Wendy M. Grossman, Author at net.wars

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.

The soul in the machine

One of the first things skeptics learn is to never assume that paranormal belief implies stupidity. Smart people believe questionable things all the time; intelligence is different from the ability to assess your own cognitive biases, especially when you are working outside your field of expertise.

The astronomer Carl Sagan, one of 26 founders of the Committee for Skeptical Inquiry hinted at this in saying that the more you want to believe something the more careful you have to be about assessing the evidence. “Extraordinary claims require extraordinary evidence,” he often said, and he was right.

This week, the evolutionary biologist and author Richard Dawkins announced he thinks “his” AI is conscious, based on a couple of days’ interaction with Anthropic’s Claude chatbot. Inevitably, someone – Matthew Sheffield at Flux – has called the story “The Claude Delusion”. Dawkins has some company; at The Register, Liam Proven reports an engineer’s similar belief, and at the Independent Holly Baxter finds several more among company CEOs.

At Unherd, where he published his account, Dawkins begins with the “imitation game”, the test Alan Turing proposed in his 1950 essay, Computing Machinery and Intelligence (PDF). Turing, who adapted the test from one intended to differentiate men and women, suggested that relying on remote communication via text would eliminate unfairness to the machine, which obviously lacks human physical capabilities. The basic idea is that the mAchine passes the test if the human judge, given a transcript of the conversation between human and machine, can’t tell which is which.

It’s clear that chatbots can pass the Turing test. What that teaches us is not that chatbots can think but that Turing’s test is the wrong tool for assessing that. What chatbots have actually shown is that Turing’s test is the wrong tool for assessing whether something can think. As James Boyle memorably wrote, “Sentences do not imply sentience”. This profound change will take time to understand. In the meantime, it’s going to fool a lot of people. Although, as a science fiction writer friend once said, “You only have to look at a baby…”

In his essay, Turing outlined his own beliefs relating to his central question. He thought that in 50 years (that is, by 2000), it would be possible to program computers so that an average questioner would have only a 70% chance of making the right identification after five minutes. He then went on to consider many different types of objections to this belief, and to lay out his case. Absent are two factors we now know are crucial: the psychology of the human questioner and judge, and the business model of the machine’s owner.

The last few years have taught us both the capabilities and the flaws in chatbots: they provide plausible answers; they frequently generate entirely wrong information; and they are sycophantic and prone to output text that flatters their human questioner. So it’s easy to find a natural explanation for Dawkins’ belief that “his” AI is conscious: he is anthropomorphizing a stochastic parrot simulation that issues realistic and flattering responses. The simplest explanation, per Occam’s Razor, is that the consciousness exists solely between keyboard and chair.

Tangentially, the fix OpenAI has proposed for outputting entirely wrong text, Wei Xang writes at Science Alert, would also help make it clearer to users that generative AI is not sentient: introduce confidence intervals to expose the uncertainty derived from the gaps in the training data that generate unfounded guesses.

Google DeepMind engineer Alexander Leichner apparently agrees; this week, Emanuel Maiberg reports at 404 Media, he published a paper arguing that large language models will never be conscious. The biologists and philosophers Maiberg quotes agree with this conclusion – and point out decades of similar conclusions in their disciplines over decades.

The claim that a human-made a bunch of computers processing inputs is sentient is truly extraordinary. We forget this, because we have all read and watched so much science fiction with sentient, emotional machines: Her; Ex Machina; Blade Runner; Marvin, the Paranoid Android); and the first fictional android I ever encountered, Daneel Olivaw in The Caves of Steel. I mention mostly movies because actors make machines so much more obviously soulful.

Extraordinary claims require proportionately extraordinary evidence. If we accept that the Turing test was inadequate, which is not moving the goalposts but *learning something*, how would we go about devising a scientific method for identifying sentience?

The Cambridge professor of communications Jon Crowcroft didn’t exactly propose one. But, he emailed, “What we do know (from cognitive neuroscientists and from AI software) is that you can actually look at the internal operations of a biological brain and of an AI software system, and you can see that in the biological case there are things going on that are some sort of process we might call consciousness, but in the AI case there is no such structure. Nor would you expect there to be because no-one programmed an AI to have such a feature. nor is it emergent. In animals (not just humans) consciousness has an evolutionary value. Things like theory of mind are part of social bonding which makes cooperative strategies, for predators and prey, more effective.”

