Research Archives

The Arizona way of death

Sometime in the late 1990s, I was asked to be a token skeptic on a TV show featuring three people who claimed they were immortal.

The production team didn’t take them very seriously. Probably no one did, but the three – all Americans – nonetheless managed a tour of the UK media. One producer mentioned salaciously that the trio had requested a hotel room with one large bed. The sanest part of the resulting discussion asked if they were leading a cult.

Usually, my goal would have been to avoid arguing about beliefs and say something humorous that might stick in the minds of doubting viewers. But this was one you hoped the audience would mock without prompting.

I think it was the medical journalist Caroline Richmond who suggested that if they were so sure they were never going to die they should write wills in her favor. They were oddly resistant to this proposal.

Time passed. I forgot all about them.

Meanwhile, on the technology scene you began running into people who believed technology could solve aging and, yes, maybe even death. First as comedy, in Ed Regis’s 1991 book, Great Mambo Chicken and the Transhuman Condition: Science Slightly Over the Edge. In the Arizona desert, Regis found people hoping to upload their brains to make backup copies that could live on, even if only in a simulation. Regis also checked into cryonics, the hope that preservation at a sufficiently low temperatures would allow you to be “reanimated” someday when medical science had learned how to cure whatever killed you (and how to repair the damage caused by cryopreservation). Today we call Regis’s clutch of topics TESCREAL, a mash-up of Transhumanism, Extropianism, Singularitarianism, Cismism, Rationalism, Effective Altruism, and Longtermism.

At a 2007 conference, I met people who had actually signed up for cryonics (which requires signing gruesomely detailed documents in advance). The conference was on “responsible” nanotechnology, which then occupied the hype-and-hope position AI has today. An organizer explained the connection: developing molecular tools was essential for repairing the “whole-body frostbite” problem – that is, the damage caused by cryopreservation. In 2008, when I visited Arizona-based Alcor, the leading cryonics organization, 79 people were stored in dewars awaiting these advances. Judging from its recent newsletters, the organization remains optimistic.

At the same time, other ideas were taking shape, that treating aging as an engineering problem and figuring out the right things to fix would lead to radical life extension, even immortality, without taking an extended and uncertain timeout immersed in liquid nitrogen. The name that surfaced most was the UK’s Aubrey de Grey, but there were others.

The engineering approach to human bodies is a perfect match for the dominant Silicon Valley culture. Only now it’s not so funny, as Adam Becker showed in last year’s More Everything Forever

All this is back story for Aleks Krotoski‘s new book, The Immortalists: The Death of Death and the Race for Eternal Life. While her focus is specifically on mortality, she investigates all these links. Long-termism features as a justification for almost anything – that is, the misery of today’s billions is unimportant compared to making trillions of our descendants better off. Writing that reminds of Joe Hill’s song The Preacher and the Slave, except it won’t be you getting the pie in the sky but your great-great-whatever-grandchildren.

The desire for immortality is as old as humanity. Krotoski starts her story in 1992, when the scientist Cynthia Kenyon found a life-extending molecule in the nematode C. Elegans. The discovery offered hope, which led everyone from scientists to biohackers to billionaires to con artists to investigate further. Krotoski talks to many of these as she chronicles the rise of geroscience.

As trippy and Regis-like as some of her stories are – her visit to the longevity conference RAADfest for example – the book turns serious as some of these elements coalesce, attract familiar names like Peter Thiel. turn to politics and lobbying, and gain a foothold in the second Trump White House. Part of this may be good, as politicians adopt policies intended to extend “healthspan” and encourage independent living. Others maybe not so much, such as the push to extend the Right to Try to include the latest in untested anti-aging ideas. Particularly interesting is Krotoski’s note on World Health Organization classifications: had it classed aging itself as a cause of death, which it considered in the early 2020s, then anti-aging efforts become a cure for a disease that merit the right to try – but society’s ageism and ableism becomes much worse. Plus, the costs of this approach raises critical questions about exclusion. Side note: no one believes how pervasive ageism is until they’re old enough that no one is listening to them any more.

A third of the way into the book those crazy immortals from the 1990s appeared: Charles, Bernadeane, and James, who claimed the source of their immortality was a “cellular awakening” and you, too, could have one. They renamed their Eternal Flame Foundation People Unlimited and co-founded RAADfest, both based in Arizona. The “J” in CBJ – “anti-death activist” James Strole – is the director. Charles and Bernadeane have died. Bernadeane has been cryopreserved.

Illustrations: The Fountain of Youth, painted by Lucas Cranach the Elder, 1546 (via Wikimedia).

Also this week:
– TechGrumps episode 3.40, Teletubbies vision of Judge Dredd.
– At the Plutopia podcast, we talk to Nathan Schneider, author of Governable Spaces: Democratic Design for Online Life.

Wendy M. Grossman is an award-winning journalist. Her Web site has an extensive archive of her books, articles, and music, and an archive of earlier columns in this series. She is a contributing editor for the Plutopia News Network podcast. Follow on Mastodon or Bluesky.

