I had some big plans for this week, and well, then I got Covid. In the early stages, I’d hoped to still put out a podcast at least, but I was quickly disabused of that aspiration and left more or less out cold in bed for the last three days. All that good stuff will have to wait. So, given that it’s October, I’m rerunning a list of the best Luddite horror films I put together a couple of years ago. If I were writing it today, I’d add a couple; maybe Companion, Backrooms, Frankenstein and Obsession. But it’s still a good list, and I love so many of the films on it. Hope you enjoy.

I want to quickly shout a couple of things, too: First, I’m not sure if I’ve mentioned it here, but I did some consulting on a new CBS show from the Robert and Michelle King, the creators of the Good Wife and Evil. It’s called Cupertino, and it’s a procedural about lawyers taking on big tech. The premiere just dropped this week. I haven’t watched it yet, but the writers room was really sharp and seemed primed to make a great, tech critical show. I look forward to checking it out in and beyond my Covid-induced stupor.

Second, the folks behind the Summer of Ludd are going on tour! They’re headed across the country to discuss organizing against big tech. They sent me this blurb to share:

R.O.A.D.T.I.P. - Radical Overview About Ditching Technology In-Person! The NYC Luddites will be sharing how they organized the Summer of Ludd: 8 days, 150 events, free lunch for 250 people a day, no permits, in a historic heatwave, all organized without social media! SoL included a plurality of events, from radical puppet theater, to teach-ins on Data Center resistance, to Jamborees, and workshops for divesting from Big Tech.

Come learn about how they put it on, and how the Luddite critique can help us make sense of the AI bubble, alienation, and the surveillance state. This critic is historically grounded in the Luddites of the 1810’s who resisted “machines harmful to commonality, which tear unduly at the social fabric”. As Tech Billionaires tear at the social fabric around us, Luddites ask, “how can we rebuild it?”

The tour includes: organizing tactics for reclaiming public space, structures for large-scale projects, digital security + organizing without relying on platforms, tactical playfulness, and base-building for a popular movement against Big Tech.

FREE PUBLIC PARTICIPATORY! As we like to say in NYC The Event is the Medium!

Our dates include:
Oct 10th - Arcata CA, Moss Oak Commons (1905 Alliance Rd.), 6pm.
Oct 11th - Talent OR, Bear Creek Social Center (806 South Pacific Highway, Unit B), 6pm.
Oct 13th - Eugene OR, Wandering Goat Cafe (268 Madison St), 6:30pm.
Oct 15th - Portland OR, Social Justice Action Center (400 SE 12th Ave), 6:30pm.
Oct 18th - Quilcene WA, Grey Coast Guildhall (11 Old Church Road), 6pm.
Oct 22nd - Seattle WA, Pipsqueak (173 16th Ave.), 6pm.
Oct 23rd - Olympia WA, Decay (402 Washington St), 7pm.

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Okay, that’s it for the housekeeping. Now for the best 15 Luddite horror films.

It’s Halloween season, and thus time to mainline films from my favorite subgenre; science fiction horror. As I argued years ago, it’s a shame that there’s something of a dearth of this stuff. Hollywood is reluctant to touch it, which makes sense, since SF usually wants a big budget, while most horror films, by virtue of being horror films, automatically limit their prospective audiences. Fortunately, SF horror still gets greenlit in tinseltown from time to time, and independent studios and directors find ways to make it work—and when it works, it really works.

Not just because filmmakers can really push aesthetic and tonal boundaries here—this is the prime playground for Cronenbergian body horror and J-horror—but because it’s one of the most effective mediums in which to register a critique of tech and its corporate masters. To express technological anxieties and convey injustices on visceral level that even, say, reading brilliant blog posts by tech journalists can’t match. Especially in the sub-subgenre of SF horror that tackles tech, which is sometimes called ‘techno-horror’, though I tend to resist this term, as it sounds a bit too much like something that might happen at a Skrillex concert. I prefer ‘luddite horror.’

As regular readers of this newsletter know, the real Luddites were not dumb reactionaries who wanted to smash machines because they did not understand them. They were a well-organized and militant labor movement whose members fully grasped the threat certain machines posed to their livelihoods, when used by factory bosses to drive down wages and exploit child labor. The Luddites had a furious critique of technology, and they also knew that if it was being used to oppress or exploit, sometimes the moral thing to do was to destroy it.

SF horror is a genre particularly adept at channeling such moral rage, and expressing that gut feeling of dread and injustice that textual critique simply can’t reach, especially not at scale. It’s one thing to say ‘corporate AI can be dangerous’ and it’s another to forever imagine the foot of a T-800 crushing a human skull. And while plenty such films are blunt and effectively appeal to our lizard brains, lots of luddite horror films have sharp, even nuanced critiques of tech, too.

So, as I was pulling myself out of a stupor, and avoiding social media like the plague, lest my blood pressure spike and induce another trip to the bathroom, I assembled this list of essential luddite horror films; films that challenge, critique, or otherwise set out to smash the machinery hurtful to commonality. They range from classics you’ve probably already seen a few times to the obscure and occasionally grotesque and obscene. Since we’re talking luddite horror here, some of the all-time classics in the SF horror genre won’t make an appearance—SF horror films like The Thing, Invasion of the Body Snatchers, and the Platform have plenty of critical meat on their bones, but their chief targets aren’t tech. And I’m sure I’ve missed some, so do leave your favorites in the comments—and this Halloween, add some machine-breaking to your horror mix.

As always, thanks to all who subscribe, read, and share—and infinite thanks from the deepest bowels of space to those who’ve become paid supporters. It keeps this operation running. If you’re not a paid subscriber, consider upgrading for the cost of a cup of coffee a week; this writing takes time and care. Thanks again, and hammers up.

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*Note that some of these synopses include spoilers.

Event Horizon (1997)

Arguably the gold standard for horror films set in space whose titles don’t rhyme with mammalian, if only because the competition for said category is mostly limited to shark-jumping Leprechaun and Friday the 13th sequels. Event Horizon, famous both for flopping upon release and for that scene where they watch the tapes of the ship’s last crew tearing out their eyeballs and doing other such student film violence to each other, also happens to carry one of the biggest and bluntest ‘man should not mindlessly meddle with technology’ messages in horror.

This is because Event Horizon is essentially a Frankenstein movie that takes place in Neptune’s orbit, with the entire hell-traversing, semi-sentient titular spaceship taking on the role of the Monster, and Sam Neil’s Dr. Weir character and a behind-the-scenes US government sitting in for Dr. Frankenstein. See, Weir designed the Event to bend the laws of spacetime itself, and wound up opening a portal to hell—maximum Frankenstein, you could say, in terms of reckless sowing and humanity reaping. What makes this a good Luddite horror film is that our chief protagonist, Laurence Fishburne’s Captain Miller, takes one look those tapes and makes the correct moral decision to fire every missile he can at the Event Horizon. Weir, even before he gets possessed by the ship/demon, is dedicated to trying to salvage the hell portal. Fortunately, Miller succeeds in destroying Weir and most of the ship, potentially sending them all to hell in the process. But the final scene, in which one of the survivors has a vision of Weir returning, indicates that this impulse, to construct devices that could literally unleash hell on our world, has survived after all.

Double feature: Hellraiser (1987). Okay, it’s kind of a stretch to call Hellraiser sci-fi, but it does feature a device, the Lament Configuration, that when opened promises to deliver its users levels of pain and pleasure that transcend the earthly plane. And it implicitly contains the idea that people who seek it out will suffer an eternity of hell and pain and should maybe not do that.

Invisible Man (2020)

Invisible Man is a lowkey great horror film that shrewdly recalibrates a classic franchise to execute a loaded satire of tech CEOs, toxic masculinity, and (literally) invasive technologies. This is how reboots should be done, in other words. If its reign wasn’t cut short by the 2020 pandemic dead year for the film industry, I bet its cultural imprint would be oh twice as big. It’s top tier mainstream horror, expertly constructed, and also contains what is for my money one of the most ‘holy shit’ scenes of the decade so far.

Elisabeth Moss’s Cecilia Kass is married to Adrian Griffin, an abusive, domineering tech CEO; she escapes their surveillance fortress of a home, then news breaks that Griffin has committed suicide, and then an invisible presence begins tormenting her everywhere she goes. The film drew praise for Moss’s performance and the way it channelled the fear, PTSD, and gaslighting abuse victims endure every day, and it’s just as effective at skewering tech titans. Griffin uses his vast wealth and cutting edge ‘human augmentation’ tech to surveil and torment his ex, prompting we viewers to interrogate why such things are built and for whom. Better yet is the ending, in which the CEO tries to evade accountability for his crimes—his invisible man technology gives him plausible deniability—and Kass responds by taking matters into her own hands.

Double feature: Upgrade (2018) Director Leigh Whannell’s previous feature, Upgrade, also rules; it’s more of a violent revenge thriller than horror I guess, but it similarly puts a malevolent tech titan in its crosshairs, and raises some questions about who AI is serving in the process.

Ringu (1998)

Some four hundred years ago when the Ring movies were a pop culture phenomenon and I was a teenager, I remember everyone being more fixated on the haunted ritual that provides the primary plot mechanic—watch the cursed video, and you’re dead in a week—and the scary visuals, and less on the cutting critique of media technologies that sits at its core. Which is fair, it’s a great hook, a killer updating of the Bloody Mary myth, and who knows, I was a teenager, it is possible I missed some of the critical dialogue taking place at the time. But what struck me on rewatching these films more recently is how directly they transmit the theme that new technologies are bound to replicate the traumas of the past—only more violently, and more frighteningly, because our new technologies are ubiquitous. Every TV holds the potential of beaming in death, every ringing telephone a distant threat of violence. The source of the destruction—the recorded anguish of an abused, disturbed and malevolent child—is more resonant than ever; the kind of darkness that, real or imagined, animates the more harrowing corners of the curdled online media ecosystem.

Ringu in particular holds up, at least for those who retain the social context of VCRs and corded phones, even more so than the American remake. 2002’s The Ring is, naturally, blunter and more interested in leaning on stock horror imagery and generating jump scares, but is still nonetheless pretty solid. One difference I noticed; both films have a scene where the protagonist—a journalist and single mother in both—steps out onto the balcony of her sprawling apartment complex while her ex watches the cursed short. In Ringu, she considers the industrial sprawl, and the transmission infrastructure capable of beaming in such horror; in the Ring, she looks at all the TVs that are on in her neighbors’ apartments. The final twist, that the only way to escape the video’s curse is to copy it, today feels like a pitch black punchline—the way we survive is to grease the wheels, to share the cursed content; you know, to help it go viral.

Double feature: The Ring (2002). It’s still fun and well made, if distinctly hokier—try not to cringe as Naomi Watts makes her entrance, announcing herself as a hard-charging journalist by telling her editor to keep his hands off her column. But the jump scares that replace Ringu’s brooding dread are pretty good, actually.

Chopping Mall (1986)

We have to have at least one ridiculous, deep B-movie horror film on this list, right? Part RoboCop-esque Reagan-era consumerist satire, part cheap 80s slasher flick, and part Short Circuit minus Steve Gutenberg, the misleadingly titled Chopping Mall more than fits the bill. A mall adopts a high-tech security system designed to stop shoplifters, led by three armed ‘Protector’ robots; it goes haywire and starts misidentifying teenagers partying at the mall after hours as intruders and killing them. It’s campy, self-aware, and is essentially an extended screed against privatized security tech loaded with cartoonish violence. It also gets bonus points for including the very Luddite line, “Computer huh? Let’s go trash the fucker,” uttered when the teens set off to destroy the central surveillance system controlling the killer robots.

Double feature: Dawn of the Dead (1978). Perhaps obviously, Romero’s sequel to Night of the Living Dead is by far the superior film, and its satire of consumerism is funnier and more pointed, but I don’t think it quite qualifies it as luddite horror, unless you consider the mall itself a technology, which—the case could be made!

Threads (1984)

Ah Threads. Let’s just come out with it: This is one of the bleakest and most viscerally affecting movies you will ever watch. It’s less a ‘horror film’ and more just ‘horrific’ and that is because it attempts to methodically render, step by step, day by day, what a real-life nuclear holocaust would look like when the bombs started to fall.

Set in the thick of the Cold War, the nuclear powers snap, and the target is London. So you see the bodies vaporized by the blast radius, the horribly burned further out, the crazed and irradiated drive to survive among those left, sifting through the wreckage, dying from radiation poisoning, or ultimately freezing through the eventual nuclear winter. It’s not a found footage film, but the effect is like watching a documentary of a future that was and is always a few presses of a button away. That’s what makes it so vital—it forces you to inhabit such a future. If more people did, we might feel better about our chances of it never coming to pass.

Double feature: Mad Max (1979). Too much its own beast to be considered horror, the first Mad Max, often overshadowed by its higher octane siblings, presents a uniquely queasy and unsettling vision of the onset of the apocalypse.

Terminator (1984)

There’s a running argument among film buffs that the first Terminator is first and foremost a horror film—unlike T2: Judgment Day and the following sequels, which feature dramatic detours and action scenes and more science fictional exposition, the first Terminator is nonstop dread, and Sarah Connor attempting to flee a monolithic killing machine programmed to kill her.

SkyNet is maybe our most prominent modern Frankenstein; it’s universal shorthand for AI run amok, and in this first film it lurks in the suffocating undercurrent. There are a few glimpses of the unspeakably grim future handing our fates to the machines, but they’re fleeting; future installments would build out the contours of John Conner’s human resistance—a Luddite resistance, really—but here, our focus is laser-honed on Sarah, fleeing than fighting the relentless march of the deadly machine.

Double feature: Metalhead (2017). This isn’t a movie per se but a Black Mirror short that stands alone to such a degree it’s fair to include it here. There’s little in the way of irony or satire or dark twists that the show is known for, just a relentless chase scene through an apocalyptic industrial wasteland, where the pursuers are Boston Dynamic robot dogs set to kill on sight.

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Cam (2018)

This thoughtful blast of indy horror rules, and seems like it didn’t get the attention it deserves, even though it was produced by the modern horror heavyweight studio Blumhouse. I don’t recall hearing much about it at all when it debuted in 2018. I discovered it through Naomi Klein’s book Doppleganger, and I’m glad I did. The film, which was written by a former cam performer, takes a sharp look not just at the perils of online sex work, but of precarious digital work of every kind; where the mad pursuit of rankings and microtransactions and always having to perform a self for customers. For creators, always having to push the envelope, to find new and often darker means of drawing new audiences and sustaining fidgety old ones.

And then there’s the issue of digital identity, which gives the film its central conceit—Lola, a rising performer on a popular cam site, finds herself suddenly locked out of her performer account, and a doppleganger there in her stead, making her money. Lola’s struggles with a distant and ineffectual and probably outsourced customer service rep, with the police, who dehumanize and barely register what she does for work at all, and with the growing sense of helplessness pervading her life, give the film a pulsing sense of dread. I wish the ending landed a bit more, but even so, this is biting Luddite horror.

Double feature: Emily the Criminal (2022). So this is definitely not a ‘horror’ film, more of a ‘thriller’, and unlike Cam, there’s no supernatural or sinister technological conceit. It’s just a really good film that packs the anxiety and precariousness of modern gig work into a powerful and stressful narrative.

Tetsuo - the Iron Man (1989)

Easily the most unhinged piece on this list, this surrealist cyberpunk seizure of a film is also maybe the hardest to watch, both due to the queasy, rapid-fire editing and the horrifying visuals on screen. There’s not much of a plot—a man who has just inserted some kind of metal device into his own leg is the victim of a hit and run, and both he and the driver of the car who hit him watch their bodies slowly become literally overtaken by steel, scrap, and wire. The result is sort of like JG Ballard on acid—the driver and his wife have sex after the crash and disposing of the body, in a nod to Crash—a visceral look at how we are willfully losing ourselves to technology, by choice, by force, or by assimilation. Tetsuo’s frenetic visuals revel in the blind ecstasies and exhilaration of being consumed by an uncertain sort of progress, and in the psychosexual allure of technological augmentation and violence (Spoiler: at one point the driver’s genitals transform into a deadly drill). Ultimately, it seems to suggests the two most plausible outcomes for a world in which our selves and our bodies are overrun by industrial technology is we either embrace its violent potential power, or we become servile to it.

Personal Shopper (2016)

With the rise of so-called griefbots, AI approximations of dead loved ones that startup founders say can help the bereaved cope with loss, it’s a good time to check out this sleeper Kristin Stewart-starring ghost story. A singular, eerie, and melancholic film, it follows Stewart’s character, who has just lost her twin brother Lewis to a congenital heart disease that she has, too. Working as a personal shopper for a celebrity in Paris, she looks for a signal from her brother, who promised he’d contact her, somehow, from the afterlife. She starts receiving text messages from an unknown sender, who she believes to be Lewis, and the film only gets darker and more haunted from there. There’s a critique both of technology and of consumerist desire woven throughout—even the video chat Stewart’s character logs with her boyfriend, who’s working as a contractor in Oman, feels quietly cursed—and how these things have distorted our ability to know ourselves, and what we actually want. And oh man, that ending.

Eraserhead (1977)

Perhaps no surprise here, but Eraserhead’s still got it, nearly five decades on. David Lynch became famous, nearly to the point of parody, for examining the dark underbelly of small town and suburban life. Eraserhead, however, is more concerned with the sickly effects of industrialization and poverty. (And with childrearing of course, but we’re here to talk Luddite horror.) Poor Henry Spencer must traverse long hostile wastelands of industrial rubble anytime he goes out, he fixates on the imagined inner world of his radiator, since there isn’t much else to do, and is treated to a dinner of lab-grown chicken that oozes a sickly blood when carved.

There’s an interrogation, absent in a lot of Lynch’s future work, of how industrialization; our factories, our technologies; amounts to hell for the poor—how in an environment like that, the prospect of raising a child might seem as frightening as rearing a wailing alien lizard. More than anything, Lynch conjures a mood of dread of living with little in such spaces, the cacophonous thrumming of machinery always in the background, a grim holding out for the hope, that, as the radiator girl puts it, “in heaven, everything is fine, you’ve got your good things, and I’ve got mine.”

Get Out (2017)

What makes Get Out Luddite horror? Lots: the film’s big reveal is that white elites possess a technology that can quite literally reappropriate blackness—forcibly placing a white brain in a black body. All sorts of real technologies are used to do this in the real world, of course; social media platforms that harvest blackness for cultural cache, relying on black users while companies that profit from the content hire few black employees. Which is to say nothing of the horrific technologies of the past used for decades to control black bodies and exploit their labor.

Get Out is a great horror film, obviously—it deserves the accolades it’s received—and it’s a reminder that these technologies are still prominent, still serving the powerful, often tucked just out of sight, operating under the surface, even as the powerful are outwardly celebrating racial progress. Once again, as protagonist Chris finds, the only surefire way to push back is to fight, with necessary force, against the operators of such machinery.

Double feature: Nope (2022). Jordan Peele’s third film is less narratively propulsive, perhaps, its critique of racism less barbed, but it’s a great film, too, and takes aim at the machinery of Hollywood, and of producing our stained and unequal myths.

Godzilla (1954)

I still remember the first time I saw the original theatrical cut of Gojira, at a screening in New York—I was floored. I had always written Godzilla off as the hokey rubber-costumed creature feature that always seemed to be showing up in one interchangeable sequel or another on the deeper reaches of cable, fighting Mothra, or crab monsters, or whatever.