In other words, what we have learned from all this is that Dawkins is human. Who knew?

Illustrations: Stable Diffusion’s rendering of stochastic parrots, as prompted by Jon Crowcroft.

Elsewhere this week:
This month’s Letter to America column at Skeptical Inquirer reviews Beyond Belief (Helen Pearson), Bad Influence (Deborah Cohen), and Sneeze (David Miles).

The railway and the balloon

Is AI more like a train or a hot air balloon? Veronica Paternolli and Ryan Calo asked at this year’s We Robot. Nineteenth-century hot air balloons were notoriously uncontrollable. The US legal system assigned strict liability: it was your fault if your balloon crashed in someone’s backyard, even if you did everything you could to prevent it. Railways were far more disruptive but also far more predictable, and therefore were liable only in cases of negligence. Which regime should apply to AI is an ongoing debate.

Calo and Patornolli also wondered if agentic AI could reverse 30 years of being forced to take on busy work companies formerly did for us. This “shadow work” encompasses everything from retrieving bank statements and completing reCaptchas to pumping our own gas. Actually, more than 30 years: in 1962, Agatha Christie’s Miss Marple complained that self-service supermarkets were replacing shopkeepers who served you. If companies want a negligence regime, Patornelli and Calo argue, they should deploy agentic AI to relieve us of the “sludge” instead of displacing jobs and aggregating wealth.

But would we believe them? Technologists have promised before that their products will up-end the balance of power and simplify our lives – some of them the same people and companies. The web browsers and search engines that promised a universe of information today are faithless agents serving their owners and developers. Why should agentic AI – if it’s ever trustworthy – be any different? Many of us want a life with less demanding devices – and agentic AI sounds like even more “relationship” work.

Underlying Patornolli’s and Calo’s argument, however, is a fundamental clash. Like Mireille Hildebrandt at a 2017 Royal Society meeting, they argue that law is purposely flexible so it can adapt to unforeseen circumstances and, even more important, contestable (otherwise, Hildbrandt said, it’s just administration). Computers, even dressed in “AI”, always have hard boundaries underneath. As Bill Smart explained here in 2016, no matter how “fuzzy” its logic, no computer can evaluate standards like the “reasonable woman“. No matter how “fuzzy” its logic, a computer will issue a ticket if you are going even just the tiniest fraction of a nanometer faster than the speed limit. Anti-doping authorities have a similar problem as Neil Robinson said in a recent episode of the Anti-Doping podcast: the extreme sensitivity of modern tests is catching people with no intent to dope.

Liability wasn’t the immediate problem in Tomomi Ota’s description of everyday life with a Pepper robot at home (YouTube), which she took shopping, to restaurants, and on public transit as part of the Robot Friendly project, An account that led AJung Moon to wonder if a future filled with robots is really desirable. The inevitability narrative would say we’re going to get it anyway, begging the questions of whether we have a) the resources to make billions of robots and b) where we would put them all.

Sometimes these things fail in the simplest ways: a close-up of a Pepper that has been used as a greeter shows broken fingers because it was not robust enough for the basic social protocol of shaking hands. In studying the integration of robots into customer service situations, Elsa Concas, Stefan Larsson, and Laetitia Tanqueray found staff consultation is essential. In a staged setting such as the Japanese “ramen and robots” Pepper Parlour, the robots were a draw for customers and appreciated by the staff, who were paid more. In an unstaged airport tourist information center, they were basically useless and ignored. A commenter noted the same is often true of the robots intended for elder care in Japan: most end up in a cupboard,

This theme was also picked up by Emily LaRosa, who studied the limits of explainability in automated apple picking. In this case of “epistemic injustice”, the neglect of local knowledge and ecological tradition led her to propose a “Curated Information Framework”. She concluded that trust in AI systems is not created by transparency on its own if that means handing over large amounts of inscrutable data, but by taking lived context into account – “situated transparency”.

