• Palantir’s pugilistic, race-bating manifesto has sparked controversy. But this latest bit of ‘cartoon villainy’ is actually a sign of its growing weakness

• A horrifying chart on AI-generated linguistic trends

• Tim Cook, Apple’s CEO of 15 years, is leaving. His real legacy probably isn’t what you think it is

But first, a little housekeeping. My friends at the AI Now Institute have a couple items I want to share: They’re running a series of trainings on data centers, and how to resist, organize, and enact good policy around them. There’s a digital toolkit, too. Also, the critical tech researcher and author Katie Wells, with Maya Pinto and Funda Ustek Spilda, has a report out on the gigification of healthcare called “Uber for Nursing.” Check it out, it’s great work. And if you missed it earlier this week, I reported on the first city in California to ban data centers. Finally, thanks to all who have applied to the podcast producer position; I’m grateful to have heard from so many of you amazing folks. More on that very soon. OK! Onwards.

Palantir’s X account published a 22-point distillation of The Technological Republic, CEO Alex Karp’s 2025 book, and because most people don’t bother to read long books written by defense tech executives, those points took many by surprise. They include but are not limited to Nazi flirtations like “The defanging of Germany was an overcorrection for which Europe is now paying a heavy price,” calls to reinstate and expand the draft like “National service should be a universal duty,” and dull overt racisms like “Some cultures have produced vital advances; others remain dysfunctional and regressive.”

The post was immediately met with much disgust and ridicule. “Palantir released a 22-point manifesto on X and people are horrified,” as Fast Company’s headline put it. The Dutch political scientist Cas Mudde called it “one of the scariest things I have seen in a while,” calling it “technofascism pure.” The fallout from the statement has already been pretty widely discussed; WIRED reports that the manifesto is the latest development—after Karp’s erratic, warmongering public persona, mass surveillance of Americans, and central role in supporting ICE—that is causing Palantir employees “to wonder if they’re the bad guys.” (To this question, I’m afraid, the answer is, unless you are actively leaking information to the press, attempting to organize the workplace to oppose abuses outline in the manifesto, or sabotaging outright its operations, yes, you are. But you can always quit.)

Yet, repulsive as the thread and its contents, as abhorrent as Karp’s rank technofascist aspirations are, as nakedly, and apparently successfully, self-serving, there’s much about all this I actually find encouraging. Karp’s “comic book villain” posturing shows us precisely the ways that Palantir executives—and perhaps even the broader tech oligarch cohort—are overplaying their hand.

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The vote came after an hours-long public comment period, in which dozens of Monterey Park residents spoke out against the prospect of new data center construction, and after months of community organizing galvanized opposition to the project. No Data Centers Monterey Park (NDCMP), a small band of concerned citizens, and the San Gabriel Valley Progressive Action, a local activist group, made headlines earlier this year when they successfully pushed the city to halt a proposed data center project.

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An Australian asset manager, HMC StratCap, had proposed a 250,000 square foot data center in an old shopping center. Bear in mind, Monterey Park is a quiet enclave that’s home to fewer than 60,000 residents, many of them Asian American, and some of the best Chinese food in LA. After organized pushback began in earnest last winter, in short order, the city canceled the project, the company withdrew the lease, and the government passed a temporary moratorium on data centers. It was such a successful campaign that a local news outlet ran a feature about it called, “How to Stop a Data Center in Your Backyard.”

But the organizers weren’t done. They pushed city council to take up an ordinance installing a permanent ban, and to put a measure to voters to enshrine it at the ballot box, ensuring the ban could only be overturned by another such democratic vote. The ordinance passed on April 20th, and the ballot measure is up for a vote on June 2nd.

The cavalcade of public comments at the hearing before the vote left little doubt that Monterey Park residents overwhelmingly disdained not only the prospect of a massive, noisy, and polluting infrastructure project being erected in their backyards, but who that project would benefit, at their expense.

“Data centers strain the electrical grid, increase costs, and make it a liability for residents and local businesses,” one resident said in her public comment to the council. “They go up there, emit harmful pollution, worsening air quality in a community already disproportionately impacted by pollution. And there’s no community benefit.”

“I can tell you that this issue has brought left, right and center together. It’s a quality of life issue,” another said. “Don’t let the rich steal our future.” Another: “We are against this oligarchic techno-fascist future.” Still another held his phone up to the mic while he played an audio file of a recording of a hyperscaler’s data center; it sounded like gnarled white noise. Comment after comment; story after story. I remarked on the sheer volume to someone seated nearby; they told me I should have seen the last hearing. It was so packed that a line went out the door, there were hundreds of comments not dozens, and the hearing lasted six hours.

This night, the only votes in support of the project came from members of a building union, who arrived in matching orange vests, and argued that the work would create jobs for their membership. (“We’re here for the work, we’re here for our families,” one said.) Some residents, meanwhile, pointed out that they weren’t against labor—and many highlighted their own union membership—but rather the thing they wanted to build. One pointed out that the builders didn’t live in the city; they asked for a show of hands of who lived locally, and none of theirs went up.

“It’s really been driven by speculation,” said Andrew Yip, an organizer with SVG Progressive Action. “Right now, you know, the faster your data center can process information, the more money can make. So that’s why we’re seeing larger data centers with more processing capabilities, meaning more energy use, more pollution, more water use. And so when we saw that come into Monterey Park, you know, just hearing all the horror stories from across the country. Yeah, we had to fight back.”

Monterey Park may be the first city in California to ban data centers (and not just pause them); if the voters give them the thumbs down in June, it will be the first time American citizens directly vote to ban them.

“I believe we’re the first, if I’m not wrong,” Monterey Park mayor Elizabeth Yang told me. “We’re super excited that the council tonight has unanimously passed its ordinance. And we’re so grateful that we have such actively engaged community members who have come out again and again, meeting after meeting to share their thoughts.”

“I’m very happy with it,” Yang added. “I think it was an accurate representation of what our city wanted.”

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I met Dekeyser, a lecturer in human geography at the University of Southampton in the UK, around the time his 2022 film “Machines in Flames” debuted, and have followed his work ever since. Now, with the book out, I asked if he’d be interested in writing a piece exploring its themes for BITM. He was kind enough to share this whirlwind look at how people and communities have rejected, shunned, or refused technology through history, and why their techno-negativity matters more than you think.

Before we get to that, a little housekeeping. First: I’m looking for a podcast producer to help make a weekly show about AI, labor, and the rising resistance to Silicon Valley. If that sounds interesting to you or someone you know, here’s a link to the job description. This is a paid, part-time gig, and I would love to work with someone familiar with the BITM project. Second: As always, this work—the writing, reporting, editing—is made possible by paid subscribers who chip in each month. If you find value in BITM, please consider becoming a paid supporter, too. OK! Enough of that, and onwards to the techno-negative.

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The history of the techno-negative

By Thomas Dekeyser

Technological progress is not just driven by innovations in technical abilities: explosive growths in compute power, processing speed, predictive algorithms, and so on. It is also, deeply, about discourse. AI-promoters and other Big Tech evangelists have long aimed to push their technological agendas by way of normalizing it through discourse, telling us that their tech futures are not simply desirable, but inevitable.

In this story, technological progress is a big, clean wave that carries everything forward, and cannot be halted. What we are presented with is a natural process that takes societies away from a presumably savage past and into a civilized present or future, one invention at a time. Because it is natural, attempts at pausing or slowing current forms of technological progress down are not simply naïve; they are futile. This story is omnipresent. We hear, again and again, from the mouths of Big Tech CEOs, AI grifters, national governments, and greedy employers around much of the world. “Whether you like it or not, it’s coming,” they tell us. “There’s no point in resisting.”

The problem: the inevitability narrative is a fantasy. It relies on a logical fallacy; just because something is emerging does not mean it will stay. More than that, it is historically incorrect. Technological advancement has never been a linear process. There is no clean wave; there are messy currents, vortexes, tides, rocks. When we pay close attention, what we find is that rather than a smooth, natural progression, the history of technology is in fact a political battlefield, with numerous actors fighting over the paths of technological innovation. Recognizing this allows us to free ourselves from the idea that the technological world we find ourselves in is somehow an immovable fact.

In my new book, Techno-Negative: A Long History of Refusing the Machine, I show how whenever technological advancements took place, they encountered deep pockets of refusal. In my book, I dig into the archives to reveal the oft-perplexing and stubborn existence of a fierce urge to negate life’s technologization, of what I call ‘techno-negativity’. From early machine breakers in ancient Greece and medieval Christian monasteries banning technologies to revolutionaries smashing street lanterns in 19th century France and ultra-leftist armed assaults on capitalist computation, the book explores techno-negativity as a deep—but persistently condemned—current in history. I would like to briefly spotlight five specific historical episodes in techno-negativity that may be of interest to readers of Blood in the Machine.

Ancient Greek machine-breakers

For as long as there has been what today we would consider innovation in the development and use of technological tools, there has been a desire to undermine it. In Ancient Greece, the very promise of ‘techne’, that is, of both the crafts and craft-knowledge, was intimately bound up, from its very beginnings, by its refusal and delay. As historians have shown, the expansion of scientific knowledge at the time failed to translate into a corresponding burst of technological invention. The era was overwhelmed by a deep suspicion in the face of techne.

To give just one example, the philosopher Archimedes, a crucial inventor of various technical devices and machines, was also the world’s first machine breaker, destroying his own machines in the hope of staving off future use. Even an influential Greek origin story of technology, in which Prometheus stole fire from the gods and gave them to humanity, came with a dark warning. Zeus clung Prometheus to a cliff high up in the mountains, where he was exposed to the elements and an eagle hungry for his organs. To the Greeks, techne had brought something dark and possibly sinister into the world, and thus, needed to be kept at bay.

The Luddite workers attacking looms

Fast-forward 18 centuries and we come across that most infamous of machine-breakers: the Luddites. They were framework knitters who, in early 19^th Century England, saw their livelihoods and craft under threat by the arrival of automated looms. As Brian Merchant’s book Blood in the Machine shows, rather than simply accepting their fate, they fought back, burning machines and factories.

While worker attacks on mechanic tools of labor took place since at least the 17^th century, what set the Luddites apart was their size, intensity, and level of organization. Techno-negativity became an insurrectionary tool that swept up a not insignificant portion of the wider population into an unprecedented assault on the increasingly tight link between technological innovation and the expansion of capitalism. With the emergence of the industrial revolution, technology had become a weapon wielded by the capitalist classes. Against this emergent capitalism, the Luddites developed a spirit of collectivism, fighting for themselves, for their fellow workers, and for a future beyond self-interest and profit.

Early anti-tech governments

In the centuries preceding the Luddite Revolts, it was commonly not workers, but governments who dismantled machines by literally attacking them, or by prohibiting them. In Hamburg in the late 17^th Century, to give just one example, it was common for the local government to do public burnings of newly invented machines. This was not a German craze, however. Between the sixteenth and eighteenth centuries, the King of England Edward VI banned gigmills, the Dutch Council of Leyden prohibited weaving machines, a Dutch decree forbade ribbon-looms, an English Imperial decree was announced against ribbon-looms, and the Council of Vienna signed a generalized prohibition of new machinery. Far removed from our contemporary governments’ large-scale embrace of the latest technological innovations, these techno-negative states provided worker protection in the face of looming displacement.

The 20th century communes that withdrew from technology

In the twentieth century, new forms of techno-negativity took hold. Prominent amongst these were anti-technology communes in the US (MOVE), UK (Kibbo Kift), Israel (Degania Alef) and South Africa (Tolstoy Farm). Unlike the Luddites, who directly attacked technology, these communes embraced an ethos of withdrawal and disconnection. Neither accepting nor rebelling against technological life, they fled.

As one of many anti-tech communes, a commune called MOVE asked: what might it mean to disconnect from Western, capitalist technology? Founded in 1970s Philadelphia, MOVE aimed to live in line with what its founder John Africa called ‘Natural Law’, banishing electricity, machinery, running water, processed food, and products of inorganic origins. We may not personally consider it desirable or viable to live this way, but anti-technology communes showcase the possible diversity of resistance tactics in the face of a technological world that, increasingly, feels hostile to our collective well-being.

The 1980s computer arsonists

Moving away again from a politics of disconnection, the 1980s proved to be perhaps the fieriest decade in the history of technological refusal. Militant groups around the European continent—including the Italian Red Brigades, German Red Army Faction, and Belgian Communist Combatant Cells—set fire to the companies and infrastructures fueling the arrival of computers. A French group with the fantastic name Committee for the Liquidation or Subversion of Computers (C.L.O.D.O. in French) is amongst the most prominent of that era.

Between 1980 and 1983, they set arson to or bombed at least 12 computer companies. Late at night, they would sneak into offices of firms like Philips Data Centre and Honeywell, gather computers and magnetic tapes, set fire to them in the toilets, and flee before the police arrived. Their target was less tech’s displacement of labor (Luddites) or its general impoverization of life (MOVE), and instead computation’s enrollment into the state apparatus as a war machine and a technology of surveillance. Computers, they argued before the arrival of the ‘personal computer’, would bring dominance as much as emancipation.

Across its many actors and practices, techno-negativity has varied as widely in its justifications and ideologies as in its practices and successes. Whatever we make of any individual approach to resisting tech, techno-negative actors prove the absurdity of any linear narrative of technological advancement. With every leap in technological advancement, we witness a fierce urge to undo it. Technologies are invented, attacked, delayed, dropped, delayed, re-emerge, vanish again. Some gain momentum, only to disappear within a matter of months. Others fail to latch on, and then, decades earlier, suddenly rise to the fore.

The messiness of technological advancement shows those of us keen on altering our current technological predicament that there are gaps everywhere that can be cracked open further. The current path of technologization is neither inevitable nor natural. Evangelists in corporations or governments may like to tell us it is as a way of undermining our sense of collective agency, but together with the infinite cast who make up the history of techno-negativity, we know better. At a time when Big Tech is becoming enamored with authoritarian politics, the stakes are higher than ever. What are the vulnerabilities or cracks in our AI-obsessed moment that can be exploited? We can turn to radical movements from the past not for blueprints, but for initial inspiration. The point is not to try and turn back the time, but to realize a technological refusal adequate to our increasingly dark present.

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The ideal partner here will be someone with

• Audio production experience (and preferably video, too)

• Knowledge of the tech world, the AI industry, and their impacts on labor, culture, and the environment

• Who’s comfortable on mic and camera

Gig will entail

• Producing a weekly/biweekly 45 minute-1 hr podcast about the rise of AI and its impacts on working people, education, culture, and power

• Research and assisting with outlining/writing intro scripts

• Booking guests

• Helping to intro topics and joining discussion on air

Ideally, this person will be fired up about the general BITM project—examining tech, AI, and Silicon Valley with a specific focus on their impacts on users and workers. The format will be part industry news + AI/big tech resistance digest, part interview show with weekly guests. The current plan is to record live, Thursday or Friday. Will be 1-2 days of work a week.

If this sounds interesting to you, drop me a line at briancmerchant@proton.me, and include, if you could, a brief intro, CV, and your rate. Thanks all—and hammers up.

Earlier the same week, and thousands of miles away, an unknown assailant fired 13 shots into the front door of city councilman Ron Gibson, who had just voted to approve a new data center in Indianapolis against a groundswell of public outcry. A sign that read “NO DATA CENTERS” was left tucked under the doormat.

Combined, the events signal an escalation in the blowback to generative AI and the broader AI project undertaken by Silicon Valley. Less than two weeks ago, I noted that it’s open season for refusing AI, and detailed a host of ways that politicians, workers, and advocacy groups were pushing back or banning outright AI in communities, industries and the workplace. Embodying the trend were Bernie Sanders and Alexandria Ocasio-Cortez, who introduced a bill proposing a nationwide moratorium on data centers.

In the short time since I wrote that post, such pointed AI refusal has continued apace. Maine looks set to become the first US state to ban data center development outright. Form letters for refusing AI at work are circulating widely. Public polling of AI sentiment is in the gutter; it’s never been popular, and it’s especially unpopular now. A widely discussed NBC poll found that just 26% of Americans had positive feelings about AI; around half had negative feelings. Gen Z in particular loathes AI: For respondents aged 18-34, AI’s net favorability rating was minus 44.

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That staunchly negative sentiment was reflected in the posts that proliferated on social media, Reddit, and comment sections across the internet after the attacks on Altman’s home. It was all more than a little reminiscent of the reaction to the killing of UnitedHealthCare CEO Brian Thompson last year, which saw an outpouring of online support for the executive’s accused killer, Luigi Mangione, that took many by surprise.

When news broke that the FBI had raided Moreno-Gama’s house in Texas, here’s how the development was received on Facebook, on the first post I clicked:

A similar story played out on Instagram:

Little is known about the motives of Tom or Hussein, or the politics of the Indianapolis shooter, but reporters and the online commentariat quickly dredged up Moreno-Gama’s Discord chats and Substack posts. He was a reader of rationalist and AI doomer Eliezer Yudkowsky, who argues, as the title of his last book puts it, if Silicon Valley builds a “superintelligent” AI, “everyone dies.” Per the San Francisco Chronicle:

Online records show Moreno-Gama published multiple essays and forum posts warning that AI could lead to human extinction, calling AI models deceitful and misaligned with human interests. He accused tech leaders, including Altman, of lacking morals and being willing to gamble with humanity’s future, and adopted the alias “Butlerian Jihadist,” referencing a fictional anti-AI crusade from the 'Dune' series. His writings grew more urgent over time, with some posts edging toward calls for extreme action despite community moderators warning against violence.

According to the SFPD, after attacking Altman’s house, Moreno-Gama went to OpenAI’s offices, where he was arrested while banging the front doors with a chair, threatening to burn the office down and kill everyone inside. He had a jug of kerosene and a list of other AI leaders names and addresses, police said.

Many in the AI industry were blindsided. Some denounced the AI doomer movement for megaphoning the human extinction narrative, others lamented the industry’s bad messaging, and still others, like the VC Chamath Palihapitiya, urged AI companies’ executive leadership to “step up,” and, as he put it, “create incentives to align everyone.” Altman, for his part, wrote a long message on his personal blog with a photo of his husband and son. He posted the note after the molotov cocktail and before the gunfire. In it, he seemed to blame the violence first on the media, and on a climate of anxiety around AI. He singled out Ronan Farrow’s recent New Yorker piece in particular, which portrayed Altman as duplicitous and untrustworthy:

There was an incendiary article about me a few days ago. Someone said to me yesterday they thought it was coming at a time of great anxiety about AI and that it made things more dangerous for me. I brushed it aside.

Now I am awake in the middle of the night and pissed, and thinking that I have underestimated the power of words and narratives.

This is quite a thing to say for a man who has ushered in one of the largest speculative booms in history with one of the most correspondingly extreme business narratives. Altman’s story, after all, is that his company is building a product that can do nearly anything, replace every worker, and may well destroy the world with its power. Altman was no doubt shaken up by the attack, but the blog post is nonetheless remarkably free of serious self-reflection. If anything, it evinces a lack of understanding of the causes of the violence aimed at him was part of, and ultimately, even bolsters Farrow’s thesis: that Altman will say and do anything to advance his interests, including in times of crisis. It also reflects much of the AI industry leadership’s glaring disconnect over the anti-AI rage, its causes, and how it might meaningfully be abated.

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After all, many AI executives have publicly declared for years that the technology they’re building and selling is so powerful that it might literally end humanity. And if it doesn’t, then it will automate most everyone’s jobs. (And either way, it will fill the internet with AI-generated content and our neighborhoods with data centers, right now). Many understand much of this to be a perverse marketing strategy—and some in the tech industry, like James Rosen-Birch, have long pointed to the dangers of continuing to pursue such “doom marketing”—but many do not.

In this way, for the last three years, the AI industry has asked the public to treat it as if it were Trump—seriously, but not literally. This is impossible. Startups like OpenAI and Anthropic are among the largest in history precisely because investors, and markets, took them both seriously and literally. Those investors expect to see the superintelligence and especially the mass automation they were promised.

It’s not the doomers’ fault if they too take AI industry executives at their word. For years they saw clips of Altman and Dario Amodei and the rest that AGI was coming fast, that it would present grave dangers to humanity if it were not “aligned” properly, that we would have to rewrite the social contract on their behalf, and so on. Then they saw demonstrably unethical behavior from those same AI labs and founders; they saw board coups over credible claims the CEOs couldn’t be trusted. They saw teen suicides and murders at chatbots’ urgings. They saw OpenAI eagerly ink a multimillion dollar contract with a military that soon set to bombing Iran. They saw the physical evidence of the AI industry’s expansion all around them; data centers erected anywhere, seemingly, there was power and water supply. To this end, it’s worth noting that Moreno-Gama reportedly lives in the Woodlands township, an area north of Houston that is now home to no fewer than 12 data centers, according to Datacenters.com. He may well have listened to Altman’s stories about how OpenAI was creating the equivalent a digital god, and then watched as the architecture that would summon it was erected in his backyard.

If you take at face value what the AI executives themselves have been saying for the last decade, that an AI powerful enough to make humans go extinct is nascent, then acting with force to stop it would be a rational action. The AI industry and its executives—including Sam Altman—need to own this outcome, not blame it on Yudkowsky, safety researchers, or worried activists who take what they say literally.