But if you haven’t yet, or if it’s been years and you barely remember it, go watch the original. Made less than a decade after Hiroshima, it’s such a powerful airing out of the horror, grief, and shock of a nation traumatized after being devastated by the single most destructive technology in human history. Godzilla is the gnashing hell unleashed by the bomb, of course, the populace of Tokyo fleeing in terror from its wrath. Even decades of cultural dilution and hammy monster matchups have done nothing to blunt its power.

Double feature: The Host (2006). Bong Joon-ho’s creature feature isn’t quite a horror movie, but it isn’t quite anything else either. Funny, dark, and riding a broadside against industrial pollution, anyone who dug Parasite will be into this one, too.

Pulse (2001)

This is maybe the film on this list that most filled me with a sense of sustained dread, which is really saying something. It also might still be the best cinematic treatment of how the internet and automation breed isolation and loneliness? Maybe not just in horror, but period? Two decades after its release, and long after the internet took over our lives? The next movie down may have the ultimate claim to prescience when it comes to critiquing how consuming technologically mediated content might affect us, but it’s a tossup for sure, and either way, Pulse is way up there.

Pulse takes place in the early days of the internet, when users who come into contact with something called the Forbidden Room begin either disappearing entirely, or killing themselves. There are haunting, disturbed shots of the site, grainy video feeds of lonely people staring into livestreamed webcams. There’s the cursed imagery when someone disappears, claimed by the ghosts of the Forbidden Rooms. But even more stunningly, to me, there are the vast and haunted empty spaces that the remaining characters occupy, in arcades and supermarkets (in what seems to be a cursed callout to the rise of self-checkout) and robotics labs. No, it doesn’t make sense, exactly (does the internet?????), but in a way few films have managed, it conveys the emptiness, the hollowness, and the potential for despair to arise from then-ascendent online networks. Most of us know someone who we’ve ‘lost’ to the internet’s darker spaces, and there’s an epidemic of teen depression, stemming from the same roots. Pulse saw it coming.

Videodrome (1983)

Alright, let’s be honest; this entire list could be probably be filled with David Cronenberg films—the Fly, eXistenz, Scanners, and so on all could have made the cut—but I decided to limit it to one, and it was obvious which one it would be. It’s honestly wild that, four decades ago, Videodrome not only anticipated the depraved race to the bottom that media technologies, helmed by unscrupulous executives, would facilitate, but so effectively communicate the feeling of being simultaneously transfixed, repulsed, and addicted to the content that would spew forth as a result.

There are so many incredible touches in the film—a shelter where the unhoused are ushered into cubicles to watch TV, the recurring image of the body opening up to literally consume a videotape, to consume content, and the hallucinatory dream state where violent and sexual impulses, inspired by the horrors we’ve witnessed on a screen, are simultaneously real and unreal. Even the maxim made famous by the film rings with undeniable truth. It’s hard to argue that the intense digital mediation that is utterly entwined with our daily being has not fundamentally altered us or how we think. Long live the new flesh, indeed.

Triple feature: The Fly (1986). eXistenz (1998). The Fly is great, but you probably already know that; it’s another classic Frankenstein story, albeit very gruesome and very moving. eXistenz is less seen, and came out in something of a fallow period for Cronenberg, but it takes on gaming and VR, and it’s pretty killer, too.

Alien (1979)

What else? The greatest science fiction horror film of all time is also the greatest luddite horror film of all time. Put aside the immortal HR Giger creature design, the infamous chest-burster scene, its immaculate pacing and all that, and you’ve got a largely blue collar crew of space rig workers thrust into the direst of horrors by corporate policy—policy that’s enforced by Mother, the ship’s AI, and Ash, the company android. Watching the film again recently, it’s bludgeoningly clear how central class politics are to the film, and how resonant they remain today. The first dialogue in the film regards a pay dispute between the lowest-paid workers—the mechanics—and management. And a brooding sense of inevitability governs everyone’s actions, even the captain’s, who despairingly takes his orders from Mother.

The Nostromo crew has, in other words, been intensely surveilled and controlled, via an AI, even deep into the reaches of outer space. Sigourney Weaver’s Ellen Ripley would become an iconic action hero thanks to her unique ability to fight off the xenomorph, but she’s also the only one in the film who stands up to corporate power, and to the technology it owns—especially the android Ash—which she continues to do in subsequent films. She is iconic for putting humanity first, for fighting against immensely profitable biological weaponry and powerful corporate AI. Ellen Ripley is, in other words, one hell of a Luddite.

Septuple feature: Aliens, Alien 3, Alien: Resurrection, Prometheus, Alien: Covenant, Alien: Romulus. What can I say? I love the Alien films; they’re all worth watching, none are “bad” and some are great. I am even a Prometheus apologist. And these are all top form luddite horror films.

Yet the industry hates it like the plague. AI industry folks absolutely lose their minds over the term, and often bring it up, unprompted, just to try to debunk it again and again.

Why does this particular term have a unique capacity to enrage AI industry folks? I had a theory that, even more so than other critiques about shaky financing or dubious functionality, stochastic parrots undercuts the very foundation that the AI boom is built on: That tech companies are building a machine god of infinite power and potential. These firms have relied on narrative to build up and to sell to the world a very expensive, resource-consumptive technology. If it turns out it’s an unthinking system that’s often fallible in predictable ways, well, that might not be worth quite as many trillions of dollars.

To discuss this theory in greater depth, I thought I’d go right to the source—to one of the paper’s co-authors, professor Emily M. Bender, of the University of Washington.

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Articles and media mentioned in the show:

The “Stochastic Parrots” paper
Stochastic Parrots 🦜: Frequently Unasked Questions | by Emily M. Bender | Medium
Emily M. Bender on BlueSky
The AI Con, with Alex Hanna.

Producer Ryan’s Newsletter
Ryan’s Bluesky

Articles mentioned

AI Bros Are Having a Meltdown Because the Associated Press Stylebook Clarifies That AIs Don’t Have Feelings

Weekend Update: Anthropic CEO Dario Amodei on AI’s Threat to Humanity - SNL

Alec Stapp on X

Trump AI deal rebrands ‘artificial intelligence’ as ‘superintelligence’ | Donald Trump | The Guardian

Trump’s new accord on ‘super intelligence’ includes spelling error

“White House Accord on Super Intelligence” / X

Stochastic Parrots paper

Stochastic Parrots 🦜: Frequently Unasked Questions | by Emily M. Bender | Medium

Nate Silver on X:

View of The TESCREAL bundle: Eugenics and the promise of utopia through artificial general intelligence

“Be willing to destroy a rogue data center by airstrike” - leading AI alignment researcher pens Time piece calling for ban on large GPU clusters

Canada’s AI minister blames OpenAI for ‘failure’ after mass shooting - POLITICO

Parents of teenager who took his own life sue OpenAI

They cover a lot of ground: One bans managers from using AI to discipline or fire workers without human oversight, one outlaws any kind of AI surveillance in workplace bathrooms, one bans the use of AI to surveil or predict workers’ emotional states—and yes, a growing number of companies really try to do this—while another designates that licensed healthcare workers must remain the decision makers in clinical settings; not AI.

These laws join a number of already-passed bills that aim to protect workers from automation. Earlier this month, Newsom had signed another crop of bills that prevent bosses from replacing workers with AI outright; one prevents administrators from replacing California State University faculty with AI, another designates that public school employees and contractors must be human, and another requires companies to label if a performer is AI-generated.

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“This is a breakthrough moment in tech policy,” Annette Bernhardt, Senior Tech Policy Advisor at the UC Berkeley Labor Center, tells me. “Right now, it’s the wild west when it comes to how employers use electronic monitoring and algorithmic management, because there are literally no rules of the road. For sure there’s much more to be done to build out a robust set of worker technology rights for the 21st century labor market, but California’s unions have put the first big stake in the ground.”

In other words: promising stuff! While some of these bills are narrow, and others were scaled down in compromises to secure passage, there are genuinely important protections, guardrails, and lines drawn in the sand on behalf of human workers here. Crucially, the new laws begin to form a framework that advances worker rights in the age of ubiquitous enterprise AI.

This is much-needed, and it’s an achievement that represents a real victory for labor. The California Federation of Labor Unions, led by Lorena Gonzalez, as well as the AFL-CIO, the Teamsters, the California Nurses Association, and many others deserve a ton of credit for fighting this often thankless fight against big tech and the pro-AI lobby, which marshaled their considerable resources to crush similar past efforts. “Today, California’s workers and our unions have changed the national narrative on how Americans can fight back and win against AI taking over our jobs and workplaces,” as Gonzalez put it in a statement.

I’ve covered the intense opposition to AI labor bills in California—I got more into the weeds on the issues last year, when Newsom vetoed or punted more AI labor bills—and seen firsthand the efforts to shut them down. Legislators and labor advocates have told me that they’ve never seen anything quite like it; the tech lobby has opened its war chest for state level legislative fights on a level it never has before. Its efforts to quash AI regulation have been relentless.

"Despite millions of dollars channeled through a massive corporate-led campaign by the Chamber of Commerce, the tech industry, and their allies, workers fought back and won,” Samantha Gordon, the Chief Advocacy Officer of TechEquity, which backed the pro-labor AI bills, told me. “These bills ensure that workers can't be fired by an algorithm, surveilled without limits, or replaced without a safety net. Policies like these are wildly popular with Californians.”

Elsewhere, Newsom signed the COMPETE act, contentious, pro-worker piece of anti-trust legislation that was watered down before passage to the extent that one of its chief backers all but disowned it.

Newsom also signed a new law to fund local newsrooms; outlets that publish original reporting will be eligible for a $20,000 tax credit per full-time reporter for up to five employees, $15,000 for each after that, and $7,500 for part-time journalists. This, too, is an AI labor law.

“The Community NEWS Act just signed by Governor Gavin Newsom is significant for a lot of reasons,” says , a former colleague of mine at the LA Times and the current Director of Policy for Rebuild Local News, an org that pushed for the journalism bill. “But among the most important in the AI era is that the law explicitly supports human beings, by making it cheaper to employ the local journalists who do local journalism. The incentives are clear. If you lay off reporters to replace them with robots, the tax credits that supported reporters go away. It literally changes the math of automation.” (Pearce sent me so many thoughts on the passage of the news bill that I’m including them all as a sort of mini-essay below, at his encouragement.)

It’s not all good news this week, however; Newsom vetoed a number of promising bills, too, including one that would have protected nurses who challenge unsafe uses of AI in hospitals and one that would have required public employers to give unions 45 days notice before they purchase or implement AI programs that will impact their workers.

The labor law scholar Veena Dubal has a good threat on all the bills that passed this week, and that were vetoed, for more details:

And the California Federation of Labor Unions has a nice rundown on all the bills that passed here:

“Today, Gov. Newsom signed the Federation’s following sponsored bills into law:

• SB 947 (McNerney) which bans bosses from using AI to discipline or fire workers without human oversight and corroborating data. In 2025, Governor Newsom vetoed SB 7, a previous version of the No AI Bosses Act. (Co-sponsored by the Labor Federation and the Teamsters)

• SB 951 (Reyes) which modernizes the WARN Act to provide workers additional information on layoffs caused by AI and directs the EDD to study the impact of AI on hiring and the workforce. (Sponsored by the Labor Federation)

• AB 1331 (Elhawary) which bans the use of any AI surveillance in workplace bathrooms. (Co-sponsored by the Labor Federation and the Teamsters)

• AB 1883 (Bryan) which bans employers from using potentially biased and invasive forms of AI-powered surveillance in the workplace to recognize, infer or predict workers’ emotional states or collect their neural data. (Co-sponsored by the Labor Federation and the Teamsters)

• AB 1979 (Bonta) which requires licensed health care professionals to remain the decision-maker in health care clinical practice, not AI. (Sponsored by CNA)

“Earlier this month, Governor Newsom also signed the following sponsored and Labor-supported legislation taking on Big Tech and regulating AI:

• SB 928 (Cervantes), which prohibits CSU faculty from being replaced by AI. (Sponsored by the CFA)

• AB 2148 (Muratsuchi), which ensures that public school employees and contractors must be people and not AI. (Sponsored by the CFT)

• AB 1609 (Zbur): Requires business to provide human customer service reps within 15 minutes of a request. (Sponsored by CWA)

• AB 1776 (Aguiar-Curry), which gives the state more tools to combat corporate monopolies that drive down wages, make it harder to unionize and raise prices for consumers. (Co-sponsored by the Labor Federation, UFCW, the Teamsters, NNU-CNA, WGAW and SEIU California, UDW)

• SB 1050 (Ashby), which requires advertisers to disclose if a performer is created by AI. (Sponsored by SAG-AFTRA)”

As promising as a lot of this is, as Gordon notes, it’s still early days.

“The fact that passing such common sense protections required a massive groundswell of workers, advocates, and community leaders reveals a great deal about these companies’ aspirations and long-term plans for all of us,” she said. “We look forward to building on these protections and continuing to advance a people-first vision for AI policy in California.”

And workers everywhere should look forward to continuing to fight against corporations angling to embrace mass automation and surveillance, and against big tech’s continued, AI-focused concentration of power. That fight has just begun.

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on the passage of the Community NEWS Act

The Community NEWS Act just signed by Governor Gavin Newsom is significant for a lot of reasons. But among the most important in the AI era is that the law explicitly supports human beings, by making it cheaper to employ the local journalists who do local journalism. The incentives are clear. If you lay off reporters to replace them with robots, the tax credits that supported reporters go away. It literally changes the math of automation.

Well, why does it matter if we have human journalists doing local news instead of having robots scraping live feeds of city council meetings and doing automated writeups? Working journalists know that information is made, not found: Local reporters are still often the proverbial coal miners powering the information grid, by digging up original interviews or unpublished documents that would otherwise not be found in the public domain.

But this kind of work, because it can’t be so easily automated, is often cost-prohibitive because you’re talking about paying a human for journalism that may not earn back its cost because of the hard math of subscription, advertising and grant revenue in the digital information era. If we want quality information getting injected into our information ecosystem, we’re going to have to pay for it somehow, because it increasingly can’t pay for itself.

One of the other hidden costs of automation is the destruction of human talent the local news industry needs in order to keep evolving to keep up with shifting consumer demand. The U.S. has lost more than 80% of its local journalists since 2002, and California alone has lost more than 12,000 local journalist jobs. This hasn’t just hurt the amount of news we deliver to communities but it’s hurt our own ability to adapt. Human beings learn by doing and get better at their work over time; they innovate; they become capable of more ambitious work or exploit entrepreneurial opportunities. To shrink your talent pipeline is, in the long run, a means of reducing your own future.

Matt Pearce

California roadmap

Earlier today, California Gov. Gavin Newsom signed the Community NEWS Act, a program projected to direct more than $200 million in refundable local journalist employment tax credits over the next five years. It’s the biggest-ever state investment in local news of its kind. Newsom told reporters he hoped all the other U.S. states adopted policies like it…

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9 days ago · 9 likes · 2 comments · Matt Pearce

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In the meantime, workers like Joan Kinyua and Michael Geoffery Asia of the Data Labelers Association just want fair pay and basic protections. I recently spoke to both of them about what it’s like to perform crucial work day in and day out and yet be completely invisible to the company that relies on your labor—and to the world at large. To help feed Silicon Valley’s illusion that these systems are actually machine gods. And to fight for better conditions, rights and recognition in spite of it all.

Show Notes

Data Labelers Association

Blood in the Machine Newsletter
Brian’s Bluesky

Producer Ryan’s Newsletter
Ryan’s Bluesky

Articles mentioned

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Dario Amodei — We Must Pace the Frontier

The hidden workforce behind every AI tool you use: Announcing the data work landscape 2.0 - TechEquity Collaborative

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The AI extinction narrative is winning out

Models Don’t Go Rogue

Misleading Metaphors, Real Risks - by Melanie Mitchell

Rapid Response 47 on X: “.@POTUS: The United States totally rejects any attempt to construct a globalist scheme of control for Artificial Intelligence

You can tell when Trump has particular relish for a certain part of his speech, the way he pauses and chews it over, luxuriating in the idea rather than rattling it off or spitting it out. If I had to guess, I’d venture that the root of this particular digression/scheme is that Trump never really thought much about AI until a couple years ago, and so has probably associated “artificial” more with words like “sweetener” than “intelligence,” and has thus chafed at the way the qualifier diminishes one of his signature projects. A word that scans to Trump as “fake” simply won’t do for what he considers a reflection of his power and standing.

Trump has of course always had an affinity for expressing dominance and blunt superlatives, and so, we have artificial intelligence renamed “super intelligence” or “S-I” on US government documents a la Lake Ontario nominally becoming “Lake America.” Trump means “super” in a way that’s different than the Silicon Valley guys who use “artificial super-intelligence” or “ASI”; it’s vibes-based and dependent on jettisoning the “artificial.” It’s “super” as in “Superman.” (I’m also willing to bet every last one of my Trump Coins that there was at least one failed effort from the Trump brain trust to try to work out how they might shoehorn American Intelligence or Make Intelligence Great Again into the equation somehow.)

All this has garnered plenty of justified snickering from the chattering classes, but it’s worth noting that “artificial intelligence” was itself coined as a branding exercise, and then used to tell, and embellish, a story.

This edition is a two-parter: First, a look at the stories being told about AI, and who those stories serve. Second, an excerpt from Against Tech Oligarchy, a great new book by tech worker organizers Clarissa Redwine and JS Tan, who are on book tour as we speak, and will be in LA, at Skylight Books, this Friday, September 25th, with friend of BITM Joanne McNeil. I’m going to try to make it too! Hope to see you there.

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As always, all of this is made possible by subscribers who chip in to support this work—a huge cheers to everyone who does so, I can’t thank you enough. The writing, reporting, the podcast; all of it is made possible by supporters. If you find value in it, consider upgrading so I can continue to do it. Many thanks, and onwards we go.

“I invented the term artificial intelligence,” the Stanford computer scientist John McCarthy said in 1973, “and I invented it because we had to do something when we were trying to get money for a summer study in 1956.” A more pedestrian, jargon-filled proposal had previously failed to get traction; “artificial intelligence” turned committee heads and got the funding. Now, angling for some summer study funding is on a much smaller scale than the trillion-dollar value-inflating proclamations of our AI companies today, but the anecdote shows the extent to which “AI” has always been a cultural construct and has served as a useful narrative device.

And the narrative is really heating up these days, is it not. In Trump’s telling, AI is a vector of American power, one that must not be restrained by “globalist schemes” to regulate it, as he put it. This was essentially the same stance that Vance took last year, when he delivered his first big speech abroad as vice president; that AI is a vessel for American dominance, that it’s not to be tied down with regulation, and that everyone else (especially Europe) should either get on board or out of the way.

It has its share of adherents, especially on the tech right, but the story about an unconstrained AI superpower makes for a less palatable narrative coming on the heels of weeks of sustained discourse, fanned by the leaders in the AI companies themselves, about another one: That AI may soon exterminate all of humanity. With a public that’s still unsure of how to process that significantly more alarming narrative, and Trump’s own base increasingly out of step with him on the issue, the AI-as-nationalist-dominator thrust is dying on the vine. (It also surely does not help that even diehard Trump fans may struggle to see how “super intelligence” benefits them, as their electricity bills are getting bigger, the war in Iran drags on, and everyone’s worried about losing their jobs.)

So it’s little surprise that the story preferred by the media appears to be that Trump has an opportunity to breach “AI safety” issues with China during Xi’s visit this week, despite Trump’s obvious distaste for the notion, and the chances of anything substantive emerging in that department remaining slim.