LaRosa’s study echoed the paper Ota co-wrote with Rikiya Yamamoto, which derives new “laws of robotics” to update Isaac Asimov’s Three Laws, which can’t be programmed and whose fixed, “top-down” nature was what he needed in a story-telling device. The real world, they argue, requires principles built bottom-up from practical experience. Their selection: mutual respect, social membership, and co-evolution.

They have lots of competition. Moon counts more than 100 sets of principles and ethical frameworks published since 2018, many of which she says make assumptions debunked in the 2025 paper The Future is Rosie?” or as Paul Ohm and David Atkinson discussed, encoded in the benchmarks – documents used to define AIs’ behavior and priorities. This “latent rulebook”, they said, is increasingly secret.

Meanwhile, like explainability, the right to repair fails for AI, which changes constantly with software updates, networking, and interacting. Ryota Akasaka argued that current legal approaches don’t work for products that aren’t fixed and will lose everything they’ve accrued when “repaired” to their original state. When Ota was offered the opportunity to upgrade her development model Pepper, she declined in shock. Replacing your robot’s head, it seems, ends a beautiful friendship.

Illustrations: “Hidden Labour of Internet Browsing”, by Anne Fehres and Luke Conroy. Via A14 Media (CC-by-4.0).

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.

Long Island AI

The peak of dot-com mania was identifiable even at the time: it was in January 2000, when AOL bought Time Warner for $183 billion. Peak podcast mania arguably came in 2020 when Spotify paid Joe Rogan $100 million (per rumor). It’s now time to call the peak of AI mania: Allbirds, which was loved a few years back for making sustainable wool shoes …has sold off all stock and assets, and is rebranding as Newbird AI to sell “AI compute infrastructure”. At The Overspill, Charles Arthur compares this to 2017, when Long Island Iced Tea renamed itself Long Blockchain, arguably the peak of bitcoin mania. His theory that all Newbird AI has left is a bunch of empty warehouses, so hopes someone will put data centers in them is the only possibility that makes any sense.

Most of those bits of history led to more financial silliness and then a crash. The AOL-TimeWarner marriage was notoriously catastrophic. AOL, which was supposed to modernize old, slow Time-Warner, in fact was already becoming obsolete as users shifted to new technology (broadband) and the wider Internet. By 2003, the company was selling itself off in pieces. Long Island Blockchain cratered; a year later it had abandoned its plans to buy bitcoin mining equipment. Its delisting by NASDAQ was accompanied by the SEC’s charging three people with insider trading. Joe Rogan of course remains hugely popular and Spotify is doing fine, but it’s certainly not controlling the business of podcasting as it appeared to hope it would.

The day following the announcemenet, Newbird AI’s shares rose as much as 700% (briefly), partly on the additional news that it will close a funding round of $50 million in the second quarter of 2026. Even CNBC calls this “pivot” bizarre.

For our purposes, it doesn’t matter if this wacky strategy works (pick your definition of “works”), because when the share price of a basically assetless company goes up 700% because it’s added “AI” to its name we have reached the absurdity that marks the peak of every bubble.

It’s not the only sign (or the only absurdity). In the UK, last month Aisha Down reported at the Guardian that many of the efforts prime minister Keir Starmer – and Rishi Sunak before him – has announced to “mainline AI into the veins” of the British economy are based on what she calls “phantom investments”. She reported faithfully that the Department of Science, Innovation, and Technology said it “rejected these assertions”, but this week we learned that at least one piece of her reporting was absolutely correct.

This week’s news revolves around a project called Stargate, announced in September 2025 and involving the UK-headquartered AI infrastructure provider Nscale, Microsoft, Nvidia, and OpenAI. This week, OpenAI announced it was putting the project – for which it was supposed to build a data center – on hold. OpenAI blames energy prices and, as Joseph Bambridge reports at Politico, the government’s decision last month to shelve proposals to allow data miners to use copyrighted content unless its owner opts out. The proposal was widely opposed by the UK’s creative industry, and was indefinitely delayed in a report issued on March 18 (ReedSmith has a useful legal summary)..

The loss – or delay – of Stargate is a rounding error to companies the size of Microsoft and Nvidia. It’s more significant for Nscale, which according to CNBC raised $2 billion in a funding round just last month with investments from Nvidia, Dell, Lenovo, and other much less famous names; at the same time, it added former Google and Facebook ad business builder Sheryl Sandberg and former Facebook global policy head Nick Clegg to its board. The new funding raised Nscale’s valuation to $14.6 billion. At his blog, Ed Zitron calls the ability to raise funding for a data center that doesn’t exist “weird“, and suggests that AI companies should admit that their chatbots are just “regular old software”.