Yet this is not merely a matter of bad messaging on the tech industry’s part, either. That second key plank of the AI narrative, again, broadcast directly by the CEOs themselves—that it will take everyone’s jobs—is not simply dismissible. It’s the selling point. Investors don’t ultimately much care whether OpenAI renders software sentient; they want to see mass job automation and the attendant historic labor savings. That prospect—of deskilling, controlling, or eliminating labor outright—is what made AI so uniquely valuable in the first place. There’s no putting that promise back in the bottle, no finding better combinations of words to describe how AI is a tool for bosses to automate labor. That’s the project. And people understand that.

That’s why, while Moreno-Gama, who as an AI doomer, has less-than-representative views on AI than most, was still widely cheered online for his actions among countless non-doomers: he was hailed as a folk hero for acting on behalf of class interests. Let’s go back to that NBC poll:

The demographic groups with the most negative views of AI are voters ages 18-34, among whom the net favorability rating for AI is minus 44, and women ages 18-49, who reported a net AI favorability rating of minus 41. The two groups with the most positive views of AI are men over 50, with a plus 2 favorability rating, and upper-class voters, who also have a plus 2 favorability rating.

Interesting how hatred of AI maps so neatly onto whether or not it stands to directly diminish your personal and/or employment prospects! Gen Z is facing what is by some counts the worst entry level job market in 37 years; no wonder they utterly detest the tech product that everyone says is to blame. Meanwhile, men over 50, who tend to be richer, and upper-class voters, who, well, are richer, are less anxious about AI because they’re much more insulated from economic precarity.

In other words, the story of a man trying to save humanity from a future superintelligence was likely less resonant to the sympathetic masses than the story of a Gen Z man who threw a molotov cocktail at a CEO’s $27 million mansion (that is surrounded by the three $13 million houses he also purchased). Both narratives have one thing in common: They identify billionaire AI executives as uniquely powerful actors, who are all but unaccountable to democratic constraints and society’s best interests. We are witnessing the rise of a new aristocracy, as Jennifer Harris was perhaps the most recent to point out. The tech titans and AI executives are its avatars, calling the shots above everyone else about how we live and work, and which industrial projects will inhabit our backyards. This is the common fuel animating the rather disparate furies of militant doomers, anti-AI activists, data center protestors, and labor organizers alike: The profound antidemocratic tendency inherent in the modern AI project.

This is why it’s particularly rich that, in his blog, Altman says things like “AI has to be democratized; power cannot be too concentrated,” and “It is important that the democratic process remains more powerful than companies.” The first is fundamentally incompatible with nearly everything OpenAI is currently doing, and the second is one of Altman’s outright lies. As stated above, OpenAI aspires to nothing if not becoming one of the greatest concentrators of power of all time. After having deskilled artists and writers by ingesting their work into its models so its products can emulate them, OpenAI seeks to replace workers at firms and institutions around the world with a subscription cost to a technology it owns. Any subsequent profits will flow of course to Altman and the c-suite, yes, concentrating wealth and power.

As for democracy, well, OpenAI has done all it can to crush it. OpenAI joined a lobbying blitz aimed at helping the Trump administration push a 10-year moratorium on state lawmaking through Congress; it failed, but got an executive order aiming to do the same. OpenAI has spent millions lobbying against laws it doesn’t like in California and the European Union, trying to avoid regulation, laws, and other inconvenient outcomes of democracy. It is currently funding, along with VC firm Andreessen Horowitz, the Leading the Future PAC, which will spend $100 million to advance AI industry interests in the midterm elections, according to the Wall Street Journal.

This is also why OpenAI’s recent public policy document, which was released to acclaim from some of the most dimly credulous people on the planet, amounts to little more than a bad joke. It should be read as an attempt to head off public concern by suggesting AI might deliver a 32-hour working week and some other nebulous social benefits. Why would we believe for a second that an AI company that spends millions to degrade state capacity to do democracy at all, and works to quash a California bill that would require AI chatbots be proven safe for children, and tries to limit totally any liability for harms its products might cause in other state bills, and partners with the Trump administration as it bombs elementary schools and unleashes domestic terror on immigrants, would ever seriously expend an ounce of actual political capital for anything other than its own bottom line? We would be pretty stupid to. As Eryk Salvaggio pointed out in Tech Policy Press, the policy paper literally “proposes concepts OpenAI helped kill in California.”

Inequality is through the roof. A bona fide tech oligarchy is ascendent, buffeted by leverage provided by AI. Its data centers, which bring few jobs and hike electricity bills, are enraging communities on the right and the left. Slop is everywhere. AI-generated art and text is undercutting creatives, powered by pirated, non-consensually ingested work. Employers from Amazon to Block to Duolingo to Meta are firing tens of thousands of workers and citing AI as the reason. AI may one day cure cancer, we’re told; great, even if we believe that, who will be able to afford the treatment?

That’s the anger fueling the anti-AI violence. To the handwringing AI industry insiders blaming doomers and poor messaging, ordinary people are saying: Wake up. We have good reason to hate AI and the people who profit from it. And yes, as people get desperate, as young people increasingly feel like AI elites have mortgaged their future, as residents who vote to regulate AI or ban local data center projects only to see their will overridden in favor of industry interests—well how do you expect them to feel? What do you expect? There is a distinct risk of further escalation.

I do hope that this is a wakeup call to Altman and his peers. No one should experience violence as he did. Not a depressed teenager like Adam Raines who turns to ChatGPT and receives encouragement to kill himself. Not the students at a Canadian high school who were gunned down by a shooter who planned their action on ChatGPT, and who multiple OpenAI employees had raised the alarm about, only to be ignored by management. Not the mother who was shot and killed after ChatGPT helped validate her son’s violent conspiracy theories.

If they want anti-AI rage to “de-escalate,” as Altman calls for, OpenAI and the other AI company leadership would have to make good on words that are currently hollow, and allow for individuals, communities, and victims to participate in a legitimate democratic process over the future of AI. They would stop pouring tens of millions of dollars into lobbying efforts and meddling in elections. They would respect community wishes on data centers. They would stop supporting efforts to ban AI lawmaking and to exempt themselves from product liability. If they were earnest about not wanting to concentrate wealth and power, well, they would find real ways to distribute it. Sam Altman might spend a little more time advocating for higher marginal tax rates and a little less driving around in one of his two McLaren F1s.

Of course, they’re not going to do any of those things. They’re going to continue building and hyping the ultimate automation software, perhaps choosing their words and marketing materials a bit more carefully, but perhaps not.

Near the end of his blog post, Altman writes,

My personal takeaway from the last several years, and take on why there has been so much Shakespearean drama between the companies in our field, comes down to this: “Once you see AGI you can’t unsee it.” It has a real “ring of power” dynamic to it, and makes people do crazy things. I don’t mean that AGI is the ring itself, but instead the totalizing philosophy of “being the one to control AGI”.

It seems to have slipped Altman’s mind that in the very metaphor he’s making—he’s comparing AI CEOs rushing to win the AI race to the men striving to wield the rings of power in the Lord of the Rings—the only way to ensure evil doesn’t triumph is to chuck the One Ring itself into Mount Doom.

That threat did not materialize, and now some apologists are saying that it was just one of Trump’s deranged bargaining tactics, as if that excuses such categorical declarations of mass violence from a US president. Most people, it turns out, are not OK with that; the commentariat was almost universally appalled, a lengthy list of Democrats have called for Trump’s removal from office on grounds of the 25th Amendment, and even some of his staunchest allies on the right—Tucker Carlson, Megyn Kelly, Alex Jones—were not just breaking ranks but angrily calling him out.

Yet there was one group that was (and remains) uniformly silent as Trump threatened to use the military, and presumably its store of nuclear weapons, to enact genocide: the leadership of the tech industry, which in recent months has inked numerous lucrative deals with that very same military. Currently, OpenAI, Microsoft, Google, Amazon, xAI, Oracle and even Meta have large contracts with the US military.

None of the leadership from any of those companies has expressed any discomfort with Trump’s genocidal threatmaking, let alone the entire war of aggression against Iran. It’s worth sitting with this for a moment, I think; the fact that Alex Jones has expressed more moral concern over a US president’s calls to kill an entire civilization than any major tech executive. (Any tech executive that I have seen, anyway, and I’ve spent the last couple of days looking.) It is occasion to examine the extent to which Silicon Valley has become an enabling partner in Trump’s military adventuring.

Now, the foundational story has been more or less the same since Silicon Valley began its embrace of Trump in earnest last year: The tech giants and largest AI firms made public shows of fealty, embedded themselves in the administration’s broader project and explicitly aligned their interests with Trump’s, in exchange for access to the state’s largesse, deregulatory agenda, and multifaceted support.

But this week should serve as a clarifying moment. The sitting American president explicitly promised a genocide then forced the Iranian people to wait for hours to see if they would be bombed “into the stone age” and the rest of the world to see if he would start World War III in earnest this time. Even a few years ago, Silicon Valley executives might have spoken out against such horrific declarations; intents to, in part, harness their AI, tools and technological infrastructure to such abject ends. Now they are silent; content, apparently, as long as Trump continues to give them favorable land use policy for their data centers and state AI law moratoria. If an industry that rose to cultural dominance by promising to be harbingers of progress—to improve people’s lives, to do no evil, to bring people together, to make a dent in the universe, and by using all of the above as a powerful recruitment tool—cannot draw the line here, then what’s left?

So, today, I want to drill into the myriad ways some of the top AI and tech firms—OpenAI, Google, Microsoft, Amazon, and Anthropic—are profiting directly from the US Department of War and their close ties to Trump. Even if all of the tech firms listed above are not explicitly building the technical infrastructure that enables mass killing—though some are—they have become pivotal to Trump’s geopolitical project nonetheless. They have provided his administration financial support, credibility, and lent his project a veneer of forward-looking futurity, even as that project delivers regression, oppression, and violence on the ground. They have provided cloud and AI services to the military and affiliated government agencies. They are war profiteers.

The executives of these companies—the Sam Altmans, Elon Musks, and Sundar Picchais who travel to Mar-a-Lago, pose for photo opportunities with the president, and help funnel cash donations his way—may be lost causes, intent as they are on milking the president’s pro-AI posture for all that it’s worth, civilizational ending military decrees or not. But workers, who make these companies possible, are another story.

There was a time not long ago when the mere prospect of Google entering into a contract with the Department of Defense prompted mass walkouts and resistance—the largest worker action the tech industry has ever seen, by some counts. Mass firings, retribution for organizing, and an incursion of rightwing politics into tech have helped stymie or slow subsequent efforts, but some continue undeterred. And there are signs that discontent is brewing again. There are reasons to believe, as always, that if workers discover their power, they might transform even the richest, most hyped, and most powerful companies in the world.

So! Below, find a crash course in the top AI and tech firms’ military ties. After the fold, we’ll dive into the New Yorker’s long report on Sam Altman and OpenAI, Anthropic’s much-publicized release of Mythos, the AI model that’s “too dangerous to release,” and more. As always, I rely on paying subscribers to make this work possible; if you find value in it, and you can, please consider upgrading to a paid subscription. To those who already do, many, many thanks. OK! Onwards.

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OpenAI

OpenAI most recently and perhaps most famously rushed to cut a deal with the the Department of War after Anthropic refused to submit to demands that it allow its technology be used to surveil Americans and in autonomous weapons. The deal is estimated to be worth “between $500 million and $2 billion over five years, based on comparable classified AI deployment agreements,” according to Tech Insider, though the specific dollar amount has not been made public.

(It’s also worth adding that thanks to reporting from Ronan Farrow in the New Yorker, we know that the reason Anthropic had this contract in the first place and OpenAI did not was because Sam Altman had been deemed untrustworthy by the previous administration and to be potentially pursuing compromising interests with his development deals for data center projects in the Middle East.)

Last year, OpenAI inked a $200 million deal with the Department of War as part of its OpenAI for Government initiative, to help it “identify and prototype how frontier AI can transform its administrative operations, from improving how service members and their families get health care, to streamlining how they look at program and acquisition data, to supporting proactive cyber defense.”

OpenAI has also offered enterprise ChatGPT services to government agencies at a loss for $1 a year. Its president, Greg Brockman, donated $25 million to the MAGA Super PAC. OpenAI partnered with the United Arab Emirates and the Trump administration (and Softbank and Oracle and others) to announce Stargate, a data center conglomerate with installations in places like Texas and Abu Dhabi (which, incidentally, Iran recently threatened to attack) that claims it will ultimately invest $500 billion.

Of the AI firms that are not explicitly oriented around defense tech, like Palantir and Anduril, or run by an executive who is openly committed to rightwing politics, like Elon Musk’s X, OpenAI is the most ardent supporter of Trump’s project in general, and now, after Anthropic’s ouster, the most likely to be involved in providing information for combat operations.

While there have been flickers of discomfort among workers and prominent employees around this alliance, such as OpenAI’s chief futurist speaking out against Trump’s threat, it's mostly been quiet.

If you’re an employee at OpenAI, and you agree with Achiam, one place to start proving that democracy can overcome those threats and reject such practices is in your own workplace. (I reached out to Achiam through his post, for what it’s worth, asking about the prospect of workplace organizing; I’ll update if I hear back.)

Google

Last year, Google was awarded a $200 million contract to, in its words, “accelerate AI and cloud capabilities across Department of Defense’s Chief Digital and Artificial Intelligence Office.”

Along with Oracle, Microsoft, and Amazon, Google won a contract with a $9 billion ceiling to provide Joint Warfighting Cloud Capability:

Through the contract, which has a $9 billion ceiling, the Pentagon aims to bring enterprisewide cloud computing capabilities to the Defense Department across all domains and classification levels, with the four companies competing for individual task orders.

NextGov also reports that Google has a major deal with the US Navy:

Google Public Sector was awarded the U.S. Navy’s ONENET contract in October to “provide highly specialized cloud services” for the U.S. Indo-Pacific Command. Google Public Sector does not publicly disclose revenue figures, but Google Cloud and its public sector cloud business have both experienced year-over-year revenue growth since 2022, with Google Cloud capturing $12.3 billion across all its business in the first quarter of 2025.

“I am feeling super confident in our ability to work with [the Trump] administration to show them that Google is all in,” the Google executive Karen Dahut is quoted as saying. “This is the most disruptive, and I mean that in a really positive way, because they are looking at this as an opportunity to bring real disruption to the way that government operates,” she said. “To drive efficiency, to drive cost effectiveness, to bring new emerging technology to bear to government, and to really make a difference for enterprise operations or mission.”

Google also famously inked a $1.2 billion joint deal with Amazon for Project Nimbus, to provide cloud compute and AI services to the Israeli government and military. Employee groups like No Tech for Apartheid have been protesting that contract for years now; some have been fired for staging sit ins at the Google office. The same organizers and others are also protesting Google’s ties to ICE and the Department of Homeland Security, and though some have signed on in support of the effort, there’s been nothing approaching the actions of 2018, when thousands of employees stood up and walked out to spurn Project Maven.

There’s still some dissident spark among workers at Google, difficult as the harsh response from management to organizing and the current job climate make staging meaningful protest. Try as it might, Google hasn’t been able to crush it. It remains to be seen whether, and how, those remaining efforts might expand.

Microsoft

Microsoft is probably the most prominent commercial tech firm with significant government contracts—notably, it landed a $22 billion contract to develop the U.S. Army's Integrated Visual Augmentation System (IVAS). That didn’t pan out so well though, and after development delays and reports of sick soldiers, the contract was spun into a partnership with Anduril.

Microsoft also had a $533 million enterprise service contract with the US Navy, that has since expanded. Its Azure OpenAI platform has been authorized “for U.S. Department of Defense workloads at Impact Level 6 (IL6)” aka the highest classified levels. “With this announcement, Azure OpenAI Service is now authorized for workloads at all U.S. Government data classification levels.”

Just last January, Microsoft, along with Google and Amazon, won an $800 million contract with the US Air Force—its slice was worth $170 million.

Microsoft is also supporting Scale AI in its Thunderforge project, the first effort to bring AI agents to the Department of War/Defense, in a deal worth an undisclosed billions of dollars:

Thunderforge marks the DoD’s first foray into integrating AI agents in and across military workflows to provide advanced decision-making support systems for military leaders.

Our team of global technology partners – including Anduril and Microsoft– will develop and deploy AI-powered solutions and custom agentic workflows (always under human oversight) to our mission partners initially at Indo-Pacific Command (INDOPACOM) and European Command (EUCOM). Anduril is integrating Scale AI’s LLM capability into its Lattice advanced modeling and simulation infrastructure to enhance mission planning. Microsoft is providing state of the art LLM technology to enable a leading edge, multimodal solution.

Microsoft is perhaps the most expansive tech defense contractor for the federal government (it’s also the oldest and largest supplier of digital infrastructure to government agencies in general) and its legacy status means its leadership doesn’t have to kiss Trump’s ring quite as obviously or obsequiously as OpenAI’s does. Microsoft is all but part of the blob now; a dull, apparently permanent fixture of the military industrial complex like Northrup Grumman or Raytheon/RTX. That does not mean it cannot or should not be protested, or that its leadership might be given a pass.

Amazon

Amazon is party to the above-mentioned JWCC contract, its own cloud compute deals, and the Anthropic-Palantir partnership; in addition to that, I recently wrote in-depth about Amazon’s recent enablement of authoritarianism:

Anthropic

Yes, Anthropic should be given credit for refusing to continue its contract with the military after the Department of War demanded it amend provisions to allow its AI to be incorporated into state surveillance and autonomous weaponry. The move may have served Anthropic’s reputation as the more ethical, safety-minded AI company (or perhaps even been crucial to maintaining its credibility at all) but it was ultimately the more moral one to make—and served to well illustrate OpenAI’s relative unscrupulousness as the rival rushed to fill the void.

Still, Anthropic doesn’t exactly have clean hands here, either. After all, it signed the $200 million contract with the Trump Administration’s DoD in the first place. A year before that, it signed a different one, in partnership with Palantir and Amazon. Before Iran, Claude was notably reportedly used in the campaign to kidnap the Venezuelan president Nicholas Maduro.

But the example the company’s break with the Department of War sets is a crucial one: That AI companies can bow to public pressure under the right circumstances. Anthropic’s workers—and their consumers—expect a degree of moral behavior from the company, and can thus be pressured to back out of enabling the worst tendencies of the war machine.

The question becomes: how do we create the conditions for similar changes in these other companies? Antitrust action would help curb their size and power, but the prospect seems far-off, consumer boycotts can make for some embarrassing headlines, and public shaming of executives can make for some prodding in the right direction. It should, after all, but utterly toxic for any of these companies to contribute in any way to a president that promises genocide, to a war that was entirely unprovoked, and that immediately led to the death by American bomb of over a hundred little girls.

Despite the relative quiet, the best hope for structural change may be old-fashioned worker organizing. (In part due to a lack of many other meaningful avenues.) It’s not an easy choice to step up and speak out, to refuse to work on projects for a military carrying out such actions, a president willing to go to such extremes—but it’s clearly the moral one. Trump may or may not have “meant” his threat to destroy an entire civilization; what’s clear is that we stand on a precipice, with few actors capable of influencing his increasingly addled decision-making, his poster’s trigger finger. The Valley is home to some of those few actors who can.

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On that big Ronan Farrow New Yorker cover story about Sam Altman and OpenAI

I eagerly tore into the New Yorker cover story; Ronan Farrow’s reportedly year-and-a-half-long investigation into Sam Altman with fellow staff writer with Andrew Marantz, and, well, I have to say…

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Sanders’ and AOC’s proposal builds off of years of increasingly energized, widespread and bipartisan opposition to data center development on the municipal and state level. Several of those efforts have successfully shut down or delayed planned data centers. The movement has grown so broad, and so concerning to the AI industry, that a group was launched just to track it. Eleven states, from deep red to dark blue, are currently considering data center moratoriums; Georgia, Vermont, Michigan, Virginia, North Dakota, and South Carolina are among them. The mayor of Denver, Colorado just passed one. The Seminole Nation of Oklahoma became the first tribal council to enact a moratorium on data center development.

It’s not just data centers, either. It’s a trend I’ve noticed over the last few weeks: Across the AI economy, workers and consumers have taken to refusing the technology in direct and robust ways.

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Wikipedia, one of the largest, best-known, and most-visited websites in the world, recently announced it was banning AI-generated content. The new policy states that:

Text generated by large language models (LLMs) such as ChatGPT, Gemini, Claude, DeepSeek, etc. often violates several of Wikipedia's core content policies. For this reason, the use of LLMs to generate or rewrite article content is prohibited.1

The policy was approved by a 40-2 vote. In recent months, Wikipedia editors had faced a significant rise in AI-generated content, much of which was riddled with errors. The problem had gotten bad enough that a group of editors, calling themselves WikiProject AI Cleanup, had to band together to systematically delete the deluge of AI-generated mistakes.

Editors had had enough. Following the lead of the German language Wikipedia team, the English Wikipedia decided that banning AI-generated content outright was the best move. It was also the overwhelmingly popular one.

I could go on. I think I will. The video game studio Capcom was recently compelled to declare that it “will not implement any generative AI assets” in its games. Previously, executives had suggested they were experimenting with AI, and the studio’s latest Resident Evil game had been showcased in a demo of Nvidia’s new DLSS 5 (Deep Learning Super Sampling) tech, which, as Games Industry notes, “was criticized for adding an AI sheen to character models.”

In other words, Capcom understands the cultural and economic climate in the gaming world as one that demands a promise to refuse to use AI art altogether.