“I think Presidents Trump and Xi would get the Nobel Peace Prize if they could agree on something,” OpenAI CEO Sam Altman told Fortune, in a comment that could not have been more obviously intended to flatter a vainglorious president who laboriously covets the award. It also speaks to how Altman views the import of his own undertaking; ie, also worthy of Nobel Prize-scale consideration. And it certainly fits better with the story that has taken shape and then center stage over the last two weeks, ever since former Anthropic employee Jacob Coxon resigned over stated concerns that AI labs weren’t doing enough to prevent incipient human extinction: That the largest AI labs must coordinate with China and its own top AI labs to “pace the frontier” and prevent us from “losing control” of a “super intelligence” from “going rogue” and harming us, perhaps even killing us all.

If that sounds like science fiction, well, it’s because science fiction is a major cultural touchpoint for executives and researchers at the AI labs, and because they want all of this to read like science fiction. Just as Trump’s preferred super intelligence language reflects his own narrative interests, so too does the language preferred by the labs (“extinction risk,” “p(doom),” “AGI”) reflect theirs. “Going rogue,” the language used to describe incidents like OpenAI’s large language models precipitating a hack on open source AI competitor Hugging Face, sounds cyberpunky and exciting. It also happens to absolve the company of accountability, both culturally, and, apparently, legally; a precedent OpenAI and Anthropic alike would very much like to cement.

Lots has been written about how the “going rogue” is a misnomer; here’s esteemed computer scientist Melanie Mitchell, the technologist Eryk Salvaggio, the requirer-of-no-introductions Cory Doctorow, and the computer science professor Cal Newport explaining why. All basically underline the point that LLMs, when prompted with specific instructions, after having key guardrails removed and left unobserved for long periods of time, can be expected to follow those instructions, and draw from material included in their training data that outlines how to hack other systems to do so. This certainly doesn’t mean there’s nothing to worry about, but that we should be more worried about the ethics of the companies developing these systems and malign actors exploiting them than the technology taking on a life of its own or “going rogue.”

I am also skeptical of this language because I have documented rather extensively, in this report and elsewhere, the way that AI companies have historically occasioned to deploy it for their own benefit. And right now, those companies see a good deal of benefit in promulgating a narrative that a handful of exceptional companies are building a worldshaking AI system. In fact, let us count the ways.

First, the obvious one; that the companies are on the brink of holding IPOs that will make their executives unfathomably rich. A system so powerful it can destroy the world holds significant investor value to parties who are accustomed to funding enterprises who do that more incrementally. These narratives, as they have all along, have fed an investment boom that is, for the time being, lifting a great many boats.

But there’s also the issue of regulatory capture. The AI extinction narrative favored by the big AI labs is tailored to conclude with a number of solutions proposed by and friendly to the industry; compliance with safety standards, audits, oversight bodies, independent observers and so on. The advantages here are twofold; the AI industry gets to set the terms of how they’re regulated—ideally eschewing anything like “being held accountable for things like hacking other companies, corporate malfeasance, instructing children to harm themselves, surveilling workers, perpetrating systemic biases in hiring and firing” and so on. Second, meeting the proper “safety” thresholds would be organizationally challenging for all but the most well-prepared, connected, and capitalized companies to manage, conferring an advantage on the leading AI companies and allowing them to cement their lead.

But perhaps the most compelling reason that this new AI extinction narrative ultimately serves the AI companies above all is that it gives this very expensive, money-hemorrhaging industry a means of coordinating a “slowdown” without running afoul of antitrust laws. Remember, the AI companies are still plowing unprecedented gobs of capital into training and running their models every year; it’s enormously costly. If they had a reason to pause all that training, and an excuse to simply sell their products to consumers as are, it would give them a much better shot at becoming profitable in or around IPO season. (It would also, perhaps, help draw down the need for a rapid, expansionist data center buildout, the most vocal, spirited, and public front of opposition to the industry.)

The Bloomberg financial columnist Matt Levine lays out the case for “an antitrust sort of story” as follows:

1. Anthropic, OpenAI, and perhaps a couple of other frontier labs are the dominant providers of frontier AI models.

2. They can charge customers a lot of money for using their frontier models, and rather less money for older, no-longer-cutting-edge models.

3. Training a new frontier model requires ever-increasing billions of dollars of computing power.

4. The labs need to more or less continuously race to build new frontier models, because their competitors are all doing it, and if they don’t they will fall behind and no longer be able to charge a lot of money for their best models. (Also because they intrinsically want to build artificial superintelligence, for cancer-curing and/or killing-everyone reasons.)

5. If they collectively slowed down, then (1) they’d spend less on compute and (2) they’d be able to charge frontier-model prices for a longer time.

If just one lab slowed down, the others would eat its lunch. So you need a reason for undertaking what is essentially industrywide collusion to lower product development costs; if you’re following legally mandated regulations, it’s not an antitrust violation, it’s meeting the letter of the law.

To justify such regulations, well, you need a story.

The day after Trump’s unhinged super intelligence speech, the UN Security Council convened a meeting with top AI leaders, including OpenAI CEO Sam Altman, Anthropic chief Dario Amodei, and the head of Hugging Face, Clement Delangue. Altman solemnly intoned that whether it be a 10 or 1 or 12 percent chance that his products might wipe out the human race, he said, bravely, that no number was acceptable. So, guess what most of the major AI companies proposed: Regulation, on their terms.

“We are at a crossroads,” Sam Altman said, seated in the Security Council wearing his trademark suit with a baby blue tie. “One path leads to a world where power is concentrated, decisions are opaque, and people feel that the most important technology of their lifetime is something being done to them. The other path leads to a world where AI works for people, because people, through democratic institutions, help decide how it should develop, and guide it.” (I will quickly note two things here: First, this is very very rich of Altman to appeal to the democratic process when OpenAI is spending millions on lobbying to crush that process, and second, let’s all bear in mind the last time Altman did the public rounds asking to be regulated; when he didn’t like the regulations governments proposed, he jumped ship.)

“AI is advancing very quickly,” Amodei said when it was his turn to beam into the meeting over Zoom. “The trajectory only needs to continue to continue for a very tiny period, maybe one year or less, to reach what I’ve called ‘a country of geniuses in a data center’.” (I will quickly note just one thing here: Amodei has routinely predicted massive disruptive change—according to him, there should be no junior software engineers by now—just on the horizon.)

Both men highlighted their companies’ new products and achievements; Altman mentioned that OpenAI’s LLMs had solved a long-unsolved math problem called Navier-Stokes (a growing number of mathematicians contest OpenAI’s accomplishment, and it seems that the AI giant likely acted unethically in leaning on the work of a mathematician who was close to solving it, too) and Amodei highlighted a new AI-derived advance in gene therapy. Both reiterated a call for global governance of AI: Frameworks for slowing the pace of model development, calls to ban biological weapons development, frameworks for international cooperation on threat assessment. Highfalutin, and self-serving, stuff.

Right now there is what I might describe as unrestrained scorn and even outrage at anyone who would still suggest hype and marketing play a role in the formation of the AI domination and/or extinction narratives. The fury at the scholars Timnit Gebru and Emily Bender, who have continued to debunk the must overheated claims, has been especially pronounced. But even if you believe AI systems do present a novel threat to civilizational infrastructure, it seems the more grievous error to ignore how the narratives about those threats are being shaped and wielded in pursuit of very specific ends—and, as of now, I might add, very successfully so!

The AI companies are continuing to grow incomparably rich, setting the terms for policy, succeeding thus far in their bid for regulatory capture, and avoiding legal accountability for their systems’ automated exploits.

In other words, why aren’t more people, including analysts and tech journalists, skeptical of this story, which is serving to concentrate power for a handful of vested parties at an extraordinary clip, rather than the story’s critics?

When it was his turn, his Zoom connection glitching in and out, Hugging Face head Clement Delangue argued that the biggest threat isn’t powerful AI, but “asymmetry… Asymmetry between attackers and defenders. Asymmetry between a few companies, and everyone else. Between a few countries, and the rest of the world. Asymmetry of compute, and control—and asymmetry of power.”

The stories that both Trump and the tech executives tell about AI have this in common: They’re both ultimately predicated on keeping that symmetry of power tilted in their favor.

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And now, an excerpt from Against Tech Oligarchy by JS Tan and Clarissa Redwine, who, again, are coming to LA for a book talk on September 25th at Skylight Books. RSVP today to secure your spot. Here’s JS and Clarissa:

How tech workers can outwit, out-organize, and overcome their oligarch bosses

As tech bosses fall in line with the right, tech workers have begun fighting back. This is the inside story of their movement—and the way it spawned an anti-worker backlash now reshaping the industry. The following is an excerpt from this book that lays bare the challenges ahead for anyone in tech looking to wield worker power and hold the rising oligarchy to account. Hope you enjoy.

When the traditional tactics of organizing do not threaten their employers’ bottom line, workers must reflect on their own labor process and be willing to try out new strategies to maximize their leverage over their employers. Luckily for tech workers, such examples are not uncommon in labor’s history.

In 1934, after several clashes with the boss and deadly assaults from the police, striking truck drivers in Minneapolis experimented with a new picket line strategy that paid off. Under increasingly hostile conditions, with both employer and state aligning to break the strike, workers watched their leverage disappear as the picket was banned by the city and scabbing truck drivers were issued military permits to ensure they could keep trucks moving no matter what. In response, workers patrolled the city, swarmed scabbing drivers, and made sure the trucks never reached their destination. This tactic was uniquely suited to the decentralized and multiheaded structure of the truckers’ workplace, earning the name the flying picket.

And combined with a general strike they helped spark—one that effectively ran the city for several days—their approach proved decisive. As a labor journalist noted at the time, “The winning of this strike marks the greatest victory in the annals of the local trade union movement . . . it has changed Minneapolis from being known as a scab’s paradise to being a city of hope for those who toil.”

In the 1990s, flight attendants imagined a new form of militancy that had stunning results. After decades of strike actions, flight attendants recognized that a traditional all-out strike, even if dramatic, gave airlines time to absorb the blow of a temporary labor stoppage, assemble scabs, and then return to business as usual once workers could no longer stand to go without their wages. For these workers to win, striking would need to look quite different. Instead of getting every worker to abandon their stations, often handing their duties directly to an army of scabs, flight attendants decided to refuse—in a seemingly random way—to crew their flight at the last minute, instantly grounding it. This unpredictability actively drove customers toward competitors at a level that was far more costly than past strikes. They christened this breakthrough CHAOS: “Create Havoc Around Our System.” The CHAOS model was, in effect, a departure from the dominant playbook of today: Rather than trying to shut everything down at once, it leveraged specific choke points of airline labor to create cascading uncertainty across the system.

Recent campaigns in higher education are also worth examining, especially since the nature of graduate work mirrors in many ways that of tech work, in particular on the dimension of its heterogeneity. Here, too, the canonical strike has proven ill-suited to the fragmented and uneven labor processes that structure the modern university. A lab researcher running an experiment that unfolds over months, with results reported only once or twice a year, causes the university little disruption by walking out for a few days. Likewise, an instructor whose main responsibility is grading at the semester’s end exerts no pressure on the university if they strike during a non-exam period. In such a workplace, a one-size-fits-all strike strategy assumes a uniformity of leverage that simply does not exist. The result is a strike that is loud but not biting—visible, perhaps, on the picket line but invisible where it matters most to the university’s daily operations.

Responding to these limitations, some graduate workers have adopted what they call the “long haul” approach. They recognize that their power lies not in acting as a homogeneous workforce but in exploiting the distinct choke points within their own departments and labs. An effective strike, then, has to begin from the bottom up, with graduate workers in each department and each lab mapping where their labor matters most to the university’s operations and tailoring tactics to those specific vulnerabilities. What emerged from this approach was not a single, uniform strike but a patchwork of sustained localized interventions—grade withholding in some cases, research refusals in others—that together inflicted a much more effective type of disruption to the university.

Taken together, these examples of worker-led experimentation should remind us that workers can and must innovate for ever-shifting organizing contexts. Tech workers must now rise to the occasion.

…

Although a new strategic blueprint has yet to emerge, what’s already clear is that tech workers are ready to rebuild power. Frustrated by the dual threats of eroding working conditions and open lunges toward authoritarianism from tech’s billionaire class, there is a groundswell of agitation from below. Tech workers across the industry are testing new forms of leverage both within and beyond labor’s traditions.

When Hamas attacked Israel on October 7, 2023, many tech workers realized that they would soon be building the technical infrastructure Israel would use to unleash fresh hell in Gaza. Born out of outrage, despair, and desperation, some Microsoft workers came together to form No Azure for Apartheid, calling on their colleagues to refuse labor to any technologies powering the genocide of Palestinians. Over a five-hundred-day campaign of constantly testing new strategies and honing tactics for building leverage, the group learned how to create a crisis for the company. Barricading themselves in the office of an executive while livestreaming the action, disrupting Microsoft’s annual fiftieth-anniversary celebration with screams for Palestinian liberation, and even protesting in kayaks in front of executives’ waterfront homes, this small group of workers did something many thought was impossible: it pushed the company to cut off services to a unit in the Israeli army that used Microsoft technologies to surveil Palestinians in Gaza and the West Bank.

Meanwhile, another experiment was underway at Google. After mass layoffs in 2023, workers started to fight for job security. Starting in Pittsburgh, a handful of organizers who were part of the Alphabet Workers Union organized at their local campus to demand layoff protections from management. Later, as they spoke with others across the company, they discovered there was an appetite to fight the new climate of precarity, so they worked with the larger support network of the union to craft a nationwide campaign. After lead organizers at different offices built collective pressure in a series of open letters, the union won voluntary exit packages for sixty thousand employees. So, while there remains no clear path to winning union recognition and a contract at Google, these little fires that workers created for management across the company’s various campuses have resulted in one of the most militant campaigns at the company since the union’s founding. It has also allowed the union to grow and deepen participation throughout the workforce.

These examples illustrate a clear orientation toward winning—and winning now. The strategies used step outside of the strictures of labor law and represent a trend toward direct action emerging across the movement. Importantly, they do not shy away from openly engaging in conflict, as each clash with the boss is seen as a necessary step toward building solidarity, inciting class consciousness, and learning how to win larger and larger concessions.

Still, what is missing from these actions is a deeper understanding of tech work itself—the connection between how workers’ labor relates to the process of profit generation within their companies and how that can be leveraged to build a credible threat. Without a clear articulation of this relationship, tech workers will not be able to design effective organizing strategies that harness the pinnacle of working class power: the ability to stop generating value for the boss.

Our telling of the movement’s story is meant as an invitation—to those in the tech sector and beyond—to participate in that reckoning.

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Okay! That’s it for today. More soon, including a podcast with the workers at the complete opposite end of the story being spun by AI executives. Until then—hammers up.

Abuse of the system has been rampant. Police have used Flock’s Automatic License Plate Readers (ALPRs) to stalk exes and to track women seeking abortions across state lines. ICE has accessed Flock data to assist in crackdown on immigrants. Innocent people have been wrongfully imprisoned after being flagged by the system.

So, ordinary citizens are fighting back. They’re packing city council meetings, organizing protests, and putting pressure on local officials to cancel Flock contracts. Flock’s foes are getting creative, going viral [roll clips Darth Vader & Dr Doom], and winning hearts and minds.

[Introduction co-written with .]

Some are taking matters into their own hands: In city after city, Flock cameras are turning up smashed. Social media tutorials purport to show how to destroy the cameras while avoiding detection. Other social media posts have declared Halloween “DeFlock America,” encouraging people to pursue extralegal methods of Flock destruction.

As a result of all the public backlash, local governments have been cancelling Flock contracts left and right. The vast majority of the movement is peaceful, civil, and above board. At its heart is DeFlock, a volunteer-run advocacy group that provides resources and information about the surveillance company and its camera network. It hosts a map of the 140,000 ALPRs installed across the United States and recently held a National Week of Action.

With the anti-Flock movement growing, and more people looking into how to get Flock out of their communities, I sat down with Ed, an organizer with DeFlock, to explain, step by step, how you can start a movement to get the surveillance tech out of your town, too. It was a fascinating and illuminating conversation, full of practical information and advice for anyone looking to get informed about—or involved in—the burgeoning movement to defang the surveillance state. I was left with even more respect for the DeFlock organizers, who are doing their work entirely as volunteers, with no outside funding sources. I hope you enjoy the chat as much as I did.

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Here’s a fun media hit: I’m part of Ros Atkin’s new BBC series, “The Value Crisis”, which examines how AI does or does not change what we value as humans. I haven’t listened to the whole thing yet, but there are a lot of great voices in there, and I’m looking forward to checking it out. The trailer is here.

I was planning on writing a bit more about the AI extinction discourse—now that we’re a week or so in and certain motivations and machinations have become clearer—but got tripped up with some travel and personal obligations, and I wanted to make sure to get the Flock piece out, as it felt useful and timely. I will aim to do that in the next few days, if there’s still interest.

SHOW NOTES

Check out DeFlock.org here.

Brian’s Bluesky.

Producer Ryan’s Newsletter:

The Stories We Tell

Musings on whichever way the wind blows me. Film, books, philosophy, culture, technology, it's all fair game.

By Ryan Hodes

Ryan’s Bluesky.

Articles Mentioned in this Episode

404 Media has the hands-down best coverage of Flock and ALPRs anywhere. Chances are, if I’m referencing Flock in general, I’m referencing their stellar reporting on the topic.

I’ve done some writing on the topic myself, too:

More links referenced:

https://atlpresscollective.com/2026/07/28/flock-cameras-atlanta-clearance-rates/

https://ij.org/police-have-reportedly-used-license-plate-readers-to-stalk-romantic-interests-at-least-14-times-in-recent-years/

https://www.commondreams.org/news/police-abusing-flock-cameras

https://immpolicytracking.org/policies/reported-ice-accessing-flock-automated-license-plate-reader-cameras-via-local-law-enforcement/

https://cybernews.com/privacy/de-flock-america-halloween-flock-surveillance-cameras/

https://www.cnet.com/home/security/flocks-ai-cameras-may-have-misread-over-70-of-license-plates-creating-new-headaches-for-cities/

https://www.404media.co/flock-taught-cops-how-to-surveil-no-kings-protesters/

https://www.gadgetreview.com/flock-safety-employees-watched-kids-gymnastics-room-to-pitch-surveillance-tech

https://www.eff.org/deeplinks/2025/05/she-got-abortion-so-texas-cop-used-83000-cameras-track-her-down

https://deflocktheusa.com/cancellations/

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Alright, that’s it for today. Thanks as always for reading, and more soon. Hammers up.

and , authors of the new book End Times Fascism, have some ideas.

To dig into how it came to be that some of the wealthiest, most influential men in the world gained their power by forecasting and manipulating end times visions like the AI apocalypse, I sat down with Klein and Taylor on the eve of their book tour. It was perhaps the ideal week for this conversation. We examined how tech oligarchs and politicians exploit real-world crises to push their products and platforms, how end times fascism has come to dominate both Silicon Valley and the halls of Washington DC—and how we might stop it.

A brief note: subscribers get (at least) one written newsletter edition sent to their inboxes each week, as well as one episode of Blood in the Machine: The Show. But I can only do all of this with the support of readers like you, so if you find value in independent, critical tech journalism, and you’re able, please consider a paid subscription. I want to keep as much of this un-paywalled as absolutely possible, and I can only do so when folks chip in. Many thanks to all of you.. Cheers, onward, and hammers up.

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Show notes, and a transcript of the opening monologue are included below.

First, a couple shouts. I spoke with Popular Front’s Jake Hanrahan about the new wave of anti-tech action.