Meta king Mark Zuckerberg, last seen losing money on the former next-big-thing metaverse, is, Megan Bobrowsky reports at the Wall Street Journal, building an AI agent to get him information and answers faster. This comes on top of last month’s announcement that Meta is buying the AI agent network Moltbook, seemingly mostly in order to hire its two founders for Meta’s Superintelligence Labs. This week, Zuckerberg also announced he was building an AI clone of himself to interact with staff so they can feel more connected to him. Seems like in reality it would make corporate management feel like automated customer service.

The question about bubbles is always: is this one like railroads or like tulips? Tulips left nothing of value behind while railroads went on to be transformative. In 2001, almost everyone knew the Internet would go on growing in size and importance. In the AI case, despite the current silliness, over time we will learn how to use these new capabilities and limit the downsides. But first, we will have to deal with the fallout of the fact that the finances do not add up.

Illustrations: Tulips, (via Wikimedia).

Also this week:
At Skeptical Inquirer, I go to this year’s Gathering 4 Gardner.
At the Plutopia podcast, we interview Tereza Pultarova, who reports on developing military technology in Ukraine.

References for “What We Talk About When We Talk About AI”

By slide number as presented at Greenwich Skeptics, 2026-04-13:

3 – Ofcom, Adults’ Media Use and Attitudes Report, April 2, 2026.

4 – What is “AI”? Clockwise from top left: Eliza (1966), by Joseph Weizenbaum, which simulated a psychotherapist; a modern data center; Sidney Harris’s 1977 cartoon, “Then a miracle occurs”; protein folding by DeepMind’s Alphafold in 2024; Privacy International‘s mockup of an AI-assisted surveillance dashboard.

6 – Automata: Ancient Greek automata; mechanical singing birds and other musical machines.

7 – Companions, clockwise from top left: Wilson, Tom Hanks’ basketball in the 2000 movie Cast Away; a Roomba (2002); C3PO and R2D2 from Star Wars; Furbys (1998); a Tamagotchi pet (1996).

9 – Helpers: Mickey Mouse’s enchanted broom in “The Sorcerer’s Apprentice” from the 1940 movie Fantasia; Rosey the Robot in the 1962 TV series The Jetsons.

10 – Guardians: a Golem; a guardian angel; HAL, from the 1968 movie 2001: A Space Odyssey.

11 – Killers: The Price of Privacy: Re-evaluating the NSA, 2014; the Terminator; IEEE Spectrum.

12 – Frauds: The Mechanical Turk; automata by Jacques de Vauconson; Clever Hans.

13 – Asimov’s Laws of Robotics, formulated in his first robot short story, “Runaround”, in 1942.

14 – Arthur C. Clarke’s three laws, first formulated in “The Hazards of Prophecy” in 1962, revised in 1973.

15 – Alan Turing, Computing Machinery and Intelligence, 1950.

16 – The Turing test, from “Computing Machinery and Intelligence”.

17 – The Unperson of the Year by James Boyle at TechDirt.

18 – The eight scientists who assembled in Dartmouth for the first workshop on artificial intelligence in 1956: Oliver Selfridge, Nathaniel Rochester, Ray Solomonoff, Marvin Minsky, Trenchard More, John McCarthy, and Claude Shannon.

19 – Personal conversation with John McCarthy, 2006.

20 – Your A.I. Radiologist Will Not Be With You Soon by Steve Lohr at the New York Times”; Ed Zitron.

23 – Demis Hassabis, quoted in the Guardian as DeepMind’s mission at its founding in 2010.

24 – Ken MacLeod, The Cassini Division, 1998.

25 – Nick Bostrom, Superintelligence: Paths, Dangers, Strategies, 2014.

26 – Charles Stross, Dude, You Broke the Future, 2017.

27 – Turing, “Computing Machinery and Intelligence”.

28 – Games: chess, Jeopardy, Go (2016).