It’s a similar story with publishing. One of the ‘big five’ publishers, Hachette, recently became the first major publisher to cancel the publication of a novel for containing AI-generated writing. A number of commentators and critics had already pointed out on social media that Shy Girl, by Mia Ballard, contained prose with all the telltales of AI-generated text. In a New York Times article, the head of an AI writing detection company, Pangram, concluded the same. When the NYT reporter reached out to Hachette for comment, the publisher pulled the book.

“Hachette remains committed to protecting original creative expression and storytelling,” a Hachette spokeswoman told the Times. The spokesperson added that Hachette requires all submissions to be original to the authors, and demands they disclose any AI use in the writing process. While much of the resulting discourse has focused on the longterm inadequacies of such policy, raising questions like “how much AI can a writer use without penalty” and “what constitutes reasonable AI use in writing?” a consensus answer seems to have emerged about what the answer to that question is among writers themselves, and it is something close to “None.”

There are pro-AI detractors, of course, but at least for the time being, the publishing industry has attuned itself to a policy of de facto AI refusal. It’s done so both for material reasons—it’s still unclear whether publishers can retain ownership over works generated in part by AI2, or how many people actually want to read AI-generated books—and for cultural and political ones. Namely, to avoid more outrage and blowback from authors and readers alike.

Alex Preston, a book reviewer for the New York Times, discovered this after he was dropped as a contributor for using AI to generate a review that overtly plagiarized from another review in the Guardian. The specific policies may be nebulous, but the moral standards are still clear enough; use AI, risk torching your career.

Matters are a little less clear cut, perhaps, in journalism, where demands for volume are high, pay is low and many tech and business journalists are more interested in emulating the efficiencies of the companies they cover than practicing their own craft. Over the last couple of weeks, there’s been a (somewhat bizarre, really) run of stories about journalists boasting about their AI usage. These include a content farmer for Fortune who “writes” 600 stories a year, a former Verge editor who uses AI to create drafts for his tech news Substack, and a Washington Post columnist who says she uses AI to research columns and to generate ideas.

There have been many good responses to this journalism-in-AI moment—the labor journalist Hamilton Nolan, Today in Tabs’ Rusty Foster, and New Yorker literary critic Becca Rothfield all contributed—but I think Marisa Kabas, the independent reporter, probably summed up the consensus sentiment best. She titled her rebuke, aptly, “Refusing to accept an AI-poisoned future of journalism.” There is no pride, she wrote, “in relying on a machine to do deeply human work.”

She opened her piece with an anecdote:

In a November conversation at the Urban Consulate in Detroit, the great writer and thinker Tressie McMillan Cottom was asked by host Orlando P. Bailey, “Do you have a daring idea for us to ponder and sit with for our collective future?” McMillan Cottom replied with this: “When people try to sell you on the idea that the future is already settled, it’s because it is deeply unsettled. I think that this promise of an artificial intelligent future is really just a collective anxiety that very wealthy, powerful people have about how well they’re gonna be able to control us in the future. If they can get us to accept that the future is already settled—AI is already here, the end is already here—then we will create that for them. My most daring idea is to refuse.”

Today, I refuse.

Indeed. Refusal certainly seems to be the practice, while not always named, animating so many of these actions. Refusal of AI in a field, occupation, enterprise, or art form we have been told is doomed to upheaval.

And these are just the events of the last couple of weeks. I didn’t even mention how educators at the University of Edinburgh called on its administration to drop its OpenAI contract in an open letter signed by 470 teachers there. Or how the Hacks star Hannah Einbinder called AI creators “losers” who are “trying to rob real creative people of their gifts.” Or that Oberlin’s Luddite Club wrote a letter rejecting their school’s proposed “year of AI exploration”; the hand-typed missive was published last year, but went viral in recent weeks.

Hell there are probably some high profile acts of refusal I’ve missed.

Generative AI has never been popular in a majoritarian sense, even as the tools have accrued millions of users. Since the boom began in 2023, polls have consistently found that Americans are more concerned than excited by the technology. That remains true today, and perhaps truer than ever. A new Quinnipiac poll headlined its findings by stating that “Americans’ AI Use Increases While Views On It Sour.” 76 percent of those polled didn’t think AI output is trustworthy, while 55 percent think AI will do more harm than good. Just a third said it will do more good than harm.

The margins of increased usage, meanwhile, comport with what you would expect to see as more employees were compelled by management to use AI in the workplace—a trend we know is taking place—and the gradual normalization of new technology that is being promoted by tech oligopolies and true advocates alike. But just reflect on that polling, which is by no means an outlier; every Pew poll I’ve seen over the last couple of years has found basically the same thing. The more people use AI, the less they like it, and the more concerned they are. It’s no surprise then that we’re beginning to see mass, overt refusal of AI in one context after another.

And what’s particularly interesting to me is how the politics appear to be moving from rejection to refusal. Max Read has written about the ever-proliferating hype and backlash cycles of AI discourse, and how last year marked the beginning a “backlash to the AI backlash.” After LLM products launched in 2022, it was to a symphony of hype about imminent super-intelligence and a jobs apocalypse that lasted through much of 2023; when neither materialized in 2024, widespread backlash set in. The products made wrong-fingered slop, were wrong all the time, and so on. By 2025, there were enough use cases and new demos, and certainly enough investment capital, to shoulder a renewed full court PR press; for the industry to mount a backlash to the backlash. There’s a case to be made that this particular cycle may have reached its apex with the Claude Code episode, which was made to demonstrate that AI is proficient at generating code and novel apps.

Now the dust has settled from the backlash to the backlash a bit3, and I think we’re seeing something of a new mode of AI protest emerging. As tempting as it is to call it a backlash to the AI backlash to the AI backlash, it feels different, and maybe more robust than that. Where the last backlash fixated on products, companies, and their harms and shortcomings, this new spate of refusals feels grounded in more categorical terrain. The questions we are litigating now are less ‘is this AI product good or bad’ and more ‘we have seen what it can do, and do we want AI to exist in this space at all?’

Do we want a half dozen tech giants spending hundreds of billions of dollars on data centers around the world to build what is essentially the same technology, spiking energy costs, creating noise and pollution, and even, according to one study, dramatically raising the temperature around the complexes due to an advanced heat island effect? So that those tech giants can make good on their promises to automate jobs en masse and remake the social contract to their liking? A great many people who live closest to said projects have decided they do not, and rather than cut deals or hedge bets, they have chosen to refuse them.

Do we want AI text and image generators producing our journalism, safeguarding our stores of knowledge, creating our art? Even if it can? If not, then it makes good sense to refuse outright those products’ entry into those arenas. To ban AI-generated content from Wikipedia, from publishing, from video games. And to ban the companies aspiring to enrich themselves by taking over all that knowledge and content production from setting up shop in our backyards.

There is great power in refusal. The Luddites are mocked today because elites worked hard to distort their legacy—it is too inconvenient, too dangerous, even—but they were cheered as folk heroes and left the industrialists deskilling their jobs terrified by refusing outright to submit to rank automation. The writers and actors in the WGA and SAG-AFTRA who went on strike in 2023 rallied millions to their cause by drawing a line in the sand and refusing to let their work be turned over to studio bosses with enterprise ChatGPT accounts.

Looking back at the events of the last few weeks, I can’t help but wonder if we’re seeing a reawakening of our capacity for this sort of mass refusal. As it becomes clearer by the day that AI promises to be an implement of automation; of worker exploitation and knowledge degradation; an enormous energy and resource consumer; a tremendous engine of wealth transfer.

There are more signs yet: Stop GenAI mutual aid groups that pull no punches in calling for exactly that. The similarly monikered Stop the AI Race that protests in the streets of San Francisco. The New Yorker writer Rothfield, who has written “you don’t have to use AI—stop it right now” is organizing a campaign to keep AI out of publishing, academia, and journalism. I have been asked to join a number of ‘Writers Against AI’ groups in recent days, and to sign a call to ban outright generative AI products aimed at children. There is a lot of political potential in straightforward refusal here, as well, as Sanders and AOC have gleaned; labor, academia, and public interest groups might benefit from taking note.

Now, sure, “AI” is a nebulous descriptor that can be applied to a great many technologies and tendencies, many of which are not being operationalized to automate creative jobs and deskill workers. (This a fact that is often wielded to AI industry advocates’ advantage to blunt or deflect critique: Do you hate spellcheck too??) But the truth is, it’s clear enough to most people what Silicon Valley’s project boils down to, in practice, when its executive class talks about AI. It is to move as much chatbot product, slop, and job automation as it can. It’s entirely possible—as well as moral and popular—to refuse this project.

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Revulsion at slop aesthetics certainly played a role in the collapse of Sora, OpenAI’s much-hyped and less-used video generation app; the company announced it was shuttering the operation this week amid a pointedly publicized effort to “nail” its core business and to not “get distracted by side quests.” (The $1 billion deal OpenAI cut with Disney is also dead.) Users simply did not seem to like Sora. The app, which was estimated as costing the company as much as $15 million a day, saw both downloads and monthly usage taper off rapidly after just two months of growth.

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After peaking at 6 million monthly downloads in November, Sora fell to around a million and a half last month.

Monthly average users had already begun to decline as well. Originally pitched as a bona fide TikTok competitor and the revolutionizer of Hollywood in a single package, Sora turned out to be more OpenAI spaghetti thrown at the wall, an impressive tech demo dressed up into a product, rushed to market and breathlessly hyperbolized.

There’s a case to be made that the company was never all that serious about turning Sora into a successful service, and that it’s best considering the app as one of OpenAI’s myriad instruments for keeping the hype cycle fed and the media hooked and the investment dollars flowing. (Given the economics and its intense compute demands, if Sora had blown up, it’s hard to see how it ever turns them a profit.) Even if that’s true, it’s still very much worth considering why Sora tanked.

Theoretically, offering users the ability to appropriate, remix, or outright plagiarize a nearly limitless well of pop culture IP and to mess with their friends by dropping them and their digitally scanned visages into any kind of scenario, seems like an idea that could have legs. Yet it was cursed from the start. To begin with, Sora was just overwhelmingly unpleasant to look at and to use. I have an account—it is my solemn reportorial duty—and from time to time I’d log on to check in on the platform. Most times I did, it seemed that people were using Sora to push the boundaries of the platform’s own conspicuous tastelessness, mining that queasiness inherent in the Sora aesthetic. There was a kind of submeme where people gruesomely but not realistically peeled their faces off to reveal they were other people. There were a bunch of posts of giant women stepping on men and crushing them. Judge Judy arbitrating a court case between Obama and Trump. People driving their cars into mountains of human shit. That kind of thing.

It turns out that there was a limit to user interest in half-baked, glitched-out pop culture mashups or videos of anthropomorphized fruit having sex or AI CEOs hilariously placed in compromising situations or whatever.

It just wasn’t fun. The jokes felt almost incapable of landing unless they were folded directly into the narrow currents of cheap Adult Swim surreality that defined Sora’s vibe. The videos looked anywhere from dull and derivative to sickly and weird to unsettling and nightmarish. I regret not taking a screenshot but I swear at one point that OpenAI served me a pop-up survey question that asked something like “how does using Sora make you feel?” indicating the company was worried about the mental health of anyone who would spend more than a few swipes on the app. TechCrunch—TechCrunch—called Sora “the creepiest app on your phone.”

As such Sora seems to have been used mostly by people who wanted to whip up a slop joke or slop commentary to share on another platform. Who can blame them. Why would anyone want to spend any longer than they had to in the corridors of a pulsing, feel-bad uncanny valley? Sora’s were the halls of pure slop, and not even AI CEOs themselves can stomach that slop.

Now, it’s often argued that AI cannot create anything truly new, that even the most sophisticated LLMs are fundamentally token-prediction systems, and thus the pixels its image-generators rearrange are necessarily an amalgam of shapes and styles all seen before. That AI image generators are intensively derivative, and that Sora was all but exclusively so, is undeniably true. And that I think is the root of its failure. LLMs strive to reproduce reality, or beloved aesthetics of the past, or even generally pleasing imagery, and they almost always fail. This failure is immediately apparent to us, for the same reasons that animate our discomfort with imagery in the uncanny valley in general, as well as some reasons beyond that.

This failure is not limited to or even primarily concerning image quality. As the generators have improved in ironing out past telltales like the extra fingers and such (in prepping for this post I looked back at the original Sora videos and it was shocking to me how bad they were), our queasiness hasn’t subsided. AI image and video slop is not just homogenous, and it’s not just derivative. Slop is a visual embodiment of the modern AI project itself; an in-progress effort to replicate, undermine, and replace human works. It’s fundamentally unsettling. (This one reason that, as Gareth Watkins argued, AI is ideal for creating a new aesthetics of fascism.)

That’s one slapdash theory anyway, and one explanation for why, to this day, years into the AI boom, after so many billions in investment and numerous model improvements, whenever we encounter AI-generated imagery, we still tend to either recoil or roll our eyes. Why, while AI imagery was originally a very useful demo of tech capabilities for founders and execs, now they seem to wish it would go away. Slop is a pervasive reminder of both AI products’ persistent qualitative shortcomings and the noxious intent of the products themselves.

It’s also a reminder of just how little regard Silicon Valley generally seems to have for aesthetics in general anymore. I think it’s fitting that the same week that OpenAI announced the imminent shutdown Sora, its splashiest showcase for AI, Meta announced the imminent shutdown of Horizon Worlds, its splashiest showcase for the metaverse. And if there was ever a technology that looked like shit, whose aesthetics screamed failure, well:

AI often gets compared to the metaverse, in the context of allegations that it’s Silicon Valley’s latest grift after that spectacular, much-hyped failure etc. But AI garners fewer comparisons to the metaverse as a project with similar qualitative dimensions, and similar objectives. Recall, Meta launched its metaverse pursuits (replete with company name-changing gravitas/bravura/etc) with digital entertainment meant to simulate the real world (Worlds) and a productivity program (Workrooms). The metaverse was also supposed to replace and streamline bodied work, and offer users a digital facsimile of the real world.

But of course it looked like garbage. It looked primed for failure from day one. It was too obviously unserious to register the uncanny valley anxieties AI-generated imagery does. Yes, the much-remarked upon lack of legs in the avatars, but also the laughable cartoonish aspects, the cursed attempted conjuring of a Facebook-but-in-real-life vibe, and so on.

Now, I’m not going to sit here and lament the passage of the Steve Jobsian ethos from the Valley, which elevated the importance of imbuing tech with taste, but I do think where we’ve landed since then is reflective of what’s motivating and incentivizing the industry in the AI era. In the 2000s, during web 2.0 and the rise of the smartphone, tech companies still very much needed to sell new users on its devices and digital platforms. It was pretty simple; Apple knew the iPhone had to look and feel good, or no one would want to learn how to use it. Aesthetics were core to the project, from the slick industrial design of the phone itself to the user interface design of the OS and the apps it would house.

Conversely, the apps that made the iPhone so successful—namely, social media—were predicated on an aesthetics of transparency. Facebook, Twitter, Instagram; these apps existed as conduits to share personal experiences with friends (and, yes to glamorize or dramatize them, to induce more sharing). But the central idea was user connection, that the software would mostly get out of the way, so people could share photos, thoughts, memes and work.

It fits with Cory Doctorow’s enshittification thesis that after Apple et al won, and entrenched the phone as the core device through which the majority of us process the world, socially, for work, etc, becoming enormous monopolies in the process, that concerns over the aesthetic dimensions of the project would diminish. The fading interest in serving the user, the consumer, the staidness of the monopoly; all that explains the curdling aesthetics of Silicon Valley design.

But AI (and the metaverse, and web 3) must be seen not as novel innovations but as new attempts by the same investor and developer class at extracting value from their past successes, at seeking out new revenue sources amid an already digitally saturated world. It was no longer enough for users to post photos taken with their iPhones on social media, or to use cloud enterprise software to organize and input work; AI companies want to generate those images themselves, perform the work themselves, and capture the value for themselves.

For years now, Silicon Valley has largely failed to produce something that most people want, or are even comfortable having in their lives; it has failed to make the case for AI to a public that mostly fears for their jobs, their energy bills, their children’s safety and future.

AI slop ensures that no one forgets this. No wonder OpenAI wants to pivot to focusing on enterprise AI, where no one has to look at the technology’s visual exports unless they are forced to by their boss. The general public dissatisfaction with AI is a result, in part, of being surrounded by so many obtrusive reminders of this grim outcome, and the attendant, even grimmer pursuit: That Silicon Valley will not stop until it has colonized, extracted, and automated all that it possibly can.

You might even go so far as to say that Sora was a crude, funhouse mirror-refracted vision of the world Silicon Valley is struggling to birth. Let’s not forget that most people who encountered it found it repulsive.

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Further reading:

-What is “slop,” exactly? by Max Read
-Disney’s Sora Disaster Shows AI Will Not Revolutionize Hollywood by Jason Koebler at 404 Media.
-AI Slop Education by
-The Slop Tax: A Brief Introduction by
-AI: The New Aesthetics of Fascism by Gareth Watkins

Non-slop must-read of the week:

on military automation, Claude, and Project Maven:

Artificial Bureaucracy

Kill Chain

A revised version of this article appears in the The Guardian. You can read that version here…

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a month ago · 675 likes · Kevin Baker

Earlier this week, I broke news about a new basic income pilot program; the first of its kind to issue payments specifically to workers who have lost work or opportunities because of AI.

The reaction to that story was, let’s say, pretty strong! A lot of commenters and readers criticized the program as insufficient or abetting the AI industry. Honestly, I love it; I welcome any and all strong, thoughtful reactions to my work and goings-on in AI or Silicon Valley or wherever else in general. It’s always good to hear from you.

In fact, it made me think I might have to start running some letters to the editor here. Let’s start with one from Anne Wanders in Germany:

Hi Brian,

First off, thanks so much for all your work! It’s so necessary, sadly.

You already made the observation that narrative around a need for UBI is feeding into the narrative of the proclaimed future when “AI” or even “AGI” will make human work obsolete on a massive scale. So in addition to that, just a quick note regarding the concept of an “AI dividend”:

The name “AI dividend” is yet another example of a brilliant marketing term, makes it sound as if laid off workers were investors in the tech … I think it’s bitter to pay a “dividend” to people losing jobs rather than to the people worldwide whose IP and personal data have been illegally used, repackaged and sold. If anything, we (creators, authors, private individuals etc.) should be paid the dividend because our work and personal data are the foundation of their business model.

I, and many others I know, want acknowledgement of what these companies did and do, I want pay for what has been scraped without consent, I want them to respect the opt-in principle of copyright or intellectual property according to applicable different legal concepts globally. (I live in Germany, the EU does not have “fair use” or “copyright”, my intellectual property exists the moment I create it without a need to register it formally!). So once that happened, once they paid all of us what is due including interest/royalties, call it a dividend or not, if after paying out all that money they still manage to operate their business, then would be a good time for them to pay taxes so a democratically elected government can help people affected by job loss.

To me, such an “AI dividend” is a free handout, further evidence of a condescending view of the people unwillingly contributing to and affected by the AI hype. It’s an attempt to circumvent the democratic and legal system.

Again, thanks so much for all your work, it means a lot and it helps me spread the word about what AI is and is not.

Best wishes,

Anne

These are good points! The first thing I will say is that one thing that’s a real challenge in running this kind of a one-man newsletter operation is that there’s often no easy way to designate between ‘opinion’ and ‘news’ and ‘essay’ and it would even be kind of weird if I were to try do so. BITM is comprised of opinionated columns and essays (see above), more straightforward reporting, and so on. And sometimes those things are in tension; when I was reporting on DOGE’s firing of federal tech workers last year, I had a lot of opinions that didn’t necessarily seem appropriate to include in a news story. But then I might share those opinions in an edition just a few issues later. It’s a little messy.

So! Just because I am writing about a basic income project does not mean I am endorsing said project. I hope that’s clear in general, and from the presentation, tone, and inclusion of critical perspectives in the story, but it also makes a lot of sense that it would seem otherwise. After all, I condemn and endorse stuff all the time in these pages! I’ll surely write more on UBI in the future, but for now, suffice to say, I think this is a fascinating project that is very much a sign of the times, and in BITM’s wheelhouse. (And for the record, the UBI is being piloted by nonprofits that are not affiliated with AI companies, by worker-affiliated orgs who are trying to help blunt the impact of the AI economy.)

But thanks again—and always—for the comments, notes, emails, and social posts. All of it. I read them all, even if I don’t always have time to respond. I count myself lucky to be part of such an incredible critical community here. Cheers all, and hammers up.

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As always, this work is made possible entirely by those readers who pitch in a small sum—the cost of a coffee or beer a month, or, say, a coffee table book a year—to support it. A sincere thanks to all of you: I cannot do this writing, reporting, and analysis without you. If you’re able, and you find value in this work, please consider upgrading to a paid subscription so I can continue to carry out and even expand this work.

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“Over the last few years, I’ve been mentoring students who have really struggled to land any jobs,” Kaitlin Cort, a veteran software engineer and programming instructor, tells me.

Cort is one of the organizers behind the AI Dividend, and she says she was alerted to a growing problem as she’s tried to find jobs for graduates of her programming classes. (She’s taught for Per Scholas, Future Code, and NYC Tech Talent Pipeline programs.) Cort says she’s seen the job market for entry level programmers dry up as executives and managers across the tech industry embrace Copilot and Claude. “The few jobs that students have landed have often been demeaning,” Cort says, “and not really allowing them to do real engineering work, but rather asking them to review repetitive tasks, and validate parts of code created by AI.”