Intimacy capitalism

Many non-human characteristics make AI attractive, Sue-Anne Teo said to open this year’s We Robot: endless patience, long and detailed memory, and sycophancy. I’m less certain about the last of those; lots of us react poorly to undisguised flattery. And yet: Stanford researchers agree with her that this is a thing. The AIs are certainly programmed to *try* to human-wash themselves: they use the perpendicular pronoun, “apologize” for errors, and type “you’re right”. And the Stanford folks’ research shows that users respond by becoming “more self-centered, more morally dogmatic”. Probably it’s easier for that to happen if you’re consulting the AI on a personal matter than if you’re just asking it to find an article you read once based on a few hazy memories of what it’s about. No chatbot has yet congratulated me on my choice of half-remembered reading material.

Teo’s vision of the business potential of AIs is part of a long-running theme at We Robot: the subscription service that terminates your relationship when you stop paying. The potential for emotional manipulation by a company that is programmed to maximize profits as if they were paperclips is as great as that of a spirit medium over a client who believes their only link to a beloved deceased person is through their belief in that medium’s ability to establish contact. When I suggest this, Teo says mediums don’t scale. True. But the potential for emotional dependence and manipulation for those individuals seems psychologically similar.

A couple of months ago, Kate Devlin, a professor of AI and society at Kings College London, talked more positively about human-AI relationships, arguing that those engaging in them are often not the archetypal lonely and isolated people we all imagine. Some are married – happily, they tell her. Still, she frequently reminds people “your AI does not love you back”. The same can be true in reverse. Here, a Japanese researcher with three Peppers at home is asked if she misses them when she’s away. “No.”

As a psychologist, Devlin’s job is not business models. But they drive the AI’s design. Companies spend money in time and effort to make robots humanoid – or at least cute – to make them successful in the marketplace. The same is true of chatbots programmed to appear conscious. Cue (again) James Boyle: “For the first time in history…sentences do not mean sentience.” We are some way from having adapted to that.

Teo has a name for the peculiarly toxic mix of anthropomorphism, cold-eyed profit, data collection, and dark patterns that she’s ruminating on: “intimacy capitalism”. New to me, but instantly compelling.

I can see where an academic must rigorously untangle this into a solidly-founded theory; Teo is still working out fully what it means. But the phrase resonates without that depth: the rapaciousness described by surveillance capitalism and surveillance pricing crossed with the new ability to exploit personal vulnerabilities exposed by those same non-human characteristics of infinite patience and a long, detailed memory. Ugh.

I wish I could say that people do not respond as well to the blandishments of synthetic pretend-humans, but the statistics are against me. Worse, a study referenced in discussion found that people award authority to AI companions’ pronouncements because they trust them – which sounds to me like exactly the same as trusting an online “influencer” on subjects where they have no expertise because they’re familiar and maybe got some random things right in the past. As skeptics found in studying years of psychic predictions, people remember the hits and forget the misses.

So while you or I might say, make the chatbot act like a chatbot instead of dolling it up in human signage, the business model, fed by popular preference, is against us. Related, Gizem Gültekin-Várkonyi, who presented a discussion of “robot literacy”, wants people to stop saying “the algorithm” is discriminatory or “the algorithm” makes a decision. “It is us,” she said, reminding me of Pogo.

The presumption is that loading these various toxicities into robots will be worse. I’m less sure; I think the cute but less human ones ought to have a better chance because the more humanoid ones are so obviously *not* human and more likely to fall into the Uncanny Valley.

But for how long? In the lunch break, someone was running a series of “pick the AI” image tests. Two breakfasts, side by side. One had perfectly presented fried eggs, a fruit medley with strawberries, and I think some potatoes. The other had frazzled fried eggs, baked beans, and, nestled next to them, a dead giveaway. What AI knows from black pudding?

By next year, or soon after, AI chatbots and image generators will have been fed data about black pudding (without ever tasting one). Similarly, someday in the future, crude robots will be both cuter and, possibly, more lifelike.

Would you trust your baby with one of those robots? Who is liable if it puts the baby in the washing machine? At that moment, as multiple legal opinions awaited voicing, the actual two-month-old baby in the room howled. Can robots have such exquisite comic timing?

Illustrations: Pepper, as seen at We Robot 2016.

Also this week: At Gathering4Gardner’s YouTube channel, mathematician and juggler Colin Wright and I talk about skepticism.

Turn left at the robot

It’s easy to forget, now that so many computer interfaces seem to be getting more inscrutable, that in the early 1990s the shift from the command line to graphical interfaces and the desire to reach the wider mass market introduced a new focus on usability. In classics like Don Norman’s The Design of Everyday Things, a common idea was that a really well-designed system should not require a manual because the design itself would tell the user how to operate it.

What is intuitive, though, is defined by what you’re used to. The rumor that Apple might replace the letters on keys with glyphs is a case in point. People who’ve grown up with smartphones might like the idea of glyphs that match those on their phones. But try doing technical support over the phone and describing a glyph; easier to communicate the letters.

Those years in which computer interfaces were standardized relied on metaphors based on familiar physical items: a floppy disk to save a file, an artist’s palette for color choices. In 1993, leading software companies like Microsoft and Lotus set up usability labs; it took watching user testing to convince developers that struggling to use their software was not a sign the users were stupid.