29 – Clockwise from top left: protesters freeze a Cruise robotaxi by placing a traffic cone on its hood; Microsoft services agreement; BBC; Nature; Hacker Noon; Red Dog Security; Waymos Freeze in Place, Snarl Traffic En Masse During Saturday’s Citywide Power Outage; The Register.

30 – Cory Doctorow, at Pluralistic.

31 – 404 Media

32 – Books: Ghost Work, by Mary L. Gray and Siddharth Suri (2019); Behind the Screen, by Sarah T. Roberts (2019); The Costs of Connection, by Nick Couldry and Ulises A. Meijas (2020); Atlas of AI, by Kate Crawford (2021).

33 – Books: Automating Inequality, by Virginia Eubanks (2019); Black Software, by Charlton R. McIlwain (2019); Unmasking AI, by Joy Buolamwini (2023); Algorithms of Oppression: Why Search Engines Reinforce Racism, by Safia Umoja Noble (2018).

34 – Chart showing the flow of money in the LLM ecosystem. Drawn by Edward Hasbrouck for the (US) National Writers Union.

35 – Good ongoing coverage of behind-the-scenes human workers at Rest of World.

36 – 1X’s Neo robot home servant, launched 2025.

38 – London’s Ringways: The first map of the capital’s unbuilt motorways.

39 – Ringways.

41 – Exponential future: Ray Kurzweil’s projection of the “law of accelerating returns”; Mickey Mouse drowns in exponential growth in “The Sorcerer’s Apprentice” in Fantasia, 1940.

42 – Turbli.

43 – Present harm, clockwise from top left: Kings College London; Ars Technica; Bureau of Investigative Journalism; Anadolu Ajansi; Toronto Star; NBC News; Guardian.

44 – Madeleine Claire Elish, Moral Crumple Zones: Cautionary Tales in Human-Robot Interaction (2019).

45 – Hildebrandt, Mireille, keynote at Computers, Privacy, and Data Protection 2025.

46 – Replace by Clawd.

Further reading:

Becker, Adam, More Everything Forever: AI Overlords, Space Empires, and Silicon Valley’s Crusade to Control the Fate of Humanity (2025).

Bender, Emily M., and Alex Hanna, The AI Con: How to Fight Big Tech’s Hype and Create the Future We Want, 2025.

Booth, Robert, at the Guardian: Number of AI chatbots ignoring human instructions increasing, study says.

Broussard, Meredith, Artificial Unintelligence: How Computers Misunderstand the World (2018) and More Than a Glitch: Confronting Race, Gender, and the Ability Bias in Tech (2024).

Couldry, Nick, and Ulises A. Meijas, Data Grab: The New Colonialism of Big Tech (and How to Fight Back, 2024.

Darling, Kate, The New Breed, 2021.

Grossman, Wendy M., Finding the gorilla.

Jones, Phil, Work Without the Worker (2021).

Marx, Paris, the Tech Won’t Save Us podcast.

O’Neil, Cathy, Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy (2017).

Shane, Janelle M., You Look Like a Thing and I Love You: How Artificial Intelligence Works and Why It’s Making the World a Weirder Place (2019).

Standage, Tom, The Turk: The Life and Times of the Famous Eighteenth-Century Chess-Playing Machine (2003)

Strengers, Yolanda, and Jenny Kennedy, The Smart Wife (2020).

Stross, Charles, Shaping the Future, 2007.

Waste management

This week, Amazon announced it would cripple a bunch of older Kindle models. Users will be able to go on reading the books that are already stored on their devices, but they won’t be able to add anything new, whether it’s borrowed, bought, or downloaded. The switch will be toggled on May 20, and applies to Kindle ereaders and Kindle Fires released in or before 2012. These devices had already been locked out of the store in 2022.

There is no benefit to consumers from doing this, even though Amazon is offering a substantial discount on newer devices for those who want to switch. There are presumably benefits to Amazon – namely, that it can update its store and other software without having to cater to older devices, plus sell an extra bunch of new ones. But overall, it’s a globally hostile move that creates a new pile of electronic waste composed of functioning hardware. One of these days, that’s going to be your car when some auto manufacturer decides that a “legacy” model isn’t worth supporting any more.

