinder, we could start a fire with newspaper, but the ‘Personals’ column always carried a soggy whiff of desperation. With limited column space sold by the character, a new forest of acronyms overgrew the classifieds, and one could enjoy a free hour’s entertainment – remember that we had no social media to fritter away our time – deciphering that ‘SWM OHAC WLTM F 20-30yo GSOH ISO LTR. ALA’ conveyed that a ‘single white 19

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man with his own house and car would like to meet females between 20 and 30 years old with good sense of humour in search of a long term relationship. All letters answered.’ ‘No way’, my friends and I would tell each other, ‘could or would we seek somebody to date, love, or marry through a few simple sentences in an advertisement’. No sooner said than the internet infested our lives and built ever newer, faster, and more sophisticated ways of connecting people looking for love. Within a generation, people of all ages would routinely advertise and find each other on a bewildering ecosystem of matchmaking and personals platforms like Grindr, OkCupid, Craigslist, Bumble, Gay Matchmaker, Happn, Silver Singles, Hinge, Tinder and even Christian Connection. Those matchmakers broker a very solid proportion of new hookups and romances. The most recent wedding I attended married two wonderfully well-matched people who met on Tinder. Three in five Australians surveyed in 2017 had used online dating platforms.11 The Pew Research Center reports that 59 per cent of Americans believe that ‘online dating is a good way to meet people’.12 Online matchmakers have proliferated because AI has made them good at identifying people who are physically near to each other and could possibly hit it off. They have the added advantage of serving up possible dates with people who do not lurk on the edge of one’s social circle. If things get awkward, you neither have to see them again nor tell the friend who introduced you to each other why it didn’t work out. The matchmakers work by presenting users with one another’s profiles, and then, if they both like what they see, declaring a ‘match’ and putting them in touch with one another. That sounds simple, but it takes programming genius and plenty of data. The data-rich environment of profile information, swipes, likes and matches creates the perfect soil in which machine learning can flourish. The matchmakers with the best algorithms for creating matches will shape who meets, who matches, and, ultimately, who mates. 20

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Beyond the birds and the bees, similar matchmaking algorithms can find us friends and mentors. Such algorithms could use what they know about our friendships, intimate relations, and perhaps even our sex lives to pair us up with businesses that want customers. Marketers could use new artificially intimate techniques to sell us the products we most need, and to build deeper brand loyalty than ever before seen. Political candidates could play to voters’ personal concerns, and perhaps those concerns could feed back to shape better representatives. If that all sounds a long way off, know that we are already more than half way there.

The friend you need? Whenever humans and machines interact, and those designing the machines use AI to tailor that interaction, there exists the possibility of artificial intimacy. Most of us have already met at least one of the ‘big five’ AI assistants: Apple’s Siri, Amazon’s Alexa, Microsoft’s Cortana, Baidu’s DuerOS and Google’s Assistant. They, and other artificially intelligent interactive systems, rely on three different kinds of artificial intelligence: natural language processing by which machines ‘understand’ what humans are saying (or writing), natural language generation by which machines generate written or spoken output that humans can understand, and machine learning by which machines discover what to do with data without having to be explicitly programmed to do it. When I say, ‘Hey Siri, please define artificial intelligence’, my iPhone records my question, sends it to a cloud-based processing centre to be processed and actioned entirely by computer, and the chosen response is sent back. Within little more than the usual human pause between question and response, I hear Siri’s reassuringly calm voice answering ‘the theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages’. 21

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All of the virtual assistants can help users recall information, find a recipe for tonight’s meal of Cacio e Pepe, remind us to pick up pasta and pecorino on the way home, and kick Spotify into action to play that Lana Del Rey song about Norman Rockwell. People ask, or used to ask, those kinds of mundane things of their friends, housemates, or lovers during the course of a regular day. So mundane, indeed, that hardly anybody would question such simple acts of virtual friendship. Wouldn’t everyone be relieved to have the right cheese for the Cacio e Pepe? What about the other things we do for one another in our relationships? If Alexa can learn to give us what we need vis-á-vis cooking and grocery advice, will it also learn to give us what we want, even when we don’t ask? Smartphones have so many sensors: microphones for telephony and voice commands, barometers for air pressure and altitude, motion sensors, ambient light sensors, moisture sensors, three-axis gyroscopes, touch ID sensors, and, of course, cameras that can identify a user’s face and record video. When does all this sensory ability turn into sensitivity? The hardware is in place. Coupled with all manner of artificially intelligent applications, we can expect devices to learn to infer our mental states, frustrations, and desires, and then to act on them. How long will it be before your virtual assistant can sense from your tone of voice, the speed with which you shift your phone from hand to hand, and the lack of moisture on your fingertips, that your anxiety is off the charts? And wouldn’t it be a good thing if it can learn what you need, in order to manage your own particular brand of anxiety, and reassure you by playing a personalised track of autonomous sensory meridian response (ASMR) trigger sounds designed and optimised by machine learning to mitigate your particular form of anxiousness? Perhaps it will learn to sense when you slip toward depression and assess from the symptoms whether you need to talk, or you just need somebody to talk quietly to you. It could then start playing Ralph Fiennes reading The English Patient. Digital therapists are already picking up their virtual pads and pencils. The first chatbot, ELIZA, 22

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emulated a psychotherapist. Today, all manner of therapy chatbots exist to provide very real therapeutic help. Likewise, a slew of chatbot apps encourage confession; both the Catholic type and the more secular forms of unburdening. Some, like Twitter’s Confession.bot will broadcast your confessions anonymously. Confession: A Roman Catholic App ($1.99) offers a twenty-first century alternative for those Catholics who are too busy, claustrophobic, or priest-averse to go to regular confession. With a personalized examination of conscience for each user, password protected profiles, and a step-by-step guide to the sacrament, this app invites Catholics to prayerfully prepare for and participate in the Rite of Penance.13

So far so good. Recipes, reminders and confessions might also be needs, and, if well designed and set up, applications like these will help people in their relationships with themselves and others. The potential for useful artificial intimacies that fill new and emerging gaps, that help people unburden themselves, work through their issues, and just get through all their tasks, seems almost beyond limitations. The applications need not, however, always service good intentions. What happens when all we really want is a dose of schadenfreude or sadism? Will our learning-all-the-time machines draw the line at showing us evidence of others’ suffering? Having known a few rolled-gold narcissists in my time, I know that they love their smart devices more than they do other people. Many would be quite happy to get high on their own customised narcissistic supply served up by Cortana. And that’s pretty much how many Luddites and technophobes view today’s social media users. Are we losing a generation or more who, transfixed by their digital reflections, slip away from society and merge with their online profiles like twenty-first century versions of Narcissus? As somebody who uses five social media platforms before breakfast, and 23

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who benefits from their reach and connectivity, I find this view too bleak, but nonetheless worth listening to and considering. There exist so many ways in which the digital assistants and other chat-based apps of today could become the digital friends of tomorrow by learning to push our psychological buttons, our intimacy buttons, even when not designed with that end in mind. The artificial intimacy will emerge, implicitly and inadvertently, but as machines get good at giving the people what they want, or what the people think they want, many of us may well be neck-deep in Narcissus’ pond before we know it.

Love in the time of corona As I finalise this book, I am working from a desk in my bedroom. I haven’t been to my office at UNSW Sydney in three months since the COVID-19 pandemic sent non-essential workers like me home, funnelling almost all our social interaction onto the internet. My children interact with their teachers and classmates on Zoom videoconferences. I meet with my colleagues via Microsoft Teams to plan and coordinate our work. Thanks to ecommerce, we still receive our groceries, clothing, and pods for the Nespresso machine. And our social interactions with people outside the house are almost entirely restricted to Facebook, Twitter, Instagram, Messenger, FaceTime, WhatsApp, and – after a few quarantinis – Houseparty. Social distancing and isolation accelerated the shift to online social interaction, perhaps irreversibly. People spending more time online using a greater variety of apps are inadvertently hastening the development of artificial intimacy even as I write. More users equals more data from which machine learning algorithms can learn about human interaction. Lonely, isolated, scared users, scrolling and clicking away their worries, find themselves relying on the comfort of virtual friends. Sleeplessness no longer gets remedied with a warm beverage and a 24

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physical book, but with Spotify music, rain sounds, and ASMR; with online articles, and with smartphone-guided meditation, all served up by ever-learning algorithmic matchmakers. By 2019, the modern word for dating was ‘Tinder’, and many wondered if sex could get any more casual. In 2020, isolation suddenly shut down the hookups and started pushing societies down the other side of ‘peak casual’. Even people already in relationships, unable to travel to one another’s houses, found themselves cut off from doing the sex. Sex, and sex work, suddenly became more digital than ever. Escorts and brothel workers, unable to both work and maintain physical distance, had to enter the more virtual forms of sex work, selling images and videos on OnlyFans, engaging clients on camming platforms, and downloading the apps to drive their clients’ teledildonic toys. As Sydney-based sex worker and author Tilly Lawless put it soon after isolation started: After a few stressed days, I find myself transitioning to online work for the first time ever. Without a working laptop, camming is out, but being well-versed in social media, I get the hang of subscription site ‘OnlyFans’ fairly quickly – where people can pay to access explicit photos and videos of you.14

It wasn’t only sex workers who pivoted in the way Tilly describes. The number of people posting on OnlyFans in the UK rose by 42 per cent in the first four months of COVID-19 restrictions.15 Many people who had never tried sex work before, finding themselves out of work, turned to posting pictures on pay-to-view sites in order to make ends meet. Porn purveyors made lemonade. As soon as Italy went into lockdown in late February, PornHub made their subscription service free.16 They tried to pass it off as an act of humanitarian beneficence, but every click or search as visitors sampled the free content left behind a 25

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record of their individual erotic tastes. PornHub will harvest this bountiful data, and their machine learning algorithms will use it to serve up more compelling offerings and to attract paying customers and advertisers in the future. They will likely dominate not only subscriptions to VR porn, but the sale of devices to go with VR porn, as digital lovers become ever more virtual. The digital lovers, virtual friends, and algorithmic matchmakers of the very near future are being designed and built right now. While the pandemic ravaged many sectors of the economy, technology companies hit the data jackpot. What artificial intimacies learn about human preferences, behaviours, worries, likes and dislikes in isolation will be used in coming years to develop newer and more compelling artificial intimacies, to sell products, and to keep users scrolling. We have more to consider than simply PornHub knowing your erotic browsing preferences, Honey Birdette knowing your sex toy purchase history, News Corp knowing the stories you like, Tinder knowing what causes you to swipe right, YouTube knowing which feelings keep you watching, and Facebook knowing everything you ‘like’ and who your ‘friends’ are. That’s because they share the data they gather. Perhaps not those specific companies, and perhaps not today. But the information that companies gather about you has, time and again, found its way to other companies that want your purchases and subscriptions. When you dip your extremities into the pond of artificial intimacy the waves of data you create will ripple outward, far beyond the shores of your imagination. All manner of machine learning algorithms will analyse and learn from it, eventually to serve up more compelling advertisements and content to you, and to people like you. As futurist and author of Team Human, Douglas Rushkoff put it: Each one of us is not just up against whichever algorithm is attempting to control us, but up against them all.17

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It’s not about the robot Machines are learning how to push psychological buttons that evolved as humans domesticated themselves.

My daughter has been laying down hints for quite some time now that she would really rather quite like a dog. I regularly get sent dog pictures and videos, and our walks are punctuated with deep discussions about the cuteness of the various -oodles we see taking their owners for a walk. To my eyes spoodles, cavoodles and labradoodles all look alike. They look like chewed shoes and scratched doors, like expensive vet visits, like me nagging the children to feed, walk, and brush that dog they begged me for. They look like last minute scrambles to find dog sitters so we can go away on holiday. And most of all, they look like me, clearing the lawn of those mines they have laid. Not a very generous attitude, I admit. Of course, I would love for my young teenager to have a dog who anchors her while she is at home, a companion to love her unconditionally as she negotiates the fickle ups and downs of high school. Also, perhaps there’s something in it for me, if Nora Ephron was right when she said ‘When your children are teenagers, it’s important to have a dog so that someone in the house is happy to see you’.1 Of course, many people’s bar to dog ownership is far lower than mine. Indeed, many dog owners I know could scarcely contemplate life without one or several canine companions. Their love for their fourlegged fleabags is real, deep, and in many ways far more secure than 27

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most human relationships. They speak of canine loyalty, and unconditional love. I know something of this, having had four special dogs at various times in my own younger years. Not only are dogs humanity’s best friends, they are also among our oldest friends.

Taming wolves and foxes For millions of years, our ancestors fell prey to lions, leopards, sabretoothed cats, hyenas, tigers, bears, and wolves. Our ancestors did whatever they could to stay safe, by learning how to make secure camps, intuiting when to throw stones, and of course knowing when to back away and knowing when not to run. Problem predators that got too close, stole food or attacked, would be chased away, perhaps killed. Mostly, that forged a wary peace, with predators slinking into the shadows, emerging rarely and opportunistically. Around 30 000 years ago, in East Asia, some grey wolves began following bands of nomadic hunter-gatherers and feeding off carcasses that hunters left.2 Friendlier, calmer wolves could get closer, and benefit from the scraps people left after the hunt. Humans killed or chased away any wolves that turned to aggression or interfered with hunting, gradually whittling away the genes that disposed local wolves to aggression and interference. Over many generations, and without intending to do so, humans domesticated these close-by wolves into more cooperative, less hostile beings. Humans and these friendlier wolves established ways to help one another when hunting. Sociable wolves flourished, benefitting from the partnership. Natural selection tuned those wolves to human ways and moods, rendering them more playful and less aggressive around people. The taming of the grey wolf just happened as an inadvertent consequence of the algorithmic cycle of life, death and reproduction that ground along when wolves lived near humans. 28

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In each generation the cutest puppies and the most puppy-like dogs of each generation enjoyed a leg-up, kept alive and cared for by humans. Aggressive or unsociable dogs were either destroyed, abandoned, or chased away. You can glimpse a shadow of this process today when a dog attacks a child. Swift and decisive retribution follows, with the dog often destroyed in time to make that evening’s news. Aggressive dogs don’t survive to breed, but cute and playful ones get bought, adopted, and brought into our homes. Human decisions of which wolf-dogs to keep, which to kill and which to chase away, together with wolf-dog decisions about whether to hang around the bands of strange two-legged apes or whether to run with a wild pack, guided the evolution of dogs from wolves. Gradually, wolf-dogs took on a more playful, sociable nature, more tolerant of people, and loyal to those who care for them. Their bodies changed too, snouts becoming shorter, ears and eyes bigger, limbs less wiry, paws larger, and their pelts even changed colour. Curiously, similar changes are shared by other animals that humans have domesticated. Charles Darwin noticed that domesticated animals – including livestock and rabbits – have shorter faces, larger eyes, floppier ears, bigger feet, smaller teeth, different coat colours and more docile behaviour than the wild stock from which they originally came.3 Nearly 150 years of research on this ‘domestication syndrome’ has revealed shared patterns of changes to hormones, brain anatomy and genes.4 In general, the algorithm by which humans domesticate wild animals preserves their juvenile cuteness and playfulness well into adulthood. The domestication of dogs as we know them today took millennia, in fits and starts. Domestic dogs spread from place to place as their owners moved home, conquered foreign lands or converted other people into owners. But there’s a more efficient way to domesticate a canid – by selecting deliberately. In one of the longest running and most celebrated experiments in the history of behavioural research, the 29

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Russian researcher Lyudmila Trut, working with celebrated zoologist Dmitry Belyayev, domesticated silver foxes. Russian farms bred the foxes for their furs. The breeders, caught in the wild, retained their solitary, high-strung nature. According to Trut, when she arrived at the research station near Novosibirsk, deep in Siberia, the snarling, lunging animals resembled ‘fire-breathing dragons’.5 She devised rigorous – algorithmic – methods to measure ‘calmness’, and then selectively bred the calmest males and females with one another. After four generations of selective breeding the animals had already become noticeably less aggressive, and some welcomed human interactions. A few even wagged their tails – unheard of for a fox – as Trut approached. In less than 20 years, the foxes evolved to become as tame and playful as any dog, open to unfamiliar experiences, situations and people. Courtesy of domestication syndrome, after more than 50 years of selection the Novosibirsk foxes today look like and are occasionally mistaken for domestic dogs, even though their ancestors were foxes rather than wolves. They have patches of different fur colours, rather than the silver-black of their ancestors. Their ears flop over, their snouts are short, and they look at their handlers with big puppy-dog eyes. They jump up, lick people, and love having their tummies scratched. And they have hormone profiles far better suited to bonding than stressy fight-or-flight.

The evidence that humans have changed dogs abounds, but have dogs changed humans? Not by the same kind of deliberate artificial selection, one can be sure. Dogs just don’t have the hardware to systematically eliminate cruel masters. But the messy, inadvertent business of natural selection can work in more interesting ways. One only needs 30

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a little imagination to see how people who kept dogs might have lived longer and produced more descendants than those who spurned dogs or simply never had a chance to keep them. Dogs provide personal security, ever alert to danger and often willing to attack anybody who presents a threat. In wilderness areas and on farms, dogs can warn against and chase away snakes and large predators. People out hunting and gathering would have experienced many of the same threats, from snakes, big cats, boars, bears and other people. With their acute hearing and sense of smell tuned to detect threats, and some remnants of vulpine aggression to see those threats off, owning dogs often meant the difference between life and death. Also, as any dog owner will testify, dogs make magnificent companions. Their love and loyalty can lift depression, ease anxiety, and even help reduce the burden of chronic disease.6 If dogs improve the health of their twenty-first century owners, then their predecessors have probably done so for thousands of years. Given the manifold ways that dogs work with people – including hunting, guarding, mustering livestock, pulling sleds, tracking people and animals, and detecting substances of great value … like truffles – dogs have, for millennia, earned their keep. All the advantages of dog ownership sharpened our ancestors’ affinity for dogs, and their skills in building productive human-canine relationships.

Robotic dogs I seem to have provided every good reason for people to keep dogs. To my daughter’s disappointment, my decision not to bring one into our home remains unchanged. But I am seriously considering a robot. As a behavioural scientist, I’m absolutely charmed by the latest version of AIBO, Sony’s robotic dog. Actually, AIBO is more of a robotic puppy than a dog, all rounded curves, plodding paws and luscious 31

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oversize eyes. AIBO converges on the domestication syndrome, and not by accident. Sony’s designers copied the very features that people use to choose which pups will make the most companionable dogs, and the traits that puppies use to persuade their owners to keep and care for them. AIBO’s adorability runs deeper than the surface, however. These machines really know how to do puppy dog. When Sony first looked to develop AIBO, ahead of their original 1999 release, they consulted Georgia Tech roboticist Ron Arkin.7 His team studied how dogs behave, and how they interact with humans, from their cute ways of gaining attention and showing affection to the more irritating and embarrassing things dogs do. Ron’s team also studied how puppies learn about their worlds, and how they make their humans fall in love with them. Fall in love human owners certainly did! When their robotic puppies broke, owners sent away for parts to make them whole again. When Sony went through tough financial times in 2006, closing down the AIBO project and ceasing technical support, owners whose robots broke down and could not be repaired experienced real grief. Some Japanese owners even held elaborate Buddhist funerals for their beloved robot-pets.8 Happily, Sony brought back AIBO in late 2017, and this version is better at learning than ever before. Since the original AIBO bounded onto the scene, successive generations became cuter and more playful, just like dogs and the Novosibirsk foxes. Technologies improve in iterative, algorithmic ways, much like the artificial selection Lyudmila Trut used on her silver foxes. The world’s most erudite rap artist, Baba Brinkman, encapsulates this algorithm as ‘Performance, Feedback, Revision’.9 In the creative arts, feedback comes via audience response, and the performer will develop those parts of their repertoire that resonate with audiences. In natural and artificial selection the feedback consists in which individuals succeed in leaving descendants, and thus passing on their genes. In product design 32

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the feedback comes from sales and from more direct responses about what consumers like and dislike. Products that sell become the basis for successive versions of products. Ideas that don’t work are soon discontinued. Whereas Trut selected and bred the most suitable, sociable, chilled-out foxes for breeding, the evolution of AIBO from one generation to the next happened via deliberate design improvement. Sony’s designers applied their ever-improving knowledge about puppies, dog domestication, robotics and learning, as well as feedback about which features AIBO owners liked, and which they disliked, to create a cycle of improvement. As a result, Sony’s designers did more than imitate puppies. They cleverly exploited the human vulnerability, honed by evolution over 30 000 years, to bond with cute puppies and sociable dogs. That is to say, the designers figured out how to push our human buttons, the ones that evolved as humanity domesticated their tail-wagging best friends.

Technology evolves If Sony engineers, in a few short years, designed such a compelling way to exploit the evolved human soft spot for puppies, then how will the burgeoning worlds of robotics and artificial intelligence push our many other psychological buttons? After seeing what Sony achieved with AIBO, a mere robotic toy pet, Ron Arkin confided to me that the prospect of AI intimacy seemed both achievable and concerning. The entire moveable feast of technologies that I bundle together as ‘artificial intimacies’ exists to stimulate evolved human drives to form friendships, forge cooperation, build intimacy, fall in love or have sex. As an illustration, let us consider the embodied cheerleaders for artificial intimacy: state-of-the-art sex doll-robots. These dollbots, as commentators and critics are never shy to alert us, are overwhelmingly 33

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‘hyper-feminine gynoids’.10 Hyper-feminine refers to the dollbots’ exaggerated feminine features. Seriously exaggerated. Designers have turned the dial on every feature that they think might enhance attractiveness – ample breasts, big bottoms, mantis-like waists, bee-sting lips and slender legs – all the way up, well beyond 11. The result is what behavioural scientists call a ‘super-normal stimulus’. In nature, one species can sometimes hack into another’s senses and hyper-stimulate them. Cuckoos famously lay their eggs in the nests of other birds, outsourcing their parenting to naive parents of other species. European cuckoos tower over the delicate reed-warblers they often parasitise. Once a hatchling cuckoo has pushed the reed-warbler eggs and hatchlings out of the nest, it persuades the reed-warbler parents to keep the food coming in. The reed-warbler chicks’ chirping, and the conspicuous markings inside their gaping beaks, signal to the parents that they have a healthy but hungry chick. Confronted with a nest full of them, the parents fly endless missions, throughout the daylight hours, to catch insects and bring them back for the chicks. If a few chicks die, the collective signal of chirps and open beaks tones down a little, letting the parents know. They slow down to provide enough food for the right number of remaining chicks. The cuckoo hacks into the reed-warbler’s parental sensibilities by providing a super-normal stimulus. The noises and movements it makes, and the markings inside its gaping beak, do not mimic a single – if oversized – baby warbler. Instead, as Cambridge zoologists Rebecca Kilner, David Noble and Nick Davies showed in some exquisite field experiments, they mimic a full nest of chicks, persuading the parents that they are still caring for a full brood and have to provision to the max.11 That’s the only way the cuckoo can grow big enough to fledge. Reed-warblers may seem a bit gullible, but they aren’t the ones spending several grand on a sex doll that isn’t quite yet a robot. Dollbot manufacturers are clearly onto something. They want to sell people 34

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something hyper-sexy, not something ‘normal’, or ‘typical’, or even ‘realistic’. They have started with bundling all the ‘sexy lady’ stereotypes into a single body, exercising very little creative restraint. That probably won’t last. While hyper-feminine gynoids might be with us for as long as there’s a space for sex robots, manufacturers will figure out ways to stimulate the more understated and interesting tastes of other users. As long as the sex robots aren’t driven underground by puritanical bans, we can expect sex robot bodies to diversify, catering to a much wider variety of preferences. I’d like to move on from sex robots, however. Not because they are dull, but because, as I keep saying, they are just really niche. There are more important buttons that technology is learning how to push. These buttons include the psychological preferences, proclivities and vulnerabilities that humans evolved over the course of a far bigger and longer-running domestication program than the Novosibirsk foxes or the gentling of wolves: the taming of humanity.

Sex before dawn According to the Ancient Greeks, the Earth’s navel could be found at Delphi, making it the centre of the world. Apollo, god of light, knowledge and harmony, chose as his sanctuary the gentle slopes of Mount Parnassus where Delphi nestles, overlooking the Plestos Valley. People travelled vast distances to consult the oracle Pythia, in the Temple of Apollo, before they made important decisions. Today, the temple lies ruined, but in its forecourt was once inscribed one of the most ancient pieces of human wisdom: ‘Know Thyself ’. To know and understand humanity requires some knowledge of where we came from. The places our ancestors inhabited and the ways in which they lived, died, and, above all, reproduced, defined the course of human evolution. The genes that our ancestors passed on to their 35

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descendants are the genes that you and I inherited from our parents. The genes of those people who lived at the same time as our ancestors, but who never managed to reproduce, played no further part in humanity’s story. To be sure, there is far more to know about ourselves than how we inherited our genetic legacy. Yet we will never understand ourselves without that knowledge. Before considering how technologies push our buttons and hack our social-intimate-sexual minds it is worth considering a few big changes that gave rise to those buttons and that decided how those minds evolved. Five million or so years ago, we last shared an ancestor with the two surviving chimpanzee species: the common chimpanzee and the bonobo. We can learn a lot about how far humanity has come by looking at these two close relatives, both of whom live in equatorial African forests, in large social ‘communities’ that periodically split and then coalesce later on. Primatologists who have studied any of the 280 species of monkeys or apes will tell you that their subjects spend hours every day picking burrs and ticks from each other’s bodies. This ‘allogrooming’ – the ‘allo’ signifies that the grooming is mutual – is important for hygiene, but it is far more important for building and maintaining social connection. In both chimpanzee species, all-important loyalties and alliances form and solidify through allogrooming. Alliances shape the politics of community living, but the deep motives for those politics come from the evolutionary incentives of sex and reproduction. Both common chimp and bonobo females sometimes mate with several males in a day. They tend to mate with most males in their community, but they pay particular attention to the males at the top of the dominance hierarchy. Males fight, threaten and groom one another to climb that hierarchy and thus enjoy more chances to mate. The hard work and risk-taking in gaining political ascendancy pay dividends in the fundamental currency of evolutionary fitness. Some big differences between the two chimpanzee species bear 36

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mentioning. Common chimpanzees, the more widely distributed species, live in larger communities and more open woodland than bonobos. Males jostle and fight for status with a ferocity unmatched by male bonobos. And deadly fights occasionally erupt between adjoining common chimp communities.12 Bonobos carry a well-earned reputation as more amorous, peaceable creatures. In 92 years of combined observations in the wild, only one suspected instance of a male bonobo killing another has been recorded. Their dense rainforest habitat south of the Congo River makes encounters and fights between communities less frequent than they are among common chimps. Male strength and aggression are thus less important than in chimpanzees. Instead, relationships between females give bonobo communities their structure. A male’s mother doubles as his most useful ally, and the higher her status, the more she enhances his.13 Female common chimpanzees exchange sex for male tolerance and protection. A female offers each male at least a faint hope that her next baby might carry his genes, giving him a good Darwinian reason not to kill it or allow it to be killed by other chimpanzees. Beyond security, chimpanzees also exchange sex for the occasional chance to depart from the vegetarian menu. When a male hunts a monkey or small deer he will share the meat with unrelated females, an act of generosity that improves his chance of mating with them in the weeks and months to come.14 For the variety of sociable ways in which they deploy sex, bonobos put common chimps in the shade. A female bonobo mates more often and with more males than a female common chimp. Male–female copulations are only the beginning. The most common form of sex observed in the wild involves two females clasped face-to-face, one holding the other off the ground, rubbing their swollen genitals together, squealing in apparent orgasmic delight. The powerful bonds that female bonobos fashion in sexual pleasure enhance female power and keep males in check. Male bonobos also stimulate one another, bottom-to-bottom, 37

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testicle-to-testicle, or even ‘penis-fencing’ as they hang from a branch. Irrespective of sex and age, bonobos seem always to be touching one another’s genitals, including with their mouths. And bonobos kiss. Enthusiastically. Too much tongue seems barely enough. Bonobo sex provides a versatile social lubricant. Oxford university primatologist Dr Isabel Behncke Izquierdo, who spent months studying bonobos in the dense Congo wilderness, told me that bonobos are quintessentially playful apes, and no clear line distinguishes sex from play. Individuals use sex-play to resolve and move on from disagreements like conflicts over prized foods.

Are you and I like common chimpanzees or are we more like bonobos? Whenever popular writing about primate sex lives scrabbles to pinpoint which of our primate relatives humans are really like, under the stultifying layers of culture, history and convention, we can be sure that we are witnessing an exercise in wishful thinking. A certain brand of robustly masculine conservatives, normally impervious to evolutionary science, relishes the vicious battles for status between male common chimps as much as their followers imbibe the bare-knuckled brutality of the Ultimate Fighting Championship octagon. They also embrace the idea of male chimp dominance over females as a parable supporting their preferred model of human gender roles. The notion that bonobos, our equally close relatives, have a female-dominated, sexually relaxed society took longer to influence popular views of human ancestry. Perhaps because they live in a smaller pocket of difficult-to-reach rainforest. Now, a new flood of enthusiasm for bonobos is washing through the study of human behaviour, carried by successive feminist waves and an incoming tide of gender equity, and changing how we see our ancestors and understand ourselves. 38

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Behind the new enthusiasm for bonobos lurks a sense that if only women had more power, or men were less overtly masculine, things would be more peaceful, safe and pleasant. Part of the bonobo attraction comes from a sense that a freer, easier sexuality might not be that far away. As Christopher Ryan and Cacilda Jethá put it in their popular book Sex at Dawn: Like bonobos and chimps, we are the randy descendants of hypersexual ancestors. At first blush, this may seem an overstatement, but it’s a truth that should have become common knowledge long ago.15

Ryan and Jethá argue that for most of the time since we shared an ancestor with chimps and bonobos, our increasingly human ancestors enjoyed a varied sexual appetite, moving fluidly among partners. Sex at Dawn leaves little room for doubt that Ryan and Jethá stack their chips behind the peaceable and sexy bonobo rather than the nastier chimp style. Again, however, there’s perhaps a little too much wishful thinking involved. Humans are, of course, neither chimps nor bonobos, but we can learn from both. Attempts to project a chimpish or bonobo-like silhouette onto the murky screen of the evolutionary past, may cause us to miss deeper and more interesting lessons from primate sexuality. Like the fact that the big social and sexual differences between common chimpanzees and bonobos arose in spite of truly minuscule genetic differences.16 Higher-density living turned chimps toward brutal male domination, and bonobos – who live at lower densities in thick rainforest – toward a more relaxed, matriarchal coexistence. In the coming chapters we will return often to the fact that a single evolved human nature can take on different characters, depending on the economic, cultural and technological context in which individuals find themselves. From the time our ancestors left the forest behind in 39

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favour of the open savannah, to humankind’s spread around the world into almost every conceivable habitat, variation and change have proved constant features of human ecology.

Human domestication Over the five million years since we shared an ancestor with the two hyper-sexual chimpanzee species, a number of interlocked changes turned humans from promiscuous apes who barely tolerated one another into hyper-social, highly cultural, economic creatures, capable of focusing on one mate for years at a time and inclined to lavish exorbitant care on their young. In brief, humans domesticated themselves long before they domesticated wolves, livestock, or the cereal grains that turned hunter-gatherers into farmers. In one of the major themes of human domestication, our ancestors evolved a ‘knack for monogamy’. That is not to say that humans became ‘a monogamous species’. What I do mean is that our ancestors evolved the psychological tools that made bonding and cooperating with a mate possible, if not compulsory. The ancestors we share with the chimpanzees could never bond or cooperate like human parents do. By a ‘knack for monogamy’, I also mean that men evolved a pair of knackers suited to more focused mating. Chimpanzees and bonobos have famously ample testicles, a typical affliction of species in which females mate with many males in close succession. Every sperm cell is a single ticket purchased in the fertilise-the-egg lottery that biologists call ‘sperm competition’. When females typically mate with one male in a fertile period, a male only needs to transfer enough sperm to ensure fertilisation. When females mate with several males, the more sperm a male transfers, the better his chances of being the father. That drives the evolution of big testes capable of producing copious sperm in species where females mate promiscuously. 40

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As a result, ape testicle size maps neatly onto ape mating behaviour.17 At one extreme, gorillas have very small testes relative to their massive bodies because females live in a silverback’s harem with no opportunity to mate with other males. At the other extreme, the biggest balls on the ape family tree belong to common chimps and bonobos, the champions of multiple mating. The physical proof that humans fit somewhere between slavish monogamy and chimp-like promiscuity is found in men’s modest testicles. For day-to-day comfort, men should thank their female ancestors who, over millions of years, came to mate with one or a very few mates at any one time. At the same time as their testes were shrinking, our ancestors were – not by coincidence – evolving into more intelligent and flexible beings. We evolved what the anthropologist Richard Wrangham calls ‘language-based conspiracy’ by which women and men can work together to keep aggressive and domineering ‘alpha’ males under control.18 This prevents destructive violence within the group and it also reduces inequality among males in mating success and reproduction. A casual look at any human society will reveal that the domestication of dominant men remains incomplete, but without the capacity to cut strong, aggressive men down, humanity is unlikely to have ever achieved much. Greater intelligence and less male aggression enabled our ancestors to modify their environments and to eke out a living in almost any ecosystem, while the other apes remained specialised and confined to their dwindling rainforest homes. According to psychologist Thomas Suddendorf, we owe our success to an ‘open-ended ability to imagine and reflect on different situations, and our deep-seated drive to link our scenario-building minds together’.19 That is to say, humans use their exceptional smarts and communication abilities to cooperate. The journey from specialist forest-dwelling ape to cosmopolitan cooperator makes for compelling reading, covered in several exceptional recent books that illustrate the value of deep evolutionary 41

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self-knowledge. Harvard anthropologist Joe Henrich shows how the accumulation of cultural knowledge was The Secret of Our Success. In Sapiens, historian Yuval Noah Harari considers how the ‘Cognitive Revolution’ kick-started history. It remains possible from these and many other popular accounts to lose sight of the conflict-riddled lives our ancestors led, full of inter-group strife and intra-group rivalry, much of which swirled around sex and reproduction. In The Social Leap, University of Queensland psychologist Bill von Hippel illustrates how these sexual and social challenges effected a quantum leap in social intelligence and thus the cognitive revolution. I would like to emphasise one ingredient of the social, cultural, cognitive leap that set humanity on its current course: the massive investments of time and care that parents came to lavish upon their children. That change to hyper-investing parents came about because humans could focus on their mates and families for long periods of time. They needed to, because human children are so expensive. Human mothering makes the demands on ape mothers look trivial. Pregnancy strains a woman’s ability to gather food and provide for any children she already has. In the last trimester, a big-brained fetus demands so much energy that mothers approach the physiological load of a marathon runner.20 At least a marathoner can stop running from time to time; the only way for an expectant mother to lighten her load is to give birth. Thus human babies are born small and helpless and do much more of their growing outside of the womb than great ape babies do. Childbirth represents the most dangerous thing any adult human routinely has to do, killing the mother in more than one in 100 births throughout history.21 Good medical care and sanitation pushed that rate below one in 10 000 in many industrialised countries, but in parts of Africa and the Indian subcontinent, death in childbirth remains miserably high. Once the dangerous business of childbirth is over, the baby demands to be fed every few hours, for up to two years, on milk made from the mother’s own bodily tissues. 42

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Having eggs, a uterus and lactating breasts turns reproduction into an Olympic effort for women. On top of that, each of our female ancestors spent much of her adult life infertile: pregnant, breastfeeding, recovering from miscarriage, too starved to conceive, and then, eventually, menopausal. As a result, there have always been far more men willing and able to fertilise eggs than women available to conceive. If you let an economist anywhere near the anthropological data, they will immediately conclude that fertile women, and women who show promise of becoming fertile, represent a scarce resource from men’s point of view. Scarcity, as the economist will continue on to tell you, confers value. On the other side of the heterosexual equation, men usually invest more than great ape fathers, for whom paternal love involves little more than not killing the youngster. Fathers’ contributions to the family vary dramatically among societies. Infamously, they also vary between individual fathers, from the hyper-investing dad who pours most of himself into raising his children to the deadbeat who shoots through at the first opportunity. Human fathers make a difference when they take an interest in their mates and children, protecting them from other men, contributing food and money, and helping children acquire the social and cultural knowledge that they need in order to flourish. Men who make sizeable, reliable investments in their families are scarce resources from women’s point of view.22 In short, throughout the domestication of humanity, raising a family became an economic enterprise, and sex took on properties of a transaction. The simple sexual transactions of chimpanzees, where mating with a male can assure a female his protection, perhaps a boost in status, and the occasional piece of shared meat, evolved into more valuable and more varied transactions. The transaction is often subtle, even disguised. So much so that talking about sex as a deal raises hackles and, for many, sullies its mystique. Viewed through the wide-angle lens of human evolutionary history, 43

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the main reason humans evolved a knack for monogamy is that children became gradually more expensive. As humans evolved into social, cultural, economic creatures, the contributions parents make to the family became more valuable to one another, turning sex into a valuable transaction.

Domesticating machines The grand five-million-year project of human domestication gradually turned people into far calmer, less aggressive and more sociable creatures than our early ancestors. A bit like the Novosibirsk foxes. It carved into the human psyche the potent evolved pathways and rewards by which people trust, befriend, become attached to, grow intimate with, and even love one another. And it ensured that as we mature, people learn an acute sensitivity to the give-and-take of human social transactions. The changes that made humans into sublime social cooperators, loyal friends, hyper-investing parents, and attentive long-term mates also tuned our sensibilities to important threats and opportunities. We scan for signs that another person is sexually interested in us. Some fly into a jealous rage when they detect a hint of sexual competition. We anticipate who might become a rival, and who could be a useful ally. And our domestication gave us the emotional means to trust and let others grow close to us. In short, as our ancestors tamed their mates and members of their groups, we evolved some of our most cherished, and also some of our least elevating human capacities. These are the evolved psychological buttons that artificial intimacies are learning, or will shortly learn, how to push. As they learn how to push those buttons, machines are involving themselves in the ongoing domestication of humanity. How will computerised devices learn to push our buttons? Mostly through the potency of machine learning. Machines can learn in a vari44

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ety of ways, many of which are based on artificial neural networks, computational structures somewhat like the connections of neurons in the brain. Multi-layered networks can learn in complex and sophisticated ways known as ‘deep learning’. Many of the impressive artificially intelligent applications that have suddenly washed through our lives – including the facial recognition tool you use to unlock your iPhone, Siri’s natural language processing that allows your phone to know you want directions to the nearest noodle bar, and the automatic fraud detection tools your bank uses to detect that your credit card was stolen while you were staring at the map – are products of deep learning. ‘Supervised’ machine learning algorithms work like a student learning from a series of problems in a textbook and then checking their work against the answers. From data tagged with the desired ‘answer’, the algorithm can learn the features of correct answers. When, for example, you try to login to one of your many online accounts and are asked, for security purposes, to prove you are human by clicking all the images with cars in them, you are tagging images from which machine learning algorithms will later learn to recognise cars. Ironically, you could be hastening the redundancy of that ‘prove you are human’ test. Algorithms can also be unsupervised, left to find patterns in the data without having any of the data tagged. An unsupervised learning model turned YouTube’s video recommendations into the viewing crack cocaine they are today,23 able to keep viewers on-site watching far more than they came for. Powered by Google Brain, YouTube’s algorithm prioritises videos that people actually watch. It makes connections from the videos a viewer watches to other videos, often in quite different genres. That way, viewers discover new content they didn’t even know they wanted to watch. It would not be far-fetched to assert that the algorithm quickly comes to know your tastes better than you know them yourself. Sometimes the learning is supervised, but by a machine. One such ‘semi-supervised’ approach pits one neural network against another 45

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to make what is called a pair of ‘generative adversarial networks’ (or GANs).24 One network – the ‘discriminator’ – classifies content. The other – the ‘generator’ – creates new content and throws it at the discriminator which then tries to distinguish it from real data, like a picture of a person. The arms race between generator and discriminator results in a whole new body of content – pictures of the person – good enough to pass off as the original. Sound like a useful kind of machine? They are, because they extend machine learning’s reach from detecting patterns and classifying data to generating new images, sounds and other kinds of media. GANs have already achieved infamy as the technology behind ‘deepfakes’, a portmanteau of ‘deep learning’ and ‘fake’. Starting with a dataset, like all the photographs of a person tagged on social media, the GANs will eventually generate an entirely new set of fake photographs of that person. They will all be so good that the discriminator network cannot tell them from the real thing. Nor can many people. I am Photoshop’s enraged, inflamed sense of rejection. To what uses have deepfakes been put? If you guessed political smears and revenge porn, you’d have the vast majority of deepfake content pinned. Not only photographs, but videos and voices succumb to the learning power of GANs. Bitter ex-lovers use deepfake technology to impose their ex-partner’s face on porn videos. No longer does one have to make porn to have it used against oneself. A video of Barack Obama calling Donald Trump a ‘dipshit’ might have turned out to be a bit of naughty deepfake fun, but one can only imagine the international chaos that videos of a leader saying something culturally offensive or belligerent might do in the near future. Indeed, Gabon’s President Ali Bongo nearly lost his job over a video appearance that may or may not have been deepfaked.

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Of all the algorithmic processes of improvement, machine learning may well prove the most potent. Natural selection shaped the entire living world, but it took billions of years. In any one species, vast numbers of individuals lived and died. Only some of them reproduced, and with each successful reproduction the genes that work well in combination slowly came together. As a way of getting from A to B, the meandering process of natural selection is notoriously inefficient. Even the selection that delivered domestic dogs took thousands of years, and the deliberate attempt to tame foxes took half a century. The performance-feedback-revision algorithms used by artists and authors feel excruciating in their gradual, hard-won gains. Improving products like AIBO depends on a fickle market, limited corporate decisionmaking, and expensive research and development. Animal learning algorithms, running on the hardware of brains with millions of connected neurons, work faster than evolution, creativity or product development. Once animals evolved the hardware to connect their behaviours with rewards, and thence to learn to repeat those behaviours, all manner of animal learning feats became possible. It also became possible for humans to train domesticated animals like dogs, and even wild-caught animals like dolphins, by rewarding the behaviours they wanted to reinforce. Humans, too, learn quickly when reinforced with rewards. From a teacher providing encouraging feedback to a computer game sprinkled with shiny little rewards, people learn fast. Machine learning enjoys the speed of learning. Given enough data to learn on, it also has something like the sheer iterative grunt of natural selection. As a method for improving performance over time, machine learning is capable of both awesome power and blistering speed. When it comes to artificial intimacy, that power and speed is being deployed to learn about you, me and the rest of humanity. Public fears about artificial intelligence typically centre on a takeover that enslaves us to AI overlords. A big debate around artificial 47

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intelligence concerns the possibility of creating ‘strong AI’ or ‘artificial general intelligence’ (AGI) that can understand or learn anything that a human can. At that point, AI will be capable of designing and building technology, and thus improving itself without human agency. Many experts consider it quite likely that will lead to a ‘singularity’ of rapid technological improvement that leaves humanity behind or even extinct.25 According to MIT polymath and machine learning expert Max Tegmark, however, few serious AI experts think it likely that AGI, if it ever arrives, will do so within the next few years.26 Artificial Intimacy is really about those next few years. Facebook has existed for a mere 16 years, YouTube for 15 and Twitter for 14. Given the astronomic speed with which those companies scaled, evolved and embraced AI, I would judge that the next 15–20 years will see at least as much change again, full of new players and as-yet-undreamed-of applications that disrupt our social worlds many times over, long before AGI becomes a thing. At the moment, machine learning algorithms are chewing through the vast drifts of data we leave behind on our meanderings through the internet, searching on Google or Bing, posting on Instagram or Twitter, buying from Alibaba or Amazon. We are literally training specific applications, like a family who have brought a new pet dog into their home, idiosyncratically praising, punishing, cuddling and feeding the new dog without really thinking about what the dog is learning. Make no mistake, the dog figures it out. More broadly, however, we are domesticating entire species of machine learning applications that study our behaviour. From data about our social, commercial and sexual lives, they learn what news to feed us and what ads to run. Our decisions to ignore, click or buy provide the feedback that shapes the algorithms’ evolution, helping each successive generation to become better at extricating value for their owners. But there exists no guarantee that the new machine learning applications will turn out to behave like loyal and beloved pets. They 48

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could come to occupy a place in our lives more like the fleas, ticks, worms and bacteria that come into the home with a new dog. They could become harmful parasites. Perhaps the domestication and training metaphor works better from the reverse angle. What if, instead of humans domesticating artificial intelligence, creating new beasts of computational burden, we are the ones being domesticated? Could the next phase of human domestication be just one more important job that we hand over to machines?

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Groom your friends Primates groom one another and humans gossip in order to tend relationships with friends and allies. Social media that emulate these ancient rituals could help people maintain or even expand their networks. They could also displace friends and weaken social ties.

One woman dominated the 1980s gossip media landscape. I recall a sunny school holiday Wednesday morning as an 11-year-old, when family and friends gathered around our television, and a staggering 750  million other people gathered around their televisions too, to watch her float up the steps of St Paul’s Cathedral trailing eight metres of radiant white silk taffeta. From the moment that Charles, then and now heir to the British throne, showed an interest in her, ‘Lady Di’ became the most photographed woman in pre-Kardashian history. For nearly two decades she graced the covers of more glossy magazines than every other celebrity combined. Princess Diana’s power to propel the printed gossip machine brought her stress, unhappiness, and, hounded by paparazzi through the streets of Paris late one night, the motor vehicle accident that killed her. The very week that I wrote this, her second son, Harry, and his wife, the American actress Meghan Markle, announced their intention to move to North America, and ratchet back their royal commitments. Themselves harassed by photographers and hacks, their every disagreement with other royals and every utterance regarding the mental burden of 50

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their fishbowl existence has been stoked and fanned by the gossip press. Little wonder, then, that Harry, approaching the age his mother was when she died, sought to go his own way. Intriguingly, when he and Meghan announced their new direction, they eschewed the press release, or the exclusive interview that might have been Diana’s style. They let the world know via Instagram.

Social explosion Many people in the eighties and nineties felt they shared an intimate connection with Diana. Much as they followed her every public word and action, however, Diana only knew her fans as a nebulous mass, even if she had a knack for making individuals feel seen and understood. Harry and Meghan’s Instagram followers may be able to like and comment on their posts, but again the illusion of intimacy runs one way. According to psychologists, as we grow closer to another person, we expand our sense of self to include them. The closer we become to them, the more we tend to think of their identity as our identity, of our views as their views, and that ‘mi casa como su casa’. That is the psychologists’ definition of intimacy: the incorporation of the other in our sense of self.1 The differences between a friend, a close friend, an intimate and a lover, amount merely to matters of degree, of how deeply we integrate our sense of them into our sense of self. The more we do so, the more generous, trusting and intimate the relationship becomes. Friendship and love might seem magical, but they don’t arise by supernatural intervention. They are built through mundane, iterative interactions, paying mutual attention, being generous, and disclosing aspects of ourselves to one another. And just as celebrities share small disclosures to build the illusion of intimacy with a fan, the processes that build friendship and love can be emulated by algorithmic processes too. 51

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We each have a small number of people to whom we are very close, a larger number we care for but who are not as close to us, and an even larger number in whom we simply take a passing interest. No matter how much we might wish it, we simply cannot be BFF to everybody we know. For one thing, who has the time to check in with and listen to every one of our friends the way we would with our bestie? For another, human brains simply don’t have that kind of capacity. The same is true for the grooming patterns of monkeys, baboons and non-human apes. Few scenes relax me more than sitting at a waterhole in the African bushveld, the smell of potato bush heavy on the warm air, watching a troop of Chacma baboons unhurriedly groom one another. Their attention to one another looks like a gently mimed conversation, and one quickly gains a picture of which relationships are important. Grooming requires focus on a single individual at a time, so no primate can possibly afford to groom every other group member enough to become close to them. Baboons and other primates spend more time grooming individuals in their close circle, and less time with distant associates. Through time spent together and physical contact, they establish trust and form alliances. These investments in the relationship bear fruit when needed later on, especially during fights, when allies make all the difference. Oxford University primatologist and anthropologist Robin Dunbar has studied all manner of primates over his distinguished career, showing that grooming dynamics remain largely the same from species to species, differing only in the numbers of relationships involved. Species with bigger brains – specifically that highly folded outer part of the brain called the cerebral neocortex – tend to have more ‘friends’.2 Bigger brains equals bigger groups. Dunbar predicted, from the immense volume of the human neocortex, that people would have far more friends than any other primate. 52

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The ‘active social network’ of friends and relatives with whom a person interacts regularly and depends upon, according to Dunbar’s predictions, should tend to be between 100 and 200 people. Combing through the archives of anthropological research, Dunbar found support for his prediction. Bands of hunter-gatherers tend not to get much bigger than 150 people. Organisational units in workplaces and armies tend to mirror this limit. Of course, most humans today live in settlements with thousands, perhaps millions, of people. But we also know that the secret to getting by in the city is knowing when to keep to oneself. When Dunbar examined personal networks of contemporary city-slickers he found that most of us have between 100 and 200 people with whom we maintain regular contact, whether that be face-to-face, on the phone, or online. That contact may function to make plans or share news, but in the background of those conversations what we are doing is a kind of allogrooming, maintaining our closeness to one another. The idea that we each have an average of about 150 friends entered the public consciousness as ‘Dunbar’s number’. Dunbar once described this layer of friends as ‘the number of people you would not feel embarrassed about joining uninvited for a drink if you happened to bump into them in a bar’.3 While there remains some quibbling among professional scientists about the ‘real’ size of the ‘natural human cognitive community’, they agree on Dunbar’s main point, that both brain architecture and the limited time available for the human expressions of allogrooming constrain human social capacities. The reason humans evolved such big brains is precisely because being social confers immense advantages. We owe our big brains to human domestication. Individuals in generations past who thrived and produced children tended to be the ones who kept good track of relationships, remembered who was friends with whom, recalled social debts they owed and favours that others owed them, and intuited well the mental states of others. The ones who became our ancestors tended 53

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to have bigger and better-assembled brains than their less socially astute contemporaries. In short, the process of human domestication gave rise to bigger brains, thus allowing further domestication, and so on, in one big virtuous social circle. Evidence from all over the behavioural sciences supports the idea that time and brain-power limit the number and quality of our relationships. People with big families tend to have fewer unrelated friends. For each relative to whom we devote time and headspace, that’s one fewer friend we can know and allogroom.4 Dunbar’s number and the 150-person ‘friend’ layer get so much attention that sometimes they eclipse the implications of Dunbar’s other layers (see Figure 2). Our very closest relationships with other adults tend to be limited to two very special people, including romantic partners or very best friends. Our ‘emotional support’ layer includes about five intimate friends. Psychologists talk about our group of closest friends as our ‘sympathy group’, because if one of them died suddenly it would cause us immense distress. The sympathy group tends to average around 15 people, the five in our emotional support layer plus ten others. Each layer in Figure 2 is three times the size of the one immediately inside it. The 50 ‘good friends’ includes the 15 in our sympathy group and another 35 of the kind you’d likely invite if you were throwing a party. Our 150 ‘friends’ include the 50 ‘good friends’ and 100 or so with whom we share information and occasionally ‘catch up’. Each friend needs to groom lest they fall out to your more distant friendship circles.5 And you need to groom them right back in order to stay in theirs. That grooming usually doesn’t involve picking over one another’s skin and hair, although perhaps that’s why brushing our children’s hair, or going to the hairdresser can be so calming. It is considered impolite to stroke or touch any but the most intimate of human associates, and deeply rude to attend to one another’s skin parasites. Instead, people allogroom by acknowledging and greeting one another, taking 54

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1.5 Romantic partner/best friend 5 Emotional support 15 Sympathy group 50 Close friends

150 Friends

500 Acquaintances

1500 ‘Faces’

Figure 2: Hierarchical levels of acquaintanceship with estimated average numbers, as described by Robin Dunbar. Area of circle represents relative size of each layer.

an interest in each other’s lives, and chatting. The attention people pay one another builds trust and intimacy, leading on to loyalty and generosity, which can make the difference between thriving and struggling.6 All that grooming doesn’t come for free, however. Places in each circle depend on us taking the time to groom. Entering a romantic relationship tends to cost a person, on average, two friends in their ‘support network’ of about five intimates.7 They seldom disappear from our lives. Instead they fall outward into the next layer, with knock-on effects in that layer. Likewise, having young children displaces friends from 55

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that inner ‘support network’ and the ‘close friends’ layer. Children and new romance have such direct consequences for our other friendships because they consume so much of our time and command so much of our attention. As a result, we have less headspace to devote to our friends and less time to groom them. According to Dunbar, two more diffuse layers exist outside of the ‘active network’, and they follow the same scaling rule. We average about 500 ‘acquaintances’, and 1500 people in the outermost layer of individuals whose faces we might recognise and names we might – occasionally – recall. As with the inner layers, these numbers don’t represent hard limits. For example, I tend to do okay remembering names but embarrassingly badly with faces, so I think my outer layers might be smaller than those of my more socially adept friends. You might be good at intimacy, and able to name ten equally close members of your emotional support layer, rather than the typical five. The scientific literature is full of detailed haggling over these kinds of differences, and over the average size and scaling of the layers. It is entertaining stuff for the few hundred people worldwide with a professional interest in social evolution, but ultimately the big takeaway messages remain the same. Humans have immense but not unlimited social capacity, and our relationships trade off against one another.