With that background, it was interesting to attend this year’s edition of the 20-year-old Human-Robot Interaction conference. Robots don’t need metaphors; they *are* the thing itself. Although: why shouldn’t a robot also have menu buttons for common functions?

In the paper I found most interesting and valuable, Lauren Wright examined the use of a speaking Misty robot to deliver social-emotional learning lessons. Wright’s group tested the value of deception – that is, having the robot speak in the first person of its “family”, experiences, and “emotions” – versus a more truthful presentation, in which the robot is neutral and tells its stories in the third person, refers to its programmers, and professes no humanity. The researchers were testing the widely-held assumption that kids engage more with robots programmed to appear more human. They found the opposite: while both versions significantly increased their learning, the kids who used the factual robot showed more engagement and higher scores in the sense of using concepts from the lesson in their answers. This really shouldn’t be surprising. Children don’t in general respond well to deception. Really, who does?

The children’s personal reactions to the robots were at least as interesting. In Michael F. Xu‘s paper, the researchers held co-design sessions and then installed a robot in eight family homes to act as a neutral third-party enforcer issuing timely reminders on behalf of busy parents. Some of the families did indeed report that the robot’s reminder got stuff done more efficiently. On the other hand, the experiment was short – only four days – and you have to wonder if that would still be true after the novelty wore off. There were hints of this from the kids, some of whom pushed back. One simply bypassed a robot reminding him of the limits on his TV viewing by taking the TV upstairs, where the robot couldn’t go. Another reacted like I would at any age and told the robot to “shut up”.

The fact versus fiction presentation included short video clips of some of the kids’ interaction with the robot tutor. In one, a boy placed his hands on either side of the robot’s “face” while it was talking and kept moving its head around, exploring the robot’s physical capabilities (or trying to take its head off?). The speaker ignored this entirely, but the sight hilariously made an important point: the robot’s physical form speaks even when the robot is silent.

We saw this at We Robot 2016, when a Jamaican lawyer asked Olivier Guilhem, from Aldebaran Robotics, which makes Pepper, “Why is the robot white?” His response: “It looks clean.” This week, one paper tried to tease out how “representation bias” – assumptions about gender, skin tone, dis/ability, accessibility, size, age – affect users’ reactions. In the dataset used to train an AI model, bias may be baked in through the historical record. With robots, bias can also present directly through the robot’s design, as Yolande Strengers’ and Jenny Kennedy’s showed in their 2020 book The Smart Wife. Despite its shiny, unmistakable whiteness, Pepper’s shape was ambiguous enough for its gender to be interpreted differently in different cultures. In the HRI paper, the researchers concluded that biases in robot design could perpetuate occupational stereotypes – “technological segregation”. They also found their participants consistently preferred non-skin tones – in their examples, silver and light teal.

“Who builds AI shapes what AI becomes,” said Ben Rosman, who outlined a burgeoning collaborative effort to build a machine learning community across Africa and redress its underrepresentation. The same with robots: many, many cultural norms affect how humans interact with them. That information is signal, not noise, he says, and should be captured to enable robots to operate across wide ranges of human context without relying on “brittle defaults” that interpret human variation as failures. “Turn left at the robot,” makes perfect sense once you know that in South Africa “robots” are known elsewhere as traffic lights.

Illustrations: Rosey, the still-influential “old demo model” robot maid in The Jetsons (1962-1963).

Also this week:
At the Plutopia podcast, we interview Marc Abrahams, founder of the Ig Nobel awards.
At Skeptical Inquirer, the latest Letter to America finds David Clarke conducting the English folklore survey.

A short history of We Robot, 2026 edition

On the eve of We Robot 2026, here are links to my summaries of every year since 2012, the inaugural conference, except 2014, which I missed for family reasons. There was no conference in 2024 in order to move the event back to its original April schedule (covid caused its move to September in 2020). These are my personal impressions; nothing I say here should be taken as representing the conference, its founders, its speakers, or their institutions.

We Robot was co-founded by Michael Froomkin, Ryan Calo, and Ian Kerr to bring together lawyers and engineers to think early and long about the coming conflicts in robots, law, and policy.

2025: Predatory inclusion: In Windsor, Ontario, a few months into the new US administration, the sudden change in international relations highlights the power imbalances inherent in many of today’s AI systems. Catopromancy: in workshops, we hear a librarian propose useful AI completely out of step with today’s corporate offerings, and mull how to apply existing laws to new scenarios.

2024 No conference.

2023 The end of cool: after struggling to design a drone delivery service that had benefits over today’s cycling couriers, we find ourselves less impressed by robots that can do somersaults but not anything obviously useful; the future may have seemed more exciting when it was imaginary.

2022 Insert a human: following a long-held conference theme about “humans in the loop, “robots” are now “sociotechnical systems”. Coding ethics: Where Asimov’s laws were just a story device, in workshops we try to work out how to design a real ethical robot.

2021 Plausible diversions: maybe any technology sufficiently advanced to seem like magic can be well enough understood that we can assign responsibility and liability? Is the juice worth the squeeze?: In workshops, we mull how to regulate delivery robots, which will likely have no user-serviceable parts. Title from Woody Hartzog.