One option is to stop buying devices whose manufacturers demand that you surrender ownership in favor of their ongoing control. The other main possibility is to continue spreading right to repair laws so that a company like Amazon (or John Deere) wishing to shed itself of the responsibility of supporting older devices would be required to open them up to their users and the third-party ecosystem around them that would doubtless form. As the population of Internet of Things devices continues to grow around the world there will be much more of this – when we need much less. It’s absolutely maddening. Try a Kobo and the Gutenberg project.

***

It came out this week that language added in October 2025 to Microsoft’s terms of use says: “Copilot is for entertainment purposes only. It can make mistakes, and it may not work as intended. Don’t rely on Copilot for important advice. Use Copilot at your own risk.”

This is like the disclaimers that psychics and mediums in the UK issue to prospective customers to prevent exploitation of the credulous. A software company, though…if it’s going to admit up front that the service it’s providing can’t be relied on, why force it on people in the first place?

Obviously, the point here is to cover the company’s ass in case of lawsuits. It fits right in with companies’ general refusal to accept liability for problems created by the software they make. I’m glad the company is warning people, but the better solution – if the company can’t bring itself to discontinue it altogether – would be to either remove Copilot and let people download it if they want it or leave it turned off by default, warning people up front instead of in terms of use that normally wouldn’t have been read. Instead, what we have to do is search for instructions to remove it and hope Microsoft hasn’t made following them impossible.

***

In the midst of a lot of science fictional hype-scares about “AI” along come some more real concerns. We’ll start “small”: The New York Times has done a study that finds that Google’s AI Overviews are right 90% of the time. Sounds not-so-bad, until you remember the Law of Truly Large Numbers. That “90%” success rate when the remaining 10% is applied to trillions means the overall result is, as Ryan Whitwam puts it in summarizing the story for Ars Technica, “hundreds of thousands of lies going out every minute of the day”. That’s automation for you. Used to be you needed an army of bots to disseminate misinformation at any sort of scale, and even then it was less effective since it wasn’t backed by an apparently authoritative name (see also Microsoft, above).

More alarming are the reports surfacing about generative AI’s effectiveness at aiding and amplifying online crime. In November, Google announced internal researchers had found hackers experimenting with a script that interacts with Gemini’s API to create just-in-time modifications. Last month, at Hacker Noon polymorphic viruses, but again, this appears to be a step up in sophistication and speed.

At the same time, Casey Newton reports at Platformer, Anthropic’s latest model is likely the first of many that can find and exploit vulnerabilities in software in “ways that far outpace the efforts of defenders”. The announcement, which appears to have been inadvertent, was quickly followed by another, formally launching the new model, Claude Mythos, and Project Glasswing. The latter, per Newton, gives more than 40 of the biggest technology companies early access so they can use the model to find and patch vulnerabilities in both their own systems and open source systems that underpin digital infrastructure.

Unlike most AI-related scare stories, this one is backed by people who are usually sensible, such as Alex Stamos, formerly chief security officer at Facebook and Yahoo, and other security practitioners. These warnings are not coming from AI company CEOs with a concept to sell .

So: on the one hand, (hopefully) better software; on the other, (potentially) newer, more dangerous attacks. Ugh. To restore calm, I recommend Terry Godier’s essay The Last Quiet Thing.

Illustrations: Bill Steele, who in 1970 wrote the environmental anthem Garbage!.

The Silicon Valley chronicles

We should have seen this coming. At Platformer, Casey Newton reports that Meta has discussed pulling funding for the Oversight Board after 2028 after already reducing it “significantly” this year. Who needs fripperies like independent governance after reporting billions of losses in its Reality Labs unit, the bit responsible for the seemingly now-abandoned metaverse, the smartglasses, and, of course, AI? Per Newton, there are ongoing discussions about continuing the Oversight Board somehow, perhaps by opening it up to adjudicate for other platforms.

The reality is the Oversight Board’s moment has probably passed. In 2018, creating it was an effective public relations response to a series of scandalous revelations, beginning in 2017 with Carole Cadwalladr‘s work exposing Cambridge Analytica‘s use of Facebook to collect personal data to target political advertising. Its biggest moment was probably in January 2021, when the Oversight Board backed Facebook‘s decision to ban then-“former guy” Donald Trump for two years following the January 6 insurrection. Twitter banned him, too, and there was a brief crackdown on postings calling for violence. Much public criticism followed from whistleblowers such as Frances Haugen and Sarah Wynn Williams (2025), and the Netflix documentary The Great Hack..