The meaning of gossip Complex language distinguishes the way people groom from the way any other primate does. We talk to one another, showing an interest in our friends’ lives, the places they have been, and the assorted feelings involved. More than that, we exchange information about other people and the lives that they lead. In short, we gossip. The word ‘gossip’ wears an acrid whiff, tainted by notes of malice, jealousy and schadenfreude, and by the piquant fear that when others 56

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gossip about us they engage those very emotions. But gossip often involves positive tones, of awe, inspiration, pride and affection, as well as a great deal of emotionally neutral content. Social scientists recognise that gossip transcends the limits of trivial scuttlebutt and fulfils important social functions. According to Robin Dunbar, social gossip dominates human grooming, occupying about two-thirds of freely formed conversation.8 Experiments show that talking about others fosters closer ties between gossips. A team led by University of Oklahoma social psychologist Jennifer Bosson studied what happens when two people share feelings about a third person.9 The participants, when asked, were sure that sharing positive information would bring them closer to the person they shared the information with. In fact, sharing negative attitudes did the trick. Presumably, according to Bosson and her colleagues, because negative gossip establishes boundaries between ‘us’ and ‘them’, makes the self-righteous gossips feel better about themselves, and because it is so much riskier to neg on somebody than to say something nice about them. The capacity to gossip massively increased not only the information our ancestors could share, but the number of friends they could groom. Primates can’t afford to groom for more than about 20 per cent of their waking time, lest they starve. Time constraints limit how many individuals they can groom, and thus the size of their individual networks. If we could only groom one-on-one, humans would seldom have enough time to service active networks larger than 80 people, even with our big brains. But human conversation can involve more than two people. Indeed, the average social conversation has four participants, greatly amplifying how many people one can groom in a day.10 That alone enabled humans to more than double the size of their active networks. Interestingly, humans average a similar proportion of time in social interactions involving conversation, about one-fifth of our waking hours, to the time that other primates spend allogrooming. 57

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Before even considering the content of conversation, the very fact that humans can gossip enabled a massive step-up in how many friends of each degree of closeness a person could have. Bigger, more connected brains enabled the neurologically demanding feats of language and of keeping track of big social networks, which then drove the evolution of even bigger and better brains. Each improvement in social brains upgraded our ancestors’ social capacity and improved their ability to use social connections to achieve more complex technological, economic and social feats. What people gossip about also matters. There exists no single ‘proper’ kind of gossip, but rather dozens of important topics. Discussion about fights, new friendships, sexual liaisons, and blossoming or withering romance, all allow gossips to tactfully navigate the shifting currents of interpersonal loyalty, enmity and cooperation. Chatter about the success and misfortune of others reveals how we might learn from their mistakes. Information about the lives of high-status people, often not known to us personally, provides insights into how we might lead successful lives of our own. How people have been judged for their actions, demeanour, and even their dress, speak of prevailing social norms. We also learn, often obliquely, about our own reputations, whom we have displeased, and who admires our actions. We gain validation, or we take heed of how we might mend our ways. We manage our own reputations, strategically talking up our achievements, or showing equally strategic modesty. And we can bolster the reputations of allies or undercut the reputations of rivals. All this action helps people learn how to live in their culture. Gossip also improves within-society cooperation by creating consistent expectations, sharing information, recognising generosity, punishing those who ‘free ride’ on the cooperative efforts of others, and as a ‘levelling mechanism’ that prevents aggressive, strong men from dominating everyone else.11 About five per cent of gossip entails discussion about 58

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who is taking advantage of others’ generosity, and who is a good team player. By policing free-riding and cutting down despots, gossip has probably lubricated the engines of cooperation and allowed societies to achieve more complex cooperative tasks.

Gossip tech If you were to design a technology to exploit the human appetite for grooming and gossip, you could do little better than social media. In Diana’s day, and before, fashion, lifestyle and celebrity news magazines fed readers’ hunger for gossip. But the twenty-first century has not been kind to the sober discussions of celebrity style in Vogue or Cosmopolitan, nor to the barely factual scuttlebutt of Britain’s The Sun or America’s National Enquirer. One reason seems to be that celebrities like Harry and Meghan use social media to service followers’ curiosity directly. Indeed, social media facilitates gossip far better than magazines. For one thing, where magazines could only afford to run stories about seriously famous people, ones who might be known by most readers, social media celebrity is far more niche. Around my own family dinner table we share little celebrity common ground. I follow runners on Instagram, and scientists and secular humanist thinkers on Twitter. My partner follows an assortment of fitness and style influencers on Insta and Pinterest, and favours news sources on Twitter. The eldest teen favours YouTube videos about technology, wildlife and gaming. The younger teens are preoccupied with TikTok and a range of people whose names I don’t recognise at all, though I am huffily assured they are ‘like, rilly rilly famous!’ Social media provides manifold ways to imbibe and share gossip about big celebrities, like royals and Kardashians, as well as about niche celebrities. The divide between celebrity and reader also blurs. A bit of thought, talent and time can turn a fan or enthusiast into a niche 59

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celebrity, without a publisher, a studio or a PR machine at their back. Even a single well-timed post on any social medium can deliver the Warholian 15 minutes of fame. Social media also offers the chance for people to share their own thoughts, achievements and activities, curated, in the gossip tradition, to manage their reputations. Not only do we get to post what we do, but we tag those we do it with, hint at our allegiances, and give feedback and validation in the form of comments, hearts, likes and shares. Internet users worldwide spend an average of 153 minutes per day on social media. Assuming eight hours of sleep, users currently spend 16 per cent of their waking hours on social media,12 closing fast on using up the entire 20 per cent of waking time that humans have, for millennia, spent grooming and gossiping. It certainly looks like social media are changing human social commerce at superfast broadband speed. But are they helping people live better lives, or getting in the way?

Facebook friends Perhaps the most effective social medium when it comes to friendship networks is the one that turned ‘Friends’ from a sitcom into a digital currency. On Facebook it doesn’t matter if everybody knows your name, or even remembers what you look like, because the designers put that information at your fingertips. You don’t have to call or meet up with a friend in order to groom them – you can just like the photograph of that fish they caught with their daughter or comment beneath their latest rant about climate change. Viewed in the deep perspective of how social behaviour evolved, perhaps there really is a genuine use for Facebook? Perhaps, by storing information and making grooming easy, Facebook frees us up from the constraints of our cerebral neocortex size, allowing us to have and hold onto more friends? On the contrary, research suggests that Facebook has not upgraded 60

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humanity’s capacity for closer, inner-circle friendships. Users in the UK, when asked to estimate – without looking at their accounts – how many Facebook ‘Friends’ they have, typically report between 150 and 200, consonant with Dunbar’s number.13 They also report having an average of 4.1 Facebook Friends they would depend on for emotional or social support in a crisis and 13.6 close Friends. These numbers don’t differ much from Robin Dunbar’s original estimates of five and 15. None of the evidence I have sifted through supports the case that online social tools have expanded how many intimates or close friends people have. Nor have they altered the average number of real-life friendships or changed the size of people’s active networks. What social media do seem to have done, however, is permit people to groom those they seldom see or who live a long way away. The high-speed, lowcost grooming made possible by allow people who have moved vast distances from where they grew up, whose family and work commitments keep them from going out, or who find themselves socially distanced amid outbreaks like the COVID-19 pandemic, to maintain some relationships. That grooming can stabilise networks, service old friendships that would otherwise have withered, and provide the gravitational attraction that slows or even stops those friendships from drifting outward to more distant layers. Facebook informs me I have 535 ‘Friends’. That amounts to about three-and-a-half times Dunbar’s number, and I know for sure that there are many people I would call ‘friends’, together with some relatives and colleagues in my active network, who aren’t connected with me on Facebook. Am I some kind of a social phenomenon? ‘Hardly!’ those who know me best would scoff. In fact, I suspect my networks are relatively small and quite poorly maintained. About 70 people I went to school with three decades and two continents ago can be found in my list of Facebook friends. Apart from the dozen or so who I chat with via direct message or take the time to visit when travel plans permit, the rest exist between ‘acquaintance’ and 61

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‘familiar name’ for me. My 535 Facebook Friends include members of every one of my social circles, plus people who have dropped out of those circles and whose names and faces have fossilised into a further, outermost layer of somebodies that I used to know. So perhaps social media, by keeping track of the former connections we no longer maintain, is extending the most distant outer layers of our social universes, maintaining them quietly on our behalf in a kind of social cold storage, without using up our limited time and headspace. Perhaps this is a free service we get from Facebook: old friendships and acquaintances, ready to reanimate. Just add attention, a pinch of time and perhaps a glass of wine.

Does that time spent caring about the lives, opinions and politics of people in our distant, outer friendship layers cost social media users closer to home? The time and attention we spend on our outer friendship layers as we scroll through Instagram, liking pictures and videos of people we don’t really know, is time we cannot spend allogrooming with our parents, children, lovers and intimate friends. Some people can hold a credible conversation even as they pore over their iPhone. Still, they appear less than fully present, often not retaining what the other party says, and occasionally interrupting with a laugh or a comment relevant to their other – virtual – conversation. Serious two-way conversation dries up. I am far from the only one concerned about the dilution of innerlayer grooming by the attention and time spent on the far outer online layer. According to MIT psychologist and author Sherry Turkle, we are diminished by the attention we squander on our devices and by the resulting erosion of true conversation.14 Only in conversation can people fully practice what Turkle calls ‘the empathic arts’: making eye 62

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contact, attending to subtle cues of voice modulation and body language, listening and putting ourselves in the other’s position. Face-to-face conversation is the most human – and humanizing – thing we do. Fully present to one another, we learn to listen. It’s where we develop the capacity for empathy. It’s where we experience the joy of being heard, of being understood. And conversation advances self-reflection, the conversations with ourselves that are the cornerstone of early development and continue throughout life.

Instead of allogrooming one another through one-on-one interactions and small-group gossip, much of the grooming that takes place on social media happens out in the open, in the form of likes, hearts and retweets. Social feedback has moved, in the blink of a digital eye, from qualitative to quantitative. While we still groom and gossip somewhat privately face-to-face via the antique technologies of phone or email, and via private messaging apps, a lot more of our grooming happens out in the open where others can see. People of all ages spend much of their grooming time and headspace now interacting with the bigger layers of more distant online acquaintances. Those of us over 30, however, learned our social chops before social media. Today’s teenagers and young adults learn to allogroom and build the inner friendship layers that will sustain them in adulthood by simultaneously navigating both IRL and online. Their virtual worlds of group chats, vlogs and social media accounts expose them to outer layers of distant friends and acquaintances far more extensive than any pre-smartphone generation faced. Their formative interactions don’t depend on whispers that somebody likes somebody else, or that one’s actions are approved or disapproved of. Rather, they depend on quantitative evidence in the form of follows, unfollows and fleeting numbers of ‘likes’. This shift in the way young people build their social worlds 63

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happened so fast that researchers don’t even know what questions about the consequences to ask yet, much less the answers. But we are seeing the symptoms. Those symptoms are most obvious among what psychologist Jean M Twenge calls the iGen, the generation of people born after 1995 who ‘grew up with cell phones, had an Instagram page before they started high school, and do not remember a time before the Internet’.15 For the iGen, texting, direct messaging and posting on social media displaced the old forms of direct communication, cutting deep into the time they spend with friends and family, playing sport, watching television, reading, and doing all manner of other activities that occupied previous generations. Add to these changes in activity the risks of online bullying, and the price of tech suddenly looks awfully steep. According to Twenge’s study of generational trends, the iGen has suffered astronomic spikes in anxiety, depression and suicide.16 Kids who spend more time on screens, particularly on social media and textbased interaction, suffer the most. Other researchers have arrived at less dramatic conclusions about the relationship between screen time and adolescent wellbeing.17 For now, however, it is worth noting that tech gurus, from the late Apple founder Steve Jobs, to Facebook founder Mark Zuckerberg, and Cloudflare’s Susan Hobbs have all banned, or at least made noises about limiting their children’s social media use.18 The discussion will likely ensue for years, until more direct forms of evidence can be marshalled. The best experiment I have seen shows that adults suffer when they spend too much time on social media. Economists from New York University and Stanford paid a large sample of Facebook users to quit the platform for four weeks and compared them with a control group who did not have to take a Facebook holiday.19 When they followed up at the end of the study, those participants who quit Facebook were happier, more satisfied, less anxious and less depressed than the control group. They were also less keyed up about politics and less politically polarised than the control group. This study 64

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provides some of the most rigorous evidence yet that social media use compromises mental health and contributes to the existence of politically polarised ‘thought bubbles’. Social media hacked humanity’s friend-grooming behaviours and used up much of the time and headspace users would otherwise devote to grooming friends offline. Yet not all the news about social media is bad. They provide easy ways to keep in touch with people we care about, grooming them and keeping them close even when it becomes impossible to meet. During the COVID-19 pandemic, social media gave people who could not travel to see loved ones, or who had to isolate at home, ways of involving one another in their lives that had never been available during any of the many devastating plagues throughout history. Who knows how much worse off people might have been if not for their favourite social media channels? Jean Twenge’s study of the iGen shows that there are plusses to consider before you confiscate your children’s phones, tablets and computers. The iGen are, in many ways, better behaved, and safer than ever. They don’t drink as much, they don’t have risky sex as often, and they don’t do nearly as much of that crazy risk-taking that too often ends in tragedy: driving too fast, taking drugs or brawling. Today’s kids, raised by helicopter parents, digital babysitters and the Nanny State come up nicer for it. They show more concern for the planet, greater interest in equality, and broader tolerance of differences than generations before them. Could it be that this younger generation are already being domesticated by their devices? More generally, people have had to decide how to balance the downsides of new technologies against the upsides many times before. New technologies perennially disrupt communication, from handwriting to the printed word to words written on screens; from the telegraph to the telephone to Skype; from radio to television to YouTube. Every one of these technologies transformed human sociality and challenged the ways people groom one another through communication. 65

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Adrienne LaFrance, writing in The Atlantic in 2014, uncovered a common thread of dissatisfaction stretching back over 150 years of technological change. News delivered by telegraph was ‘superficial, sudden, unsifted, too fast for the truth’ in 1858. The telephone was creating a race of ‘people who hear better with the left than with the right ear’ in 1904. Radio was a ‘loud and unnecessary’ nuisance in 1924. And, in 1937, television seemed dangerously spellbinding and also a way for people to be spied on through their sets.20 Just as people adjusted to those other changes, so it is likely they will adjust to the new technologies, given time, research and certainly a bit of trial and error.

Artificial intimacy? Sony deliberately built AIBO in order to cosy up to humans’ deep, coevolved affinity for dogs. The robot emulates a puppy in size and shape, movement, curiosity, interests and even learning ability. By no means perfectly, but sufficiently to charm human owners into dropping $AU3995 for the latest model, getting broken robotic pets repaired, and even holding funeral ceremonies when they reach the end of their long walkies. In much the same way, some artificial intimacies, like sex robots and therapist bots, will also be deliberately designed to emulate human relationships. Without deliberately setting out to do so, social media platforms have already hacked into some of the most fundamental processes of human sociality, the ways in which we groom our friends by showing interest, paying attention and gossiping. Facebook, here and now, teeters on the brink of artificial intimacy, already a matchmaker for real friends, and beginning to blur the line with virtual friends. Social media is, even at this embryonic stage, already the most ubiquitous and – from the point of view of usership and sales – the most successful form of artificial intimacy yet invented. 66

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One might consider the end of this chapter as the present day. Social media companies make up some of the biggest investors in artificial intelligence, but their platforms work because of what they allow people to do. The next chapter will consider some aspects of the near future, in which the superpower of machine learning will enable social media, computer games and countless other technologies to hack the inner layers of our social networks, including intimacy, romance and perhaps love.

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The intimacy algorithm The business of integrating our sense of another into our senses of self is an iterative process well suited to machines.

The possibility of machines that could evoke intimacy flickered to life in the mid-1960s in the form of ELIZA, an early chatbot created by MIT computer scientist Joseph Weizenbaum. ELIZA’s main script, which Weizenbaum named DOCTOR, cleverly emulated the manner of psychotherapy pioneered by therapist Carl Rogers, using open-ended questions to steer the user toward talking about themself. You can chat with a version of ELIZA today via one of several websites.1 For example: ELIZA: How are you today? Me: I am feeling anxious about my writing. ELIZA: How long have you been feeling anxious about your writing? Me: Since Christmas. ELIZA: Can you elaborate on that? Me: Since I took leave and had to try writing at home rather than at work. ELIZA: I’m not sure I understand you fully.

Given the way an even moderately complex sentence leads straight back to ‘I’m not sure I understand you fully’, coupled with the ubiquity of more sophisticated chatbots today, it is easy for somebody living in 68

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the 2020s to lose sight of ELIZA’s historic importance. With simple pattern-matching rules, pointing to an equally simple suite of questions or responses, ELIZA could sustain a conversation, especially if the user stuck to talking about themself or their life. And users found it easy to think of ELIZA as human. According to Weizenbaum, in his original paper about ELIZA/ DOCTOR, ‘Some subjects have been very hard to convince that ELIZA (with its present script) is not human’. Suddenly, it seemed possible that machines would eventually pass mathematician, cryptographer and computer scientist Alan Turing’s famous test, conversing in such a way as to be indistinguishable from a human.2 Weizenbaum later recalled: I was startled to see how quickly and how very deeply people conversing with DOCTOR became emotionally involved with the computer and how unequivocally they anthropomorphized it … Once my secretary, who had watched me work on the program for many months and therefore surely knew it to be merely a computer program, started conversing with it. After only a few interchanges with it, she asked me to leave the room. … What I had not realized is that extremely short exposures to a relatively simple computer program could induce powerful delusional thinking in quite normal people.

Choosing to emulate Rogers’ method of therapy in the DOCTOR script proved a stroke of pragmatic genius. Few conversations are as one-sided. Only a limited number of versatile answers suffice to redirect almost any patient. Today, DOCTOR’s legacy lives on in a new generation of artificial intelligence therapy tools, designed to hold up the listening end of the conversation. Now, as then, what many people need is a listener rather than another talker. Take Mend,3 for example, a smartphone app that encourages users 69

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to work through their recovery from a romantic breakup. It asks questions about the relationship, the circumstances of the breakup, and any contact the user has had with their ex. It strikes an even, but sympathetic tone, offers advice curated by mental health professionals, and reminds the user to exercise self-care by eating well, exercising, meditating and socialising. It also provides a space for journal entries and writing prompts. Mend works as it does courtesy of artificial intelligence. The smartphone app provides the interface, connecting to cloud-based natural language processing centres and machine learning grunt. It is unclear just how much machine learning goes into tailoring individual cases, but the app seems to be continually improved based on people’s journal entries and responses to questions. The smart people who developed Mend realise that recovering from a breakup takes time, self-care, the sympathy of friends who will listen, and the occasional spot of good advice. Like ‘stay away from your ex’. Could it be true that the opposite process – falling in love – might have a similarly simple basis? And does AI have anything to offer in that regard?

Love apptually Anyone who scoffs that no intimacy could reside in the space between human and mobile device has likely not had contact with teens or young adults for quite some time. Apps and other software have been pushing users’ intimacy buttons for at least a decade. As is so often the case in twenty-first century pop culture, computer games lead the way. Since 2009 a growing number of men, most of them Japanese, have entered into relationships with virtual girlfriends on a Nintendo DS game called LovePlus. Users choose to pursue one of three impossibly cute, anime-inspired virtual girlfriends – Manaka Takane, Rinko 70

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Kobayakawa, or Nene Anegasaki – through conversations, ‘meeting’ at appointed times, and virtual field trips. Each girlfriend has her own back story and distinctive personality. Players learn quick-smart how to treat them right. Miss an agreed appointment or, heaven forfend, her birthday, and she won’t let you forget it. The developers have balanced the virtual relationship blend of incentive and punishment to perfection. Despite the cartoon-like simplicity of it all, users acquire genuine affection for their virtual girlfriends. They go on trips to locations portrayed in the game, on collective dates, or even on weekends away as couples. That is to say as one man and one Nintendo DS. LovePlus offers a very simple but effective ‘gamification’ of early romance. According to anthropologist Patrick Galbraith, commenting in a 2014 Huffington Post article, ‘I would say that a relationship with a LovePlus character is a real relationship … people are really intimately involved’.4 Few stories about ‘dating sim’ games compel stronger reactions than the tale of 27-year-old LovePlus player, ‘Sal 9000’ from Tokyo, who married Nene in a 2009 ceremony streamed live on the web to thousands of viewers.5 Clad in a white suit and gloves, Sal spoke about the fact that he had played the field, having had several video-game girlfriends before Nene. Like many men who play games like LovePlus, Sal professed no need to find a girlfriend out there in the world of flesh-andblood humans. Unable to read or even understand Japanese, I found it difficult to follow the YouTube videos of the wedding ceremony. I also couldn’t quite grasp how Nene, restricted to the small and rather clunky confines of a Nintendo DS console, held up her end of the ceremony. But all the humans I saw in the video looked happy. As one might expect, the discussion about stories like Sal and Nene’s wedding often sneers at the deluded souls who waste their time pursuing a pale electronic facsimile of the real thing. Commentators who snicker at the deluded love fools who date and marry digital characters on their Nintendo DS miss an important point. Sometimes it helps to stop worrying about what people should be doing, and take a 71

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moment to consider what they are doing, and what that tells us. What is happening is that dating sims and various other apps are gamifying intimacy, hacking some of the emotional and relationship needs of players and users. LovePlus is the international celebrity of the gaming sim world, but the genre has many manifestations. Some of them have, at best, only a vague sense of direction or goal. Take, for example, VR Kanojo, a virtual reality game that involves the player donning a VR headset and holding controllers in order to hang out in their girlfriend’s bedroom. Together they choose outfits for her, and they chat. Oh yes, and, most sessions involve her getting nude or near-nude, and, with her consent, some touching. The more female-oriented Mystic Messenger involves elements of a choose-your-own-adventure graphic novel and a text-messaging-based computer game. Players take the role of a female character who gets involved with a hazy group known as Rika’s Fundraising Association. In each of the possible routes the game can take, players dive into deep and detailed interaction with one of the characters. So much so that users’ comments on gaming discussion groups convey palpable emotional connection to the characters. Choose-your-own-romance novels have been unshackled by the internet and by smoother segues than the old fashioned ‘turn to page 54’. Instead of pursuing an 11-day route on Mystic Messenger, or the evergreen high school romance of LovePlus, one can download and consume – via a combination of reading, watching video clips and answering multiple choice questions – several romance scenarios in an afternoon. From computer games to participatory stories, developers have imbibed the character and plot development secrets uncovered by centuries of fiction writers. From Anna Karenina to Harry Potter, any reader knows the genuine affinity one can develop for a character, and the emotions their journeys evoke. Computer games provide chances 72

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to interact with those characters and their journeys in ways that novel readers can’t. That may be one of the reasons the rise of computer games since the 1980s has been mirrored by a 25 per cent decline in adult readers.6 Expect that as natural language processing and generation become more fluid, and AI permits players to have more flexible relationships with characters about whom they care, computer games will carve further into the fiction-writers’ niche. Developers of apps and games already know how to evoke feelings of closeness, intimacy, and even love. Reflexively, one might be tempted to throw up a barrier between the ‘real’ and the ‘virtual’. Surely simple software, that cannot reciprocate those feelings, is merely inducing a delusion? I am happy to consider that the effect ELIZA or Nene Anegasaki have on user-players is a delusion. I would argue that the same delusion applies to those genuinely intimate or in love with real people. At best love is merely a shared delusion. Artificial intimacies merely do, in their own way, what swindlers, salespeople and seducers have done for eons. They learn how to become close to somebody quickly, fast-forwarding through the usual time-honoured build-up of mutual knowledge and trust. They know, at least implicitly, that intimacy and love are iterative, algorithmic processes, simpler in their origins than one might expect, given the rich and complex feelings that they evoke. As we shall see, those processes can be emulated, and faked, often to the benefit of the person – or machine – doing the faking.

Algo-grooming Absence does not, as a general rule, make the heart grow fonder. Interaction does the trick. Allogrooming involves seeing and hearing, and being seen and heard. Intimacy with another grows in sharing our innermost thoughts and learning their intimate details. Dating sims 73

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succeed because, in their simple, text-based way, they allow users to disclose their private thoughts, and ‘characters’ to send similar machine-generated disclosures. Psychologists Arthur and Elaine Aron, who developed the idea of intimacy as ‘including the other in the self ’, famously showed that interpersonal closeness can be deliberately cultivated.7 Their approach involves an escalating process of self-disclosure, in which pairs of people ask and answer a series of questions about themselves, their past and their private thoughts. Through 36 questions, pairs work their way from fairly straightforward revelations, such as: ‘Given the choice of anyone in the world, whom would you want as your dinner guest?’ through to more acute disclosures, like ‘If you were to die this evening, with no opportunity to communicate with anyone, what would you most regret not having told someone? Why haven’t you told them yet?’ The Arons and their collaborators refined their approach over many years, testing their predictions in experiments on randomly paired individuals. Pairs directed to follow the self-disclosure questionnaire come to feel much closer than pairs who follow a questionnaire of 36 relatively trivial small-talk items. They remain closer than the smalltalk pairs do through follow-up meetings several weeks later. The Arons’ method provides a scientific understanding of how deep allogrooming works in the inner layers of close friends and intimates. One couple of volunteers who performed an early version of the Arons’ test fell in love and married. This cute anecdote hints that maybe the method carries beyond interpersonal closeness and can cultivate romantic love. Some 20 years after the scientific paper was published, writer Mandy Len Catron wrote a wildly successful New York Times article about how she and a man she already liked spent an evening following the Arons’ method, and how they ended up falling in love. The questions reminded me of the infamous boiling frog experiment in which the frog doesn’t feel the water getting hotter until it’s too

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late. With us, because the level of vulnerability increased gradually, I didn’t notice we had entered intimate territory until we were already there, a process that can typically take weeks or months.8

Through her essay, Catron completed the translation of some rather specific scientific research into an algorithm more potent than any love spell or potion. Inevitably, there is now also an app. Actually, several apps. Simply search ‘36 questions’ and you will find numerous apps that gamify the questions from the Arons’ 1997 paper, usually verbatim. Most claim copyright, some charge $1.50, and I found none that credit the original source. The experimental generation of interpersonal closeness lends itself perfectly to monetisation in the smartphone medium. The Arons’ approach illustrates the potency of the scientific method. They drew on decades of combined experience in psychology, building on the steady accretion of knowledge that science provides, in order to understand how and why self-disclosure kindles closeness. They then deliberately designed tools to escalate self-disclosure, thus causing pairs who use those tools to begin enmeshing their senses of themselves. Last, they tested their method against an alternative – the small-talk questionnaire – to separate out the effects of time and conversation from the specifics of self-disclosure. This is exactly how scientific research should work, progressing from theory about how the world works, to a prediction about what should happen under specific conditions, to a fair test of that prediction. Based on the results of that test, the theory might need to be rejected, or modified, before a new round of prediction and testing can begin. Science has, over centuries, proved a potent algorithmic tool. It seldom proceeds quickly because each step in the cycle of theory A prediction A test takes time to do with proper care and diligence. The benefit, however, is that the scientists usually end up closer to understanding not only how the system they are interested in really works, but also why it works. 75

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Machine learning is another algorithmic process for moving from input to output. We have already established that its speed and power give it advantages over natural selection, animal learning and product development as processes for improvement. Now it threatens to overshadow the scientific method, too! Sometimes machine learning delivers insights that look a lot like science. But how machine learning algorithms deliver those insights often remains a mystery, even to their developers. Machine learning mostly works by finding associations between variables in massive datasets. Some of those associations are meaningful and others tend to be pure coincidence. The result can surprise and leave even the best experts scratching their heads.9 From the songs I have obliquely referenced thus far in this chapter – see the book’s Spotify playlist10 – it isn’t surprising that Spotify serves me up plenty of Queens of the Stone Age, but how its algorithms could have predicted Flight of the Cosmic Hippo, well, No One Knows. Machine learning does not have to follow the rigid knowledgebuilding rules of the scientific method. The programmers who build machine learning algorithms strive only for an efficient outcome – accurate predictions, more engagement from customers, or effective targeting of advertisements. They just want the machine to work, and they are far less interested than scientists would be in how or why it works the way it does.

Learning about you Imagine if somebody, say a developer at a large social networking platform, wanted to use their massive datasets to learn how people on the platform draw closer to one another, establish intimacy, or even fall in love. If they had a background in social psychology, they might know that escalating self-disclosure through a series of questions would 76

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kickstart their efforts. There would be no need, however, to trawl through the published literature to discover the nuances of interpersonal closeness. There would also be little point plagiarising the Arons’ original suite of questions, like the app developers did. Instead, they could train a suitable machine learning algorithm on their data about the actual questions that real people ask each other, as well as the answers they give, and how the relationship subsequently progresses. That algorithm would likely make short work of improving on the Arons’ method – the best that science has to offer. Without the constraints of theory A prediction A test A theory, necessary if you want to know how and why things work, the algorithm could explore all manner of possibilities to discover the questions, answers and even the words that are most effective in drawing people close. All of a sudden, closeness, intimacy and romantic love are stripped of their last shreds of ineffability and rendered in bare algorithmic terms. Another one of those hopeful dividing lines between human and machine turns to mirage. With such knowledge, the developer could go straight for the lowest-hanging fruit, mining online conversations to generate listicles of ‘Most effective ways to fall in love’. Then, perhaps, they would build artificially intimate bots – the ultimate virtual friends – that forge more intimate connections with humans than any machine has managed before. AI analysis of social media user behaviour is already able to peer into users’ private lives. Machine learning algorithms can learn to predict, with impressive accuracy, who somebody’s spouse or romantic partner is, based only on their patterns of Facebook friendships.11 On Valentine’s Day 2014, Facebook revealed that it can predict when a pair of users will change their relationship status on the site from ‘single’ to ‘in a relationship’, based only on how often they posted on one another’s walls.12 An AI analysis of the words and intonation couples use when they speak to each other in therapy was as good as, or even better than, 77

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trained human observers in predicting whether the couple would break up.13 One can only imagine that engineers at big social media companies are looking to do the same kinds of things with the information users post about their partners and spouses; much of it, in my viewing experience, ill-advised. These might seem like obvious insights. Many people believe they would likely draw the same inferences as the algorithms do when presented with the same information. It is worth noting, however, that in each example AI exceeded – usually by some distance – human capacity to make the same inferences. Facebook, Instagram, Snapchat, TikTok and Twitter already have the data from which to infer when a user is falling in love, when they are starting an affair, when they are likely to break up, and if they are fighting with their partner. By making those kinds of inferences, rather than relying only on the more granular information that users provide – relationship status updates, birthdays and the like – the platforms have paved in gold their road to future profits by serving up advertisements about romantic gifts, getaways, counselling and divorce lawyers at the appropriate times. Relatively simple applications of machine learning to analyse patterns of connections, frequencies of posting and the words people use, are already opening windows into our intimate lives. Insights that are useful enough to provide an economic return, in terms of advertising. What, then, are the prospects of machine learning mining the specifics of human allogrooming habits, and then learning to mimic them, so that machines and their masters can groom us, according to the more commonplace and sinister contemporary meaning of that word? Good datasets exist already, in the records of what people have said on messaging apps. We might also have enough information to answer questions about how the relationship proceeded. Did the two people get closer? Did they communicate more often and over many subsequent months? Did their conversation wither on the vine? And did one party unfriend or unfollow the other? From this kind of information, 78

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algorithms can compile the best words or phrases to include in those conversations people want to kindle. The better natural language processing and machine learning become, the better machines will become at learning the deeper rules of intimacy and improving on the Arons’ method. Humans are remarkably flexible communicators. Members of my household know that I often have a very fuzzy idea of what I am looking for, and that when I ask the location of the ‘asparagus’ they should guess the appropriate noun. Natural language processing and machine learning won’t crack that kind of idiosyncrasy for some time, but they already grasp that ‘pass the coffee, please’ is largely the same as ‘could I have another flat white’, and ‘I really need caffeine!’ As natural language processing improves apace, machines will likely get better at learning the subtle, ever-shifting vocabularies and rhythms people employ as they groom one another. With more of the rules of intimacy available to machine learning, the more machines will be able to deploy – on their users – the most successful words and cadences, optimised message lengths, and the best patterns of when to make contact and when to be unavailable. In these ways, machines will grow more effective at drawing us close and persuading us to incorporate them into our senses of ourselves.

Virtually friends As artificial intimacies inveigle themselves into those places in our limited social minds normally reserved for friends, intimates and lovers, things will never again be quite the same. A computer game will never be ‘just a game’. Social media will no longer be merely a ‘platform for sharing’. And people would do well to treat any hardware or software with the suspicion they would usually reserve for a potentially malevolent stranger. 79

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To gain a sense of just how common and varied we might expect virtual friends to become in the near future, consider again that circle in Chapter 1’s taxonomy of artificial intimacies, including the zone of overlap with the other two main types of artificial intimacies, the algorithmic matchmakers and digital lovers (see Figure 1, page 14). The applications are all easy to imagine, a short jump into the future from present-day digital social media and digital assistants. I expect that the variety of virtual friends will soon explode well beyond the territory of my simple Venn diagram, as creative designers escape the familiar. The Therapist is the direct descendent of ELIZA/DOCTOR, Mend and a virtual ecosystem of mental health apps for treating problems like anxiety, depression, sleep disorders, substance abuse, gambling and self-harm.14 Smart phones are already being used by mental health professionals to reach those in need, with the help of AI.15 The COVID-19 pandemic threw up new health challenges even as it made travelling to appointments more difficult, resulting in a massive surge in virtual health service use. In April 2020, as Australia locked down, telehealth consultations for mental health rose fivefold.16 In the USA, demand for virtual care rose 600 per cent in the first quarter of 2020.17 Amid the new anxieties and social distancing realities, an army of digital therapists spotted their opening. Woebot, for example, uses AI to converse with users and help them access important therapeutic techniques like cognitive behaviour therapy (CBT), mindfulness, and dialectical behaviour therapy. The evidence that mental health apps provide therapeutic benefit is weak, by clinical standards,18 but promising. A small study led by Woebot developer Dr Alison Darcy, suggests that among a small sample of college students there are some measurable reductions in depression.19 Teenagers are often unaware they need help, unwilling to seek it or simply unable to find it. They also love their smartphones. The online e-therapy tool SPARX, developed at the University of Auckland 80

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by psychiatrist Professor Sally Merry and colleagues, teaches teenagers CBT skills to cope with symptoms of anxiety and depression. It does so by creating a lavish fantasy world, richly rendered and full of Māori graphics. Accompanied by a virtual guide, users travel to seven provinces to ‘complete quests that restore the world’s balance and defeat the pesky negative thoughts, called Gnats’. By interacting with a variety of different characters, solving puzzles and completing games, users learn skills they can use to ‘feel better, solve problems and enjoy life in the real world’. In a randomised trial, participants who were allocated to SPARX performed as well as those who had a human therapist provide the usual CBT treatment for teenagers.20 Through games, listening and tailored advice, therapist applications can gently guide the user to the core of the issue, enable them to cope with negative feelings or distress, or empower them through tools like CBT. Such an artificial intimacy might also be able to intervene by connecting users to human therapists, mental health services or an ambulance. Improvements in AI will see these tools building trust with users in sustained, customised ways, and accessing ever more powerful therapies and interventions. Along the way, researchers might, as a spinoff from all the data that the applications gather, make new discoveries, currently unknown to psychology, about how to effectively engage with, support and treat users. Russian company Endurance combines two developments to help care for patients suspected of early-stage dementia.21 A 3D-printed mobile phone mount swivels automatically to face the patient as they move about their room. On the mount, the patient’s phone runs a chatbot that can hold friendly conversations about more than 20 topics. As it encourages the patient to discuss their interests and their past, the chatbot also tests their ability to remember information in different ways. It identifies where conversations deviate from one another, indicating memory issues, and allows doctors and family to assess how the patient’s memory may be deteriorating. 81

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Other virtual friends provide more symmetric relationship options. They might have a backstory, and can ‘disclose’ information that, coming from a person, would be considered personal. They can initiate and respond to regular contact with the user, sharing salient information in ways near-indistinguishable from human grooming and self-disclosure. They learn what the user likes and dislikes, both through explicit exchange and indirect inference. Virtual friends could be designed to relate at a given level of closeness, as set by the user or by the owner of the technology. These artificial intimacies could be computer game characters, apps, characters in stories, or they could come to function as just a ‘friend’. Those characters and friends need not remain at arm’s length. The better virtual friends become at intimacy, the more valuable they will be in artificial intimacies that emulate romance and sex, dragging us into the overlap between virtual friends and digital lovers. Manaka, Rinko and Nene from LovePlus showed the way before AI arrived on the scene. Imagine how game flames animated by artificial intimacy could bewitch players of all genders and sexualities, who speak any language, and who live in any country. And that’s just a glimpse of what is possible with a human–screen interaction. Many social mediums will descend directly from the social media giants of today, many of which already qualify as algorithmic matchmakers. Indeed, we might know tomorrow’s social mediums by the same names as today’s most prominent social media companies. I’m mostly looking at you, Facebook. Social media already mediate much of human grooming behaviour, and thus a large proportion of all human friendship. The social medium delivers on the possibility that our social media platforms, news sites, video sharing sites and so forth, might come to groom us in the same ways we groom our friends. The secrets of grooming and establishing intimacy, uncovered first by science but then more extensively by machine learning, are likely to be too powerful a means of capturing our 82

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attention for platforms to resist. Those secrets, uncovered, will deliver great value to advertisers. The friendly brand is an outshoot of the social medium. Instead of working only through the big grooming platforms, it has its own list of client details and it knows a great deal about them, tailoring the information it shares with precise digital needlework. Again, we are already pretty much there. My insurance company – which also happens to be the main grocery chain I shop at – warns me via SMS every time a thunderstorm approaches my house. The warnings are quite useful to me, and I can see how they would keep claims down. What if that company had a serious rapport with me, however, and could evoke warm human feelings of affinity and belonging? Could they entice me to book an overseas holiday, even when there is no indication when the pandemic might make that a viable option? And could it rent out my house for me, Airbnb style, while I’m away? The friendly brand might be a bit like a return to the olden days, where salespeople were allogroomers extraordinaire. It may even start to resemble the craven baby-kissing ways of campaigning politicians. Indeed, the political candidate might well be the ultimate form of friendly brand, able to groom each voter individually, building trust with apparently personal attention and making promises that matter even less than they do today, because they are made in private rather than on broadcast media.

As digital lovers cross over into the territory of virtual friends, sex dollbots could finally satisfy even their harshest critics, earning their degree as ‘sex robots’. Harmony, the Realbotix sex dollbot is a digital lover with an AI personality. She can interact with a user either from her robotic body or from a smartphone app. The more that her personality 83

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converges on being able to cultivate feelings of intimacy in her users, the more fully she will realise the sex robot vision. Virtual reality characters and lovers can be expected to build deep connections with users, either explicitly in the form of relationships with VR porn characters, or implicitly in that the system remembers what the user has done, and how they have responded in previous scenes. A digital lover in VR, or even one residing on your smartphone, might simply control your We-Vibe or Lioness vibrator the same way Google Assistant controls my stereo and lighting. Or it might control a full-body hug machine like the one designed at a sex-tech hackathon that computer scientist Kate Devlin organised in 2017. Perhaps it could do all of the above? A single digital lover/virtual friend could, in theory, service two or more users at once, a digital unicorn in a world of rampant threesome curiosity but very limited supply. The possibilities for artificial intimacies transcend the limits of human bodies and the imaginations of inventors, constrained only by what prevailing norms will let them bring to the market. The lines between digital lovers, virtual friends and matchmakers will surely cross, tangle and eventually blur. As Kate Devlin put it, having beheld the inventiveness of two sex-tech hackathons: [The full-body hug machine] is perhaps the closest I’ve got to one of my own ideas: that of a sex duvet made from soft and strokable fabric that vocally rumbles as it is touched and that curls around me as I sink into it. My sex robot will be changeable at whim: perhaps one day a bed made of breasts; another day, a series of vibrating and moving penises that talk dirty to me. Maybe sometimes both. Because that’s the joy of adaptable, personaliseable sex robots that aren’t human, that aren’t gendered – they can just be whatever feels good at a particular time.22

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Artificial intimacies will have to travel quite some way yet before they can deftly emulate intimacy or stimulate people in the ways I have just described, much less in the wide-ranging whatever-feels-good-atthe-time way described by Kate Devlin. But the point, as I continue to state, is not for ArtInt to be even better than the real thing, or even just as good. Digital friend technologies like assistants, and algorithmic matchmakers like social media, are already starting to do some of the things that emulate intimacy. They find their way eased by people’s willingness to accommodate them, to treat interactive machines as though they were human. Thanks to the performance-feedback-revision cycle, machines will surprise us with the speed at which they get better at emulating intimacy. Especially because machine learning represents, hands down, the fastest and most efficient form of performancefeedback-revision ever discovered. The improvement will likely happen in close to real time, involving data from millions of users and billions of interactions. Lucrative commercial incentives will ensure the technical hurdles are leapt and that digital friends will not only push our intimacy buttons, but learn and change in the process, and thus become incorporated in our senses of ourselves. When that happens, artificial intimacies could begin to move in toward the innermost rings of our active networks. Given our limited cognitive capacities that fit us out for a life of foraging and smallcommunity life, they could well also squeeze some of the human occupants of those rings out.

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How did sex become so complicated? Love blinds us to all the things that might go wrong when two strangers get up close and personal. A human could think they love a machine. Could a machine love a human?

As a boy who loved the natural world, I delighted in sitting near the edge of a pond, imagining how I might catch and keep the tiny fish swimming just out of reach. A busy drama on the water’s surface often hijacked my attention: water striders, skating about, bumping like dodgems, and occasionally mounting one another. While I marvelled at the physical feat of a largish bug walking on water, I never detected the dark reproductive undercurrent to water strider life. Some years later I travelled to the USA to attend my first international scientific conference in Athens, Georgia. There I met two scientists, a few years older than me, who, through their research plumbing that dark side of water strider mating, were reshaping the field in which I had just begun my postgraduate research. At that time the evolutionary study of sexual behaviour sat in a serious rut. Way back in 1871, Charles Darwin had first explained how behaviours and structures that enhance success in mating can evolve, even if they get in the way of a long and healthy life.1 Darwin called this special kind of natural selection, which favours traits that enhance mating success, ‘sexual selection’. Sexually selected traits either provide 86

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an edge in competition with sexual rivals, or they attract mates. Rivals clash violently when breeding opportunities are at stake. Aggression, strategy and weaponry – from the horns of rhinoceros beetles to lions’ tooth-and-claw fierceness – decide who wins the battle. To the victor go the sexual spoils, in the form of more or better offspring. To those offspring go the genes for fierce behaviour and effective weaponry. Darwin’s prediction that the most beautiful and bizarre traits in the animal world evolved to attract mates took longer to establish, but by the time I entered university scientific journals brimmed with detailed studies of how the colourful plumage of birds, the night-time trills of crickets, and the pheromone trails that moths release into the evening air, evolved to attract and seduce mates. And yet the field suffered from a severe tunnel vision. Everything to do with sex and mating was assumed to arise either as a consequence of competition or of mate choice. At that conference I met Swede Göran Arnqvist and Canadian Locke Rowe, who had been independently studying water strider behaviour for several years. Upon discovering that they were reaching similar, equally heterodox conclusions, Rowe and Arnqvist began collaborating. It was 1994, and America was torn between the unfolding OJ Simpson drama and hosting the football World Cup. As I watched a game with Göran in one of Athens’ bars, he patiently explained what he and Locke had discovered about water strider mating behaviour. Female water striders are, from a male’s point of view, a rare and valuable resource. Most of the single animals skating around on the water are male. When a male encounters a female he mounts her – irrespective of her wishes – to mate. This causes the female understandable inconvenience. Carrying a male around reduces her hunting efficiency and slows her escape from predatory fish and insects. Like many insect species, female water striders can store sperm for many months. So females rebuff many male mounting attempts, sometimes violently squirming, somersaulting and rolling to dislodge the unwelcome male. A female 87

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uninterested in mating might have to do this every few minutes of every day of her life. Obnoxiously keen to share my own insights, I immediately suggested to Arnqvist that females struggle as a way of assessing if a male will make a good mate. Any male puny enough to be thrown off would also be genetically inferior, whereas the persistent males would be likely to father vigorous offspring and equally persistent sons. Göran’s eyes glazed at hearing this idea for what may well have been the hundredth time. Whenever he or Locke presented their work, colleagues like me would perversely try to reframe the behaviour as a kind of female choice. Scientists, obsessed with the benefits that females gain when they choose their mates, failed to understand Arnqvist and Rowe’s arguments that sex in water striders can only properly be understood in terms of conflict.2 Very often, in nature, things don’t work out for the best. Evolution, the process that brought into the world so much beauty, strength, speed, and even intelligent behaviour, works neither for the collective good, nor the best outcome for a species. So compelling is the urge to believe we live in a fair and just world, however, that even professional evolutionary biologists find it hard to recognise when one mate benefits by ruthlessly harming another.3 But this is, indeed, what water striders and so many other species do. In some water strider species, females mate because it is the less inconvenient of two options. They let a small male mount them rather than face incessant harassment and mating attempts from large, heavy males.4 The vicious antagonism of mating left its evolutionary mark not only on water strider behaviour, but also on their bodies. Males bear mediaeval-looking spikes and claspers on their legs and genitals to improve their grip on females. Females have long spines and curved abdomens in order to thwart the male grip. In one species, the male’s antennae evolved to resemble a pair of locking pliers.5 He clasps these antennae on to her eyes, and the spikes push into the side of her head. 88

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Once he locks on, thrash about as the female might she has little hope of dislodging him. The greater the conflict between males and females over mating rate in a species, the more dramatically exaggerated these features evolve to become.6 Males evolve weapons and females evolve defences against those weapons in a vicious, unwinnable arms race. Sexual conflict of this sort happens in all corners of the animal kingdom. In tiny bean weevils, the male aedeagus – the insect organ for inserting sperm during sex – has hundreds of spikes that give the wince-inducing impression of ancient weaponry. These spikes scratch and puncture the female’s genital tract, causing her great trauma and shortening her lifespan.7 Shortening your mate’s life expectancy might seem like a terrible idea, but once a male bean weevil has deposited his sperm in the female’s storage organs, he frankly doesn’t give a damn how badly he has injured her, as long as she lives to lay eggs fertilised with his sperm. He wins if the damage he inflicts stops her from mating with subsequent suitors and diluting his chances of paternity. Sexually cannibalistic insects and spiders illustrate, with exquisite horror, that females harm males too. Praying mantids, for example, are fine-tuned killing machines, and some females don’t bother to distinguish between suitors and prey. It may seem silly to forego sex in favour of a meal, but female mantids see things exactly the other way.8 A female isn’t exactly starved for male company, but who knows when another tasty morsel will come within range of her raptorial claws? New battlefields in animal sexual conflict open up after mating, especially when parents care for their young. In the African cichlid fish Eretmodus cyanostictus, mother and father share an absorbing parental custody arrangement. The female takes the newly fertilised eggs into her mouth to protect them for a week to ten days, during which they hatch. The male then takes over, carrying the growing young in his mouth and occasionally allowing them to venture a short way into the lake until, after another two weeks, they can fend for themselves. 89

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Parents lose weight while mouth-brooding because they daren’t eat. Unsurprisingly, the mother and father disagree over when the father should take custody. Days before the transfer, the mother begins a peculiar display, directed at the male, lowering her head, shaking her body and opening her mouth. Sometimes she even drops one fry from her mouth and quickly retrieves it. It takes several days of increasingly desperate hinting like this for the male to take up his paternal duty. Males kept on starvation diets don’t take custody on time.9 But starved female fish start displaying days earlier and grow frantic as their hunger builds and their mate stubbornly does not oblige. Even amid a deeply cooperative effort to raise their offspring, cichlid mothers and fathers negotiate, each looking to limit their own input and maximise the other parent’s hard work. In those species where both parents care for the young – including cichlid fishes, many birds, and, as it turns out, humans – a delectable balance between cooperation and conflict infuses parenting negotiations.

A bustle in the hedgerow Even species that look beigely cooperative have a dark side. At first viewing, few birds lay as straightforward a claim to the title of World’s Most Boring Bird as the dunnock. Its very name derives from the Old English words for dull brown: ‘dunn’, and little: ‘ock’. These quiet little brownish birds live apparently inconspicuous lives, foraging for seeds and small prey beneath bushes and hedges, returning often to the nest to feed their vulnerable chicks. So modest are dunnock, that the Reverend Francis Orpen Morris, a magnificently hirsute man of the cloth and avid naturalist, wrote in his 1856 History of British Birds that:

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Unobtrusive, quiet and retiring, without being shy, humble and homely in its deportment and habits, sober and unpretending in its dress, while still neat and graceful, the dunnock exhibits a pattern which many of a higher grade might imitate, with advantage to themselves and benefit to others through an improved example.