2020 (virtual) The zero on the phone: AI exploitation and bias embedded in historical data become what one speaker calls “unregulated experimentation on humans…without oversight or control”.

2019 Math, monsters, and metaphors. We dissect the trolley problem and find the true danger on the immediate horizon is less robots, more the “pile of math that does some stuff” we call “AI”. The Algernon problem: in workshops, new disciplines joining the We Robot family remind us that robots/AI are carrying out the commands of distant owners.

2018 Deception. We return to the question of what makes robots different and revisit Madeleine Clare Elish’s moral crumple zones after the first pedestrian death by self-driving car. Late, noisy, and wrong: in workshops, engineers Bill Smart and Cindy Grimm explain why sensors never capture what you think they’re capturing and how AI systems use their data.

2017 Have robot, will legislate: Discussion of risks this year focused on the intermediate situation, when automation and human norms must co-exist.

2016 Humans all the way down: Madeline Clare Elish introduces “moral crumple zones”, a paper that will resonate through future years. The lab and the world: in workshops, Bill Smart uses conference attendees in formation to show why getting a robot to do anything is difficult.

2015: Multiplicity: W
When in the life of a technology is the right time for regulatory intervention?

2014 Missed conference

2013 Cautiously apocalyptic: Diversity of approaches to regulation will be needed to handle the diversity of robots, and at the beginning of cloud robotics and full-scale data collection, we envision a pet robot dog that can beg its owner for an upgraded service subscription.

2012 A really fancy hammer with a gun. At the first We Robot, we try to answer the fundamental question: what difference do robots bring? Unsentimental engineer Bill Smart provided the title.

Bedroom eyes

We’ve long known that much of today’s “AI” is humans all the way down. This week underlines this: in an investigation, Svenska Dagbladet and Göteborgs-Posten learn that Meta’s Ray-Ban smart glasses are capturing intimate details of people’s lives and sending them to Nairobi, Kenya. There, employees at Meta subcontractor Sama label and annotate the data for use in training models. Brings a new meaning to “bedroom eyes”.

This sort of violation is easily imposed on other people without their knowledge or consent. We worry about the police using live facial recognition, but what about being captured by random people on the street? In January’s episode of the TechGrumps podcast, we called the news of Meta’s new product “Return of the Glasshole“.

Two 2018 books, Mary L. Gray and Siddharth Suri’s Ghost Work and Sarah T. Roberts’ Behind the Screen made it clear that “machine learning” and “AI” depend on poorly-paid unseen laborers. Dataveillance is a stowaway in every “smart” device. But this is a whole new level: the Kenyans report glimpses of bank cards, bedroom intimacy, even bathroom visits. The journalists were able to establish that the glasses’ AI requires a connection to Meta’s servers to answer questions, and there’s no opt out.

The UK’s Information Commissioner’s Office is investigating, and at Ars Technica Sarah Perez reports that a US lawsuit has been filed.

As the original Swedish report goes on to say, the EU has no adequacy agreement with Kenya. More disturbing is the fact that probably hundreds of people within Meta worked on this without seeing a problem.

In 1974, the Watergate-related revelation that US president Richard Nixon had recorded everything taking place in his office inspired folksinger Bill Steele to write the song The Walls Have Ears (MP3). What struck him particularly was that everyone saw it as unremarkable. “Unfortunately still current,” he commented in his 1977 liner notes. Nearly 50 years later, ditto.

***

A lot of (especially younger) people don’t remember that before 9/11 you could walk into most buildings without showing ID. Many authorities – the EU in particular – have long been unhappy with anonymity online, and one conspiratorial theory about age gating and the digital ID infrastructure being built in many places is that the goal is complete and pervasive identification. In the UK, requiring ID for all Internet access has occasionally popped up as a child safety idea, even though security experts recommend lying about birth dates and other personal data in the interests of self-protection against identity theft.

Now we have generative AI, and along comes a new paper that finds that large language models can be used to deanonymize people online at large scale by analyzing profiles and conversations. In one exercise, they matched Hacker News posts to LinkedIn profiles. In another, they linked users across subReddit communities. In a third, they split Reddit profiles to mimic the use of pseudonymous posting. Pseudonymity doesn’t offer meaningful protection (though I’m not sure how much it ever did), and preventing this type of attack is difficult. They also suggest platforms should reconsider their data access policies in line with their findings.

It’s hard to imagine most platforms will care much; users have long been expected to assess their own risk. Even smaller communities with a more concerned administration will not be in a position to know how many other services their users access, what they post there, or how it can be cross-linked. The difficulty of remaining anonymous online has been growing ever since 2000, when Latanya Sweeney showed it was possible to identify 87% of the population recorded in census data given just Zip code, date of birth, and gender. As psychics know, most people don’t really remember what they’ve said and how it can be linked and exploited by someone who’s paying attention. The paper concludes: we need a new threat model for privacy online.

***

The Internet, famously, was designed to support communications in the face of a bomb outage.

Building it required physical links – undersea cables, fiber connections, data centers, routers. For younger folks who have grown up with wifi and mobile phone connections, that physical layer may be invisible. But it matters no less than it did twenty-five years ago, when experts agreed that ten backhoes (among other things) could do more effective damage than bombs.