Today, though,the big technology companies seem not to care. Maybe they will again if usage shrinks enough – the BBC reports an Ofcom study showing that UK adults are actively posting 61% less than last year. But defunding the Oversight Board seems consistent with the general decline of content moderation on Facebook and elsewhere. Neither fines, nor spreading age verification laws, nor other constraints can be remedied by funding an Oversight Board that is already rarely mentioned.

Besides, the years since 2018 have seen the “billionaire class” take a hard turn to the libertarian right; they show little inclination to be constrained personally or corporately by national laws or governments.

In a January 2025 interview, Netscape creator and venture capitalist Marc Andreessen provided this explanation: US Democrats “broke the deal”. That is, Silicon Valley supported Democrats as long as they left technology companies free of regulation. (Democrats might reply that they were responding on behalf of the public to changes in Silicon Valley companies’ behavior.)

In addition, Connie Loizos reports at TechCrunch that the billionaires who signed Warren Buffett’s and Bill Gates’s Giving Pledge would now like it forgotten. At Current Affairs, Nathan J. Robinson fears most Anduril CEO Palmer Luckey’s enthusiasm for incorporating AI and robotics into more and bigger weapons. Anduril was founding in 2017, the year before Google employees petitioned the company to exit its contract with Project Maven, the Pentagon’s effort to harness machine learning and automatic targeting. By 2021, Tom Simonite was reporting at Wired that Google was bidding on military contracts. A few weeks back, at the Financial Times, Jemima Kelly called Silicon Valley billionaires “enablers, keeping us distracted and dumb”, citing a recent podcast interview in which Andreessen said he never engages in introspection.

Available to link all this together is Jacob Silverman’s new book, Gilded Rage: Elon Musk and the Radicalization of Silicon Valley. Musk is not the sole focus of Silverman’s “guided tour through America’s self-designated innovator class” and its resentment of government and power to change it. Much of the book, which Silverman began researching in 2023, focuses on other high-dollar funders such as David Sacks and DOGE co-mastermind Vivek Ramaraswamy (whom Silverman introduces as the boss who fired him from an early job), as well as members of the “Paypal Mafia” including Peter Thiel and David Sacks. Silverman also includes chapters on Musk’s acquisition of Twitter, Saudi Arabia’s growing connections to Silicon Valley, the cryptocurrency boom, the fight over TikTok’s US presence, a so-far failed plan to take over California’s Solano County, Sam Bankman-Fried’s rise and fall, and the choice of JD Vance as Trump’s running mate. The book ends with the donors’ success – that is, Trump’s election in 2024.

With Gilded Rage, Silverman revives a formerly niche publishing subgenre , which documented the beginnings of this shift. First on the scene in the US, to the best of my knowledge, was northern California native Paulina Borsook with a 1996 essay for Mother Jones, Cyberselfish. In it, and in the subsequent 2000 book, she laid out Silicon Valley’s refusal to recognize the government assistance and military funding that enabled its wealth and growth. To Borsook, who described herself in the 1998 book Wired Women as the “token hippie feminist writing for Wired“, Silicon Valley’s turn to the right and distaste for government were already visible even then. In November, David Streitfeld profiled Borsook at the New York Times and noted the price she paid for her contrarian view.

In a 1995 essay The Californian Ideology, Richard Barbrook and Andy Cameron pushed Europe to take a different path.

Silverman’s most recent predecessor is Douglas Rushkoff’s 2022 skewing of “The Mindset” in Survival of the Richest. In Rushkoff’s telling, these high-wealth individuals are planning their safety and/or escape during and after “the incident” – that is, whatever catastrophe is going to wipe us all out.

So Silverman is less documenting a shift than he is describing an outcome: a political wave whose emergence into the mainstream only seems sudden.

Illustrations: Political cartoon from 1904, showing Standard Oil’s stranglehold on US industry (via Wikimedia).

Also this week:
At Plutopia, we interview Paulina Borsook.