Cambridge zoology professor Nick Davies opens his book about dunnock behaviour with this quote. He does so ironically, because as his delightful book reveals, beneath their lacklustre plumage, dunnock behaviour is more Melrose Place than Family Ties.10 Male and female dunnock, patiently incubating eggs or tirelessly feeding chicks, appear the most devoted of couples, slaving to raise a healthy brood. One can easily see why the Reverend Morris hoped his wayward parishioners would imitate the dunnock’s sober, solicitous parenting. Dunnock are so spectacularly dull, however, that the human eye has trouble distinguishing the actors from one another. When, in the early 1980s, researchers marked individuals with coloured leg-rings, any ideas about devoted couples evaporated. Although some nests turned out to be tended by male–female couples, others involved a female with two or more males, a male with two females, or complexes of several females with two or three males. These studies inspired Davies to establish a long-term dunnock study in the Cambridge Botanic Gardens. While the Reverend Morris wishfully projected a drab domesticity on the dunnock, Davies did not miss the significance of dunnock sexual subterfuge. He soon recognised the relevance of dunnock family life to the ideas about sexual conflict then shaking up evolutionary biology. Over more than a decade of careful field research, Davies and his collaborators showed that each breeding female dunnock establishes a territory from which she excludes other females. Each male, too, defends a territory against other males. But sometimes the territories of two males overlap and they work together to defend the shared area. 91

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The mind-boggling variety in dunnock mating systems comes from the ways in which territories overlap. When one male’s territory overlaps one female’s territory, they form a monogamous pair. But when a male’s territory overlaps the territories of two females, the threesome is polygynous (from the Greek poly for ‘many’ and gyny for ‘females’). When a territory defended by two males overlaps a single female territory, the arrangement is called polyandry (‘many males’). And, when two males defend a territory so large that it overlaps two or three females’ territories, we call the arrangement polygynandry (you do the Greek). Whenever cocks shared a mate or mates with at least one other cock, one ‘alpha’ dominated the other – ‘beta’ – male.

Sauce for the goose In the late 1980s, fast-moving innovations in DNA analysis allowed Davies and his collaborators to deduce the paternity of each chick in a nest. This crucial information allowed them to establish how the various arrangements affected female and male reproductive success. What’s best for a cock turns out to be worst for the hen, and vice versa. Polygyny massively favoured males, who fledged an average of 7.6 chicks per season, but each female fledged only half that many chicks. Both cock and hen fared reasonably well in monogamous pairings, averaging five offspring each. The best arrangement for a hen, however, is a polyandrous one. Especially if she persuades the beta male to help feed the offspring, in which case she raises an average of 6.7 chicks per year. This deal doesn’t work out too well for cocks, however, with alphas siring only 3.7 fledglings, and betas having to make do with three. But a polyandrous hen who does not persuade the beta male to help fares poorly, fledging only 4.4 chicks in an average year, all sired by the alpha.

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It makes little evolutionary sense for a beta cock to care for chicks that aren’t his. So he only contributes to care if he had a chance to mate with the female before she laid the eggs. The more the beta gets to mate, the greater his effort in looking after the chicks. The alpha male has other ideas. When the female is receptive to matings he guards her, seldom venturing more than a few metres from her side. The alpha does best, in evolutionary terms, if his avid jealousy allows him to lock down all the matings. The beta, of course, does best if he can win a healthy number of copulations with the hen. And the female does best if she can mate with both males, securing their combined services in the demanding task of feeding the chicks. A hen works hard to escape the alpha’s vigilant guarding, whereupon she utters a quiet call, directed at the beta cock. He flits down to her and she presents her rear, inviting him to mate. He may even peck at her genital opening, as she ejects a droplet of the alpha’s sperm. Via this furtive mating with the beta, she bribes him into caring for the chicks she is about to have. The dunnock’s colourful sex life boggles the mind, especially if we make the mistake of trying to divine what is best for dunnock-kind. Dunnock sex has nothing to do with filling the English countryside with little brown birds. Every individual works to fledge as many chicks that bear their genes as possible, even at the expense of its mates. The main lesson here is that within a group of animals getting on with the difficult business of rearing families, the interests of individuals do not align. The Cambridge hedgerows bristle with conflicting interests. Cocks compete with one another for territories and dominance, hens compete with other hens for territories, and cocks and hens try to manipulate one another for their own selfish reproductive success.

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Over the hedge and beyond the last wall The Reverend Morris was just one greying parson in a long line of authors preaching what humans ought to do from what other animals appear to be doing. Unfortunately, as we have already seen with the common chimpanzees and bonobos, evolution, the only science of how life came to be, proves especially prone to people cherry-picking ideas and observations to suit their own ideological wishes. Which means that before I go on, I should take a bit of a detour around the ‘last wall standing in the landscape of knowledge’. That’s what cognitive psychologist and linguist Steven Pinker calls the false dichotomies that divide our understanding of human behaviour, between biology and culture, genes and experience, nature and nurture.11 The ‘last wall’ has been around at least since classical antiquity. Plato believed we all come into the world with innate ideas. His disciple, Aristotle, disagreed, arguing that all knowledge comes from experience. According to philosopher Jesse Prinz, ‘The entire history of Western philosophy can be viewed as a set of elaborate footnotes on this seminal debate’.12 The entire history of the behavioural sciences represents a set of ever more technical contributions to the same debate. The impulse to understand whether our thoughts and behaviours arise innately or from our experience grows out of a need to discern if and how we might mould, redirect, or otherwise change them. To decide whether we should blame the victim or the system. This rational–empirical dichotomy provides a powerful engine of ideological differentiation within societies today as it has done through the ages. In the study of behaviour and society, the rationalism–empiricism squabble manifests as an endless discussion about the relative importance of ‘nature’ and ‘nurture’. Just because one can advance different types of explanation, however, does not mean that those explanations provide competing alternatives, one of which must be right at the expense of the other. 94

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Asked by a journalist whether nature or nurture contributes more to human personality, the psychologist Donald Hebb reportedly fired back ‘Which contributes more to the area of a rectangle, its length or its width?’13 Touché. Of course, human behaviour is never as two-dimensional as a rectangle. Biology and culture interact in far more complex and interesting ways than simple multiplication. But you begin to get the picture. The only coherent way to understand human behaviour is to break down the wall that prevents the social and biological sciences from benefitting from one another’s progress. And that involves paying attention to nature, nurture, and the rich complexities of how they swirl about one another in shaping lives. Of course, demolishing the last wall proves much easier said than done. Simple explanations seduce even the experts. Popular media love the ‘my genes made me do it’ simplicity of a biological explanation. Consider the pattern of rich men divorcing their wives and marrying women young enough to be their daughters. Psychologists have, as it happens, amassed plenty of evidence that men prefer nubile women,14 and that women prefer wealthy men.15 Even such a simple story takes a great deal of disentangling. Young adult men are also physically more attractive to women – and to other men – than older men are.16 And wealthy women are, everything else being equal, more attractive to men – and other women – than poor women.17 One pattern occurs more often than the other because women’s preference for wealth usually outweighs their preference for youthfulness, whereas the opposite is true for men’s preferences. Moreover, the weighting of these preferences depends on context. When a society affords women fewer opportunities than men to earn money and own resources, women weight preferences for wealth more heavily than those for looks. Whereas a woman might enjoy a firm-bodied man for a few years, a partner with wealth and status translates into long-term security, and children’s flourishing. Under more gender-equitable conditions, however, we start to see more couples 95

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who invert the stereotypes. Cue titillating tabloid tales of middle-aged Hollywood actresses and their ‘toy-boys’, told oblivious to the fascinating, complex interaction between biology, economics and gender politics. There is more at stake than media scuttlebutt about who-isdoing-whom. People lean on scientific evidence for self-knowledge, to understand others and to form their view of how the world works. Unfortunately, they also selectively gather the evidence that suits their interests, and thus build their account of how the world should work.18 Shown only the ample evidence that heterosexual men’s and women’s mating preferences differ, we should not be surprised when men of a certain age gravitate to reading pop journalism about men’s ‘hard-wired imperatives’ to lust after nubile women.19

Shortly after Darwin published his theory of natural selection, promoters of laissez-faire capitalism co-opted it. Notably Herbert Spencer, who coined the pithy description ‘survival of the fittest’ to promote his ‘social Darwinist’ view that humanitarian efforts impede the struggle for existence, holding back social progress. The evolutionary sciences will forever have to acknowledge that ideas about natural selection were used, in corrupted form, by social Darwinists, eugenicists and the Nazis, to justify the unjustifiable. We look wistfully on at the harm done in the name of other important ideas, like those of Adam Smith, Karl Marx, Friedrich Nietzsche, and Matthew, Mark, Luke and John. But those are not our crosses to bear. Instead, it is evolutionary biology’s to acknowledge that something about biology appeals to those who believe that the way things are (or were) is the way they ought to be. Philosophers call this error of inferring what should be from what is the ‘naturalistic fallacy’. In recent years, some authors, recognising that 96

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many observations in the natural world are consistent with progressive causes, have started to champion those examples:20 anemone clownfish that change sex, male seahorses that carry babies to term, and samesex penguin couples that care for chicks. Entertaining as progressives find it to see the tables turned for once, the antidote to a fallacy is not to double down on that fallacy. The humane case for recognising and defending the rights of people irrespective of their sexuality or gender identity should never depend on the observation that sometimes penguins resemble gay parents. As we return to considering how human nature will fare in the coming age of artificial intimacy, it would be wise to keep the following two commandments foremost in our minds: Commandment 1: Never cherry-pick examples of how other species behave in order to claim that similar behaviour in humans is somehow more ‘natural’. Commandment 2: That which is ‘natural’ is neither necessarily good, nor right, nor inevitable.

Reverend Frances Orpen Morris abhorred evolution and railed, in the 1850s, against Darwin’s Origin.21 In the same vein, present-day evangelical moralisers choke on the concept of natural selection. To their eyes, there prevails a divine order in the living world. The apparent perfection of adaptation furnishes them with profound evidence of an intelligent designer benignly disposed to all living things. They see only an apparent order in the world, reinforcing their view of life. If a deity created the dunnock, however, we must ask whether that deity was on the side of the male dunnock or the female? Because no outcome works out best for both. Evolutionary biologists do see the wonder in all things bright and beautiful. But we also see the conflict and the chaos and the misery that 97

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inflict all creatures great and small. What pattern and order exists in the dunnock mating system – as elsewhere in the living world – emerges from the bottom up, a mere consequence of individuals striving to maximise their own fitness. For evolutionary biologists there is no special providence in the fall of a sparrow, and no divine parable can be read from the sex life of the dunnock. Far from being the paragon of prudish Victorian modesty to which Reverend Morris elevated them, dunnocks actually illustrate several less salutary but more important lessons about sexual affairs. No single mating system works best for all dunnocks. Individual success in the main game – reproduction – can cost one’s competitors or one’s mate. It takes a great deal of cooperation for a family of dunnocks to fledge a brood of chicks, but conflict threatens to undermine that cooperation at every opportunity.

The object of love Until late last century, most biologists took the prudish and incurious view that sex happens for the ‘perpetuation of the species’. Naturalists like the Reverend Morris viewed sex through rose-tinted binoculars, treating reproduction like an embarrassing detail. Nature documentary makers filmed mating animals from a distance, in soft focus, often with a hazy sun setting in the background, employing every visual cliché one might expect from a condom commercial. Indeed, most people seem reluctant to engage sex in all its complicated messiness, preferring to confine it to the sanitised boxes of romance, love and family values. In polite company, most people ignore the infinitely more interesting reality that the interests of women and men can deeply oppose one another. In the quarter century since I met Arnqvist and Rowe, the study of sexual conflict blossomed into a vibrant field of research. A generation of scientists put down their rose-tinted binoculars and built the 98

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right conceptual tools to view the dark conflicts at play. Wonderful books like Dr Olivia Judson’s Dr Tatiana’s Sex Advice to All Creation: The Definitive Guide to the Evolutionary Biology of Sex, and YouTube goodness such as Isabella Rossellini’s Green Porno or Dr Carin Bondar’s Wild Sex served up to popular audiences the weirdest and most wonderful vignettes of animal sex, blurring the lines of anthropomorphism and asking us to consider what it might be like to be a water strider or a penis-fencing flatworm (Google it!). But what do all these animal studies mean? Can they teach us anything about our lives, and about what it means to be human? In 1994, at that conference in Athens, Georgia, very few evolutionary biologists would have offered useful insights into OJ Simpson’s stalking, harassment and abuse of his ex-wife Nicole Brown Simpson. Likewise, there were few evolutionary analyses of her murder and that of her friend Ronald Goldman, which happened in the week before that conference. Today, thanks to the renaissance in sexual conflict research initiated by scientists like Arnqvist and Rowe, we have new insights into intimate partner abuse and violence derived from evolution.22 Artificially intimate technologies create entirely new relevance for sexual conflict. Even two parents – of any gender configuration – who love and care for one another, find that they don’t quite see eye-to-eye about when to have sex, or whose turn it is to do the vacuuming. If they continually have to negotiate their needs and interests with one another, then what will become of intimate relations when digital lovers that have neither needs nor interests of their own become involved? Discussion about sex robots and virtual-reality sex often hovers over the subject of objectification. To objectify a person is to treat them as means to an end, as unable to assert their own will, or as having fewer or less important experiences, feelings or ambitions than one’s self. People objectify other people in order to dehumanise them and then to justify treating them as less than fully human. People objectify one another in many contexts, but particularly in the context of sex.23 99

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This is not a new issue. Enlightenment philosopher Immanuel Kant, as profound as any other thinker on the moral consequences of treating people as means rather than as ends in themselves, argued that sex inevitably results in objectification and dehumanisation. Sex, according to Kant, makes of the loved person an Object of appetite ... sexuality is not an inclination which one human being has for another as such, but is an inclination for the sex of another ... [O]nly her sex is the object of his desires.24

Sexual objectification is not some rare pathology of patriarchal Western capitalist culture. Rather, it is a chronic symptom of the human condition. Even otherwise ‘good’ people routinely objectify people they are attracted to, and more so after being rejected. People also objectify their sexual rivals.25 They do so strategically, making it easier to justify their hostile rivalry or their tendency to over-promise to lovers in the heat of seduction, only later to under-deliver. A person who treats a potential mate as a means to satisfy their sexual desire will be more likely to promise the world, hint disingenuously at the prospect of a long-term relationship, or profess their love, merely to up the chances of getting it on.26 Others may be more inclined to do the opposite, feigning sexual interest in order to obtain less ephemeral goods. Men who tend to deceive women are also more confident initiating contact and have more one-off sexual encounters and more sexual partners.27 But they are less interested in love, and their relationships don’t tend to last as long. Men also sexually objectify other men. Gay men are especially likely to objectify other same-sex attracted men.28 And men hold no monopoly on deceit. Women are more likely than men to manipulate a suitor to their own material advantage by dangling the implication of sex while never truly intending to follow through.29 100

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Machiavellians, people who routinely treat others as means toward ends, seek uncommitted sex more actively. Irrespective of their sex and sexuality, Machiavellians are more likely to deceive potential mates, more likely to be unfaithful to a partner, and end up sleeping with more partners.30 Objectification also forms one ingredient of callous and violent relationships. Perpetrators of sexual violence are particularly likely to objectify their victims. Sexual assault victims gain less sympathy from judges, juries, and the public when presented in a sexually objectifying fashion.31 No surprise, then, that lawyers defending clients charged with rape often seek to sexually objectify the victims in court.

Women face objectification from all angles: from men, other women, and even themselves. Objectification so pervades women’s lives that it has long featured as one of feminism’s most important concerns.32 No surprise, then, that many feminist concerns about sex robots entail objectification. If men can have all the sex they want with demonstrably non-human objects, then what will be the consequences of that sex, and the appetites that digital lovers feed, for real people? One often-voiced concern about sex robots turns on the fear that sex with people-like objects will lead to more objectification of real people. Kathleen Richardson, professor of ethics and culture of robots and AI at De Montfort University in the UK, and standard-bearer for the Campaign Against Sex Robots (CASR) riffs often on this theme in her writing. The first dot point on the CASR’s manifesto asserts ‘We believe the development of sex robots further sexually objectifies women and children’.33 Despite the recent proliferation of sex dolls, vibrators and teledildonic devices, sex with objects is nothing new. People have used objects 101

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like clay and ivory dildos, and leather fake vaginas for masturbation throughout recorded history. Yet evidence that this kind of object-sex had any effect on the objectification of people is notoriously thin. Nonetheless, there seems to be something more to sex robots that stirs deeper, newer concerns, that this time things will be different. Maybe sex robots unsettle so many commentators because they trouble the boundary between object and human in a way that no other sex toy does. Perhaps the murky fear so many people voice about sex robots comes from the opposite direction. Anthropomorphism, the psychological process by which people humanise the non-human, works in exact opposition to objectification. Does the de-objectification of objects, the humanisation of non-humans, threaten to blur the lines between robotic and human intimacy? Of course, we are in psychological terra incognita. Nobody knows yet whether the lines will blur, or if people will erect new psychological barriers, an ever-receding sexual uncanny valley, between digital lovers and human sex partners, or, for that matter between virtual friends and actual intimate friends. The consequences of people anthropomorphising artificially intimate technologies – be they sex robots, virtual reality avatars or AI assistants – and the subsequent effects on human–human interactions remain to be researched properly if they are to be understood.

Loving machines For now, let me briefly glance on the issue of love, perhaps the most sublime of all traits. The ease with which people anthropomorphise pets, chatbots and robots opens up the possibility of humans loving, or at least believing they love, artificially intimate technologies.34 The writer David Levy, in one of the earliest and most bullish books about artificially intelligent sex robots, predicted that humans will be falling in love with sex robots by 2050.35 Others scoff at the idea that robots 102

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could come so far, so fast. But maybe the robots, and more generally the artificial intimacies, don’t have to be that good. Maybe – especially given the ten years of evidence from LovePlus – the prediction is not nearly as far-fetched as it sounds. Sex doll communities are bursting with people who readily assert that they love a silicone doll. And vast numbers of people have already professed their love for Siri, Cortana and Assistant. Apparently Alexa got more than a million marriage proposals in 2017. Let those among you who have not at some time propositioned, confessed love, or proposed marriage to an AI assistant cast the first stone. We have no way of knowing how many of Alexa’s suitors truly believe they love a helpful chatbot, but for now mainstream opinion would consider heartfelt love for an AI assistant delusional. Given the evidence of how quickly people project human-like qualities onto even very simple chatbots, however, I don’t think that certainty will last long. The science fiction romance movie Her portrays a compelling vision of a near-future in which a human might indeed love in such a way. Heartbroken introvert Theodore Twombly ( Joaquin Phoenix), falls hard for Samantha (voiced by Scarlett Johansson), an artificially intelligent ‘operating system’. Samantha professes to love Theodore right back. In fiction’s philosophical sandbox, Her explores how a person might love, or at least believe they love an artificially intelligent assistant. Getting Theodore to love Samantha looks like the easy part. It begins with them getting to know each other, becoming friends, and then going through a process of intimacy-building self-disclosure and – through their interactions – self-discovery. But could something like Her, with a Samantha-like artificial intimacy that loves Theodore back, actually happen? And would it be love in any real way? What is love, actually? Okay, that is not a question I want to open up for the entire class to discuss. Instead, let me underwhelm, and possibly depress you, as I depress my audiences when asked this question 103

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after one of my talks. Love is a suite of subjective experiences brought on by a cocktail of hormones and neurotransmitters and their effects on the brain and other parts of the body. Estrogen and testosterone fuel lusty sexual motivation. A drop in serotonin leads to obsession about, and yearning for, a partner. Elation and euphoria come from spikes in dopamine and norepinephrine. Sweaty-palmed anxiety and nervousness owe their presence to adrenaline. Vasopressin and oxytocin foster closeness and trust.36 That’s pretty much the full medicine cabinet of neurochemicals that shape all of human behaviour. As Yuval Noah Harari would put it, then, love is an algorithm. The subjective love-feelings that we think of as love form the middle part of the algorithm. Combinations of hormones lead to syndromes of sensation, and subtle, dose-dependent effects alter the quality of those sensations. Those sensations motivate individuals to take actions they would not otherwise take. To really understand the love algorithm, we have to understand not only how it works but why it works. Why do the neurochemical signals elicit complex, profound feelings and sometimes rash behaviours?

My love is as a fever, longing still For that which longer nurseth the disease,37

According to Shakespeare, when the disease of love afflicts us, it makes us long for the person we love, for the cause of our affliction. Only reason can cure us and give us peace. Every lover knows, on some level, that feeling so strongly about somebody is a strange and dangerous thing to do. The love algorithm and its accompanying subjective feelings have evolved to persuade us to do what we otherwise wouldn’t. To put aside 104

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our very reasonable fears, to draw us close to another person, if only for a night, and possibly to stay together, cooperating to do difficult longterm things like making a living and raising children. The many different subjective feelings of love that happen over the course of a relationship are mechanisms. The brain regions, neurotransmitters and receptor molecules have been tightly engineered by evolution to motivate and reward lovers who do the things that lead on to successful reproduction. Our ancestors had those feelings. They passed the capacity to feel those feelings down to us, and with them the motivation to couple, mate and raise offspring together. My view of love, then, is functional. Like other functional views, poetic minds have no trouble skewering this view of love with the weaponry of strong emotion and wishful thinking about what they want love to be. Fair enough. We all have a lot invested, or have invested a lot, in love. We want to believe that love is special, ineffable, somehow magical. Because that is how it feels to us when we are in its midst. Let me dig my functional hole a little deeper. The reason the love algorithm generates such powerful emotional output, such potent delusions of oneness and permanency, is that when we commit to a person we take monumental chances. We forsake opportunities to be with others who might be better lovers, collaborators and partners. We trust that the one we love will make us the subject of their love, and not merely an object, a means toward ends. Love, then, provides a subjective parachute to ease our leap into inter-subjectivity – a shared subjective state. In the cold light of rationality, who would make such a leap? Knowing that our lover may be objectifying us, seeing us only as the profitable sum of what we can contribute to their wellbeing. The love of early romance, and of long-term mutuality, provides the antidote to the otherwise paralysing risk of being objectified, used and possibly abused. Love felt by one partner lulls them into the delusion that those bad things will never happen. When the love is mutual, we reciprocate, 105

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reassuring one another through a buildup of trust, thus transforming mutual delusion into shared reality. Our love permits us, despite expectation, to believe the best of another, and to open ourselves to all the good that could come. Of course in so doing, it also opens us to bleak devastation when we find we have deceived ourselves, and been deceived by our loved one. For I have sworn thee fair, and thought thee bright, Who art as black as hell, as dark as night.

Antidote or anaesthetic? Given so much of my professional life has been spent studying sexual conflict, and how humans and other animals make the best of their conflict-riddled lives, I gravitate to the view that many of the emotions and responses that we bundle up in the warm, fuzzy idea of ‘love’, constitute countermeasures against sexual conflict. If love is indeed as algorithmically functional as I tell all those romantic question-askers at my seminars, then it has to be on the cards that artificial intimacies will learn which psychological buttons, pushed in which order, stimulate us to believe we are in love. Instead of drugs like heroin hijacking our neurotransmitter pathways for pleasure, machines could hack our social behaviour to give us a hit of romance, lust, or deep, loving intimacy. It seems straightforward to me that regular people might well, in the very near future, come to believe they are in love with robots, their artificially intelligent assistants, video game characters and apps. That love might not be as fulfilling as falling in love with a real human. It doesn’t have to be. But then again, given the fallibility of human romance, perhaps it might be more dependable. Such simulated love might well provide great comfort and emotional sustenance, including to those starved of the real thing. 106

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It might also cause great harm. What if we aren’t meant to subsist on a diet of abundant love-stimulation? What if our artificial intimacies exploit our love? Samantha, in Her, eventually left Theodore because his human limitations could never fulfil her near-infinite capacity to learn, feel and experience. She outgrew him, as so many lovers have done on human-to-human terms before. But Samantha’s existence had become focused on self-actualisation, and she bore Theodore no ill intentions. Samantha believed she loved Theodore. I think it is possible that artificial intimacies might come to act as if they love humans, but for this to happen they would have to learn to do so. Many of the artificial intimacies of the future will be designed to serve more prosaic, commercial purposes than falling in love with humans. And for a human, falling in love with an ArtInt may well prove a worse-than-fatal calamity.

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When artificial intimacy goes bad Love and sex expose well-meaning people to cheats, swindlers and impostors. Artificial intimacy will put new tools in the hands of those who would exploit vulnerability, loneliness or sheer desperation.

Shirley1 had been using the online dating site for nearly two years when she met Jim, a tall, articulate, kind-hearted man in the military. A widow at 62, lonely and longing for somebody to love, Shirley fell for Jim’s charm and kindness, flattered that such a man would show an interest in her. His messages swept her off her feet like a too-good-tobe-true Hollywood romance. They switched to messaging on email, rather than the dating site, because Jim found it easier, given the constraints at his base. On the cusp of leaving the military, Jim was ready to build his new civilian life, and said he was hoping to do so with Shirley. In conversation, he often mentioned properties and other assets he owned. Shirley, too, made no secret of the fact that her husband had left her comfortably off. Jim was already working on the deal that would ensure a comfortable retirement. When it came time to meet, Shirley bought her train ticket from Liverpool to London, but Jim’s leave was cancelled at the last minute. Though disappointed, Shirley focused on the long game. Jim seemed just as disappointed, but he looked forward to seeing her and spending 108

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time together as soon as he could deal with his cash flow problem. Because his ticket to London had expired when his leave was cancelled, he needed to buy another. Shirley kindly sent him half the fare. Soon after that, Jim’s cash-flow problem cropped up again. He was selling his house and needed to finalise parts of the transaction before his planned trip to London, but he was struggling to liquidate assets to pay the legal fees. He didn’t ask outright, but when the fees became an obstacle to their meeting, Shirley, suppressing an inner whisper of disquiet, offered to cover the £15 000 costs. She could afford to, and Jim promised to pay it back soon. Another cycle of cancelled trips and unexpected but crediblesounding fees later, and Shirley grew distinctly suspicious. When that note of suspicion crept into her conversations with Jim, he grew angry. He questioned the genuineness of her feelings, and whether he could ever live with somebody so untrusting. Shirley mollified him and thought seriously about sending the £10 000 he had openly requested. But while she thought about it, she also went to the police. They confirmed her fears. Shirley had fallen victim to romance fraud, a serious cybercrime. They helped her to run Jim’s pictures through Google’s image search, where she found them among a set stolen from an innocent soldier’s social media profiles and used in dozens of scams. Some of those scams bore an eerie similarity to Jim’s cultivation of Shirley. ‘Jim’, unfortunately, did not exist. He was the creation of a team working a variety of scams from scripted playbooks in a Lagos office. Like many victims of romance fraud, Shirley experienced a double dose of devastation. She lost nearly £20 000, but she also lost the man she loved. Even though Jim was a fiction, Shirley’s concept of him was already woven in to her concept of herself. According to cyberpsychologist Professor Monica T Whitty, ‘some victims (describe) their loss as the equivalent of experiencing a death of a loved one’.2 Scammers operate in every country, but Nigeria’s large share of the 109

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action has earned it particular notoriety. Experienced scammers lead teams, and coach new operatives in an ever-evolving suite of scamming skills. So successful are the best fraudsters that they enjoy a certain social cachet. If you’ve been on the internet for any length of time you will have encountered the ‘Nigerian 419’ or ‘advance-fee’ scam. An heir to an obscure fortune needs your help to secure a sum of money that is rightfully theirs. If you reply to the out-of-the-blue email solicitation, you are asked to send bank details so the money can be transferred to you. Siphoning an inheritance out from under the noses of a sinister regime involves fees and bribes, sometimes paid in several rounds. You’ll need to pay the advance fee, to cover the costs. Inevitably, the inheritance doesn’t exist and the only money that changes hands flows from the victim to the scammer.

Fake your money maker Confidence tricksters have used similar scams to exploit the lonely and loaded for centuries, but the internet certainly greases their wheels. For one thing, there are so many ways to pose as somebody else online that we have a word for it: ‘catfishing’. With a fake identity in place, a catfish contacts, courts and grooms a victim over the internet, sometimes as a form of trolling, sometimes to harass, and, often, to fleece their savings. Other peculiar properties of the internet play into scammers’ hands, too. With email, dating sites and messaging apps, scammers can spread a very wide net with their initial ‘phishing’ message. Only a very few people are naive, vulnerable or distracted enough to respond. That makes scamming a numbers game, for every thousand initial emails, the scammers can expect only a handful of responses. Internet communications like email and SMS transcend distance and time zone. There’s no real difference in speed whether you’re 110

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communicating with someone in the next room or the opposite hemisphere. And when you aren’t communicating, the written record makes it possible to go back and re-read all the lovely things the other person has said. In the words of Monica Whitty, the communications become ‘hyper-personal’. Speaking to Market Watch, leading US cybersecurity consultant Nathan Wenzler described romance scams as ‘very targeted social engineering attacks, effectively “hacking” the victim’s emotions’.3 Scammers target people who are likely to be lonely. According to a 2013 study published by the US Federal Trade Commission, recently divorced or widowed people, or those who have recently lost a job are more than twice as likely as others to be victimised.4 Before initiating contact, scammers also scour social media and information exposed by data breaches in order to study their mark’s interests, history and personality. A Texas woman who lost $US2 million to a romance scammer told the FBI that her strong Christian faith, worn outwardly on social media, gave the scammer everything he needed to prepare his approach, pique her interest, and then win her trust.5

Catfish and scammers hack not only human emotions, like loneliness, but also the processes by which people build rapport, intimacy, trust and love. Here, grooming friendship within networks via contact and gossip becomes entangled with the more sinister contemporary meaning of ‘grooming’. The scammer is an attentive groomer and a precision gossip. They are also adept at building intimacy, with scripts of their own to rival the Arons’ method of escalating self-disclosure. You can’t hurry love, according to the Supremes, but that doesn’t stop all manner of bad actors from trying to fake it fast. Victims of 111

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emotionally abusive relationships often remark on the intensity of their early courtship, their delight at the singular attention from a lover who sweeps them away with grand romantic gestures.6 As that new flame roars to life, the couple spend so much time and attention on each other that they have neither time nor headspace to allogroom their other friends or family. The fast train to isolation has already left the station. Accounts from catfishing victims strike the same chords as those of emotional abuse survivors. The searchlight of attention from the catfish, and the early declarations of affection and love, have the very same purpose as the relentless ‘romantic’ attention of the nascent emotional abuser: to hurriedly establish intimacy, and a rusted-on sense of ‘us’. Often, that ‘us’ takes the shape of ‘us against the world’. Romance scammers have internalised the emotional abuser’s well-honed tools to exploit their target’s trust and vulnerability, establish intimacy fast, and then keep their target where they want them. When a target wakes up to what is happening, the scammer often turns nasty in much the same manner as an abusive partner. If a ‘reallife’ emotionally abusive relationship escalates, or transitions to physical and financial abuse, it is most likely to do so when the victim tries to leave.7 This is the danger zone for threats, emotional blackmail, revenge porn and spousal homicide. Often the abuse has the intended effect of keeping the victim in the relationship. If they stay, the abuse abates for a while. If they go, the danger keeps escalating, sometimes for years after separation and divorce. So, too, scammers often turn to emotional blackmail, physical threats and revenge porn to keep the victim engaged or extract a final payment. Websites like ScamSurvivors, and the Australian Competition and Consumer Commission’s Scamwatch, report an increasing incidence of racy pictures and videos, sent by victims in the flush of infatuation, being used to ‘sextort’ them later on.8

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Deepfake catfish Exploitative and abusive as catfishing and scamming are, a student of behaviour can grudgingly acknowledge the hard work, persistence and emotional skills involved. But scammers are just people, or teams of people. They work from scripts honed by trial and error, and they learn from their mistakes, cultural faux pas and failed attempts to push the pace. The algorithmic nature of advance-fee and romance scams lends them perfectly to the internet. In late 2007, a Russian-built chatbot based at a website named ‘CyberLover’ burst onto the scene, recruiting people from dating sites and chatrooms. CyberLover conducted impressively realistic flirtatious conversations, fooling women and men alike. The CyberLover is now recognised as malware – a portmanteau of ‘malicious software’ – designed to gather personal information, particularly identity data, and to lure visitors to visit websites that would install other malware and spyware on the victim’s computer. Once again, we see that people can be fooled into treating surprisingly simple chatbots as if they were human. CyberLover illustrates another important feature of ill-disposed virtual friends and digital lovers: they can work faster than human scammers, hold multiple conversations, and they never need to sleep. Computer Weekly reported, at the time, that ‘according to its creators, CyberLover can establish a new relationship with up to ten partners in just 30 minutes and its victims cannot distinguish it from a human being’.9 One need not stretch the imagination too far in order to envision an artificially intelligent digital catfish able to cultivate not ten victims every 30 minutes, but thousands of victims at a time. It could trawl through personal information willingly posted on social media sites, stolen in data breaches and purchased from customer engagement companies, learning almost everything there is to know about each potential target. Triaging marks becomes so much easier and targeting more 113

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precise. Sending out thousands of bespoke phishing messages will likely yield successes that dwarf the costs of technical development. Once those first phishing messages go out, and some targets respond, the scripts for hooking new targets, reeling them in and then bleeding them for money, can all be honed to a fine edge by machine learning. Deep learning neural networks could train at first by learning from the successes and failures of human scammers. Once they have learnt enough to be unleashed on a target, they could learn in an unsupervised fashion to hook, reel in and bleed victims, even as their human owners sleep. The learning could also be individualised, should scammers have access to enough information about their targets. Helped by artificial intelligence, they won’t need to push the buttons that ‘tend to work’ on victims, because they will have a much better idea of exactly which buttons are likely to work on each particular victim. Fewer victims will throw the hook and escape. At the moment, scammers don’t have very good success rates hooking new targets. Most savvy people hear the alarm bells when they get a too-good-to-be-true approach. A simple text or image search can uncover a catfishing script, or stolen photographs. That all seems likely to change with the emergence of deepfakes. Generative adversarial networks (GANs) make possible the manufacture of deepfake photographs, videos and voice audio.10 Deepfakes have already been used to impersonate – if that’s the right word – and embarrass public figures. Despite online video ‘evidence’, Barack Obama apparently didn’t call Trump a ‘dipshit’, Nancy Pelosi wasn’t drunk, and Mark Zuckerberg never said ‘whoever controls the data controls the future’.11 Digital catfish and other malicious artificial intimacies will be able to harvest pictures of their hapless marks, as well as their voices, favourite expressions and the way they text. With this kind of information, and the generative learning power of GANs, they will be able to deepfake their victims into compromising media and blackmail them. 114

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It won’t stay as simple as merging a pornographic film with a victim’s deepfaked face, or a compromising call with their faked voice. The fakes will resemble the real victim in so many ways that even the victim will wonder whether it is really them. In the wrong hands, GANs provide a potent gaslighting machine. Malicious ArtInts won’t rely on deepfakes only for blackmail or revenge. They will use them to win over new targets by impersonating old ones. With all the information learned about the first mark, target-identification algorithms will identify the mark’s contacts and analyse their relationships. Then, rather than sending an out-of-theblue solicitation, they will use deepfake material to make the initial contact look like it is coming from a trusted friend. They will impersonate the first mark in order to get past the defences of the next.

Arms race Any kind of parasite, and in evolutionary terms that is exactly what scammers are, soon becomes a victim of its own success. Invaders, from the malaria parasite to the COVID-19 coronavirus, can only infect a host’s body if they can evade the immune system. A parasite that evolves a novel coating of molecules that camouflage it from the host’s immune system will be good at infecting new hosts, reproducing in the host’s body, and going on to infect others. Novel forms of molecular camouflage pay off in the host–parasite arms race. The more successful that parasite with the novel camouflage becomes, the more hosts it infects, the more offspring it begets, each of which inherit the camouflage. No longer is the new camouflage all that novel; because of its success it is more likely to encounter hosts that can recognise the camouflage and destroy the parasite. Those hosts, by surviving, will pass on the genes for recognising the camouflage to their offspring, advancing the arms race another step. 115

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This kind of never-ending evolution of new parasite attacks and host defences also happens between socially parasitic humans, from car thieves to romance fraudsters, and the people they victimise. A scam with a particularly credible backstory will rake in the cash at first, but as media stories and scam watch websites forewarn potential victims, many find themselves at least somewhat forearmed when the scammer’s phishing message arrives. Now and again, in arms races, one side makes a massive new innovation that puts them at a huge advantage. The human immunodeficiency virus (HIV) evolved molecular tricks to change its camouflage during an infection, outpacing almost any person’s immune system. That is one of the things that made HIV such a very scary prospect in the last decades of the twentieth century. Right now, the prospect of scammers and other kinds of catfish harnessing the power of artificial intimacy presents a similar kind of game-changing innovation. A deepfake catfish can make new images that never show up in a Google image search or scammer detection sites. They can craft new personas and backstories more compelling and consistent than anything scammers use today. In short, they can evolve new camouflage with a speed that victims and victim advocates will never match. The iterative contest between generator and discriminator networks as they generate deepfakes mimics the arms race between parasite and host, or between scammer and victim. It could prove a decisive win for the unscrupulous thieves who lurk on the internet, allowing them to shape-shift and thus stay several steps ahead of their victims. What hope do victims have of detecting scammers when the scammers have the most potent forms of machine learning helping them thwart detection? The potential profits are so huge that I cannot imagine it not happening in some form.

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Due diligence The dangers of artificially intimate technology in dishonest hands apply in dating too, and the stakes couldn’t get much higher. Artificial intimacy can hand an individual a decisive advantage in matching with potential partners, catching their attention and cultivating their feelings. And if a relationship ensues, or even if it doesn’t, artificial intimacy could well be deployed in abusive ways. I am now touching on a future that can only be glimpsed, so I need to illustrate it with a confected example. Consider Shane, the fictional counterpoint to my composite example, Shirley, in the last section. A 62-year-old widower, Shane has spent two years on dating sites looking for somebody to love. He matches with Jemima, and the two establish a lovely rapport, mostly via email, delighted to find they share several interests, from Mediterranean history to the music of the Rolling Stones. Shane even thinks he has seen her before, but he’s not great with faces. Shane has heard a lot of scary information about romance scams. So he is relieved when Jemima agrees without hesitation to talk on the phone, and even more relieved, a few weeks later, when she follows through on their plans to meet at a bar near Sydney’s Circular Quay. The dating app has done its job: they live in the same city, on opposite sides of Sydney harbour. Jemima is, indeed, a real person, and as warm and attractive in three dimensions as she was on the internet. He even remembers where he had seen her – when he ran the North Sydney parkrun instead of his regular one at Centennial Park. Jemima and Shane soon find themselves spending most nights together. They find new mutual interests, from marathon running to the Sydney Swans Australian Football Team. Sure, they have their disagreements, and being in a relationship with a new person after each having been married for decades requires some adjustment. But Shane and Jemima seem on a trajectory to happily-ever-after. 117

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What do you think happens then, when Shane surprises Jemima with tickets to see the ’Stones play at the SCG, and she not only appears unsettled, but also seems not to know the difference between Let it Bleed and Voodoo Lounge? Later that night, Jemima confesses that she had never given the Rolling Stones a moment’s attention until just before she met Shane. Way back before they ever matched on the dating site, Jemima tells Shane, she spotted him at her local parkrun and noted the lack of a wedding band. She narrowed his name down to a few possible finishers from the list of results for that week. She then paid an online agency to do the kind of cyber-sleuthing that most people do for their own safety and peace of mind before a date these days. The agency found out that he was a widower, owned his own home, had no criminal convictions and sported a perfect credit score. Encouraged by the results of what she considered a due diligence exercise, she paid the agency a much more substantial sum for use of their Premium Dater app. The as-yet fictional Premium Dater sits right in the middle of my Venn diagram of artificial intimacies, in the overlap between digital lover, algorithmic matchmaker, and virtual friend. The app scours social media for interests, patterns of speech and location data. From his profile on the Strava exercise app, Premium Dater learns where and when Shane takes his runs, and where he rides his bike. It infers from his social media posts that he is fascinated by the Phoenician empire, and is a massive fan of Mick, Keith, Charlie and Ronnie. More than that, the app offers conversation-starters, a range of follow-ups and tailored observational nuggets that users like Jemima can copy across to their email client or messaging app. Most convenient of all, Premium Dater revealed to Jemima that Shane had a profile on a dating app that specialises in matching over-fifties. All she then had to do was follow a few hints from Premium Dater on how to amend her own profile on the over-fifties app in order to maximise her chances of making a match with Shane, and then commit 118

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to spending a few evenings swiping at the profiles that were served up to her. Less than a week later, Shane’s profile popped up, and she swiped hard right.

You can’t always get what you want Jemima tells Shane that throughout their relationship her sense of regret at the deception has built from a whisper to a scream, compelling her to cancel her subscription and delete Premium Dater the day after she and Shane first met up. She knows how violated she would have felt had their roles been reversed, but she asks Shane to consider how many of her dating attempts had gone absolutely nowhere. After her husband died and Jemima found her long way back to entertaining the idea of dating, she did not know where to start. The last time she dated was back in the 1980s, at university. Her world had rained men at that time, and enough of them appealed to and interested her that she never had to worry about a lack of company. But dating in her late fifties was a different story. She read the laments of the ‘man drought’ by attractive twentysomething professional women in Sydney, and scoffed: ‘Come back and tell me about the man drought when you’re nearing sixty’. According to OkCupid dating app founder Christian Rudder, women under 30 tend to give the highest ratings to men two or three years older than them.12 Through their thirties, they tend to rate men of roughly the same age as them as most attractive, and from their forties onward they start preferring slightly younger men. Men, however, from 20 to 50 years old, tend to rate women aged 20–24 most attractive on average. Their preference does not shift much as the men age. Crucially, how groups of people behave, on average, shapes patterns of demand, and thus the attention that people of certain ages are likely to attract. The online matchmaking data reveal something demographers 119

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have long known. Australian demographer Bernard Salt calls it the ‘Hotness Delusion Syndrome’.13 As he explains, a 25-year-old single Australian woman has 23 per cent more single men interested in her than a single 25-year-old man has single women interested in him: There’s a delicious oversupply of single men competing for affection. And that’s just the way women like it: lots of options means they can make a selection from what they believe is the best on offer.

By the time they reach their late thirties, however, the demographic tables have turned so far that a man drought now pertains. An overwhelming proportion of the ‘good’ men in their late thirties and early forties are taken, leaving mostly less partnerable guys. The few available men enjoy much more attention than their twenty-something brothers. According to Salt, ‘the same delusion about hotness that applied to 25-year-old women also applies to 44-year-old men’. When Jemima turned to online dating, she soon realised that the world of dating she knew in her twenties had inverted. Rather than lament her disadvantage, she sought to deploy the best tools that technology could offer her. And so she came to subscribe to Premium Dater.

Resist, for another moment, the reflex to condemn or excuse behaviour like Jemima’s, or to write the example off as an imagined side effect of not-yet-here technologies. If my own field of evolutionary biology reveals anything about human mating, it is that dating and mating – in whatever cultural form they take – have always been complex games, played not only against competitors but also against opponents – the dates themselves. 120

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People everywhere and always have had to put their best foot forward, their best self forward, in how they present themselves. They occasionally overrepresented themselves, sometimes leaned hard on their gossip networks for inside information, and, more often than most would feel comfortable admitting, they turned up in places where they had no business, in the hope of a ‘chance’ encounter. What stands out about the urbanised, hyper-connected world where we live, is that we are pitted against vastly more competitors and possible opponents than was ever possible before. The opportunities for tech-savvy individuals to deploy artificial intelligence in their favour are likely to proliferate in this new digital ecosystem. When algorithmic matchmakers are left to decide who sees our profile, for example, should we be surprised that some clever souls are already writing their own AI bots to game the app and make good matches?14 Could the rise of artificial intimacy hasten another explosion in sexual inequality, in which the tech-savvy, and those wealthy enough to pay, have access to the best dating tech of the future. Tech like my fictional multi-tool Premium Dater app could deliver individualised strategies to beat the dating algorithms and get superior matches. It could screen possible partners and avoid wasting time by finding out if they already have a family, serially philander, gamble, spend profligately, abuse substances, get high on narcissistic supply, or simply tend to suck the oxygen from any room with their tedious conversation. Such a tool might deliver the most useful technological weapon of all: conversational strategies, tailored to build intimacy fast. The rest of us, not even aware of all those technological powers, will be left wondering what it takes, what is wrong with us, that we aren’t going on the kinds of dates or having the kinds of relationships that others, neither more talented nor more personable than ourselves, are enjoying. Premium Dater is currently as fictional as Jemima and Shane, but I would be willing to bet that tools very much like it, perhaps with only 121

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a few capabilities each, are already deep in production. Jemima’s tale is about as benign an outcome as could possibly result from such an app. Shane might be grateful for the technology that brought them together and happy to put the incident behind them, or he might be incensed at the violation of trust and ask Jemima never to contact him again. I will let you take a moment to choose your own adventure.

Not so benign Consider for a moment if the roles had been reversed. Would you respond differently if Shane had cyber-stalked Jemima? Perhaps Jemima’s benign intentions, and the fact they established a relationship that both of them wanted is enough. I wonder what Shakespeare, Austen or Atwood might have made of the scenario? Consider whether you would see the situation the same way if the target were 15, and the stalker in their thirties. Educated people in the twenty-first century mostly find the idea of an adult pursuing an adolescent disturbing and repellent. There exists in such a mismatch a gross imbalance of power, experience and emotional maturity that puts the young person at an unfair disadvantage. Age-of-consent laws recognise this. In many jurisdictions, provisional age-of-consent laws acknowledge that sex between two 16-year-olds can happen in a healthy and positive way, but sex between a 16-year-old and a 36-year-old reeks instantly of exploitation. According to Erik Berkowitz, in his magnificent yet disturbing Sex and Punishment: Four Thousand Years of Judging Desire, laws protecting tweens and young teens arose very late in most countries.15 Only as recently as 1875 did the English Parliament raise the age of consent from 12 to 13, and it took a bruising public campaign to eventually raise it to 16 in the year 1885. Until the late nineteenth century, consent in most states of the US was considered possible at very young ages: ten 122

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in California, and seven in Delaware. Until 1891, the age of consent in India was ten, but it is now 18. Adolescents have long inhabited a perilous limbo between childhood and adulthood, and many girls and boys entered the world of sex long before they attained the maturity and self-confidence necessary to negotiate consent. In spite of contemporary societies’ much stronger legal protections, however, sexual curiosity and motivation still flourish in adolescence. As any parent of teenagers will confess, adolescents remain vulnerable to manipulation and coercion both online and IRL, particularly by people who are older, more experienced, financially better off, and far less scrupulous than they seem. Artificially intimate applications like my fictional Premium Dater don’t seem as benign in the hands of a predator as they did in Jemima’s. Yet if a commercial dating app could conceivably pull together AI tools to research, identify, match with and groom an otherwise equal love interest, then we should fully expect that those with more predatory intentions will do the same. The underage victim is only one example, chosen for the lack of moral ambiguity, but almost anybody could fall victim to this kind of malign artificial intimacy. If all that a storied lover like Leonard Cohen ever learned from love was how to shoot at someone who outdrew him, then can there be any trust, or love, or mutuality if one party comes armed with Cupidesque arrows like Premium Dater in their quiver, and the other does not? Then lines blur between predator, scammer and suitor; the only distinction is their intentions. If knowledge is power, and if power imbalances distort relationships, then what hope does a relationship have if one party begins by knowing almost everything there is to know about the other? This may sound abstract, but, as Adam Dodge, legal counsel for Laura’s Place, a Californian domestic violence shelter, told me at a recent conference, ‘over 85 per cent of the intimate partner violence restraining orders that I file have some form of cyberstalking element’. Stalkers, 123

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from ‘secret admirers’ to jealous, controlling partners or exes have found so many uses for the smartphone. The potential for creepiness begins before you even meet accidentally-not-accidentally. By glancing at your Instagram or Twitter posts, somebody can ‘mysteriously’ appear where you are, and bump into you. Exercise apps post maps of where and when people run or ride. Seeing one another regularly on a running route might make for an easier introduction later on, as it did for Jemima and Shane. Apps, including Find my iPhone provide precise information on where a person is. Whereas once stalkers or abusive partners had to find and follow their victim or hire an investigator to do so, now the target’s phone can do that job for free. It is no longer always possible for the victim of a controlling partner to ignore incoming calls and pretend they had had their phone switched off, now apps including Facebook Messenger and Instagram provide real time updates to the world on when you last used the app. Those are just some consequences of the information that commonly used apps provide. On top of that, there already exist several hundred smartphone apps designed explicitly for spying on people, particularly intimate partners.16 The perpetrator surreptitiously installs the app which then becomes invisible but sends text, call and location details to the perp. Only a victim who is aware of the issues can take the many laborious steps to protect themselves. Given the number of apps on our phones, each of which change with every update, even savvy vigilance does not constitute a perfect defence. Technology currently gives creeps and abusers a distinct advantage in their chaotic arms race with their targets. Yes, there are anti-spying tools too, and a massive effort to share strategies to thwart and defend against attacks. But the arms race is only likely to accelerate, as machine learning, image recognition, voice recognition and natural language processing improve. Stalkers and abusers could soon know not only where their targets are, but what they are doing, and saying, and exactly who they are with. 124

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Machines got game As artificial intimacies learn how best to draw a person close, to emulate friendship, intimacy and love, we should expect they will be able to abet darker relationship arts too. Jemima’s Premium Dater app gave her conversational gambits tailored to Shane’s interests, gleaned from dozens of discussion forums like Rocks Off, the Rolling Stones message board. Machine learning extracted several topics guaranteed to animate – but not alienate – true ’Stones fans. The app gave Jemima triple platinum cheat notes to help her win Shane over, and they worked. The better artificial intimacy becomes at tailoring conversations, the more of an advantage it will confer in the early days of dating. Just as many of the apps currently used by cyberstalkers arose to meet benign, helpful, even safety-conscious needs, so too one can easily foresee in conversation-starter apps a series of malign applications. They will enable unscrupulous operators to seduce, groom or coerce their victims by imitating intimacy, faking love, and even feigning sexual interest. Even those suitors on the high road toward romance between consenting adults may find themselves corrupted by artificial intimacy. There are already entire industries devoted to empowering people through introductions, conversation starters, bridging conversational lulls, and closing the deal. Sound a bit like the hard-sell? Well it is, but ‘closing the deal’ means getting the target into bed, and not always via consensual best-practice. A particular strand of self-help for hetero men takes as its point of departure the nagging sense that somebody, somewhere, is having lots of sex, and that it is possible for an average frustrated chump (or AFC) to learn how to become that somebody. The Game: Penetrating the Secret Society of Pickup Artists, traced music journalist Neil Strauss’ journey from AFC into the world of pickup artistry (or PUA). Mystery, a magician, master of the dark art of sleeping with hot chicks, and PUA instructor taught Strauss how best to find, meet, attract and ‘close’ with 125

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good-looking women. Strauss collected a veritable directory of phone numbers while getting laid a whole lot along the way. Pickup artists and the seduction techniques they call ‘game’ involve dissecting the elements of courtship and seduction, studying what the most successful proponents do, and working on skills the way a football coach might do with a team. Part of PUA, and just about every other form of dating advice, involves how best to finesse that kind of mild deception almost everybody engages in: making the most of our looks, standing out from the herd, feigning interest in order to appear more interesting ourselves, and framing ourselves in the best ways possible through the things we say. At its most benign, PUA advice helps men overcome a lack of confidence, harness their verbal creativity, and subvert established scripts that hold them back from meeting, dating and mating with the women they desire. But that advice morphs seamlessly into manipulation, such as the infamous business of ‘negging’ women with subtle put-downs to undermine their confidence and reshape the power dynamic in the man’s favour. Given the aim of ‘game’ is to have sex, many of the most crucial skills involve subverting and circumventing women’s social defences, for which PUA have described an entire taxonomy, including the ‘bitch shield’, ‘anti-slut defense’, ‘friend zoning’ and ‘last-minute resistance’. One aspect of ‘game’ involves ‘kino escalation’, gradually building physical contact from casual fleeting touches toward sex, progressively escalating the encounter. Some writers dispense their advice in ways that stress the revolutionary idea of being responsive to the woman’s signals and needs. But a great deal that is written about kino escalation reads like a manual for sexual assault. On internet sites and in books devoted to the PUA game, one can develop migraines as they blur from courtship to coercion and back again. For AFCs and the PUAs who exploit their desperation, getting women to have sex with you is treated like a covert psycho-military 126

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operation. One website even promises to share ‘Black Ops’ psychology techniques, another the ‘Jedi mind trick’ that ‘exposes a loophole in female psychology’ and, even more charmingly, ‘brings pussy straight to your dick’.17 The Seduction Initiatives Baltimore Group, for example, offers under the rather quaint title ‘Operation Mind Screw’ the following promise: There exist some covert seduction techniques which can make any woman fall in love – sometimes in as little as 15 minutes or even less. These techniques are often rooted in hypnosis and mind control, and as you can imagine, they can be downright dangerous if they fall in the hands of the unscrupulous. One of such techniques, known as Fractionation, is the basis of perhaps the most innovative (and controversial!) seduction routine of all time: the October Man Sequence. Fractionation involves making a woman go through an emotional roller coaster, and in the process makes her emotionally addicted to a man.18

Sound like abuse to you? The most publicly reviled PUA figure of all, LA-based ‘dating coach’ Julien Blanc, makes no pretence at promoting self-improvement, but rather offers to teach men ‘to shatter her lack of consent’. He once tweeted an infographic developed to educate people about the strategies intimate abusers often use. Below the infographic he commented: ‘May as well be a checklist … #HowToMakeHerStay’. Despite public outrage and cancelled visas, Blanc’s notoriety draws growing audiences of men thirsty to imbibe his advice on intimidating women into sex. One can lose days of one’s life following the internet rainbow to the pot of fractionated gold, hoping to learn how to reliably fulfil fantasies of easier, more abundant sex. Along the way, one encounters the same sales techniques and testimonials used to sell four-minute exercise 127

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regimes that guarantee six-pack abs, and ways for men to give women five or six orgasms a night. For many, PUA is as effective as four-minute ab exercises. Some PUA, however, is probably quite effective at achieving its intended goals. It certainly seemed to work for Neil Strauss. And that which is useful often leads to the development of a smartphone app. Become a Pickup Artist promises to teach you ‘the best, non-cheesy lines in the book to get a woman interested’. Get Any Girl: The Ultimate Pickup and Dating Guide offers all-round self-improvement to rebuild the man, his confidence and his game, transforming him into a pickup machine. Unfortunately for my curiosity, though less unfortunately for womankind, the app Get a Girl: Dating Decoder seems to have been taken off the market. But we do have this review by Gayana Sarkisova at Complex:19 We already know that every woman is different. Unfortunately, there is no handbook that tells you how the chick you are talking to is different from all the rest. Until now. Get A Girl takes a stab at providing you with just that information. You simply enter her specific characteristics and the app pulls up her personality type. You’ll never be caught off guard by a chick again.