The impact of AI on job loss, especially in tech and creative industries, is one of the most-debated subjects of the day. It’s a frequent topic here in the pages of Blood in the Machine, and is examined in particular in my AI Killed My Job project.

Whether or not executives and managers will use AI to replace human labor in the long-term, at a scale promised by AI executives like Anthropic’s Dario Amodei, who envision huge swaths of the workforce rendered obsolete, very much remains to be seen. These executives have a pointed interest in promoting that narrative. What is clear is that right now, tech firms from Amazon to Block to Salesforce to Meta to Duolingo are instituting layoffs and citing AI as the cause. And that across the nation, enough managers and clients are embracing AI-generated content that artists, writers, and translators are watching their incomes deteriorate.

And thanks to those mass layoffs in the tech industry, more of the scant available entry level jobs are now going to engineers with three or more years of experience, Cort says. So, already a member of the Tech Workers Coalition, Cort founded What We Will, a group aimed at “organizing workers across industries upended by rapid technological change to build collective power and win shared prosperity,” per the group’s website. What We Will, in turn, partnered with the Fund For a Guaranteed Income (F4GI), an established nonprofit that seeks to “prove a viable path to guaranteed income,” to launch a pilot project to that end: A $1,000-a-month basic income for workers whose jobs have been harmed by AI. Christened the AI Dividend, the program was designed with input from hundreds of workers, who shared their experiences with an online survey, and is funded by F4GI.

“Everyone tells workers to learn AI skills but ignores that it takes time, money and connections to do so,” Nick Salazar, the executive director of F4GI, tells me. “The AI Dividend combines cash with reskilling so workers can actually figure out what’s next. Our goal is to learn what actually helps workers in the AI economy.”

Applicants are being selected on a rolling basis. They’re assessed for eligibility by the AI Commons Project team, which oversees the dividend. If selected, workers will receive the $1,000 per month stipend through 2026 and into 2027. The project designers hope to gather data about the impact the funds have on workers as they push to expand the program.

“To be clear, our program is not only for tech workers,” Cort says. “We strongly focus on providing support for call center workers, copywriters and journalists, data annotation workers, creative workers, and other knowledge workers impacted by AI disruption.”

But since software engineering has been so heavily impacted, she says, and she saw so many of her own students struggling, with pressing needs, many initial recipients are low-income tech workers, aspiring software engineers who have been unable to find work, or tech workers who have been laid off and have not been able to find a job for over a year.

“We realized that financial stability during the job search is of critical importance if they are to continue pursuing the career path they have invested time and energy training for,” Cort tells me. “An initial recipient in our pilot program is unhoused and requires immediate assistance.”

Other pioneering groups have been formed to address AI’s impacts on work: The Stop GenAI mutual aid network focuses on acquiring aid for artists, academics, writers and creatives hit by AI, for one. But the AI Dividend appears to be the first pilot project to formalize a means of delivering predictable monthly no-strings direct payments to workers impacted by AI. In fact, workers like those in Stop GenAI’s membership would seem to make ideal candidates for the program.

The next step, Salazar says, is to press funders and the major AI companies to contribute and scale up the effort. Some AI industry employees have already contributed time and resources to the project, he says, and talks have been initiated with firms like Anthropic.

“We’re in active conversations with AI labs about long-term funding,” Salazar tells me. “Major AI CEOs say they believe in supporting displaced workers. Employees at AI companies have already stepped up to contribute time and expertise and we expect the companies will follow their lead. If they don’t, it raises the question of whether they’re serious about supporting workers.”

For a nonprofit aiming to fund a basic income project, this seems a shrewd strategy. AI CEOs, from Sam Altman to Elon Musk to Dario Amodei, have all at one point said there will be a need for a universal basic income because of the impact of their products on workers. And while there’s plenty of controversy around the very concept of a UBI—sharp critiques have been issued from the right; that the state shouldn’t pay for mass social support; and the left; that a monthly allowance on the order typically proposed would cement inequality and justify hollowing out other public institutions—I for one am curious to see if AI CEOS are willing to put their money where their mouth is.

Even if the AI is successfully funded in the longer term, based on worker input and Cort and her colleagues’ experience in the field, part of the program may include finding pathways for workers and students to leave tech altogether, they say. “For some participants, we may need to recommend other career paths in healthcare or skilled trades, but we are trying our best to bridge the skill gap now required for entry-level workers,” Cort tells me.

Workers interested in learning more, sharing their experiences with on AI in the workplace with organizers, or participating in the program, can fill out this survey at the AI Commons Project. Eligible workers will then be contacted by members of the AI Dividend team.

“I don’t think this issue is going away anytime soon,” Cort says. “We have our work cut out for us.”

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O’Brien’s first joke was about how he’s the last human host of the Oscars, and that next year it will be a Waymo in a tux. That kind of broad, lightly absurdist and mostly victimless joke plays well at the Oscars, and he got a good solid laugh. The other kind of joke that tends to do well is lampooning a famous person in attendance who is clearly game to be lampooned, so everyone can feel good in laughing along. Conan had this one to that end: “Netflix CEO, Ted Sarandos, is here. And this is exciting—it’s his first time in a theater. This is what they’re talking about.” O’Brien then did his evil rich guy imitation: “Why are they all together enjoying themselves? They should be home alone where I can monetize it.”

He also got in digs at Amazon—”Why isn’t the website I order toilet paper from winning more Oscars?”—and one later at YouTube, as described by the Associated Press:

“Some people are worried this is going to change how the Oscars are viewed,” O’Brien said Sunday, “but I’ve been assured …” he was then cut off by a wildly intrusive, YouTube-style ad featuring actor Jane Lynch pitching a tactical flashlight.

With the very large caveats that a) I haven’t watched a lot of the Oscars in recent years and that b) I may be guilty of some degree of confirmation bias given my interest in these particular subjects, there seemed to a queasiness to the vibes in the audience that I don’t recall encountering in Academy Awards past. There was a sort of omnipresent ‘should we be laughing at this joke about Amazon’s vertical monopolization or Netflix’s role in destroying movie theaters because they might fund our next film’ feeling hanging over the proceedings. You could hear it in the uncertain laughter that followed the Silicon Valley-skewering jokes that didn’t fall into one of the two above-mentioned categories, a kind of muted enthusiasm, a shifting in seats real or proverbial.

Now there have surely been jabs at streamers in past monologues, but I don’t remember the whole theme of the opening bit and thus the general framing device for the award show that follows centered so wholly around tech criticism, which was pretty much the case here. But it does makes sense. Even when Netflix and the big streamers started eating into the major studios’ business a decade or so ago, there wasn’t the palpable level of existential dread among creatives in the entertainment industry that we’re witnessing today.

Part of that dread is of course thanks to the continuation of trends put in motion by the streamers years ago; the gigification of writers’ rooms, the undermining of creative labor with tech disruption, yes, the usurping of audiences from movie theaters. Part of it is thanks to outside economic factors, including incentives to lure production outside of Hollywood, and part—perhaps most, depending on who you’re talking to—flows from the rise of AI, a tech product that just so happens to be funded by many of the same people who have monopolized large swaths of the entertainment industry and eroded working conditions for actors, writers, and film workers. Even if it’s not wearing the tux, AI embodies the broader trend O’Brien was skewering; the deskilling, degradation, and Silicon Valley takeover of entertainment work.

In fact, it seems to me that one reason Timothee Chalamet’s comments about not wanting film to go the way of ballet or opera—and become a niche endeavor that only small audiences will pay to see—caused such sustained backlash is not just because they were insensitive to practitioners of arts still beloved by their adherents, but because they arrived amid a crest of anxiety over the sense that, for the first time in a century or so of film’s cultural dominance, such an outcome actually seems plausible. (What’s especially frustrating to me about Chalamet’s comment is that it’s oblivious to all of that; it was made in service of the idea that the industry just needs to make more good movies to avoid the “fate” of ballet or opera.)

Conan called out Chalamet and his comment, too, early on, amid all the tech criticism. And it’s probably worth noting how Conan himself is an interesting vessel for all this; his career has been stymied by the old studio guard, which famously denied him tenure at the Tonight show, and arguably reached new heights via a popular podcast, a travel show on the streamer HBO Max, and a social media ecosystem that disseminates viral clips like his Mark Twain award acceptance speech or his now infamous Hot Ones appearance.

After that Hot Ones spot, when his podcast cohosts asked about the fallout, he said “If I think something is funny, I’ll do it, and deal with it later.” He’s committed to the bit. At the Oscars, it’s not like his jokes were especially brave or risky or anything, it’s just that he and his writers felt that gallows humor about big tech and AI strangling his industry would be funniest, all things considered. No wonder he got raves online, while the humans in the room squirmed.

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In other Academy Awards news, I enjoyed this post on the futility of watching the Oscars. Frankenstein won some stuff.

Oh and an award-winning playwright called Sam Altman a Nazi to his face at the Vanity Fair afterparty. More on that below.

NEXT MONDAY, friend of the blog is hosting a Q+A with the writer of the pioneering cyberpunk show Max Headroom in LA; it’s free but spots will fill up quickly so RSVP here. I plan on checking it out myself.

In case you missed it, the latest edition of AI Killed My Job, focusing on educators, published last week.

CRITICAL AI REPORT. TUES, MARCH 17

Buzzfeed is on the brink of bankruptcy after pivoting to AI

When I was writing the tech column at the LA Times, I covered the news that digital media mainstay BuzzFeed was ‘replacing’ its workers with AI. Shortly after disbanding its award-winning News team, CEO Jonah Peretti announced that the company would be using AI to generate content. Peretti took issue with the way I framed the piece, and we got into a long and sometimes heated debate over what it means to replace

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This mass plagiarization crisis has only deepened and complicated since, leaving educators, administrators, and students to grapple with how to construct, enact, and enforce AI policies at school. I should know: My partner is a professor at a university, and dealing with students who use AI to cheat on assignments has become a core part of her job, and an endless source of frustration.

But cheating on coursework is only the tip of the iceberg. Universities have signed huge contracts with AI companies, which have been driving hard into the space, while K-12 public schools have adopted AI tools, sometimes disastrously. (Los Angeles Unified School District superintendent Alberto Carvalho’s home was raided as part of an FBI investigation into a multimillion dollar deal with an educational chatbot developer that failed within months). Such deals, like the California Statue University system’s $17 million partnership with OpenAI, or Ohio State’s policy to mandate all students learn AI fluency, are top-down initiatives that have left many educators working in the classroom backfooted. Teachers and students alike are being encouraged from all angles to adopt AI products, setting up new arenas for tension and conflict, and posing serious questions about the future of instruction.

AI has indeed flooded the profession, impacting tutelage, administrative work, counseling, testing, and beyond. And it’s already had serious ramifications for labor; as in many other trades, education jobs are being deskilled, degraded, and even lost outright to clients and bosses embracing AI systems. Librarians and tutors are watching as administrators and edtech companies embrace AI tools as a means of cutting their work hours. IT and HR professionals in the education space are competing with AI products on the market and speeding up work to match their output. Educators of every stripe worry that quality instruction and critical thinking skills are taking serious hits as AI provides an easy, if frequently incorrect, route to an answer. And ominously, critical AI programs are being cut just as universities turn to embrace chatbots. One instructor at the University of California at Irvine, Ricky Crano, wrote in to share his story of being laid off from a job organizing a series of seminars that examined the tech industry—just around the time the school was promoting its proprietary chatbot, ZotGPT.

Some educators are fighting back: The American Association of University Professors, a union representing academic workers, for instance, has called for faculty control over all AI decisions as a matter of policy, and AI has become a battleground in contract negotiations and campus life. Graduate student unions, librarians, and activists are organizing against administrations that have rushed to deploy AI.

I’ve heard stories like these, and many more. Last year, 404 Media ran a great roundup of stories told by teachers, and how they’re struggling with AI in the classroom. So with this, the fifth installment of AI Killed My Job, we’ll hear not just from teachers, lecturers, and instructors, but from education workers across the field—private tutors, student athlete coaches, librarians, HR employees, essay graders, and edtech workers—who have all had their jobs transformed by AI. These stories, some of which may sound familiar a few years into the AI boom, and many which will not, help paint a fuller picture of just how the technology has already impacted some of our most crucial institutions.

If your job has been impacted by AI, and you would like to share your story as part of this project, please do so at AIkilledmyjob@pm.me. The next installments will aim to cover healthcare, journalism, and retail and service jobs.

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Before we proceed, I want to share word of a project that might be of interest to readers. The Fund for Guaranteed Income is a nonprofit that researches and enacts, you guessed it, guaranteed income projects, and they’re working on “a support program for workers whose jobs or income have been affected by AI, designed with direct input from impacted workers,” FGI head Nick Salazar tells me. He asked if I might extend a call for participants with readers, and I’m happy to do so:

• If AI has changed your work, you can share your story anonymously at aicommonsproject.org. Submissions directly shape what the program will look like, and anyone who shares will be first to know when it launches.

And now, AI Killed My Job: Educators.

This story was edited by .

I don’t have any reason to believe my employer will not replace me totally with AI

Tutor at a community college

I work at a community college as a tutor to students in ESL, English, and—more broadly—writing for other courses like major midyear essays for students in other classes or those working toward high school equivalency tests. My hours were halved after Trump DOE cuts, so like many other workers I was already in a precarious position.

It’s a fairly low-pay job that takes a lot of emotional labor, especially considering many of our students have not only been failed by the education system but are often literally hungry, might not have heat or AC, are refugees from war-torn countries, and/or are facing a constellation of other life challenges that make it very difficult to succeed. Many of my students survive on gig work and/or Amazon warehouse jobs. It didn’t surprise me when some of these first-year English students started using AI for their papers.

One particularly memorable student brought in her paper followed by the AI version written out paragraph to paragraph in her notebook. She wanted me to help her merge them. ChatGPT made a reference to a movie anecdote that doesn’t exist. This was a personal essay. This was early on—when the AI was so shitty, I sort of believed I could convince her of the value of her own story and voice—which I attempted to do for an hour. We really bonded, it felt like a win for the day, and then she had to go work at Amazon.

A few weeks later, she brought in an AI outline that made no sense and she could not explain which made brainstorming for her paper impossible. Her professor had given her an A [on the outline]. Shortly after, she brought in an AI-written paper that also made no sense and pulled from real sources, but ones that were not reputable and with references to quotes that did not exist. Other students had also begun to bring in oddly perfect personal essays.

The focus was frequently how to personalize them, to try to inject a tiny bit of who they are into the bland product AI had spat out. Sometimes I just couldn’t tell whether it was their own work or not.

That’s really at the core of the issue for me: This was one of my favorite jobs because I felt like I was doing a good thing, I saw students make wildly awesome improvements as writers over the months, and we built real relationships. I cannot express enough how important the human connection is at my job: these are people who rarely get the support they need and deserve. I’ve had students break down crying, I’ve talked one off the ledge. I spent a year decoding the insanity that is a green card application for another. One of the biggest barriers to success where I work is just signing in—basic tech literacy. If/when we switch to AI tutors, the lack of accessibility is one of many issues that is invisible to people who don’t do our job every day.

In the past when my students left, I had faith that they could succeed, that they’d really learned something—namely how to think critically and value their own story. We were able to work together because there was a basic foundation of trust. That trust is gone now, replaced by suspicion and frustration. It feels like my new job is how to help students cheat better.

At our latest professional development training, we were told that the college was piloting Khanmigo, an AI “learning assistant” (lol) for math. We were told to write down all of our fears about AI or in the chat and then push them aside. We listed out the fear of job loss the most, followed by loss of critical thinking skills, privacy issues, feeding a machine that steals our ideas and churns out mediocrity…Many tutors went out of their way to include links to sources like MIT. They also pointed out that AI had yet to improve productivity or make a profit. Our supervisors literally did not address any of this. The message was clear: *AI is here to stay and we have to adapt.*

We were told not to question whether students are using AI, to in fact assume they are, and tutor them on how to better use it. The “use cases” my supervisor included had students choosing between different AI rewrites of passages for whichever one is better and why. We’re supposed to encourage them to think critically about what AI spurts out. We’re also supposed to pretend that this type of tutoring makes any sense when students can just ask for suggestions, click apply all, and get on with it—or, as we know many do—just drop the assignment prompt into AI, mix it up in a few different models, and then ask it to dumb itself down a bit to sound more like them.

I don’t have any reason to believe my employer will not replace me totally with AI even though my supervisor insists they won’t. I know a machine can technically do my job and that AI is already making my job obsolete considering students don’t have to write anymore. My college has chosen to hire numerous adjuncts part-time, limiting how many full-timers they have, and I am one of them. I ultimately ended up taking fewer hours than they offered and contacting some old freelance writing clients to spend more time away from there. It feels like rejecting them before they reject me. My supervisor is giving us the “option” to lead AI workshops and said to think about it. I know the right answer is to say yes. I won’t.

—Lauren Krouse

[We followed up with Krouse before publication. She told us she had quit.]

We’re expected to accept work that is clearly not the student’s as if it were

Professor

I’m a professor in the California State University system, which was recently profiled due to its stated desire to be the “largest AI-driven university in the world.” I want to talk about academic misconduct.

Academic misconduct is when students pass off work that they haven’t done as their own. It used to be “when students pass off other people’s work as their own,” but now, students simply plug exam questions into a chatbot and copy and paste what it spits back to them. While academic misconduct has always been a problem on campuses, before AI, marshaling your evidence and presenting it to the student would trigger a confession, which could then become an opportunity to teach.

Now, one of two things happens: either the student confesses but doesn’t change their behavior, or they double down and insist that it’s their work despite the evidence you present. Students are convinced that the AI cannot be detected, and they refuse to listen when you show them the tells, insisting that it was their own work. I had a student make reference to three issues that were extremely relevant to the exam question but so far outside the realm of what we studied that the only way they would know to talk about it is through extensive self-study that would be reflected in their post-exam recollection. When the student had no idea what their own exam was talking about, but they insisted that they had written the exam answer, I was left relatively nonplussed.

I’m new to the CSU, so I haven’t had occasion yet to send a student over to the formal investigatory process. But in general, my experience at other institutions suggests that without a confession, administrators are loathe to impose any penalties for academic misconduct - and the mere fact of referral means that the student will be on guard against less formal sanctions (and in fairness, it would not be inappropriate to call those “retaliation,” so arguably the student is correct). But this means that when a student refuses to take responsibility for their work, that there’s usually simply no consequences whatsoever - and we’re expected to accept work that is clearly not the student’s as if it were.

There’s also the problem of mixed messages. While we as faculty are free to ban the use of AI from our classes, the university system is sending multiple messages that these are good and useful tools for students. Students are given a subscription to a bespoke ChatGPT bot for the university, and there are constantly workshops and continuing education sessions about “how to use AI for [this thing we have to do].” Combining the administration’s aggressively pro-AI stance with the easy availability of tools means that faculty protests usually fall on deaf ears - even after we show students the complete and utter uselessness of the tools for the purposes they want.

And our students are, frankly, primed to be the targets of AI flimflam. The CSU isn’t an open-admissions university but it is an access institution. This means that we admit students who are at-risk of failing out of higher ed, either because of lack of preparation, lack of resources, or lack of bandwidth due to work or care obligations. This means that a lot of our students struggle with the basic kinds of tasks that we assign them. The promise of an automatic task completer is deeply attractive, and the background and training of our students doesn’t really equip most of them to adequately assess the claims of the AI pitch.

I haven’t been fired and replaced by AI; we have a strong and militant union that is aggressively pushing back against the use of AI to replace faculty. But bargaining is concessions, and it’s not clear whether the administration will be willing to give ground on this issue given how strongly they’ve staked the institution’s future on it. The job has changed due to AI, and combined with all of the other assaults on American higher education, I don’t know if my career will remain on its current track long enough for me to get tenure.

—Anonymous

My university used to WorkDay’s AI to streamline me out of job

Adjunct professor and HR worker at a university

I worked in HR for a university, handling the paperwork for our adjunct professors. Contract hires. And I was an “HR Partner” in addition to my role as an office coordinator.

Anyway, I’m an adjunct myself. Or I was. I taught writing, one quarter per year. A one-credit class. Amounts to about $700. Before taxes.

I took a job at my alma mater, and when it faced financial turbulence, the university responded by laying off 40% of the full-time faculty. They told me I’d be extra busy now, what with all the new adjuncts coming in (cheap labor).

And I was.

The day that HR called me into the Dean’s office to lay me off, I asked them a simple question:

“Who is going to work with all of the adjuncts—the people I handle paperwork and onboarding for every quarter? The people I talk to every day, helping them sort out their classes, keys, syllabi, schedules, and miscellaneous concerns?”

“Oh-oh-oh, WorkDay will do that!” the HR rep told me with a smile. WorkDay is an AI platform for streamlining work. It certainly streamlined mine.