This week’s horrible, spreading war in the Middle East has seen the closure of the Strait of Hormuz and the Red see to commercial traffic. Indranil Ghosh reports at Rest of World that that 17 undersea cables pass through the Red Sea alone, and billions, soon trillions, of dollars in US technology investment depends on fiber optic cables running through war zones. There’s been reporting before now about the links between various Middle Eastern countries and Silicon Valley (see for example the recent book Gilded Rage, by Jacob Silverman), but until now much less about the technological interdependence put in jeopardy by the conflict. Ghosh also reports that drones have struck two Amazon Web Services data centers in UAE and one in Bahrein.

The issue is not so much direct damage to the cables as the impossibility of repairing them as long as access is closed. The Internet, designed with war in mind, is a product of peace.

Illustrations: Monument to Anonymous, by Meredith Bergmann.

Also this week: At the Plutopia podcast, we interview Kate Devlin, who studies human-AI interaction.

In search of causality

The debates over children’s use of social media, screens, and phones continue, exacerbated in the UK by ongoing Parliamentary scrutiny of the Children’s Wellbeing and Schools bill and continuing disgust over Grok‘s sexualized image generation. Robert Booth reports at the Guardian that the Center for Countering Digital Hate estimates that Grok AI generated 3 million sexualized images in under two weeks and that a third of them are still viewable on X. In that case, X and Grok appear to be a more general problem than children’s access.

We continue to need better evidence establishing causality or its absence. This week, researchers from the Bradford Centre for Health Data Science (led by Dan Lewer) and the University of Cambridge (led by Amy Orben) announced a six-week trial that will attempt to find the actual impact on teens of limiting – not ending – social media access. The BBC reports, that the trial will split 4,000 Bradford secondary school pupils into two groups, One will download an app hat turns off access to services like TikTok and Snapchat from 9pm to 7am and limits use at other times to a “daily budget”. The restrictions won’t include WhatsApp, which the researchers recognize is central to many family groups. The other half will go on using social media as before.

The researchers will compare the two groups by assessing their’ levels of anxiety, depression, sleep, bullying, and time spent with friends and family.

In earlier research, Orben developed a framework for data donation, which allows teens to understand their own use of social media. Another forthcoming study, Youth Perspectives on Social Media Harms: A Large-Scale Micro-Narrative Study, collects 901 first-person tales from 18- to 22-year-olds in the UK. From these Orben’s group derive four types of harm: harms from other people’s behavior, personal harmful behavior evoked by social media, harms related to the content they encounter, and harms related to platform features. In the first category they include bullying and scams; in the second, compulsive use and social comparison; in the third, graphic material; and in the fourth, algorithmic manipulation. They also note the study’s limitations. A longer-term or differently-timed study might show different effects – during the study period the 2024 US presidential election took place. The teens’ stories don’t establish causality. Finally, there may be other harms not captured in this study.

The most important element, however, is that they sought the perspective of young people themselves, who are to date rarely heard in these discussions.

As this research begins, at Techdirt Mike Masnick reports on two new finished papers also covering teens and social media. The first, Social Media Use and Well-Being Across Adolescent Development, published in JAMA Pediatrics, is a three-year study of 100,991 Australian adolescents to find whether well-being was associated with social media use. The researchers, from the University of South Australia, found a U-shaped curve: moderate social media use was associated with the best outcomes, while both the highest users and the non-users showed less well-being. Girls benefited increasingly from moderate social media use from mid-adolescence onwards, while in boys’ non-use became increasingly problematic, leading to worse outcomes than high use by their late teens.

The second, a study from the University of Manchester published in the Journal of Public Health, followed a group of 25,000 11- to 14-year-olds to find out whether the use of technology such as social media and gaming accurately predicted later mental health issues. The study found no evidence that heavier use of social media or gaming led to increased symptoms of anxiety or depression in the following year.

In his discussion of these two papers, Masnick argues that this research gives weight to his contention that the widespread claim that social media is inherently harmful is wrong.

In the UK and elsewhere, however, politicians are proceeding on the basis that social media *is* inevitably harmful. . This week, the government announced a consultation on children’s use of technology. The consultation seems, as Carly Page writes at The Register, geared toward increasing restrictions, Also this week, the House of Lords voted 261 to 150, defeating the government to add an amendment to the Children’s Wellbeing and Schools bill that would require social media services to add age verification to block under-16s from accessing them within a year. MPs will now have to vote to remove the amendment or it will become law, a backdoor preemption of the House of Commons’ prerogative to legislate.

UK prime minister Keir Starmer has been edging toward a social media ban for under-16s; now with added pressure from not only the Lords but also the Conservative Party leader, Kemi Badenoch, and 61 MPs sent an open letter supporting a ban like the one in Australia. Ofcom reports that 22% of children aged eight to 17 have a false user age of over 18 – but also that often it’s with their parents’ help. Would this be different under a national ban?

Starmer reportedly wants to delay deciding until evidence from Australia and, one presumes, from the consultation, is available. A sensible idea we hope is not doomed to failure.

Illustrations: Time magazine’s 1995 “Cyberporn” cover, which raised early alarm about kids online. Based on a fraudulent study, it nonetheless influenced policy-making for some years.