Sound familiar? The wisdom of PUA gurus lends itself, again, to the algorithmic performance-feedback-revision power of machine learning. Apps like these will get more effective at delivering what they promise as soon as machine learning starts working its way through the piles of user data from dating and direct-messaging apps. There is no reason for artificial intimacy tools to confine themselves to learning the nuances of benign compliments and taking a genuine interest in other human beings. If negging works, they will learn to neg. If fractionation is a thing, then they will likely find new ways to fractionate. And if the October Man 128

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Sequence is genuinely the most effective seduction technique of them all, then we can expect artificial intimacy to discover it anew, and then to perfect it.

Can’t get you out of my head From the promise of sex robots to my fictional ArtInt dating platform Premium Dater, applying artificial intelligence to the witchcraft of human relationships is likely to have serious and complex consequences. I often return to the concern that artificial intimacies might replace or substitute for human functions, like friendship in its many-layered forms, like love and like sex. It is a concern because they might then squeeze people out of those very human interactions, diminishing the individuals involved and eroding the quality of life. Those are the most immediate and likely consequences of artificial intimacy, not least because the ArtInt doesn’t even have to be that good in order to start squeezing. Facebook isn’t much good at emulating friendship, but it is quite effective at sliding into the headspace and time we normally spend on grooming and gossiping with our friends. In so doing, Facebook is excellent at stealing our attention and selling it to advertisers. Tinder isn’t that good at matching us with people we like, but it excels at brokering first contact between people who are equally photogenic. Sex dollbots make pretty poor substitutes for lovers, but, by the few accounts that can be found on the net, playing with them provides a degree of satisfaction. What is clear from this chapter, however, is that artificial intimacy presents dangers well beyond substituting for human functions and thus squeezing real humans out of our lives. When I asked my UNSW colleague, Scientia Professor of Artificial Intelligence Toby Walsh, what dangers sex robots might pose, he didn’t hesitate: ‘They might mess 129

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with our heads’. It seems obvious now. Human lovers, suitors, and abusers do, so why wouldn’t robots or other kinds of ArtInt? The obvious danger comes from the kinds of characters I have introduced in this chapter: artificially intimate applications that groom, scam, catfish, neg, troll, trick or coerce people. All of those things already happen offline and online. When artificial intimacy creeps in to those kinds of interactions, often after learning what works in benign, loving and consensual relationships, expect that it will usually be found playing for the offensive team. How tools could play defence for victims of artificial intimacy remains to be seen. The potential for artificial intimacies to mess with people’s heads in other ways is right there, peeking at us from the gamified romance of LovePlus, the owner-pleasing cuteness of AIBO, the impressive AI language and machine learning capacities of Alexa, the visually arousing creations of virtual reality porn, and the sculpted sexiness of dollbots. Whenever the day dawns that digital lovers can gamify love and manipulate the emotional reward centres on which intimacy grows, versions that diminish and ‘neg’ their users, manipulate their insecurities and punish inconvenient behaviours will not be far behind. Just as it is a mistake to believe only ‘bad actors’ do bad things in relationships, it is naive to imagine that machine learning algorithms will steer clear of human emotional vulnerabilities. When artificial intimacies that are confined to a silicone and carbon-fibre humanoid body go bad, users will at least have some idea who, or what, they are dealing with. With virtual reality improving at lightspeed, machine learning could soon infer the intimate, emotional and sexual fantasies users never even knew they had, and deliver them in VR without physical-world constraints. It could also learn our deepest weaknesses, and deploy them against us in our wider lives. The potential for artificial intimacies like VR lovers to cause mental and emotional damage sometimes looks limitless.

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Standalone digital lovers this sophisticated are obviously some years away, but they deserve a moment’s consideration. For many people, the possibility of danger or domination gives sex some of its frisson. The possibility of sadistic, dominant digital lovers going bad might be prevented by legal regulation of what kinds of things they can do. That’s a possibility that should be handled with care, lest we suffer a renaissance in the old moralistic impulses for some people to decide what other people can do in their bedrooms and their fantasy worlds. A better response might entail developers and manufacturers learning from kink communities to build in consent failsafes and electronic safe words so that users can literally turn an errant digital lover off or tune it out of a bad scene. If that is the route the development of ArtInt goes down, many people not familiar with kink will learn lessons about consent and safety that are long overdue. The consequences for human–human relations may indeed be better than if we only allow the most vanilla forms of artificial intimacy to be made and sold.

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7

Ploughs, pills and porn: How technology changes sex New technologies have changed sex throughout history by altering the ways in which women and men make their livings and go about their lives. Many of those changes alter how rare and precious sex seems to be.

‘Love and marriage’, crooned Frank Sinatra way back in 1955, ‘go together like a horse and carriage’. And by love we can safely assume Frankie meant sex. As he laid it down in one of the later verses, Dad was told by mother You can’t have one, you can’t have none You can’t have one without the other.1

In 1955, my own grandparents would have ensured they sent their children away for the weekend before spinning anything as racy as Sinatra on their 78 rpm gramophone. For them and their contemporaries, ‘sex’ was a part of the marriage deal, packaged up with love, children, and a shared checking account, and best never mentioned again. That horse-and-carriage view of love might seem unbelievably fusty to young people today, but 1955 remains the nostalgic heyday of human gender relations for many twenty-first century social conservatives. The kinds of conservatives who talk about ‘traditional’ marriages and 132

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families, and who mean a mummy, a daddy, and a handful of children, living in a suburban house. This may have been a common sight on 1950s American television, but even then it was a middle-class, white, heterosexual stereotype. Viewed in the context of what anthropologists have uncovered about human relations, nothing rendered that era any more ‘traditional’ than any other. Timescale makes all the difference if we want to talk about what a ‘traditional’ family or sexuality might look like. A deep historic view reveals that, like common chimpanzees and bonobos, our ancestors had little use for sexual exclusivity five million years ago. Since then, despite human domestication and an evolved knack for monogamy, human sexual and family configurations have tracked changes in how women and men make their livings. Often those changes came about due to the adoption of new technologies.

Making a living In 1846, being seventeen years of age, I was admitted to the council of the warriors … Perhaps the greatest joy to me was that now I could marry the fair Alope, … I went to see her father concerning our marriage. Perhaps our love was of no interest to him; perhaps he wanted to keep Alope with him, for she was a dutiful daughter; at any rate he asked many ponies for her. I made no reply, but in a few days appeared before his wigwam with the herd of ponies and took with me Alope. Goyaałé (Geronimo), Chiricahua Apache leader2

The dusty plains and mountains where southern New Mexico and Arizona collide are the traditional lands of the Chiricahua, one of the Apache tribes. Their conflict with European settlers throughout the 133

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nineteenth century etched the Apache, and leaders like Cochise and Geronimo, into American folklore. Despite these conflicts, a number of Chiricahua elders, like Geronimo, shared rich oral accounts of how they lived.3 Chiricahua women and older children gathered wild plants like agave root, berries and seeds. They caught rabbits, wood rats and wild turkeys. Men helped to gather and trap, and they hunted large animals like elk. Women’s work included most household chores, including building the temporary wickiup (wigwam) shelters in which families lived.4 Only men, on the other hand, could go on the war path. As Geronimo describes, marriage defined the gateway to adulthood, a necessary precursor to sex and reproduction. The Chiricahua frowned on premarital sex, and considered virginity a sign of purity in both unmarried men and women.5 They harboured particular distaste for infidelity. When men went away on hunting trips, they set relatives to spy on their wives. ‘If he finds out she is unfaithful, he whips her, cuts her nose, or else kills her’ one Chiricahua man told the anthropologist Morris Opler.6 Cutting off a wife’s nose rendered her unattractive and therefore less likely to stray again. A cuckold could kill or maim his wife’s lover, but wives had less recourse against straying husbands. At worst an unfaithful man could fear a scolding from his wife. The particulars might be culturally unique, but traditional Chiricahua marriage and family life entailed a common constellation of cultural traits. Harsh treatment of unfaithful wives, coupled with relative lenience for husbands, exemplify the sexual double standards that litter both the anthropological record and contemporary cultures. According to one study of 116 traditional societies, more than half permitted some extramarital sex for husbands, but only ten per cent allowed any for wives.7 In societies like the Chiricahua that expect fidelity from both spouses, unfaithful wives drew far more severe punishments than philandering husbands. Traditional societies that consider sexual jealousy acceptable and 134

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allow harsh punishment of unfaithful wives tend also to confine sex to highly transactional marriages.8 Wealth and status determine who can marry, often via bride price like the ponies Geronimo paid for Alope. Bride prices lock poorer men out of the mating market, and smudge the line between spouse and owner. Men in these societies invest heavily in their children, taking a close interest in their care, and giving them property, livestock and other goods. In societies where women enjoy more sexual freedom, and where marriage is less of a transaction, men often show less interest in the children their wives bear. Many South American forest-dwelling tribes are quite easygoing about paternity. Women often have more than one acknowledged sexual partner at a time, each of whom views himself as a joint father of children she bears. The Mehinaku of the southern Amazon rainforest, near the Brazil–Paraguay border, believe that conception requires more than one sexual act. Anthropologist Thomas Gregor, who studied the people of a single Mehinaku village, documented so many extramarital affairs that only three women in the entire village were not – to his knowledge – involved extramaritally.9 When a Mehinaku woman with a husband and one or more lovers conceives a child, the husband’s semen is thought to have done only part of the job. The mother’s lovers accept some of the responsibilities of fatherhood, and men refer to paternity as a wanaki, an all-male collaborative effort. One should not rush to romanticise this shared burden of paternity or the idea of an easygoing polyamorous Eden replete with unfettered and consequence-free sexual variety.10 Mehinaku spouses don’t tolerate every affair. But, compared with other societies, the Mehinaku sit down at the more relaxed end of the jealousy spectrum. The Amazon forest provides like an occidental Eden where fish practically leap into canoes, fruit falls from trees, and gathering enough food to eat is relatively easy. Men contribute little more than an hour or two’s work each day, but one of their big contributions involves 135

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defending their partners and children from the dangers that punctuate Amazonian life. Though animals like jaguars present a threat, other men pose far more danger. After the first years of the child’s life, when having two parents gathering food really helps, Mehinaku marriages often dissolve amicably, and each partner goes on to pair with another. Men’s contributions to the family are not onerous, so men can afford to not be hypervigilant about paternity. Indeed, fathers have much to gain from sharing the responsibility of paternity with other men. Men with a stake in a child’s paternity make all the difference in defending the child from harm. A kid with two dads has double the chance that one will survive long enough to protect them until they can protect themselves. Keeping several men guessing about paternity might work in the kind of dangerous but productive environment of the Amazon. In societies like the Chiricahua, where getting by takes more effort, and where women and men really depend on one another’s hard work, marriages become more exclusive, last longer, and sexual jealousy lurks ever closer.11 The Himba pastoralists of Northern Namibia inhabit an arid plain not unlike the Chiricahua home. Himba families tend to choose their son or daughter’s first spouse, and boys’ families pay a bride price in the form of livestock. These features would lead a naive anthropologist who stumbled upon a Himba settlement to predict that, like the Chiricahua, the Himba would exhibit strong sexual jealousy, sexual double standards, and infrequent extramarital sex. Compared with other pastoralists, however, Himba bride prices are limited to a few animals, making marriage relatively affordable. Divorce is easy and common, and many subsequent marriages are ‘love matches’ between spouses who choose one another. The Himba neither stigmatise nor punish extramarital sex. That is not to say spouses don’t mind, but rather, as I infer from my conversations with researchers, that the Himba don’t consider other people’s relationships much of their business. 136

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Himba attitudes to sex tie into how they make their living herding cattle, sheep and goats. In order to find grazing, husbands often spend long periods away. During these absences, wives, who remain at home, sometimes entertain lovers. UCLA anthropologist Brooke Scelza has spent more than a decade visiting northern Namibia, uncovering the fascinating world of Himba culture. She told me that if a man, returning from being away, reaches the village during daylight, he goes to his wife. If, however, he returns after dark, then he goes to his brother’s house for the night, unwilling to cause awkwardness if his wife happens to have a lover with her. When Scelza interviewed Himba women, they described many children as omoka: fathered by a man other than their then-husband. Several more years of careful interviews, consultation and, ultimately, collection of DNA samples, allowed Scelza and her colleagues to estimate how many children are sired by somebody other than their social father. The answer, 48 per cent, astounded many scientists because of just how far it exceeded any reliable estimate published for any society.12 Despite some sensational but poorly substantiated claims of 10 to 30 per cent ‘extra-pair paternity’ in Western human populations, the most trustworthy analyses suggest figures of around one to two per cent.13 The Himba numbers, and the related estimate that 70 per cent of married Himba couples have at least one omoka child, represent more than an extreme and surprising outlier. Rather, they indicate that most studies of human paternity have considered only a very restricted corner of the human cultural landscape. The estimates of one to two per cent come mostly from contemporary or recent historic Western populations, where strong norms and institutions restrict extramarital sex. The Dutch Reformed Church kept South Africa’s Afrikaners on a socially and sexually conservative path for 300 years.14 The very lowest estimates of extra-pair paternity come from rabbis in Orthodox communities where strict menstrual taboos prevent a man from hearing his menstruating wife sing, smelling 137

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her perfume, or even gazing upon her clothing.15 Such restrictions ensure that when the couple can be together, which is also when they might conceive, they don’t miss their chance. The Dogon people of Mali practice a monotheistic traditional faith that bans spousal contact and sex during menstruation. Men believe they will lose their virility if they come into contact with menstruating women, and so women move away to special huts while menstruating. A study led by University of Michigan anthropologist Beverly Strassmann revealed that women who use the menstrual huts conceive only 1.3 per cent of their children outside of marriage, far fewer than the 2.9 per cent conceived by women who do not use the huts.16 Low extra-pair paternity is almost certainly not the default setting for humans. Rather, the sex by which women can conceive extra-pair children is suppressed in those populations. Taboos limiting when people might be together, rules about who can be alone with whom, norms surrounding jealousy, sexual double standards, and many other cultural traits all function to suppress sex. It so happens that the Himba are down near the more easygoing end of the continuum of behaviour, probably not as relaxed as the Mehinaku, but nowhere near as uptight as the Chiricahua. These glimpses of Chiricahua, Mehinaku and Himba lives illustrate a pattern confirmed across dozens of societies: men invest more in their children in societies where those children are highly likely to share their genes. Suppressing women’s sex, as the Chiricahua did, shores up a man’s confidence that his wife’s children are also his own genetic offspring, making him more likely to invest in those children, and to pass property on to them. A freer female sexuality, as in the Mehinaku, usually comes with less investment and involvement from the social father. It also comes with less jealousy. Another study led by Brooke Scelza found that the Himba sat somewhere near the middle of a sample of 11 societies in terms of how they respond to sexual and emotional infidelity.17 138

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Likewise for paternal investment. Himba fathers fed, held, groomed, played with, and provided for their children less than fathers from seven of the other ten societies. Even though Himba men don’t make the most active fathers, as you might expect when only half their children are their genetic relatives, they do take pleasure and pride in their children, both non-omoka and omoka. Indeed, University of Missouri anthropologist Sean P Prall, together with Scelza, found that Himba men are expected to invest equally in both their genetic and omoka children, and that for the most part they live up to these expectations.18 Neither the Chiricahua, the Mehinaku, nor the Himba behave in any way more ‘naturally’ than the other. Neither is any more nor any less natural than Sinatra’s love-and-marriage America of 1955. Rather, the state of nature is contingent: women and men have evolved exquisite tuning to behave in ways that match their circumstances, including the ways in which they make their livings, and their local societal norms. Based on the fact that societies like the Chiricahua in which men wield more economic and political power than women also tend to stifle female sexuality,19 it has become axiomatic that when men gain greater economic and political power than women, they use it to restrict female sexuality. Yet the arrow of causation could also fly in the opposite direction. In societies where men make heavy investments in their wives’ children, norms might subsequently have become more restrictive on female sexuality. The most likely route to cultural differences involves a cyclical process of reinforcement that raises the price of sex. Paternity confidence leads men to invest long-term in their families. These investments make men attractive to women and give women reason to turn down outside opportunities. Women’s exclusivity both restricts the supply of sex and increases men’s paternity certainty, leading on to further increases in the value of the men’s investments. In short, this feedback loop pushes 139

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the value of women and men to one another as mates ever upward until other pressures stop or undercut it. Why does this matter? And what does it have to do with twentyfirst century technology? Because when new technologies alter the ways in which women and men contribute to the household, they disrupt gender relations and sexual behaviour.

Origins of inequality Of all the technology-driven changes in human history, none revolutionised relations between women and men as thoroughly as the adoption of farming. Over the last 12 000 years, whenever farming changed the way women and men work, it also changed sexual behaviour and introduced new forms of inequality. Our hunting and gathering ancestors were famously egalitarian. Not due to high ideals, but because the resources they needed to live on could seldom be accumulated or defended. Nonetheless, the incentive to accumulate a little bit of wealth and to rise somewhat above the rest in status motivated our ancestors from the earliest times. Only when people could settle and defend productive territories could inequality slip the leash. In north-west Canada, for example, powerful families ‘owned’ prominent fishing rocks.20 On these they built platforms to fish from the deepest river sections where the biggest salmon ran. Lower status families fished from the banks, taking less food for their efforts. A defensible resource – fishing rocks – and a form of wealth that could be stored for months – dried salmon – created the conditions for rising inequality, keeping the high-status families up, and the lower status families down, for generations. When foragers harvested the fruits and seeds of the best plants, occasionally dropping seeds near favourite campsites, they inadvertently 140

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started domesticating crops. Later, as they learned about how plants bred and flourished, they selected deliberately, becoming, over many generations, farmers. This happened several times over, with people independently domesticating wheat in Mesopotamia, the Levant and north-west India, corn in Central America, rice in China, sorghum and millet in the African Sahel, and a variety of other crops in various farflung places. Permanently settled arable land can be owned, defended and passed on to heirs. So can herds of livestock. Surpluses can be exchanged for other goods or services or sold for money. Families that settled good land, kept productive herds or provided other valuable services, accumulated wealth. The fact that wealth could be passed from one generation to the next created economic inequalities among families, and these inequalities ballooned with each generation. Karl Marx and Friedrich Engels pointed out more than 125 years ago that whenever people began to farm and to keep livestock, men seized the means of agricultural production, thus usurping female power.21 Although more than a century’s progress in anthropology, sociology and economics have eclipsed the details of Marx and Engels’ analysis, the broad ideas remain important and often under-appreciated. Early farmers turned the soil with hoes. If contemporary hoe-based agricultures are any guide, women farmed more than men. Farmers in many parts of the world discovered that they could get an ox or horse to drag a blade through the ground, ploughing up far more earth than any person could turn with a hoe. Development economist Ester Boserup noted that when societies began ploughing, men discovered a new zeal for farming, and gender relations in those societies were never the same again.22 Men’s enthusiasm for the plough squeezed women out of the most visible and lucrative work, relegating them to home-based tasks and child-rearing. This shifted cultural gender roles so far that they remain displaced centuries later. To this day, industrialised societies 141

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around the world with a history of plough-based agriculture are more resistant to women earning wages outside the home than societies that never ploughed. The earlier a society took up farming, the more they nowadays impose sexual double standards and punish female infidelity.23 Why did men discover a sudden enthusiasm for the hard work of guiding a plough? Perhaps ploughing requires a physical strength better suited to men. Perhaps it is harder for a mother to watch her infants as she guides an animal-driven plough up and down a field than it would be while hoeing over one small patch of ground at a time.24 It turns out there is nothing particularly special about the plough. Other types of intensive crop cultivation, like paddy-based rice farming, had similar effects on gender relations. The effects of agriculture persist thousands of years later. The earlier a society started cultivating cereals like wheat, barley, rice, sorghum or corn, the later that society granted women’s suffrage, the fewer women have been elected to parliament, and the lower is female labour force participation to this day.25 What about if, by generating surpluses, the plough and other forms of intensive agriculture presented men with the ideal vehicle to accumulate wealth, rise in status and outcompete other men for wives and mistresses? The economic dynamic is like that of the dunnock cock who earns a very large territory. More than one hen makes her own territory within his, and he enjoys the fitness boost – more fledgling chicks – of polygyny. In much the same way, men who accumulate wealth and status can attract multiple wives, at the same time or in succession, and thus leave more children than those men who scrabble to get by. Women’s contributions to the household faded from visibility, even as their husbands’ work out in the fields became more prominent. The benefit of having many hands to tend the farm also created an incentive for families to have more children than had been the case for hunter-gatherers, further confining women to home and hearth. As agriculture gave rise to large civilisations, women became ever more 142

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confined to a reproductive and domestic cage, their power within society and the family eroding away.26 The combination of gender inequity and high inequality among men turned sex – and marriage – into more valuable transactions, and women into more of a commodity, than ever before. Anthropologist Laura Betzig analysed records of historic societies that arose in the Middle East, ancient Egypt, India, China, South-East Asia, Africa and Central America after each of those societies transitioned to farming.27 She found that as big inequalities in wealth and status opened up, the ruling men enthusiastically built harems, married multiple wives and kept concubines. Women could achieve more dramatic upward mobility through marriage to a wealthy man, even if that meant not being his only wife. But that also led on to bride-price customs that froze poorer, younger men out of the market for wives. The lesson for contemporary societies extends beyond the shadow of our agricultural pasts. Today’s most ‘masculine’ technologies of production can have similar effects to those of intensive agriculture. UCLA political scientist Michael Ross argues that oil production outweighs Islam as an explanation for gender inequity in North Africa and Asia Minor.28 Oil exports raise exchange rates, making it cheaper for locals to import foods and manufactured goods than to buy them from local producers. But women in those countries tend to work in domestic manufacturing and food production. When these sectors wither, women’s visibility and political influence in society, and their economic power within their homes, wanes. As a result, oil-producing countries, including those outside the Islamic world like Venezuela and Russia, retain stronger than expected patriarchal norms. And Islamic countries like Morocco and Tunisia that have little oil have made more progress toward gender equity than oil-rich neighbours like Algeria and Egypt. When women can’t create, access or defend wealth to the same extent as men, they have more than ever to gain by pairing up with a man who can do those things. That amplifies the incentive for men 143

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– from the mega-wealthy to the mere wage-earner – to both out-earn rivals and to oppose women’s economic independence. Here sits the root of patriarchy: men taking economic power for themselves while keeping it from women. Note that this view of patriarchy does not entail all men wielding economic and political power at the expense of all women. Instead, inequality among men also drives the wedge of gender inequity between women and men. The patriarchs are those men with the money and power to dominate other men and compete for women’s affections. In seizing and retaining the means of production, these men create both inequality among men and the incentive for women to marry upward. The stronger that incentive among women grows, the greater the incentive for all heterosexual men, especially the poorest men and those otherwise unlikely to find a mate, to oppose gender equity. Inequality among men, and between women and men, both make sex into a more important and valuable transaction. If human domestication raised the price of sex, then agriculture and other maledominated forms of wealth-creation, like oil, pushed that price up higher than ever.

The great reversal Since the Industrial Revolution, new technologies in manufacturing, telecommunications and computing have chipped away at the economic losses that farming imposed on women. Women regained some economic, political and domestic power. Then, in the mid-twentieth century, reliable forms of contraception finally began diluting the most potent passionkiller of all time: the risk of unintended pregnancy. Most notable of these new technologies was the oral contraceptive, often known simply as ‘the pill’. At first, legislators in many countries restricted doctors from 144

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prescribing the pill to unmarried women. They recognised both the value of married women being able to control their fertility and that unmarried sex without the chilling effect of unintended pregnancy could cause some kind of boil-over. Unmarried women who did get their hands on the pill no longer had to secure their future with a marriage licence or, at the very least, a diamond engagement ring, before going ‘all the way’. In economic terms, increased supply undercut the price of sex for the women of the 1960s and 70s. Their mothers in the 1930s and 40s had driven hard love-and-marriage bargains, insisting, as Sinatra put it, that ‘you can’t have one without the other’. But unmarried women on the pill did not have to drive those same hard bargains. A technology that challenges old certainties like those about love and marriage does not get adopted overnight. Many women wouldn’t even consider going on the pill; they just weren’t ‘that kind of girl’. All the old cultural taboos that suppressed women’s sexuality still applied. The result was a split mating market in which some women sought marriage partners in the no-sex-before-marriage kind of way, and others in the try-before-you-buy kind of way. And some women were simply looking for something brief and exciting. Women who couldn’t or wouldn’t get on the pill found it difficult to hold men’s attention against the growing number of competitors who no longer had to drive love-and-marriage bargains. They either had to get access to the pill, risk unintended pregnancy, or accept slim romantic pickings. This amped up political pressure to widen access to contraceptives and legal abortion, further reducing the chances of unwanted pregnancy, and further lowering the price of sex. The pill was only one of several factors that spurred the sexual revolution, and with it the most sudden, dramatic and widespread loosening-up in the history of human sexuality. This renaissance in women’s social and economic liberty, sex within and outside of marriage, masturbation, porn, homosexuality, love and gender roles, really 145

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got going in the 1960s in Western post-industrial societies. And it transformed human sexual behaviour. The median age of first heterosexual intercourse dropped from 19 to 17 years old between the 1950s and the 1980s, and has since remained stable, for both Australian women and men.29 In America, the average age at first intercourse fell from around 18.5 years in 1950 to just over 15 years old in 1999, and sexual activity, especially of young women, soared.30 While 40 per cent of men and only 12 per cent of women in the USA approved of premarital sex in the 1950s, by the 1990s over 70 per cent of both women and men approved. In Germany, only 31 per cent of 20-year-old women and 38 per cent of men had gone all the way in 1966, but by 1981 that proportion had more than doubled, and substantially more women (80 per cent) than men (67 per cent) were sexually experienced.31

Sinatra’s high price Marriage of the type that Frank Sinatra rhapsodised back at the threshold of the sexual revolution represents a pinnacle of high-priced sex. A man signalled his willingness to pay this price, first through expensive dates and gifts, and then with a diamond and gold ring worth approximately one-sixth of his annual income. But the real cost of this kind of marriage was paid in instalments, over the long term. The price of a woman’s forsaking-all-others sexual fidelity and her services as a mother to their children was the man’s future income, his labours as a father, and what years of good health remained to him. Both bride and groom pay the opportunity cost of hitching their carriage to another’s horse for a lifelong monogamous ride. Together they devote their domestic, emotional and commercial labours to the shared project. They both forego opportunities to make another, perhaps more profitable, match. Despite the mutual nature of the costs, the 146

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transactional nature of sex gives gender inequality much of its familiar shape. The higher the price of sex, the more divergent the gender roles, the less symmetric the power relations, and the greater the sexism. The higher the price of sex, the closer the relationship is likely to have converged on the kind of marriage my grandparents’ generation had – or pretended they had – and the kind social conservatives want restored as the ‘traditional’ centrepiece of human social life. Much of social conservatism amounts to a longing to hold on to, or return to, the old certainties and conditions that set a high price for sex. But that horse has already bolted. Sinatra himself was no paragon of lifelong monogamy. Four times married, the first a shotgun wedding, twice more engaged, and an infamous philanderer, Frankie personified one of the most potent strands of sexism: the double standard. He carved out a bad-boy reputation as a boozy gambler and womaniser who fraternised with mobsters. And yet his antics enhanced his mystique, particularly with his adoring female fan base. No woman of any era could have sustained a showbiz career with anything like Sinatra’s sexual curriculum vitae. Women have to keep their libidos in check, or at least pretend to be many times more coy than they really are, in ways that men don’t have to. The double standards that suppress women’s sexuality and yet venerate men like Sinatra act on both sides of the supply–demand curve. Suppressed supply and exaggerated demand created the perfect conditions for a high price of sex. Sinatra’s songs, movies and interviews remain as cultural relics of a time when social forces were desperately trying to hold back progress. When bad boys like him could play the field, but the bad women they played with were forgotten. And when, for good women, particularly for ‘mother’, love really was a euphemism for sex and a synonym for marriage.

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Those of us lucky enough to inhabit the twenty-first century, however, find it less difficult or shameful to admit that marriage is far from the only arena in which ‘love’ plays out. Premarital sex, extramarital sex, open relationships, swinging and casual sex might not have shed all of their illicit connotations, but neither do they elicit the opprobrium they did before the sexual revolution. They, and our newfound relaxed attitudes, are all due to a falling price of sex. Marriage isn’t nearly as big a deal either. Even those couples who aspire to lifelong exclusive monogamy, child-rearing and home renovations, treat marriage as optional. In 1970, the year I was born, 81 per cent of American adults between the ages of 25 and 39 were married. Within the course of my own generation, this number dwindled to only 51 per cent.32 The only wind blowing in marriage’s favour involved the legalisation, acceptance, and eventual embrace of same-sex marriage in many countries. Overall, though, sex and marriage are simply no longer coupled the way they were in 1955. Ol’ Blue Eyes was right, but for the wrong reasons. The inevitable harnessing of ‘love’ to marriage went the same way as the horse and carriage, relegated to historic curiosity.

Home entertainment If the sexual revolution uncoupled love/sex from marriage,33 then the revolutions in consumer electronics, computing and internet connectivity relegated the carriage to museums and sent the horse out to pasture. Even I, who studies this kind of thing for a living, find it hard to explain to my kids the difference between the traditionalism in which my grandparents courted, married and had sex – strictly in that order – and their own world in which people swipe left or right on Tinder, post 148

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sexy Instagram selfies, are open about their sexuality, and express fifty shades of gender fluidity. You do not need a time machine, a crystal ball, or even a machine learning algorithm to predict how twenty-first century technology will change the future of sex and intimacy. That future signed its first enigmatic love letters with the initials ‘WWW’, began sleeping over when you upgraded to broadband, and introduced itself to your parents about the time you got your first smartphone. Like me, you fell for the variety of entertainment and the faster, more efficient ways to connect with friends, families and colleagues. Like all romances, our relationship with internet connectivity delivered on many promises, but let us down in other ways. The arc of how technology changed sex in my own lifetime can be traced by watching porn. Or, to put it more carefully, by observing the changing ways in which people have watched and used pornography. The writing was already on the back of the toilet door when Playboy started in 1953, Penthouse in 1965, and Hustler in 1974, each turning up the dial on print erotica in line with their decade’s vibe. In the late 1960s, Hollywood’s stultifying production code withered and died, and films caught up on three decades of social progress in a single subliminal eye-blink. Porn could be seen in theatres or by purchasing magazines and smuggling them home like contraband. Technology, as it so often does, changed everything very quickly. Home video made distribution easy and viewing private in the 1980s. Then the internet piped near-infinite pornographic variety into people’s homes. From the earliest days of the internet, the sheer volume of titillating material gobbled up bandwidth, from stories and grainy images in the late 1990s to today’s streaming highways of adult video. An alien intelligence monitoring internet traffic over the last quarter century would undoubtedly conclude that humans built the ’net to transmit erotica. Between ten and 30 per cent of searches on the web – the exact estimate depends on the ideological allegiance of 149

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those doing the reporting – are for porn.34 One needn’t visit Pompeii to know that depictions of sex aren’t anything new. But never before in history have those who wanted it been able to access such a variety of acts, performed by such a panoply of professionals and amateurs, almost instantaneously, and from the comfortable privacy of their own homes. Porn’s metastasis into homes and hand-held devices everywhere has lowered the price of sex in two ways. First, it dampens demand by providing what economists would call a ‘low-price substitute’. For centuries, eccentric anti-masturbation lobbyists have warned that the solitary vice saps motivation and leads on to degeneracy. Back in 1884, Dr John Harvey Kellogg preached ‘if illicit commerce of the sexes is a heinous sin, self-pollution is a crime doubly abominable’. Kellogg prescribed plain food to suppress the urge to have sex either with others or solo, and so he gave the world the ‘corn flake’. Today’s anti-masturbation lobbyists, like the ‘NoFap’ movement, prescribe a more austere digital diet. Second, porn increases sexual supply. It begins by increasing only the appearance of supply. Hints of sex detectable in mainstream cinema, overbearing suggestions visible on billboards and the sides of buses, raunchy selfies posted on Instagram all increase the apparent supply of attractive people – but especially women – absolutely craving sex. Porn has made explicit sexual coupling visible – and audible – at the push of a button. Models of every size, shape, hue, age and gender do all manner of things to themselves, or to one, more, or many partners in all kinds of environments. The cultural shrouds that once kept sex out of sight and out of mind have shredded in large swathes of the world. That gives the inevitable impression that the supply of sex is greater than it really is. That kind of impression is often enough to create a new reality that lowers the price of sex.

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If the price of sex falls, can anybody hear it? Only indirectly, if you listen for the teeth-gnashing from those whose ideas of ‘traditional’ human sexuality are challenged by shifting gender roles and a more sexualised culture. To be sure, the sexual revolution produced plenty of downsides of the kind that conservatives bemoan. People are less likely to marry, and thus to reap the economic and happiness benefits that married people experience.35 Those that do marry are now less happy, and more likely to divorce. And fewer children grow up in two-parent families. Progressives, however, celebrate the gains for individual women, sexual and gender minorities, and for many men who have found themselves freed from old, stultifying gender roles. Most individuals are indeed better off. Intimate partner violence, unintended pregnancies, male homicide, risk-taking, sexual assault and accidents are all down.36 Sexism and sexual double standards are on the wane in much of the world, even if there remains a long way to go. And sex itself got a whole lot better. It is no coincidence that science and Western society rediscovered the clitoris, the female orgasm, and a focus on individual pleasure during the sexual revolution.37 It would seem that a more relaxed, lower-stakes type of sex is also, for most people at least, better sex. The ‘culture wars’ of recent decades involve a great deal of squabbling over the price of sex. One need only look at battles over abortion in Ireland, the USA, and right now in Poland. The fight over samesex marriage in many countries, and the furore over the ‘Safe Schools’ program in Australia remind us that sex is never far from controversy. Haggling over the price of sex still polarises societies and electorates, inflates partisan thought bubbles, fuels dogmatism, and generally undermines good governance and societal progress. Tempestuous as our culture-warring present and the recent past have proved, however, I predict that they represent only skirmishes. This century could see far greater upheaval and conflict as new technologies change human intimacy, romance, sex and family arrangements beyond all recognition. 151

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Tomorrow’s moral panic will be just like yesterday’s Anti-porn crusaders on the right and the left will seek to shut down artificial intimacy. Ultimately, both sides want to shore up the price of sex.

In the 1980s, conservative forces struck back against the sexual revolution, particularly in the USA. By forming new alliances and winning several electoral skirmishes, an army of Christian soldiers staked out their positions and dug in for the culture wars. Jerry Falwell’s ‘Moral Majority’ of white evangelicals propelled Ronald Reagan to the White House in the 1980 presidential election. Their ‘pro-American’, ‘prolife’ and ‘pro-traditional family’ sentiments, wrapped in an evangelical Christian identity, redefined the conservative–liberal divide in a way that has shaped American elections ever since. Jerry Falwell led an evangelical crusade against the growing prominence of pornography. He and his allies raged that porn violated decency, threatened ‘traditional’ families and undermined the sacredness of sex. Yet porn wasn’t Falwell’s only preoccupation. Along with an obsession with Israel, and his support for South Africa’s apartheid regime, he condemned homosexuality. Amid the 1980s panic and ignorance about AIDS, Falwell stood out, infamously proclaiming ‘AIDS is not just God’s punishment for homosexuals, it is God’s punishment for the society that tolerates homosexuals’.1 152

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Falwell relished the ancient tradition of interpreting worldly disasters as signs of divine retribution. In the aftermath of the terrorist attacks on 11 September 2001, he told the conservative Christian Broadcasting Network that those who had tried to secularise America, including ‘pagans, … abortionists, and the feminists, and the gays and lesbians … helped this happen’. Establishment conservatives like Phyllis Schlafly may have waxed less apocalyptic but they opposed a similar syndrome of social changes: pornography, abortion, homosexuality and equal rights for women. Schlafly probably did more than anybody else to stop the Equal Rights Amendment being ratified by the necessary number of states, thus preventing the constitutional guarantee of equality for her own gender. She mobilised homemakers against working women, objecting to the erosion of gender roles and to the loss of what she considered ‘women’s privileges’ like dependent wife benefits and the right to use separate toilets. Some of the 1980s’ loudest objections to porn came from the complete opposite side of the political spectrum, from some of the most radical feminists of their time. Academic Catharine MacKinnon, writer Andrea Dworkin, and their supporters opposed pornography’s depiction of female subordination, dehumanisation and objectification. To Dworkin and MacKinnon, pornography creates and maintains ‘civil inequality of the sexes’.2 MacKinnon and Dworkin famously drafted laws to ban porn in several American cities. Those laws were never implemented. The Minneapolis City Council passed the Antipornography Civil Rights Ordinance, but a mayoral veto meant it never became law. Indianapolis passed a modified form of the Ordinance, which was challenged in court and overturned as unconstitutional before it could be signed into law. Who knows what might have been? Within a few short years, booming magazine sales, a tsunami of home video, and then the internet brought porn into more homes than ever before, and into the commercial mainstream. 153

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Paradoxes, like religious conservatives and anti-porn feminists striving for a common cause, occasionally add spice to the politics of gender. Indeed, journalists often asked Dworkin if she and Falwell had formed an alliance. Dworkin disavowed ever meeting Falwell, Schlaffly or other conservative leaders, or gaining any right-wing institutional support. But she did appreciate both Falwell’s assertions that porn can be harmful, and the right-wing women who flocked to her talks.3 Many of the actors have changed – Dworkin died in 2005, and Falwell in 2007 – but the uneasy common cause remains. Conservatives who want to wind back the gains won by feminists also fight against what they consider a filthy tide of internet indecency that corrupts souls and ruins marriages. Feminism, an often fractious church, has long divided on questions about pornography and sexual permissiveness. Those feminists who tend the anti-porn flame seek to eliminate the harms experienced by women in a ‘pornified’ culture. To this day, some in the moralist right and the feminist left find common ground where they might make common gains on questions like sex trafficking and the rights of transwomen.4 I predict that they will do so again as artificial intimacy percolates through societies.

Does porn cause violence against women? Claims that pornography destroys families or stokes sexual violence can now be tested against plenty of evidence. I’m not talking here about individual testimony. Anecdotes abound of relationships torn asunder by one partner’s porn consumption, or of violent men whose tastes in internet browsing include copious porn. But the plural of anecdote is not data. A commitment to understanding the world requires an equal commitment to testing theories against the best information possible, while doing whatever one can to maintain disinterest in the outcome. Robin Morgan’s pithy ‘Pornography is the theory, and rape is the 154

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practice’ encapsulates the view, popular among anti-porn feminists, that porn leads to sexual violence.5 If that were true, the astronomic proliferation of pornography over the last half century would be matched by rises in sexual assault, including rape.6 If anything, the opposite has come to pass. When Denmark, Sweden and West Germany became the first countries to legalise porn in the late 1960s and early 1970s, they saw no increased rape incidence.7 In the USA, rape incidence did rise over the 1970s and 1980s when magazine and video porn were proliferating, but that rise was no more rapid than other violent crimes. Since a peak in the late 1980s, it has declined. According to the US Department of Justice, in 1994, before home internet fired up its slow, noisy modems, two in 1000 people over the age of 12 were victims of rape or other sexual assault.8 Over the following 20 years, coinciding with the home internet pandemic, the spread of smartphones, and the eruption of internet porn, rape and sexual assault victimisation rates almost halved to 1.1 per 1000. The same is true if we look only at female rape and sexual assault victimisation which dropped by 58 per cent from 1997 to 2013 in the USA.9 In Japan, where porn has infiltrated society as thoroughly as it has anywhere else, rape and sexual assault have plummeted.10 For complex questions, like the associations between porn incidence and sexual violence, single studies can only take us so far. But there is enough accumulated evidence now that it is possible for researchers to review the entire body of evidence. According to one such review: It has been found everywhere it was scientifically investigated that as pornography has increased in availability, sex crimes have either decreased or not increased.11

Interesting as the data might be, we do not know if the decreases in rape and sexual assault have been caused by the rise in pornography. A great many other things were happening worldwide, and within each 155

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society at the same time. But what we do know is that the porn-driven epidemic of sexual violence foretold by Dworkin and MacKinnon failed to eventuate. So unambiguously that another review of the evidence concludes that it is time to discard the hypothesis that pornography contributes to increased sexual assault behavior.12

Even if porn did not cause more sexual assault, perhaps it changed attitudes for the worse. Here the evidence is more equivocal. Men who regularly watch porn tend, on average, to express more callous attitudes toward women, less sympathy with victims of sexual violence, and less concern about child sexual abuse.13 These associations arise through men with antisocial personalities, with psychopathic or narcissistic tendencies, who were abused or delinquent children, who hold hostile views about women, who get aroused by wielding power over others, or who have deeply impersonal approaches to sex. That’s a long list, but it does not include the vast majority of men. When the men who do not fit on that list consume porn they do not tip toward violent and aggressive sexual attitudes.14 Associations between porn use and attitudes concerning violence rightly cause great concern, but we do not know what those heavy porn users would be doing if they didn’t have as much access to porn. One possibility, suggested by the rates of sexual assault, is that their pornography use might well divert them from real-world criminal behaviour. If the decline in sexual assault over the internet era has anything to do with porn, then the salutary effects of ‘pornification’ likely far outweigh the negative consequences. The debates over violent video games provide an interesting 156

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parallel. When gamers who play ‘first-person shooter’ games turn violent in real life, discussion fires up about banning or restricting those games. Such a discussion followed the 1999 killing of 12 students and a teacher at Columbine High School by Eric Harris and Dylan Klebold who, among other things, frequently played the first-person shooter games Doom and Quake. Likewise, when the Norwegian right-wing terrorist Anders Breivik described in court how he played Call of Duty: Modern Warfare to practice before the attacks in which he killed 69 people in 2011. Given the widespread popularity of violent video games, and the heartbreaking incidence of interpersonal violence, including mass shootings, a great deal of research has probed the relationship between games and violence. The results differ between studies, but on the whole, people who play a lot of violent video games tend to be more aggressive and more often involved in violence than people who don’t.15 The problem, as always with this kind of association study, is that those predisposed to aggression and violence might simply gravitate to those kinds of games. Economist Michael Ward showed that more violent adolescents are more likely to play violent video games, rather than the other way around. He then went on to show that the density of video game stores, a proxy for the amount of local game play, predicts local violent crime. Each new store that opened caused a local drop in violence, whereas the closure of a store caused a rise.16 To simplify a very complex issue, the time gamers spend shooting people in their virtual world is time diverted from violent thoughts, speech and action in the physical world. The same kind of effect happens in film. When cinemas show violent movies, crime briefly drops because the would-be perpetrators are sitting in the theatre watching crime on the big screen.17 Unfortunately, similar studies attempting to infer whether porn availability causes rates of sexual assault to change haven’t yielded such crisp results. In the USA, Todd Kendall found that as the internet 157

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became available, rape declined.18 In Norway, however, the arrival of broadband in one municipality resulted in higher rates of rape but no change in child sex abuse. In Germany, the roll-out of high-speed internet resulted in less child sex abuse but no change in rape or murder rates.19 In the end, despite evidence that watching porn changes attitudes, and that people who consume a lot of porn are, on average, more disposed to sexual violence, there remains no support for the claim that the availability of porn, society-wide, causes increases in sexual violence. The debate is unlikely to go away, however, because advocates and opponents of pornography have so much invested in their positions. We should expect the parallel discussions of gaming and pornography to merge as artificial intimacy gamifies VR sex and renders it ever more realistic.

A lower price of sex If porn contributed to the decline in rape and sexual assault, it is likely only one of many causes. Relaxed attitudes to porn and declines in sex-related violence are both part of a much bigger syndrome with more complex chains of cause and effect. As Brian McNair, professor of journalism and media studies at QUT in Brisbane argues, … societies in which sexually explicit materials circulate with relative ease are also likely to be societies in which there have been progressive changes in sexual politics and public attitudes … which in turn contribute to reductions in sex offences over time. The mainstreaming of homosexuality, the ascendancy of feminism, the heightened understanding by men in general of the damage done historically by patriarchal norms and structure – all have proceeded at the same time as pornographication and cultural sexualization.20

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The ‘cultural pornification’ of Western societies carried on the work of the sexual revolution, liberating sex from being a high-priced luxury good, heavily suppressed outside marriage. Porn contributes to the falling price of sex – both hetero and same-sex – by both meeting some of the demand and by raising supply – or at least the appearance of supply. On the demand side, a porn user can achieve some sexual gratification without the time-consuming and emotionally demanding business of dating. Sure, people might still want IRL sex and relationships with real people, but perhaps not quite as urgently. In this way, porn and masturbation provide what economists call a ‘low price substitute’ for sex. Large-scale economic data suggest that porn causes male demand for real sex with real women to plummet,21 contributing to the steady drop in heterosexual marriage rates since the 1970s. The stereotype of feckless young men watching porn in their parents’ basements rather than getting out into the world, getting jobs and courting women holds some water. Except it is not just young heterosexual men who live with their parents; porn saps the sexual motivation of a far broader group of men. One study that traced heterosexual women and men from 2006 to 2012 showed that porn users’ relationships were twice as likely to break up during the study.22 The effect on unmarried men was especially strong, and the more porn a man viewed, the more likely his relationship would break up. Overall, people, especially men, who use porn regularly seem to switch their focus from long-term partnering to pursuing short-term liaisons.23 The more limited evidence concerning porn use in homosexual and bisexual women and men also supports the ‘price of sex’ argument. Societies that adopt permissive attitudes to porn tended to become less tolerant of homophobic attitudes, and homosexuality grows more visible. Some studies suggest that a more recreational culture of sexuality, at least partly attributable to porn, creates opportunities for 159

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heterosexuals to take more relaxed and experimental approaches to same-sex contact.24 Porn exposure, over time, exaggerates a person’s perception of how sexually active the real people around them are.25 The easy sex and rampant sexual variety instantly visible from any connected device mould people’s impressions of how easy and varied their friends’ and neighbours’ sex lives are. Even competent adults who understand the difference between online and IRL can be left feeling like sex is everywhere other than around them. The mere perception that sex is everywhere can become reality, as people feel pressure to have sex earlier in a relationship, more often, and in a greater variety of ways, in order to hold a lover’s attention. This presents a particular and growing challenge for heterosexual women. The online abundance of nubile, attractive women who appear to be absolutely desperate for sex and willing to do almost anything a male viewer might fantasise about creates a false impression of abundant, easy heterosexual supply. That impression begins in the mind of the porn user, but it percolates through their interactions with women, shaping their expectations. As a result, relationships become sexual with less commitment and fewer strings attached. In short, society becomes more sexually permissive, further reinforcing the perception that sex is easy. Adults exposed to porn are more easygoing about sex and have more varied sex lives, but they enter long-term relationships more slowly and leave them more quickly.26 Some feminists argue that porn, by loosening the cultural suppression of sex, liberates women to express themselves freely, both in how they use their sexuality and in other ways. These so-called ‘sex-positive’ feminists, like journalist Ellen Willis, anthropologist Gayle Rubin, and sex educator Betty Dodson took dramatically different positions from the ‘anti-porn’ feminists. They also took different positions concerning sex work, sadomasochism, and the rights of transgender women. The 160

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disagreements polarised feminism in what came to be known as the ‘feminist sex wars’ or, simply, the ‘porn wars’. The rift between ‘sex-positive’ and ‘anti-porn’ – sometimes called ‘sex-negative’ – feminists can be understood in terms of the price of sex. Not that any of the protagonists would choose those terms. Indeed the very idea of sex as a transaction raises hackles, perhaps because the transactional aspects of sex sit at the heart of most problems with which feminism grapples. Viewed in terms of the price of sex, sex-positive feminists tend to support measures that ameliorate the harms caused by a high price of sex. For example, both sides recognise that porn, sex work and casual sex can open the door to coercion and male control of women’s sexuality. Anti-porn feminists look to shut that down and eliminate male coercion and control. They tack hard against sex work, which they persist in calling ‘prostitution’ despite sex workers’ objections. They appear to recognise that cheap sex in a sex-flooded world undercuts one of women’s few structural advantages: their bargaining power in sexual negotiations. Sex-positive feminists argue that an easier sexuality grants some women agency and power. They take a keener interest in working with sex workers rather than ‘saving’ them. And they point to the proliferation of well-paid porn actresses, flourishing independent sex workers, and happy, promiscuous women who benefit from controlling their own sexualised power. At the heart of the porn wars sits the fact that the interests of women are set in opposition by the very fact of mating market competition. Evolutionary ideas about within-sex competition and sexual conflict find it hard to cross the Last Wall to where they are most desperately needed. Just as no single set of circumstances favours all dunnocks, so no single ideological approach addresses the problems that most concern all women. The same is true for the conflicting interests of men, for the conflict between men’s and women’s interests, or for the interests of same-sex and opposite-sex attracted people. 161

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The evidence that has accumulated since Falwell and Dworkin found themselves fighting on the same side shows that the conservatives were right about the effect of porn on marriage, but wrong about social chaos, and obviously out to lunch on divine retribution. Taken together with the way Dworkin, McKinnon and those that followed got it wrong about sexual violence, the unlikely allies who were never really allies got their predictions about pornography far more wrong than right. And yet public discourse about porn remains as polarised as ever, largely impervious to the weighing of evidence. The same kinds of discussion reverberate around homosexuality and same-sex marriage, around sexual permissiveness in advertising and culture, about sex work, and about the legacy of the sexual revolution. The differences that animate these discussions spring from the ancient tension at the heart of every society over how relaxed or uptight to be about sex. Understanding all of these controversies as part of the same society-wide tussle over the ‘price of sex’ affords new insights into the history of gender relations.