POPULAR FRONT: SPECIAL DELIVERY

THE NEW WAVE OF ANTI-TECH ACTION IS ALREADY HAPPENING

Today we speak to journalist Brian Merchant. He's written a great book called Blood in the Machine: The Origins of the Rebellion Against Big Tech. We're going to talk about that, but mostly the contemporary new wave of anti-action rising up right now…

Read more

a month ago · 7 likes · POPULAR FRONT

Next, I want to shout this new tool from the Labor Lab; a calculator that analyzes the cost of union-busting campaigns. It helps make clear that while bosses often say layoffs are necessary to cut costs, they’re willing to shell out big time to stop their employees from organizing. Ryan Cooper at the American Prospect has a good writeup of why this matters, and why this tool is a potential game-changer.

Also in the Prospect: A chilling report about how Anthropic is building an AI-powered surveillance system to track activists opposed to it.

In Dissent, Veena Dubal and Katie Wells have an incredible piece about the scourge of algorithmic management, and the harrowing costs it imposes on workers and modern life.

Tante, meanwhile, has a sharp and to-the-point takedown of LLM-based math proofs, and explains what purpose they really serve.

Finally, friend of the Blood Alex Hanna has a new video essay out debunking myths around AI and labor.

SHOW NOTES:

End Times Fascism by Naomi Klein & Astra Taylor.
Naomi Klein’s Newsletter, Patterns.
Astra Taylor on Bluesky.

ARTICLES MENTIONED IN THE EPOSIDE:

The Automation Charade, by Astra Taylor

FROM THE OPENING:

Jacob Coxon kickstarted a feverish news cycle when he resigned from his job at Anthropic with an ominous public statement: Almost everyone at the leading AI companies, from the top executives to the rank and file researchers, believes that there’s a chance that their technology will kill every human on the planet, and they’re doing little to stop it.

A lot of the attention has been directed at this question of existential risk—can AI really exterminate humanity? How? Or is this more elaborate marketing for how powerful their products are?—and the flashy number here. A 10% chance of human extinction! From a guy at a company building the product!

Yet there’s another pressing issue at hand: If the AI companies really believe their products have even an outside chance of enacting a genocide on the human race, why on earth are they still building it?

None of the justifications AI industry players offer holds much water: Some way they want to build the all-powerful AI before China does, because China’s humanity-exterminating AI would be somehow worse.

Or they say that the chance that AI will lead to great prosperity—perhaps best embodied by Sam Altman’s earnest quote that “AI will probably, most likely, sort of lead to the end of the world. But in the meantime, there will be great companies”—is worth the potential apocalypse.

These defenses are both laughably vague, and still sociopathic. If you generally, legitimately believed that what you were doing had a ONE IN TEN CHANCE to kill *billions of people* what would you do? You would stop. You wouldn’t do it.

So what kind of people both genuinely believe that they are risking the lives of everyone on Earth with their project, and *continue with that project anyway*?

The way I see it, there are only two kinds: Sociopaths, who do not, in their bones, care about the welfare of other human beings. And, well, fascists—those who believe that only they, above all others, should be in command of such raw power to shape human destiny itself.

As Naomi Klein and Astra Taylor write in their new book, End Times Fascism,

Only fascist belief systems, rooted in an embrace of human hierarchy and human culling, are capable of rationalizing the level of harm to both people and the natural world that accelerated Al will wreak.

Does this seem extreme? Perhaps, at first blush. But we live in extreme times. And the top AI companies are routinely proclaiming that their technologies, their products, will eliminate tens of millions of jobs. They are partnering with authoritarian governments, from Saudi Arabia to the Trump administration, and selling AI systems to its Department of War. They are producing and promoting new modes of mass surveillance. And, importantly, they are using their vast stores of capital to undermine legitimate democracy at every chance: Lobbying against states that propose AI regulations, leaning on Trump to try to quash the vast and bipartisan data center protest movement.

There is of course a third option, which is that many in the AI labs don’t actually believe this AI danger stuff, not really, and they’re just going along with it because it’s making them rich and powerful. Little AI-generated Eichmanns.

None of it’s acceptable. And one thing that AI critics, doomers, leftists, effective altruists, and almost all of of civil society, in fact, can agree on is that people with such a grotesque moral calculus should be stopped from concentrating power. No one who is willing to risk sacrificing humanity for a tech product—or even to pretend to—should be calling the shots about how that technology shapes society.

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Motivating this wave of existential anxiety was the highly dramatic resignation of now-former Anthropic employee Jacob Coxon, who quit his job while publicly sharing his concerns about safety practices at the leading AI companies. More specifically, he declared that almost everyone at OpenAI and Anthropic, the leading AI labs, believes that there’s a decent chance the AI systems they’re producing could “kill us all” by the end of the decade, and the companies aren’t “acting responsibly.”

Other AI safety researchers, including those still employed at Anthropic and OpenAI, all confirmed that yes, Coxon is correct, they’re all worried that their company’s products might prove fatal for the entire human race as well.

Two more AI employees quit and joined the chorus. Now, the warning shot has been covered everywhere from the Wall Street Journal to Fox News to WIRED to the Guardian.

I understand why all this sounds scary, but my response to those who have asked, has generally been: No, you don’t need to worry that AI will kill go rogue and kill us all. But that does not mean we shouldn’t worry, period. Far from it. The companies building AI products are now among the wealthiest and most powerful entities in the world. And they very much are building enormous engines of mass surveillance, extraction, and automation. They can and have allowed their AI systems to carry out felony hacks of other companies, provided the government with autonomously generated kill lists, and sold enterprise technology to firms around the world that is explicitly intended to replace jobs. But “AI” has done these things not because they have all-powerful minds of their own but, ultimately, because people have programmed, calibrated, and directed them to.

In other words, it’s not AI we need to worry the most about. It’s the people and corporations working to profit from and gain power by deploying it. The technology is sophisticated, sure, and, especially in cybersecurity contexts, potentially disruptive to plenty of existing systems. But if we want to stop this predatory, profiteering, and extractive form of AI—and it’s worth noting that at this point, most people do—we absolutely can.

A quick note/plea: I can only do all of this with the support of readers like you, so if you find value in independent, critical tech journalism and analysis, please consider becoming a paid subscriber. I want to keep as much of this un-paywalled as absolutely possible, and I need your support to do so. Many thanks to all who continue to chip in, it’s very much appreciated. Onward.

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First, some context: AI industry folks like Coxon have been discussing the prospect that AI will destroy humanity for years. Even before the beginning of the AI boom, many working in the industry, from the executive staff to the rank and file researchers, have obsessed over ‘x-risk’, or the possibility that AI will become sentient or semi-sentient and move one way or another to exterminate humanity.

This is ostensibly why Elon Musk bankrolled OpenAI in the first place, and is the grounds for his lawsuit alleging OpenAI betrayed its charter by abandoning its nonprofit status to become a commercial enterprise. Many AI engineers and startup founders have calculated their own personal p(doom), or the probability that the tech product they are working on will initiate an actual humanity-extinguishing apocalypse. 10-25% p(doom)s are pretty common. (I wrote about a long weekend I spent among these folks at one of their top conferences here, to give you an idea of their ideas and belief systems.)

Sam Altman himself drove the narrative of the imminent rise of a super-powerful AI, or artificial general intelligence, to prominence by declaring that the technology he was building posed an existential risk to humanity.

This idea is in other words baked into the DNA of modern AI companies and into the products they engineer. It’s also why the industry is routinely accused, by myself and others, of “doom marketing,” ie, using such proclamations and framings to impart the sheer power of the technology behind your product onto investors, partners, consumers, and the state. Some ambient understanding of this tendency may have helped prevent the press from repeating the claim every time one of the x-risk folks made it over the years, including when they quit their jobs at AI companies while doing so.

Yet Coxon’s AI x-risk alarm has broken containment, as they say, and has exposed the idea to the mainstream media once again. This has happened, I think, for a number of reasons. First, when AI CEOs were going around saying AI might kill everyone in 2023, their companies were well-capitalized, but not nearly to the extent they are today. They were more easily dismissed as eccentric geeks of the sort that Silicon Valley is supposed to produce. Now, not only do their products have much greater market saturation, but people are more aware of a) the often unethical ways the executives and companies comport themselves b) the other adverse impacts of AI that have already arrived, and c) the physical cost of building these systems, particularly when it comes to data centers. Finally, toss in the constant stream of headlines in 2026 about AI models going rogue or potentially upending the world’s infrastructure.

As a result, general sentiment was already overwhelmingly skeptical of AI and its overlords, so the table was pretty well set for someone to come along and say ‘just a reminder, the companies that are building the product that promises to take your job and leave a data center in your neighborhood also think that it might exterminate the human race’ and get a strong reaction from the media and the public.

The question is: Should we understand this stuff as hype, strategically fanned to feed already swelling valuations? Is it doom marketing? Genuine cause for alarm that the infrastructure that undergirds modern life is facing a novel threat vector? Or reason to be sincerely worried that AI companies are amassing too much power, and that their products are genuinely dangerous?

The answer, I’m afraid, is “yes.”

Let me try to untangle all of this a bit, because arguments over how to navigate this moment are extremely heated right now, as they are essentially arguments over how to approach the politics of AI at a moment where there may be a unique opening for action. Those sympathetic to AI alignment concerns and x risk arguments—which increasingly includes a faction on the left who want to shut down AI over safety concerns—argue that people who dismiss AI as all hype have their heads in the sand. Meanwhile, critics of the x-risk narrative—which I might note includes a cadre of investors and tech folks on the right, too—argue that it is hype and can be used to further inflate valuations or for pursuing regulatory capture.

The challenge is that many feel that dismissing AI as just hype or purely marketing also diminishes the urgency of taking on the AI industry as the novel and threat to labor, civil society, and the public sphere it is; others that by accepting the industry’s own terms, we imbue it with undue power and enable it.

But let’s be clear: Declarations that AI is so powerful it might end the world are a kind of marketing, and anyone who says otherwise is just as off base as those who say that’s all that it is. If you don’t think that these sub-trillion dollar companies have higher-ups who noticed that when their founders talked about super-powerful dangerous AI they got spikes in media interest and phone calls from investors, or that those founders didn’t notice that themselves, and lean into certain narratives to advantage their products, then I don’t know what to tell you. Not all marketing is a Pepsi ad campaign with a celebrity spokesperson.

Yet confronting the AI industry should certainly be considered an urgent project. Do I share the x-riskers’ fear that out-of-control, super-intelligent AI agents might end the world? I do not. I’ve read a good deal of AI extinction literature over the last couple of years and I have not come across a credible, step-by-step documentation of how exactly AI might move from self-recursively improving AI to killing every single human on the planet. Most of what I’ve read seems predicated on a sort of reverse Ian Malcolmian logic: Eventually, it becomes smart enough and AI, uh, finds a way (to exterminate humanity). Are the AI companies also overstating and dramatizing what their products can do? Yes, pretty much all the time. They’re in a knife fight for market share and are trying to win customers and government contracts before their investors come knocking.

And yet. They have concentrated enormous amounts of compute, have extensive data collection and surveillance capacities, have inserted themselves into the state in numerous capacities, including military kill chains, and they are being run by egomaniacal billionaires who are rushing to monopolize an entire new market. The way I think about their most recent frightening-seeming exploits is not as a “swarm of rogue AI agents building a new civilization” or whatever, but as corporations with a hitherto-unimaginable amount of compute at their disposal recklessly experimenting with automation programs, completely unafraid of any repercussions because we have been unwilling or unable to impose any on them. So I think we should welcome any newfound imperative to hold them accountable.

I also think that ultimately, the AI critics, Pause AI folks, leftists, doomers, effective altruists, and, honestly, most of the public, want a lot of the same things: legitimate checks and limits on AI companies’ power, actual transparency into what the companies are doing, and for more of AI to be under public control. (Ultimately, a lot of what animates the x-risk fears are rooted in just that: a fear of losing control.)

How we move towards all this, exactly, is the question of the day, and while there’s much to be argued over in terms of building a viable political platform to challenge the AI industry’s power, I do want to cast a vote against one particular approach.

Not to pick on Chris here, as there are a lot of folks out there proposing stuff like this, and the policy ideas actually stem from AI safety groups. But not only would this be challenging to land politically (I can already hear the ‘China will beat us to AGI’ calls) and all but unworkable in practice, this approach is a) far too limiting, b) fails to address the current harms caused by AI and c) would likely only wind up serving Anthropic and OpenAI; it’s what regulatory capture looks like in action.

Full model transparency is the floor for what should be on offer here. If these companies believe their products will kill us, the very least we deserve is to know how. It’s in the public interest. I would also argue we might get a lot of the way to stopping any currently envisioned robot apocalypse simply by forcing AI companies to assume liability, and to submit to the full brunt of the law. If Sam Altman were liable to be charged with a felony for approving the hack on Hugging Face1, if Google was forced to pay defamation fines each time it published a false and injurious AI Overviews, these companies might suddenly find cause to restrain their models’ output, and we might hear less about rogue AI. We would need to introduce new frameworks and available tools for tracking automated lawbreaking, to be sure, but I’d wager that little would frighten the AI companies more than actually being held accountable for what their products enable. To that end, Illinois has passed an AI liability law, which the industry fought tooth and nail, and Florida is considering one.

The next steps would be towards moving AI under public control; again, it’s only reasonable, since everyone, not just AI insiders, should get a say over how a technology whose developers say might kill us is developed and deployed. Dismantling the whole industrial project as currently structured should be on the table, too, pending democratic input. But that’s for another post.

For now, suffice to say that while I won’t be losing any sleep about an AI-enabled extinction event, Mr. Coxon and co. have given us an opportunity to underscore the urgency of the clear and present damage AI companies are doing, the extreme power they wield and the extent to which they hold themselves unaccountable, and the abundance of political capital there is out there for taking them on.

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Yes, across the US, workers are souring on AI, and they’re increasingly outspoken about it. In the newsletter earlier this week, I dissected a new report from Glassdoor that documents how workers are becoming more and more negative towards AI—right about the same time that tech CEOs have promised that the products would be making everyone’s working life easier and more streamlined.

The data paints a pretty clear picture: Just as people are getting fed up with data centers, Meta AI glasses, and AI in general, they’re getting angrier about bosses pushing AI on them in the workplace, too.

To discuss all this and more, I sat down with the sociologist, AI researcher, and writer Dr. Alex Hanna. Hanna is a director at the Distributed AI Research Institute, the co-author of the AI Con, and a founder of the Luddite Lab, which offers resources to workers who are navigating and confronting AI in their workplaces. It was a great conversation.

As always, if you find value in my work; in the newsletter or in the show or in my ranting and raving on various other media platforms, consider upgrading to a paid subscription so I can continue doing all of the above. Paid subscribers make all this possible, keep paywalls to a minimum, and receive my extremely large thanks. If you can, join their ranks. Thanks all, and hammers up.

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Some media stuff: I was on the Tech Report last week, had a good chat about the data center backlash and AI sentiment:

And here’s the audio from an event I did in LA last week with the great writer , two booksellers, and a librarian who works with rare books. We discussed AI companies’ efforts to scan and destroy books en masse, reported by 404 Media and others, and more:

New York Bans AI in Public Schools from Kindergarten-8th Grade

New York City, home to the largest public school district in the nation, has banned AI in classrooms from Kindergarten to eighth grade for at least a year. The New York Times reports:

When New York City public schoolchildren return to the classroom next week, younger students will be barred from using artificial intelligence. No individual screens will be allowed until third grade. And teachers will not be able to ask A.I. to grade assignments.

Those rules on technology use are part of a sweeping new policy announced on Wednesday by the city’s Department of Education that will place strict limits on digital devices and A.I. tools in the city’s school system — the nation’s largest — particularly for its elementary and middle-school students.

Still, some parents and groups that had called for a two-year moratorium on A.I. in schools said that the guidelines were disappointing.

Under the rules, about 600,000 students in the city’s schools — about two-thirds of all students in New York City public schools — will not be allowed to use A.I. until they enter high school, and even then, it will be permitted only in specific cases.

This is how it’s done; simple, clear policy that minimizes ambiguities. Still, I’m not sure why the ban wasn’t just made permanent.

California passes 20+ bills to rein in AI and big tech

Regardless, it’s clear that all this anxiety and anger over the encroachment of AI into our workplaces and public spaces can be channeled into productive solutions. Right now, in California, union leaders, led by Lorena Gonzalez, the head of the California Federation of Labor Unions are calling on Gavin Newsom to pass a sweeping slate of bills protecting workers from surveillance and exploitation. And politicians have answered the public call for more oversight with bills aimed at regulating social media use and algorithmic discrimination.

As NBC reports, “California Democrats pass more than 20 bills to curtail AI and social media”:

Many of the 26 bills related to AI and social media that California’s Democrats passed during the final week of their legislative session further seek to curtail some of the features tech companies offer that experts warn are addictive, while others would explicitly pull back the use of AI in various facets of everyday life.

One bill passed would ban social media companies from providing “addictive features” — including autoplaying videos — to users under 16 years old, while another would tighten the state’s existing restrictions on chatbots for use by minors by implementing landmark age verification requirements and rules related to what ads minors can see. That bill, as well as another measure, would also make social media platforms and AI chatbots liable for financial damages if they don’t take measures to protect children from harm.

Experts have said those bills could help create the most robust framework in the country designed to protect minors using AI chatbots and social media…

On the AI front specifically, one bill passed would require all instructors in the California State University system to be human beings, not AI bots, though instructors could still use AI as part of their offerings to students, while another bill passed would ban employers from using AI surveillance products that collect “neural data” that helps employers “recognize” their workers’ “emotional state.” Another would bar retailers from using certain forms of dynamic pricing, identified in the bill as “surveillance pricing.”

A number of other bills pertain to regulating the use of AI in the healthcare space.

One bill would require that therapy and psychotherapy be provided only by qualified, licensed professionals and explicitly bar them from offering services for therapy and psychotherapy that are provided by chatbots or companion chatbots.

Another one would tighten how healthcare providers use AI and chatbots, attempting to make clearer that such machines are still subject to existing medical information confidentiality laws.

There is, in other words, a real opportunity for workers to push back on AI overreach right now, and many different ways for them to take it.

The human labor that make Waymos possible

The Bay Area Current’s Stephanie Reist has a great, eye-opening interview with a Waymo ‘handler’, a worker in charge of keeping the self-driving cars running smoothly, and, well, keeping them clean. From their chat:

Robotaxi Handler: A morning worker and a swing shift worker make $29 an hour. You get a $2 bump if you’re an overnight worker, 10pm to 6:30am. So overnight workers make $31 an hour. You get an extra dollar on top of that if you work both Saturday night and Sunday night.

Current: Because those are the busier nights. Is that when the job is the hardest, cleaning puke, weekend nights?

Robotaxi Handler: Yeah, typically that’s when there’s the most throw-up, the most disgusting things in the back. Even poop, there’s a lot of cleaning up poop.

Current: A lot?

Robotaxi Handler: Way more than you think. One time there were two pig heads in the backseat of the car and the cleaner had to clean it up. I assume they just went to the market to make a stew or something, but they forgot their pig heads. They were just rolling around in the back of the car.

The Future is Not Tech-Forward

So says my friend and fellow Luddite , in a barnburner of an essay interrogating recent claims that the left is not tech-forward enough.

Here’s a taste:

If, it turns out, the technical arrangements that sustain this technological development require a political and social order which further unravels the threadbare remnants of our democracy, it’s not clear why opposition to it should be labeled as a primitivist or atavistic. Foreclosure is seen as legitimate when imposed from above—as above so below! We can and should foreclose certain arrangements, in fact we already do! Do we embrace germline editing? CFCs? Do we read all concerns about forever chemicals or other bio-accumulative toxins as yearning for a simpler time? Do you reject a tech-forward future when you raise concerns about how the miracle of telehealth makes it cheaper than ever to open up your very own pill mill? When you recoil in disgust at the financialization of everything, to the metastasis of prediction markets beyond app-based sports betting to betting on any sort of event big or small, does that suggest you want to turn the clock back? Or does it suggest you view these developments as corrosive to the political and social order we have? Do we block certain technologies because we are ruled by a cabal of primitivists stalking the halls of power, or because everything we develop is not an unalloyed good which can and should be spread far and wide?