Also this week:
At the Plutopia podcast, we interview Dave Evans on his work to combat misinformation.

Passing the Uncanny Valley

A couple of weeks ago, the Greenwich Skeptics in the Pub played host to Sophie Nightingale, who studies the psychology of AI deepfakes. The particular project she spoke about was an experiment in whether people can be trained to be better at distinguishing them from real images.

In Nightingale’s experiments, she carefully matched groups of real images to synthetic ones, first created by generative adversarial networks (GANs), later by diffusion models (GeeksforGeeks raters’ demographics.

Then the humans were given some training in what to look for to detect fakes and the experiment was rerun with new sets of faces. The bad news: the training made a little difference, but not much. She went on to do similar experiments with diffusion images.

Nightingale has gone on to do some cross-modal experiments, including audio as well as images, following the 2024 election incident in which New Hampshire voters received robocalls from a faked Joe Biden intended to discourage voters in the January 2024 primary. In the audio experiment, she played the test subjects very short snippets. Played for us in the pub, it was very hard to tell real from fake, and her experimental subjects did no better. I would expect longer clips to be more identifiable as fake. The Biden call succeeded in part because that type of fake had never been tried before. Now, voters, at least in New Hampshire, will know it’s possible that the call they’re getting is part of a newer type of disinformation campaign aimed at

In another experiment, she asked participants to rate the trustworthiness of the facial images they were shown, and was dismayed when they rated the synthetic faces slightly (7.7%) higher than the real ones. In the resulting paper for Journal of Vision, she hypothesizes that this may be because synthetic faces tend to look more like “average” faces, which tend to be rated higher in trustworthiness, even if they’re not the most attractive.

Overall, she concludes that both still images and voice have “passed the Uncanny Valley“, and video will soon follow. In the past, I’ve chosen optimism about this sort of thing, on the basis that earlier generations have been fooled by technological artifacts that couldn’t fool us now for a second. The Cottingley Fairies looks ridiculous after generations of knowledge of photography. On the other hand, Johannes Vermeer’s Girl with a Pearl Earring looks more real than modern deepfakes, even though the subject is generally described as imaginary. So it’s possible to think of it as a “deepfake”, painted in oils in the 17th century.

Fakes have always been with us. What generative AI has done to change this landscape is to democratize and scale their creation, just as it’s amping up the scale and speed of cyber attacks. It’s no longer necessary to be even barely competent; the tools keep getting easier.

Listening to Nightingale it seems most likely that work like that in progress by an audience member on identifying technological artifacts that identify fakes will prove to be the right way forward. If those differences can be reliably identified, they could be built into technological tools that can spot indicators we can’t perceive directly. If something like that can be embedded into devices – phones, eyeglasses, wristwatches, laptops – and spot and filter out fakes in real time, and we should be able to regain some ability to trust what we see.

There are some obvious problems with this hoped-for future. Some people will continue to seek to exploit fakes; some may prefer them. The most likely outcome will be an arms race like that surrounding email spam and other battles between malware producers and security people. Still, it’s the first approach that seems to offer a practical solution to coping with a vastly diminished ability to know what’s real and what isn’t.

***

On the Internet your home always leaves you, part 4,563. Twenty-two-year-old blogging site Typepad will disappear in a few weeks. To those of us who have read blogs ever since they began, this news is shocking, like someone’s decided to tear down an old community church. Yes, the congregation has shrunk and aged, and it’s drafty and built on creaking old technology (in Typepad’s case, Moveable Type), but it’s part of shared local history. Except it isn’t, because, as Wikipedia documents, corporate musical chairs means it’s now owned by private equity. Apparently it’s been closed to new signups since 2020, and its bloggers are now being told to move their sites before everything is deleted in September. It feels like the stars of the open web are winking out, one by one.

On the Internet everything is forever, but everything is also ephemeral. Ironically, the site’s marketing slug still reads: “Typepad is the reliable, flexible blogging platform that puts the publisher in control.”

Illustrations: “Girl with a Pearl Earring”, painted by Johannes Vermeer circa 1665.

Hallucinations

It makes obvious sense that the people most personally affected by a crime should have the right to present their views in court. Last week, in Arizona, Stacey Wales, the sister of Chris Pelkey, who was killed in a road rage shooting in 2021, delegated her victim impact statement offering forgiveness to Pelkey’s artificially-generated video likeness. According to Cy Neff at the Guardian, the judge praised this use of AI and said he felt the forgiveness was “genuine”. It is unknown if it affected his sentencing.

It feels instinctively wrong to use a synthesized likeness this way to represent living relatives, who could have written any script they chose – even, had they so desired, one presenting this reportedly peaceful religious man’s views as a fierce desire for vengeance. *Of course* seeing it acted out by a movie-like AI simulation of the deceased victim packs emotional punch. But that doesn’t make it *true* or, as Wales calls it at the YouTube video link above, “his own impact statement”. It remains the thoughts of his family and friends, culled from their possibly imperfect memories of things Pelkey said during his lifetime, and if it’s going to be presented in a court, it ought to be presented by the people who wrote the script.