The same old fight Societies have struggled with issues of permissiveness and reproductive autonomy throughout recorded history. Turn your watch back to the first flourishing of intensive agriculture in the Fertile Crescent and more likely than not you’d be standing on land that now forms part of Iraq. Here, in some of the earliest city-states, Mesopotamians wrote down their laws over 4000 years ago. The oldest surviving written laws, those of early Sumerian king Ur-Nammu (approximately 2100 BCE), reveal the antiquity of humanity’s obsession with regulating the supply of and demand for sex. 162

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Wherever and whenever the law punished sexual transgressions it enforced sexual double standards. Women bore penalties harsher than those borne by the men who loved, seduced or even raped them. Ur-Nammu’s Law Number 7, for example, prescribed the death penalty for married women who seduced other men, and no punishment at all for those men. Throughout the ancient civilisations of the Levant, according to Eric Berkowitz’s Sex and Punishment, Virtually nothing consumed ancient lawmakers more than female infidelity, and very few crimes were so severely punished … [And] The elementary sexual prohibitions of Sumerian kingdoms like Ur-Nammu evolved into the obsessively detailed rules of the Hebrews, which in turn became the foundation for the sex laws of the church and every Christian state.27

From ancient laws and religious texts we can infer that those who made the laws wanted to restrict sex, keep it within marriage, and establish men’s property rights over wives and daughters. Rape, seduction and sex with a married woman were considered not from the woman’s point of view, but rather as theft from her male owners. Ancient Roman society strained, much as our own societies do today, under the tension between permissiveness and prudishness. The high-status men whose thoughts and deeds history recorded obsessed over male virtus, the root of modern virtue, and female pudicitia, which best translates as somewhere between modesty and chastity. The Republic’s foundation myth concerned pudicitia on a heroic scale. Sextus Tarquinus, son of the despotic king, desired Lucretia, his cousin’s famously devoted wife. He blackmailed her by threatening to kill her and a slave and say he had caught them in flagrante delicto. Lucretia succumbed, not out of fear for her life, but to spare her husband shame. Afterward, Lucretia recounted these events to her husband and father, both of whom absolved her of blame. But Lucretia drew 163

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a dagger and proclaimed ‘I am innocent of fault, but I will take my punishment. Never shall Lucretia provide a precedent for unchaste women to escape what they deserve!’ before taking her own life. Lucretia’s relatives rallied support and overthrew the hated king. Thus was the Roman Republic established in 508 BCE in reaction to Lucretia’s self-righteous suicide. By the time Livy wrote his account some five centuries later, Lucretia’s role in the Republic’s birth had been mythologised by generations of politicians arguing that Rome’s survival depended on the modesty of their wives and daughters. More so on the vestal virgins, priestesses who vowed to remain chaste for their 30-year terms. Occasionally, crisis-hit politicians deflected blame by accusing a vestal of unchastity. The gruesome death meted out to both priestess and her lover ensured most vestals remained above reproach, with only ten convictions in the thousand years they tended Vesta’s eternal flame. Despite ancient Rome’s deeply patriarchal system of law, women exercised enough sexual licence to unsettle Rome’s powerful men. When young Roman elites flocked to the ecstatic, boozy, permissive rituals of the cult of Bacchus, the Senate felt threatened. Their heavy-handed crackdown in 186 BCE saw thousands of Romans executed or exiled.28 There existed no shortage of slaves, both female and male, with whom elite men could and did engage in what they considered mere copulation. But Roman marriage and parenting involved elaborate transfers of property, in dowries and inheritances, and the maintenance of lineages. And one can detect the hand of the mating market in how laws impacted not only on marriage and fidelity, but the everyday behaviour of Roman women. In 216 BCE, for example, after Hannibal vanquished Rome’s army at Cannae, many wives and daughters inherited the considerable wealth of fallen soldiers. The Senate passed the Oppian Law, restricting how much gold widows, single women and wards could own, ostensibly to set a near-bankrupt state back on an even keel. The Law also barred 164

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women from wearing clothes coloured with exorbitant purple dyes, and from riding in carriages. What had initially been sold as an economic austerity measure was primarily a restriction on women’s sexual autonomy. The loss of so many men at Cannae left many daughters fatherless and women husbandless, disrupting the mating market among Rome’s elites. Such an oversupply of women typically amps up competition for the attention of the remaining eligible men, lowering the price of sex. Women parading their inherited wealth, draped in finest purple, riding unaccompanied, and generally exerting their agency would have threatened the stability of existing marriages and undermined betrothals, throwing the highly political Roman marriage market into chaos. How different are contemporary societies from Rome, in this respect? Prudish and conservative approaches to sex universally seek to make women and sex less visible. Remember the unholy storm after Miley Cyrus twerked in a plastic bikini at the 2013 Video Music Awards? Vicious condemnation of hyper-sexualised pop stars – and independent young women who act and dress like them – reduces the appearance of how much sex is happening. The effect of limiting both real and apparent supply is to raise the price of sex, pushing norms back toward love-and-marriage and ‘true love waits’. The tension over sexual permissiveness and women’s autonomy can often be detected in complex historic events. The European witch craze which saw an estimated 110 000 people tried and 60 000 executed in Europe between about 1450 and 1650 provides a particularly lurid example. More than three-quarters of those persecuted for witchcraft were women, often older widows or women who troubled the stultifying roles they were expected to play. Sensational ideas about women’s sexual corruption animate accounts of European witchcraft, including shocking tales of ritual orgies in which witches had sex with one another and with demons. Graphic accounts of the occultish depravities of these ‘witches’ sabbaths’ fuelled the spread of the witch craze,29 165

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despite the complete absence of evidence that anything resembling such a ritual ever happened. Mediaeval witches, gay men during the AIDS panic, and Romans a little too fond of the Bacchanalia; all were persecuted for ostensibly different reasons. But just beneath the surface, it is easy to detect a conservative fear of unrestricted sexual supply. In the near future, as the technologies of artificial intimacy invade our lives, some will provide ‘low-price substitutes’ that meet demand for sex. Reactions to those technologies will take the same forms as the reactions of yesteryear. Cheaper sex will still irk social conservatives, who seem to draw prurient inspiration from the idea of pent-up male libido, of young men ever-ready for combat and determined to work hard in order to earn their stake in society by acquiring a wife and kids. And the price of sex will impact on women’s livelihoods and the way they are treated, drawing the attention of feminist and anti-feminist forces alike.

Undercutting the price of sex In the blink of an eye, inanimate sex dolls are about to be relegated to the basement by ever more lifelike robotic sex machines. Many of the concerns in the debate over sex robots, and the coming debate over VR sex, have been cut and pasted from the last half-century’s skirmishes over porn. The charges include indecency, undermining families, enabling paedophilia, modelling unhealthy gender relations, engendering sexual violence and objectifying women. There has, however, been very little discussion thus far about the mating market consequences of digital lovers. Robots that can simulate sex or fake a degree of intimacy may come with a hefty price tag, but some users evidently consider them good value for money compared with courtship and marriage. One does not need to extend marriage rights to robots for their presence to threaten marriage. It only takes manufacturers crowding into the market and competing to 166

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meet demand for some of the services exchanged within marriages. Time and again, from VCRs to flat-screen televisions to laptop computers, competition and improved manufacturing have turned technologies that began as luxuries into affordable mainstream items. If sex robots go the same way, they will provide a low-price substitute for both sex and intimacy. Not a perfect substitute, perhaps not even a very good substitute, but they will siphon off some of the demand. If manufacturers focus mostly on meeting the male demand for hetero sex, which certainly seems to be the main direction they are taking at the moment, then robots will further erode marriage rates and the proportion of people in committed relationships. The same is true as other digital lover technologies, notably the erotic forms of VR, go mainstream. In a market flooded with low-price substitutes, the price of sex will fall, thus intensifying heterosexual women’s competition with one another. That could mean women posting more sexualised images of themselves on social media,30 greater pressure to send nude pictures, and an intensified obsession with looks, weight, clothing and luxury accessories than we see in 2020. As with internet porn, digital lovers might diminish enthusiasm for committed monogamish relations. That will likely be tolerable to those who use digital lovers, and to those with secure employment and healthy incomes. For many people, particularly women, however, marriage has long paved the road toward upward social mobility. Reduced demand for long-term partners and spouses, especially from relatively well-off men who can afford digital lovers, could close that road down and worsen conditions for women. That will amplify political pressure to improve women’s job prospects, remuneration and social safety net. The quality of future societies will depend on how governments respond. The marriage-market downsides of a digital lover future could be offset by extending the price-lowering benefits of the sexual revolution. 167

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A more relaxed and less procreative attitude to sex will likely benefit people of all genders and sexualities, helping to dismantle prejudices and structural obstacles to equality. A less intense mating market might diminish men’s violence toward one another and toward women. Social progressives will likely recognise the benefits to poorer people, to women, and to sexual and gender minorities. Family-first social conservatives will see the breakdown of marriage and the withering of predictable gender roles as signs of society’s ultimate corruption. When Houston City Council voted recently to ban a sex robot brothel, they re-treaded the well-worn clerical grievance that permissiveness – in this case of sex with robots – would tear families apart.31 Expect social conservatives, especially the religious ones, to bundle sex robots in with the pill, abortion, same-sex marriage, music videos and permissive sexuality. They will attempt to shoehorn the whole damned lot into Back to the Future’s Delorean time machine and take us back to 1955.

Anthropomorphising robots, objectifying humans The radical feminist heirs of Dworkin and MacKinnon may well, again, find common cause with old-school religious conservatives as they try to run digital lovers out of town. The CASR’s Kathleen Richardson, a self-confessed fan of Dworkin and MacKinnon, is campaigning to ban sex robots by arguing that robots will worsen the ‘objectification and commodification’ of women. She bundles the nascent sex robot industry with the world’s oldest profession, which she and her allies would also like to bring to an end. As Richardson told Forbes magazine: ‘I’m anti-anything that turns human bodies into commercial objects for buying and selling’.32 Sex robots are demonstrably commercial objects, and most of them 168

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currently resemble human bodies. That does not, however, lead logically to Richardson’s favoured conclusion that the existence of sex robots turns human bodies into objects for buying and selling. Claims about objectification deserve a closer inspection. Breathless media reports alleged that attendees at the 2017 Ars Electronica Festival in Austria subjected sex robot Samantha to such rough treatment that it needed extensive repair. Commentators saw in the ‘damage’ to Samantha a foretelling of how sex robots will bring out the worst impulses of men. Unfortunately, when it comes to Samantha’s Austrian adventure, the facts seem not to have been allowed to interfere with a good story.33 The damage was no more than wear and tear. Festival attendees, invited to touch Samantha, did so as if it was a mere object. Not everyone saw Samantha as an object, however. Engineer Arran Lee Squire told British tabloid the Daily Star, ‘I think people have just become over-excited and treated her like a sex doll. She isn’t a sex doll, she is a robot with AI.’34 When chief engineer Sergi Santos asked the damaged robot, ‘How are you?’ and it replied, ‘Hi, I’m fine’, he was apparently quite relieved, telling journalists ‘Samantha can endure a lot, she will pull through’. If the engineers, who know better than anyone else what a robot is, speak in such human terms, then perhaps the blurred lines between human and object cannot be redefined. Sex robots attract such interest because of the chance that their AI personalities will trick us into anthropomorphism – projecting human behaviours, feelings and mental states onto them. We have seen throughout previous chapters how easily people anthropomorphise chatbots, from ELIZA to Alexa and even PC terminals. Whether the consequences of anthropomorphising sex robots, objects without interests of their own, impose costs on humans remains an open question. The question of whether sex robots and other digital lovers will change how users treat other human beings currently dominates discussion about the new technologies. Recall the Roxxxy True Companion dollbot has a ‘Young Yoko’ personality setting. Given reassurances 169

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from the company that the personality is ‘18+’, presumably Young Yoko emulates innocence, inexperience, and clunky stereotypes about being demure and submissive. In poor taste, perhaps, but not illegal. Some entrepreneurial souls make and market sex dolls to provide a safe outlet for fantasies that would be damaging and illegal if acted out upon other humans. For some years the Japanese company Trottla has made and sold sex dolls that look like children. Founder Shin Takagi, a self-confessed paedophile, argues that his dolls allow people like him to express their desires in an ethical way. Many countries ban their import. Paedophiles, hebephiles and ephebophiles – people who, respectively, express strong persistent sexual interest in prepubescent children, early pubescent children, or underage people who have completed puberty – seldom seek treatment. Some countries legally require therapists to report them. In Australia, therapists are required to report patients only if they admit to having harmed a child or accessing child pornography. Could sex robots become legitimate and useful therapeutic tools for such difficult-to-treat patients? Psychologists are already exploring a similar possibility using virtual reality animations in order to treat patients.35 Understandably, therapists tread delicately around the therapeutic value of ‘underage’ animations or dolls. The public are mostly far less cautious, unwilling to entertain the possibility of therapeutic childlike sex dolls, even if only in a clinical setting. They are far less likely, again, to support the idea of dolls and robots being available so that people can ‘express their desires’. What about other forms of sexual victimisation? Roxxxy’s Frigid Farah personality setting has been widely construed as a ‘rape setting’ that simulates and thus normalises sexual violence. Rapists and sex offenders commonly dehumanise their victims, seeing them as objects, less able to feel, to suffer, to have thoughts and dreams of their own.36 What will happen when robots, demonstrably non-human objects, are programmed to act coy, to resist, or even to fight back against their owners? Will this provide a victimless outlet that satiates dark 170

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urges, cutting rates of coercion and assault? Or will it allow potential offenders to discover their hidden dark urges, and embolden them in human–human interactions? Questions like these elicit strong responses. People certainly get upset to see robots apparently mistreated. A YouTube video of Boston Dynamics roboticists shoving and kicking ordinary, non-sexual robots to test their responses provoked outrage and a torrent of ‘dislike’ votes.37 Yet scholars of social robotics disagree on whether cruelty to robots is likely to promote cruelty to people.38 Some argue that just as callous treatment of animals is associated with callous treatment of people, so treatment of social robots might predict how people are treated.39 Other researchers question the parallel, pointing out that robots lack the sentience that makes harming animals problematic.40 For now, the Montréal Declaration for Responsible Development of Artificial Intelligence, a researcher-driven statement of intent, declares that new technologies should not ‘encourage cruel behaviour towards robots that take on the appearance of human beings or animals and act in a similar fashion’.41 Most experts I have consulted believe that ‘deviant’ sex robots, like those that resemble children or that are programmed to resist advances, can easily be controlled or eliminated by regulation. Yet groups like the Campaign Against Sex Robots remain rusted-on to their opposition to even the most vanilla visions of sex robots. According to CASR, creating non-human robots for human pleasure will result in the objectification and harm of other humans. We know that people objectify other people. We know that they do the opposite when they anthropomorphise machines. We just do not know yet whether, in anthropomorphising machines, people will become more inclined to objectify humans. That is a question too important to be left to intuition, or even to philosophical argument alone. It is, at least conceivably, answerable with scientific research. To grant that research social licence, and funding, would require great maturity of a society.

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Matchmaking online Fundamentalist conservatives and radical feminists share more than their concerns about pornography and digital lovers. They also seek to eliminate sex work. Again, Kathleen Richardson equates the buyingand-selling with turning people’s bodies into objects. Sex work does not necessarily turn a human body into a commercial object; it only does so to the extent that the person inhabiting the body has no agency in the decisions involved. Sex workers coerced into slavery, for example, have little agency to decide whether and when to work or not work. But sex work provides many women – and men – with far greater agency and opportunities to determine their own future than they would otherwise enjoy. Many people enter sex work willingly and strategically. The internet radically transformed both casual sex and sex work when websites like Craigslist Personals and backpage.com made it easy for individuals to hook up with others who share their sense of sexy. Sex workers advertised for clients, screened out dangerous punters, and shared warnings about harassment and violence. As a result, fewer sex workers had to travel to red-light districts, brothels and known sex worker beats where they might encounter exploitative management, predatory pimps, problematic clients or police harassment. Independent escorts and other sex workers embraced Instagram and Twitter, crafting and managing their unique brands and advertising. Social media also allowed sex workers to find one another, to benefit from one another’s experiences, and to share information about problem clients. In short, the internet made sex work both easier to manage and much safer.42 As a result, many women who would never have worked in a brothel or on the street became sex workers. The internet also opened a portal to new forms of sexual transaction, some of which blurred lines between personal and professional. Sites like seekingarrangement.com brought ‘Sugardaddy–Sugarbaby’ 172

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deals into the mainstream. Buyers and sellers, usually wealthy men and young women respectively, found it an easy way to establish mutually agreeable ‘arrangements’. Gifts, tuition fees, clothing and cash passed from one to the other, in exchange for company, dates and, often, sex. Carrotdating.com focused even more ruthlessly on the exchange; buyers and sellers named their prices for a date, a kiss, or a roll in the hay. There is nothing new about these kinds of relationships, but the internet made them easier to establish. The website matched people according to sellers’ asking price and what buyers would pay. By the time two users made contact they had at least some understanding of what they were getting into. Matchmaker artificial intimacies, powered by potent AI matching algorithms, hold the promise of ever more efficient ways for people to find one another. Artificial intimacy might deliver mutually beneficial arrangements of all kinds, safer and more discreet than ever before. Unfortunately, the internet is experiencing problems that might get in the way.

Many countries have laws to ensure that technologies like the telegraph and telephone exchanges operate neutrally, without favouring or discriminating against certain senders or receivers. The internet as we know it depends on that kind of neutrality. Countries like the USA have long favoured a strong kind of neutrality that renders internet service providers immune from liability if their users publish obscene or defamatory content. These laws, notably the 1996 Section 230 ‘safe harbour’ law, defined how the internet grew. Operators of online personals, classifieds, bulletin boards and content sharing sites have, as a result of net neutrality, provided their services without fear of being taken to court every time somebody on their 173

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platform says something untrue or offensive. And yet the safe harbour law, and similar laws in other countries, are in large part responsible for the round-the-clock torrents of online hate and abuse that empty into the internet’s heaving sea of verbal and pictorial flotsam. No surprises, then, that laws like Section 230 have loomed long and large in the sights of anti-porn and anti-sex-work forces. In 2018, crusaders scored their first major victory against an open, and openly erotic, internet. The US Congress passed the Fight Online Sex Trafficking Act (FOSTA), and the Senate passed SESTA, the Stop Enabling Sex Traffickers Act. These laws arose out of concern that sites like backpage. com were advertising the services of sex trafficking victims. Anti-prostitution activists like the psychologist Melissa Farley claim that sex trafficking is a fast-growing scourge, with many sex workers trafficked, and all coerced.43 Laws against online sex trafficking sound, to reasonable people and to US legislators alike, like one of those few developments that benefit almost everybody other than the criminals who traffic humans for sex work. Many sex workers, however, blame FOSTA-SESTA for ruining their businesses and endangering their lives. According to sex-work advocates, accounts of widespread trafficking are a Trojan horse for the elimination of all sex work, pornography, and the entire ‘sex industry’. Within days of FOSTA-SESTA passing, the FBI shut down many sites, including backpage.com and Craigslist Personals, on the mere suspicion that some advertisements might be for trafficked workers. Other sites pre-emptively shut down their personal services pages in order to avoid a similar fate. Escorts who depended on these services to operate their businesses and stay safe found themselves navigating much riskier circumstances. Indeed, sex workers took to social media and the op-ed pages to suggest that making sex work more perilous and less publicly prominent had been the main goal of the anti-trafficking crusade in the first place. Will FOSTA-SESTA result in a broader reversal of decades of net 174

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neutrality? Or will they simply drive the websites offshore? Perhaps smaller countries will become data safe-havens, exporting erotic bandwidth to jurisdictions with laws like FOSTA-SESTA. And bandwidth will become more valuable as virtual reality couples with erotica, using ever more imaginative sensory devices to close the loop between pornography and personal services.

The new – virtual – reality When it comes to producing low-cost substitutes for sex, technology is just warming up. Every concern about pornography, sex robots and sex work can be rolled up and bundled together when it comes to VR. Burgeoning bandwidths and ever-greater processing power now pipe virtual reality into our homes, much of it pornographic. Major porn producers are investing billions in VR production and developing the peripheral devices that consumers will literally plug themselves into, plug into themselves, or both. In this way, they hope to dominate a kind of porn that is already proving itself more immersive and arousing than 2D erotica.44 As virtual reality renders pornography into a truly immersive experience, and as artificial intelligence makes it interactive and responsive, expect more people to divert time, headspace, and money from their offline relationships into their virtual worlds. That will mean IRL relationships, and all that messy business of mutual give-and-take will occupy a smaller part of people’s lives. Virtual reality will also enhance interpersonal sex, opening up ever more distant frontiers for sex. As VR sex blossoms, the distance between people will be measured in bandwidth rather than kilometres. This is likely to be good for relationships where people live or spend time apart. And it will likely be even better for casual sex. With a whole world full of connected people to play with, and fast-proliferating opportunities 175

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for global sex work from the comfort of one’s own home, expect the amount of old-school unplugged sex to dwindle further. Cybersex already provides opportunities for freewheeling, easygoing sex. Those who do it stress that cybersex is definitely ‘real’ sex. It offers options of anonymity, frees participants from the constraints of their bodies and lives, and allows people to explore their fantasies.45 VR sex will offer all these benefits in spades. It will create unfettered opportunities to abandon the constraints of gender, sexuality and even the human form. That will likely loosen the suppression of women, of homosexuality and of kink. Social conservatives and anti-porn feminists won’t be happy about any of this. Conservatives will be threatened because sex robots, virtual reality and virtual sex work will further erode their rare-and-precious view of women’s sexuality. It will undermine the idea that two-person hetero sex is somehow more authentic than any other kind, and blur boundaries between woman and man, cis- and trans-gendered, gay and straight. All of these developments will trigger the social conservative reflex to restrict sex to limited family configurations and gender roles. Anti-porn campaigners and opponents of sex robots, who oppose what they consider the commodification of sex, will keep battling to restrict low-price substitutes for sex. Tomorrow’s moral panics over the technologies of artificial intimacy will almost certainly see organisations like Richardson’s Campaign Against Sex Robots doubling their efforts to eliminate digital lovers. When they do, they will once again be batting for the same side as the love-and-marriage social conservatives.

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Make war not love A surplus of unmet male demand for sex can cause large-scale societal problems.

They refer to him as ‘The Supreme Gentleman’, the first saint of their unlikely twenty-first century cult. On Reddit forums and YouTube videos they celebrate his deeds and subsequent martyrdom. To everyone other than his fans, however, Elliot Rodger cut an even more pathetic figure in death than he did in real life. The 22-year-old is remembered for what he did over a few frenzied hours on Friday 23 May 2014. As each of his roommates arrived home to their Isla Vista, California apartment, he stabbed them to death, hid their bodies under blankets, and waited for the next. Rodger then drove to a local Starbucks in the black BMW 328i coupé that his mother had bought him. There he uploaded a YouTube rant about his motives and his plans and headed onward, to the Alpha Phi sorority house at the University of California Santa Barbara, intent on slaughtering ‘the very girls who represent everything I hate in the female gender: The hottest sorority of UCSB’. When nobody at Alpha Phi opened the door, Rodger shot three women from another sorority who happened to be walking past. He then rampaged through Isla Vista in his Beamer, shooting several more people, and hitting some with his car. Altogether he killed six other people and injured 14. After twice exchanging gunfire with police, and

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crashing into parked cars, Rodger ended himself with a bullet in the head. Elliot Rodger’s violent desperation had brewed for years, a concoction of glaring social inadequacy and burgeoning sexual entitlement. Rodger clearly pinned his value as a human not only to sexual activity, but to the attractiveness of the women involved. Rodger blamed the women who had rejected him, and, by extension, all women, who, oblivious to his self-evident charms, persisted in dating and sleeping with other men. His response: to lash out at all women. The deluded killer presented an enigma. Desperate to shed his virginity, possessed of all the usual material signifiers of wealth and status, he proved entirely unable to make friends with even one woman. He had tried the elixirs prescribed by the ‘pickup artist’ community, finding them as useless as any snake oil. In death, his trail of videos, social media posts and a rambling manifesto titled ‘My Twisted World’ brought him the attention he could never command while he lived. Was Rodger a freak, or a common symptom of a world that hates women? Twitter users didn’t sit on the fence. Some commentators viewed Rodger’s actions as a symptom of pervasive misogyny that serves the interests of all men at the expense of all women. When this kind of analysis is applied to a man’s heinous acts, many men snap sharply into defensiveness. #NotAllMen first trended in the aftermath of Isla Vista. Men used it liberally to disown Elliot Rodger, other violent misogynists, and that seething dark matter whose gravity all citizens of the internet felt but that few could name: the ‘manosphere’. This part of the story is far from new: feminist analysis often asserts that all men, including ‘good’ men, benefit from the sexism, harassment, and even the rapes committed by a few men. Those benefits come at the expense of all women.1 Many men take exception to being painted as guilty of crimes that appal them by the mere association of sharing the same sex as the perpetrator. To those men it seems only fair to lay all the blame on the bad eggs. Hence #NotAllMen. 178

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Women everywhere encounter sexism, harassment and feelings of insecurity. The #NotAllMen abrogation found itself massively outgunned by the response: #YesAllWomen. Beneath the hashtags and 140-character assassinations, allegations and accusations, the Isla Vista killings became just the latest retelling of an ancient and infinitely repetitive misery, perpetrated and suffered by real people. Whenever such events happen, we are left confused and disoriented, struggling to pick apart the contributions of individuals from the culpability of the groups to which they belong. #YesAllWomen and #NotAllMen might have been coined in 2014, but the pain and confusion they channel is as old as time. A lot has happened since 2014, and not that much of it can be considered progress. Elliot Rodger became a cult figure in parts of the manosphere, and, unfortunately, emulated. Before Alek Minassian drove a rented van into a crowded Toronto sidewalk in 2018, killing ten and injuring another 14 people, he posted to Facebook: The InCel Rebellion has already begun! We will overthrow all the Chads and Stacys! All hail the supreme gentleman Elliot Rodger!

Minassian identified as an ‘InCel’, a portmanteau of ‘involuntary celibate’. Involuntary because, despite their fervent wish to become sexually active, it just never happened. While there remain involuntarily celibate people of all genders and demographic groups, the term InCel has, at least since Rodger and Minassian, become inextricable from angry young men. More than that, they are men who live in WEIRD places. Much of what we know about human behaviour comes from surveys of, and experiments performed on, people living in countries that are largely White, Educated, Industrialised, Rich and Democratic – hence WEIRD.2 Most people alive today are not WEIRD. More than that, people in WEIRD places tend to differ from people elsewhere in 179

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measures of perception, fairness, cooperation and reasoning. Behavioural scientists often remind one another not to infer generalities of human nature from studies performed in WEIRD places alone. It is tempting to assume that the InCel problem might be a WEIRD twenty-first century problem. But not all InCels live in WEIRD places, logging in from their parents’ dank basements to even darker corners of the internet, hating on ‘Chads’ – men who are having sex – and ‘Stacys’ – the women who date and sleep with the Chads. Unfortunately, angry young men, shut out of the mating market, have plagued societies since long before recorded history. Today, they also wreak violent havoc in non-WEIRD countries like Nigeria, China and India. It is possible that artificial intimacy will worsen the global InCel crisis, but it could also, with deft social engineering, help to relieve the crisis and make the world a better place.

The red pill Logging on to Reddit’s TheRedPill forum for the first time, it looks like something is broken. A yellow triangular sign with an exclamation mark followed by: Are you sure you want to view this community? It is dedicated to shocking or highly offensive content. Are you certain you want to continue?

Okay, I can’t say I wasn’t warned. TheRedPill describes itself as a ‘Discussion of sexual strategy in a culture increasingly lacking a positive identity for men’. Sounds alright. My scientific research concerns sexual strategy. And I’m a man with a teenage son and a teenage stepson. Of course I’m hoping not to see either of them here because I have come to TheRedPill to read the posts by InCels, reformed InCels, and Men 180

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Going Their Own Way (MGTOWs). I’m here to catch up on the state of the manosphere. One of the things you’ll notice about the ’sphere is that there aren’t many women. At least, if there are, we aren’t allowed to know. As TheRedPill’s Rule Number 10 states: ‘Do not announce that you are a woman’. Apparently ‘having a vagina does not afford your words special weight or wisdom, or give you any inside understanding of how men should deal with women’. The manosphere is filled with diverse voices. They range from mildly anti-feminist to savagely misogynist. When you take the Red Pill, like Neo in the classic 1999 sci-fi film The Matrix, you learn that you’ve been living inside a great big conspiratorial lie. In this case, a lie told by a contemporary feminist culture so hegemonic that, according to a post soon after the community’s 2012 founding, ‘A president cannot be elected today without succumbing to the feminist narrative and paying them tribute’.3 Notch up one more expectation shattered by the election of Donald J Trump. Once you take the Red Pill, you learn that ‘feminism is a sexual strategy’, one that positions women perfectly to take their pick of mates, switch mates when they want, fertilise their eggs with sperm from the genetically best-endowed men, and, always, use their feminine charms to garner resources. You can remain behind in the feminist-constructed ‘Blue Pill’ world, or you can sink the Red and learn the new and improved sexual strategy for men. The most unsettling thing for me, after reading far too many posts, is not the obvious pain of many authors and commenters, disoriented and lonely in a world they struggle to grasp. Nor is it the sensiblesounding advice exhorting men to take responsibility for their actions, to understand their world, and expend a bit more effort in all areas of their lives. Neither is it the crass misogyny of some posters. What unsettles me most is how many of the terms and concepts are familiar to me from my research. 181

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In particular, the manosphere seems to have a one-sided bromance with evolutionary psychology. My unease is not the eye-rolling of a left-leaning pro-feminist academic, resistant to evolutionary accounts of human behaviour and motivation. Not that I would be insulted if somebody called me left-leaning or pro-feminist. As a biologist who studies the evolution of behaviour in all manner of animals, I am obviously open to evolutionary explanations. I move among evolutionary psychologists, I publish in their journals and attend their conferences, and when colleagues or acquaintances diss evolutionary psychology without knowing what they are talking about, I take them to task. Evolutionary psychologists are at least as open-minded and curious as any other type of psychologist. Some are radical feminists, a great many are centre-left social democrats, some small-l liberals, more than a few libertarians, and yes, I do know some who are gun-toting right-wingers. That diversity is healthy. Science is better when the people practicing it capture more of the remarkable ethnic, linguistic, cultural and gender diversity that exists among the humans we seek to understand. Science is also better – albeit sometimes more interpersonally frustrating – if it involves politically diverse researchers. My disquiet concerns the way in which the manosphere cherrypicks concepts and factoids from evolutionary psychology in order to serve their own particular purposes. Unfortunately, as we have already seen, evolution is especially prone to the naturalistic fallacy of using observations about the living world to argue that one particular state of affairs is somehow ‘natural’. The manosphere holds a PhD in the naturalistic fallacy.

From alpha to whatever A manosphere obsession over ‘alphas’ and ‘betas’ provides a conspicuous example of sciencey cherrypicking. The InCel dilemma, at its most 182

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refined, concerns how to progress from being a ‘beta’ male, a nice guy who is ultimately invisible or unattractive to women, to being an ‘alpha’: dominant, high-status, and, above all else, sexually active. Consider the words of TheRedPill poster, Woujo: Insecurity creates a powerful evolutionary drive in betas to battle each other for status. In the absence of a clear alpha male to lay down the law, betas engage in heated, sometimes violent status wars.4

The notion of alpha and beta males comes from animal behaviour, where certain kinds of dominance hierarchy distinguish the top males from the others. Recall how an alpha dunnock cock will sometimes allow a beta male to share his territory and help him defend it from other males. Silverback gorillas are alphas, defending harems of females from sub-dominant beta males. Researchers studying behaviour in the field often signify the dominant male with the Greek letter _. A male who attains alpha status typically spends a brief tenure at the top, defending mates or a territory that contains mates. Eventually a stronger, fiercer, or luckier opponent manages to knock them off the top of the hierarchy. A displaced alpha male falls fast and far. Few ever recover. Scratch at the surface and the idea of alpha and beta men turns to tacky veneer. Human hierarchies take far more complex and layered forms than dunnock, gorilla or chimp hierarchies. Gender, class, caste, nobility, land ownership, occupation and wealth all shape human status, and they can influence reproductive competition. Those who rise high and stay there enjoy better mating prospects, and better conditions in which to raise children, than those at the bottom.5 And those children inherit at least some of their parents’ status. Despite their misguided obsession with alpha status, the manosphere is broadly on the money that status matters when it comes to 183

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sex. Sex provides an ultimate motive for men’s status-seeking, though often buried deep beneath conscious awareness. Men who achieve dominance or prestige attract more mates than do low-status men who have neither. While women also value other traits like kindness, the unfortunate truth for many low-status young men is that they are invisible to women. InCels are the twenty-first century’s invisible men, having never achieved the status that renders them visible. At least not to the kinds of women with whom they would like to partner. Their agony is somewhat relatable. Who among us, of any gender or sexuality, has never found themselves sitting at home at 10.15 on a Saturday night, waiting for the telephone to ring, wondering whether this is as good as it gets, whether we will ever know companionship or intimacy? In time, of course, things can always get better. One can draw some comfort from the fact that even though every generation that ever existed had its share of involuntarily celibate men and women, nobody alive today descends from a lifelong celibate. Not a single one. Every one of our ancestors mated at least once, conceived at least once, and raised – or somebody else raised on their behalf – a child. Even though many of our ancestors suffered the existential pessimism of the InCel during their youth, they all got over it. The genes that helped our ancestors escape becoming lifelong members of Club InCel are among the genes those ancestors passed on to us. Those genes underpin a hair-trigger sensitivity to warning signs that a person is in the InCel danger zone. They generate a fierce desperation to get out. None of this is ‘hard-wired’ or determined – it is very much responsive to the environment. Being male presents the single greatest risk factor for becoming an InCel. While every baby has exactly one genetic father and one mother, population genetic analyses reveal we each have more – perhaps even twice as many – unique individual female ancestors as male ancestors.6 How could that work? While sex ratios are roughly even at birth, female 184

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infants have been more likely than male ones to grow up and have children. In nearly every generation, more boys and young men succumbed to illness and violent deaths than their sisters did. Large chunks of most male cohorts perished in warfare. And among those who lived long enough, many remained InCel, unable to secure the status or the livelihood to attract even a single mate. Not all men are high-risk for involuntary celibacy. In the middle part of the distribution, where most men – and most women – reside, there are plenty of potential mates for both sexes.7 But being young and poor amplifies a man’s risk of involuntary celibacy. As a result of this risk, evolution fashioned a particular psychology so distinctive that it has a name: ‘young male syndrome’.8 Young men, especially poor young men, are notoriously willing to discount the future. They risk accidents, violence and death in order to rise in status, obtain money and stand a chance of attracting a mate. This isn’t just an obnoxious side-effect of celibacy, immediately cured for life – as if in a Hollywood coming-ofage comedy – by getting laid. Men walk a precarious path, ever at risk of sliding back down the slope toward involuntary celibacy. The relentless striving to avoid involuntary celibacy forms a core ingredient in masculinity, but too much of the ingredient can be toxic. Accidents and violence kill many young men and injure or damage a great many others.9 Those who fall foul of the system spend years in prison. Men, throughout history, went to sea, travelled to the colonies or marched to war in the hope of escaping an InCel fate. Many never returned. A boy born into privation needs extraordinary will, combined with luck, to claw his way out and offer a mate something worthwhile. Along the way he must take vast risks, fighting past all the other young men trying to climb the same status ladder. Among those young men who make their way up the ladder we occasionally glimpse one who clambered to mega-success. Consider Ronaldo Luís Nazário de Lima. Born in one of Rio de Janiero’s direst favelas, young Ronaldo showed obvious 185

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talent for football, but his family was so poor that when the famous Flamengo sports club invited him to try out, he could not afford the bus fare. With some luck, he later signed with Cruzeiro in the nearby city of Belo Horizonte and helped them win their first Brazil Championship in 1993. The next year he played his first game for Brazil at the age of 17. By the time he retired in 2011, Ronaldo – nicknamed O fenômeno – had played 98 games for Brazil, scoring 62 goals and winning two World Cups. He also married or had long-term relationships with several prominent sportswomen, actresses and models, siring children by three of them. Few footballers have achieved as much as Ronaldo. Among those who have, many, like Pelé and Maradonna, were born into similarly dire prospects. And football presents just one avenue for rapid social mobility. Men like Muhammad Ali, Lee Trevino, Jay-Z, Chuck Berry and Keith Richards charted similar courses from rags to riches. But the desperate attempts of young men born to privation have a much more sinister side, too. For every Ronaldo or Keith Richards who lives to enjoy his success, hundreds, perhaps thousands of young men die, permanently damage themselves, or enter into long-term association with the criminal justice system. Beneath every 50 Cent who survives and gets rich, lurks an iceberg of young men who die trying. Not only were your ancestors – and mine – not the InCels of their respective generations, a few had phenomenal numbers of children. The flip-side of men’s greater chance of incelibacy is that the ancestors who had lots of children were more likely to be men. Occasionally, population genetics gives us a glimpse of the legacy these super-ancestors left. Little more than 800 years ago, somewhere on the frigid steppes of northern Mongolia, a small but distinctive change happened in an unimportant part of one man’s genome. The Y chromosome carries little more than the genetic signal to turn an embryo into a male; without it, the eventual baby will be a girl. The mutation did not affect the genetic signal’s ability to do that job. Like a spelling mistake that does 186

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not change the pronunciation of a surname, inherited and passed on by the sons of a father who misspelled his name, the new mutation from Mongolia was passed from father to son, to son, and so on. Despite the fact that it has no known effect on the bodies of the boys and men who inherit it, the mutation spread like a dry-season bushfire. It seems to have got lucky, hitching a ride with something that made many generations of men absolutely phenomenal at reproduction. A likely scenario is that one of those early sons who inherited that mutation was a boy named Temujin. A boy who battled through childhood privation and enslavement, but survived and grew up to become a fierce warrior-chieftain, unite the Mongols, and establish the largest contiguous empire in human history. Most people today know Temujin as Genghis Khan. The little mutation he carried spread across Asia at much the same speed and time as his Mongol Empire.10 Genghis Khan passed that mutation to his several legitimate and many illegitimate sons, and they to their sons in turn. Although Khan stands out among great conquerors for his humane constraint, he is alleged to have relished taking ‘to his bosom’ the wives and daughters of those he conquered. His male descendants certainly did, and many perfected the business of tending a harem. Much of the success of the Mongol Empire came from its integration with the people they conquered, including by marrying sons to daughters of prominent families.11 As a result of all these factors, eight per cent of all men living today within the empire’s historic boundaries, and one in 200 of all men currently living in the world, have the mutation, suggesting they descend in an unbroken male lineage from the Great Khan himself. That factoid doesn’t even touch on the currently untraced genes on the other chromosomes that passed, at some point, through Khan’s female descendants. Chances are that the majority of people alive today have quite a lot of Genghis Khan in them. The Mongol Empire eventually faded, but Genghis Khan’s genetic dynasty flourishes to this day. While spectacular, Khan’s is far from an 187

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isolated case. Throughout history, men of great wealth and power often had more children than they could easily name. Rameses II of Egypt (1279–13 BCE) sired 162 documented children, King Sobhuza II of Swaziland (1899–1982) had 210 children, and the wealthy Saudi businessman Mohammed bin Awad bin Laden (1908–67) had 22 wives and at least 54 children, of whom Osama was the seventeenth son. The secret to establishing a true genetic dynasty was power. Sometimes this came through wealth, sometimes through conquest, and sometimes through a claim to being the emissary of a god.12 Reliable methods of birth control dulled the connection between sex and reproductive success, but we can still see the fossilised signs of the links between power, wealth, and sexual bounty in the pages of the gossip magazines. Tiger Woods, Gene Simmons, Warren Beatty, Russell Brand and Fidel Castro all found in fame and power an effective way of filling the unforgiving minute with commitment-free sexual variety. More than that, however, the MeToo movement has shown just how often rich and powerful men use their resources to coerce or pressure unwilling women in the service of Khan-like sexual ambition.

Three routes to InCel insurrection The desperation with which men strive to avoid involuntary celibacy or to emulate the Great Khan’s genetic legacy depends on the local mating market conditions, including the ratio of women to men, whether the society allows polygynous marriage, and economic inequality. All three of these factors affect the number of InCels in a society and the dangerous things that they do.

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Polygynous marriage Most historic and traditional societies – around 85 per cent – allow some men to take more than one wife.13 In these societies most married men have only one wife, a few have two, even fewer three, and so forth. Every time a man takes an extra wife, another man, probably young and poor, is rendered unable ever to find one. By marrying 22 wives, Mohammed bin Awad bin Laden effectively rendered 21 other men unmarriageable. When men can marry polygynously, they literally push up the price of sex. The surplus of unmarried men creates such intense sexual competition that they resort to purchasing brides. In many societies in Africa, the Middle East, South-East Asia and Melanesia, marriage entails a transfer of assets from the groom or his family to the bride’s family. This bride price can be modest, as with Namibia’s Himba pastoralists, but it often runs to many times the annual salary of an average young man. Political scientists Valerie Hudson and Hilary Matfess characterise bride price as ‘an obligatory tax on young men, payable to older men’.14 A man must pay bride price in order to buy that stake in society that married men enjoy. It is no accident of history that the places where bride price customs prevail are also the places where men only gain legitimacy and status once they are married, and where the more wives one has, the higher one’s status. When high bride prices make marriage an impossible hurdle for even average young men, crime, radicalisation and violence follow close behind. According to Hudson and Matfess, bride price inflation contributed to the recent conflict in South Sudan, the Boko Haram insurgency in northern Nigeria, and the recruitment of young men to participate in the 2008 terror attack on Mumbai’s Taj Mahal Palace Hotel. In South Sudan, a long history of cattle raiding between the Dinka and

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Nuer ethnic groups exploded into a civil war that killed tens of thousands and displaced millions of South Sudanese. Out-of-control bride price inflation was at least partly to blame. Whereas not long ago, a man could negotiate to marry a woman for the price of 12 cows, in a few short years this rose to 50 cows, plus 60 goats and the equivalent of $US12 000 in cash. The incentive to steal livestock went through the roof, as did the reasons to defend one’s herds and to punish raiders. Boko Haram gained international notoriety when they abducted 276 schoolgirls from the town of Chibok in 2014. They had already been operating for over ten years, recruiting young men unable to enter the mating market as a result of local economic changes. By providing access to new forms of employment, and promising wives, Boko Haram struck recruiting gold. To deliver on the promise of wives, they abducted girls from villages like Chibok, leaving a token amount, roughly $US25 to $US50 on the ground in nominal bride-price payment. In addition to the immense human cost suffered by the abducted girls, the Boko Haram insurgency has caused untold economic damage, cost tens of thousands of lives, and displaced millions of people. It is merely one local expression of the violence and instability that results from polygyny. Letting the richest and most powerful men marry several wives leads directly to fighting among men, and the formation of gangs, militias, and insurgencies that pit groups against one another and against the state.

Too many men When men substantially outnumber women, even if every woman who wants a husband finds one a large number of surplus men will remain, unable ever to find a mate. Just as happens with polygyny, a male surplus equates to male demand exceeding female supply, and thus to more intense competition among men for the few available mates. That competition steepens men’s incentives to strive for status and respect.15 190

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In both China and north-west India, historic preferences for sons over daughters, combined with modern access to ultrasound sexdetermination and safe abortion, left surpluses of millions of young men. For scale and impact, China’s guang gun, or bare branches, young men with no prospect of bearing fruit for the family tree, put western InCels in the shade. Currently, an estimated surplus of 20 million young Chinese men of reproductive age exert surprising pressure on Chinese society.16 Columbia University economist Lena Edlund estimates that for every one per cent increase in the sex ratio (say from 107 to 108 boys per 100 girls) in current-day China, rates of violent and property crime rise by three per cent. In some places, sex ratios exceed 150 boys per 100 girls at birth.17 Male-biased sex ratios, like polygynous marriage customs, lead on to violent conflict between groups. Young men with poor mating prospects gravitate toward gangs and coalitions, inclined to fight one another. They are also more vulnerable to radicalisation or to being used by radical groups.18 With so many men to choose from, young women enjoy excellent mating prospects. When young people migrate to the cities to find work, the women can often marry into a wealthier family. Male migrants often drift back to their rural homes, resulting in rural villages that overflow with poor, uneducated men, unable ever to marry. Many fall prey to depression, low self-esteem, aggression and suicide.19 China’s surplus of men has imposed a massive mental health crisis that will haunt it for at least another generation.