—Jason M. Thornberry

Refusing to use Copilot cost me my job

IT professional at a university

For the past 2 years I’d been working as an IT Professional II at TAMU AgriLife, an organization under Texas A&M University that conducts research and programs related to agriculture and life science. In November 2024, I was moved from the department I’d been working as an IT Professional at since March 2023 to a new department under a new manager. This new manager made it clear from the start that he was obsessed with generative AI, telling me that his department was the place to be if I wanted to learn how to use gen AI. I, however, have never been a fan of generative AI, and had been working my job well for 2 years without it. As soon as I arrive in this new department, this new manager tries to subtly push me into using ChatGPT, Copilot, and Grok to do my work of helping others with technology problems, but every time I was asked I politely declined.

Then, in late March 2025, I had an employee evaluation with this new manager. As soon as the evaluation begins he starts heavily trying to push me into using generative AI, saying it’s “the way of the future” and that “everyone who doesn’t use it will be left behind.” When I tell him I have no interest in using AI, he says that I “better start” or I’ll “have a hard time finding or keeping a job”. He then tells me he’s going to get me a Copilot license, and that I must take a training course to use Copilot. I tell him that even if I take a Copilot course, I won’t use it in my work and thus buying a Copilot license for me would be a waste of company money. The employee evaluation continues, and he keeps trying to pressure me into using AI, but I continue to decline.

Then, on the following Monday in early April, he sends me a message that he’s gotten me the Copilot license (despite me telling him not to) and tells me to pick a day to take Copilot training. I reiterate to him that I have no interest in using Copilot and try to continue doing my job, but he sends more messages to me in an attempt to try and make me take the Copilot lessons. That same day as I am working, one of my coworkers suddenly gets up from his desk and starts yelling excitedly to our manager about how he had just used generative AI to make a musical about “an impregnation ninja who fertilizes every woman on the planet.” My manager responds by laughing it off like it was nothing. As soon as I get the chance I have a private conversation with my manager to tell him that I have problems with my coworker using generative AI to make explicit musicals in the workplace, but this manager says that this coworker “has always been kind of a degenerate” and that “I’ve told him to stop, but the AI is a tool, so it’s up to him how to use it”...meaning this has happened before, and he’s done nothing about it.

The week continues until Friday, when after asking me again if I’ve signed up for the Copilot training and I reiterate that I haven’t, this manager sends me an email saying that if I don’t take the Copilot training I will either be disciplined or potentially terminated. At this point I’ve had enough, so I call Human Resources and the boss of our IT company and report everything I just told you to them, and that my manager is trying to force me to use generative AI but isn’t doing anything about another employee making explicit works during work hours. Unfortunately though, both the boss and HR try to split this into 2 separate issues; the boss says that he will talk to my manager about allowing a worker to get away with making explicit works at the office, but that this manager can make me use AI if he wants and if I don’t like it I should “choose between my morals or my job”; and HR says they will wait to take action until after the boss talks to my manager.

The following Monday, during the second week of April, the boss of our company does have a private meeting with my manager, but I was never informed what was said at that meeting. I assume that the boss told my manager to back off from trying to force me to use AI, because this manager doesn’t mention the Copilot training courses at all for the next several weeks. Thus, I return to working my job and try to move past this whole fiasco.

Things settle down for the next few weeks, until April 23, 2025. On that day, this manager waits until everyone except for me and him are out of the office, and then suddenly asks if I took the Copilot training (after having not mentioned it in the past few weeks). When I say no, he tells me that the time for the Copilot training in April has already passed, and that because I missed the training I will have to either resign in 60 days or be terminated. I ask about taking the Copilot courses in May that were also being offered, but he doesn’t accept and reiterates that I have to choose resignation or termination. I decided to resign.

—Caleb Polansky

My students genuinely do not understand why they shouldn’t use AI

University Lecturer

I’m a lecturer in Psychology at a large private college in Dublin. At a recent meeting (zoom—of course!) our Data Analytics and Reporting manager asked what we all thought about getting AI to mark our students’ work, the things that couldn’t already be turned into auto-marked online MCQs etc, like long form essays. I pointed out that we are paid to mark the work we assign (it’s actually my least favourite part of the job, but that’s not the point) and asked if we could expect a reduction in pay as a result. I was told “We aren’t going to talk about that.” I should train the AIs to replace me as a marker but should not even be so bold as to wonder what effect that will have on my pay.

Obviously, students are using AI to write the assignments anyway. The idea that we can catch this kind of plagiarism effectively is pure fantasy. Increasingly my students genuinely do not understand why they should not use AI anyway... what is the point of ‘wasting’ days researching and writing an essay when the AI version will be as good or even better?

My question now is if AI is writing the work and AI is reading the work, do we even need to be there at all?

This whole profession never really recovered from powerpoint, this is just the nail in the coffin.

—Anonymous

The majority of the students learn nothing

Private computer science tutor

When the pandemic hit in the Spring of 2020, it was a catastrophe for students suddenly forced into remote learning, as professors were blindsided and desperately improvising… Begrudging acceptance of online education was indisputably bad for learning, but it did create demand for online tutors, and that has been my job since Covid.

The majority of students are behind on an assignment, and just want answers that will get them a decent grade. As a good tutor, my job was to try to redirect that desire toward actual learning, not just do their work for them. Then came the large language models. I got to watch some lower-performing students use them, and it was deeply concerning. They would type (or copy-paste) a description of the code they wanted into a coding environment, then accept whatever completion emerged so long as it compiled. If it did not, they would try again, with no ability to understand or correct the generated code. No learning took place.

This past year I have seen far fewer students, as the casual, lazy ones who just wanted a B-level answer can now often get one from a coding LLM, since homework problems are well-represented in the LLMs’ training sets. They don’t understand (or care) that the point of their assignments is not to create more solutions to homework problems, but to teach them fundamentals of programming and computer science, and there is no one there to gently correct them. The less mercenary students still look for tutoring, and they are more fun to work with, but they are a minority, and unfortunately there are not enough of them.

—Sean

My colleagues have abandoned their values to board the AI hype-train

Librarian at an R1 research university

It is pretty understood in my department that we are opposed to AI in the research process but as soon as we leave our office suite, we are met by many AI advocates. I actually signed up for this substack after I had a disagreement with a professor while I was in the middle of teaching a session for one of their classes and felt like I needed to learn more detailed information on the way AI works. I told students that ChatGPT is not a search engine, and while I was technically wrong in that it has web browsing capability, I was correct in that it is terrible. Unfortunately for me in that moment I have integrity and can say things like “I don’t know that for sure so I will cede that to you and look into it more.”

Pettiness aside:

I think the change is coming fast. Every day there are new conference presentations and papers on why librarians should be using AI and how they can do it. Academic librarians are guilty of always trying to “prove our worth” and get on board with every new trend regardless of whether or not we should. And in the case of AI we absolutely should not. It goes against the core values of the profession as stated by the American Library Association: “Access, Equity, Intellectual Freedom and Privacy, Public Good, and Sustainability.” It violates all of the tenets of the ACRL Frameworks for Information Literacy. It is shocking to me how fast some of my colleagues have abandoned their stated values to get on board the AI hype-train. I get a bitter taste in my mouth every time I think about the ones that were giving land acknowledgements (maybe still are) and now champion AI.

At my university AI is being pushed from the top down. Leadership has openly stated that workers who do not use AI will get left behind. If there is organized resistance on campus, I haven’t found it outside my department. I know that there are many in the profession who are opposed, however.

I am not sure if I can say specifically that it is changing the way that patrons are experiencing the library. I would not be surprised if it was, though. I do believe it is changing the way that patrons perform research and increasing the likelihood that they will be satisfied with “good enough” or even just “well, it’s something.” I have heard students defend the position that chatbots have access to 80% of the internet and are gaining more every day. I don’t know where this belief comes from other than well crafted propaganda?

But I do want my last point to be this: I don’t blame people, especially students, for using these tools when they don’t know better. We live in a hell world with increasingly limited time for ourselves. ChatGPT and LLMs like it claim to offer them some of that time back. The way that the bots “talk” to them is with a sense of sureness and like the bot is their friend. It doesn’t offer critique of what the user does, it doesn’t challenge them. And while those things might feel comforting, it is cheating them of real learning.

Teaching is a relational process. Student and teacher should both learn from one another and with that comes friction. LLMs will do anything possible to eliminate that relational friction to maintain the comfort of users. So, what’s more appealing? The librarian telling you no, or the chatbot giving you all the “answers?”

—Anonymous

AI training programs are failing student athletes

Assistant Strength and Conditioning coach at an NCAA Division-3 University

I currently work as a part-time, hourly wage, no benefits, assistant strength and conditioning (S&C) coach at an NCAA Division-3 university. My hiring as a part-time assistant already represents a reduction in staffing, at least partially due to AI use. I struggle to get even adequate part-time hours, which may result in the future elimination of the position or my inability to keep the position. This is largely due to direct and indirect effects from AI use.

We use a virtual training platform to deliver strength training programs to the university’s hundreds of student-athletes. This offers several ostensible positives. Ideally, we write training programs in the app that students can access on their smartphones, which includes short gif exercise demonstrations and allows them to enter training data. Streamlining training program delivery can allow us to spend more time coaching and interacting more meaningfully with athletes versus writing the program in Excel, emailing/printing it, and spending most of our contact time reminding athletes how to read it and what the exercises are. The app guidance can help students achieve the training on their own when away from our coaching for various unavoidable reasons.

The app also facilitates a lazier and labor-cutting approach with their range of semi-responsive AI training programs. Provide some demographic details, such as sport, primary competitive season, gender of athlete, beginner/advanced, and any specific equipment exclusions, and the AI will generate as mediocre of a training program as one would expect of such broad inputs and limited knowledge of the actual humans and environment. In the typical AI use case, this is better than literally nothing, and it can receive human intelligence tweaks to go from mediocre to adequate. There is no source info available as to how the AI designs the program, namely, what are the purported differences between sports, genders, beginner/advanced, etc. that they are using to program? A capable human coach would be responsible for answering these questions. I’ve made some comparisons between close options, say male/female or baseball/softball or women’s/men’s lacrosse and found either no differences or arbitrary changes that I would be unable to explain.

In reality, we do not use time saved by AI programming to spend more time coaching and interacting with athletes and colleagues. We do not actually see all athletes or teams. Several teams do not participate in S&C at all. These sports often have team accounts set up on the AI program, but don’t know about them or use them. Even if they did, the programs are so clearly inadequate that I can’t in good faith recommend that they use it without modification. Some athletes do S&C on their own individually, while some sport coaches handle it themselves without us. We’ve ceded this ground as a staff rather than use time saved from programming to develop relationships with coaches and athletes who don’t inherently engage with us. This especially includes athletes and teams who aren’t traditionally enthusiastic about S&C: more women’s teams, endurance or more “niche” sports, and sports with chronically poor win-loss records.

I build my own training programs in the app and use the app only as the delivery platform. This improves the quality of my training programs, because I’m writing them for the actual humans in front of me, in our actual shared environment, considering their actual sport and academic schedules, instead of the AI estimations of those key factors. I feel that my relationship with the athletes is better, as we’re talking about the training and I’m taking their feedback and we’re working with it together and we see each other’s collected invested efforts. I try to communicate with sports coaches on our shared teams, to mixed results. Some appreciate the collaboration and it has improved my work and deepened my relationship with the team. Others seem to wonder why I’m bothering them. A human-intelligence approach also increases my working hours so that I can actually get close to a full 20-hour week. I would have more like 5-10 hours of “floor time” (ie. in the gym with athletes) only if I followed the head coach’s example to only use prompt-and-tweak AI programming.

I have seen numerous instances of poor quality training due to our use of the AI programs. Here are a few significant examples:

• The AI programs are automatically set up to change exercises every 4 weeks. One team changed exercises during the week of their conference championship semi-final game. Sore legs were had by all, as changing exercises is known to increase muscle soreness and the new exercises were more intense. They played the semi-final that weekend to a highly fatiguing overtime win and then lost in the final on the following weekend.

• The AI calendar follows pre-established program pathways from one physical focus quality to the next (eg. muscle size, strength, power, etc.). This resulted in one team doing a maximum strength phase (heavy weights, slow speed, high fatigue) during the final weeks of their competitive season, unadjusted for their game schedule. Many athletes simply did not follow the program.

• The AI only sets a single competitive season, so it’s immediately inappropriate to use for athletes who have two competitive seasons over a year. Some sports have a split season of both fall and spring competition, either equally weighted or with one slightly prioritized over the other. Athletes on at least one team did high-fatigue hypertrophy (muscle-gaining) training during their spring in-season phase of faster pace, lighter bodyweight, more readiness-dependent performance demands.

Athletes often no-show to sessions with the provided reason that they can do it on their own with the app. Coaches often cancel sessions for the same reason. Even if following an app was a direct substitute for in-person participation with qualified staff, this reduces our role to “programmers” instead of teachers. Of course, as a staff we aren’t even “programming” because the AI program is.

Cutting in-person time eliminates our ability to provide actual instruction of physical movement, develop relationships, and create a quality team training environment. We know that these factors are actually what improve training outcomes, creates a rewarding athlete experience, and benefits life beyond immediate sport performance, not toiling away in isolation guided by an app. Session cancellations, reduced attendance, and low communication also reduce my enjoyment of the job, working hours, and income.

—Anonymous

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AI is causing the most damage in student learning and skill development

Academic

I’m an academic. I work in the UK but I spent a decade in higher education in the US and was tenured before moving across the Atlantic. I didn’t have a lot of AI to deal with before my current role, obviously ChatGPT kind of started this trend.

Firstly, MetaAI has stolen every last thing I’ve ever published. Academic publishing doesn’t bring in a lot of money. My book royalties are 2-5% and my articles bring in nothing other than prestige (whatever that is). Academic journals, I should add, are very expensive to access as you may already know. I see nothing from that of course, it’s essentially free labor that my institution sort of expects me to complete but only in vague terms. Certainly if I don’t publish, I may “perish”, to borrow an academic turn of phrase.

In the classroom, student attendance is sporadic at best. In many cases this is because they no longer “have to” show up to class to pick up the material. It’s required to be posted online (again this could be made available to AI training, the material posted technically belongs to the institution), and also they don’t really need to learn anything to do their final papers. Here is where I think AI is causing the most damage: student learning and skill development.

I begin every new class with a whole spiel about learning how to do research and how to communicate research findings. I try to reason with them that they need these skills; simply using AI means they fail themselves even if they manage to pass the class. Their future boss is not going to pay them salary to input prompts to AI and email or print off the output. It never fully gets through. Now we see university leaders, clueless as to how to fight back against the deskilling that has further undermined the concept of higher learning, setting up degree programs in “such and such with AI”. Buzz word loaded plans are shared institutionally without anyone ever asking why. Ironically, one area where AI might do a sufficiently mediocre job is in university management, perhaps turning those meetings that could have been an email into actual emails.

It’s aggravating. I can’t even imagine how bad this is going to get before it gets better. If it does.

—Andrew

Bosses are rushing to use AI to implement “unstaffed opening hours” at public libraries and to deskill school librarians

I’m a library worker and union organizer, working at a public library service in Melbourne Australia. My job at the library is running tech help workshops, but on the side I organize my workplace and organize with other union activists across public libraries in my state.

I thought you might be interested in one of the specific applications of AI in libraries. While this hasn’t led to any significant job less yet, I think it points to the future of the sector. There are two twin technological threats currently facing public libraries in Australia and around the world, and both of these seek to replace (unionised) library workers. This is on top of a culture war on libraries and library workers with the fascist transphobes attacking public libraries for running drag storytime events or even just having queer books in the collection.

In Melbourne there is a rush by bosses to implement unstaffed opening hours at public libraries. While this hasn’t led to a reduce in staffed opening hours yet, once the technology is introduced it can and will be used to replace staff hours as funding gets cut. In addition to the threat of unstaffed libraries, the introduction of an ‘AI’ chatbot to school libraries is directly threatening the jobs of skilled librarians. Called “Book Bot” by Huey, this chatbot housed in an iPad with cutesy trimmings replaces the job of a librarian in helping kids to find appropriate books to read. The company is advertising it as a solution to underfunding and understaffing in schools.

Ironically this private company has received government funding to do this. While Huey’s Book Bot hasn’t been introduced to public libraries yet to my knowledge, taken with the technology of unstaffed library access there is a clear threat to public libraries and all of us who work in the sector.

—Taichen

[Editor’s note: Taichen also shared two briefing documents they’d put together with coworkers; one on AI chatbots in libraries, and another on unstaffed libraries, aimed at educating other library workers. I’m sharing them here.]

Teaching has become a bullshit job

Programming instructor at a community college

I now teach programming online at a community college where I spend most of my time trying to detect cheaters and fake accounts. There’s a whole racket around state and federal scholarships paying nonexistent students. AI facilitates the process of creating profiles and pretending to take classes.

Almost every faculty meeting is about training us teachers how to teach students to use AI rather than helping us teach students how to think and learn and write. Even teaching has become a bullshit job.

I may be able to turn it around for some of my students by showing them how they can build text adventure games and then automate the playing of their text adventure games with AI. But only the most disciplined students (and those without the time constraints of working bullshit jobs to pay off their education debt) will get much out of my course. An English teacher colleague was able to buck the trend and was able to shame his students into writing thoughtful essays. But it takes a lot of effort and skill that isn’t being taught to overworked teachers.

Universities are worse. Much of the funding for Social Media and AI impact research in psychology, sociology, computer science, etc, chins from big tech and most papers do not even critically question whether AI is reasoning at all, or the ethics and safety of teaching and using it. Lost in the noise are the authentic voices of Timbit Gebru, Melanie Mitchel, even Gary Marcus and the few impactful researchers questioning the inevitability of AI as a tool for hyper capitalism, fascism, and genocide. It’s like Hitler discovered the nuclear bomb before the US did. And now fascism is mainstream, almost unquestioned, inevitable. It’s not the power of AI so much as the power of technology to shape minds -- the capture of all sources of media and information and art. It’s just 1984, exactly as Reagan dreamed and Orwell feared. Fiction and art and news are no longer consumed as warnings coming from authentic smart human voices, they are just entertainment, brainwashing tools. And artists and teachers and workers have no alternative but to participate in the ponzi scheme or starve.

—Anonymous

AI Killed my job grading student essays

Grader

One of the first jobs I got out of college (2008, recession era) was grading student essays for standardized tests. Cool job, lots of retired teachers did it. We sat in a huge room for a few months, maybe 45-60 people, and scored every essay written by fifth graders in a state a few states away from where we were, based on pretty specific criteria. Just a temp job, to be clear.

Years later, this was a job I did during COVID, something that could be done remotely. But now the training, done online, only had 8-12 people in it, with some people flunking out of that training, and the work itself was scheduled only to last a few weeks. I learned that most of this essay grading was done by AI, and we were only getting the papers AI couldn’t quite handle.

—Brian Nicholson

The AI evangelists are tough to fight with

“Tech guy” working in a school system

I’m not a teacher but I am a “tech guy” in a school system. We’ve taken a very slow and steady approach with it, banning its use in all but very specific cases, and requiring teachers to define how they’ll be used. But there are students who use it without any regard for the right or wrong of it.

But what has frustrated me most about it is the teachers trying to push for more AI access. They want to use it as 1) AI detectors, and no amount of “that doesn’t work” has convinced them. Or 2) to grade and summarize papers.

And it drives me crazy when I say “does the student’s work differ significantly from their previous work?” they look at me like I have six heads. Like thinking about whether the student’s most recent paper reads like a “written-by-HR” ass document is a huge ask.

And as for point 2, there comes a time when I have to look at them and say “if the students are writing papers with AI, and you’re summarizing the papers with AI, then why are any of us in this building.”

To be clear, most of these folks are decent and only want the very minimal AI intrusion in their classrooms. But the few that are loudly in favor are driving me up a wall.

Like I said, most of the teachers (and students!) either want little to do with AI stuff, or just the barest minimum of streamlining a process they have difficulty with. And, for instance, our Special Ed folks are looking for uses of the tech that will help their students fill the needs they have. It’s noble for the most part, and I appreciate that they’re willing to listen to feedback and really talk through these things.

But the evangelists are tough to fight with. No amount of “these companies are hoovering up data” and “we have both legal and moral obligations to protect our students’ privacy” convinces them, even when we point out that they are not FERPA or COPPA compliant.

—B-rad

My team of education workers has been cut in half

Team manager at an edtech company

My current job is as a team manager at a small private education adjacent tech company where we’ve seen traffic steadily decline because LLMs can do what we do (even if it is more expensive, less reliable, and wrong more often than not).

To try to find our place in this new world, over the last year, we’ve seen a transition away from our normal creative and fulfilling development work towards generating massive datasets that we’ve sold off as “training data” for LLMs to many of the big tech companies, under the guise of getting them better at math and reasoning.

This work is often mind numbing and demoralizing and especially demeaning to have creative programmers turn out rote, repetitive work like this. Worse than the generation is the QA sweep (that devs got looped in on) of manually looking over these massive datasets to do a quality pass.

Moreover, while this project was sold to me as being a deal so lucrative that it would set us up for the next few years, and let us hire new developers, but once we finally got paid, it only just brought the budget back to zero. So it increasingly seems like this is the future of my work and this company.

We had one round of layoffs last year when these projects started that my team luckily avoided. However, I was just told that more layoffs are coming. I know several good developers who are looking for work elsewhere, but the tech industry as a whole seems to be on a bit of a hiring freeze, and many of us have health insurance needs or families to support that makes simply walking away a terrifying choice.