This is especially true because humans are so susceptible to forming relationships with *anything*, whether it’s a basketball that reminds you of home, as in the 2000 movie Cast Away, or a chatbot that appears to answer your questions, as in 1966’s ELIZA or today’s ChatGPT.

There is a lot of that about. Recently, Miles Klee reported at Rolling Stone that numerous individuals are losing loved ones to “spiritual fantasies” engendered by intensive and deepening interaction with chatbots. This reminds of Ouija boards, which seem to respond to people’s questions but in reality react to small muscle movements in the operators’ hands.

Ouija boards “lie” because their operators unconsciously guide them to spell out words via the ideomotor effect. Those small, unnoticed muscle movements are also, more impressively, responsible for table tilting. The operators add to the illusion by interpreting the meaning of whatever the Ouija board spells out.

Chatbots “hallucinate” because the underlying large language models, based on math and statistics, predict the most likely next words and phrases with no understanding of meaning. But a conundrum is developing: as the large language models underlying chatbots improve, the bots are becoming *more*, not less, prone to deliver untruths.

At The Register, Thomas Claburn reports that researchers at Carnegie-Mellon, the University of Michigan, and the Allen Institute for AI find that AI models will “lie” in to order to meet the goals set for them. In the example in their paper, a chatbot instructed to sell a new painkiller that the company knows is more addictive than its predecessor will deny its addictiveness in the interests of making the sale. This is where who owns the technology and sets its parameters is crucial.

This result shouldn’t be too surprising. In her 2019 book, You Look Like a Thing and I Love You, Janelle Shane highlighted AIs’ tendency to come up with “short-cuts” that defy human expectations and limitations to achieve the goals set for them. No one has yet reported that a chatbot has been intentionally programmed to lead its users from simple scheduling to a belief that they are talking to a god – or are one themselves, as Klee reports. This seems more like operator error, as unconscious as the ideomotor effect

OpenAI reported at the end of April that it was rolling back GPT-4o to an earlier version because the chatbot had become too “sycophantic”. Tthe chatbot’s tendency to flatter its users apparently derived from the company’s attempt to make it “feel more intuitive”.

It’s less clear why Elon Musk’s Grok has been shoehorning rants alleging white genocide in South Africa into every answer it gives to every question, no matter how unrelated, as Kyle Orland reports at Ars Technica.

Meanwhile, at the New York Times Cade Metz and Karen Weise find that AI hallucinations are getting worse as the bots become more powerful. They give examples, but we all have our own: irrelevant search results, flat-out wrong information, made-up legal citations. Metz and Weise say “it’s not entirely clear why”, but note that the reasoning systems that DeepSeek so explosively introduced in February are more prone to errors, and that those errors compound the more time they spend stepping through a problem. That seems logical, just as a tiny error in an early step can completely derail a mathematical proof.

This all being the case, it would be nice if people would pause to rethink how they use this technology. At Lawfare, Cullen O’Keefe and Ketan Ramakrishnan are already warning about the next stage, agentic AI, which is being touted as a way to automate law enforcement. Lacking fear of punishment, AIs don’t have the motivations humans do to follow the law (nor can a mistargeted individual reason with them). Therefore, they must be instructed to follow the law, with all the problems of translating human legal code into binary code that implies.

I miss so much the days when you could chat online with a machine and know that really underneath it was just a human playing pranks.

Illustrations: “Mystic Tray” Ouija board (via Wikimedia).

Wendy M. Grossman is the 2013 winner of the Enigma Award. Her Web site has an extensive archive of her books, articles, and music, and an archive of earlier columns in this series. She is a contributing editor for the Plutopia News Network podcast. Follow on Mastodon or Bluesky.

A short history of We Robot 2012-

On the eve of We Robot 2025, here are links to my summaries of previous years. 2014 is missing; I didn’t make it that year for family reasons. There was no conference in 2024 in order to move the event back to its original April schedule (covid caused its move to September in 2020). These are my personal impressions; nothing I say here should be taken as representing the conference, its founders, its speakers, or their institutions.

We Robot was co-founded by Michael Froomkin, Ryan Calo, and Ian Kerr to bring together lawyers and engineers to think early about the coming conflicts in robots, law, and policy.

2024 No conference.

2023 The end of cool. After struggling to design a drone delivery service that had any benefits over today’s cycling couriers, we find ourselves less impressed by robot that can do somersaults but not do anything useful.

2022 Insert a human. “Robots” are now “sociotechnical systems”.

Workshop day Coding ethics. The conference struggles to design an ethical robot.

2021 Plausible diversions. How will robots rehape human space?

Workshop day Is the juice worth the squeeze?. We think about how to regulate delivery robots, which will likely have no user-serviceable parts. Title from Woody Hartzog.

2020 (virtual) The zero on the phone. AI exploitation becomes much more visible.

2019 Math, monsters, and metaphors. The trolley problem is dissected; the true danger is less robots than the “pile of math that does some stuff”.

Workshop day The Algernon problem. New participants remind that robots/AI are carrying out the commands of distant owners.

2018 Deception. The conference tries to tease out what makes robots different and revisits Madeleine Clare Elish’s moral crumple zones after the first pedestrian death by self-driving car.