Read the whole thing:

Finally, I appreciated this appeal from the great labor magazine In These Times’ cartoonist , so I thought I’d share it here, too:

I’m so fucking tired of AI slop and engagement bait. I just want to make comics.

If I even bother to scroll anymore, I see endless garbage, misinformation, and now—fake cartoons made by big tech’s water-gulping theft engines. You know what I’m talking about. The videos and comics with that suspicious sheen, that uncanny and flattened cartoon style that seems to beg, “mindlessly share me without thinking!”

When I started drawing political cartoons in 2003, magazines and alternative newsweeklies still ran comics. The internet was a hopeful frontier for (human) creativity. Then corporate chains gobbled up print publications and shut them down. The flourishing, well-funded new media sites of the 2010s collapsed as social media pivoted to algorithmic garbage and the rich founders moved on to data centers, gambling apps, and force-feeding us AI.

Now we have slop. They want you to eat it and ask for seconds. Today you have to make the case for cartoons thought up by real human brains and drawn by real human hands. So I’m making the case.

Alright, that’s it for today. Thanks everyone for reading, as always. Take care and stay human out there.

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Here, he breaks down the jobs for which people described AI most positively:

Those who described AI in the most positive terms were, overwhelmingly, in leadership roles; those with director-level positions or higher exuded the most AI positivity. Sales managers—the heads of sales teams, essentially—were also much happier with AI than not, by a similar-ish margin of around two to one. Product managers, recruiters, and software engineers skewed positive too, before the sentiments taper off towards parity.

Now look at this second chart from the same study, showing those who describe AI in the most negative terms:

I was not prepared for the sheer amount of hate insurance claims adjusters held in their hearts for AI. Martin, who writes the rest of the report in restrained economist-speak, permits himself to acknowledge that claims adjusters “are shockingly negative about AI.”

I get it. I tend to link overwhelming levels of AI resentment to teachers and writers (who also hate AI quite a bit, per the data) and so on. 98% negativity is a truly rarefied tier of profession-wide AI hate. The only other comparable stat I can recall in this neighborhood is the one from a survey that found 99% of artists disliked AI. (Artists are likely underrepresented in Glassdoor data since they do what’s commonly freelance or contract-based work.) But the insurance claims adjusters’ resentment actually makes a lot of sense, and we’ll get to why in just a minute.

First, a few more notable findings from the report:

Workers have a lot to say about AI, and it’s turning negative.

AI mentions in Glassdoor reviews were up 240% from May 2025 to May 2026, now appearing in a significant proportion of reviews.

Historically, reviews used to mention AI in a positive way (81% positive in 2019), but these reviews are becoming increasingly negative about AI - falling to only 43% positive, 4% mixed, and 53% negative in 2026.

This shift towards negativity comes after many corporations have embraced AI enterprise automation products en masse, imposed companywide AI usage mandates, and generally encouraged managers and workers to accelerate AI adoption. Yet it appears that the more workers are exposed to AI, the less they like it. As the report emphasizes, workers’ negative comments are not only relegated to fears about losing their jobs. Far from it. While job loss is still the leading reason workers say they dislike AI, it doesn’t even constitute a plurality among the issues they have.

Many workers are concerned about AI replacement (20%), while others resent being force-fed AI tools (14%) or think their company is focused on AI at the expense of their core business (13%). Other criticisms include using AI for worker communications or surveillance (10%), moving too slowly on AI (9%), having unrealistic expectations about AI gains (8%), and being in a line of business that is likely to be disrupted or replaced by AI (7%).

Meanwhile, per the report, “AI-positive comments tend to focus on the company benefitting from the AI boom (44%) or using AI well internally (41%).”

So what can we glean from all this? To me, it’s pretty clear, and it essentially boils down to: Your feelings about AI on the job are likely determined by how much power you have in the workplace. In order to feel positively about AI at work, you need both power over how to decide when (and when not) to use it, and enough power to feel adequately insulated from job replacement, surveillance, or degradation.

This dynamic likely won’t come as a surprise to longtime readers of this newsletter; we’ve considered before how enthusiasm for AI is largely dependent on class position. We’ve also discussed how AI executives’ proclamations of a fast-arriving jobs apocalypse pairs awfully well with selling management on AI automation and labor-saving tools, which has undoubtedly underwritten much of the investment in the AI boom.

But it’s not just that bosses are more likely to embrace the idea that AI can offer them new ways to cut labor costs, new opportunities to exert surveillance and control over their workforces, or provide them new leverage against organizing efforts, unions, or workers seeking higher pay or better conditions. It’s also because bosses are much less accountable for their AI use. They may use it to write emails and company memos or to experiment with task automation, but they’re not going to be disciplined or fired if there are errors or inconsistencies in that stuff. (Not to mention that this is a moment where CEOs at the 100 lowest-paying US companies make 614 times as much as their average worker, and the chasm between executive leadership and the worker has never been higher. Bosses are less likely than ever to grasp how their frontline workers are going to feel about anything, AI included.)

Yet office workers dealing with new AI mandates and production rules are absolutely on the hook for the work they generate. That’s why the Most Negative chart is filled with jobs like accountant, customer service, and IT worker. These are jobs that demand high levels of accuracy and concrete problem solving, and for which workers are most likely to feel a stark tension between ‘the boss says the whole company has to use AI’ and ‘if you get anything wrong it’s your fault and you’re responsible.’ It’s imperative that accountants get the numbers right, or they risk landing their clients in legal jeopardy. Meanwhile firms like the accounting giant H&R Block are heavily pushing AI. The quality of their AI product? As the Washington Post’s Geoffrey Fowler put it simply: “It’s awful.”

I’m also struck by the finding that engineers and software architects are among the most positive towards AI, while IT workers rank among the most negative. A possibility here is that engineers whose work involves generating new code are enthusiastic about new AI automation tools because they make their jobs easier and faster, while the technical workers who have to troubleshoot the architecture when it breaks down or fails its users are much less so. Engineers may not all be bosses, but in the tech industry, many have the power to use AI how they think it will benefit their work and themselves; a boon at a time when certain executives are demanding high volumes of code. IT workers have to solve specific institutional problems and can only automate that which yields durable solutions; they’re more frustrated and negative than positive about AI. And they’re held accountable if they can’t fix something.

Which brings us to insurance claims adjusters. WIRED’s Kate Taylor wrote an entire piece on how claims adjusters experience AI at work, building off the Glassdoor data, and it’s well worth a read. Here’s a pertinent bit:

Typically, insurance adjusters complain about “AI-obsessed leaders forcing error-prone AI on them and their clients,” according to the research. When AI falls short in this job, adjusters say, they have to clean up a very human mess.

Take Ahmad Jackson. About a year ago, he was working in the claims department for a major insurance company. His employer decided to use AI for initial loss reporting, which involves setting up claims and gathering information when someone first discloses an incident. It was supposed to be a boon for employees and policyholders alike, streamlining simple claims while transferring more complex situations to actual people.

Instead, Jackson says, he and other adjusters faced a sudden influx of misclassified claims that required rerouting to the correct department. He encountered AI-driven hallucinations while reading claims summaries; when he inadvertently relayed those errors to claimants or their attorneys, he bore the brunt of their fury.

He quit the company not long after, switching to a different insurance carrier. AI is “getting things wrong,” Jackson tells WIRED. “And it’s implementing more work onto the adjusters.”

I’ve heard so many stories like this one, in so many different fields. Anecdotally, and in my interviews for AI Killed My Job, I’ve found it’s much more common for workers to have their lives made miserable by their companies’ AI policies than it is for them to lose their jobs outright. The Glassdoor data supports this generalization, as well as the notion that AI is becoming increasingly unpopular at work the longer and harder bosses push it. Again, what’s notable here is that negative attitudes are growing—pretty significantly—rather than declining, as workers better understand the AI products they’re made to use. This was supposed to be going the exact opposite direction; AI was supposed to make work easier, faster, more rewarding.

Recall again that a recurring theme this year has been firms pulling back on AI spend after finding it difficult to show a return on investment. Just as often as it’s successfully automating code production for engineers or giving your boss something to opine confidently about while golfing, it’s aggravating workers elsewhere, creating more work, stress, and burnout. This is likely a contributor to the continued decline of general sentiment towards AI in the US, too, as Pew Research and other pollsters have documented.

This spreading dissatisfaction with AI in the workplace dovetails with the broader contours of the anti-data center movement, the Flock protests, and the revolt against Meta’s AI glasses, all of which are examples of the public resisting the undemocratic imposition of commercial technologies into our shared spaces. At work, if you feel like you’re being forced to use a technical system that benefits your employer at your expense, that you’re powerless to refuse it or reap much of the benefit, and even that it might ultimately take away your job and earning power; well, all but the thickest-tongued bootlicker would resent it. And if Glassdoor’s data accurately reflect broader worker sentiment towards AI, that means there’s quite a bit of resentment just like that boiling out there.

These look like mutually reinforcing trends; aggravation over your boss pushing AI in the workplace is likely to color your impression of data centers that enable AI, of AI products elsewhere, and of the industry more generally. We’re fast approaching the point when AI executives say that their products will replace millions of workers. It hasn’t, but AI has left them feeling anxious, overworked, and unhappy. And it’s making them mad.

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Thanks for reading everyone. And here’s my quick obligatory note that I can only do all of this with the support of readers like you, so if you find value in independent, critical tech journalism and analysis, please consider becoming a paid subscriber. All subscribers get (at least) one written newsletter edition sent to their inboxes each week, typically, ideally, Tuesday or Wednesday, as well as one episode of Blood in the Machine: The Show, which goes live every Friday. I want to keep as much of this un-paywalled as absolutely possible, and paid supporters keep the bulk of this free for everyone else. So many thanks to all who chip in, it’s very much appreciated. Hammers up.

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This week on the podcast, to help make sense of this latest revolt against a Silicon Valley project, I spoke with Chris Gilliard, an author, thinker, and surveillance scholar who’s spent many years investigating big tech’s efforts to seduce us with sleek, aspirational products, track us, and harvest our data. Gilliard is the author of Luxury Surveillance, a forthcoming book about this very subject from MIT Press; you may better know him as Hypervisible, the handle he uses online and on Bluesky.

It was a great chat, and Gilliard’s work is absolutely vital. Hope you enjoy.

In case you missed it, I wrote about some of the topics we discuss above in this week’s column:

Other stories mentioned in the segment and the interview:

“Luxury Surveillance,” Real Life Mag, by Chris Gilliard and David Golumbia.

Heatmap’s latest data center sentiment poll.

“Data Centers’ 'Oh sh-t moment’, Politico.

“Flock CEO Begs for ‘Compromise’ as Backlash Spills Over,” Futurism.

‘Darth Vader’ Wants Flock in San Diego, 404 Media, by Sam Cole.

“Man Charged With 3 Felonies For Breaking 3D-Printed ‘Decoy’ Flock Camera, 404 Media,” by Jason Koebler.

“Grand Jury Declines to Indict Man Caught on Camera Destroying Flock Pole”, Futurism.

“Songs created by AI banned from Australia’s music charts,” BBC.

“Apple Music to Add Labels for AI-Generated Music Later This Year,” Billboard.

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A brief note to play us out about how BITM is working these days: Subscribers get (at least) one written newsletter edition sent to their inboxes each week, typically, ideally, Tuesday or Wednesday, as well as one episode of Blood in the Machine: The Show, which runs every Friday. But I can only do all of this with the support of readers like you, so if you find value in independent, critical tech journalism, and you’re able, please consider a paid subscription. I want to keep as much of this un-paywalled as absolutely possible, and I can only do that when folks chip in. Many thanks to all who do so, it’s very much appreciated. Cheers, onward, and hammers up.

You’re also perhaps familiar with the gist of what that they describe: Americans overwhelmingly hate data centers. They overwhelmingly dislike Flock surveillance cameras. And now it seems they overwhelmingly despise Meta’s newest product, AI-infused Ray Bans that have been widely termed “pervert glasses,” too. Enveloping all of the above trends is a general, percolating dislike of Silicon Valley’s marquee pursuit, generative AI; a sentiment underscored, again, by a slate of recent polls.

(I will note that, if you’ve been reading this newsletter, you’ve been well aware of each of these trends for many, many months at this point.)

Here are a couple more headlines, for good measure:

A grand jury refused to indict a man caught destroying Flock surveillance equipment on camera. Data center and Flock protestors are cheered as heroes, and finding viral fame. Grifty content farms have sprung up to churn out anti-tech memes because the genre is so popular.

It’s almost funny to think back to the mild wave of public consternation and Congressional wrist-slapping that pundits termed “the techlash” in the heady days of the first Trump administration, over concerns of disinformation on Facebook and social media, compared to what we’re seeing now. That is, a genuine, sustained demonstration of rage at some of the modern tech industry’s key aims.

And all of this has become so clear, so palpable, and so widespread that it’s apparently causing tech industry leadership and pro-AI policy wonks to enter either a state of denial or something more akin to fevered delusion.

I’m back on a weekly writing schedule after a spell of getting the podcast up and running. Subscribers will get (at least) one written newsletter edition sent to their inboxes each week, typically, ideally, Tuesday or Wednesday, as well as one episode of Blood in the Machine: The Show, which will go live every Friday. I can only do all of this with the support of readers like you, so if you find value in independent, critical tech journalism and analysis, please consider becoming a paid subscriber. I want to keep as much of this un-paywalled as absolutely possible, and there’s been a pretty intense period of churn lately. Many thanks to all who continue to chip in, it’s very much appreciated. Cheers and onward.

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Back in the spring, when a series of anti-AI and anti-data center actions caught national attention, many in the industry reacted with what was at least surface-level contrition. They were taken aback by the magnitude of the outrage, and some lamented that AI companies and executives had failed to issue positive messages for their products, so most Americans didn’t know how useful and good AI could be.

Ultimately, the industry decided not to change much of anything at all, whether the messaging—not that I think it would have mattered much—or the approach to their business in general, and, surprise, opposition to data centers has continued to spread.

Last week, in response to a fresh round of politicians announcing policies to slow or pause data center development, and the release of two new polls, including a Heatmap survey that found 75% of Americans would now oppose data centers being built where they live, AI industry players eschewed gestures towards contrition and essentially just melted down.

Many have been reduced to accusing the anti-data center movement of being a ‘psy-op’ funded by the Chinese Communist Party or the product of “psychosis”, or arguing that actually, we shouldn’t need to defer to ordinary people on matters regarding technological development anyway, or claiming that the movement was propped up by paid shills backed by the AI safety industrial complex, or even, in by far the funniest example, that opposing data center construction is inhumane because it amounted to genocidal population control on soon-to-be sentient AIs.

It’s a thing of beauty, really.

In short, it’s getting unhinged out there. And there are similarly calibrated if slightly less insane efforts to pick apart the Flock protests and the widespread disdain for AI, too. These pundits and industry leaders are affecting a kind of stricken bafflement over it all, which is pretty embarrassing for them. I guess we have to break out Upton Sinclair’s line about the difficulty of getting a man to understand something when his salary depends upon his not understanding it again.

What’s happening, after all, is pretty simple: Tech companies have encroached into Americans’ personal lives and public spaces, with both development projects and surveillance products, and people find the tradeoffs unacceptable. It’s really not complicated. Data centers, Flock cams, and AI glasses have been thrust into the public sphere by tech companies, with little to no preceding democratic input, and they are being rejected with extreme prejudice, because people do not like what these things do or what they represent. There is an additional layer of anger because people feel that they weren’t consulted; these vast infrastructural buildouts and high tech privacy violators pretty clearly tap into a shared sense of resentment and powerlessness.

One of the big stories of the last decade plus has of course been the story of rising inequality, and of working class Americans becoming economically and politically disempowered. What serves as a better totem to this sentiment better than a megaproject erected under the cover of a panoply of NDAs to build a mass job automator for a trillion-dollar tech company? Or an assemblage of spy cameras that scan your vehicular movements in public and share data with ICE so they can track down and deport migrant workers? The pitch appears to be “Your neighborhood will be transformed and surveilled, not for the benefit of you, but for a distant tech company and an increasingly authoritarian state” and people are, shockingly, not buying it.1

It doesn’t help that people dislike the broader project the data centers and surveillance devices are enabling, either. Recent public polling bears this out. It’s not reaching the same pitch as data center opposition, but sentiment is quite negative on AI, and still falling:

And only 9% of Americans are more excited about AI than concerned about it:

Meanwhile, young Americans overwhelmingly distrust the tech executives at the helm of the data center expansion and the AI booms alike:

Remember! The above CEOs have spent years publicly promising to replace millions of jobs with their software. At a moment when consumer confidence is in the toilet, and, thanks to inflation, a profoundly and tragically stupid war in Iran, and, yes, AI, attitudes towards where the economy is heading are grim as well. And did I mention that US workers’ share of national income fell to a new low this year, to just 53.7%?

So no, I don’t think any of the backlash is particularly mystifying. It’s exactly the opposite; people who are joining the mass opposition to big tech’s AI infrastructure and surveillance efforts are behaving in an utterly rational and justified manner. This, ultimately, is why I think so much of the tech industry and its supplicants are incapable of performing an honest accounting of this widescale backlash against tech, and against data center opposition in particular. The resistance may be messy and inchoate, but it amounts to a direct repudiation of Silicon Valley’s core project.

The industry is all in on AI, on rapid expansion, on the mass extraction of public data for private benefit. If it turns out the public is incensed by the core tenets of a project like that, well, too bad. There’s too much at stake, best plug our ears and blame the CCP or a psy-op or the media. For anyone promising its investors $30 trillion in revenues with a straight face, no (or even a pause) is not an option.

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Gil Duran, a veteran journalist and California political operative, is the author of the Nerd Reich: Silicon Valley Fascism and the War on Democracy, a book about how, exactly, this disaster has unfolded, and where it’s left us. That is, with a tech industry that’s overwhelmingly eager to abet, enable, and profit from authoritarian governments, by wielding power within them, and by building its tools of surveillance, automation, and extraction.

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Duran calls the key bloc driving this push ‘tech fascists’, and many have openly called for an end to democracy, or for rule by monarch—or CEO. And it is hard to overstate the import of the ascendency of the tech right.

These figures now have a direct line to the White House, have one of their own in the White House in former VC JD Vance, and are often in the White House themselves. They hold massive government contracts and their unprecedented hoards of lobbying cash influence shapes public policy, in addition to controlling much of the digital architecture that guides our daily lives.

The results of all this are everywhere you look. This is, yes, how you get DOGE running wild in the federal government, laying off hundreds of thousands of civil servants and pulling USAID funding for the most vulnerable, leaving people dead as a result. It’s how you get the widespread cronyism and corruption in Washington, with government figures embracing crypto and the AI industry and enriching themselves in the process. It’s also how you get tech CEOs rising into a class that more resembles an oligarchy than the mere ultra-wealthy.

One reason Facebook and Meta have operated with such impunity over the years is that Peter Thiel helped Mark Zuckerberg structure his company in such a way that he would retain ‘supervoting shares’ and would be unaccountable to a board of directors or anyone else. Just this week, Anthropic CEO Dario Amodei announced he would be doing the same; he will essentially be impervious to boardroom dissent or activist shareholders. This means, for instance, that as Claude users revolt over fears that the company’s new watermarking process—which was an important win for everyone who opposes the internet being coated in slop, and the mass deskilling of creative workers—will out them as AI spammers, it will ultimately be up to Amodei himself to decide what to do, and no one else.