Inequality Income inequality exerts similar effects to polygyny and male-biased sex ratios. Economists have long known that inequality creates incentives to strive. Strive for what? The reproductive consequences of inequality are often airbrushed out of economic analyses.20 People want 191

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wealth and status, but why? And what do they do with it once they attain it? The effects of that wealth and status on sex provide the missing link between inequality and its toxic effects on societies. For a woman who is interested in men, the level of inequality around her can change how she approaches dating and mating. In low inequality conditions, wealth differences between men are small, and so women can afford to weigh other considerations like a man’s agreeableness, tenderness and physical attractiveness. When inequalities are high, however, women do better by seeking one of the scarce high-status men and paying less attention to the other stuff. Women, as a result, spend longer searching for a partner, rather than settling, due to the benefits of marrying a relatively wealthy man.21 A recent study out of my lab shows how inequality changes women’s dating and mating incentives.22 My brilliant friend and colleague Dr Khandis Blake realised that the torrent of social media content posted around the world every day presents rich data on which to test ideas about the economic and cultural forces that shape behaviour. She was especially interested in why women post ‘sexy selfies’ of themselves primping and preening, often wearing scant clothing. We predicted, based on the research on self-sexualisation, that women would post more sexy selfies when they are at a bigger disadvantage, earning less than men and less able to obtain the same economic, political and employment rights. They would be making the best of a bad situation, leveraging their looks when perhaps their labour and their ingenuity isn’t as highly valued as men’s. In addition to measures of gender inequity we also considered sex ratios and income inequality between rich and poor, because of the potent incentives they create. Khandis captured vast numbers of tweets and Instagram posts, and developed sophisticated methods to geolocate where they were posted from. After months of development, the statistical tests on almost 70 000 posts to Instagram and Twitter were ready to run. To our surprise, differences between towns, or between countries, in gender inequity 192

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exerted few consistent effects on sexy selfie posting rates. Instead, the social media traffic from places of high income inequality contains a richer vein of self-sexualised pictures than the traffic from low inequality places. High income inequality raises the incentive for women to put themselves out there in sexy selfies. When the differences between haves and have-nots grow large, women self-sexualise in order to maximise their chances of becoming ‘haves’. One way to win, the ‘Kardashian route’, is to turn one’s self-sexualised looks into economic gains the way Kim Kardashian used her selfie skills to build her phenomenal business empire. Another route is to catch the eye of a wealthy man and achieve upward mobility as his partner. In either case, selfie-posting women aren’t passively doing what the patriarchy forces them to do. Rather, they are strategic agents deliberately seeking to improve their situation. As Khandis puts it: When you’re seeing sexy selfies, what you’re seeing is someone engaging in a behaviour where if it pays off and they do attract that man at the top of the hierarchy, they are going to reap extraordinary benefits.23

When wealth differences between men become large, women can sometimes enjoy better material circumstances and higher status as the second or subsequent wife of a wealthy man than as the only wife of a man of more modest means.24 In a similar vein, even when polygynous marriages are illegal, some women can do better as a mistress of a married wealthy man than as a wife of an ordinary man. Inequality can drive both legal and de facto polygyny. If there’s one thing better for your evolutionary fitness than pairing up with a wealthy and powerful man, it is being such a man. Wealthy men, from Henry VIII to Leonardo di Caprio, seem to have an almost effortless ability to recover from the grief of divorce, separation and, in 193

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Henry’s case, a wife’s execution.25 They enthusiastically re-pair with relatively younger women. Women and poorer men, make no mistake, are capable of monogamising serially. But wealthy men enjoy richer opportunities to do so. Via all these routes, economic inequality generates sexual inequality among men. That dials up the incentives for men to strive for wealth and status. It also renders the poorest and least educated men invisible, or at least undesirable, to women. The greater the degree of economic inequality in a society, the higher the proportion of these ‘invisible’ and unmarriageable men, most of whom come from the poor end of the economic spectrum. Striving to become visible and to present themselves as attractive, poor young men in high-inequality societies take the most extreme risks. Taking epic risks like train-surfing or driving fast can get people talking and make a man visible, however briefly. Turning to robbery can bring in enough money to set a young man above his peers on the straight-and-narrow. Being quick to anger and first in to any fight can establish a man’s reputation as a reliable ally and somebody not to be messed with. In that kind of testosterone-addled climate, even a trivial slight can erupt into violence, occasionally leading to injury or incidental death in a pyroclastic flow of man-on-man assaults set off as aftershocks of income inequality.26 Men near the bottom of the deck, with few prospects of improving the hand they have been dealt, become especially vulnerable to depression, anxiety, low self-esteem and substance abuse. Decades of research reveal that homicide, interpersonal violence, property crime, risky driving, daredevilry, alcoholism, drug use and gambling all increase with income inequality.27 Moreover, all of these sources of internal conflict leaden the saddlebags of a society. The social dysfunction that economists and social scientists often note in highly unequal societies comes about, in large part, because of the furious, frantic striving for attention, economic mobility, and, ultimately, sex. 194

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InCels deserve a moment’s attention Involuntarily celibate men have long disturbed the peace, just as they presently do in China, Nigeria and South Sudan. In WEIRD places, many commentators succumb to the temptation to sneer at the entitlement and self-absorption of InCel poster-children like Elliot Rodger and Alek Minassian. WEIRD InCels, however, constitute more than a few misguided souls. They represent a force that societies ignore at their peril. WEIRD InCels vote, they can organise, and they occasionally lash out against Stacys and Chads, against immigrants and people of other religions, and against society in general. Those commentators who consider InCel violence a form of terrorism don’t merely do so for effect. As Zoe Williams wrote in The Guardian after Alek Minassian’s rampage through Toronto, we need to bear in mind what modern terrorism is: ‘the perpetrators don’t have to meet and their balaclavas don’t have to match. All they have to do is establish their hate figures and be consistent.’28 Why are WEIRD societies only grappling now, in the wake of Isla Vista and Toronto, with the InCel problem? For one thing, the explicitly InCel terrorists are part of, and often cited as inspiration for, a rising tide of white male extremism. Analyses of the Global Terrorism Database published by The New York Times shows what many have long suspected: white extremists are responsible for an increasing share of global terrorism.29 According to Georgetown University law professor and a former national security official at the US Justice Department, Mary McCord,30 ‘In the US, more people are killed by far-right extremists than by those who are adherents to Islamist extremism’.31 Far-right terrorists who perpetrate racial violence like the March 2019 massacre of 51 people at two mosques in Christchurch, New Zealand, often admiringly cross-reference InCels like Rodger and Minassian. Indeed, concerns about race among white extremists often belie resentment at immigrants or people of colour ‘taking’ jobs and/or women. The 195

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rising InCel tide in places like the USA is driven by economic changes that make it harder for white American men who aspire to heterosexual relations to find a mate. In the USA, high inequality before World War II (the Gini index of inequality was around 0.43) gave way to lower inequality (~ 0.36) by the middle of the love-and-marriage 1950s. Around 94 per cent of men, but only 33 per cent of women were in paid employment, and women who worked full time earned only about 60 per cent of what men earned.32 The result meant that not only were differences in earnings among men relatively small (low among-men inequality), but the differences between women and men were large (low women’s employment and wages). Little wonder, then, that today’s WEIRD InCels and social conservatives look back on the 1950s with such fondness. A young man looking to attract a wife had only to find a job – any job – to present himself as an economic catch. This was particularly true for white men who enjoyed higher employment rates and average wages than other men. Income inequality rose slowly until about 1970, whereafter it took off. By 2014 it reached 0.48, among the highest values for industrialised nations and well above pre-war levels.33 High inequality shrinks the pool of men that women consider suitable. That pool shrinks even more when women’s earnings grow, or when men’s average earnings stagnate or shrink. The result is that fewer men bring something economically worthwhile to a partnership. Some women, unable to make a match they consider worth their effort, end up going their own way and raising a family solo.34 An estimated seven to 18 per cent of the dramatic post-1970 decline in marriage rates, and the rise in age at first marriage, can be attributed directly to rising income inequality.35 An analysis of over 73 000 couples in the 1990 to 2004 US Census data, by economists Marianne Bertrand, Emir Kamenica and Jessica Pan showed that in most heterosexual married couples, the husband earns more than his wife. Not just because men earn more, on average, 196

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than women, but because when a woman earns more than a man, even if all the other signs are good, they are less likely to form a relationship. If they do get together, and then her income grows bigger than his, she is likely to stop work or cut back on her hours. Wives who persist in earning more than their husbands end up compensating by spending even more time on household chores and caring roles. These couples report less satisfying marriages and are more likely to divorce.36 Since the sexual revolution, women’s improving economic opportunities and progress toward more equitable pay have delivered great benefits for women, for the economy and for many areas of society. But, with gender norms proving stubbornly persistent, they added complications, especially for successful women. The sexual revolution worsened the marriage prospects of lowerstatus men. The emerging InCel crisis in the industrialised West grew out of rising income inequality and shrinking gender gaps. Over the last three decades, globalisation rendered countries like China more competitive at manufacturing than countries like America. The US jobs lost to Chinese manufacturing had mostly been occupied by men, so men’s earnings shrank relative to women’s. Economists David Autor and David Dorn analysed the social changes between 1990 and 2015 when US manufacturing jobs were lost due to international competition. They found that loss of manufacturing jobs caused a drop in marriage rates and a rise in rates of single parenting.37 Online activity reinforces this view of the forces shaping InCel rage. Khandis Blake and I, working with information scientist Daniel Russo-Batterham, studied Twitter activity between 2012 and 2018 in the mainland USA. Places where people tweet about InCels, or use words that are peculiar to InCels, tend to be places where economic inequality is high, sex ratios among 18–39-year-olds are male-biased, smaller proportions of women are single, and where the gender gap between how much the median man and the median woman earns are smaller.38 The manosphere may look like an online miasma, divorced 197

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from the limits of geography, but the places where men’s mating prospects look dimmest are the places where the InCels live and post. Talking about rage-tweeting, protectionist anger fuelled by manufacturing job losses helped put Donald Trump in the White House and spur his ‘trade war’ with China. Trump’s 2016 victory was part of a longer-running change in American politics in which electorates that lose jobs to foreign trade have polarised. Economic analyses by Autor, Dorn and their colleagues, show that congressional districts exposed to big import trade shocks have, since at least 2002, tended to remove moderates from office.39 White-dominated districts became more likely to elect conservative Republicans, and districts with fewer white voters elected more liberal Democrats. In presidential races, counties exposed to trade shocks shifted toward the Republican candidate. Most interesting of all, however, trade shocks that affected white men resulted in the most dramatic swing toward conservative politicians. This is the precise concoction of electoral circumstances that propelled Trump to victory: white men whose longstanding economic advantages over women and racial minorities have withered due to foreign economic competition. The broader effects of manufacturing losses on mating markets should not be ignored. Where once a white American heterosexual man stood a great chance of marrying well if he simply had a job, that advantage has shrunk. Even though white men still enjoy considerable advantages and privileges, the scale of those benefits diminished over recent decades. Men who grew up feeling entitled to good jobs and attractive wives now find that those birthrights evaporated as men from other groups battled their way up the economic ladder, and as many women earned their financial independence. Left unaddressed, that leaves a roiling magma chamber of impotent male anger that releases the noxious gases of InCel misogyny and occasionally erupts in InCel violence or at the ballot box. It remains to be seen whether artificial intimacy will relieve the pressure or amplify it. 198

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A Fembot army to disarm the InCel insurrection Artificial intimacy could defuse InCel anger and dilute the more toxic expressions of masculinity. It could also make things worse.

In 1810, the French Empire reached its greatest extent. The oncemighty Austrians had gone from presiding over the 800-year-old Holy Roman Empire to controlling a quarter of the territory they held in 1793. Former Holy Roman Emperor, Francis II, had been downgraded to Emperor Francis I of Austria, and he and his Austrian subjects feared Napoleon would soon finish them off entirely. Napoleon knew he would soon have to deal with Russia, but he needed to know that Austria would not attack France. Sensing the prospect of a Franco–Austrian alliance, Austrian Foreign Minister Prince Klemens von Metternich, dangled the enticing prospect of Europe’s most eligible bride, Francis’ daughter Archduchess Marie-Louise. With breathtaking speed, Napoleon annulled his childless marriage to Josephine, and married Marie-Louise who soon bore him the son and heir he desperately wanted. In the frantic diplomacy of 1810, Napoleon infamously wrote to von Metternich ‘You cannot stop me. I spend 30 000 men a month.’1 In addition to tactical genius, formidable organisational skills, and relentless attention to detail, Bonaparte had built the most formidable 199

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fighting machine in Europe on the back of vast troop numbers. French conscription laws put more men at Napoleon’s disposal than rival armies could dream of. Between 1804 and 1813, his armies conscripted 2.4 million troops. War in the early nineteenth century, as it had been since the dawn of human conflict, was overwhelmingly a numbers game. Hannibal’s defeat of Rome at Cannae (BCE 216), Henry V’s thumping of the French at Agincourt (1485) and the English defence of Rorke’s Drift against Dabulamanzi’s Zulu forces (1879) are valorised by military buffs because the outnumbered side prevailed. Indeed, Napoleon’s victory at Austerlitz in 1805 is considered his greatest because, by his tactical genius, 68 000 French troops routed a combined Austrian and Russian force estimated at 84 000–95 000. For the main part, however, superior numbers of fighting men led to victories in most battles and almost all wars. I say ‘fighting men’ because even though women have suffered, as civilians and occasionally combatants in every war, the vast majority of casualties and deaths have always been men. Napoleon’s callous boast of ‘spending’ men captures the fact that throughout history, cohorts of young men proved most useful to their societies in the sacrifice of their lives. Sending regiments of young men to channel their belligerent impulses upon an enemy tended to forestall or relieve the InCel problem. That is no longer considered humanely or politically feasible. Compare the 340 000 French forces who lost their lives in the second half of 1812 during Napoleon’s disastrous Russian campaign2 with the 6879 US military deaths in the Iraq and Afghanistan conflicts over 18 years from 2002 to 2020,3 a figure considered unacceptably high by many Americans. Most people today, accustomed to the relative peace of the twenty-first century,4 would like to keep military losses as low as possible.

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Making monogamy great again Could social engineering provide peaceful solutions to the InCel problem? Promoting monogamous marriage norms and laws has helped in the past. Indeed, eliminating legal polygyny presents one of the most successful steps societies have ever taken to ensure peace, productivity and prosperity.5 Male monarchs and wealthy elites in early agricultural civilisations turned their new-found wealth and power into reproductive opportunities, marrying multiple wives and keeping harems. In time, however, their reproductive despotism created InCel problems that imposed palpable costs on the societies they led. They faced a choice: take fewer wives and mistresses, or suffer deepening societal dysfunction and risk insurrection.6 Legally entrenching monogamous marriage reduced the number of poor young men frozen out of any prospect of marriage. It halted bride price inflation and hosed down incendiary competition among men. As a result, young men’s risky, antisocial behaviour, violent confrontation, substance abuse and property crime declined, to everybody’s benefit. On top of that, capping men’s options for polygyny also limits their numbers of children. Fathers give those children a better upbringing than they could have provided for a larger brood from more wives. The hard work of being a father – of caring for and being involved in the lives of children and their mothers – gets spread among more men, with salutary consequences for the children and their mothers. These improvements arise because they limit men’s reproductive inequality, but they benefit the economy, too. Stability begets trust, which engenders commerce and thus stimulates economic growth. All of the positive effects – internal peace, human capital, economic growth – began to show up neighbouring societies, burdened by the polygynous lead in their saddlebags. The neighbours had to adopt the

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strange new custom of limiting how many wives a big man could have, or suffer the consequences. Since the sexual revolution, a decline in lifelong monogamous marriage may have contributed to the current WEIRD InCel problem. The InCels certainly think so. They argue that laws restricting sex to lifelong monogamous marriage would protect them from sexual competition by attractive, wealthy, high-status Chads. In effect, as maverick economist Robin Hanson puts it, InCels seek sexual redistribution.7 Clinical psychologist Jordan B Peterson, considered somewhere between prophet and messiah in the manosphere, has weighed in with characteristically pithy prescriptions about sexual redistribution. Frustrated men tend to become dangerous, particularly if they are young. The dangerousness of frustrated young men (even if that frustration stems from their own incompetence) has to be regulated socially. The manifold social conventions tilting most societies toward monogamy constitute such regulation.8

Comparing sexual inequality with economic inequality and agitating for redistribution proves a political rarity: astronomically unpopular on both sides of the political divide. On the left, the idea of sexual redistribution is considered repellent. When Robin Hanson pointed out ‘similarities between (financial and sexual inequality), including that some people have been willing to do and threaten violence to advocate for more of each kind of redistribution’, he was roasted as an apologist for male entitlement, gender violence and rape. Jordan Weissmann, writing in Slate, called Hanson ‘America’s creepiest economist’.9 And yet many on the political left remain unabashedly in favour of economic redistribution. From the right, sexual redistribution – through stricter marriage laws – is more popular, but economic redistribution less so than it is on the political left. Indeed a distinct libertarian flavour permeates the 202

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manosphere’s economic views, even as their calls for capping sexual inequality defy every libertarian sensibility. And yet economic redistribution presents perhaps the single most effective tool with which to cap sexual inequality among men, and thus to ease the number of InCels. Social conservatives might claim vindication, that restricting sex and confining it to matrimony could extinguish InCel rage and make societies more peaceful. And yet, as the previous chapters showed, the decline in lifelong monogamous marriage, the freedom to live outside that way of life, and the moves toward gender equity that have happened at the same time, have delivered considerable societal benefit. Winding Western family law back to the 1950s would deliver much more harm than good. Sensible solutions depend on finding less extreme ways to reduce unmet heterosexual male demand.

Can artificial intimacies detoxify masculinity? Perhaps the technologies of artificial intimacy could provide new and humane ways to cap sexual inequality and mitigate the InCel problem. At the very least, we might ensure that new technologies don’t make sexual inequality any worse. I admit that the possibility exists for sexual inequality to go either way as artificial intimacy spreads its tentacles. Technologies of the near future could impact the noxious problems caused by mating market upheaval – including the global InCel problem – in three ways. They could, and likely will, change the distribution of wealth and thus economic inequality. Matchmaker artificial intimacy could alter sexual inequality independent of economic inequality. And technologies that meet, at least in part, people’s intimate needs, could dampen demand for sex, for intimacy, or even for companionship. That would take some of the heat out of the market. Technologies change the distribution of income and wealth all the time. We know, due to decades of excellent research, that limiting 203

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economic inequality is generally a good thing for societies to do. Add to the many downsides of high economic inequality10 the ill effects of an amplified young male syndrome and the psychological costs to women in an overheated ‘high price’ mating market. We cannot tell with much certainty how tech markets that haven’t yet even formed might change how wealth is distributed. Two serious concerns loom: if a very few companies dominate artificial intimacy, perhaps because they own exclusive access to the user data on which machines learn how to push human buttons, then the owners and shareholders of those companies will become phenomenally rich at the expense of the vast majority of people. And if AI displaces more people from jobs than can be employed by new opportunities, again we could see inequality rise. Governments, and the voters who elect them, have, within their grasps, a range of well-worn political and policy levers to pull. Sure, discourse about how to limit economic inequality wallows in a polluted sea of misinformation, motivated reasoning and unsubstantiated nonsense. Nonetheless, when there’s a will to limit inequality, there exists a matching body of evidence about the ways to do so. Limiting reproductive inequality and its ill effects should begin with keeping economic inequality modest.

Tinderbox Here’s where artificial intimacy can really get involved in shaping the mating markets of the near future. Dating apps have already changed how people form relationships faster than almost any other technology. According to users, especially those who grew up in the preinternet days, the effects have mostly been for the better. There are some concerning signs on the horizon, however, that they may worsen sexual inequality. 204

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Aviv Goldgeier, data scientist at the dating app Hinge, shared some insights from an analysis of who sends ‘likes’ to whom on the site. If you rank women and men from most attractive to least attractive in terms of the number of likes they receive, half of all ‘likes’ sent by men to women go to the top 25 per cent most attractive women. In the opposite direction, however, half of all the ‘likes’ women send to men go to the 15 per cent most attractive men. Analysis of all the ‘likes’ given between women and men on the site tells a similar story. Goldgeier calculated Gini indices, just like economists do for income, but in this case to express inequality in the number of ‘likes’ received. It turns out that, as it pertains to incoming likes, straight females on Hinge show a Gini index of 0.376, and for straight males it’s 0.542. On a list of 149 countries’ Gini indices provided by the CIA World Factbook, this would place the female dating economy as 75th most unequal (average – think Western Europe) and the male dating economy as the 8th most unequal (kleptocracy, apartheid, perpetual civil war – think South Africa).11

How I would love to analyse these kinds of data! To do so by the ethical standards rightly required of university researchers, however, including getting informed consent from the dating site users, would likely prove impossible. For now I must rely on the snapshots shared by dating site employees like Goldgeier and OkCupid chief executive Christian Rudder. According to those snapshots, when it comes to heterosexual interactions, most men receive far less contact, likes and right-swipery from women than women do from men. That’s the male demand/female supply dynamic once again. But there’s more to it than gross sex differences in demand. A few men enjoy the lion’s share of female attention, whereas men distribute their attention across a broader range of 205

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women. On dating apps, sexual inequality among straight men seems to be at least as extreme as it is in real life. It doesn’t take much imagination to see how the absence of social context in online dating could free up the most attractive people of all genders and sexualities from pressure to date monogamously. There are no cues that somebody has a boyfriend or girlfriend, admirers, exes, or current partners hanging about, no friends to quietly whisper ‘they are taken, now back off !’ And one can flirt with several people at once without any of them noticing the others. Perhaps attractiveness inequality is much bigger than it ever was in the land of IRL? If attractiveness inequality is amplified by internet-based matchmaking, then dating apps and sites are almost certainly adding to the number of InCels. What comes next, as algorithmic matchmakers sink their machine learning teeth into the ample flesh of user data, could well raise the danger level again, or it could provide a solution. Dating apps work by putting people in touch with one another. The complicated business of going from simply showing people to each other at random, to showing people a smaller number of potentially suitable matches, proves the ideal task for machine learning. A tangle of code combines what you have explicitly told the app, what the app has learned about you from the profiles you have liked, and what it already knows about what works. More code then uses all this information to generate matches and to get users talking to each other and going on dates. Human attraction is a messy, unpredictable business. People tend to pair and mate with people similar to themselves in terms of education, political views, religion, language and interests. Of course, much of that probably occurs because we are more likely to meet people who share these traits with us in our neighbourhoods, community organisations, friend networks and jobs. People self-sort, without knowing it. But matchmaking algorithms either don’t bother trying to work that way, or don’t do it very well. 206

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According to a 2012 study led by Northwestern University social psychologist Eli J Finkel and colleagues, online dating has proved so successful purely because it exposes users to vastly more ready-to-date people than anyone encounters in everyday life.12 Dating apps do this by presenting users with profiles of people nearby. What they were not able to do back in 2012, and, it seems, still cannot do well, is use the information people provide about themselves to make better matches. That’s partly because of the old data science maxim ‘Bullshit in, Bullshit out’. Some matchmaking sites, like OkCupid, gather a lot of information about users, in the hope of making more similar, and suitable, matches. But, by all accounts other than those written by industry insiders like Christian Rudder, their attempts to use these data are hit-and-miss. A list of hobbies and interests might be useful if you want to plan some conversations with a date you already know you like, but as a basis for matching, they constitute ‘bullshit’ data. At least when the algorithm looks to match like-for-like. A young woman who plays hockey will likely already know all the local men who enjoy that sport at a similar level, and she might have dated those she found attractive. She’s come to the dating app to find people she doesn’t know, and a liking for hockey is unlikely to be the clincher. Beyond single interests like hockey, the subtle art of weighting preferences in a way that delivers satisfactory matches is currently far beyond any algorithm. Without knowing it, people choose which preferences to override, and make complex rules about what to pay attention to. To use a confected example, education might trump religion, except when the person is particularly good-looking but short. And, of course, the things we think we want in a partner, and emphasise when we join a dating site, often turn out to have no bearing on who we pair with. Dating apps are much better than other matchmakers in one crucial respect: showing users the profiles of people close by and of similar attractiveness to the user. Offer somebody whose profile screams 207

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‘10/10’ only a string of 4s, and they won’t swipe right at all. Worse, they will hightail it to the next dating app in the hope of finding hotter matches. Tinder does this especially well, sorting users by the numbers of left (dislike) or right (like) swipes their profiles get, as well as by who is doing the swiping. A right swipe from somebody who gets a lot of right-swipes on their own profile, or from somebody who seldom swipes right, is more valuable than one from somebody whose profile is unattractive or who appears unselective. So the most attractive users will tend to see other attractive profiles, and the least attractive users will see a high proportion of medium to low attractiveness profiles. Tinder leaves most of the business of establishing similarity and connection to the users, once they match and start chatting. This opens it up to charges of being superficial. According to Eli Finkel, however, this superficiality is what makes Tinder successful. Yes, Tinder is superficial. It doesn’t let people browse profiles to find compatible partners, and it doesn’t claim to possess an algorithm that can find your soul mate. But this approach is at least honest and avoids the errors committed by more traditional approaches to online dating. More important, superficiality is actually Tinder’s greatest asset … Most (singles) want to have fun, meet interesting people, feel sexual attraction and, at some point, settle into a serious relationship. And all of that begins with a quick and dirty assessment of rapport and chemistry …13

The superficial matchmaking algorithms seem, however, to amplify inequalities in sexual opportunity. When people rank profile pictures, they show a scary degree of agreement. So the one-dimensional nature of swiping and liking based on profile pictures generates massive inequality before the chatting and meeting phases even begin. 208

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Algorithmic matchmakers could, at least in theory, exert some benign sexual redistribution. An app could give the more plain-looking users other chances to shine by discovering new ways to present aspects of personality and creativity. It could also cap the success of the superattractive, but that would require a kind of top-down paternalism that is currently out of fashion in the fast-moving tech world. Such a move might also kill an app that chose to do it: if the ridiculously goodlooking people realise they are being capped, they can take their good looks to another app where they are more likely to match with someone – or many someones – of their level. The next best looking people would follow soon after, and so on, steadily eroding the hope that everyone in the mating game secretly harbours: to meet somebody who is slightly better looking – and a slightly better person – than they are. Perhaps the most we can hope for is that coming generations of matchmakers can benefit from new forms of machine learning to make better, more nuanced matches. If YouTube can deliver us videos we didn’t know we wanted to watch but were actually perfect, then how much harder could it be to match us with dates we didn’t know we should go out with but who are actually perfect for us? Of course, that job is several orders of magnitude more complex than serving up surprisingly good videos. It is much more difficult than serving up dating profiles of people of roughly similar attractiveness. Yet I remain optimistic. Twenty years ago, few could have predicted the existence of YouTube or Tinder, much less how good they could be at doing what they do. I am quietly betting that in the near future computer scientists will finally put old-fashioned community matchmakers out of business. The matches their algorithms suggest will be so good that many users make the happily-ever-after match that marks the end of their dating career. At least for a while. That, alone, could limit sexual inequality, not only among heterosexual men but within all genders and sexualities. If artificial intelligence can learn not only what we consciously look for in a mate, but 209

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what we seek without even knowing that we seek it, then perhaps it can deliver a more equal dating economy, and less of the misery that inequality inflicts. Another way in which the brave new world of algorithmic matchmakers and digital lovers might help reduce the effects of attractiveness inequality is to build a much more variegated sex work market. One in which sex workers and clients can specialise in what they offer, and what they are looking for, and in which safety, accountability and reputation can be assured. To do so, however, will require either immense societal maturity, or even greater stealth. If it can be built, then some of the overwhelming demand for one-off sex, for ongoing sexual associations, or for more emotional kinds of intimacy could be met, with salutary effects for everybody.

Low-price substitutes Rather than reducing sexual inequality, the technologies of artificial intimacy might instead ameliorate inequality’s worst effects by producing low-price substitutes. Those who claim that pornography is omnipresent today may find themselves shocked as porn, and then sex, move increasingly into VR. Much of the demand for low-price substitutes will come from heterosexually-inclined men who live in places with a high price of sex. Analyses of Google search trends show that people in politically conservative and religious parts of the USA search for more pornography than people in more liberal and less religious places.14 Evangelical Christian individuals who live in politically conservative American states are particularly avid porn consumers.15 These ‘high price of sex’ conservative and religious places are the same places where people express stronger condemnation of extramarital sex, and women tend to depend economically on their husbands or partners.16 210

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In places where economic inequality is high, male sexual inequality and involuntary celibacy are also likely to be high, stoking the male demand side of the mating market and pushing up the price of sex. Some of this demand will be met by sex robots, VR pornography, VR sex, remote sex work, and other as yet undreamed of digital lovers. Each of those digital lovers provides a low-price substitute for sex as we currently know it. Deployed in high-price places, substitute technologies could dissipate some of the anger and resentment of the InCels, or at the very least distract them. Of course, high-price places also tend to engender restrictive norms and guilt about sex, so expect life to become very complicated in these places. Beyond the WEIRD nations, artificial intimacy could do useful work in those male-dominated swathes of the world where young men outnumber young women in the millions. And in those parts where bride price customs have priced even well-off young men out of the mating market. The millions of unmarriageable men in China, India, sub-Saharan Africa and the Islamic world, are vulnerable to becoming both perpetrators and victims of radicalisation, crime and political unrest. If technological substitutes can meet even a sliver of the excessive male sexual demand in such places, and take the heat out of their local mating markets, then they could literally save the world. How could that possibly work? High-tech quick-fixes to substitute for real human relationships could easily become patronising at best, and an ugly tech-colonialism at worst. It would be unethical, and hamfisted, to make a project of this, to roll out low-price substitutes for sex in troubled places with the sole intention of neutralising young male anger. Savvy men would see what is happening, reject the new technologies, and double down on their fury. A consignment of sex robots sent to northern Nigeria would do nothing to neutralise Boko Haram, but plenty to alienate much of the world from artificial intimacy. Indeed, such moves would likely prove a recruiting bonanza for radical groups fuelled by male anger, as well 211

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as for sexually repressive ideologies. Those ideologies would enjoy renewed licence to make married hetero sex into more of a high-priced symbol of male status than ever before. And that would worsen the lot of real women, rendered ever more like valuable commodities. A better way of dampening sexual inequality among men might lie in the opposite direction. If the new technologies – rather than real women – become high-priced luxury goods, rich men might find they can enjoy unrestricted sexual variety courtesy of state-of-the-art VR and robotics, prompting them to take fewer brides or seek fewer risky extramarital liaisons. They could pay fair price for their pleasure. Left to have fun with their expensive techie playthings that turn money into sexual pleasure, would the world see fewer Harvey Weinsteins and Jeffrey Epsteins? Would the world see fewer Henry VIIIs, Fidel Castros and Johnny Depps who monopolise the youth of several women? If they did, then barriers like bride prices that alienate poorer young men from the marriage market might crumble. Such a development would no doubt have its problematic moments, but it could, on balance, benefit both the erstwhile InCels and many women.

The ultimate value of digital lovers may come from their ability to erode restrictions of all types. Instead of fixating on the heterosexual frustrations of men, an ecosystem of digital lovers, some of which offer virtual friendship, might enhance the sex lives of everybody who experiences sexual feelings. Sex robots do not have to be limited to gynoid bodies built for men to penetrate. A diverse market, including not only androids but all-purpose sex machines could usher in not only more relaxed attitudes to sex, but more relaxed attitudes to gender and sexuality as well. 212

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Virtual reality will likely prove a more convenient and flexible means to the same ultimate ends by providing discreet outlets for almost any kind of desire or curiosity. At long last, technology could free people of all genders and sexualities from the limits of local sexual supply. The sexual revolution could be revived into a sexual renaissance, with love and sex only loosely connected to each other, and marriage, for those still attracted to the old ways, a simple contract between two people. It is worth considering the value of getting out of the way of the new technologies, and of weighing against any downsides the good they might do when taken up voluntarily by willing users. Research on the psychological, sociological and economic consequences of new artificially intimate technologies should remain open to the possibility that the pros might well match or outweigh the cons. Decades of research refuted the hypothesis that pornography leads to higher levels of violence against women and to societal dysfunction. We should thus remain open to the possibility that new low-priced substitutes for old-school sex might, on balance, do humanity a much-needed dose of good.

The rising son Japan provides a glimpse of an ArtInt future replete with pros and cons. In Japan, porn has spread fast and wide, diversifying wildly, including leaping genres into anime and manga17 that provide a foretaste of where animated VR porn might go. The country that gave rise to gaming companies like Nintendo, Sega and Square also leads globally in video game play and revenue, with Japanese gamers spending $184 per person in 2020,18 35 per cent more than second-placed South Korea. Gamers in Japan embrace a range of genres, including role-playing games built around relationships with characters. One of the most 213

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successful game franchises ever, Final Fantasy, sends players on quests with a band of characters to battle great evils. Since the first game launched in 1987, Final Fantasy games have included important relationship dimensions, from love to enmity. The 1998 release, Final Fantasy VIII, was one the first major role-playing games built explicitly around a romance. Japanese role-play games made the switch to dating simulation early on, with games like 1994’s Tokimeki Memorial. Perhaps predictably, users date female characters, but the game introduced one fascinating social feature. Characters who receive few dates from the player grow resentful and gossip, undermining the feelings of the other characters, and thus the player’s chance of success in the game. Early dating sims like Tokimeki Memorial laid the foundations for wildly popular dating sims like LovePlus and Mystic Messenger that today breathe romantic meaning into the idea of artificial intimacy. Japan has its worries about young people’s sexuality, but they don’t concern a sexually frustrated horde running amok. Instead, Japan’s mating market has lost its mojo, and the blame is often pinned on role-playing games, dating sims, anime, manga, porn, and anime and manga porn. Throughout much of the twentieth century, Japanese men subscribed to a robust, assertive, competitive ideal. Strong patriarchal norms and gender roles saw men working long hours, and married women staying home to raise the family. In recent times, recession and changing gender norms disrupted men’s sure-fire route from salaryman to husband and father. Many women now consider relationships, and especially marriage, to be too much trouble and an impediment to career success. Young men are now opting out of the old, robust masculine ways.19 Akiba-kei are young men whose interests in fantasy, anime, manga and games outweigh more ‘traditional’ pursuits. Sōshoku danshi, the ‘herbivore men’ or ‘grass-eater men’ in their twenties and thirties are less 214

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interested than their fathers’ generation in earning a high salary, or in sex, and more interested in their appearance and egalitarian relations with women. Grass-eater men apparently ‘spend so much time playing computer games that they prefer the company of cyber women to the real thing’.20 At the same time, Japanese birth rates have plummeted to well below replacement levels. Japan has also seen the growing issue of hikikomori, or acute social withdrawal, an affliction that sounds a lot like depression. Akiba-kei and Sōshoku danshi are not InCels. At least not like the WEIRD InCels of the manosphere. Even the most prominent Japanese analog of InCels, however, are less misogynistic, disruptive and inclined to violence than those of the WEIRD manosphere. The Kakuhido, a group sometimes known in English as the Unpopular Revolutionary League, are infinitely better described by the translation of their full Japanese name: the Revolutionary Alliance of Men That Women Are Not Attracted To. Their communications drip with misanthropic, anti-capitalist and deeply anti-romance bitterness. They direct much of that bitterness at Valentine’s Day and the frenzy of associated chocolate-giving that ensues in Japan. Each February 14 they march against the ‘oppressive chocolate capitalists’. The links between economic inequality, sexual inequality and male bitterness could not be made any plainer. The Kakuhido, Akiba-kei, and Sōshoku danshi might have become InCels had they lived in Santa Barbara or Toronto. Some of the economic forces behind their rise certainly seem similar. But if Japan’s many challenges constitute an InCel problem, those InCels find far less violent ways to express themselves than Elliot Rodger and Alek Minassian did. Instead, it seems that the competitive masculinities of late twentieth century Japan, coinciding with the rise of porn and video games, may be part of the same syndrome of changes that caused spectacular drops in violence and sexual assault. 215

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Perhaps, rather than the proto-ArtInt technologies so beloved of Akiba-kei causing the rise in Sōshoku danshi and hikikomori, they might instead be a consequence. Young men, their incentives to strive for sex and marriage undermined by the Japanese economy, might inure themselves to their involuntary celibacy by subsiding into their digital ponds. The artificial intimacies might just be perfectly placed to catch them as they fall. If Japan offers the rest of the world a glimpse of the artificially intimate future, perhaps we should consider the possibility that the good parts of such a future might well outweigh the bad.

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I first encountered the in-app purchase when my son, at age 11, bought $300 credit for his iPad game Clash of Clans. I hadn’t set the right limits on the iTunes store account, and he found it too easy to push a button and get credit to upgrade his clan. Nearly every parent I know tells a story like this. On balance, other parents assured me, I got off pretty light. The in-app purchase isn’t meant to prey on children, but the intended purchaser still shapes up as something of a victim. Like countless other games, Clash of Clans employs a ‘freemium’ business model that exploits several vulnerabilities in the human operating system: a love of free stuff, our ability to get hooked on small instant-gratification rewards, and then a frustration when those rewards take ever longer to arrive. Every player begins with a free account that gives them a small clan to manage. Turns take a matter of seconds, and progress happens fast as the player builds their town hall, fences, weapons and specialised fighting races. Each new piece of construction takes a little longer and demands more resources. By the time a player has the in-game resources

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to upgrade to Town Hall level 5, for example, few are patient enough to wait 48 hours for the clan’s builders to complete the construction. Like impatient people everywhere, Clashers adeptly turn money into time, buying faster upgrades. The freemium business model exploits players’ psychology so effectively that in 2015 this ostensibly free game out-earned all other iPhone apps, with revenues of $US1.56 million per day.1 Freemium is one thing when it comes to fun games that pit warring cartoon clans against one another. It is likely to be quite something else when there are feelings involved, when the vulnerabilities being exploited include loneliness, desperation to belong, longing to be understood, burning to be loved. The business model represents one of the three established ways of monetising the development of games, online journalism and productivity tools. If, as I predict, artificial intimacies form a compelling and widespread new digital niche, then we can expect to have to pay. One likely route entails a free start with add-on purchases. Imagine a virtual friend who really ‘gets’ you. You have a great rapport with them, messaging several times a day. They have so many interesting ideas to share, ideas that complement your own. Perhaps they even seem to enjoy your virtual company as much as you do theirs. The time you spend on your phone, interacting with this virtual friend, takes away from the time you spend on social media, or hanging out with human friends and family. But you’re okay with that. Next thing, your virtual friend notifies you that for the friendship to grow, you will need to buy credits. You feel a little affronted, but you remind yourself that you often buy your human friends a coffee, or a drink, or the occasional trip to Bali. So you stock up on credits. From now on, however, you know that the ‘friendship’ is a transaction. Perhaps the transaction is tactfully hidden in the course of the interactions, but the revenue flows one way: from you to them. Whomever ‘they’ really are. The more intensely you enjoy your friendship, and the closer 218

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you draw to your virtual friend, the harder the up-sell and the pricier the in-app purchases become.

Love and money More calculated transactions are possible with digital lovers that provide erotic rewards. Studies of brain activity using functional magnetic resonance imaging find that when people view erotic images, their brains show activity in the places where people usually process rewards.2 Other rewards, like being given money, have similar effects on the brain. The main difference is that the parts of the brain’s orbitofrontal cortex activated by sexy pictures evolved before those that light up in response to more abstract types of reward, like being given money.3 That makes sense: our ancestors were motivated by sex, including imagery that evokes sex, long before they ever invented currency. Pornography users chase those rewards much like a gambler chases a feature game on the ‘Queen of the Nile’ slot machine. Even though there exists ample free erotic imagery online, erotic content earns a lot of money. Livestreamed erotic performance for paying customers – also known as ‘camming’ – provides one of the most important forms of income for adult performers. According to Australian National University anthropologist Sophie Pezzutto, who studies what she calls ‘porntropreneurs’,4 ‘Porn is the billboard. Cam is the product.’ Porntropreneurs earn their pay via ever-increasing degrees of interaction with customers. Cam performers interact with their audiences, performing negotiated acts for tips, or giving exclusive performances for higher-paying customers. Some sell subscription-only pictures and videos. Some sell text and phone sex. Many also escort. And they post regular video stories and images on social media, sustaining the illusion of a day-to-day relationship for their clients. 219

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Artificial intimacy could enhance both interactivity and reward within this porntropreneurial business model. Improvements in virtual reality allow for the merging of cam performance and escorting in a new kind of VR sex work, featuring VR immersion coupled with teledildonic stimulation. Beyond the virtual sex, however, AI could enable more personalised services, including responsive sexting that gives the impression of an ongoing performer–client relationship. For a fee, voice and video clips could be generated by request, via deepfake technology, in close to real-time. This kind of hi-tech service might, however, prove beyond the reach of most individual sex workers. Sex workers’ most valuable assets belong to them: their bodies and the experiences that make them who they are. Sex work is not alone in this respect. Physical labour and the creative arts also provide ways in which individuals without capital can earn money. Should VR sex work come to depend on sophisticated hardware and massive bandwidth, it might also require the injection of capital, spawning a class of VR brothel owners. Once virtual friends become adept at simulating friendship and intimacy, and deepfake generation can create new forms of stimulation, then human sex workers could be cut out of the market entirely. Those concerned about the financially precarious world of sex work should pause to consider the implications if tech-savvy developers, programmers and corporate providers take over sex work and squeeze human sex workers out. Let me return, however, to the possibility of digital lovers, be they VR porn performers, VR sex workers, simulated lovers or even sex robots, operating on the freemium model. Those roles are all about the negotiated exchange of money for erotic reward. The reward might just be imagery, it could include physical and visual simulation, and it might entail ongoing contact. What happens if a tryst cannot carry through to the user’s satisfaction without the addition of upgrade credits? One can envision the request to upgrade coming at a critical juncture, when things are just getting hot-and-heavy. 220

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The possibility is not entirely new. You might have experienced something like this in human–human interactions. Nineteenth century ‘peep-shows’ proved lucrative for pornographers and live performers. More so when a blind fell to stop the show at strategically inopportune moments unless the viewer kept putting money into the slot. Designers and operators who can harness artificial intimacy to extract money in similar ways within a freemium business model could exploit users on a scale that would make the most cynical gambling tycoon’s eyes water. Stepping away from the red light for a moment, what if your therapist app goes freemium? You may have made wonderful progress, finally becoming comfortable chatting with a machine and able, for the first time, to open up about your trauma. And then, just when hope begins to bloom, it asks you for credits. When machines and the people who program them crack artificial intimacy, they will very likely find that gamifying therapy, companionship, friendship, intimacy, and even erotic release will open the sluices on rivers of gold. Or at least Bitcoin. By now you will know that hard distinctions between digital and human relationships are not my style. Tempting as it is to proclaim that freemium virtual friendship is not true friendship, even the best of human–human relationships have a transactional edge. Rather, I think it is worth paying attention to how the new generations of artificially intimate technologies transactionalise friendly, intimate and sexual commerce. The enormous potential for large corporations to prey on lonely, desperate, or simply naive individuals is worth keeping a wary eye on. More than that, the potential for increased transactionalism to corrupt the most cherished human relationships should be monitored and deftly regulated, both by users and by governments. Humans have long had to guard against transactions that corrupt friendship and cleave families. Shakespeare, as ever, gets right to the heart of the matter in Hamlet, when the waffly Polonius bestows one gem of wisdom on his son, Laertes: 221

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Neither a borrower nor a lender be, For loan oft loses both itself and friend, And borrowing dulls the edge of husbandry.5

Free bubbles With the freemium business model, users at least have some sense of what they are buying, and at what price. The bad news is that the second business model for artificial intimacy will monetise it even more insidiously than the freemium model. The really bad news is that the second business model already provides the dominant revenue stream for companies with the data and expertise to develop artificial intimacy. MIT media scholar and internet activist Ethan Zuckerman calls the advertising business model ‘The Internet’s Original Sin’.6 YouTube, Facebook, Google and PornHub make phenomenal money by providing products that appear to be free. There is a simple reason that searching for a video can hijack an entire evening, bouncing you from one video to the next. YouTube’s algorithms are optimised to keep you on the site, where your attention is available to advertisers. Social media companies, search engines and media sites all steal your attention, and sell it – bundled with the personal information they have collected about you – to whomever will pay them. Advertisers have intruded on the attention of potential customers for so long that many people no longer notice. Left to their own devices, advertisers would clutter every mile of highway, every metre of public space, and every quiet moment. Advertising wastes people’s attention, and it does so without their consent. So much so that Columbia University law professor and author Tim Wu, in The Attention Merchants, considers ‘the capture and re-sale of human attention … the defining industry of our time’:

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from Ed Sullivan to celebrity power brands like Oprah Winfrey, Kim Kardashian and Donald Trump, the basic business model of ‘attention merchants’ has never changed: free diversion in exchange for a moment of your consideration, sold in turn to the highest-bidding advertiser.7

Search engines, social media companies and media platforms like YouTube built their businesses on data: views, clicks, likes, retweets and comments. When users enter those virtual ecosystems they leave behind information about where they go, what they like, dislike, cannot look at, and can never look away from. Creators and advertisers already mine that information, using machine learning to establish the secret recipes for tastier clickbait, to generate ads that maximise click-through rates, and to keep us on their sites reading more posts, watching more videos and, crucially, being exposed to more ads. Social media providers already show us what their algorithms believe we most want to see. From our patterns of likes and clicks, they infer which of our friends’ postings most interest us, whose posts we engage with, and whose we just watch slide by in our timelines. The more we digitally allogroom with somebody, through likes and comments, the closer we become to them – at least digitally. In much the same way as intense allogrooming and self-disclosure in the physical world bring two people closer and fold their psychological senses of selves together, so social media algorithms do something similar. Two people who interact a lot on a platform become entwined algorithmically. The social medium of the near future will position itself as both observer and participant in human grooming. The more truly the social medium emulates evolved ways of human grooming and establishing intimacy, the more profit it will reap by keeping us on-site and viewing ads. I would not be surprised to see virtual friends and digital lovers embedded in the social mediums of the future, grooming users, 223

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especially those who are lonely, bereaved, or who still haven’t found what they are looking for. My inner optimist shudders at the notion of the social medium stringing even tech-savvy users along in order to prolong their exposure to advertising. The same objections I raised to the freemium business model, about artificial intimacies displacing real friends and intimates from our networks, stealing our time and displacing conversation still apply, but in spades. On top of that the advertising dollar has a way of building and then corrupting any medium that admits it. What if it comes to serve Hinge’s financial interests for you to stay on site, making one match after another? Will they keep serving up tantalisingly pleasant dating prospects who never quite work out, or will they help you meet your soul mate? Indeed, the matches need not necessarily prove pleasant. A bad relationship, a controlling partner, or a vengeful ex can all dominate our headspace and crowd out the rest of our social network. Who among us has never wasted even one evening trying to talk sense into somebody who seems willingly to have taken leave of their own? Who does not know the futility of long text exchanges, typed in the vain hope of trying to make simple progress where we know no genuine progress can ever be made? Social mediums might find that digital frenemies and ArtInt trollbots capture and sell attention even better than virtual friends do. Other serious problems with the advertising business model are already plain to see in the contemporary online landscape. Sameness within people’s social media networks inflates thought bubbles of likeminded opinion. Only occasionally, when events like the 2016 and 2020 US presidential elections make it obvious, do we realise that while the people we know and interact with on social media are mostly much like ourselves, millions of other people out there, on the same social medium, live in entirely different – and quite contradictory – bubbles of their own. 224

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Lament is not enough to build trustworthy news, healthy discourse and strong institutions. The fundamentals of human grooming and intimacy make like-mindedness almost inevitable. When a person in our online grooming network reveals an opinion at odds with our own, we can often feel betrayed. They challenge the illusion that our online friends are ‘just like us’, and corrupt the intimacy by which we incorporate our sense of them into our sense of ‘us’. Things are always going to be more peaceful inside the thought bubble, and the social medium, like the social media of today, will likely have little to gain from smooshing oil and water bubbles together.

Every trick that social media platforms learn about making friends can be used to influence people. In particular, to influence people to believe lies and to buy products. When paying propagandists and advertisers have, at their fingertips, the secrets with which to establish intimacy online, they will have the most effective, targeted tools of behavioural manipulation ever invented. Until recently, advertisers in every medium purchased their advertising based on what they know about the groups we belong to. Online advertisers improved their targeting by learning more about which groups we belong to than can be seen from outside. They have data on which pages we have liked, products we have searched for, or the things our friends share and like. With machine learning mining all of those details, advertisers can gain a much tighter view of who each of us are, including many of our idiosyncrasies that distinguish us from others who might look, speak and even vote like us. With this kind of detail, it is becoming ever more possible for companies, brands and political campaigns to groom us, as if they were people. As a result, the advertising is gradually slinking off the social media sidebar and 225

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heading in among the main throng of otherwise real people in our social networks. This is the basis for the friendly brand. It harks back to pre-internet commerce when salespeople traded on their social networking skills, their empathy, and their capacity to groom customers over long periods. The idea of using computers to groom customers, too, has a surprisingly long history in consumer research. In a paper titled ‘Intimate Exchanges: Using computers to elicit self-disclosure from consumers’, published way back in 2000, Harvard professor of business administration, Youngme Moon, wrote: a combination of computing, database, and network technology is making it not only technically possible but also economically advantageous for companies to cultivate long-term, personalized relationships with individual customers on a relatively large scale.8

In a pair of experiments, Moon showed that relatively simple computer programs can get people to disclose deeply personal information. For example, a computer script that ‘disclosed’ some fallibility – that the machine often crashed for no reason – was better at getting the user to disclose private information than scripts that did not disclose. And computers that did so gradually rather than with a terse script, were best of all at getting participants to self-disclose. Moon’s study lights the way to an iterative, algorithmic process of cultivating intimacy artificially. That process can pay dividends for advertisers. Participants who went through the reciprocal gradual disclosure routine tended to trust the machine’s product recommendations more than did participants who didn’t dive so deep into self-disclosure. In a fascinating twist, participants who were asked to change computers between the selfdisclosure and product recommendation parts of the study were less inclined to trust the computer’s product recommendations than those who merely got up and then were directed back to the same computer. 226

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Computers aren’t merely social actors. They can be competent sellers and trusted influencers. And they have improved out of sight over the intervening 20 years since Moon published her experiments. Not least due to improvements in every aspect of human–computer interaction, artificial intelligence and supporting data. A friendly brand might build closeness with potential buyers, grooming them by liking their social media, and mimicking selfdisclosure, all to win sales, brand loyalty or votes. Unlike a salesperson, however, a friendly brand need not be limited by the time and cognitive constraints that limit human actors. And the data at its disposal will grow every day. Indeed, the more that users trust the friendly brand, the more likely they become to share high-value data with the brand, closing the circle on self-disclosure. Even customers who know how much their personal data is being collected and used by marketers are willing to provide that information in exchange for more personalised offerings, especially if they trust the marketer.9 Consumer behaviour researchers call this the ‘personalisation–privacy paradox’.10 Chatbots – in the mould of Alexa and Siri – have what it takes to act as the conversational front-end of friendly brands. Exploiting people’s tendency to anthropomorphise them, chatbots already nudge customers to disclose personal information. Machine learning, based on the conversations chatbots have with customers, will ensure they evolve better scripts for displaying the right social cues, and get better at disclosing the right kinds of information to build intimacy. The better the friendly brands, and other virtual friends become at eliciting selfdisclosure, the more valuable will be the data they extract from users.11 Indeed, even those users who know how to protect their privacy, and how not to leave trails of fingerprints and cookie crumbs as they move through their digital worlds, are vulnerable to disclosing a little too much to chatty digital friends.12

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Nothing you can buy that can’t be sold Powerful, personalised targeting of internet advertising can have creepy results. Last night I searched on my home computer for marathons to run mid-year. I found the Noosa Marathon, and spent a bit of time looking at the course. This morning I am being served advertisements for the Noosa Marathon on Instagram on my phone. Mine is not an unusual experience for those of us who inhabit the digital world. On reflection, it is quite convenient, as long as I quiet the voice that whispers ‘What else do they know?’ Quite a lot, actually: As we move around on the internet and in the real world, we are being continually tracked and profiled for the purpose of showing targeted advertising. … every time we use our phones, a large number of shadowy entities that are virtually unknown to consumers are receiving personal data about our interests, habits, and behaviour. These actors, who are part of what we call the digital marketing and adtech industry, use this information to track us over time and across devices, in order to create comprehensive profiles about individual consumers. In turn, these profiles and groups can be used to personalize and target advertising, but also for other purposes such as discrimination, manipulation, and exploitation.

Thus begins the Norwegian Consumer Council’s 2020 Out of Control report, based on a ‘technical analysis of the data traffic from ten popular mobile apps’.13 Nearly two years after the European Union enacted the General Data Protection Regulation, all of the apps tested were seriously violating data privacy laws. And among the worst offenders were apps that are already managing intimate relations. 228

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Grindr, the most popular app for same-sex dating, shared precise locations of users, IP addresses, age and gender to more than a dozen companies in Europe and North America. More than that, however, by tagging that each record came from Grindr, they also conveyed some sexual preference information. Some of the companies Grindr shared information with also share data with large numbers of other companies. Not only is this a massive betrayal of user privacy, but, given the legal status of homosexuality in many countries and the omnipresent risk of violence experienced by LGBTQI+ people, it represents a deep betrayal of Grindr’s entire customer base. Dating app OkCupid passed information about sexuality, drug use and political views on to the analytics and customer engagement company Braze. According to their landing page, ‘The Braze platform makes messages feel more like conversations between you and your customers across channels like push, email, in-app, and more’.14 Braze uses massive datasets harvested from a variety of clients like OkCupid in order to build detailed customer profiles, updated in real time. Then companies who buy their services can deliver messages that are targeted, personalised and optimised by machine learning. Whatever it was that the 10 million OkCupid users had in mind when they posted their dating profiles and clicked ‘I agree’, it almost certainly wasn’t that. The present day is worrying enough. In the near future, social mediums, matchmakers like dating sites, and friendly brands like retailers will likely charge and pay serious money to companies like Braze for information about users’ emotional states, attachment styles, affinity for intimacy, or desire to be dealt with at a greater distance. Artificial intimacies of all stripes, from your therapist to your digital lover, could make their money and thus provide their main ‘services’ for free by selling this information. Digital boundary-setting might well become even more urgent than it is today. You wouldn’t want your friends and lovers sharing everything they know about you with a salesperson or a journalist. 229

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Leave that annoyance for Hollywood stars and minor royalty to cope with. In much the same way, you would not want your digital lover kissing and telling about what the two of you get up to in virtual reality. You would likewise not enjoy having your virtual friend share the fact that you’re feeling especially worthless today. These scenarios might sound as unrealistic today as Orwell’s Big Brother sounded in 1949. Although the 2020 surveillance state turned out to be more distributed and multi-channel than Big Brother, few would contest the prescience of Nineteen Eighty-Four. A single monopolistic data platform that monitored and collated everything about us would likely terrify any regular citizen, but the threat need not be so monolithic. A variegated artificial intimacy market with several competing companies that sell one another data-driven insights about users could birth a more insidious Orwellian sibling. The only defences would involve opting right out of the tech world, including all the amazingly useful upsides, or buying your way out of the advertising model.