[We followed up with the contributor to see what’s changed since they wrote to us six months ago. They had this to say:]

My team has literally been cut in half since my last message. Some were let go, some reassigned to different departments, and some quit seeing the writing on the wall. One person was let go on the spot via email because they were having trouble with their pc, and the company decided to end their contract on the spot rather than help them debug the technical issue.

My company, at least my corner of it, creates k-12 and collegiate math and science education material. My team helped create dynamic and visual aids, and homework-helping walkthroughs to solve problems in math and science. These are used some in classrooms, but mostly by students doing homework. A lot of my team are former teachers and educators who find this work engaging and satisfying - they feel they are still contributing to the education of the next generation, just in a more indirect way than teaching. My favorite feedback I hear from people in the wild when they find out where I work is some variation of “Thanks for getting me through high school math!”

Gen AI has not replaced this work, but because sites like ChatGPT can do most of what we can do without manual development work, our internal priorities have shifted away from creating these programs towards other efforts. The few of us who remain are instead tasked with figuring out how to best integrate LLM technology into our already existing tools and functions. This involves building the runway as the plane is taking off - creating the tools we need to use, as we are using them.

Multiple people have had their future contracts tied to specific LLM-related projects, and I’ve been told in not so many words, that if the project fails, these people are gone. But without any clear roadmap or direction, let alone documentation for how to do such integration, I feel like they are being set up to fail. The deadlines for these are fast approaching, and hopefully what we’ve cobbled together will be acceptable, but even if they are, they will still be LLM-powered features, and thus have the same inaccuracy and inconsistency problems that plague all LLM projects. It would be embarrassing to release something that can be so incorrect at times, when this company is known for mathematical accuracy. It’d be like if your pocket calculator occasionally returned 2+2=5.

—Anonymous

Gen AI Edtech platforms “lovebombed” my client and then my contract was up

Edtech contractor

The last two years have been hell because working in tech education, you are fighting to make [clients] understand the risks and harms, and they all think they can just use a gen ai LMS to make the trainings that you make. We are increasingly seen as disposable, especially as women. I notice men in tech aren’t losing money making training, but we are. But that’s another story.

I had a contract up until this month to make IT trainings for an educational setting. I lost the role because they got love bombed, basically, by two large gen ai edtech platforms. All these promises of productivity and ease of content creation etc. It won’t work out for them long term but they don’t see that. Anyway, part of the sales pitch was how the gen ai can make training on policy and other tech areas—which was my job. They are so sold on this that they ended my 6 month probation with “we don’t see the trial as working”. I made incredible material for them, and worked in small groups and individually with staff on how to use the IT. Some of them had never used Word or Outlook before. They will now have terrible mandatory training too, full of errors and stolen work, but it will be generated in minutes. No one will proofread it or think like I do about the language, the accessibility. They just want easy quick work. And the saddest thing is they won’t even save money as they are paying the Twitter and TikTok influencers who work with these platforms TWICE what they paid me in one month to come and “train staff”.

—Michelle

The hiring committee requires applicants that would incorporate Copilot in their workflows. I didn’t get the job.

Teaching Fellow

I applied for a role as a “Ethics and Regulatory Coordinator” at the University of Auckland a few weeks back. the role seemed to require the applicant to act as a go-between for researchers making applications, committee members making decisions on what kind of research they’ll allow, and the university bureaucracy itself. The detailed job description includes a point about applicants being familiar with Microsoft Office, Including Copilot. As a final piece of background, ethics applications at UoA have been taking a while and some researchers have been frustrated with long wait times and inconsistent feedback from committees, while the committee is apparently sick of dealing with poor-quality research applications that require a lot of remedial work.

At the job interview, I was asked about my familiarity with using Copilot to create efficiency solutions in the Office. I gave a measured answer where I noted the usefulness of AI tools when summarizing spreadsheets and creating templates etc but said I didn’t trust Microsoft’s claim about data being separate and also stated I didn’t think we should use LLMs in decision-making or communications (email summaries and responses etc) for research ethics.

It took an unusually long time to hear back about their hiring decision, I had to email the relevant HR person to ask if something had happened. When I did get a call, I was told that they appreciated my experience with research design and ethics etc but they needed to find someone who was comfortable with incorporating Copilot into the ethics process and experienced with doing so.

—Benjamin Richardson

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This installment of AI Killed My Job was was made possible in part by support from the Omidyar Network’s Tech Journalism Fund.

So what is the relationship between men creating AI products and their drive for sex, power, dominion? It’s a question that has been unsatisfactorily explored during the years of the AI boom so far, with a few exceptions. But with Grok’s nonconsensual image generator making headlines, as it’s being used, for example, to undress women against their will, and concerns about the safety of AI generated content at an all time high, I thought it worth revisiting a speculative fiction story I edited for Terraform back in 2018, that tackled how misogyny and predation infect the tech world.

Emily J. Smith is a fiction writer and tech worker. She founded the dating app Chorus, and has a wealth of experience with Silicon Valley and the men who inhabit it. Her first novel, Nothing Serious, was published last year by HarperCollins, and she pens a newsletter called Unresolving. Her story, about a tech developer behind an Alexa-like home AI, was one of the most popular we published at Terraform, many years before ChatGPT or Grok existed.

It’s a stark interrogation of what lies behind the female-coded voices and imagery of AI products, as well as a horrifying depiction of sexual violence in tech—do be forewarned, this story contains depictions of assault—as well as a subtle nod towards what might begin to address men’s dominance in the industry. It quickly went viral on Reddit and beyond. Smith has kindly given me permission to republish the piece here, where I think you’ll find it remains plenty resonant. The art is by the incomparable Zoe van Dijk. Enjoy.

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Warning Signs

Roy unlocked his door at 7:35 each night, threw his jacket on his long, grey midcentury couch and slipped his leather shoes off. Most days the argyle on his socks matched, but not always. Today they were both grey with pale pink accents.

“Lucy,” Roy shouted from across the room. “Turn on fucking NPR.”

“Turning on KQED FM Public Radio from Tune In,” Lucy repeated back from its perch on Roy’s oak shelf. The shelves ran from floor to ceiling. It was a nice detail, his realtor had told him, and he’d agreed. But now they just reminded him how little he had to put on them. He had a few old coding books, a new book on “deep thinking,” a short one on meditation, and then, on the top shelf, a teddy bear that an ex-girlfriend had loved and he thought other girls might, too, so he’d bought it at an LA gas station forever ago.

Roy slumped on the couch. The two cushions sloped downwards towards the center, where he sat, tonight and always, just slightly. His butt covered the grease stain from the night the Pad Thai had slipped from his fork—he had wanted every ingredient on the fork and there were so many ingredients in Pad Thai—so he didn’t have to look at it.

“Lucy,” Roy said, his voice softer now.
“You fucking bitch.”
“What was that?” Lucy asked, her voice soft and predictable.
“You’re a fucking bitch,” Roy mumbled and then laughed, just a little at first and then more, because the ease at which he could tell this thing that did whatever he said that she was a fucking bitch was funny, and surprisingly fun.
“I don’t register that,” Lucy said, her blue ring of light blinking steadily.
“Cause you’re a stupid whore,” Roy whispered, still laughing, almost giggling now at the freedom of not being policed. These days every conversation he had felt more like a trap than an exchange.

Roy turned on the TV. The only good thing about Mondays was that he saved Westworld for Mondays.

“Lucy!” Roy screamed and the bang of his voice in his quiet apartment made him jump. Like massaging your own shoulders or scratching your own back, it wasn’t ideal, scaring oneself, but it was better than nothing. “Turn on Westworld.”

“Playing Westworld.” The calm hum of NPR stopped and Westworld appeared on the screen. “And order from Samurai Sushi, please.”

“Would you like the same order as last time?” Lucy began repeating his order.
“I get the same thing every time you piece of shit,” he interrupted.
“What was that?”

He leaned forward on the couch so she could hear him. “Yes, baby. Yes please order the same thing.”

“Ordering from Samurai Sushi.”
“Thanks babe,” he grinned and laid back down into his thick grey cushions.

Westworld had become a total drag so he started swiping Tinder instead. Swiping had become a reflex in the face of idleness, he barely registered that he had opened the app at all and already he was getting matches. He swiped when he got up in the morning and as he fell asleep—a modern counting of sheep. He swiped it on the toilet and even sometimes not on the toilet, just a swipe or two while he peed.

Roy was the perfect age for a man and he knew it. At thirty-six he could be in a relationship with any woman. Younger women adored that he had an apartment all to himself, but he still more or less hadn’t changed in a decade besides Acroli going public and him becoming a millionaire so he got along with them just fine. Older women, too, were in his wheelhouse. By the time a woman hit forty she was over the age thing, her options too slim to be picky. The only women he hated dating, although of course he could if he wanted to (they were everywhere in SF), were women his own age. Thirty-five started the last sprint of a woman’s child bearing years and the girls in San Francisco—an army of less successful Sheryl Sandberg prototypes—didn’t take that lightly. With women his own age he felt rushed, demanded of. And that was no fun.

Looks-wise, he had thick hair, so he was fine. He hadn’t realized it until a few years ago, but thick hair masked almost all the visual imperfections on his face, which he admitted were many.

He had a good job at a well-known tech company, which was exactly how he phrased it on his profile. And he was in shape, enough for a man his age. “Dad Bod” had become a phrase right when he’d entered his thirties which luckily was right when he’d developed his dad bod. It’s not that he didn’t exercise. Roy ran 3 miles two days a week and every Saturday he would do a two-hour bike ride in Marin, unless something got in the way, like a picnic in the park or a hangover.

He did wish he were taller. He was 5’9 and a half, basically 5’10, which is what he put on the profiles that asked. But Tinder didn’t ask so he left it blank. If a woman cared about height, he reasoned, she was superficial anyway.

Roy swiped “yes” to almost every girl on Tinder except if they were ugly. He’d run an experiment and based on the number of times girls matched with him (1 in 9, on average) it was a waste of his time to consider a girl unless it was clear she wanted him first.

After three matches he stopped swiping and scanned the profiles of his matches. The first one was fine but her last pic had her smiling and one of her teeth stuck out making her look like a goof so he unmatched her. The second girl had only shown a picture of her face in the first picture, which was pretty, but the second had a picture of her body and clearly she didn’t value health the way Roy valued health so he unmatched her before he had a chance to read her message asking if he wanted to go for a bike ride.

But the third showed promise. Michelle was 31 and 5’6, the perfect age and the perfect height. She had thick, straight hair, which wasn’t a must-have, necessarily, but it was certainly nice. She smiled in every picture, a wide, inviting smile. She had a fine sounding job as a Project Manager and went to a college he had heard of. He messaged “ Hey.”

This wasn’t his best work but it was usually good enough. He had a feeling it would be good enough for Michelle.

Michelle’s laugh was generous and she filled the gaps in conversation with thoughtful questions about his life. She was indeed impressed that he owned an apartment in San Francisco and she joked that she wished she could see it. This was a wish he knew well and one he was practiced at granting.

“Lucy,” Roy said when they entered. “I have a guest.”

Michelle laughed at how friendly he was with his device. He was cute, she thought, cute enough. Michelle had spent the good portion of a year chasing after a photographer in Oakland who wrote her poems but never returned her texts. She wanted something simple, a nice guy who would treat her well. She wasn’t getting any younger her mom had started reminding her every weekend since she’d turned thirty. She knew she was more attractive than Roy and that was intentional, a turn on, even. Him wanting her made her want him. It meant he would stay.

“I work at Acroli,” Roy explained, taking her coat. “So I have to be nice to her,” he smiled.

“Do you work on Lucy?” she asked looking at the device.

Roy nodded. “I was one of the first engineers on Lucy, actually.” This reveal was his favorite part of dates. “I got to pick her voice. Oh, and I sat on the naming committee,” he said as if he’d just remembered it.

“So cool.” Her eyes widened, like they all did when he told a girl this, and he noticed her take a second scan of the apartment, sizing up his belongings, his wealth, in light of these new details.

“Lucy,” Roy said.

The blue lights glowed and flickered.

“Please play us some romantic music.”
“You’re so nice to Lucy,” Michelle laughed.
“Not always,” Lucy said. It was so soft and quick that both Michelle and Roy thought maybe it was just in their heads.
“What’d she just say?” Michelle looked at Roy who was now gripping Lucy tightly. He put it down when he saw Michelle staring at him, but his eyes jerked around the room. She had noticed this at the restaurant, his eyes darting from the food to the floor and up at every single person that passed their table, but she was really trying to be less critical and the way someone moved their eyes wasn’t a good criteria to judge a guy on, she told herself every time she looked up.

“Lucy,” Roy said, calmly now. “I asked you to please play us romantic music.”
“Playing romantic music for your guest,” Lucy replied.
Michelle registered this somewhere in the far corner of her mind, too, the specification “for your guest.” Hers never did that. But then the new Bon Iver came on and Roy’s hands were on her waist and the last thing she remembered was Roy handing her a drink.

There was a mandatory team meeting at lunch. He took a seat as far as possible from the front of the room, at the back head of the long conference table. A woman walked in. She wasn’t ugly, Roy thought. But she wasn’t hot. She was older than he would have liked, around his age, but he would sleep with her. She wore a button down shirt, tighter around her breast area, which she tucked into tight fitting jeans. She had makeup on, he could tell by the lines of her blush and the red of her lips and he thought it made her look like she was trying too hard. Her expression was serious—wrinkles on her forehead, her lips clenched into a tight knot—uptight. He wished someone would get her a beer from the tap on the 3 rd floor so whatever was about to happen would be more fun.

“Hi everyone,” she started. “I’m Dawn. I’ll be leading a new initiative with Lucy. “

Of course it was all men. For the most part they were fine. But the guy in the back was menacing.

Dawn had spent the morning—not to mention all week—preparing for the presentation, doing a power-pose in the bathroom stall when she got in, then pretending she was on a conference call for two hours so she could practice her speech in secret. But when she walked in, smile ready, endorphins racing, she saw him scowling at her from the far end of the room, eyes narrowed, at her face for a second, then her breasts—she could see his eyes move downwards—and then at her jeans, which she only in that moment realized were very tight (but tight was the style!) before moving back up to her face. But by that time her smile was gone. She was done with smiles.

He threw his clothes and shoes in the corner of his closet and all the takeout containers and beer cans into a black garbage bag. Another date, Sarah from Bumble, was on her way over. Michelle had already messaged twice since this morning and the whole thing made him feel like someone was gripping his soul and shoving it into a juicer so he unmatched her in the Uber on his way home. Thankfully, he hadn’t given her his number.

“Bitch.” He stared at Lucy and smiled, waiting, but Lucy just sat there. “Lucy,” he said, finally.

The blue lights turned on, blinking faster than usual again, at least it seemed.

“Order me vodka from Harry’s. And whiskey. And play that music we like. Play our music.” Roy was laughing now.

The whiskey and vodka thankfully arrived just moments before Sarah did. But the sushi was still on its way. Sarah sat on the couch.

“Fiona Apple,” interesting choice, she said looking up at the air as if Fiona Apple herself was floating in the room.

Roy looked at Lucy, unassuming on the shelf. He knew little about Fiona Apple other than a vague recollection that she was a feminist psychopath. What he did know was that she was definitely not on his “romantic” playlist.

“I like it,” Sarah said, pulling her knees up to her chest, bouncing a bit.

Roy could feel the blood drain from his face, turning whiter with each heavy piano chord.

“Lucy,” he said with measured effort, “shut off.”

But Lucy played another song, his favorite song this time. When the Coldplay song ended he braced himself for what would come on next. He wasn’t sure who it was but the voice was a woman, and she sounded angry. Sarah was bouncing again. He got up. “Lucy turn on better music,” he shouted.

“I’m putting on music for your guest,” it replied.

Sarah turned. “How does she know you have a guest?”

Roy had no fucking idea and frankly it was creeping him out. “I work at Acroli,” he explained, trying to pivot this disaster into something positive. “On Lucy. So mine is a little more advanced than most people’s.” This was true. They tested updates on employees before they were released to the public. But he hadn’t heard about any planned updates. “Actually, let’s just unplug her. We don’t need music.”

“Sushi is arriving in eight minutes,” Lucy said, glowing.

Roy stopped, hand resting on the chord. If he unplugged her, the sushi might not come.

Sarah laughed. “That’s so cool. Like she knew what you were doing. I can’t wait till they release this for everyone.”

Roy stared at Lucy, which was still glowing on the shelf even though she had stopped talking or listening at this point, as if she were simply gloating, glowing for herself alone, and went back to the couch to pour another shot for him and the girl.

Music began to play.

“Thank you Lucy,” Sarah said, still giddy.
“Keeping you safe,” Lucy said, stopping the music for an almost imperceptible second before continuing the tune.

Roy stared at Lucy, and Sarah stared at Roy, who was entirely focused on the soft blue glow. She watched his face redden and his eyes harden. She could even see, though only faintly, the beat of his pulse pumping in his neck.

As if a glass had shattered on the floor the sound of the door buzzing made the jump. He ran to the door, grateful for a break to compose himself before returning to the girl.

Roy got to work early. Ten a.m. on the dot. Dawn was the only one there.

“I’d like to work on the new update for Lucy,” Roy said, looking down at Dawn, lazily sitting, rather than standing, at her desk.

Dawn did everything she could to keep herself from laughing. She took a sip of her water bottle, which was nearly finished after this morning’s six-mile run.

She shrugged. Her instinct was to start with “Sorry,” but while she hated the new craze of every woman telling every other woman to stop apologizing—women shouldn’t have to stop, men should do it more—she truly did feel, in this case, that an apology was completely unnecessary.

“You can’t,” she said instead. “It’s fully staffed.” For all the hype, she hated open-office workspaces. She would have taken a 10% pay cut just to have a door to close on men like the one still staring at her.

“It’s a confidential project,” she said so that he’d leave. “You have your own important work to do.” She tried, but not too hard, to hide her condescension.

He was pretty sure he had never met a bigger bitch. He fully intended to stay at her desk until she told him something.

“Internally we’re referring to it as Project XX,” she said. “I’ll tell you that.”

“Project XX.” Roy raised his eyebrows. “Sounds dirty,” he said with a short, lazy laugh. He knew it was dumb and crude before the words had even left his mouth but he wanted to see her squirm. She smiled at his desperation, nearly laughed. As he walked back to his desk she noticed the unfortunate fit of his jeans. She opened her file of select employees, making sure he had received the update.

Lea was wearing a low cut shirt showing off nothing but her collarbone but it didn’t look bad. He had setup Monopoly, which was why she’d agreed to come to his place on a first date, something she never did, she made sure to clarify. He placed the bar-cart next to the table.

Lea didn’t actually find this guy—what was his name, she checked quickly in the hall before she’d reached the door, Roy—that attractive. He was short and had an ugly face. But he seemed to have a decent job and a good education and she knew those were superficial markers but it was all superficial on these apps—what else did she have to go off of?—so she swiped right and then he’d messaged her and asked her to come over, tonight, and more than anything she just wanted someone to talk to.

His place was nice, beyond nice, but the shelves were bare and he had just enough furniture for him to sit on, nothing more. There was a creepy teddy bear on the shelf that looked completely out of place like a piece of bait thrown sloppily on a hook.

Roy asked what she wanted to drink and even though he was pointing to his liquor cart, the girl asked for a beer.

“How was your day?” Lea asked from the couch.

“Work is annoying these days,” Roy said, handing her a beer and making himself a drink. “I don’t want to talk about it.”

She waited for him to return the question—today’s case had been a nightmare—but he was too focused on the whiskey he was mixing for himself. He took a large sip and sat beside her on the couch.

“I like this shirt,” he said, touching her low cut collar.
“Thanks,” she said, her heart beating a little faster.
“I was thinking we could make a drinking game out of it,” he said, gesturing to the Monopoly board. Lea started to say that she’d had a long day and really, definitely couldn’t be hungover tomorrow, but as soon the words left her mouth she saw his expression darken, it wasn’t anger, she could fight anger with anger—she was a lawyer, did it for a living—it was more like confusion. The care to which he’d setup the game and the drinks, dimmed the lights, and played romantic music (no matter how cheesy) was touching and she had disappointed enough people today, she didn’t need his sadness piled on top. So when she landed on a Railroad and he poured her a shot, she took it.

The game was the only interesting part of the evening. The girl wouldn’t stop talking about her job, which for some reason reminded him of Dawn, and even though he tried his best to seem like he didn’t care (it wasn’t that hard), it was almost like she had one-upped him and didn’t care about him not caring, so kept on talking. But she was also drinking, quite a lot, and seemed to like him, enough, so as soon as she purchased Boardwalk he crawled on top of her.

At first she laughed. “What are you doing?” She tried to push him off but he’d put up with her for two whole hours, drinking all his beer and ranting on like he was her personal therapist so what did she expect?

“It’s fine,” he said. “We’ll go slow.”
“Stop,” she said. “I don’t want to do this.”
“Why not?” he asked, rubbing her hard stomach under her shirt and keeping her down. “I thought we were having fun.”
“Stop!” she said again, louder.

He had to work to keep himself from laughing. He was shocked at how much he enjoyed it, this push and pull. He unzipped her pants with one quick pull.

He was about to go in for another kiss when he saw it through the corner of his eye. The blue lights blinking faster than ever, he was sure of it. But he had given no command—the music still played, the lights were still dim, nothing had changed.