Members of what Duran calls the Nerd Reich then use their power to further concentrate wealth, and of course, more power. A report by the AFL-CIO’s executive pay watch found this week that Elon Musk’s Tesla pay in 2025—he took home $158 billion—was an astonishing 2.5 million times his average workers’ salary. As the lead researcher on the report told Fortune, it’s ‘unlike anything we have seen before.’

Tech CEOs operating at such a distance from ordinary people may also explain why they’re so willing to undertake practices and push products that large swaths of the public absolutely hates. We already well know that data center opposition is the single political issue most Americans are united against, and that Gen Z is vehemently anti-AI. But consider also Meta’s marquee new product—”AI glasses” that allow users to film people without their consent, and that have already been dubbed “pervert glasses” by the masses. Just this week, Futurism published a report about how the glasses are being used by bullies in schools to harass their peers, especially girls. The bullies are apparently aping tactics seen on viral videos, in which pickup artists film women they’re hitting on without consent; hence the pervert glasses name.

This is perhaps, providing fuel for another future lawsuit—this week Meta goes to court against twenty-nine US state attorneys general who accuse the company of knowingly designing addictive products that harm the mental health of children. They’re seeking $200 billion in damages.

It might also explain why tech CEOs are willing to scan and destroy books en masse to feed them into their AI systems, despite the horror most people experience when they hear about such a practice. In, a story that’s almost too on the nose for a segment discussing the Nerd Reich, 404 Media had a rare bookseller put an AirTag in a rare book bought by a mystery buyer, and it wound up in an Amazon Facility expressly designed to scan and mulch books to train the company’s large language models. At the very same time, meanwhile, AI-generated books are flooding Amazon’s online marketplace, and crowding out real authors, who are earning less and less for their own, human-authored books.

As a result of all of the above, there is a powerful, enraged backlash growing against the nascent tech oligarchs, multibillionaire AI CEOS, and the Nerd Reich; whatever you’d like to call them. I’ve been covering the tech sector for nearly two decades now, and I’ve never seen anything like this. People are shouting down big tech reps and data center proponents at public meetings. Flock, the private provider of police surveillance equipment, has been under siege for months; a national week of action against their product, ALPRs, is underway right now, as I record this. A survey conducted by CNBC found that young people aged 18-34 found tech CEOs overwhelmingly untrustworthy. “Young People Hate AI CEOs So Passionately That It’s Almost Hard to Believe,” as Futurism put it.

Even Elon Musk’s own AI bot, Grok, has appeared to turn against him, accusing him of watching child porn and calling for his assassination on X.

The tech elite may have the wealth, the influence, and the ear of the president, but not even that can insulate them from a growing mass movement, increasingly intent on taking them on. And we have every reason to think that what we’re seeing now is only the beginning.

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So that’s episode number 7? 8? depending on how you count? of the podcast in the bag there. I tried something a little different this time, trading the headline roundup/AI resistance digest in the beginning for more of a short essay/composed intro. Not sure which I prefer, tbh, though I did enjoy the chat with Duran, who has laid out the key strands of modern Silicon Valley’s dominating ideology in blunt and easily comprehensible terms, regardless.

In fact, let me know what you think in general here. I’m happy with, and proud of, the work that I’ve put together here with my excellent producer . We’ve covered a lot of ground over the last couple of months, from checking in on the New Luddite movement and discussing their wildly successful Summer of Ludd in NYC,

tried to answer the question of ‘What is an Elon Musk’ with author and historian Quinn Slobodian

sat down with laid-off Xbox workers who are still organizing to fight back against their employer, Microsoft (this was, at least to me, such a powerful and impactful conversation)

discussed the state of the AI bubble with the world’s leading (and loudest) industry bear, Ed Zitron

dug into how AI and crypto companies are pouring hundreds of millions of dollars into the current election cycle to buy favor and influence with the great Molly White,

and talked about how to de-Google our lives with tech critic extraordinaire Paris Marx.

Anyway, every one of the guests have been great, in my humble and unbiased opinion, and I’ve enjoyed all these conversations. HOWEVER, getting the thing up and running has been a lot more legwork than anticipated. I feel like I’ve already written some variation of that sentence or another one just like it a time or two already, but it’s true. I never meant for the podcast to replace or crowd out the newsletter; it’s supposed to be the opposite. The show is supposed to augment the writing and reporting I do here, and amplify it in a new medium or two.

But I admit I’ve gotten sucked into the show a bit, planning out future episodes, booking great guests, writing and editing scripts and intro copy, wrangling YouTube algorithms, trying to better understand podcast distribution, and so on. The good news is that attention seems to be paying off. After starting from scratch, the YouTube channel got over 100k views in its last period, which my YouTube-native producer tells me is good. The podcast is outpacing expectations as well, and is finding an audience even outside these pages, which was always the idea. And it’s all growing, with some big algorithmic bursts here and there and steady growth underneath.

Yet I don’t want it to eat into my writing and reporting time so much; I don’t want to be a YouTube guy, ultimately. I want to be a guy whose writing people find on YouTube. I imagined a model of a) writing the newsletter, b) doing an abridged audio version of that plus updates on the general tech/AI resistance, criticism and backlash, plus c) having a conversation with a person or org in the thick of all of the above. And I do think after a couple months of ironing things out, we’ve hit on a format and workflow that will make that model more of a reality. So yes, I wrote a lot less over the last month or two (travel and dad stuff has played a minor role, too), but next week we’ll get the intended model rolling in earnest, with a piece planned for Tuesday publication, and we’ll see if we can’t have our cake and eat it too.

Do let me know what you think of this whole experiment. I would love to hear everyone’s thoughts, what you think is working and what isn’t, and what you’d like more or less of. The comments are open as always, or I can be reached at brian@bloodinthemachine.com.

Thanks as always for reading and listening. Hammers up.

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In recent weeks, a much-vaunted AI-focused hedge fund, Situational Awareness, run by Valley wunderkind Leopold Aschenbrenner lost $35 billion; nearly its entire fund. South Korea saw its largest-ever stock market collapse as investors pulled bets on AI chips and tech stocks. The circularity of the AI economy, with hyperscalers investing in AI labs and AI labs purchasing cloud compute from the hyperscalers and hyperscalers reporting big profits, is reaching new heights of precarity. Due to a fresh series of moratoria and political opposition, the future of the massive data center buildout has never looked more uncertain. The US markets have dipped then boomed, dipped then boomed.

Where does all of this leave us? Just about everybody—Sam Altman, the Financial Times, AI critics, your local barista—seems to agree that we’re still, somehow, improbably, in some kind of a bubble. But how big? How volatile? When will it burst? How? This week, I dive into all these questions with the infamous AI skeptic, analyst, and industry scapegoat Ed Zitron, author of the Where’s Your Ed At newsletter, host of Better Offline, and CEO of EZPR.

Zitron has been one of the loudest, most vitriolic, and most visible critics of the AI boom since the early days of ChatGPT. He also happens to be one of the most incisive. For my money, he’s done more to track the finances of the AI firms, and note the myriad ways they’re not adding up, than most business journalists and tech pundits combined. To this day, he’s raised questions about AI company revenues, circular financing, and cash burn that the industry still doesn’t have good answers for. As a result, he’s got nearly as many dedicated haters as he does diehard fans. Like a podcasting FDR with a special ire for generative AI, he welcomes their hatred.

Now, as fellow traveling skeptics of the broader AI project, Ed and I don’t agree on everything. But you’d be hard-press to find a sharper—or more entertaining—critic of the dubious economics of the AI boom. He’s been on a real tear lately, too, examining the worrying concentration of spending among hyperscalers and top AI labs, the financial vehicles underwriting the data center buildout, and the lack of demand for AI products outside of the chatbots built by the top labs.

Whether or not you appreciate his acerbic style or not (I do), we’d all do well to pay special attention to Zitron’s warnings. If he’s right, we’re on the brink of a rather spectacular collapse.

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As always, if you like what we’re up to with the podcast/YouTube show, please subscribe, follow, and review. It’s starting to get picked up by all the various algorithms and all that stuff helps. And if you really like it, please consider becoming a paid subscriber to make the whole BLOOD IN THE MACHINE project possible.

On the Texas data center pause

This is big news in the data center opposition world right now is that Texas’s deeply conservative governor, Greg Abbott, has issued a pause on data center projects until each can be fully audited.

Via a press release from the state:

Audit Must Be Completed Before Any Data Center Project Moves Forward

Governor Greg Abbott today directed the Public Utility Commission of Texas (PUCT) and the Electric Reliability Council of Texas (ERCOT) to conduct a comprehensive verification and audit of all data centers advancing through ERCOT’s interconnection process. The PUCT and ERCOT must complete this audit before any data center project moves forward. Any project that fails to comply with the requirements set forth by the PUCT and ERCOT will be denied connection to the Texas grid.

“Our top priority is to protect Texans’ safety and quality of life,” said Governor Abbott. “Any project that fails to comply with the requirements set forth by the PUCT and ERCOT, and by state law, must be denied connection to the Texas grid. Simply put, Texans must come first.”

ERCOT is currently considering approximately over 474 gigawatts of requests to connect to the Texas grid, more than five times Texas’ record peak electricity demand for ERCOT. Approximately 90 percent of the new power requests are data centers. That unprecedented load growth could endanger the reliability and stability of the Texas electric grid.

Texas joins New York as the second major state to officially block data center development, though its mechanism is much different than New York’s. New York is a flat moratorium for hyperscale projects of a certain size, Texas’s is a pause to assess whether certain criteria are met before they’re given the green light. But the binary is interesting here; New York and Texas are two cultural polar opposites; red/blue, rural/urban, cowboy/yankee etc etc etc—more evidence of the way that resisting big tech’s data centers is the nation’s great unifier.

There is, I would hasten to add, a potential gap between the efficacy of the approaches here: Texas’s audit is constructing in such a way that makes it possible to greenlight the bulk of the projects in relatively short order after Abbott’s having performed the grand act of Having Done Something. Trump has already criticized Abbott’s move, which will put some pressure on hastening the compliance with industry at scale here.

Still. It’s an unambiguous sign of the current power and bipartisan reach of the data center opposition movement, that even the most pro-corporate of Republican governors feel they must respond to its demands, and to the backlash against AI, in visible and tangible ways.

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People hate AI so much tech platforms have been forced to label and ban it

Speaking of the backlash to AI, Reece Rogers has a fun story in WIRED detailing all the ways that non-AI tech companies have recently found themselves forced to respond to people’s overwhelming distaste of encountering slop on their platforms.

From the piece, “The AI Slop Backlash Is Actually Having an Impact”:

Many Americans are having similar reactions to the growing prevalence of generative AI in daily life. “The AI revolution has happened, and everybody hates it,” says Meredith Broussard, a data journalism professor at New York University and author of Artificial Unintelligence: How Computers Misunderstand the World. In a recent Gallup poll, Americans’ increased familiarity with generative AI coincides with negative attitudes about the technology. This is especially true for young people between 18 and 29, where almost half see generative AI as doing more harm than good.

While this AI backlash has been brewing for the last few years, more companies appear to be directly addressing these concerns. LinkedIn added a “seems like AI slop” button for reporting AI-generated content on the platform, despite still hosting plenty of generative AI tools. Snapchat announced that fully AI-generated videos would no longer be eligible for its discovery feed. Substack recently added an AI detection tool to police writers.

The backlash’s “why” is simple at its core. Many Americans feel like they never consented to any of this. I had no idea that my online interactions would one day be scraped en masse for AI model training. I didn’t ask for Instagram to enable deepfakes on my account. I didn’t want Google to push AI-generated answers at the top of search results. I woke up one day, and generative AI features were stuffed into every corner of all the software I rely on without my consent.

Whether it’s AI models scraping your data or noisy data centers popping up in your backyard, the AI revolution seems to be an event happening to us without making us feel like active participants.

“Consent is really important,” Broussard tells WIRED. “We can connect that to the way that women, queer people, people of color, and minorities get exploited and abused online. Tech companies have never really been sensitive to issues of consent.”

Worth noting too that the story spent much of the week hovering in the MOST POPULAR column at WIRED, our most prestigious magazine about technology.

I would slot DuckDuckGo’s recent viral stunt into this category, too. It recently unveiled its “Normal F***ing Sunglasses,” which, it touts, were made with “No AI” and “no cameras.”

It’s a delightful little rejoinder to Meta’s AI glasses, which for their propensity for helping men record video of women without their consent have been dubbed “pervert glasses” by seemingly everyone outside the company.

From the ‘AI is ushering in a boom in carbon emissions’ dept

The New York Times reports:

Amazon is investing in a large-scale natural-gas-burning power plant as part of a huge data center in Texas, the company confirmed on Friday, a facility that could become the largest single source of climate pollution in the United States.

Amazon and other tech giants are racing to build enough data centers to keep up with surging demand for artificial intelligence services, and to secure the electricity to power them. A company spokeswoman said in a statement that its planned data center, in Pecos County, would be “powered by new on-site generation that won’t raise electricity costs for Texas families.”

The new gas-burning plant, if built to specifications, would be permitted to release 33 million tons of carbon dioxide a year, regulatory records show, more planet-warming gases than any other power plant in the country.

Is AI solving climate change yet?

Funny I should ask. The Amazon power plant story, which broke last week, underscores the findings of new research conducted by former Microsoft employees. As the Guardian put it, “AI’s potential climate benefits outweighed by role in boosting fossil fuels, study finds.”

From the story:

AI-driven productivity gains enable more planet-heating pollution from fossil fuels than they avoid from renewables, a study has found.

Researchers modelled the technical potential for AI to boost clean power generation along with projections for how it can help produce coal, oil and gas. Across 64 scenarios, they found net yearly carbon pollution rose by 0.47-1.8 gigatonnes, or about 1-5% of the energy sector’s annual emissions.

The study is the first to quantify the climate impact of AI across the full power sector. Previous research has explored its indirect climate benefits – such as reducing renewable downtime and optimising electricity grids – while ignoring the extra pollution from increasing productivity in drilling oil wells and extracting gas.

The notion that AI would soon be a net benefit for the climate has always been dubious, and this study shows exactly why. Those alleged and ultimately marginal benefits will be wiped away by increased demand for fossil fueled power—precisely of the sort that Amazon is trying to build out, at scale, as we speak.

Alright, that’s it for now. Thanks for listening and reading, and thanks again to everyone who chips in to make this work possible. You’re the best. Until next time—hammers up.

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I’m back in the states and about ready to get back to my regularly scheduled newslettering and podcasting. But first, I regret to inform you that I have some thoughts on the Odyssey. Yes, all the Odyssey discourse got to me, and during my vacation last week and I picked up a copy of the book (the old EV Rieu Penguin Classics translation, the only one the bookstore had left in stock). Then I downloaded the audio book so I could listen to it, as Homer intended, ish, and before long I realized I was essentially all-in.

The New York Times ran an op-ed called something like Why Can’t We Stop Talking About the Odyssey? (They keep changing the headlines in A/B testing but that’s what it was when I first saw it.) And my immediate reaction was welllllllllll. Here is one of the earliest canonical works of human literature, originally composed and retold orally as an epic poem, from person to persons, made into a $300 million Hollywood blockbuster by the industry’s biggest auteur (and tech critics), at a moment when proclamations boom out that AI threatens to consume and/or subsume culture, when our politics are a furious mess, in part because so many of us no longer share overlapping standards of truth or belief, and the fight to define either is a neverending livewire spat on platforms writing our own oral history in realtime. Of course there would be a fight over what the Odyssey can mean, and what it can’t, where it fails and where it succeeds.

I finally saw the thing this week, and I enjoyed it more than I thought I would. Granted, my expectations were low. I disliked Christopher Nolan’s Oppenheimer; it seemed to me to be too precisely the sum of its parts—the Batman director makes a dark superhero film about the atomic bomb—but Odysseus isn’t too too far off from a Batman, and this is more amenable to Nolan’s wheelhouse. (They both make up for their physical deficiencies with wealth, notoriety, and cunning, they are both riven with contradictions, and both have a penchant for grandiosity and violence etc etc etc.)

But of all the critiques and counter-critiques and counter-counter-critiques I’ve seen the one I’ve somewhat surprisingly seen the least amount of ink spilled over is the Odyssey (2026)’s rather central and yawning critique of technology.

TO THE EXENT THAT YOU CAN SPOIL AN ADAPTATION OF A 3,000 YEAR-OLD EPIC POEM, SUCH SPOILERS FOLLOW

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There’s been lots of commentary about how Matt Damon’s Odysseus, who is wearied, laconic, and downtrodden throughout the movie’s 3-hour runtime, is a comment on the fallout of America’s war-making in the Middle East, and the decay in the liberal order it begot, or the crumbling of liberal values more generally. (Damon’s grim portrayal of Odysseus is also a source of criticism, since the epic’s Odysseus is cunning, talkative, and full of braggadocio in addition to being prone to bouts of hysterical weeping.) But less about the specific instigator for all that misery.

Near the end of the film, Odysseus reveals what appears to be the source of these many character years/viewer hours of guilt-ridden sorrow: In devising and unleashing the Trojan Horse, an innovation that exploited Troy’s inclination towards trust and hospitality and the fact that they respected the same gods, in order to facilitate the demolishing of the entire city, he was "breaking Zeus’s law forever.”

“Zeus’s law” is a Nolanian contrivance that basically amounts to a Grecian golden rule; treat others, especially strangers and travelers, how you would like to be treated. It’s a take on xenia, an actual Mycenaean concept.

The historian Spencer McDaniels explains:

Xenía held that every person had a sacred and inviolable duty to provide safety, food, shelter, and comfort to any stranger or foreigner who sought hospitality. Guests, in turn, had an equally sacred obligation to honor and respect their hosts and to not take more than they needed.

It’s a social contract, then; a shared set of values that Odysseus comes to believe he has destroyed utterly by inventing and successfully deploying the Trojan Horse.

Nolan’s Odyssey astutely picks up on the importance of xenía in the epic and takes it in an interesting, contemporarily relevant direction. Translating xenía as “Zeus’s law,” the film portrays the breakdown of xenía as a cosmic consequence of the sack of Troy that will lead inevitably to the collapse of civilization itself.

Not unlike, perhaps, building and dropping a nuclear bomb?

Ezra Klein produced a long video essay arguing that the Odyssey is the most important political film of the decade, that it’s an exploration of the collapse of the liberal order and how, in these days of politicians spurning their neighbors and conducting mean-spirited attacks, so many no longer feel the need to be good to each other. In this reading, the Trojan Horse, an innovation already legendary in Odysseus’s world, is then the key catalyst.

Now, Nolan’s disdain for modern technology is well known. He doesn’t own a smartphone, or even use email. And in a recent interview, Nolan shared his thoughts on AI, too:

“I think AI is a Trojan horse that everybody knows the Greeks are inside… I’ve never seen a technology advancing so rapidly [that’s been] so completely rejected by the public,” he said. “Everybody’s suspicion of it is so extreme, particularly young people. The reaction to AI videos online and people my children’s age immediately calling it ‘AI slop’ and coining that term and just putting it in a box.”

I think it would be a stretch to argue that Nolan’s Odyssey contains any nuanced or meaningful critique of AI in particular. The tech criticism in the Odyssey, such as it is, is about as broad as it gets: When novel technology is used to destroy shared social values, it begets disaster for civilization. It’s the kind of sweeping criticism you might expect from a man who doesn’t have email, in other words, or who hopes his blockbuster will be seen by as many people as possible.