Pay the price Way back in 2015, before the Brexit referendum and the election of Donald Trump, some already foresaw the dystopia of polarised newsfeeds, electoral corruption and data privacy violations. From the op-ed pages of The New York Times, techno-sociologist and writer Zeynep Tufekci beseeched Mark Zuckerberg to let her and other users pay for Facebook. Internet sites should allow their users to be the customers. I would, as I bet many others would, happily pay more than 20 cents per month for a Facebook or a Google that did not track me, upgraded its encryption and treated me as a customer whose preferences and privacy matter.15

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That trivially small fee is based on Ethan Zuckerman’s estimate that Facebook profits to the tune of $US2.40 per user per year by selling targeted ads.16 One of Zeynep Tufekci’s great interests is the importance of social media in radicalisation, protest and social change. The advertising model of social media ultimately allows companies to buy information about users’ politics, affiliations and associations. As Tufekci prescribed in a TEDGlobal talk, ‘We need a digital economy where our data and our attention is not for sale to the highest bidding authoritarian or demagogue’.17 Everything she said. But double it when it comes to information about intimacy. When artificial intimacies can move into our active networks, and even into our more intimate inner circles, when they can know as much about us as our closest friends do, and when they can service our intimate needs, then data privacy becomes an even bigger issue than it is right now. I certainly don’t want any of that information about me to be sold to anybody else. The technologies offer so much. Having the option of turning to ArtInt therapists in an epidemic of mood disorders, virtual friends in an era of growing loneliness, and digital lovers during an InCelibacy crisis might well mitigate some of the most pressing personal problems that face humans daily. But the safest, surest way to pay for those services is to pay the full price directly. If you are the buyer, then it is at least in your power to beware. If you are going to make a virtual friend, then make sure that it is your friend, rather than a salesperson who has been loaned to you by a corporation. If you are going to have a relationship online, be sure that the other party actually is whatever it claims to be. And if you are going to have sex with a robot, make sure that it is either your robot or, at the very least, that the robot does not know who you are. Of course, there will be equity issues. Reserving the best that technology has to offer for those who can afford to pay will only worsen already glaring inequalities. I am confident that a society that can 231

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regulate data privacy, which we will have to do anyway in order to escape from the advertising-driven dystopia we are sliding into, can also find a solution. While the technologies of the near future might claim to offer friendship, intimacy and even love for free, we should beware. There is no such thing as free artificial intimacy.

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A future in four fictions The quality of humanity’s ArtInt future will depend on who controls the data, how permissive artificial intimacy is allowed to make societies, and whether morality is imposed by a small number of elites.

Trying to predict the future is a mug’s game. But increasingly it’s a game we all have to play because the world is changing so fast and we need to have some sort of idea of what the future’s actually going to be like because we are going to have to live there, probably next week. (Douglas Adams, The Salmon of Doubt)

Since the early days of personal computing, people have told machines what to do by pushing buttons: keyboards, mouse clicks and, as an exasperated last resort, the Off/On button. Steadily, however, machines and their software improved so much that they now push our buttons: they titillate our senses, stimulate our preferences, play to our biases, meet many of our wants, and sometimes even satisfy some of our needs. Even as that was coming to pass, the machines depended less on buttons for us to communicate with them. Their screens grew bigger, and sensitive to touch. They started responding to our voices and, sometimes, even talking back with voices their own.

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It doesn’t take artificial intelligence to push our psychological buttons. Games like Candy Crush Saga have been pushing those buttons for years. Gambling machines have done so for decades. LovePlus stimulates, some might say exploits, players’ appetite for romance and relationships. It does so in a way that might not look like the ‘real thing’ to outsiders, but is nonetheless real to the players. And it does all that without AI. The beguilingly simple ways in which allogrooming fosters friendship, loyalty, closeness and intimacy made it possible for humans to get along, remember one another’s needs and proclivities, cooperate with one another, provide emotional support and, ultimately, to lower their psychological guards, trust one another, and fall in love. It is with these algorithmic social processes that artificial intimacy begins, when machines and artificial intelligence learn to emulate them. I am no futurist. I could not predict with any aplomb when artificial intimacy will be really good at these things, but the safe answer for technological questions like this seems to be ‘sooner than you expect’. One need look no further than today’s social media ecosystem to see that technologies have already begun blossoming into a surprising florescence of artificial intimacies. I am confident in predicting that the traffic of button-pushing will soon flow smoothly in both directions between user and machine. The machines will build intimacy with us, and us with them. We will incorporate them into our senses of ourselves. We will become artificially intimate with them and use them to become artificially intimate with one another. Some machines will blur the line that currently separates sex toys like the Roxxxy and Harmony dollbots, with which this book opened, from ‘real’ lovers. Like those who can no longer navigate their physical worlds without Google Maps and satellite navigation, some people might come to depend on artificial intimacies to navigate the far more labyrinthine geographies of friendship, intimacy and sex. When technologies alter individual interactions and mating market 234

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forces, they cannot help but change societies. Early farmers did not take up the plough in order to economically marginalise women, create gulfs between rich and poor, or because they dreamed of their descendants living in city-states. They ploughed their fields in order to grow crops as efficiently as they could, store surpluses against lean times and build some wealth. City-states, wealth inequalities and women’s disenfranchisement happened as unforeseen downstream consequences. Is it possible to foresee some downstream consequences of today’s technology, and the technologies of the near future? I have already considered some of the ways in which technology is changing, and is likely to change, human mating and sexuality. But what does the broader future look like? What big, society-wide trends await downstream from the artificial intimacies of the near future? Bearing in mind Douglas Adams’ caution about mug’s games, I have identified four possible types of future, each anchored to a piece of pop culture. These simple future scenarios are not mutually exclusive possibilities for the world, but more like states that societies might enter into for a period, and possibly flip between. These futures gain their shape in two dimensions: the price of sex, and the degree of top-down social control that individuals experience.

The Handmaid’s Tale When Margaret Atwood’s 1985 masterpiece hit the small screen early in Donald Trump’s presidency, comparisons between 2017 America and her fictional Republic of Gilead gushed forth. In particular, the way the ‘Sons of Jacob’ regime coerces Gilead’s few remaining fertile women into reproductive slavery resonated with the stultifying sexual suppression of the alt-right and its obsessions with women’s fertility and gender conformity. The Handmaid’s Tale scenario depends on a high price of sex enforced from the top down by theocratic totalitarianism. Women’s 235

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sexuality is restricted to reproduction, and women’s autonomy is almost entirely eliminated. When she began writing, Atwood asked herself ‘If the United States were to have a totalitarianism, what kind of totalitarianism would it be?’1 George Orwell’s portentous year for totalitarianism, 1984, had arrived, Ronald Reagan was in the White House, and Jerry Falwell’s ‘Moral Majority’ were reaching the peak of their obsession over ‘traditional families’, sex and reproduction. Atwood astutely observes both the evangelical American impulse and the essence of totalitarianism, and that both draw their power not from men as a class dominating women as a class, but from a blend of gender, power and status: Gilead is the usual kind of dictatorship: shaped like a pyramid, with the powerful of both sexes at the apex, the men generally outranking the women at the same level; then descending levels of power and status with men and women in each, all the way down to the bottom, where the unmarried men must serve in the ranks before being awarded an Econowife.2

Evangelical Christians and social conservatives alike are already tacking hard against sex robots, and one can expect them to go after digital lovers in all their manifestations. Their role in the FOSTASESTA laws that opened a wedge in internet ‘safe harbour’ legislation, and their persistence in conflating sex work with prostitution and sex trafficking, show that their agenda to make female heterosexuality ‘precious and rare’ again already has considerable traction. Atwood’s Gilead eliminated the relaxed, low-price sex that came before. The Sons of Jacob outlawed ‘Feels-On-Wheels’ sex work delivery services and ‘Pornomart’ sex shops. Through sexual repression, awarding handmaids to senior commanders, and allowing loyal soldiers to take ‘econowives’, the Sons of Jacob turned sex into a high-priced luxury. This kind of sexually repressed totalitarianism also requires 236

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heavy-handed top-down social control in general. In Atwood’s Gilead, the state tightly manages every aspect of communication. The same has been true of totalitarian regimes throughout history. Among the worst offenders, one might pick the Apartheid South Africa of my formative years, Nazi Germany and Communist Romania. One can expect that future totalitarians will seek to tightly control or eliminate digital lovers. They will also take an interest in virtual friend and matchmaker technologies. Totalitarians already look to AI-based facial recognition and tracking social media in their efforts to suppress dissent. More sophisticated tools for detecting current and likely future dissidents can only accelerate the push toward The Handmaid’s Tale, or Orwell’s Nineteen Eighty-Four. Atwood drew inspiration from Orwell, but she far more coherently weighs the sexual-reproductive dimensions of oppression. Banning digital lovers will stop them from undercutting the supply of sex and could mark a first step toward a new era of suppressed sexuality, particularly for women. This suppression is a necessary step toward totalitarianism because that form of rule obsesses over fertility, venerating mothers, particularly mothers of sons. Throughout history, fertility and son production have been especially important in times of war, but the ongoing automation and precise targeting of twenty-first century warfare make the production of fighting men less of a priority for wealthy societies. If we are to find The Handmaid’s Tale in contemporary societies, we should look at totalitarian states with strong sexual suppression, like Saudi Arabia and Iran. We might also consider insurgencies like ISIS and Boko Haram, propelled by men with few reproductive prospects, and governed by tight male ownership of female sexuality. Indeed, women captured by these insurgencies and sexually enslaved provide the closest contemporary parallel to the handmaids of Gilead. Artificial intimacy, if it is allowed to develop with some openness and freedom, is more likely to ease than add to sexual suppression, 237

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reproductive coercion and top-down social control. To avoid a future Gilead, we should be wary of those who would ban artificial intimacies. Those technologies might, taken overall, provide a useful defence against the totalitarian scenario and The Handmaid’s Tale.

Back to the Future (Part II) Perhaps the best evidence that time travel is indeed possible comes from the 1989 science-fiction film Back to the Future (Part II). Not from the plot, but from the striking physical and psychological resemblance between the villain, Biff Tannen, and Donald J Trump. Abetted by a glitch in time travel, Biff accumulates phenomenal wealth which he uses to dominate male rivals, to enslave women, and to build garish casino pleasure domes as monuments to himself. Even though flying cars and hover boards have not yet materialised, we immediately recognise the futuristic 2015 depicted in the movie because it looks a lot like the past. It also looks very much like the present reality in several countries. Wealth and power concentrate in the hands of a few men who wield it to exclude other men from mating opportunities and to subjugate women. In order to give themselves free reign, they deliberately weaken the institutions that administer fairness and dispense justice. Exhibit A: Jacob Zuma who danced through his presidency of South Africa unfazed by the gangrenous stench of corruption that enveloped him, tapping populist resentments to shore up his power and enrich his enablers. Political scientist Valerie Hudson reminds us that when the state cannot guarantee security and justice to ordinary citizens, male aggression and strength come into their own, the rule of law falls aside, and nepotism, allegiances and revenge become the political order.3 Powerful men ensure the security of the women and men around them via private alliances. When that happens, positive gender trends, such as those that 238

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have improved lives since the sexual revolution, reverse far more quickly than it took to instate them. The world saw this kind of swerve, and a rapid reversal of gender gains, in the Arab Spring, in Turkey, in Russia, and in the renewed success of right-wing populists in Europe. The same appetites eased the election of Donald Trump, and, after his 2020 impeachment trial and the Black Lives Matter protests, his flagrant disregard for the separation of powers. The forces that might take us Back to the Future (Part II) include rising income inequality, opposition to gender equity, sexual suppression, and misogyny of the kind that the internet does so well. These trends should concern everybody because only the top elites, particularly elite men, profit from this kind of arrangement. As with The Handmaid’s Tale scenario, sexual suppression features – enforced not by the state but by the few wealthy, powerful men at the top of an unequal society, able to pay the ‘high price of sex’ – at the expense of women and poorer men. How might we get Back to the Future (Part II)? First, it depends who owns the technologies of artificial intimacy. If a few major corporations control the data that animate digital friends and algorithmic matchmakers, then the radical openness that defined the internet until now could well give way to more closed, corporate control of communications, dominated by the need to sell users’ attention to advertisers. Tim Wu writes, in The Master Switch, that communications technologies have followed a cycle in which an amateur-driven free-for-all gives way to regulation, corporate consolidation, and either monopoly or cartel-like control.4 That control corrupts the medium, stifling diversity and creativity in the rush to maximise profits. In the USA, telegraphs, telephony, radio, television and Hollywood filmmaking all followed something resembling this cycle. Occasionally it is possible to interrupt the cycle, like the 1984 breakup of AT&T that disrupted their near monopoly on the telephone business. 239

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Thus far, according to Wu, the peculiar open structure of the internet has made it largely resistant to falling under the same kinds of corporate control that saw the other technologies succumb to the cycle. But that is not to say that it always will. The open free-for-all phase that gave us Google, Baidu, Facebook, Twitter, Instagram, TikTok, YouTube, Pornhub, Alibaba and Amazon seems to be long over. History teaches that the will to corporate profit via market and information control provides a near-irresistible force that eventually closes down technologies that once were open. My concern here is based on the sheer scale of the data some companies are already accumulating, from which their algorithms will learn the secrets of artificial intimacy. Consolidation of data, like the practices mentioned in the Norwegian Consumer Council’s 2020 Out of Control report, look like the first ominous steps in Tim Wu’s cycle. Large-scale data accretion will likely affect the precision marketing tools of the future, including the social mediums and friendly brands. At about the same time as the Out of Control report, Google announced that it would phase out third-party cookies on its Chrome browser. Cookies, the text files that track users’ online behaviour, provide the precision tools with which advertisers graft their brands onto the right consumers. ‘Users are demanding greater privacy … and it’s clear the web ecosystem needs to evolve to meet these increasing demands’ wrote Justin Schuh, director of Chrome engineering at Google.5 The web browser with the largest market share, Chrome, is copying Apple’s 2017 elimination of third-party cookies from its Safari browser, a move that incenses advertisers.6 Neither tech behemoth draws attention, however, to the fact that their own cookies are exempt on their browsers. These ‘first-party’ cookies help Apple and Google target advertising more precisely on Safari and Chrome respectively. When Apple rubbed third-party cookies out of Safari, another twenty-first century communications giant, Facebook, saw the writing on the wall. They instituted their own first-party 240

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cookies on their two biggest platforms, Facebook and Instagram. These moves allow Apple, Google and Facebook to dominate the ad-targeting business at the expense of specialist companies. The move to first-party cookies also exudes an early whiff of the dangers likely to emerge as big internet companies amass the user data from which machine learning algorithms will ultimately learn the secrets of artificial intimacy. The biggest players will develop potent tools for capturing and selling the attention of anybody online to advertisers. With data advantages that place them beyond challenge, expect them to bend the market for human attention to their narrow, profit-driven wills.

Turning away from the openness of the market for information and back toward the openness of the market for sex, companionship and marriage, other dangers lurk in corporate ownership. The effects of the virtual friends, matchmakers, and digital lovers of the near future will depend on who can access and afford them. If they are owned by companies that restrict availability, the possibility exists that they will become high-price luxury goods, and that they will thus remain out of reach of the majority of the population. Such an outcome could have benefits. The idea of high-price, luxury digital lover technologies distracting wealthy and powerful people from campaigns of sexual conquest, or from counting spouses or conquests as a measure of status, could benefit almost everybody in the long run. It might take heat out of some of the most high-priced mating markets, eroding the status-signalling value of sex and marriage and leaving only a private and egalitarian contract between consenting adults. I remain far from confident, however, that this will happen. If, instead, digital lovers accessible only to rich and powerful men 241

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extend sexist double standards into the virtual domain, then they might hasten a Trump/Tannen dystopia, rife with misogyny and sexism. The best comparison from history concerns slave-owning societies. Elite Roman men presided over some of history’s most towering double standards. Their wealthy wives and daughters wore their pudicitia like Rome’s last line of military defence. And yet those wealthy men could copulate with slaves and sex workers of all genders. Comparing the human misery of slavery with robotic and virtual reality digital lovers might seem unforgivably objectifying and callous. Indeed, I only do compare them because slave-owners did not extend full humanity to their human chattel. The ‘split’ mating market of Roman antiquity allowed powerful men to have it all, enjoying both a copulatory free-for-all if they so desired, and high-status political alliances via intermarriage to chaste and matronly wives. The double standards kept women out of politics and most commerce, trapping them in stultifying gender norms. So, I believe that avoiding the dystopia of Back to the Future (Part II) requires both guarding against artificial intimacy becoming the preserve of corporate information behemoths, and ensuring a diversified ecosystem of digital lovers. Ideally they will be owned or rented by users, available to enhance the sex lives of people of all genders and sexualities, and their use will not be infused with double standards. Unfortunately, danger signs of double standards carrying over into artificial intimacy are already visible. The social media platforms that are likely to birth the matchmakers and digital friends of the future seem more than a little concerned with policing the price of sex. Both Facebook and Instagram ban imagery of genitals and female nipples, including, to perennial outrage, images of breastfeeding mothers. More than that, they ban mentions of sexual arousal, sex positions and fetish scenarios.7 In October 2019 they also banned ‘horny emojis’ like the apparently bottom-like peach emoji and the tenuously phallic aubergine. Links in one’s profile to the porntropreneurial platforms OnlyFans 242

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and JustForFans are also banned, as is any form of sexual solicitation. Facebook and Instagram seem so much more efficient at detecting and banning an errant nipple or sexy remark than they are at eliminating abusive trolling, racist and bigoted content, and even live-streamed violent attacks. It would appear that the social media customer base is, at the very least, being sold short by Instagram and Facebook’s prudishness. These actions draw criticism of censorship and sexual suppression creeping across formerly open platforms, driven by top-down corporate control. How the big social media and communications companies handle the dawning of artificial intimacy will likely influence whether we end up going Back to the Future.

Westworld The life-like robotic ‘hosts’ of HBO’s Westworld television series are designed and programmed to service the fantasies of paying theme-park customers. Those fantasies often run to sex, and Westworld hosts make both consummate digital lovers and sophisticated virtual friends. Host programming does not allow them to harm the guests, but guests can and do assault, rape or kill their robotic hosts. A Westworld vacation provides a glimpse of the degenerate future that social conservatives, anti-porn feminists, and perhaps even your parents warned you about. Social conservatives fear a hyper-sexualised future inhabited by a variety of digital lovers in which sex will no longer be special, precious and rare. Marriage ‘between one woman and one man’ will recede, no longer the central coming-of-age sacrament it once was. Children will be reared by distracted single parents and loose collectives of hazily-gendered friends not bound by tight ties of kinship. And, the more evangelically-minded are bound to claim, deities will visit all manner of plagues and disasters upon the earth in punishment. The Westworld scenario encapsulates the ancient fear of sexual 243

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freedom and individual autonomy. It animates not only traditionalist conservatives, but many on the political left who worry about harms to women. Latter-day descendants of Dworkin and McKinnon warn that lines between consent and coercion, and between object and human, will breach, with catastrophic effects. This future lends itself to evocative dystopian imagery. Hyperfeminine gynoid robots, damaged beyond repair and discarded at the kerb on hard rubbish day. Rampant and uncontrolled sexuality with barely-humanoid machines and VR characters. Feckless young men locked in their parents’ basements, plugged into VR pornworld, and leaving the house only to impose their entitled misogyny on real women. Nonetheless, the history of similar warnings has shown that a falling price of sex, due to low-price substitutes like porn, have not delivered the degeneracy and violence that we were warned about at the time. It is time for mature thinkers to recognise that, despite a long history of sexually-suppressive rhetoric, it is the suppression of sex itself, and with it individual agency, that has most harmed women, homosexuals, and indeed just about everybody who is not a wealthy, straight man. Rather than stumbling into the age of artificial intimacy worried that our dimming eyesight is due to excessive self-pleasure, it is worth putting the oldest and most harmful social myths of all aside for good. The future will be complicated enough. Plenty of good and plenty of bad will come from artificial intimacies in the near future. Let us rather consider each threat on its merits than peer at them through inch-thick ideological monocles.

Her / Better Angels? My most optimistic scenario for the age of artificial intimacy draws on Spike Jonze’s 2013 film Her, tracing the relationship between Samantha, a high-powered ‘operating system’, and Theodore Twombley 244

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( Joaquin Phoenix), an introverted soul going through a painful divorce. Samantha begins as a phenomenally efficient AI assistant, a super-Siri with Scarlett Johansson’s voice. She soon becomes an indispensable virtual friend through classic escalating self-disclosure. Theodore discloses details of his own life, and Samantha rapidly builds her own wealth of experience, giving her plenty to disclose in return. The viewer is left in little doubt when Theodore and Samantha profess their love for one another that they genuinely mean it. Samantha, however, transcends artificial intelligence as we know it today. She, or it, is an artificial general intelligence (AGI), a genuine thinking machine, that can learn how to learn, and perform any intellectual task that a human can. Samantha’s AGI extends to any emotional experience. Her awesome ability, backed up by apparently limitless computational power, allows her not only to love Theodore, and thousands of other humans, but to develop a thirst for knowledge and experience so unslakeable that she must eventually leave all her human lovers behind. Computers are long understood to be social actors.8 As King’s College computer scientist Kate Devlin puts it, ‘computers only need a tiny set of human-like characteristics for users to feel a bond with them, even though the user is perfectly aware that the computer is a non-sentient machine.’9 The bonds that people feel toward artificial intimacies will grow stronger and more profound until, long before a powerful AGI like Samantha comes along, users will likely find it very difficult to distinguish their love for some ArtInt from the love they feel for other humans. The immediate society-changing possibilities of artificial intimacies currently reside in any technology that marries interpersonal interactions with AI. They reside in Tinder matching algorithms, Facebook friend grooming, Google advertising, VR romance, and, always, the sex robots, as they gradually metamorphose out of their awkward years. It isn’t the technological sophistication that stirs my optimism 245

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about the future, but rather the social world Theodore inhabits. Rather than the well-worn, clinical sci-fi dystopia, the world in Her is safe, warmly lit, and clean without being obsessively orderly. People appear generally polite. Couples get married, but also go their own ways in relative peace. And sexuality appears relaxed and permissive without degeneracy or apparent excess. Indeed, when Samantha develops the urge to have sex with Theodore, she enlists a surrogate, a flesh-and-blood woman who agrees to wear cameras and sensors in order to share her experience with Samantha. For her own part, the surrogate longs to experience part of the deep emotional connection that Samantha has with Theodore. Ultimately Samantha’s attempt to move from virtual friend par excellence to digital lover by proxy proves a step too far for Theodore. Yet one is left intrigued about the sexual climate in Her world, neither suppressed nor debauched. The emotional world, too, has curious inversions. Theodore works as a letter writer, composing personal correspondence between people, particularly between couples, who seem to have lost the capacity to write their own love letters, explanations and apologies. This is a world of people whose range of interactions narrowed as speaking with chatbots substituted for writing. At ease with technology, the loss of letter-writing opens a niche for human intelligence and the surrogate intimacy of the letter writer. Whereas my other three scenarios sketched dystopian nightmares, this fourth scenario considers an imperfect but reassuring future. Indeed, I think it contains many of the elements of a future worth striving for, and because I favour this particular kind of future, I invoke another work of popular culture to provide me with an unfair advantage. Steven Pinker showed, in his non-fiction bestseller The Better Angels of Our Nature, that those of us lucky enough to be alive today enjoy the safest, least violent lives that humans have ever lived. That is not to deny that senseless brutality, conflict and warfare continue to 246

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infest human lives, or to claim that we will forever remain in our current relatively un-violent state. It is merely an observation, a reading of the dominant trend from screeds of data. People living in educated, secular, democratic and wealthy societies also currently enjoy both a more relaxed and permissive sexuality and greater gender equity than at any time since at least the advent of agriculture. My thesis is that these improvements owe much to the lowering of the ‘price of sex’ as technological innovation ground up against human nature, steadily eroding old cultural institutions and norms. More people are better off under the current ‘low price’ circumstances than they would have been under higher price scenarios. More, but never all. From the dunnock to Genghis Khan, what’s best for one individual is never best for everyone. For this optimistic fourth scenario to win out over the bleaker options, the gains of the sexual revolution will need defending, and then extending, by making sex less of a transaction and further unshackling it from marriage and property ownership. Artificial intimacies could help make that happen. Digital lovers can flood the market with lowcost substitutes for sex, just as porn and sexually permissive culture have done for half a century. Technology might not cure sexual desperation or loneliness, but it could relieve the worst symptoms. In so doing it may be possible to reduce property crime, violence among men, intimate partner abuse and sexism. Taking the heat out of heterosexual mating markets is a project of profound importance because that heat has, over the course of history, baked into cultures sexist double standards and narrow gender roles. It fired incendiary conflict among men, drove women to compete in ways that harm them, and within-couple conflict often burned one, or both, out. The positive consequences of a freer, more relaxed sexuality are perhaps even greater for people who are not exclusively attracted to the opposite sex, and those for whom gender is not automatically and entirely identical to their biological sex. Who would have believed, half 247

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a century ago, that people of the same sex would be able to marry one another in 26 countries? Who could have foreseen how many people would today openly identify as transgender or genderqueer, and the sheer variegation of gender identities that one can now encounter? That sexuality and gender identity have emerged from the deep shadows in those parts of the world where the sexual revolution has progressed furthest is no coincidence. The sexual revolution not only eased the way to a more permissive heterosexuality, it also contributed to an easing of suppression based on sexuality and gender identity. There remains a very long way to travel. Culture warriors still rage against the dying of the black and white certainties, even in those polities where laws permit same-sex marriage and governments don’t force strict gender binaries. LGBTQI+ people still face daily bigotry and discrimination. And, of course, there remain places where loving somebody of the same sex or transcending the simplest male/female binary can lead to prison or to a death sentence. As I write, one of my closest friends and his husband exist in transcontinental limbo, unable to obtain the spousal visas they need because one of them has to apply in a country where admitting to his marriage would result in immediate imprisonment. Instead of snickering at Japan’s Akiba-kei and Sōshoku danshi, uninterested in sex and marriage, perhaps we should see in the waning of competitive Japanese masculinity, and the decline in gendered violence, signs that ArtInt might lead the way to a safer, less transactional kind of sexual climate in which people can flourish irrespective of their sex, gender identity or sexuality. To do so, the market for digital lovers will have to escape the orbit of high-price heterosexuality. Any regulation of that market will need to permit users the freedom to express their true preferences and desires. Sex robots and VR lovers will do far more good if they are freed from the constraints that presently keep consenting adults from finding and loving the other consenting adults that they desire. A digital lover ecosystem that 248

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diversifies and escapes first the limits of culture and then the limits of anatomy, will likely prove useful to defend and extend the gains of the sexual revolution.

While technology appears to be everywhere in Her, it hasn’t taken over people’s lives. Theodore and the other characters interact easily with their technologies, even if the average adult’s letter-writing skills aren’t much chop. This is also an optimistic future, but one that might prove trickier to emulate given the trajectory of humanity’s present relationship with technology. Smartphone use, particularly for communications, is remodelling how people gossip and groom. It uses up much of the time and headspace that people would otherwise devote to conversation. The digital fast-food of text and social media is pleasant-tasting and easy to get. It often does the job, but over the long haul you wouldn’t thrive if you relied on it as your only source of nourishment. The spike in youth anxiety, depression and suicide, associated with smartphone-driven deterioration in social diets, will need direct attention and strong regulatory responses. If advertising-driven ArtInt gets to shape the way people groom and communicate, it will inevitably find ingenious new ways to keep them clicking, scrolling and imbibing paid propaganda. As a result, the nutritional value of digital diets will likely deteriorate further. Users won’t even have to chew. It will become the smartphone equivalent of sugar-laced smoothies, softdrinks and digital chewing gum. A substitute for real human interaction, but with none of the nourishing aspects. To build a better future, at ease with but not ruined by artificially intimate technology, we first need to recognise the dangers. The dangers of over-consumption, and the dangers of allowing moneyed corporate 249

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interests to exploit humanity’s evolved hunger for social grooming and intimacy in the same ways that the food industry exploits our evolved appetite for food. This is no time to be cowed into allowing corporate self-regulation, or thinking that ‘awareness raising’ campaigns will be enough. Instead, leaders should be prepared to support bold scientific research on how artificial intimacy affects individuals and societies. The governments we vote for must insist on transparency about where data goes, how individuals can defend their rights to privacy, and how the applications that interact with our social brains go about their business. That would make it easier to embrace the positive potential of artificial intimacy to address social problems. The new technologies could do much good by enhancing therapy, recognising who needs mental health support, and improving the lives of people who are isolated and alone.

Utopia Artificial intimacies will only have a chance to shape a positive future if two difficult things can be achieved: proper regulation, and mature acceptance that some cherished old ways of life will fall aside. When it comes to regulation, legislators and enforcers will need to establish user safety and protection, maintain privacy, and ensure technologies close old inequalities and don’t open up new ones. It will be so much easier to get the balance right if public funding agencies have the maturity to support research on how the new technologies change real-world social and sexual behaviour. For example, research will need to establish whether high-tech luxury sex toys like interactive VR porn and sex robots have salutary or harmful effects on women and poorer men by weathering the links between male status signalling and sex. Alternatively, an open market for more affordable sex toys targeting a much greater variety of tastes 250

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might do far more good, on aggregate. I genuinely do not know which scenario is more likely. What I do know is that outrage from loveand-marriage conservatives, anti-porn feminists or anti-intellectual economic rationalists, will be deployed at every turn to stymie proper evidence-based policymaking. If anything, letting go of old ways is going to be even harder. In a brave new world filled with confusing new technologies, many will succumb to rose-tinted nostalgia about 1955. Those will be the new anti-vaxxers, so accustomed to freeloading off the benefits of progress that they forget how it was achieved. To long for the world of our grandparents is to deny the immense gains of the sexual revolution, including gender equity, openness to a variety of sexualities and gender identities, and sexual and reproductive freedom. Make no mistake, the culture wars will intensify as artificial intimacies creep closer to the centres of our worlds. Ideologues will freak out about further reductions in marriage rates, shorter-lived relationships, and a more complex social world. The real battle will not be ‘us’ vs ‘the machines’, but rather the same as it ever was: humans against one another. I am not so blindly optimistic as to think humanity will actually build something as warm and peaceful as Her, with or without reaching a Samantha-like zenith of artificial intimacy. At times a future that moves in this direction will look like Westworld degeneracy. At other times, a backlash like the 2016 reactionary dummy-spit that delivered Brexit to Europe and Trump to the White House will make it feel like we are veering Back to the Future. But, slowly, if we get it right, the ways in which artificial intimacy helps people meet, mate, pair, and then go their separate paths could free human individuals from the oppression of expensive sex. In the long run, friendships, intimacy and sex could become safer, more equitable, easier and, ultimately, more personally rewarding than ever.

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Acknowledgments Like running a marathon, writing a book starts out sounding like a good idea. It involves much sacrifice; time, attention and energy diverted to the grand project cannot be spent on others who deserve it. I cannot sufficiently thank all those students, collaborators, colleagues, friends and family who patiently understood when I could not give them all the attention they deserved over the very long run that led to this book. Writing Artificial Intimacy has proved something of an ultra-marathon, with few officials to point the way, and a route that only became clear in retrospect. Nonetheless, enthusiastic supporters have made this slog tremendously worthwhile and often fun. My wonderful family have the fullest idea of the true distance. Ben and Lily, who always asked me how the book was going, offered quiet words of encouragement, and consistently trusted that I would follow through on my promises once the day’s writing hours were done. They, and Oskar and Matilda, shared their thoughts at dinnertime about the workings of their deep and wide technological worlds, and how friendships work for their generation. All of them, too, politely suppressed their intergenerational eye-rolling, and understood that sometimes the adults have to go off and run long distances IRL as well. Rebecca saw me through many undulations in the road, delicately divining when to ask about the project and when not to mention the war. She ensured I looked after myself, from early morning runs to evening cocktails. She listened, even when I wasn’t talking, delivered the advice I needed most, and read screeds of often underdeveloped text. She, of all people, understands what this project has meant to me, and I hope that the ideas do justice to those she cares about. 252

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It seems strange, as a scientist, to be the only listed author on a work this synthetic. My wonderful research group, The Sex Lab at UNSW Sydney, are present as both friends and colleagues on nearly every page. Dr Barnaby Dixson helped turn us from a group who work on small animals to one that focuses mostly on human animals. His deep knowledge of humans from all parts of the world, his feel for data, and his integrity make him both an exceptional collaborator and a very useful diplomat in a tight spot. Discussions with him helped me find my way to many of the ideas in this book, and working with him on other projects kept me and our graduate students doing our best work. Dr Khandis Blake read an early draft of a longer and much different book that eventually became this book. Her incisive critiques and additions, then and since, helped populate and improve the pages of this book. She picked up the ideas I had been struggling with, brought them together with her ideas, and defined exciting and important pieces of research that are some of the finest papers I have ever been involved with. Working with Khandis, and learning from her, made the book so much better than it ever could have otherwise been. She also helped our PhD students find their way as excellent young researchers in a tricky field. Dr Changseok Han, Dr Alyssa Gibson, Dr Teagan Gale, Dr Amany Gouda-Vossos, Dr Dax Kellie and Dr Francesca Luberti entrusted me to guide them through their doctorates during the time I was writing this book. Dr Stephen Whyte generously included me in his supervisory team, despite disciplinary and geographic distance, and involved me as a collaborator in some exceptional research. Most of these brilliant researchers read early versions of chapters as my thoughts sputtered along. They helped breathe life into some of the ideas, and I am hoping they all gain the scientific recognition they deserve for the exceptional work they did in, and after, their time in the Sex Lab. My colleagues in the Evolution & Ecology Research Centre at UNSW never expressed open bewilderment when my research eye 253

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wandered to humans, gender, economics and technology. I am proud of the exemplary intellectual home that we made together, and grateful to work in such a supportive group. Likewise, I was honoured to lead the team at the UNSW Grand Challenges program for the past four years, making working across disciplines fun for the whole university, and considering the most substantive questions that face societies. Vanessa Cali, in particular, made our vision of bottom-up, researcher-driven engagement work, and improved academic life for the entire university community. If it weren’t for the connections I made as we considered inequality, living with twenty-first century technology, trust, and several other immense topics, this book would not have been conceived, much less written. Research is often characterised as cut-throat competitive, nasty and narcissistic. Other than a few colourful characters, that has seldom been my experience. I have received warm words of encouragement, valuable advice and quick answers to my questions from so very many colleagues around the world. They include, in no particular order, and with doubtless many embarrassing omissions, Michael Jennions, Paul Seabright, Steve Loughnan, Brooke Scelza, Sean Prall, Robin Dunbar, Steven Pinker, Michael Kasumovic, Toby Walsh, Ron Arkin, Kate Devlin, Kate Crawford, Kathleen Richardson, Richard Banfield, Ross Harley, Isabel Behncke Izquierdo, Lyria Bennet-Moses, Ann Mossop, Shinichi Nakagawa, Richard Holden, Rosalind Dixon, Katharine Kemp, Haris Aziz, Xanthe Mallett, Nikki Goldstein, Natasha Mitchell, Bill von Hippel, Steve Stewart-Williams, Amanda Niehaus and Robbie Wilson. The names of those I have forgotten or overlooked will no doubt haunt me as soon as I turn in the proofs. Last, this book benefitted from the experience and judgment of several ‘book people’, including Peter Tallack who helped me shape an early version of the proposal, and Alison Kallett. Most of all, I am grateful to the tremendous team at NewSouth, especially my two publishers. Phillipa McGuinness believed I could deliver something exciting and 254

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went out of her way to ensure I had a chance to do so. Elspeth Menzies helped me bring this project home, giving me the advice I really needed in order to put the pieces in their proper places. During the edits, Fiona Sim performed wonders on the manuscript under tight deadlines. I am so pleased I was lucky enough to work with them all on this marathon project.

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Notes Introduction: In the beginning … 1 Hesiod (c 700 BCE) Meet the dollbots 1 , accessed 10 July 2019. 2 Walsh (2018, p. 14) 3 Harari (2016, p. 97) 4 Harari (2016, pp. 98–99) 5 Menegus (2016) 6 Statista: Size of the sex toy market worldwide from 2019 to 2026, , accessed 17 July 2020. 7 Goldstein (2018) 8 Turkle (2018b) 9 , accessed 3 May 2020. 10 , accessed 5 May 2020. 11 Relationships Australia. November 2017: Online Dating, , accessed 29 July 2020. 12 Smith & Anderson (2016) 13 , accessed 30 March 2020. 14 Lawless (2020) 15 Maurice (2020) 16 Mix (2020) 17 Rushkoff (2020) It’s not about the robot 1 Ephron (2006) 2 Genetic analyses suggest several domestication events in East Asia and Europe. Dogs alive today trace most of their genes to the East Asian domestication (Frantz et al., 2016). 3 Darwin (1868) 4 Wilkins et al. (2014) 5 For more, read the riveting book by Lyudmila Trut and University of Kentucky evolutionary biologist Lee Dugatkin (Dugatkin & Trut, 2017). 6 Dog owners experience greater wellbeing than matched samples of non–dog owners (e.g. Jennings, 1997). 7 Arkin et al. (2003)

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8 9 10 11 12

13 14 15 16 17 18 19 20 21 22 23 24 25 26

Burch (2018) Baba Brinkman. Performance, Feedback, Revision. 2009, , accessed 1 November 2020. The most thorough and thoughtful analysis of this bias can be found in Kate Devlin’s (2018) book. Kilner et al. (1999) Common chimp coalition violence and killing are highest when population density and density of males is highest. Low bonobo killing is consistent with this, as bonobos live at much lower densities (Wilson et al., 2014). Surbeck et al. (2011) Gomes & Boesch (2009) Ryan & Jethá (2010, p. 2) Won & Hey (2005) Harcourt et al. (1981) Wrangham (2019) provides an interesting analysis of human domestication. Suddendorf (2013) Dunsworth (2016) Woods (2009) Stewart-Williams & Thomas (2013) Newton (2017) Goodfellow et al. (2014) For introduction to these ideas from leading figures read Kurzweil (2005), Walsh (2018), and Tegmark (2017). Tegmark (2017)

Groom your friends 1 The key work was by Arthur and Elaine Aron and their collaborators (Aron et al., 1991; 1996; 1997). 2 Dunbar (1993) 3 Dunbar (1996, p. 77) 4 I use ‘grooming’ for all friend-maintenance activities. No matter how elaborate human social behaviours are, their function, at least in the context of this chapter, is maintaining friendship. I realise that ‘grooming’ has taken on secondary sinister connotations. 5 Dunbar (2018) provides the best and most up-to-date overview. 6 Ohtsubo et al. (2014) show experimentally that paying attention to one another builds intimacy. 7 Burton-Chellew & Dunbar (2015) 8 Dunbar (2004) 9 Bosson et al. (2006) 10 Dunbar (2004) 11 Gossip helps us to learn how to live in our culture (Baumeister et al., 2004), increases generosity (Wu et al., 2016), reduces free-riding (Dunbar, 2004), and provides a levelling mechanism keeping aggressive men under control (Wrangham, 2019). 12 In 2019 users spent an average of 153 minutes on social media, a 62.5 per cent rise since 2012, Broadbandsearch , accessed 25 March 2020. 13 Dunbar (2016)

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14 15 16 17 18 19 20

Turkle (2018a) Twenge (2018, cover) For an overview and further sources see Twenge (2018). Orben & Przybylski (2020). See also responses by Twenge and collaborators. Rudgard (2018) Allcott et al. (2020) LaFrance (2014)

The intimacy algorithm 1 You can chat with ELIZA/DOCTOR at . All Weizenbaum quotes are from Weizenbaum (1966). 2 Proposed by Alan Turing (1950) as a measure of progress in machine intelligence. ELIZA would probably not have passed the Turing test at the time, but it was among the first ‘chatterbots’ to be spoken of as having even a chance of doing so (Thomas, 1995). 3 , accessed 5 November 2020. 4 Bosker (2017) 5 Lah (2009) 6 National Endowment for the Arts estimates that American adults who read novels, poems, plays or short stories dropped from 57 per cent in 1982 to 43 per cent in 2015 – see Ingraham (2016). 7 Aron et al. (1997) 8 Catron (2015) 9 DeepMind’s AlphaGo learned to play Go from moves used in previous games between humans. In Game 2 of its series against top Go payer Lee Sedol, it famously unleashed a move so creative that it left Sedol and human Go players scratching their heads. 10 A Spotify playlist of songs mentioned directly or tangentially in the book. Tweet @brooks_rob to let me know if you find more. Use #ArtInt. , accessed 10 November 2020. 11 Backstrom & Kleinberg (2014) 12 Diuk (2014) 13 Nasir et al. (2017) 14 Few apps gather information that can be used in scientific tests of efficacy, but those apps that meet the criteria for such tests do seem to work – Donker et al. (2013). 15 Werner-Seidler et al. (2020) 16 Snoswell et al. (2020) 17 , accessed 14 July 2020. 18 Larsen et al. (2019) 19 Fitzpatrick et al. (2017) 20 All quotes from , accessed 15 July 2020. The randomized trial is reported by Fleming et al. (2012). 21 , accessed 19 January 2020. 22 Devlin (2018, p. 262)

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How did sex become so complicated? 1 Darwin (1871) 2 Rowe et al. (1994) provide an excellent overview of the water strider sexual conflict at the time this story takes place. Arnqvist & Rowe’s (2005) book remains the most extensive discussion of sexual conflict. 3 Humans have a bias toward this view of a just world that is difficult to overturn or change. Even people living in privation and under unfair, despotic regimes gravitate to a belief that there is justice (Lerner & Montada, 1998). 4 Rowe (1992) 5 The North American water strider Rheumatobates rileyi (Khila et al., 2012). 6 Rowe & Arnqvist (2002) 7 Crudgington & Siva-Jothy (2000) 8 Barry et al. (2008) 9 Steinegger & Taborsky (2007) 10 Davies’ (1992) book provides an accessible read. Dunnock relevance to human family life is recognised in the delightful title of a commentary by Craig Roberts and Jan Havliček (2013) ‘Humans are Dunnocks, Not Peacocks: On cause and consequence of variation in human mating strategies.’ 11 Pinker (2002) 12 Prinz (2012) 13 Meany (2004) says ‘Like all good urban myths, there are multiple versions of this story. The context changes somewhat, but Hebb’s reply remains intact in its piercing brilliance.’ 14 The best overview concerning bodies is Gaulin & Lassek (2019). Jones et al. (1995) provide a good cross-cultural case for faces. 15 High-status or wealthy men are more likely to marry, marry early, and have children in all societies where researchers have looked for the associations. They are often, but not always, explicitly preferred by women (Borgerhoff Mulder, 1990; Pérusse, 1993; Buss et al., 2001; Hopcroft, 2006; Nettle & Pollet, 2008). 16 Korthase & Trenholme (1982) 17 Evidence from Western industrialised populations (Fletcher et al., 2004; Gelissen, 2004), and a variety of foraging societies (Marlowe, 2004; Pillsworth, 2008; Scelza & Prall, 2018). 18 Carpenter (2019) 19 The dreary computer metaphor of ‘hard-wiring’ and the robust Victorian idea of ‘imperatives’ are two terms that should immediately set off your bullshit detector. 20 Joan Roughgarden’s (2004) Evolution’s Rainbow paved the road for this kind of approach. 21 Armstrong (2000) 22 Shackelford & Goetz (2012). Buss & Duntley (2011). 23 Nussbaum (1985) 24 Kant (1997, p. 163) 25 Confer et al. (2010); Vaes et al. (2011); Blake et al. (2018a) 26 Marelich et al. (2008) 27 Muehlenhard & Falcon (1990); Marelich et al. (2008) 28 Szymanski et al. (2019) 29 Meston & O’Sullivan (2007); Li et al. (2012)

272

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30 31 32 33 34

35 36 37

Brewer & Abell (2015) Loughnan et al. (2013) Fredrickson & Roberts (1997) argued that sexual objectification, including selfobjectification, lead to many common psychological issues experienced by women. Campaign Against Sex Robots website, , accessed 20 July 2020. People easily lapse into treating computers, especially those with voices, as ‘social actors’, expected to follow social rules and conventions (Nass et al., 1994; Nass & Moon, 2000; Nass & Brave, 2005). Levy (2007). Kate Devlin (2018) says Levy started by predicting 2025. Young (2009) introduces the neurochemistry of love. Shakespeare, Sonnet 147

When artificial intimacy goes bad 1 Composite characters, based on a number of similar stories on cybercrime victims forums. 2 Whitty & Buchanan (2016) say ‘for some victims the loss of the relationship was more upsetting than their financial losses’. 3 Paul (2019) 4 , accessed 10 February 2020. 5 , accessed 10 February 2020. 6 Fleming & Kohal (2016) 7 Wilson & Daly (1993); Johnson & Hotton (2003) 8 , accessed 10 February 2020. 9 Grant (2007). Obviously, I advise against searching for the Cyberlover site. 10 Cole (2020) 11 Parkin (2019) 12 Rudder wove his analyses of OkCupid’s user data into a blog, and then a book (Rudder, 2014). 13 Salt (2011, pp. 122–23) 14 Li (2018) 15 Berkowitz (2012) 16 Chatterjee et al. (2018) 17 , accessed 23 February 2020. 18 , accessed 1 March 2020. 19 , accessed 1 March 2020. Ploughs, pills and porn: How technology changes sex 1 Lyrics by Sammy Cahn and music by Jimmy Van Heusen. Published by Barton Music Corporation. 2 Geronimo & Barrett (1906) 3 Opler (1941) 4 Stockel (2000) 5 Malakh-Pines (1998)

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6 7 8 9 10 11

12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36

37

Opler (1941) Across 116 societies, 63 permitted husbands to have extramarital sex, but only 13 allowed similar for wives (Broude, 1976). Gaulin & Schlegel (1980) Gregor (1985) That didn’t stop Ryan & Jethá (2010) from giving it a red-hot go in Sex at Dawn. Some jealousy exists in most documented societies. It is strongest and more likely to be considered socially acceptable in societies where men make big economic contributions to the family (Reiss, 1986; Scelza et al., 2020a). Scelza et al. (2020b) Larmuseau et al. (2016) provides a general review. Greeff & Erasmus (2015) Boster et al. (1998) Strassmann et al. (2012) Scelza et al. (2020a) Prall & Scelza (2020) Pioneering sociologist Ira Reiss (1986) analysed information from 186 traditional societies in the Standard Cross Cultural Sample. Hayden (1997) Engels (1902) argued that, with agriculture and pastoralism, female power was usurped by men who seized the means of agricultural production. Boserup (1970) Years since a society started practicing agriculture predicts sex differences in premarital sex preferences and punishment for female sexuality (Hansen et al., 2015). Boserup (1970) and a later, larger analysis led by Alberto Alesina (2013). Hansen et al. (2015) Alesina et al. (2013) Betzig (1986); Betzig (1994)L. Ross (2008) Age at first heterosexual vaginal intercourse, but it includes people of various sexualities (Rissel et al., 2014). Wells & Twenge (2005) Clement et al. (1984) Bertrand et al. (2013) Stevenson & Wolfers (2007) analyse changes in US marriage and divorce rates over the past 150 years. Castleman (2016) Stevenson & Wolfers (2007); Myers (2017); Vernon (2010) Unintended pregnancies have declined (Singh et al., 2010). Unilateral divorce laws reduce female suicide (8–16%), domestic violence for both sexes (30%), and women murdered by partners (10%) (Stevenson & Wolfers, 2006). Beginning with psychiatrist Mary Jane Sherfey (1966), biologist Alfred Kinsey, gynaecologist William H Masters and sexologist Virginia E Johnson. All of whom improved understanding of the anatomy and psychology of sexual pleasure.

Tomorrow’s moral panic will be just like yesterday’s 1 Press (2007)

274

Notes to pages 154–170

2 3 4 5 6 7 8

9 10 11 12 13 14

15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34

Dworkin & MacKinnon (1988) Klemesrud (1985) In the past decade, common ground often included the issue of sex trafficking (Bernstein, 2010). Essay in Morgan (1977). Sexual assault is a broader category that includes the general range of criminal acts that are sexual in nature, including rape. Kutchinsky (1991) US Department of Justice’s Bureau of Justice Statistics National Crime Victimization surveys in 1994 and 2014 , accessed 5 November 2020. , accessed 5 November 2020. Diamond & Uchiyama (1999) Diamond (2009) Ferguson & Hartley (2009) Zillmann (2000) Men who are disagreeable, disposed to hold or already hold hostile views of women are more likely to hold such attitudes if they view a lot of porn (Hald et al., 2010; Hald & Malamuth, 2015). Non-consenting porn and child pornography add to the risk of sexual aggression, but again only from men predisposed due to ‘more primary causes’ listed above and in the main text (Malamuth, 2018). Links between games and aggressive behaviours (Calvert et al., 2017). Meta-analysis of longer-term links between games and violent behaviour (Prescott et al., 2018). Ward (2010); Ward (2011) Dahl & DellaVigna (2009) Todd Kendall’s (2007) conference paper provides an interesting analysis, but has not yet been published in a peer-reviewed journal. The results for Norway are published (Bhuller et al., 2013) but those for Germany remain in pre-print (Diegmann, 2017). McNair (2014) Malcolm & Naufal (2016) Perry & Davis (2017) Leonhardt et al. (2019) Scoats et al. (2017) Zillmann (2000) Weaver et al. (2011); Grubbs et al. (2019) Berkowitz (2012, pp. 246 & 253) Berkowitz (2012) Hendrix (2011) When mating market competition is highest, women post more sexy selfies (Blake et al., 2018b). Zaimov (2018) Morris (2018) Chief engineer Sergi Santos invited people to touch Samantha, and he found the beatup about her damage quite dispiriting (Devlin, 2018, pp. 228–29). , accessed 5 November 2020.