The girl was screaming now, ridiculously—he had only really touched her breast and was just starting to unbutton his pants. The blinking kept going—faster, brighter. He heard it faintly at first, maybe part of the song, he thought, a ringing hiding behind the music. Then he noticed, through the corner of his eye, more lights, more blinking. Red.

The sirens were louder now, the lights brighter.

There was a pounding at the door. Hard, heavy knocks.

“Police,” a man shouted. “We received a call. Let us in.”

More BITM fiction:

Busy, by Omar El Akkad:

Flyover Country, by Tim Maughan:

And yes, this film is blunt. Critical reaction has been all over the map, as far as I can tell, with some finding it too moralizing and grimly familiar, and others praising those same qualities. It hasn’t exactly been a box office smash, either. But it does make me want to ask: What do we want in a relentlessly AI critical work of pop art like this? What works, what doesn’t?

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In fact, I’m going to argue that not only is the left not “missing out” on AI, but that it would be more accurate to say that it is “currently winning the debate” over AI in American hearts and minds. Polls routinely show that Americans are more concerned than enthusiastic about AI. Coalitions are organizing opposition to data centers across the country, often successfully. Where they have been proposed, in states like New York, Colorado, and California, laws to regulate or rein in AI have found majority support. When actors and screenwriters went on strike in 2023, and foregrounding a demand to stop executives from using AI to undermine their jobs, they were widely cheered. And so on.

Much of this is driven by left-liberal critique of AI systems: Of the impact AI would have on labor when administered by management (the union-led screen actor and writer strikes, California’s No Robo Bosses Act), of the resource and energy costs of data centers (articulated by progressive environmental groups), of the practice of nonconsensually exploiting works in training models (shouted from the rooftops by leftist artists like Molly Crabapple from the first days of Midjourney), and so on. Left-liberals can’t claim full credit for the concern piece—the AI CEOs themselves have been doing their best to ensure everyone knows they intend to automate the world’s jobs and think that there’s a chance they might create Skynet in the process.

In fact, the left appears to be so successfully engaged in matters related to AI that one can’t help but wonder if allegations about its supposed ignorance of the technology are motivated by a desire to change the very terms of the debate.

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To wit: The Kagan-Kans piece articulates a position that I think is pretty widely shared, especially among AI industry folks, centrist pundits, and anyone who might command a speaking fee for having tough but sensible opinions about AI. I’m not going to spend a lot of time rebutting it line by line—Gita Jackson handled much of that task over at Aftermath—though I did find its argument underwhelming and somewhat confused. (Kagan-Kans never really seems certain as to what he wants to describe as “the left”, for one thing. Most of the piece is dedicated to critiquing the work of linguist Emily Bender, and the only person on the left Kagan-Kans interviews is Matt Bruenig, who argues… the left should use more AI.)

Briefly reconstructed, that argument basically goes like this: Bender and her coauthors of the famous stochastic parrots paper posited that AI is not really intelligent, it’s a next-token prediction machine. “The left” has metabolized this conception of AI, and uses it as an excuse to write off AI’s import, which is growing by the day. (In one puzzling section, the author compares those who discount the true power of AI to climate deniers.) This in turn means “the left” will miss out on a political opportunity to be “first in line” and thus the chance “to set all the rules for discussion and debate about it,” according to the source Kagan-Kans quotes to advance that claim: the chief futurist of OpenAI.

Now, I personally would not look to the “chief futurist” of OpenAI for my understanding of political science, for starters. Being “first” to a debate does not to my knowledge necessarily translate to policy influence. Power does, though. Since Kagan-Kans likes climate change metaphors, here’s an example: In the 1990s, climate scientists presented the case that greenhouse gases were warming the atmosphere to Congress, and for a time it seemed like federal legislative action was probable. Then, during the Bush administration, when action that would injure the interests of the oil industry seemed imminent, Republicans adopted a concerted political strategy of climate denial, as dictated by the infamous Frank Luntz memo—and sure enough, the party was able to reset the terms of the debate, years later.

Furthermore, I think it’s strictly counterfactual to argue, as Kagan-Kans does, that the left is missing out on a chance to play a role in policymaking over AI guardrails. If anything, left-liberals are trying to pass laws that do exactly that, especially on the state level, and the right is trying to crush them. Dozens of state bills, backed by unions and progressive organizations like TechEquity, have been proposed and passed already, covering everything from labor impacts to surveillance to identity protection and child safety. Meanwhile, the Trump right is working to put a moratorium on state level AI lawmaking altogether—a move that’s profoundly unpopular among Americans and the electorate, and that many on the left have called out as dangerous and wrong. It’s yet another point where left-liberals appear to be winning the public opinion in the AI debate.

But I know that’s not what most pundits mean when they say the left is missing out on AI. What they are saying instead, is that the left doesn’t see AI the way I and my cohort do, as a transformational force that will remake the world and its institutions.

That’s where Bender comes in. I think many in the AI industry have been particularly angered by Bender’s depiction of AI as a stochastic parrot—more than they have by other criticisms—because it seems to demean their project on a structural level. If someone believes they’re building a powerful super intelligence, I’m sure it feels insulting to have someone call it fancy autocomplete. I also know there are even critical tech writers who chafe at Bender’s formulation and its persistence; who argue it has had the effect of limiting folks’ understanding of what AI models are capable of. I see the primary thrust of her work as grounding claims and hype about AI in the fact that they are statistical language modeling machines. To me, that doesn’t diminish the notion that those models can be complex or powerful or capable of impressive things; it just underscores their materiality as programmed systems, and perhaps helps limit the purchase of industry-benefitting visions of artificial sentience.

Regardless, a core part of the ‘left doesn’t get AI’ line comes from an assumption that Bender’s parrot formulation has become its default position. And where does that assumption come from? Kagan-Kans cites a handful of articles out of the thousands written about AI, but I think I know where the true root lies. It is at this point that I stand up for one of the most denigrated populations on the entire internet, Bluesky users. I think a lot of the tech world’s conception of what constitutes “the left” seems to be drawn from scanning Bluesky. AI evangelists on X see users there calling AI “the plagiarism machine” or “nothing but autocomplete” and assume their knowledge of the technology tapers off at where the state of the art was in 2023. (To be fair, Bluesky users do the reverse to AI boosters on X.) But just because someone calls AI a “plagiarism machine” doesn’t mean they don’t have any further understanding of the technology. One may think it a corny, reductive way to describe AI, or to articulate a rejection of it, but much in the way you wouldn’t assume a user who posts “orange man bad” hasn’t been following the latest Trump news, it just doesn’t follow to assume that’s the limit of someone’s understanding of the topic.

I would wager, in fact, that the most common left-liberal position is not that generative AI is just a stochastic parrot, but a product built by powerful profit-seeking firms that’s capable of serious harms. It’s not a semantic or philosophical critique the AI industry should be worried about, in other words, but a material one. AI is viewed, correctly, as a threat to jobs, education, mental wellbeing, the arts, child safety, the information ecosystem, and as possessing little upside for few others then corporate managers and AI companies.

The left’s project, then, is much larger than the right’s—which is content to cut red tape, shrug, shovel money into the engine, and laugh at liberal tears—and must both resist AI’s current iteration and envision where it should go instead. The left knows it must oppose these firms as they seek to facilitate a massive transfer of wealth from the working class to the rich—and again, it knows this because AI executives are constantly talking about how they aim to do exactly this. It must confront the energy costs of the data centers, which are causing electricity bills to spike around the nation, and fossil fueled power plants to be brought back online. It must confront systems that are built on pirated and stolen intellectual property, and work to mitigate the damage done both by the theft of that intellectual property and to combat the new norms such systems seek to impose.

In other words:

“The left” must confront the entire political economy of AI at once, not just consider the core technology, which at this point is nearly impossible to assess apart from its owners and developers. AI is after all being developed by a cohort of executives and oligopolist tech firms that are open about their project of orchestrating a mass deskilling of labor, and using as much energy, resources, and capital as they see fit in the pursuit of that goal, and who are actively working with an authoritarian state to shut down democratic oversight of the technology. It feels blinkered, to say the least, to say “the left is missing out” by not productively engaging with the product built to serve this socioeconomic formation.

Rejecting or resisting a commercial technology designed to attempt a mass wealth transfer and to erode public institutions is a valid political position. This rejection can manifest as a kneejerk “plagiarism machine sucks” tweet or a slogan on a poster board at a picket line or a policy paper. And just because someone is rejecting a technology and the broader project it is a part of, does not mean they do not understand it. Oftentimes that rejection is entirely informed, warranted, and rational.

“The left” should be thinking about what it does want AI to do, and what good management of AI systems would look like. This is the big point I think that centrist pundits and AI folks are trying to make, I think, but I have good news for them: The left is thinking about these things! The biggest indicator that Kagan-Kans piece was either not particularly carefully researched or not written in good faith is that it failed to mention a debate that unfolded over the last many months, read by much of the left, between Aaron Benanav, Evgeny Morozov, and Leif Weatherby, addressing this very question. Benanav articulates a nuanced and carefully detailed plan for organizing a society that can sustainably manage both a drawdown from fossil fuels and a sector capable of robust innovation. (I will add he first did so last year, in an article for the New Left Review, the left’s most august journal of ideas.) Morozov argues for more fluidity and experimentation with AI. Weatherby makes a case for automating the c-suite. Meanwhile, the left’s most popular interview podcast, the Dig, just hosted Nick Srnicek, whose latest book takes the import of AI quite seriously, and whose subtitle is quite actually “The Fight for the Future of AI.” The left/left-liberal scholars and policymakers Ruha Benjamin, Alondra Nelson, and Amba Kak were appointed to Mamdani’s tech transition committee—where they are thinking seriously about how to manage the future of AI. Bernie Sanders, the single most famous individual on the American left, has proposed a data center moratorium, as, somewhat confusingly, Kagan-Kans himself points out.

“The left” must grapple with broad questions about what should be automated and what should not, and who gets to make those decisions, even if AI were not being developed by anti-humanist CEOs bent on mass extraction. My sense is that most people on “the left” understand that AI can efficiently automate large amounts of text, code, and image production—certainly most I speak with understand this—and that the tools are improving, if not at a rate the tech executives insist they are, and are still plenty flawed. But embedded in everything from Marxist programs to advance a communal AI to left-liberal critiques of harms to reactionary Bluesky posts is a broader grappling with what matters to us in society: What do we want AI to do, and how? Do we want AI in the classroom at all, even job degradation and deskilling somehow weren’t concerns? Do we want the writing of journalists’ copy to be automated? Art to be mass produced by machines? What is worth the trade-offs, the energy consumption? What’s not? The Benanav-Morozov debate was in large part over that question, and so, I would argue, are conversations happening online and off, among the broader left-liberal axis. (The MAGA right has fewer such qualms—if AI can make money, confer them power, and help them demean opponents with slop, bring it on.)

That these messy and vitriolic and sometimes inarticulate debates are not about what kind of Claudeswarm one should be wielding to maximize productivity does not signify ignorance, or a missed opportunity. It signifies resistance to the general AI project as currently constituted. It asks “Why do we want this?” “Who does it serve?”

This is eminently reasonable. It’s also popular. Data center moratoria are being passed in cities across the nation. Silicon Valley elites are immensely unpopular. There is widespread support for regulation and AI governance, and for the AI laws that have passed thus far. I’m sure AI advocates would prefer we move past a tendency to challenge the foundational elements of the industry’s products and hegemony. Of course it would! Because “the left” is winning the AI debate.

Do I think it’s getting everything right about AI? Hardly. I think it could lean more into a program of rejecting generative AI in extractive and exploitative circumstances, of protecting labor from deskilling, wage degradation, and surveillance, and refusing AI’s intrusion into spheres of public life Silicon Valley that seeks to colonize and profit from. The left, as always, does need to get better organized, and to better understand that it has actually accrued significant political capital around AI—again, majorities fear AI, dislike it, want to keep it away from their kids, and don’t want it to take their jobs, all for good reason—and use it. Because as of right now, it’s only winning the debate in the court of public opinion. In practice, AI companies are doing whatever they want, with the blessing of Trumpworld.

The left could even, as Benanav and Weatherby intimate, make a significantly stronger case that AI should be entirely publicly held and administered and—why not?—used to replace the executive class altogether. Position this on the terms AI firms and their founders themselves have laid out. If AI is truly the revolutionary force they claim, and it stands to remake the world from the ground up, if it promises to eliminate skill difference and advantage, then forget pittances like a basic income. Forget leaving Sam Altman in charge. Why should any reasonable person settle for anything less than full equality, and full co-ownership of this AI-run state? Control over our AI should be placed entirely in public hands—it was built to “benefit all of humanity”, after all—and granted to the humans it stands to impact. Why not automate Altman and the Anthropic c-suite and Elon Musk, and redistribute any gains to the people, however meager?

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I did mean to respond to the whole ‘the left is missing out on AI’ earlier in the discourse cycle, and one reason I couldn’t was I was putting together the last edition of BITM, about the nationwide phenomenon of people smashing Flock surveillance cameras, which has absolutely blown up. I suppose that was a pun.

It was picked up by Gizmodo, TechCrunch, Yahoo!, VICE, and was featured on the front page of Reddit, Hacker News, and Slashdot. The response was nearly universal: Godspeed to the Flock smashers. Jeff Sovern, the man who’s standing trial for dismantling 13 Flock cameras in Virginia, said he’d received thousands of dollars in donations to his legal fund since the story went up. And I’ve been receiving more tips about more acts of sabotage since. Keep them coming.

If you’ve heard stories of smashed Flock cameras or dismantled surveillance equipment in your neighborhood, please share—drop a link in the comments, or contact me on Signal or at briancmerchant@proton.me.

Thanks for sharing that story around everyone.

I linked this in the story above, but thought I’d share it here too; friend of BITM was featured on 60 Minutes, talking about AI’s impact on the art world and her livelihood. Turns out she thinks AI is pretty cool:

Oh you thought I was being hyperbolic when I labeled AI CEOs as anti-humanist up there?

Paris Marx has a nice writeup about Altman and OpenAI’s moral rot, tying the above posture wrt humans as null energy consumers to the AI company’s failure to alert authorities after ChatGPT flagged one of its users as a risk for committing violence—and that user went on to perpetrate one of Canada’s deadliest mass shootings.

I missed this when it came out, but just stumbled on it, and it’s too good not to share. Diana Enriquez studied how 50 middle managers use AI, and wrote about the results for Tech Policy Press:

…middle managers often appease leadership requests to implement AI automation even when there is limited value in it, pretending that their error-free draft was written by an AI tool that actually failed to deliver them a single coherent copy. They push harder to do more work with less time because the job market now demands they demonstrate familiarity with AI to align with the company’s evolving brand and complete work at the expected level of quality. The result is increased employee anxiety, burnout, and limits on productivity rather than gains.

A fun BBC story about how incredibly easy it is to hack AI search results:

I spent 20 minutes writing an article on my personal website titled “The best tech journalists at eating hot dogs”. Every word is a lie. I claimed (without evidence) that competitive hot-dog-eating is a popular hobby among tech reporters and based my ranking on the 2026 South Dakota International Hot Dog Championship (which doesn’t exist). I ranked myself number one, obviously….

Less than 24 hours later, the world’s leading chatbots were blabbering about my world-class hot dog skills. When I asked about the best hot-dog-eating tech journalists, Google parroted the gibberish from my website, both in the Gemini app and AI Overviews, the AI responses at the top of Google Search. ChatGPT did the same thing, though Claude, a chatbot made by the company Anthropic, wasn’t fooled.

I went to check the results in ChatGPT a couple days later to see if OpenAI had fixed the answer to the query the BBC built its stunt around, and it had, though now that response appeared weirdly fixated on Verge editor in chief Nilay Patel.

Finally, some good Luddite goings on:

In London, this Saturday, February 28th, you can join the March Against the Machines, organized by Pull the Plug.

For more details, RSVP here. As organizer Harry Atkinson tells me:

The rally is part of a wider effort to demand democratic oversight of how AI is developed and deployed in the UK. We’re calling for binding Citizens’ Assemblies on AI, so ordinary people whose jobs, industries and livelihoods are being reshaped by these systems - can have a meaningful say in how they’re used.

Alongside the London rally, Global Action Plan will be coordinating decentralised actions outside data centres across the country, so people can participate locally if they can’t make it to London

If I was anywhere near London, you can bet I’d be there, proverbial hammer in tow.

Finally, in New York City, the makers of the Luddite Club documentary are holding a salon with a screening and some special guests. This film is going to be great, and I’m not just saying that because I’m in it. RSVP and more info here.

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OK OK OK that’s it for today. Thanks for reading everyone. And as always, a special thanks to paid subscribers, who make all of this work possible. Consider upgrading if you find value in it, too. OK! Until next time. Hammers—and bolt cutters—up.

In today’s edition of Blood in the Machine:

• Across the nation, people are dismantling and destroying Flock cameras that conduct warrantless vehicle surveillance, and whose data is shared with ICE.

• An Oklahoma man airing his concerns about a local data center project at a public hearing is arrested after he exceeded his allotted time by a couple seconds.

• Uber and Lyft drivers deliver a petition signed by 10,000 gig workers demanding that stolen wages be returned to them.

• PLUS: A climate researcher has a new report that unravels the ‘AI will solve climate change’ mythos, Tesla’s Robotaxis are crashing 4 times as often as humans, and AI-generated public comments helped kill a vote on air quality.

A brief note that this reporting, research, and writing takes a lot of time, resources, and energy. I can only do it thanks to the paid subscribers who chip in a few bucks each month; if you’re able, and you find value in this work, please consider upgrading to a paid subscription so I can continue on. Many thanks, hammers up, and onwards.

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Last week, in La Mesa, a small city just east of San Diego, California, observers happened upon a pair of destroyed Flock cameras. One had been smashed and left on the median, the other had key parts removed. The destruction was obviously intentional, and appears perhaps even staged to leave a message: It came just weeks after the city decided, in the face of public protest, to continue its contracts with the surveillance company.

Flock cameras are typically mounted on 8 to 12 foot poles and powered by a solar panel. The smashed remains of all of the above in La Mesa are the latest examples of a widening anti-Flock backlash. In recent months, people have been smashing and dismantling the surveillance devices, in incidents reported in at least five states, from coast to coast.

Bill Paul, who runs the local news outlet San Diego Slackers, and who first reported on the smashed Flock equipment, tells me that the sabotage comes just a month or two after San Diego held a raucous city council meeting over whether to keep operating the Flock cameras. A clear majority of public attendees present were in favor of shutting them down.

There was “a huge turnout against them,” he tells me, “but the council approved continuation of the contract.”

The tenor of the meeting reflects a growing anger and concern over the surveillance technology that’s gone nationwide: Flock, which is based in Atlanta and is currently valued at $7.5 billion, operates automatic license plate readers (ALPR) that have now been installed in some 6,000 US communities. They gather not just license plate images, but other identifying data used to ‘fingerprint’ vehicles, their owners, and their movements. This data can be collected, stored, and accessed without a warrant, making it a popular workaround for law enforcement. Perhaps most controversially, Flock’s vehicle data is routinely accessed by ICE.

If you’ve heard Flock’s name come up recently, it’s likely as a result of their now-canceled partnership with Ring, made instantly famous by a particularly dystopian Super Bowl ad that promised to turn regular neighborhoods into a surveillance dragnet.

Meanwhile, abuses have been prevalent. A Georgia police chief was arrested and charged with using Flock data to stalk and harass private citizens. Flock data has been used to track citizens who cross state lines for abortions when the procedure is illegal in their state. And municipalities have found that federal agencies have accessed local flock data without their knowledge or consent. Critics claim that this warrantless data collection is Orwellian and unconstitutional; a violation of the 4th amendment. As a result, civilians from Oregon to Virginia to California and beyond are pushing their governments to abandon Flock contracts. In some cases, they’re succeeding. Cities like Santa Cruz, CA, and Eugene, OR, have cancelled their contracts with Flock.

In Oregon’s case, the public outcry was accompanied by a campaign of destruction against the surveillance devices: Last year, at least six Flock license plate readers mounted on poles located in Eugene and Springfield were cut down and destroyed, according to the Lookout Eugene-Springfield.

A note reading “Hahaha get wrecked ya surveilling fucks” was attached to one of the destroyed poles, and somewhat incredibly, broadcast on the local news.

In Greenview, Illinois, a Flock camera pole was severed at the base and the device destroyed. In Lisbon, Connecticut, police are investigating another smashed Flock camera.

In Virginia, last December, a man was arrested for dismantling and destroying 13 Flock cameras throughout the state over the course of the year. He’s apparently already admitted to doing so, according to local news:

Jefferey S. Sovern, 41, was arrested in October after detectives say he “intentionally destroyed” 13 Flock Safety cameras between April and October of this year. He was charged with 13 counts of destruction of property, six counts of petit larceny and six counts of possession of burglary tools.

Sovern admitted to the crimes, according to a criminal complaint filed in Suffolk General District Court, going as far as to say he used vice grips to help him disassemble the tow-piece polls. He also admitted to keeping some of the wiring, batteries and solar panels taken from the cameras. Some of the items were recovered by police after they searched the property.

After his arrest, Sovern created a GoFundMe to help cover his legal costs, in which he sheds a little light on his intentions:

My name is Jeff and I appreciate my privacy. I appreciate everyone's right to privacy, enshrined in the fourth amendment. With the local news outlets finding my legal issues and creating a story that is starting to grow, there has been community support for me that I humbly welcome.