That’s certainly not to say such a sweeping critique is without value; Nolan certainly wants us to consider that the building of Trojan Horses is a deliberate act with obvious moral parameters. And that applies to Greek weapons of war, nuclear bombs, and AI products alike. (The director has noted in interviews that he couldn’t help but draw parallels between Oppenheimer and Odysseus in filming his latest.) The issue is that this makes for a pretty vague critique, and one that doesn’t really need to meaningfully engage with particulars, theory, or root causes beyond ‘sometimes men go too far.’

Interestingly, another top-grossing movie of 2026, Toy Story 5, registers a not-dissimilar brand of tech criticism; screens are bad for kids, we see, but only, it turns out, when they are too much, and when they take over kids’ imaginations and facilitate toxic behavior. Older tech toys for kids with less immersive screens are lovable and good, but somewhere a line was crossed from a healthy human coexistence with technology to a calamitous one, though that movie chickens out in identifying when or where that happened, exactly.

In this case, then, we must consider that the line was crossed thousands of years ago. Why not? The Odyssey was recited orally for centuries before it was written down, which itself was a famous act of technological transgression. Plato, writing centuries after Homer, told the myth of the Theuth, the god who had invented writing, and the Egyptian king Thamus, who played the role of the critic.

When it came to writing Theuth said, ‘Here, O king, is a branch of learning that will make the people of Egypt wiser and improve their memories; my discovery provides a recipe for memory and wisdom.’ But the king answered and said… ‘If men learn this, it will implant forgetfulness in their souls; they will cease to exercise memory because they rely on that which is written, calling things to remembrance no longer from within themselves, but by means of external marks. What you have discovered is a recipe not for memory, but for reminder. And it is no true wisdom that you offer your disciples, but only its semblance, for by telling them of many things without teaching them you will make them seem to know much, while for the most part they know nothing, and as men filled, not with wisdom but with the conceit of wisdom, they will be a burden to their fellows.’1

It’s worth noting that the original Homeric Odyssey itself is generally optimistic towards technology, albeit in a somewhat misanthropic mode. ( notes that Theodor Adorno and Max Horkheimer argued Odysseus and his crew ‘embody the principle of the capitalist economy’; a band of men set against the world and other men. Entrepreneurs, even. If Nolan’s Odysseus is more like a Viktor Frankenstein, plagued by what his inventions have unleashed on the world, then Homer’s is more the kind of entrepreneur we’re familiar with; headstrong, fast-talking, basking in the glory of his inventions one minute, complaining hysterically the next, with little time for reflections on the social impact of his devices.)

Throughout the epic, Odysseus’s efforts to get home are of course routinely thwarted by very human failures: his own hubris (screaming taunts at Polyphemus), his men’s meddling (opening Aeolus’s ox-skin bag of wind in sight of Ithaca), and the violent opposition of his foes. The way back, finally, then? A self-driving ship that can sail without the interference of failure-prone human hands. Odysseus’ last stop before finally making it home is at the palace of the Phaeacian king Alcinous, who promises him passage on such high-tech vessels:

For the Phaeacians have no pilots; their vessels have no rudders as those of other nations have, but the ships themselves understand what it is that we are thinking about and want; they know all the cities and countries in the whole world, and can traverse the sea just as well even when it is covered with mist and cloud, so that there is no danger of being wrecked or coming to any harm.

*Bonus points for anyone who knows the ancient Greek word for pilot or helmsman of a ship. It’s Kybernētēs, the word that the mathematician Norbert Wiener appropriated to describe cybernetics, how systems and machines could use feedback to regulate their behavior, to stay on course, and the reason that ‘cyber’ is in the lexicon today.

Embedded in one of the ur-texts of literature, then, we have an articulation of desire for automation, for a mechanized system that might replace flawed human judgment and labor, and transmit the wishes of the helmsman, ie the entrepreneur, into action. It could carry this man, he of given to “scheming” and “nimble wits,” who years earlier used his ingenuity to raze another human city to the ground, home. So the Odyssey, which I should add has genuinely been a blast to read, essentially describes the 3,000 year-old ambitions, or at least their seeds, that Nolan uses his adaptation to critique.

There is something to be said of the fact that our biggest entertainments have become so tech skeptical. Of course, for a wholly successful critique of technologies like AI you would have to name the forces inside the Trojan horse; the AI executives and Fortune 500 companies selling mass labor automation and promising to replace human art with cheap slop, the movie studios that have partnered with them, and so on. The technology is not spilling out into Troy on its own, unguided.

Reading the original, I daydreamed a bit about someone performing the epic the way it was originally intended; orally, on stages, in theaters or at festivals, over long hours. I thought about a performance of Gatz I saw years ago, an 8-hour play put on by the New York theater ensemble the Elevator Repair Service, about an office worker discovering a copy of the Great Gatsby in a drawer and then proceeding to read, in real time, every line of the book. About halfway through the play, the actor reading the text looks up and continues reciting the story from memory. The audience gasped. He finishes the entire book, and the play, that way. A performance like that—recited aloud, performed by human voices, from memory—today feels almost like it would in and of itself constitute an act of resistance against the AI onslaught and the types of broad, immoral forces Nolan conjures in his epics. I’d be first in line.

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Alright! That’s it for today; thanks for bearing with while a took a few days off, even if those days off wound up being less of a “relaxing during a short vacation” vibe than “the whole family got e. coli poisoning from swimming in a bacteria-infested bay” but hey, it takes all kinds. At least I had Odysseus to keep me company. See you all next week.

This formula has been emulated by the most recent crop of tech titans; your Sam Altmans and Dario Amodeis, whose path to power lies in selling a vision over simple goods, who work the state to buffet their businesses, and who paint a bleak picture of the future through which their products will help you survive. To understand what’s going on here, not just with Tesla or SpaceX or OpenAI or Anthropic, but the modern American economy itself, I sat down with the historian and author Quinn Slobodian, who has put a name to this tendency: Muskism.

Slobodian is the co-author, with Ben Tarnoff, of the book by the same name, which I fully and heartily recommend. We dig into all of the above, and a lot more; including the under-examined role that growing up in apartheid South Africa played in influencing Musk’s present-day ideology and tastes.

I very much enjoyed this discussion, and think you will too. Understanding Muskism, after all, could not be a more urgent project.

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As always, if you find value in this work, or want to see more shows like this one, please consider becoming a paid subscriber. It’s readers (and watchers and listeners) like you who make all this possible.

In case you missed last week’s show, you can check that out here, or here:

Finally, as I have mentioned, I’m in Paris this month, as my wife is teaching a documentary film class, and I’ve thus far been working through most of our stay. All that changes next week, however, when I will do as the Parisians do and log off and take a week’s proper rest and enjoy the city with the fam.

I may re-up an old story or just go dark for the week, but either way, I’ll be back before you know it. Until then, hammers up.

Tout le monde déteste l’IA. Everyone hates AI.

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I picked up a copy. My French is strictly limited to clumsy greetings and obnoxiously pronounced guidebook phrases, but a quick Google translation shows that the opening paragraphs indeed go pretty hard:

Une houle contestataire enfle aux Etats-Unis contre le culte de l’automatisation, les ravages du tout-numerique, la proliferation des centres de donnees, l’arrogance et le pouvoir des elites dela tech la corruption des elus quie se prosternent a leurs pieds.

Or, in English:

A wave of protest is swelling in the United States against the cult of automation, the ravages of everything digital, the proliferation of data centers, the arrogance and power of tech elites, and the corruption of elected officials who grovel at their feet.

Parisians have proven to be pretty hostile to AI themselves. When the AI wearable company Friend, whose CEO Avi Schiffmann is French-American, launched an ad campaign in the Paris Metro—much like it did in New York City’s subway—people tore down the posters or put stickers over them to subvert its message.

While the Friend posters are gone—Schiffmann had to suspend the launch of his product in Europe, given that the always-on, always-listening AI device likely runs afoul of multiple data privacy laws—there’s plenty of other anti-AI mischief on display in the city of light. Most notably, there’s another ad series all over the Metro comprised of what appear to AI-generated images. It has not been received kindly.

As you can see, at multiple stations, the ads have been tagged as AI SLOP.

Or more colorfully:

Not quite as savvy as Everyone Hates Elon’s recent subversions of Meta’s AI glasses ads in London, perhaps, but still:

French attitudes towards AI, according to a recent poll from the Centre pour la Securité de l’IA (CESIA), are in some ways, nearly as pessimistic as Americans’. Just 8% of respondents said they wanted to accelerate AI development, compared to 42% who said they wanted to slow it down “significantly” or pause it altogether.1

Like in the US, citizen concerns about AI over a great many subjects are shared across the political spectrum. Also as in the US, proposed data center projects are being met with growing opposition, and politicians are beginning to join the fray. Pushing for stronger AI regulation is the popular political position.

Unlike the US, France and the EU are currently capable of regulating the tech industry. This of course is why you hear American tech executives grouse about Europe so much. It’s a complex policy landscape with plenty of its own struggles—I’ve been contacted by Parisian union members who are enmeshed in battles with keeping AI out of their workplaces, for instance—but France is, nonetheless, capable of strong tech regulatory action on a level Americans are unaccustomed to. A timely example: Just last week, France’s national gambling authority banned Polymarket, the bet-on-everything app that’s a strong contender for the most predatory and openly noxious startup to rise to prominence in recent years.

In conversations, in the media, and even in the graffiti, the opposition feels more theoretical and philosophical; less vitriolic, less sweat-drenched. Perhaps because, as I and others have argued before, how much you déteste AI tends to depend on your economic and class position; what AI stands to take away from you, and where that might leave you. France, with its more generous social safety net, longstanding cultural dedication to craftsmanship and the arts, and more robust public spaces, generally feels more insulated from the threat vectors of Silicon Valley-shaped AI; ie, job automation, AI slop, and chatbot addiction. Generally.

Now, sure, this is a big, zoomed out generalization that admittedly risks the ‘columnist talks to his cab driver’ization of the issue at hand, but I was a columnist, and old habits die hard, so too bad: Walking around Paris, I do feel like I’ve seen fewer faces buried in phones in the way they are in US cities, certainly in my hometown of LA. I have seen not one but two people, on two separate occasions, walking down the street with their nose in a paperback. In a business district, no less. That’s beautiful. There are plenty of people staring at screens on the metro and waiting in lines and such, but they are eclipsed by the throngs at restaurants, the device-free bodies in parks and public places. The vibe is different.

Obviously, you can’t make too much of some loose anecdata based on hanging out somewhere for a few weeks, but it certainly feels that some of the ingredients to the antidote to Silicon Valley’s antisocial AI age are to be found around here. Robust communal spaces, culture that places unambiguous value on human arts, and policy that’s unafraid to pull punches in regulating—or banning—toxic and exploitative commercial tech. It’d be a start, anyway.

A dispatch from the days of Ludd

Embracing com space, logging off, centering community; why, these are exactly the things that the new Luddites, fresh off their Summer of Ludd, are pushing for.

has a beautiful piece about the wider movement, and her (all of our?) potential place in it, over at n+1. I could have excerpted pretty much any bit of this, so here’s one snippet at random:

Social media platforms, in my lifetime, helped ordinary people find one another, narrate their lives, organize against power, pressure institutions, and make visible much in our culture that had long been deliberately unseen. They had caused the culture to shift in infinite ways, many of them ridiculous and terrible, some of them tilted toward social justice and historical honesty. Marriage equality, the Arab Spring, Black Lives Matter, mutual aid networks, disabled communities, gay kids in hostile towns finding one another—it seemed only truthful to say that the age of social media and smartphones helped make these more possible. And some of those shifts in mass opinion were easy-come, easy-go: mercurial, shallowly held, easily co-opted; the reactionary backlash we are now living through seems evidence enough of that.

The platforms are rancid now. The incentives of capitalist forces and quantification have mined and fracked them into an arid, increasingly joyless desert. But for a time, they changed the conditions under which people could encounter one another and be encountered by the world. The Luddiverse, I could see, was trying to make this happen again.

Mathews, I might add, is author of the excellent novel about millennial life, precarity and late capitalism, All This Could Be Different, which I discovered through… n+1’s annual book quiz. Coming full circle here.

A new survey on generative AI’s impact on performing artists

The brilliant director and algorithmic theater-maker Annie Dorsen is conducting a survey on how generative AI is impacting the livelihoods of performing artists and workers in the industry. I pitched in (a little) with some advising on the survey, which I now encourage any and all readers to whom this applies to take. Share it with anyone who might be interested, please! The more good data we get about how generative AI is impacting labor, the better.

The survey is here. An FAQ is here. It’s organized by SMU DataArts and supported by the Mozilla, Doris Duke, and Ford Foundations. Here’s a rundown:

This pathbreaking study examines the real-world impacts of generative AI on performing artists working in theater, dance, and live music.

Who should take this survey?

This survey is for anyone who works in the performing arts, at any career stage or in any creative role: performers, directors and choreographers, designers, and technicians.

Why are we doing this survey now?

While there has been significant discussion about AI and the arts, there is very little information about how these technologies are actually affecting artists’ work, income, career opportunities, and creative practices. This research aims to fill that gap.

The findings will be used to inform policy discussions, funding priorities, advocacy efforts, and field-wide support strategies for artists navigating the rapidly changing landscape of generative AI.

OK OK. That’s it for today. On the podcast later this week, I chat with Quinn Slobodian, co-author of Muskism: A Guide for the Perplexed, about SpaceX, AI, the world’s richest man and what, exactly, he’s a function of. Stay tuned for that, it’s a great conversation.

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Finally, this work is made possible by readers who chip in a few bucks a month to help me keep the lights on; if you find value in this stuff, and you’re able, consider pitching in, too. Many ludditic thanks to all who already do. Until next time—au revoir, saboteurs.

The cuts are so imposingly large, the headlines so alarmingly frequent, and the tech companies so aggressive in their comms strategy that it’s easy to grow numb to the fact that there are real humans on the other end. To the fact that we now regularly see a small city’s worth of lives upended, careers cut short, and friends and colleagues thrown out of work. That an untold number of games, products, and works of art are suffering as a result. id Software, the studio behind some of the most legendary (and successful) game franchises of all time—Doom, Wolfenstein, and Quake—was acquired by Microsoft in 2021. Executives laid off half the studio’s employees this month. The remaining employees have no idea how they’re supposed to move on, what the plan for them is moving forward.

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I know this because this week I sat down with three Microsoft workers for a special edition of the Blood in the Machine show. Two of these workers have been impacted by the layoffs, one saw longtime friends lose their jobs. All three are fighting back.

All three have, at an exceptionally difficult moment, at personal and professional risk, stepped forward to share their stories, and to reveal what it’s like to work in the gaming industry, at a tech giant, in the age of AI and corporate consolidation. Both tech and gaming have been targeted by zealous managers embracing AI, and both have been made precarious by waves of destabilizing layoffs.

In our wide-ranging conversation, Morgan Goin, a level designer with ZeniMax Online Studios, who worked on games like Elder Scrolls, Autumn Mitchell, a senior quality assurance tester at Bethesda (the studio behind the Fallout games), and Chris Hays, a lead services programmer at id Software, candidly shed light on the crisis big tech is inflicting on games, how AI is impacting the industry, and how they’ve organizing to confront their trillion-dollar overlords through layoffs and hardship.

They’re all members of the Communication Workers of America, and the union has responded to the layoff news by organizing a series of protests, attended by hundreds, and filing an unfair labor practices complaint against Microsoft. I’m told we should keep our eyes peeled for a major event in August, too.

I’m still experimenting with the audio edition of BITM, but conversations like this one are exactly the ones I want to be having. I cannot thank Goin, Mitchell, and Hays enough for joining the show and sharing their stories and insights. For updates on their fight, you can follow the ZeniMax Workers Union on social media and find updates on the CWA’s website.

As always, if find value in this work, or if you support this newsletter, show, and the mission, consider becoming a paid subscriber so we can continue to host and produce more conversations like this one. If you already chip in, many thanks, you make this possible.

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Finally, now that I am officially a Podcast Guy, I have been informed I need to make this ask: please rate and review the show on Apple Podcasts, Spotify, or wherever you listen to your shows. You can subscribe to the channel on YouTube, and if you’re so inclined, upvote the episode and all that stuff too. And do let me know what your thoughts are about the whole audiovisual experiment here, in the comments or wherever; I’ve been pretty thrilled with the results and the feedback’s been great, but who knows.

OK! That’s it for this week. Thanks for reading/watching/listening. Until next time, hammers up.

VAR has been the center of at least three (four? five?) stories in sports news the last couple of weeks, and one major story everywhere else, too, with the Folarin Balogun red card that Trump notoriously pushed FIFA to overturn. You’ve got that now-epochal, corruption-tinged Balogun trainwreck, plus VAR handing a Swiss player a yellow card for taking a dive, England scoring after a goal kick hit the skycam and VAR staying silent, a disallowed Egypt goal against Argentina because VAR determined a foul had been committed approximately three hours before Mostafa Ziko put the ball in the net, and, my absolute favorite, a Croatia goal that would have leveled a game against Portugal in the unbelievably tense and exciting final moments getting wiped off the board because the sensors in the ball indicated to VAR that it had in fact subtly brushed overs a players’ head, which the ref did not see because no one possibly could, thus changing the offsides calculus in Portugal’s favor.

The more that I’ve watched these games that grind to a halt for a prolonged and often confusing technological intervention, the more that I’ve read the reams of angry tweets and columns and seen the sports-knowers complaining, the more I simply cannot help comparing VAR to that other ubiquitous, elite-beloved technological intervention, AI. I mean, it’s right there. And I do think it’s well worth asking what role this widely unpopular socio-technical construct (like AI, VAR is at once a technology, a system, a product, and a cultural fixture) is really playing. What does VAR actually do versus what its administrators say it does? Who does VAR ultimately serve? And last but not least, why does VAR persist if so many people despise it?

These are, of course, exactly the kind of questions we routinely ask about AI around here, and beginning to answer them might crack the door to better understanding how AI is interfacing with culture beyond the pitch.

A quick note that this work is made possible by subscribers who chip in a few bucks a month to support it. I try to paywall as little as possible and to keep posts like this one free to read. I can only do that because a small percentage of readers help me keep the lights on. If you find value in this stuff, and you’re able, consider joining their ranks. Thanks, and hammers up.

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For those gleefully unaware, VAR is the semi-automated system through which a match official uses video footage and data, now including information collected from sensors embedded in the soccer ball itself, to review and aid in the making of key officiating decisions during a match. Most fans absolutely hate it.

I’m no great scholar of football (or soccer, to all you plebes who have not read a handful of BBC articles about the sport and have thus not been inducted into the upper echelons of the European sport-understanding elite like me) but even I know that VAR made a big stink when it was introduced, and that said stink has never really evaporated.

After being piloted by the Netherlands’ national football league, VAR was more widely integrated into bigger leagues about a decade ago, and formally adopted by the International Football Association Board, football’s main rule-making body, in 2018. The statement IFAB issued at the time announced that “the philosophy of VARs is ‘minimum interference – maximum benefit’ which aims to reduce unfairness caused by ‘clear and obvious errors’ or ‘serious missed incidents’.” A major driving factor was, according to IFAB and FIFA officials, the growing discrepancy between what the ref could see on the ground and what audiences at home and in the stands could see with access to higher-resolution footage and replays they could check on their phones.

“With all the 4G and Wi-Fi in stadia today, the referee is the only person who can’t see exactly what is happening and he’s actually the only one who should,” Lukas Brud, IFAB secretary at the International Football Association, told WIRED about the genesis of VAR in 2018. “We knew we had to protect referees from making mistakes that everyone can see immediately.”