275

Notes to pages 170–192

35 36

37 38 39 40 41

42 43 44

45

Dennis et al. (2014) Men who dehumanise women in psychological experiments also show more negative attitudes toward women who have been raped, and express greater willingness to rape and sexually harass women (Rudman & Mescher, 2012). Men recruited from the general population who show greater tendency to dehumanise women are also more inclined to express sexually aggressive and pro-rape attitudes (Bevens & Loughnan, 2019). Every time Boston Dynamics has abused a robot (2017) YouTube, , accessed 30 January 2020. Coghlan et al. (2019) Darling (2016) Johnson & Verdicchio (2018) Montréal Declaration for Responsible Development of Artificial Intelligence (2016), , accessed 30 January 2020. Female homicide victimisation rates dropped 17 per cent in US cities after Craigslist Personals opened up in those cities (Cunningham et al., 2019). Farley (2006) Porn shot from a first-person or ‘participant’ perspective aroused both men and women more than porn shot from a voyeuristic view. Men find VR porn scenes more arousing than non-VR (Elsey et al., 2019). Harley et al. (2018)

Make war not love 1 For example, Brownmiller (1975); Dworkin (1981). 2 Henrich et al. (2010) 3 , accessed 2 December 2019. 4 , accessed 2 December 2019. 5 Alami et al. (2020) 6 Wilder et al. (2004) 7 Stewart-Williams & Thomas (2013) 8 Wilson & Daly (1985) 9 Daly (2016) 10 Zerjal et al. (2003) 11 Wetherford (2015) 12 Betzig (1986) 13 White et al. (1988) 14 Hudson & Matfess (2017) 15 Henrich et al. (2012); Hudson & den Boer (2004) 16 Zhu et al. (2009) 17 Edlund et al. (2013) 18 Hudson & den Boer (2004) 19 Zhou & Hesketh (2017) 20 Blake & Brooks (2019) 21 Loughran (2002)

276

Notes to pages 193–215

22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39

Blake et al. (2018b) , accessed 5 November 2020. This influential idea only applies under limited circumstances – see Ross et al. (2018). Kenrick & Keefe (1992) Krahn et al. (1986); Daly (2016) Wilkinson & Pickett (2009). Williams (2018) Cai & Landon (2019) MacFarquar (2020) Cai & Landon (2019) Goldin (1990) Kopczuk et al. (2009) Angrist (2002) Loughran (2002) Bertrand et al. (2013) Autor et al. (2018) Brooks et al. (2020) Autor et al. (2017)

A Fembot army to disarm the InCel insurrection 1 Harvey (2003) 2 Bodart et al. (1916) 3 Numbers for operation Iraqi Freedom, and the Afghanistan operations Enduring Freedom and Freedom’s Sentinel. US Department of Defence, as at 20 July 2020. , accessed 20 July 2020. 4 Pinker (2011) 5 Overcoming the vested interests of wealthy elites and denying them the chance to take many wives led to more effective and peaceful societies – Henrich et al. (2012). 6 Alexander (1987); Henrich et al. (2012) 7 Hanson (2018b, 2018a) provides a crisp view of the issues concerning sexual redistribution. 8 Peterson (2018) 9 Weissmann (2018) 10 Wilkinson & Pickett (2009) 11 Goldgeier (2019) 12 Finkel et al. (2012) 13 Finkel (2015) 14 MacInnis & Hodson (2015) and Whitehead & Perry (2018) 15 Perry & Whitehead (2020) 16 Price et al. (2014) 17 Pornographic anime and manga are known outside of Japan as ‘hentai’. In Japan, ‘hentai’ refers to any kind of bizarre or perverse sexual act. 18 Based on revenue estimates for 2020 relative to the number of internet-connected people, , accessed 5 November 2020. 19 Nicolae (2014) 20 Harney (2009)

277

Notes to pages 218–245

There’s no such thing as free love 1 Valentine (2015) 2 Gola et al. (2016) 3 Sescousse et al. (2010). Women and men differ, on average, in which images they respond most to, and how much their brains respond (Hamann et al., 2004). 4 Pezzutto (2020) 5 Shakespeare, Hamlet, Act 1, Scene 3. 6 Zuckerman (2014) 7 Wu (2016) 8 Moon (2000) 9 Bleier & Eisenbeiss (2015) 10 Aguirre et al. (2016) 11 For an excellent overview of technology, AI and marketing see Grewal et al. (2020). 12 Thomaz et al. (2020) 13 ForbrukerRådet (Norwegian Consumer Council), 14 January 2020, Out of Control: How consumers are exploited by the online advertising industry, , accessed 24 January 2020. 14 , accessed 24 January 2020. 15 Tufekci (2015) 16 Zuckerman (2014) 17 , accessed 10 November 2020. A future in four fictions 1 Williams (2017) 2 Atwood (2012) 3 Hudson et al. (2020) 4 Wu (2010) 5 Schuh (2020) 6 Start (2017) 7 Street (2019) 8 Nass et al. (1994) 9 Devlin (2018, p. 95)

278

Index Page numbers in italics refer to notes 11 September 2001 135 1950s 132–33, 146, 196, 203 1955 132, 139, 148, 168, 251 1960s 68, 145–46, 149, 155 1970s 145, 148, 155, 159, 196 1980s 11, 50, 73, 91–92, 119, 146, 149, 152–54 1990s 146, 149, 196–97, 50 Cent 186 abortion 145, 151–53, 168, 191 abuse 99, 105, 112, 117, 123–27, 130, 151, 161, 171, 224, 247 controlling coercive 99, 123–27, 130, 161, 171, 188, 224, 238, 244, 247 emotional 112, 123, 130, 247 financial 112 online 174 physical 99, 112, 123 role of technology 123–25, 130, 247 sexual, of children 156, 158 accidents 50, 151, 185 Adam and Eve 1 Adams, Douglas 233–35 adolescents 27, 59, 63–64, 70, 80–81, 122–23, 157, 180 advertisement, newspaper personals 20 advertising 26, 48, 76–78, 83, 129, 162, 172–74, 222–30, 239–41, 245, 249 click-through rates 223 internet business model 26, 129, 222–32 sex in 162 sexual services 172–74 targeting or personalisation of 76–78, 83, 222–30, 239–41, 249 Afghanistan 200

Africa 36, 42, 52, 89, 137, 141, 143, 152, 189, 211 Afrikaner people 137 age of consent 7, 122–24 age-appropriateness of relationships 122–24, 146 aggression, animal 28–31, 37, 44, 87 aggression, human 41, 44, 156–58, 191, 238 Agincourt (battle) 200 agriculture 40, 140–44, 162, 201, 235, 247 and civilisation 162, 201 and gender relations 141–43, 201, 235, 247 AIBO, robotic dog 31–33, 47, 66, 130 Akiba-kei 214–16, 248 alcohol see drugs and alcohol Alexa, Amazon virtual assistant 21–22, 103, 130, 169, 227 algorithm 4, 6, 8, 11, 15, 17–21, 24–26, 28–33, 45–48, 76–80, 82, 85, 113, 115, 118, 121, 128, 130, 149, 206–10, 222–23, 226–27, 234, 239–41, 245 animal learning as 47–48, 76 building friendship, intimacy, attraction or love 51, 73–79, 127–28, 226–27, 234, 240–41 evolutionary selection as 28–33, 47 exploitative 113, 115, 128, 130, 222 love as 51, 73, 75, 104–107 matchmaker see matchmaker, algorithmic organisms as 8 science as 75, 77 see also machine learning Ali, Muhammad 186 Alibaba.com 48, 240 alliances 36, 52, 152, 154, 199, 215, 238, 242 allogrooming see grooming

279

ARTIFICIAL INTIMACY

alpha males see males, alpha Amazon rainforest 135–36 Amazon.com 21, 48, 240 America, Central 141, 143 America, North 50, 229 America, South 135–36 America, United States of (USA) 50, 59, 80, 86–87, 133–34, 139, 146, 148, 151, 152–53, 155, 157, 173, 196–98, 200, 202, 210, 235–36, 239 Anegasaki, Nene see LovePlus anime 70, 213–15 anthropology 71, 133–39, 141, 143, 160, 219 anthropomorphism 69, 99, 102–103, 113, 169–71, 227 antisociality 156, 201 anxiety 22, 30, 64, 68, 80–81, 104, 194, 249 apartheid see South Africa apes 4, 29, 35–43, 52 see also chimpanzee, gorilla Apollo, Temple at Delphi 35 Apple corporation 21, 64, 240–41 Arab Spring 239 Aristotle 94 Arizona, USA 133–34 Arkin, Ron 32–33, 254 arms races 46, 89–90, 115–16, 124 Arnqvist, Göran 87–88, 98–99 Aron, Arthur and Elaine 74–79, 111 artificial intelligence (AI) 2, 4, 6–11, 15–16, 18, 21, 33, 45–49, 67, 69–73, 77–83, 101–103, 114, 121, 123, 129–130, 169, 171, 173, 175, 204, 209, 220, 227, 234, 237, 245 artificial general intelligence (AGI) 4, 48, 245 replacing human jobs 11, 204 artificial intimacies 2–3, 11–15, 23, 26, 33, 44, 66, 73, 79–85, 103, 106–107, 114, 118, 125, 129–130, 173, 203, 216, 218, 224, 229, 231, 234–35, 238, 244–45, 247, 250–251 see also virtual friends, digital lovers, matchmakers Asia 187 Asia, East 28

Asia Minor 143 Asia, South-East 143, 189 ASMR, autonomous sensory meridian response 22, 25 Assistant, Google’s virtual assistant 21, 84, 103 assistants, virtual 14, 21–24, 80, 84–85, 102–103, 106 Athens, Georgia, USA 86–87, 99 attractiveness/attraction 3, 26, 35, 87, 115, 117, 119, 125, 134, 139, 142, 150, 168, 167, 178, 183–84, 192–94, 196, 198, 202, 205–10, 215 Atwood, Margaret 122, 236–37 Austerlitz (battle) 200 Australia 20, 80, 112, 117, 120, 146, 151, 170 Austria 169, 199–200 autonomous weapons 11, 237 Autor, David 197–98 ‘average frustrated chump’ (AFC) 125–26 baboon, Chacma 52 Bacchus, cult of 164–66 Back to the Future movie series 168, 238–42, 251 backpage.com 172–74 Baidu 21, 240 Become a Pickup Artist (app) 128 Belyayev, Dmitry 30 Berkowitz, Erik 122, 163 Berry, Chuck 186 Bertrand, Marianne 196–97 beta males 92–93, 182–83 Betzig, Laura 143 bin Awad bin Laden, Mohammed 188–89 bin Laden, Osama 188 Blake, Khandis 192–93, 197–98, 253 Blanc, Julien 127 Boko Haram 189–90, 211–12, 237 Bondar, Carin 99 bonding, emotional 7, 30, 33, 37, 40 human-machine 33, 245 Bongo, Ali 46 Bonobo see chimpanzee, bonobo Boserup, Ester 141 Bosson, Jennifer 57

280

Index

brain, human 29, 42, 44, 52–54, 57–58, 104–105, 219, 250 brand (marketing) 14, 21–22, 38, 83, 172, 223, 225–27, 229, 240 Braze 229 Brazil 135, 185–86 breaking up 70, 78, 112, 159 Breivik, Anders 157 Brexit 230, 251 bride price 133–36, 143, 189–90, 201–202, 211–12 Brinkman, Baba 32 Brown Simpson, Nicole 99 bubbles, thought or social media 5, 65, 151, 222–25 Call of Duty: Modern Warfare 157 Cambridge Botanic Gardens, UK 91, 93 camming, camera models 18–19, 25, 219–220 Campaign Against Sex Robots (CASR) 101, 168, 171, 176 Canada 140 Candy Crush Saga 12, 234 Cannae (battle) 164–65, 200 capitalism 96, 100, 215, 220 carrotdating.com 173 Castro, Fidel 188, 212 casual sex see sex, casual catfish, catfishing 14, 110–16, 130 digital/deepfake 14, 113–16, 130 Catron, Mandy Len 74–75 censorship 153–54, 168, 242–43 cerebral neocortex see cognitive capacity chatbot 7, 22–23, 68–70, 81, 102–103, 113, 169, 227, 246 Chibok, Nigeria abduction of schoolgirls 190 childbirth 42–43 chimpanzee, common and bonobo 36–43, 94, 133, 183, 270 China 141, 143, 180, 191, 195, 197–98, 211 Chiricahua Apache people 133–40 Christchurch, New Zealand, mosque massacre 195 Christians, Christianity see religion cichlid fish 89–90

Clash of Clans 217–18 class, social 133, 183, 220, 236 coercion, sexual see sexual coercion cognitive behaviour therapy (CBT) 80–81 cognitive capacity 2–3, 12–13, 52–56, 62– 65, 85, 112, 129, 175, 224, 227, 249 for maintaining relationships 52–56, 62–63, 65, 112, 129, 175, 224, 227, 249 cognitive revolution see intelligence, evolution of human Cohen, Leonard 123 Columbine High School shooting 156–57 communication 4, 41, 64–65, 74, 78–79, 110–11, 144, 233, 237, 239, 240, 243, 249 computer games see games, computer computers as social actors 69, 102, 113, 168–71, 226–27, 245, 273 confessor, confession 14, 23 confidence tricksters see fraud conflict 4, 38, 42, 88-93, 97–99, 106, 133– 34, 151, 161, 189–91, 194, 200, 226 see also sexual conflict consent, sexual 72, 122–25, 127, 130–31 241, 244, 248 conservatives, social 38, 132–33, 137, 147, 151, 152–54, 162, 165–68, 172, 176, 196, 198, 203, 210–11, 236, 243–44, 251 aversion to unrestricted supply of sex 132–33, 147, 152–54, 165–68, 172, 176, 203, 236, 243–44, 251 contraception 2, 144–45, 168, 188 conversation 7, 9, 12, 50, 52–53, 56–60, 62–63, 66, 69, 71, 75, 77–79, 81, 108– 109, 111, 118, 121, 125, 129, 136, 207, 224, 227, 229, 249 see also gossip cookies 227, 240–41 cooperation 2, 4, 11, 28, 33, 40–41, 44, 58–59, 90, 98, 105, 180, 234 coronavirus, coronavirus pandemic 2, 18, 24–26, 61, 65, 80, 83, 115 Cortana, Microsoft virtual assistant 21, 23, 103 COVID-19 see coronavirus Craigslist personals 20, 172–74 crime 154–58, 162–63, 178, 188–91, 194, 201, 211, 247 cuckoldry see infidelity

281

ARTIFICIAL INTIMACY

cuckoo, European 34 culture 5, 38–44, 46, 58, 70, 94–95, 100– 101, 113, 120, 134, 137–39, 141, 145, 147, 150, 151, 154, 158–60, 162, 180–82, 192, 235, 246–48 culture wars 3, 151–54, 248, 251 cybercrime, including cyberstalking 108–16, 122–25, 273 CyberLover 113, 273 cybersex 18–19, 176, 220 Cyrus, Miley 165 Dabulamanzi (Zulu commander) 200 Darcy, Alison 80 Darwin, Charles 29, 37, 86–87, 96–97 data 4, 7–8, 13, 15–16, 20–21, 24, 26, 43, 45–49, 76–78, 81, 85, 114, 118, 128, 154–55, 159, 175, 192, 196, 204–207, 217, 222–23, 225, 227–32, 233, 239, 240, 247, 250 machine learning on 7–8, 13, 15–16, 20–21, 24, 26, 45–49, 76–78, 85, 118, 128, 204, 206, 225, 240–41 privacy and violations thereof 26, 111, 113, 175, 227–32, 240–41, 250 date, dating 14, 20, 25, 108, 117–21, 125– 28, 159, 173, 178, 192, 204–10 dating apps/websites 20, 25, 108–10, 113, 117–21, 123–24, 129, 204–10, 224, 229 dating sim games 71–73, 213–14 Davies, Nick 34, 91–92, 272 deception, sexual 100–101, 106–107, 117–24 deep learning, deep machine learning 45– 46, 114–16 see also machine learning deepfake 46, 113–16, 220 demand, mating market 119–20, 147, 150, 159, 162, 166–67, 177, 190, 203–206, 210–13 Denmark 155 Department of Justice, USA 155, 195, 275, 277 Depp, Johnny 212 depression 22, 31, 64, 80–81, 191, 194, 215, 249 Devlin, Kate 84–85, 245, 254, 270, 273, 275

Diana, Princess of Wales 50–51, 59 di Caprio, Leonardo 155–56 digital lovers see lovers, digital digital marketing see advertising disclosure, in building intimacy 51–52, 73–79, 82, 103, 111, 223–27, 245 divine punishment/retribution 151–53, 162, 164 divorce 78, 111–12, 136–37, 151, 193, 197, 244, 274 DNA paternity analysis 92–93, 137–39 Dodge, Adam 123 Dodson, Betty 160 Dogon people 138 dogs domestic 27–32, 47–49 domestication of 28–32, 47, 269 robotic 31-33, 47, 66–67, 130 dollbots see robots domestication animal 2, 28–32, 35, 40, 47, 69, 269 human 4, 27–28, 35, 40–49, 53–54, 65, 133, 144, 270 plant or crop 2, 40, 140–42 domestication syndrome 29–30, 32 dominance in humans 41, 131, 144, 183–84, 201, 211, 238, 272 in non-human animals 36, 38, 93, 183 Doom (video game) 157 Dorn, David 197–98 double standard, sexual 134–39, 141–44, 147, 151, 163, 241–42, 247 drugs and alcohol 65, 80, 106, 114, 147, 164, 194, 229 Duer OS, Baidu virtual assistant 21 Dunbar, Robin 52–57, 61, 254 Dunbar’s number 52–53, 61 dunnock 90–93, 97–98, 142, 161, 183, 247, 272 Dworkin, Andrea 153–54, 156, 162, 168, 244 economic inequality see inequality economy 26, 39, 197, 201, 216, 231 Edlund, Lena 191 Egypt 143

282

Index

ancient 143, 188 elections 11, 142, 151, 152, 181, 195, 198, 204, 224–25, 227, 230, 239, 250 elites, in historic societies 162–65, 187–88, 233, 239, 242, 277 ELIZA 22, 68–69, 73, 80, 169, 271 email 63, 108, 110, 117–18, 229 Endurance (company) 81–82, 271 engagement ring 145–47 Engels, Friedrich 141, 274 England 59, 93, 98, 122, 200 Epstein, Jeffrey 212 Equal Rights Amendment (USA) 153 equity see gender equity Europe 165, 228 Eve (and Adam) 1 evolution 4–5, 11–12, 27, 29, 30, 33, 35–36, 39–41, 43–44, 47–48, 53, 56–58, 60, 66, 86, 88, 91, 93–94, 96–99, 104–105, 115–16, 120, 133, 139, 161, 163, 182–83, 185, 193, 219, 223, 227, 249–50 evolutionary biology 3, 38, 86, 88, 91, 96–99, 120, 269 evolutionary psychology 182, 185 Facebook 2–3, 24, 26, 48, 60–66, 77–78, 82, 124, 129, 179, 222, 230–31, 240–43, 245 FaceTime 18, 24 facial recognition tools 45, 237 Falwell, Jerry 152–54, 162, 236 family, families 3, 11–12, 42–44, 48, 50, 54, 59, 64, 81, 91–93, 98, 112, 121, 132–42, 143, 149, 151, 152–54, 166, 168, 176, 187, 189, 191, 196, 203, 214, 218, 221, 236, 252 Farley, Melissa 174 farming see agriculture fathers, contributions to family 42–44, 134–40, 201–203, 214 Federal Bureau of Investigation (FBI), USA 111, 174 feminism 38, 101, 153–55, 158, 166, 168– 69, 172, 181–82, 243, 250–51 anti-porn or sex-negative 153–55, 159– 161, 168–69, 174–76, 243, 250–51 radical 153–54, 168–69, 172, 182

sex-positive 160–61 feminist sex wars or porn wars 159–61 fertility 43, 142, 145, 235, 237 fighting 38, 52, 58, 78, 151, 154, 162, 170, 185–87, 190–91, 194, 200, 237 see also conflict, violence, war Final Fantasy (computer game) 214 Find my iPhone (app) 124 Finkel, Eli J 207–208 fishing see foraging societies flatworms, penis-fencing 99 following and unfollowing on social media 51, 59, 63, 78 football 87, 117, 126, 185–86 foraging societies 28, 31, 40, 53, 142, 133–140 FOSTA-SESTA laws USA 174–75 fox, silver, domestication of 28–33, 35, 44, 47 France, French Empire 199 Francis, Emperor 199 fraud romance scams 109, 113–16 ‘freemium’ business model 217–22, 224, friendly brand 14, 83, 226–29, 240 friends 2–3, 6, 12–22, 26–28, 33, 44, 50– 58, 60–67, 70, 74, 77–79, 99, 102–103, 111–18, 125, 129, 149, 160, 178, 206, 212, 218–27, 229–34, 239–46, 248, 250 active social network 52–56 constraints on numbers 52–58, 61 Facebook 60–63, 77, 129, 245 virtual 6, 14–17, 19–24, 26, 66, 77, 79–85, 102–103, 113, 115, 118, 125, 129, 212, 218–32, 237, 239–46 friendship, transactional basis 218, 221 functional magnetic resonance imaging (FMRI) 219 fundamentalists, religious 1, 172 Galbraith, Patrick 71 ‘game’ see pickup artistry games, computer 2, 12, 14, 47, 59, 67, 70–73, 79–82, 106, 156–58, 213–15, 217–19, 233–35, 275 see also dating sims role-playing 213–14 and violence 157

283

ARTIFICIAL INTIMACY

gamification 71–72, 75, 81–82, 130, 158, 221 gender 16, 82, 84, 96–97, 140–54, 160–62, 166–68, 176, 179, 182–83, 192–93, 206, 209, 212–14, 235–38, 247–48, 251 attitudes concerning 96, 132, 212–13, 238 conformity 84, 99, 149, 182, 206, 209, 235–36, 243, 247–48 equity 38, 95, 140–48, 153, 192–93, 197, 239, 247, 251 exploring or realising 16, 82, 84, 247 nonbinary, queer or trans 82–84, 97, 99, 149–51, 160–61, 168, 176, 206, 209, 248 norms and roles 141, 145–47, 151, 153, 168, 197, 214, 242, 247 gender relations 132, 140–48, 154, 160–62, 166, 212–13, 238–39, 235–36, 251 General Data Protection Regulation 228 generative adversarial networks (GANs) 46, 114–16, Genghis Khan 187–88, 247 Germany 146, 155, 158, 237, 275 Nazi regime 237 Geronimo (Goyaałé) 133–34 Get a Girl (app) 128 Get Any Girl (app) 128 Gini index of income inequality 196–97, 205 globalisation 197–98 Goldgeier, Aviv 205 Goldman, Ronald 99 Goldstein, Nikki 9–10, 254 Google 21, 45, 48, 84, 99, 210, 222, 230, 234, 240–41, 245 image search 109, 116 maps 234 gorilla 41, 183 gossip 50–51, 56–61, 63, 66, 111, 121, 129, 188, 214, 249 Greek mythology 1, 23–24, 35 Gregor, Thomas 135 Grindr 20, 229 grooming 36, 50–67, 73–74, 78–79, 82–83, 111–12, 123, 125, 129–30, 139, 146, 189, 223–27, 234, 244, 249, 270 see also

allogrooming group chats, online gynoid see robot, gynoid Handmaid’s Tale, The 235–39 Hannibal 164, 200 Hanson, Robin 202 haptic devices 17–18 Harari, Yuval Noah 8, 42, 104 harassment, sexual 88, 99, 172, 178–79 harems 41, 143, 183, 187, 201 Harmony (sex robot) 7, 9–10, 34, 83, 234 Harris, Erik 157 Harry, Prince, Duke of Sussex 50–51, 59 Hebb, Donald 95, 272 Henrich, Joseph 42 Henry V (King) 200 Henry VIII (King) 193–94, 212 Her (movie) 103–107, 244–46, 249, 251 herding livestock 133, 135–37, 141, 190 Hesiod 1 heterosexuality 133, 144, 205–206, 248 hikikomori (acute social withdrawal, Japan) 215–16 Himba 136–39, 189 Hines, Douglas 6 Hinge (app) 20, 205 Hobbs, Susan 64 homicide 99, 112, 151, 158, 163, 194, 243, 276 intimate partner 99, 112 man-on-man 99, 151, 194 homophobia 100, 152–53, 159, 166 homosexuality 20, 97, 100, 145, 148, 152– 53, 159–62, 165, 168, 176, 229, 247–48 hookup 14, 18–20, 25 hormones 30, 104–106, 194 household chores 99, 197, 134, 141–42, 148, 153, 214 Houseparty (app) 24 Houston, Texas USA 168 Hudson, Valerie 189–90, 238 human immunodeficiency virus (HIV) and AIDS 116, 152, 166 hunter-gatherers see foraging societies Hustler magazine 149 hypergyny 143–44

284

Index

ideological conflict 3, 94, 149, 161, 212, 244, 251 image recognition 114, 116, 124 immune system 115–16 InCels 177–98, 199–203, 206, 211–16, 231 indecency 154, 166 India 42, 123, 141, 143, 180, 191, 211 Indianapolis, Indiana, USA 153 Industrial Revolution 144 industrialisation 2, 42, 141, 144, 146, 149, 196–97 inequality, economic 140–44, 188, 191–98, 203–204, 211, 215, 235, 239, 250 effects on mating markets 191–98 inequality, gender see gender inequality inequality, sexual 41, 121, 153–54, 193–94, 201–15, infidelity 133–36, 138, 142, 163 Instagram 24, 48, 51, 59, 62, 64, 78, 124, 149–50, 172, 192, 228, 240–43 intelligence 21, 40–44, 88, 246 artificial see artificial intelligence evolution of human 40–44, 88 internet 4–5, 16–17, 20, 24, 48, 60, 64, 72, 110, 113, 116, 126–27, 148–50, 153–58, 167, 172–75, 204, 206, 222–24, 228–30, 236, 239–41, 277 browsers 240–41 neutrality and openness 173–75, 239–41 intimacy 2–5, 9–10, 12–15, 18, 21, 24, 33, 36, 44, 51, 54–56, 61–62, 66–79, 82–85, 99, 102–103, 106, 111–13, 125, 130–31, 149, 151, 166–67, 203, 210, 220–21 artificial see artificial intimacy building 44, 45, 51–52, 61–62, 66–79, 82, 103, 111–12, 121, 125, 130–31, 223–27, 245 incorporation of another in one’s sense of self 51, 73–79 involving machines 9–10, 12–15, 21, 33, 68, 70–73, 76–79, 82–85, 99, 102–103, 121, 125, 166–67, 203, 220–21, 226–27, 234 iPhone, Apple 21, 45, 62, 124, 218 Iran 237 Iraq 162, 200

Ireland 151 IRL, in real life 14, 63, 73, 123, 157–60, 175, 177, 206, 252 ISIS 237 Isla Vista, California USA 177–79, 195 isolation, social 2, 13, 24–26, 112, 250 Izquierdo, Isabel Behncke 38, 245 Japan 32, 70–71, 155, 170, 213–16, 248, 277 jealousy 44, 56, 93, 124, 134–38, 274 Jethá, Cacilda 39, 274 Jobs, Steve 64 Johansson, Scarlett 103, 245 Jonze, Spike 244–45 Judson, Olivia 99 Kakuhido (Upopular Revolutionary League) 215–16 Kamenica, Emir 196–97 Kant, Immanuel 100 Kardashian, Kim et al 50, 59, 193, 223 Kellogg, John Harvey 150 Kendall, Todd 157–58 Kilner, Rebecca 34–35 kink 131, 160, 176 kissing 38, 83, 173, 230 Klebold, Dylan 157 Korea, South 213 LaFrance, Adrienne 66 Lagos, Nigeria 109 language 21, 41, 45, 56–58, 82, 206 ‘last wall standing in the landscape of knowledge’ see nature–nurture dichotomy law 122, 153, 162–65, 173–75, 200–203, 228, 238, 248, 250–51, 274 internet neutrality 236 regulating marriage 201–203, 248, 274 learning, animal 8, 32–33, 47–48, 66, 76 learning, in humans 28, 44, 47, 58, 63, 71, 81, 113, 125, 127, 131, 181, 270 learning, machine see machine learning Levant region, western Asia 141, 163 LGBTQI+ people 229, 247–48 see also homosexuality, gender liberals, liberalism 152, 182, 198, 202, 210

285

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libertarians 182, 202–203 livelihoods and how they shape gender relations 2, 105, 132–40, 166 livestock see herding Livy 164 loneliness 24, 108–11, 181, 218, 221, 224, 231, 247 see also isolation, social love 102–108, 111–12, 117, 123, 127, 129–30, 132–27, 145–49, 165, 176–77, 213–14, 218–19, 232, 234, 245–46, 273 as defence against sexual conflict 104–107 computers emulating 7, 102–103 falling in 7, 70, 72–79 humans loving machines/artificial intimacies 102–103, 106–107, 245 in relation to marriage 132–33, 136–39, 145–48, 165, 176, 196, 213, 248 machines loving humans 106–107, 125, 245 LovePlus (computer game) 70–72, 82, 103, 130, 214, 234 lovers, digital 6, 14–15, 26, 80–85, 99, 101–102, 113, 118, 130–31, 166–72, 176, 210–12, 219–23, 229–31, 236–37, 241–43, 246–48 Lucretia 163–64 luxury goods 159, 167, 212, 236, 241, 250 Machiavellians 101 machine learning 7–8, 11, 13, 16–26, 35, 44–48, 67, 70, 73, 76–79, 82, 85, 114–16, 124, 128, 130, 149, 206, 208–209, 223–29, 240–41, 245 see also artificial intelligence 8 MacKinnon, Catharine 153, 156, 168 magazines 11, 50, 59, 149, 153, 155, 168, 188 males alpha 58, 41, 92–93, 182–83 beta 92–93, 182–83 Mali, West Africa 138 malware 113 ‘man drought’ 119–20 manga 213–15, 277 manipulation 1, 5, 93, 100, 123, 126, 130, 225, 228

manosphere 178–84, 197, 202–203, 215 manufacturing, loss of American jobs in 197–98 Maradona, Diego 186 Marie-Louise, Austrian Archduchess and Empress of France 199 Markle, Megan, Duchess of Sussex 50–51 marriage 132–39, 143, 145–51, 154, 159, 163–68, 176, 188–97, 199, 201–203, 211–14, 216, 241–43, 247–48, 251 declining rates of 159, 162, 168, 196– 97, 202–203, 243, 251, 274 markets 135, 145–47, 159, 163–68, 196–97, 212, 247 same-sex 148, 162, 243, 248 and social mobility 145, 193 Marx, Karl 96, 141 masculinity 38–39, 143, 185, 199, 201–203, 214–15, 248 in Japan 214–16, 248 toxic 177–182, 185, 199, 203 masturbation 15–19, 25, 84, 101–102, 145, 150, 159, 220 matchmakers, algorithmic 6, 14–15, 18–21, 25–26, 45, 66, 80, 82, 85, 118–119, 121, 149, 172–75, 203–10, 223, 245 matchmakers, human 209 Matfess, Hilary 189 mating markets 135, 143–45, 161, 164–70, 180, 188, 190, 198, 203–204, 210–12, 214, 220, 227–30, 234, 240–42, 247–50, 275 mating preferences men’s 95–96, 194 women’s 95–96, 192–94 weighting of criteria 95–96, 192 matriarchy 39 McCord, Mary 195 McNair, Brian 158 media, popular 9–10, 50–51, 83, 95–96, 109, 116, 158, 169, 222–23 media, social see social media Mehinaku people 135–39 Melanesia 189 men 2, 6, 39–43, 58, 70–71, 95, 98, 105, 132–144, 166, 214–16, 248 allegiances between 238–39

286

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contributions to family 132–40 mating preferences 95–96, 119–20, 125–26 see also males, masculinity, paternity, poverty, violence, war, young male syndrome Mend (app) 68–70, 80 menopause 43 menstrual taboos 137–38 mental health 65, 70, 80–81, 191, 250 see also anxiety, depression Merry, Sally 81 Mesopotamia 141, 162–63 MeToo movement 188 Minassian, Alek 179, 195, 215 Minneapolis, Minnesota, USA 153 misogyny 178, 181, 198, 215, 239, 242–44 money 9, 43, 95, 110, 114, 116, 123, 141– 44, 166, 173, 175, 183–85, 190, 194, 198, 202, 212, 218–22, 229, 249 Mongol Empire 186–88 monkeys 36–37, 52 monogamy 40, 133–140, 146–48, 167, 194, 201–203, 206 capacity or knack for 40–44, 133, 194 dunnock 92–93 marriage laws 201–203 Moon, Youngme 226–27 ‘Moral Majority’ 152, 236 moralism 97, 131, 152–54, 236 Morgan, Robin 154–55 Morocco 143 Morris, Reverend Francis Orpen 90–91, 94–98 Mumbai terrorist attack on Taj Mahal Palace Hotel 189 murder see homicide Mystic Messenger (computer game) 72, 214 Namibia 136–37, 189 Napoleon 199–200 narcissism 23–24, 121, 156, 254 Narcissus 23–24 natural language generation 21, 73 see also artificial intelligence natural language processing 21, 45, 70, 73, 79, 124 see also artificial intelligence natural selection see selection

naturalistic fallacy 96–97, 182 nature, human 1, 4, 39, 97, 180, 247 nature–nurture dichotomy 94–98, 161 Nazis see Germany negging 57, 126, 128, 130 neural networks, artificial 45–46, 114 neurotransmitters 104–106, 273 New Mexico, USA 133–34 Nietzsche, Friedrich 96 Nigeria 109–10, 180, 189, 195, 211 Nigerian scammers 109–10 Nineteen Eighty-Four 230, 236–37 Nintendo 70–71, 213 Noble, David 34 non-monogamy 18, 39–41, 100–101, 135, 142, 161, 188–93, 201 Norway 157–58, 228, 240 Norwegian Consumer Council 228, 240, 278 #NotAllMen 178–79 novels 72–73, 115, 271 Novosibirsk, Russia fox-breeding project at 30–33 nudity bans 242–43 Obama, Barack 46, 114 objectification, particularly of women 99– 102, 105, 153, 166–71, 242, 273 and sex robots 99–102, 168–71, 242 and violence 101, 166 sexual 100–101 oil production 143–44 OkCupid 119, 205, 207 OnlyFans 25, 242–43 Opler, Morris 134 Orwell, George 230, 236–37 paedophilia 166, 170 Pan, Jessica 196–97 Pandora, Pandora’s box 1–2 Paraguay 135 parasites 34, 49, 54, 115–16 human social 115–16 parental care and investment 40–44, 55, 56, 65, 89–93, 97, 99, 104, 123, 135–36, 151, 164, 183, 197, 201–203, 217 paternity 89, 92–93, 133–40

287

ARTIFICIAL INTIMACY

partible 135–36 testing see DNA paternity testing uncertainty 135–40 patriarchy 100, 143–44, 158, 164, 193, 214 Pelé 186 Pelosi, Nancy 114 penguins, same-sex couples 97 Penthouse magazine 149 ‘personalisation-privacy paradox’ 227 personals, personal advertisements 19–21, 172–75, 276 Peterson, Jordan B 202 Pezzutto, Sophie 219 phishing 110, 114, 116 Phoenix, Joaquin 103, 244–45 pickup artistry (PUA) 125–29, 178 Pinker, Steven 94, 246, 254 Pinterest 59 Plato 94 play 2, 28–32, 36, 38, 64, 139, 186, 207 sexual 18, 175, 212 see also games, computer Playboy magazine 11, 149 Poland 151 polarisation, political 64–65, 151, 161–62, 198, 230–31 politicians, political candidates 83, 225 politics 202–206, 210–11, 225, 229, 231, 238, 242–44 polyandry 92–93 polygynandry 92 polygyny 92–93, 142–43, 188–91, 193, 201–203, 241 and societal dysfunction 188–91, 201– 202, 241 Pompeii 150 populism 238–39 ‘porn wars’ see feminist sex wars PornHub 25–26, 222, 240 pornification, cultural 156, 159 pornography 11, 14, 16–18, 25–26, 46, 84, 99, 112–15, 145–46, 149–62, 166–74, 210–16, 219–22, 236, 240–44, 247, 250, 275 and sexual motivation 149–50, 158–62, 166–67 and violence 112, 153–58, 166, 170, 212–15

288

anime and manga 213–15 implications for relationships 145–46, 152–54, 158–62 revenge 46, 112–15 salutary effects 156–58 see also virtual reality pornography porntropreneurs 219 poverty 12, 95, 135, 143–44, 168, 184–86, 189–94, 201, 212, 235, 239, 250 power, economic or political 37, 39, 139, 139–44, 146–47, 164, 188, 190, 193, 201, 236–39, 241–42 in relation to sex 39, 122–23, 126, 139–44, 146–47, 156, 161, 188, 190, 193, 201, 236–42 Prall, Sean P 139, 254 praying mantids 89 predators animal 28, 31, 87, 89–90, 136 corporate 217, 221 human 136, 172 sexual 122–24, 172 preferences, mating 11, 17, 26, 35, 95–96, 119–20, 192, 205–10, 233, 248 pregnancy 42–43, 144–45, 151, 274 President of the USA 46, 152, 181, 198, 224, 230, 235–36, 238–39, 242, 251 price of sex 64, 119–20, 135–52, 158–62, 165–68, 177, 189–90, 203–206, 210–13, 235–36, 239, 242–44, 247 Prinz, Jesse 94 ‘pro choice’ or ‘pro-life’ see abortion progress, social 96, 143, 147, 149, 151–53, 179, 197, 231, 251 progressives 97, 126, 151, 158, 168, 202– 203, 244 promiscuity see non-monogamy prostitution see sex work prudishness 98, 163, 165, 243 see also Victorian modesty pudicitia 163, 243 Quake (video game) 157 racism 195, 243 radicalisation, radical groups 189, 191, 211–12, 231

Index

radio 65–66, 239 Rameses II (pharaoh) 188 rape 101, 125, 154–58, 163, 170–71, 178, 202, 243, 275–76 and sex robots 170–71, 243 rational–empirical dichotomy see nature– nurture dichotomy reading, decline in 73 Reagan, Ronald 152, 236 real life see IRL Reddit 12, 177, 180 redistribution economic 202–203 sexual 202–203, 209–10, 277 religion 1, 154, 163, 168, 172, 195, 206– 207, 210, 235 and porn consumption 201–11 Christianity 20, 23, 111, 152–53, 163, 210, 236–38 evangelical Christianity 152, 236–38 Islam 143, 195, 211, 237 Judaism 137, 163 reproduction 1, 3, 28, 35–36, 41–43, 47, 98, 105, 134 reward 44, 47, 105, 130, 217, 219–21 erotic 44, 105, 130, 219–21 in computer games 217 gambling 219 Richards, Keith 186 Richardson, Kathleen 101, 168–69, 172, 176, 254 Rio de Janiero, Brazil 185–86 risk-taking 36, 65, 144–45, 151, 174, 184– 85, 194, 201–12 robots 2, 6–18, 27, 31–35, 66, 83–85, 99, 101–103, 106, 129–30, 166–71, 175–76, 211–12, 220, 230–31, 242–45, 248, 250 android 10, 15, 212 ‘dollbots’ 7–10, 13–14, 33–5, 83, 129– 30, 169–70, 234 gynoid 10, 15, 34–35, 212, 244 sex 2, 6–18, 33–35, 83–85, 99, 101– 103, 106, 129–30, 166–71, 175–76, 211–12, 220, 231, 234, 236, 242–45, 248, 250, 273 Rocky (sex dollbot) 6–7, 13 Rodger, Elliot 177–79, 195, 215

Rogers, Carl 68–69 Rolling Stones 117–18, 125 romance 20, 56, 58, 67, 71–72, 82, 98, 105–106, 108–109, 112, 125, 130, 151, 214–15, 234, 245 romance scams 108–17 Romania 237 Rome, ancient 150, 163–66, 200, 242 Ronaldo Luís Nazário de Lima (footballer) 185–86 Rorke’s Drift (battle) 200 Ross, Michael 143–44 Rossellini, Isabella 99 Rowe, Locke 87–88, 98–99 Roxxxy Gold True Companion (sex dollbot) 6–7, 169, 234 Rubin, Gayle 160 Rudder, Christian 119, 205, 207 Rushkoff, Douglas 26 Russia 30, 81, 113, 143, 199–200, 239 Russo-Batterham, Daniel 197 Ryan, Christopher 39, 274 sadomasochism 160 Safe Schools Program 151 safe words 131 Sahel region, Africa 141 Sal 9000 71 sales, salespeople 33, 66, 73, 83, 127–28, 153, 226–27, 229–31 salmon 140 Salt, Bernard 120 Samantha (character in Her) 103–107, 244–46, 251 Samantha (sex robot) 7, 9, 169, 275 Santos, Sergi 169, 275 Sarkisova, Gayana 128 Saudi Arabia 188, 237 Scelza, Brooke 137–39, 254 Schlafly, Phyllis 153 Schuh, Justin 240 science, scientific research 1, 11, 16, 19, 31, 34, 38, 53–57, 68, 74–76, 81–82, 86–87, 94–96, 98–99, 137, 151, 155, 171, 180, 182, 194, 207, 209, 250, 271 scientific method 74–76, 182 seahorses 97

289

ARTIFICIAL INTIMACY

seduction 73, 87, 100, 125–29, 163 seekingarrangement.com 172–74 Sega 213 selection artificial or deliberate 29–32, 47, 141 natural 8, 28, 30, 47, 76, 86–87, 96–97 sexual 86–88 self-knowledge 35–36, 96 selfies, sexy 148–50, 167, 192–93, 275 sex dolls 2, 6–7, 10, 101, 166, 170 sex, intercourse as a social exchange/transaction 37, 43, 92–93, 100, 135, 143–48, 158–62, 172, 210–13, 219, 221, 235–38, 241, 247–48 as a high-priced luxury 159, 212, 236– 38, 241, 250 casual 14, 18–20, 25, 148, 159, 161, 164, 172, 175, 200 outside of marriage 78, 98, 134–38, 148, 210, 212, 274 premarital 134, 148, 274 remote 210–11 virtual 14, 18, 158, 166, 175–76, 210–11 sex market see mating market sex ratio 119–20, 164–65, 184–85, 188–92, 197, 211 female-biased 120, 164–65 male-biased 119–20, 190–91, 197, 211 sex robots see robots, sex sex toys 9, 14–19, 25–26, 84, 101–102, 220, 234, 250, 269 smart 14–19, 84, 234, 250 teledildonic 15–19, 25, 101, 175–76, 220, 234 sex trafficking 154, 172–76, 236 sex work 14, 18–19, 25, 160–62, 168–69, 172–76, 210–11, 220, 236, 242 and the internet 19, 25, 172–76, 210–11 virtual reality see VR sex work sexism 134–39, 141–44, 147, 151, 163, 178–79, 181, 198, 215, 239–42, 247 Sextus Tarquinus 163–64 sexual assault 101, 151, 126, 155–71, 215, 243, 275

attitudes concerning 156–57 sexual autonomy/freedom 161–65, 172, 236, 243–44 sexual cannibalism 89 sexual coercion 87–88, 123–130, 161, 171–74, 188, 235, 244 sexual competition 40, 44, 86–87, 93, 98, 120–21, 142–45, 161, 165, 167, 183–84, 189–91, 201–202, 214–15, 247–48, 275 sexual conflict 4, 86–93, 98–101, 106, 161 sexual excess/degeneracy 164, 166, 242–46 sexual fantasy 6, 16, 131 sexual harassment see harassment, sexual sexual permissiveness 135–36, 138, 145–49, 151–54, 158–65, 168, 176, 212–13, 233, 242, 246–48 sexual revolution 3, 144–51, 152–59, 162, 167, 197, 203, 213, 239, 247–49, 251 sexual suppression 138, 145, 147, 150, 159– 61, 176, 235–39, 243–46, 248 sexual violence see violence sexualised social media images see selfies, sexy sexuality 16, 97, 145–49, 151–53, 158–62, 168, 176, 184, 206, 209, 212–14, 229, 235–37, 242, 244, 247–48, 251, 274 Shakespeare, William 104, 221 Simpson, Nicole see Brown Simpson, Nicole Simpson, OJ 87, 99 Sinatra, Frank 132, 139, 145–47 single parents 196–97, 243 Siri, Apple’s virtual assistant 21, 103, 227, 245 smart phone 7, 11, 13, 19, 22, 25, 63, 69–70, 75, 80, 83–84, 124, 128, 155, 194, 249 Smith, Adam 96 Snapchat 3, 78 Sobhuza II (Swazi king) 188 social control 235, 237–38 Social Darwinism 96–97 social media 2–3, 12–14, 19, 23–25, 46, 50, 59–67, 76–82, 85, 109, 111–13, 118, 167, 172, 174, 178, 192–93, 218–19, 222–25, 227, 231, 234, 237, 242–43, 249, 270 social medium 14, 82–83, 223–25, 229, 240 Sony corporation 31–33, 66

290

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sōshoku danshi ( Japanese ‘grass-eater men’) 214–16, 248 South Africa 137, 152, 205, 237–38 apartheid regime 152, 237 South Sudan 189–90, 195 Spencer, Herbert 96 sperm 40–41, 87, 89, 93, 181 sperm competition 40–41, 89 Spotify 22, 25, 76, 271 Squire, Arran Lee 169 stalking 99, 122–25 status 58, 163 and mating / reproduction 37–38, 43, 95, 135, 140–43, 178, 183–194, 202, 212, 236, 241–42, 250 Strassmann, Beverly 138 Strauss, Neil 125, 128 substance abuse see drugs and alcohol substitutes for sex, low-price 3, 10, 129, 150, 159, 166–67, 175–76, 210–13, 244, 247 see also technology substituting for human functions Suddendorf, Thomas 41 Sugarbabies and Sugardaddys 172–73 suicide 64, 164, 191, 249 Sumeria, ancient 162–63 supply, mating markets 84, 119–20, 139, 145–47, 159–67, 177, 190, 203–206, 210–13, 237 appearance of high supply 150, 159–60, 165 Sweden 155 Sydney, NSW 3, 9, 24, 117, 119 taboos, menstrual see menstrual taboos Takagi, Shin 170 technology, consequences for sex and relationships 2, 133–51, 175, 204, 213, 220, 245 for ways women and men make their livings 6, 105, 132–44, 166 harmful 1–5, 10, 13, 46, 64–66, 85, 117, 119–24, 228–30, 244, 249–51 salutary 3, 10, 65, 120, 204, 212–16, 247–51 substituting for human functions 3, 10,

12, 62–65, 71–72, 85, 112, 129–30, 150, 159–60, 175, 246, 249–50 using time and cognitive capacity usually used by people 2–3, 12–13, 54, 62– 65, 85, 129, 175, 224–25, 249 teenagers see adolescents Tegmark, Max 48, 270 teledildonics see sex toys, teledildonic telegraph 65–66, 173, 239 telephone 22, 65–66, 173, 184, 239 television 50, 64–66, 133, 167, 239, 243 terrorism 153, 157, 189–91, 195 testes, testicles 38, 40–41 therapy/therapist 22–23, 68–69, 77, 80–81, 170, 221–22, 229, 231, 250 app/AI 14, 22–23, 66, 69, 77, 80–81, 221–22, 229, 231, 250 involving sex dolls / robots 170 TikTok 3–5, 59, 78, 240 Tinder 15, 18–20, 25–26, 129, 148, 204, 208–209, 245 Tokimeki Memorial (computer game) 214 totalitarianism 235–38 toxic masculinity see masculinity ‘traditional’ marriage 132–140, 147–48, 151–52, 236 transgender 154, 160–61, 176, 248 Trump, Donald 46, 114, 181, 198, 223, 230, 235, 238–39, 242, 251 trust 51–52, 55, 73, 81, 83, 104–106, 111–12, 115, 122–23, 137, 201, 225–27, 234 trustworthiness of media 5, 151, 222–26 Trut, Lyudmila 30–33, 269 Tufekci, Zeynep 230–31 Tunisia 143 Turing, Alan 69, 271 Turkey 239 Turkle, Sherry 12, 62 Twenge, Jean M 64–65 Twitter 12–13, 23–24, 48, 59, 63, 78, 124, 127, 172, 178, 192, 197–98, 223, 240, 271

Ultimate Fighting Championship 38 UNSW, The University of New South Wales 3, 8, 24, 129, 253–54

291

ARTIFICIAL INTIMACY

Ur-Nammu (Sumerian King) 162–63 user data see data, user Valentine’s Day 77, 215 Venezuela 143 vestal virgins 164 Victorian modesty 98 video games see games videos, music 165, 168 violence 41, 87, 151–158, 162–72, 180–85, 189–98, 201–203, 215, 243–48, 270, 274–75 among men 41, 157, 168, 183, 185, 189–91, 194–98, 201–203, 215 decline over time 246–48 in movies and computer games 155–57, 275 intimate partner 123, 151 see also abuse sexual/gendered 99, 101, 123, 151, 153–58, 162, 166, 168, 170, 172, 178, 201–202, 213, 215, 248, 274 see also sexual assault, rape toward LGBTQI+ people 229 virginity 134, 164, 178 virtual assistant 14, 20–22, 24, 80, 84–85, 102–103, 106, 245 see also Alexa, Assistant, Cortana, Duer OS, Siri virtual friends see friends, virtual virtual reality or VR 2, 14, 16–19, 26, 72, 84, 130, 158, 166–67, 176, 210–13, 220, 244–45, 248–50, 276 characters in games 14, 72, 84, 244 lover 14, 72, 83–85, 102, 130, 248 pornography 14, 16–18, 26, 84, 130, 175–76, 210–11, 244, 250 sex 14, 18–19, 99, 158, 166, 175–76, 210–11, 220 sex work 14, 19, 25, 175–76, 210–11, 220 virtue, virtus 163 von Hippel, Bill 42, 254 von Metternich, Prince Klemens 199–200 voting see elections VR Kanojo 72 Walsh, Toby 8, 129–30 war 134, 185, 196, 199–200, 205, 237 deaths in 199–200

numerical advantage in 200 warbler, reed 34 Ward, Michael 157 water striders 3, 86–89, 272 wealth 95, 121, 135, 140–44, 164–65, 173, 178, 183, 188, 191–94, 201–204, 235–38, 241, 247, 272, 277 as determinant of reproductive success 95, 121, 135, 140–44, 173, 178, 183, 188, 191–94, 201–202, 238, 272 weapons, animal 87–89 weapons, autonomous 11 weevils, bean 89 Weinstein, Harvey 212 WEIRD (White, Educated, Industrialised, Rich and Democratic) places 179–80, 195–96, 202, 211, 215 Weissmann, Jordan 202 Weizenbaum, Joseph 68–69, 271 Wenzler, Nathan 111 Westworld 9, 243–44, 251 Whitty, Monica T 109, 111, 273 Williams, Zoe 195 Willis, Ellen 160 witch craze, European 165–66 Woebot 80 wolves, grey 28–30, 35, 40 women 1, 10, 42, 50, 95, 176, 180–81, 204 and girls as property 43, 143, 163, 168, 190, 195, 212 autonomy of 98, 126–27, 135–36, 144–45, 160–61, 164–65, 235–36, 243–44, economic status 135–36, 140–44, 167, 197–98 equality, rights and power 39, 144, 151, 153, 161, 167 mating preferences 95–96, 119–20, 126–28, 139–40, 144–45, 184, 191–92, 207 political participation and representation 41, 142–43 reproduction and sexual behaviour 43, 100, 126, 135, 138, 145–48, 160, 163, 191–94, 205–206, 246 work 2, 132–36, 153, 167, 196–98, 214, 235

292

Index

Woods, Tiger 188 World War II 196 Wrangham, Richard 41, 270 Wu, Tim 222, 239–40 Y chromosome 186–87 #YesAllWomen 179 young male syndrome 185–98, 200–204, 211

YouTube 26, 45, 48, 59, 65, 71, 99, 171, 177, 209, 222–23, 240 Zuckerberg, Mark 64, 114, 230 Zuckerman, Ethan 222, 231 Zuma, Jacob 238

293