Workshop day Late, noisy, and wrong. Engineers Bill Smart and Cindy Grimm explain why sensors never capture what you think they’re capturing and how AI systems use their data.

2017 Have robot, will legislate. Discussion of risks this year focused on the intermediate sitaution, when automation and human norms clash.

2016 Humans all the way down. Madeline Clare Elish introduces “moral crumple zones”.

Workshop day: The lab and the world. Bill Smart uses conference attendees in formation to show why building a robot is difficult.

2015 Multiplicity. A robot pet dog begs its owner for an upgraded service subscription.

2014 Missed conference

2013 Cautiously apocalyptic. Diversity of approaches to regulation will be needed to handle the diversity of robots.

2012 A really fancy hammer with a gun. Unsentimental engineer Bill Smart provided the title.

Return of the Four Horsemen

The themes at this week’s Scrambling for Safety, hosted by the Foundation for Information Policy Research, are topical but not new since the original 1997 event: chat control; the online safety act; and AI in government decision making.

The EU proposal chat control would require platforms served with a detection order to scan people’s phones for both new and previously known child sexual abuse material – client-side scanning. Robin Wilton prefers to call this “preemptive monitoring” to clarify that it’s an attack.

Yet it’s not fit even for its stated purpose, as Claudia Peersman showed, based on research conducted at REPHRAIN. They set out to develop a human-centric evaluation framework for the AI tools needed at the scale chat control would require. Their main conclusion: AI tools are not ready to be deployed on end-to-end-encrypted private communications. This was also Ross Anderson‘s argument in his 2022 paper on chat control (PDF) showing why it won’t meet the stated goals. Peersman also noted an important oversight: none of the stakeholder groups consulted in developing these tools include the children they’re supposed to protect.

This led Jen Persson to ask: “What are we doing to young people?” Children may not understand encryption, she said, but they do know what privacy means to them, as numerous researchers have found. If violating children’s right to privacy by dismantling encryption means ignoring the UN Convention on the Rights of the Child, “What world are we leaving for them? How do we deal with a lack of privacy in trusted relationships?”

All this led Wilton to comment that if the technology doesn’t work, that’s hard evidence that it is neither “necessary” nor “proportionate”, as human rights law demands. Yet, Persson pointed out, legislators keep passing laws that technologists insist are unworkable. Studies in both France and Australia have found that there is no viable privacy-preserving age verification technology – but the UK’s Online Safety Act (2023) still requires it.

In both examples – and in introducing AI into government decision making – a key element is false positives, which swamp human adjudicators in any large-scale automated system. In outlining the practicality of the Online Safety Act, Graham Smith cited the recent case of Marieha Hussein, who carried a placard at a pro-Palestinian protest that depicted former prime minister Rishi Sunak and former home secretary Suella Braverman as coconuts. After two days of evidence, the judge concluded the placard was (allowed) political satire rather than (criminal) racial abuse. What automated system can understand that the same image means different things in different contexts? What human moderator has two days? Platforms will simply remove content that would never have led to a conviction in court.

Or, asked Monica Horten suggested, how does a platform identify the new offense of coercive control?

Lisa Sugiura, who campaigns to end violence against women and girls, had already noted that the same apps parents install so they can monitor their children (and are reluctant to give up later) are openly advertised with slogans like “Use this to check up on your cheating wife”. (See also Cindy Southworth, 2010, on stalker apps.) The dots connect into reports Persson heard at last week’s Safer Internet Forum that young women find it hard to refuse when potential partners want parental-style monitoring rights and then find it even harder to extricate themselves from abusive situations.

Design teams don’t count the cost of this sort of collateral damage, just as their companies have little liability for the human cost of false positives, and the narrow lens of child safety also ignores these wider costs. Yet they can be staggering: the 1990s US law requiring ISPs to facilitate wiretapping, CALEA, created the vulnerability that enabled widescale Chinese spying in 2024.

Wilton called laws that essentially treat all of us as suspects “a rule to make good people behave well, instead of preventing bad people from behaving badly”. Big organized crime cases like the Silk Road, Encrochat, and Sky ECC, relied on infiltration, not breaking encryption. Once upon a time, veterans know, there were four horsemen always cited by proponents of such laws: organized crime, drug dealers, terorrists, and child abusers. We hear little about the first three these days.

All of this will take new forms as the new government adopts AI in decision making with the same old hopes: increased efficiency, lowered costs. Government is not learning from the previous waves of technoutopianism, which brought us things like the Post Office Horizon scandal, said Gavin Freeguard. Under data protection law we were “data subjects”; now we are becoming “decision subjects” whose voices are not being heard.

There is some hope: Swee Leng Harris sees improvements in the reissued data bill, though she stresses that it’s important to remind people that the “cloud” is really material data centers that consume energy (and use water) at staggering rates (see also Kate Crawford’s book, Atlas of AI). It’s no help that UK ministers and civil servants move on to other jobs at pace, ensuring there is no accountability. As Sam Smith said, computers have made it possible to do things faster – but also to go wrong faster at a much larger scale.

Illustrations: Time magazine’s 1995 “Cyberporn” cover, the first children and online pornography scare, based on a fraudulent study.