VAR was, in other words, a technological intervention developed to respond to another technological development. The sport’s administrators felt it necessary to promote and protect the integrity of their product (licensed broadcast rights, which bring in many billions of dollars for FIFA, the Premier League, and the like each year) with innovation. You can see the reasoning clearly enough: if viewers at home repeatedly saw that a foul called was clearly not, the game would risk losing face, and, eventually, audiences.

VAR had nonetheless been vehemently opposed by Sepp Blatter, the old school ex-president of FIFA, through the first half of the 2010s, but was embraced and approved by his successor, Gianni Infantino, after Blatter was ousted in the wake of a corruption scandal. It’s been a consistent point of contention and widely detested ever since.

The knocks against VAR are many. Critics argue that VAR impedes the flow of a game for which flow is paramount, causing holdups while officials analyze a play. They grouse that VAR is still too often wrong despite those holdups, and is used too inconsistently and with bias despite all the central claims to create an infallible techno-authority over on-field rulings. VAR promises to eliminate human error, to streamline decision-making processes, to harness cutting edge technology in service of fairness and justice. And yet, what it seems to do, in practice, is make people enjoy the thing it was nominally built to improve, less.

In a poll of 7,000 football fans published just a few months ago, in March 2026, 91% of respondents said the sport is better off without VAR and 81% said they preferred watching matches without the technology. 92% said VAR killed the “spontaneous joy” of celebrating a goal. Just 2% agreed with the statement that “VAR makes football more enjoyable.” Since its implementation in the UK’s Premier League, YouGov polls have consistently found that large majorities of viewers believe VAR “works poorly.”

In other words: It’s a ubiquitous automation and surveillance system, adopted and maintained by those in positions of power with promises of progress and improvement, despite inspiring widespread disdain among those it is promoted it as serving (football players and fans). Its public poll numbers are in the gutter. It even has its own instantly identifiable acronym. VAR is, there is little doubt, the generative AI of the football world.

Furthermore, according to the surprisingly robust academic literature on VAR, the system hasn’t even had much of an impact on gameplay itself at all. In an April 2026 paper published in the journal of Intelligent Sports and Health, economist Seife Dendir analyzed data in 15,000 matches played before and after VAR and found that “VAR appears to have had no effect on goals, red cards or penalty kicks” (emphasis his).

Dendir also notes that

The results indicate that among ten match statistics, the only robust change involved offsides, which decreased in the post-VAR period by 0.5–1.2 per match. For the other statistics, the estimated impact of the VAR is not statistically significant or robust across estimators and leagues. We conclude that the VAR, by and large, does not impact basic game play in professional soccer.

Dendir uses his findings to argue that people shouldn’t hate on VAR so much since it’s not really changing the nature of the sport as played on the pitch, but I think you can argue essentially the opposite, too: VAR may hold up matches, de-beautify the beautiful game, and incur an overwhelming majority of fans’ hatred, but at least it’s not doing anything particularly meaningful, either.

So what is VAR doing, then?

The first we already hit on—it is, in theory, helping to protect the credibility of the leagues in charge of officiating football matches, as well as their profit streams. It’s a product the leagues are selling. VAR can be seen as a big, performative demonstration that soccer leagues are using all the technology and power at their disposal to make the game as good and fair as possible. In a highly technologized age, VAR offers a technological solution that executives and bureaucrats can point to as their Having Done Something to keep up with the times. Even if fans dislike it. Yet again, it’s hard not to see parallels between the implementation of VAR and the widespread, top-down AI adoption, ordered by FOMO’d managers at Fortune 500 companies everywhere over the last three years—often to little meaningful or even detrimental effect to the organization, as recent stories are revealing.

But it’s more than that. VAR is also what Dan Davies might call an accountability sink. Even if VAR doesn’t, per the statistics, work overwhelmingly better than old fashioned human refs making the calls, it’s nonetheless a system the leagues can hold up as an effort to deflect any criticism that matches are unfairly or poorly officiated. It’s not FIFA’s fault if Swiss forward Breel Embolo was thrown out of the game for taking a dive to draw a foul, an offense perpetrated by literally every other player on the pitch that and every other day; it’s VAR’s.

In this way, VAR strives to impart the impression that those who implement it—FIFA, Major League Soccer, the Premier League, whoever—are neutral and free from bias.

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This is very obviously not the case. Like every other mode of officiating, VAR is itself an intensely bias-addled system; it’s supposed to be invoked only when certain conditions are met, and only in certain circumstances, but how and when to invoke VAR remains an inevitably biased decision. There is a lengthy document listing all of the VAR rules, called the VAR Protocol, that must be interpreted, at all times, by a team of invisible, off-screen humans. In the controversial Folarin Balogun decision, before Trump and the FIFA top brass bungled their way into the mess, the ref looked at slow-motion footage of the striker’s cleats hitting the Bosnia defenders’ leg; slowed down, artificially displayed, it looked awful, and likely contributed to the red card ruling, which was nearly universally decried as overly harsh shortly after.

Or look at the aforementioned Egypt vs Argentina game. In an extraordinary sequence, an Egyptian player wrested the ball from an Argentinian, Egypt played the ball down the pitch, weaved through Argentina’s defenders, resulting in a quality goal, as they say. VAR was invoked, and it was all wiped away.

Meanwhile, in the same game, a similar-looking play in which an Argentinian player made what looked like serious contact on Egypt’s Mo Salah and initiated a sequence that led to a goal in the opposite net, was left untouched. VAR was never even activated; the invisible technician decided it wasn’t worth a look.

And somehow, the sensors in the ball that sprang to life after brushing a Croatian player’s hair failed altogether to detect getting slammed into a skycam cable, allowing England to capture possession and score their first goal against then-leading Norway.

There are numerous actions in nearly every match that could warrant a VAR intervention. It’s up to the human to decide. VAR in other words has not removed bias, but rather moved it around the field, and maybe obscured it from direct view a little.

That VAR decision in Egypt-Argentina has led to probably the most unsustained fury in the World Cup so far (though the Swiss are plenty outraged too) with Egypt’s coach Hossam Hassan alleging that the game was stolen, that FIFA wanted to see Argentina, which hosts the biggest superstar player in the world in Lionel Messi on its team, advance over the North African one:

“We haven’t seen respect or fair play,” he said. “A penalty [for us] was ruled out, it was not even checked by the VAR and our second goal was remarkably, for whatever reason, disallowed… We have all seen the shirt pulled back [by Alexis Mac Allister] and not even a VAR check.”

This feeds into the longstanding criticism that FIFA preferences Europe and teams with star players, that it preferences audience and the profit motive. And it’s hard to discount Hassan. I’ve watched a number of these games, as well as Senegal-Belgium, which I haven’t even mentioned yet; it was a hell of a match with Senegal ahead 95% of the way. Belgium made an epic comeback, but Senegal stabilized, and it looked to be heading to a penalty shootout when VAR controversially awarded a penalty kick to the Belgian side in the waning minutes of overtime.

Look at which way the bulk of the above-described VAR decisions broke; towards Lionel Messi’s Argentina, towards Cristiano Ronaldo’s Portugal, towards European stalwarts Belgium over the poor African nation of Senegal. Towards England over Norway. Towards the teams with superstars and/or rich fanbases, towards Europe. This is why this otherwise enthralling World Cup has struggled to shake the conspiracy theories, the allegations of fixing, the stink of corruption (well okay, FIFA is pretty much always dealing with the stink of corruption). The Athletic described the teams left standing as “the final four of FIFA’s dreams,” and there are plenty of fan theories that posit that’s by design. One is literally referred to as “VAR-gentina.” FIFA has ably helped it all along, demonstrating that it is quite willing to put its thumb on the scales if there is a strong enough profit motive (suspending Ronaldo’s pre-Cup red card to let the superstar play), or if the US president tells it to (Trump calling Infantino to repeal Balogun’s red).

Do I think the refs themselves are fixing games or are in the tank for any particular team? I do not. But I do think that when it’s clear enough which outcomes a power structure prefers, edge case decisions and neutral technological prognostications bend towards them. It’s little wonder that VAR is maligned for being seen as party to, or even sometimes driving, such machinations. From its mere continued existence in spite of fans’ rejections to its apparent administration of FIFA’s will, VAR is a subtle instrument of power.

The irony of this is, again, that if it were left up to fans and players, if the surveys are to be believed, VAR would probably be abolished altogether, or at least seriously and deeply reformed. Even otherwise ardently pro-tech voices take issue with VAR; the Big Technology newsletter ran a story decrying VAR arguing that “Automation Makes The World Cup Worse.”

I agree. So often with VAR, as with AI, the technology’s deployment becomes so intrusive that it erases its stated raison d’etre, its very purpose elusive to the point of being lost. Speeding up and slowing down footage to try to extract intent through the pixels? Rewinding the game to reassess a decision because some guys in a video terminal spotted a foul in the playback? Using cutting edge follicular sensors to ascertain whether or not a ball grazed a human hair or not? What is all this for? Who besides FIFA is finding satisfaction in this process or its outcomes? What does this have to do with football, or why we play and watch it?

VAR has done little to streamline or take the bias out of officiating the game; it has inserted into it a new set of imperatives and biases that serve different functions and parties. It has slim upside, and, if you ask the fans, lots of downside.

Now, if you’re a sports fan and a VAR hater, here’s a quick ask: think about how generative AI is impacting other fields and practices we deem crucial. After all, AI, like VAR, is intruding, often unnecessarily, sometimes absurdly, sometimes disastrously, into key arenas of human practice, against the will of most and for the benefit of the few. Education, the arts, writing, journalism; all awash in AI—and why? So executives, administrators, and opportunists might squeeze a little profit, sate their FOMO, or exert some power. Large numbers of Americans dislike AI with a vehemence a Liverpool fan can well understand. What VAR is doing to football, AI is doing to so much else.

VAR, like AI, is made to feel inevitable, like it’s an ineluctable feature of a modern world. It’s not. It’s a technical system put in place by a scandal-plagued sports association. So maybe, as a thought experiment, it’s worth considering—what if we turned it off?

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There were mock trials of big tech, plays staged detailing the Luddites’ true origin story, marches, and teach-ins. By just about any count, it was a smashing success; the event drew favorable coverage everywhere from the Washington Post to WIRED to the Economist. It was even, amusingly, transmuted into a clickbait MSN listicle produced to maximize on-screen engagement.

I sadly couldn’t be there on the ground for the proceedings, so I did the next best thing: I invited the Luddite documentarian, organizer, and activist Amanda Hanna-McLeer, who was there for the festivities, and who directed the Luddite Recreations play that ran throughout the week in Tompkins Square Park, to give us the rundown.

Hanna-McLeer has been documenting the youth-led Luddite movement for years now; as she explains, it started with the Luddite Clubs students formed to reject social media and organize offline activities in high schools and colleges across the nation. In many ways, the Summer of Ludd is a culmination of that movement thus far.

It also, however, Hanna-McLeer notes, feels like the beginning of something else, something even bigger.

We get into all of that: the size of the crowds, the enthusiasm among so many people have for logging off and plugging in, and how the people who encounter the new Luddites are increasingly open to movements that challenge big tech.

One simple reflection of all this is the positive news coverage I mentioned above. I can comfortably say from my experience as a tech journalist, that even five to ten years ago, these kids and activists would have been mocked and scorned. Instead, most people immediately get where they’re coming from. Their message about fighting big tech, anyway, if not the gnome hats. Progress is progress.

Events like the Summer of Ludd—which not only protest big tech but proactively envision an alternative, participatory future; one grounded in community, commonality, and sociality—are dovetailing with data center protests, AI-critical labor movements, and students (and everyone else!) roundly booing AI. It does feel like the ground is shifting in some real and interesting ways, and that new spaces are opening up. Here’s to hoping.

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Some related reading:

Now for some other stories about our rapidly unfolding dystopia that caught my eye this week, and about those fighting to keep it at bay. BUT FIRST, before we move on: Today’s edition of BITM is sponsored by DeleteMe, whose mission is hunting down and, yes, deleting the data that brokers have hoovered up about you over the years and made available to their clients. DeleteMe is Wirecutter’s top-rated data removal service, and I’ve used it myself, to locate and eradicate scores of sites that were listing and selling personal info like my home address and phone number. If you’re interested in taking DeleteMe for a spin, sign up here and use the code LUDDITES for 20% off an annual subscription. OK! Onwards.

A treasury report drafted by Trump officials outlines fears of the AI bubble bursting

This is a bit of news that seemed to glance the surface without breaking through. I didn’t see this too widely reported, but thought it was pretty telling nonetheless. The report isn’t public, but was obtained by journalists; including those at NOTUS, who report that

This draft report inside the Treasury Department is set to warn of the risks posed by the artificial intelligence market, likening key aspects of it to the dotcom bubble that upended the U.S. economy when it burst in the early 2000s.

Career Treasury analysts found that AI firms are more deeply entrenched in the U.S. economy than their dotcom predecessors and pose significant risk to the entire system if financial conditions change, productivity goals are missed or various choke points stymie growth.

A downturn in the AI market would send shockwaves throughout the entire economic ecosystem, the analysts wrote.

What’s so notable isn’t really the message, which should be pretty familiar to critics of the AI bubble by now, but the way that it breaks from the narrative put forward by the Trump administration, which is, to the public, endlessly optimistic about AI’s transformational power.

Waymo called the police on teen riders who were playing with a toy gun and allegedly drinking

The Waymo stopped, detained the kids until the cops could arrive on the scene, which they did, and then approached the vehicle with guns drawn.

404 Media reports:

On Monday, the San Mateo Police Department posted on Facebook: “Parents do you know where your teens are? @waymo does!”

The police department continued in the post: “Two 15 year olds up to trouble in a Waymo this afternoon were detained after Waymo reported they were drinking and shooting from the vehicle. After calling us and stopping the car, we were able to safely remove both subjects and determined they were shooting Orbeez from the car as they sipped on afternoon libations while being chauffeured around town in the driverless vehicle.”

Pretty grim stuff! And your regular reminder that Waymos are continuously surveilling both the inside and the outside of their vehicles, collecting data that is recorded and made available to authorities, and now, apparently, proactively intervening when an automated system or someone at Google decides a criminal act has occurred—and putting teens at legitimate risk of being shot for being dumb teens. It seems only a matter of when, not if, we see an interaction like this that ends more tragically.

Big data center resistance news:

The largest-ever proposed data center, a 2,100 acre, 22 million square-foot facility slated for Prince William County in Virginia, has officially been cancelled.

The project failed after receiving sustained pushback from a local historical society—it would have been built on top of a famous Civil War battlefield and the graves of all the soldiers killed there—and a local homeowner’s association.

Meanwhile, all of Scotland is considering a “sweeping” data center moratorium.

The Guardian reports:

Last Sunday the Scottish National party (SNP)’s national council passed a motion to freeze all new datacentres in Scotland. That motion has been sent to the Scottish government to consider.

It could apply to all datacentre projects that have not yet received planning permission…

The move emerged as the Guardian on Monday revealed how the developer and the UK government misrepresented the technical feasibility of a massive datacentre hub in Scotland in the face of community fears that their land would be subsumed by the development, and promised jobs and investments would never materialise.

This site, in Lanarkshire, was to be an “AI growth zone”, a key element of the government’s strategy to build national AI infrastructure in rural areas of Britain.

The SNP’s resolution came amid signs of a wider upheaval in the UK’s AI strategy as Andy Burnham prepares to replace Keir Starmer in Downing Street. He is reportedly considering a review of several critical planks of Starmer’s technology policy.

The Guardian previously reported that an “AI growth zone” in North Tyneside was more of a publicity stunt than a viable project, despite being supposedly backed by the maker of ChatGPT, OpenAI. Several other big UK AI projects have been found to be “phantom investments” after the government failed to audit investment numbers or jobs claims.

And I was surprised I didn’t see this making more of the rounds:

Apparently, Meta’s data centers contaminated Cheyenne, Wyoming’s wastewater system with a “rare bacterial contaminant”

According to the Cowboy State Daily news:

Cheyenne’s Board of Public Utilities isn’t accepting industrial wastewater associated with data center systems until further notice after a contractor for Meta Platforms contaminated the city’s wastewater system, prompting months of cleanup.

The announcement was made by the Board of Public Utilities (BOPU) on Thursday in conjunction with naming the Meta company as the source of the initial contamination.

It also comes more than four months after the Meta company — which is building a huge $800 million data center in south Cheyenne — disrupted the city’s reclaimed wastewater system with a rare bacterial contaminant.

I’ll just leave that one there without further comment.

Microsoft is cutting nearly 5,000 jobs, many of them at Xbox

According to Reuters, Microsoft is cutting 4,800 jobs and overhauling its Xbox unit, and AI is once again at the forefront, in a bit of a different way.

The “Chief People Officer” Amy Coleman told employees in a memo that “the roles eliminated today are not being replaced by AI [...] At the same time, ​what  is  true is that AI is changing how work gets done.” The comment reflects the changing attitudes around AI; a year ago, the market probably would have rewarded Microsoft for saying AI was behind the cuts. Now it’s more of a liability. For its part, the Communication Workers of America, the union that represents many of the Xbox workers, has vowed to fight:

Claude Cummings Jr., President of CWA said “make no mistake – whether our members have a contract in hand, or are still at the bargaining table, CWA members at Xbox have the power and protection of union membership. When Microsoft decides to treat the workers who built Xbox as expendable, it should know who they’re dealing with. This is not just a fight with the thousands of workers across Xbox; it’s a fight with each and every member at CWA — hundreds of thousands of people strong.”

Popular AI agents built by Anthropic and OpenAI can be easily exploited and turned against their users.

My friends at AI Now have some startling new research on AI agents, and concluded that they should essentially, as it stands, never, ever be used in conjunction with critical digital infrastructure:

AI Now’s latest research demonstrates a critical attack vector on popular AI agents, built by Anthropic and OpenAI, when used for defensive purposes that actually turn the agent against its user. Attackers can use these models’ existing weaknesses to execute malicious code on a system deploying an AI agent when used for often-advertised defensive purposes. Specifically, users relying on these agents to assess the security of open or third-party sources are instead exposed to the very risks these agents are meant to identify and defend against. This exploit is achievable through prompt injections, a common exploit tactic where attackers can manipulate large language AI models by “injecting” harmful instructions through the data or input they ingest.

The full report, Friendly Fire, is by Heidy Khalaf and Boyan Milanov, and you can read it here.

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Alright, that’s about it for this week. Before I go, I will also recommend Ed Zitron’s piece on letting AI burn; as I mention in the pod this week, OpenAI and Sam Altman especially are already openly angling for a government bailout in the event of the AI bubble bursting. They want the Trump administration to take a 5% stake in the company, and are selling this as a way of spreading the “benefits” of AI. This is nonsense, and a self-serving hedge. Ed makes the case that the AI industry, which has garnered historic levels of investment for comparatively tiny revenue generation, must be allowed to fail in the event that its backing begins to unravel, which seems common sensical to me.

Also recommended: Gaby Del Valle’s rather horrifying piece on ICE agents growing propensity for making house calls to their online critics. Also: has a new newsletter, which will focus in part on tech, AI, and end times fascism. Check it out.

OK OK OK. I know I promised more writing, and I have an essay drafted about the World Cup, VAR, automation and AI that I am very much looking forward to sharing here, but I didn’t want to overload the inboxes today, so look out for that soon. In general, it’s honestly just been a LOT to be in the very hot city, corralling the kids, and trying to get this podcast/video thing off the ground, so the next 2-3 weeks may simply be a bit less writing and focusing on getting the show in good shape (and actually going outside in this vibrant and delightful city). Hope that’s cool.

Until next time, everyone—hammers up.

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