Eating the web

“Traffic to my blog has plummeted,” a friend said recently. Over decades, he’s built a thriving community, and his core users persist. But Google was crucial for bringing in new readers – and its introduction of AI and changes to its algorithm have punished small sites.

This week, Sean Hollister reports at The Verge that Google is using its AI to replace the headlines on news stories. For Google, it is, as Charles Arthur comments at The Overspill, a “small” and “narrow” experiment – until it becomes a feature. For The Verge, however, the impact is noticeable: the headlines it crafts to market its journalists’ work are being replaced with boring titles that do not accurately convey the articles’ content.

Then, the week before last, Joe Toscano reported at Forbes that Google has patented a system that uses AI to rewrite website landing pages to produce customized versions for its users. Toscano links this to an earlier announcement in which Google announced a protocol to make websites’ structure more readable to AI agents. Toscano suggests that taken together the two elements allow Google to break websites apart into their component parts for reassembly by AI agents into whatever version they identify as best for the user they represent.

In the early 1990s, someone I met directed me to read the work of Robert McChesney, whose books recount the cooption and commercialization of radio and television, also originally conceived as democratic, educational media. Helping to prevent a similar outcome for the Internet is a lot of what net.wars has always been about. Now, Google, which would not exist without the open web, wants to eat the whole thing.

***

On Tuesday, a jury in a New Mexico court found Meta guilty of misleading consumers about the safety of its platforms and enabling harm including child sexual exploitation, as Katie McQue reports at the Guardian. The jury has ordered the company to pay $375 million in civil penalties. Meta will appeal. Snapchat and TikTok, which were also accused, settled before the trial began.

The New Mexico attorney general’s office says it intends to pursue changes to platform design including age verification and “protecting minors from encrypted communications that shield bad actors”.

On Wednesday, a jury in Los Angeles found YouTube guilty of deliberately designing an addictive product. As Dara Kerr reports at the Guardian, the case was brought by a 20-year-old woman who claimed her addiction to Instagram and YouTube began at age six, damaging her relationships with her family and in school and causing her to become depressed and engage in self-harm. The jury awarded her $6 million, split between Meta (70%) and YouTube (30%). Both companies say they will appeal.

They will have to, because, as Kerr reported in January, there are more of these trials to come, and even to trillion-dollar companies thousands of fines can add up to real money. In a consolidated case, in California state and federal courts thousands of families accuse social media companies of harming children. Reuters reports that more trials are scheduled: a school district in Breathitt County, Kentucky in federal court against Meta, ByteDance, Snapchat, and Google, and one in state court in California in July against Instagram, YouTube, TikTok, and Snapchat.

In January, the Tech Oversight Project reported newly unsealed documents contained the “smoking gun” evidence – that is, internal email discussions – that the four companies deliberately designed their products to be addictive and failed to provide effective warnings about social media use. Certainly, the leaked documents make it sou9nd like a plan. Tech Oversight quotes one: “Onboarding kids into Google’s Ecosystem leads to brand trust and loyalty over their lifetime.” It’s hard not to see the commonality with Joe Camel and so many other marketing strategies.

Key to these cases is Section 230 – the clause in the Communications Decency Act that shields online services from liability for the material their users post and allows them to moderate content in good faith. The plaintiffs argued – successfully in New Mexico – that the law does not shield the platforms from liability for their design decisions. The social media companies naturally tried to argue that it does.

At his blog, law professor Eric Goldman discusses the broader impact of these bellwether cases. As he says, whatever changes the social media companies feel forced to make by the potential liability of myriad jury trials and new laws may help some victims but almost certainly hurt other groups who were not represented at the trial. Similarly, at Techdirt Mike Masnick warns that features like autoscrolling and algorithmic recommendations are not inherently harmful; it’s the content they relentlessly serve that is really the issue; cue the First Amendment. And few who are not technology giants can afford to face jury trials and fines. Are we talking a regime under which every design decision has to go through lawyers?

In a posting summarizing the history of S230, Goldman predicts that age verification laws will reshape the Internet of 2031 or 2036 beyond recognition, killing most of what we love now. So much doom, so little time.

Illustrations: The volcano of Stromboli, on which JRR Tolkien based Mount Doom in The Lord of the Rings (by Steven J. Dengler at Wikimedia.

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.