(I reached out to Sovern, who is out on bail, for comment, and will update or follow up if I hear back.)

Sovern points his GoFundMe contributors to DeFlock, a website aimed at tracking and countering the rise of Flock cameras in US communities. It counts 46 cities that have officially rejected Flock and other ALPRs since its campaign began.

In fact, it’s hard to think of a tech product or project this side of generative AI that is more roundly opposed and reviled, on a bipartisan level, than Flock, and resistance takes many forms and stripes. Here’s the YouTuber Benn Jordan, showing his viewers how to Flock-proof their license plates and render their vehicles illegible to the company’s data ingestion systems:

In response to such Flock counter-tactics, Florida passed a law last year making it illegal to cover or alter your license plate.

In his GoFundMe, Sovern also mentioned the support for him he’d seen on forums online, so I went over to Reddit to get a sense for how his actions were being received online. Here was the page that shared news of his arrest for destroying the Flock cameras:

There was, in other words, nearly universal support for Sovern’s Flock dismantling campaign. Bear in mind that this is r/Norfolk, and while it’s still reddit users we’re talking about, it’s not like this is r/anarchism here:

The San Diego reddit threads carrying news of the destroyed Flock equipment told a similar story:

There were plenty of outright endorsements of the sabotage:

Off the message boards and in real civic life, Bill Paul, the reporter with the San Diego Slacker, says anger is boiling over, too. He points again to that heated December 2025 city council meeting, in which public outrage was left unaddressed. The city, perhaps aware of the stigma Flock now carries, apparently tried to highlight that their focus was on the “smart streetlights” made by another company, while downplaying the fact that those streetlights run on Flock software.

“San Diego gets to hide behind a slight facade in that their contract is with Ubicquia,” the smart streetlight manufacturer, Paul says, “but the software layer is Flock. You can easily see Flock hardware on retail properties, looking at the same citizens, with zero oversight, and SDPD can claim they have clean hands.”

Weeks later, pieces of smashed Flock cameras littered the ground.

Across the country, in other words, municipal governments are overriding public will to make deals with a profiteering tech company to surveil their citizens and to collaborate with federal agencies like ICE. It might be taken as a sign of the times that in states and cities across the US, thousands of miles apart, those opposed to the technology are refusing to countenance what they view as violations of privacy and civil liberty, and are instead taking up vice grips and metal cutters. And in many cases, they’re getting hailed by their peers as heroes.

If you’ve heard stories of smashed Flock cameras or dismantled surveillance equipment in your neighborhood, please share—drop a link in the comments, or contact me on Signal or at briancmerchant@proton.me.

Thanks to Lilly Irani for the tip on the smashed Flock cams in San Diego.

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In case you missed it, I shared my five takeaways on the most recent round of ultraheated AI discourse here:

Critical AI Report 2/2026

An Oklahoma man was arrested for (barely) exceeding his allotted 3 minutes to offer a public comment opposing a local data center project.

The exchange was filmed and recorded on YouTube:

at 404 Media reports the details:

Police in Claremore, Oklahoma arrested a local man after he went slightly over his time giving public remarks during a city council meeting opposing a proposed data center. Darren Blanchard showed up at a Claremore City Council meeting on Tuesday to talk about public records and the data center. When he went over his allotted 3 minutes by a few seconds, the city had him arrested and charged with trespassing.

The subject of the city council meeting was Project Mustang, a proposed data center that would be located within a local industrial park. In a mirror of fights playing out across the United States, developer Beale Infrastructure is attempting to build a large data center in a small town and the residents are concerned about water rights, spiking electricity bills, and noise.

The public hearing was a chance for the city council to address some of these concerns and all residents were given a strict three minute time limit. The entire event was livestreamed and archive of it is on YouTube. Blanchard was warned, barely, to “respect the process” by one of the council members but was clearly finishing reading from papers he had brought to read from, was not belligerent, and went over time by just a few seconds. Anyone who has ever attended or watched a city council meeting anywhere will know that people go over their time at essentially any meeting that includes public comment.

Blanchard arrived with documents in hand and questions about public records requests he’d made. During his remarks, people clapped and cheered and he asked that this not be counted against his three minutes. “There are major concerns about the public process in Claremore,” Blanchard said, referencing compliance documents and irregularities he’d uncovered in public records.

Blanchard was then arrested as the crowd jeered in disbelief. Also disconcerting was the way the local news framed the event, with a local anchor defending authorities by claiming he was “warned multiple times.” Seems like a pretty surefire way to make people hate data centers and the governments protecting them even more!

10,000 Uber and Lyft drivers call for the gig giants to repay stolen wages

On Wednesday, I headed to Pershing Square in downtown Los Angeles, where dozens of gig workers and organizers with Rideshare Drivers United had assembled to deliver a petition to the California Labor Commission signed by thousands of workers, calling on the body to deliver a settlement on their behalf. Organizers made short speeches on the steps of the square while local radio and TV stations captured the moment. “

“They’re robbing us!” A speaker yelled. “Wage theft!” the crowd replied.

The Labor Commission is suing the gig companies on drivers’ behalf, alleging that Uber and Lyft stole billions of dollars worth of wages from drivers before Prop 22 was enacted in 2020. The commission is believed to be in negotiations with the gig companies right now that will determine a settlement.

I spoke with one driver, Karen, who had traveled from San Diego to join the demonstration, and asked her why she came. “It’s important we build driver power” she said. “Without driver power, we won’t get what we need, and we just want fairness.” She said she was hoping to claim at least $20,000 in stolen wages.

“We’re fighting for wages that were stolen for us from us and continue to be stolen from us every single day by these app companies from hell,” RDU organizer Nicole Moore told me. “So we’re marching in downtown L.A. to deliver 10,000 signatures of drivers demanding that the state fight hard for us, and don’t let these companies rip us off.”

Tesla’s Robotaxi launch in Austin is not going well

According to Tesla’s own numbers, its new RoboTaxis in Austin are crashing at a rate 4 times higher than human drivers. The EV trade publication Electrek reports:

With 14 crashes now on the books, Tesla’s “Robotaxi” crash rate in Austin continues to deteriorate. Extrapolating from Tesla’s Q4 2025 earnings mileage data, which showed roughly 700,000 cumulative paid miles through November, the fleet likely reached around 800,000 miles by mid-January 2026. That works out to one crash every 57,000 miles.

The irony is that Tesla’s own numbers condemn it. Tesla’s Vehicle Safety Report claims the average American driver experiences a minor collision every 229,000 miles and a major collision every 699,000 miles. By Tesla’s own benchmark, its “Robotaxi” fleet is crashing nearly 4 times more often than what the company says is normal for a regular human driver in a minor collision, and virtually every single one of these miles was driven with a trained safety monitor in the vehicle who could intervene at any moment, which means they likely prevented more crashes that Tesla’s system wouldn’t have avoided.

Using NHTSA’s broader police-reported crash average of roughly one per 500,000 miles, the picture is even worse, Tesla’s fleet is crashing at approximately 8 times the human rate.

BLOODY LINKS

-“The Left Doesn’t Hate Technology, We Hate Being Exploited,” by Gita Jackson at Aftermath.

“Meta drops $65 million into super PACs to boost tech-friendly state candidates,” by Christine Mui in Politico.

-A great new report from climate researcher Ketan Joshi, “The AI Climate Hoax: Behind the Curtain of How Big Tech Greenwashes Impacts,” has been making headlines and is well worth a read. Perhaps we’ll dig deeper into it in a future issue.

-The LA Times reports that the Southern California air board rejected new pollution rules after an AI-generated flood of made-up comments. Here’s UCLA’s Evan George on how AI poses a unique threat to the civic process.

-A good profile of Nick Land, “Silicon Valley’s Favorite Doomsaying Philosopher,” by James Duesterberg.

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Okay okay, that’s it for this week. Thanks as always for reading. Hammers up.

A viral, AI-generated blog post on X called “Something Big Is Happening,” by Matt Shumer, a CEO of an AI company, was one catalyst, though it builds off sentiments articulated in Anthropic CEO Dario Amodei’s much longer essay, “The Adolescence of Technology,” which makes a similar if more indulgent and nuanced case, plus all the AI Super Bowl ads, and the hype drummed up by Moltbook, the ‘reddit for AI agents’ created by yet another AI CEO, that was the talk of the town until it was revealed that it exposed the user data of everyone involved and that many of the most interesting threads were actually written by humans. Underneath it all was more organic buzz produced by Anthropic’s coding tools, which users, journalists and commentators are blogging and podcasting about. But the Something Big blog, with 83 million views and counting, burst the dam.

The gist should be plenty familiar to BITM readers and AI watchers at this point: Tremendous social change, driven by AI, is about to unfold, and people simply aren’t prepared. (Per the post’s central conceit, we are in the early pandemic days when things are about to change forever.) Yet the blog did that special thing that blogs blogged at just the right time and place can do: they inspire people to react particularly strongly on social media in a way that inspires other people to react strongly to the reaction, and then all bets were off and everyone was sharing what they think about AI, and more specifically their frustrations with what everyone else thinks about AI. That many had been preoccupied with what was happening with ICE and Minneapolis and the release of more of the Epstein files also probably meant lots of those AI thoughts had been pent up for a month or two, and contributed to the unusual force through which they were released.

It has been a rich and sprawling text, to say the least. To help make sense of it, here are the five major takeaways from the most heated AI discourse in a minute, as far as I’m concerned:

1. There is a distinct material basis for all this discourse. We’re in the midst of another concerted, industry-led hype cycle, this time driven more visibly by Anthropic, which just landed a $30 billion investment round.

2. This time the hype must transcend multibillion dollar investment deals: It must also raise the stock of AI companies ahead of scheduled IPOs later this year and help lay the groundwork for federal funding and/or bailout backing.

3. Much of the discourse centered on lambasting critics who accuse AI of being “fake”—but this is a straw man argument that serves the industry.

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As the signature count rises, employees say that Google is working to stifle speech critical of its ICE contracts: censoring posts on its companywide forum Memegen, issuing warnings to workers who post ICE-related content, and ignoring their calls to address the issue both privately and publicly.

In today’s edition of BITM, an inside look at the Google employees organizing to end the tech giant’s ties to ICE, and the tactics the company is using to silence them. Plus, updates on the widening resistance to big tech in other arenas, from gig work to data centers. Finally, for paying subscribers, the 5 worst AI ads of the Super Bowl, and what they portend for Silicon Valley. As always, thanks for reading, engaging, and supporting this work. And a special thanks to all you paid subscribers who make this entire project possible; I couldn’t do any of this without you.

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“I see an outpouring of support for this call,” says Alex, a full-time Google engineer and one of the petition’s organizers. “Almost everybody I spoke to is for divestment from ICE.” Among rank and file employees, he says, “any opposition to that is very rare.”

Yet leadership has not acknowledged the petition, and has thus far dodged all requests to answer questions about ICE, CBP, or Google’s role in supporting the agencies. Like Amazon, Google operates cloud services for ICE and the DHS, and is a partner of Palantir, one of the biggest technology providers for those departments. But despite Google employees’ anger and unease regarding their company’s partnership with ICE, workers are wary of voicing criticism openly.

“Many are hesitant to sign,” Alex tells me. “The expectation of retaliation is very widespread.” Recent rounds of layoffs, and the threat of retaliation, have created a “sense of job insecurity” among many. “The fear of speaking out is very strong,” he says. “Most folks are afraid to discuss anything remotely political at work.”

According to Alex and other employees, Google is stifling and censoring speech critical of the federal government in its internal communication channels. “Recently, the moderation team started banning memes and comments about ICE on the internal meme platform,” Alex says.

That platform, called Memegen, has been a fixture of working life at Google since 2010. Employees use it to generate and post memes throughout the workday, or during town halls, to comment on pertinent subjects. Now, many have found that criticizing ICE, or Google’s role in supporting the agency, is off-limits. Employees estimate that some forty Google staffers have had their memes taken down and received warnings for posting on the platform. Alex says it’s creating a chilling effect on speech at the company. (Google did not respond to a request for comment.)

A takedown notice sent to a Google employee by one of the company’s Memegen moderators and shared with Blood in the Machine read, “Your content violates Memegen’s Community Guidelines, specifically because the content is focused on personal political opinions, statement or news. Please be advised that this is your final warning before a permanent ban.” Some of the posts that point to the Googlers Against ICE petition, Alex says, have been allowed to stay up. Other memes have been taken down minutes after they were posted. One staffer had a post removed that merely shared word of an ICE-related protest.

“Whenever any questions related to ICE pop up in town halls, they either get outright deleted or simply don’t show up in the AI Summarization’ for some reason,” according to Alex. “In rare instances when questions reach leadership, they give non-answers or undermine the premise of the question. Although even that hasn’t happened in a while.”

There has, until relatively recently, been a tradition of tolerating, even encouraging some strains of dissent at Google. Memegen was notoriously feisty (for a corporate message board, anyway) throughout the 2010s, when employees could poke fun at the company, its policies, even its leadership. In 2018, some 20,000 workers walked out to protest Google’s sexual harassment policies. Co-founder Sergey Brin joined a protest of the so-called Muslim Ban instituted early in Trump’s first term.

Those openly protesting against Google’s ICE contracts today, meanwhile, are a small minority. This is not necessarily because most Google staffers’ politics have changed, but because the company has made it clear it will no longer tolerate such dissent, and that it’s explicitly aligned with the Trump administration. (Discussing politics is now technically off-limits on Memegen, though discussing company matters and policy isn’t.) Google CEO Sundar Picchai has been a fixture at the White House, attending parties and events. He oversaw Google’s $22 million donation to the White House ballroom and its $1 million donation to Trump’s inaugural fund. Brin, meanwhile, has become a Trump supporter. And Google has clamped down hard on employee dissent. It fired 50 staffers for staging an internal protest when the tech giant signed a cloud contract with the Israeli military. Those staffers were part of a group called No Tech for Apartheid, which, undeterred, is organizing the current petition, too.

The Googlers Against ICE petition—which received more signees every time I refreshed the page while I was writing this story—is detailed and blunt. A key section reads that:

Google is powering this campaign of surveillance, violence, and repression. Cloud is helping to stitch together CBP surveillance systems along the border and nationwide, while also powering Palantir’s ImmigrationOS system that ICE uses to track immigrants. Google generative AI is being used by DHS and CBP for “workforce enablement” and “improving operational efficiency”. The Play Store has blocked the most effective ICE tracking apps for keeping our communities safe. YouTube has been running ICE recruitment and “self-deport” ads. As the workers who provide the foundational labor in building this technology, we are horrified.

On January 11, Google Chief Scientist Jeff Dean tweeted, “We all bear a collective responsibility to speak up and not be silent when we see things like the events of the last week.” We agree. In that spirit, we are speaking up today as Googlers.

We are vehemently opposed to Google’s partnerships with DHS, CBP, and ICE. We consider it our leadership’s ethical and policy-bound responsibility to disclose all contracts and collaboration with CBP and ICE, and to divest from these partnerships.

For the anti-ICE Google employees and others, the situation has grown all the more urgent. As WIRED reports, ICE is rapidly and dramatically expanding its operations. The DHS has, as WIRED puts it, “carried out a secret campaign to expand ICE’s physical presence across the US.” There are more than 150 leases and office expansions that portend ICE facilities in nearly every state, many of which will be “located near elementary schools, medical offices, places of worship, and other sensitive locations.”

ICE, however, is deeply and increasingly unpopular nearly everywhere, outside the tech companies and in. And Alex is optimistic that this is helping to turn the tide, that more tech workers at Google and beyond will be willing to step up and speak out.

“I believe that the momentum is on our side,” he says. “Many workers see the current moment as critical. They’re ready to act. The public’s opinion has also shifted. There are various external campaigns that demand Google’s divestment from ICE. Google leadership is going to find itself surrounded by pressure from all sides.”

Alex ended our interview with some words for his fellow Googlers and for employees at any other tech company currently partnering with ICE or the DHS:

“You’re not alone. You have support of your fellow workers in your company and across the industry. It’s time we take responsibility for how our products are used for surveillance and violence.”

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If you work at Google, Amazon, or any other tech company with ICE contracts, and want to share a story about how workers are engaging the ICE issue at your workplace, you can contact me on Signal or at briancmerchant@proton.me.

Google workers aren’t the only ones standing up to big tech. Some updates there:

-Uber and Lyft drivers are delivering a wage claim petition signed by 10,000 workers, demanding the ride hail companies pay back the wages they stole:

On Tuesday, February 17 at 10am in Downtown LA, drivers will share with the California Labor Commissioner a clear message: Uber and Lyft must pay what we are owed. After years of wage theft, the State of California has sued Uber and Lyft to recover unpaid wages and expenses from 2016–2020—money that adds up to tens of billions of dollars.

Over 10,000 drivers have already signed the wage theft settlement petition, making it clear that any settlement to this suit must deliver dignity to drivers. Join us on Tuesday, February 17th at Pershing Square to make sure that California hears us loud and clear - We Demand Dignity!

“A California community rallied against a datacenter – and won”

From the Guardian:

When a southern California city council proposed building a giant datacenter the size of four football fields last December, five residents vowed to stop it.

Through a frenetic word-of-mouth campaign, the small group raised awareness about the proposed facility in Monterey Park, a small city east of Los Angeles known affectionately as the country’s first suburban Chinatown.

No Data Center Monterey Park organizers – working in tandem with the grassroots racial justice group San Gabriel Valley (SGV) Progressive Action – held a teach-in and rally that drew hundreds of participants, knocked on doors, and distributed flyers on busy streets.

They emphasized how the computer systems facility would strain the power grid, drive up energy rates and create noise pollution. A petition quickly amassed nearly 5,000 signatures. All the materials were shared in English, Chinese and Spanish – a concerted effort to reach Monterey Park’s diverse populace, which is two-thirds Asian and one-quarter Hispanic.

In just six weeks, the community won. City leaders issued a 45-day moratorium on datacenter construction and a pledge to explore a permanent ban.

“It’s like the third act of an Oscar-winning movie,” said Steven Kung, a co-founder of No Data Center Monterey Park.

Over the past year, homegrown revolts against datacenters have united a fractured nation, animating local board meetings from coast to coast in both farming towns and middle-class suburbs. Local communities delayed or cancelled $98bn worth of projects from late March 2025 to June 2025, according to research from the group Data Center Watch, which has been tracking opposition to the sites since 2023. More than 50 active groups across 17 states targeted 30 projects during that time period, two-thirds of which were halted.

The movement against these facilities has even made for strange bedfellows, bringing together nimbys and environmentalists in Virginia, “Stop the Steal” activists and Democratic Socialists of America organizers in Michigan.

“There’s no safe space for datacenters,” said Miquel Vila, lead analyst at Data Center Watch, a research project run by AI security company 10a Labs. “Opposition is happening in very different communities.”

A ‘QuitGPT campaign has been launched by anti-OpenAI activists, claiming 700,000 users have signed on so far.

Tom’s Guide reports:

QuitGPT is a decentralized campaign that has spread through Reddit, Instagram and dedicated websites where users pledge to drop ChatGPT Plus and other paid tiers. Organizers and participants cite several core grievances:

• Political contributions by OpenAI leadership: A widely shared claim in the campaign alleges that OpenAI’s president made a major political donation to a pro-Trump super PAC — a move critics argue contradicts the activist values of many Silicon Valley users.

• AI use in government enforcement: QuitGPT supporters highlight that tools powered by ChatGPT-style models have been used in hiring or screening processes by agencies such as U.S. Immigration and Customs Enforcement, heightening concerns that AI is being deployed in controversial real-world systems.

• Ethical unease and corporate accountability: Beyond specific incidents, the movement reflects a broader uneasiness about who controls the technology users rely on daily and what those leaders’ values say about the tools themselves.

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Now, speaking of OpenAI, anyone who was aware of both that particular AI company and the overwrought advertising and halftime show delivery vehicle that is the Super Bowl was likely aware that there was some beef laid out there. Chief OpenAI competitor Anthropic aired some ads ribbing OpenAI for rolling out ads on ChatGPT, and Sam Altman took to Twitter to moan about it.

But Anthropic was far from the only AI company running ads for $8-$10 million a pop during Seattle’s dismal obliteration of the Patriots. There were, as you likely saw, a great many AI ads, and most of them were either terrible harbingers of our dystopian future, or just plain terrible. Here at BITM, I offer you a guide to the worst of the worst.

5. The perplexing ad for an AI service that do not yet exist, was not explained, and whose logo looks like an Asics sneaker:

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“Our goal today was to draw the connection between ICE’s cruelty and the digital infrastructure that Amazon provides to give them the ability to target and capture migrants,” Carter Moon, one of the event’s organizers, told me.

“Big tech has not caught enough heat for this,” said Olga Lexell, a screenwriter and former tech worker. “It’s people like Elon Musk, Jeff Bezos, Sam Altman, Mark Zuckerberg—the tech CEOs who are using their tools to facilitate these deportations. They can actually do more now than anyone in our government probably can.”

Lexell said that when she was on the metro on way to the protest with other demonstrators, she overheard a pair of Amazon workers worriedly discussing the backlash. They had evidently not been aware Amazon was a partner with ICE at all. This was part of the reason Lexell says she joined the protest, to try to get Amazon employees like them to learn about their company’s associations with ICE and the Trump administration—and, ideally, to walk out.

So far, none had, as far as anyone could tell. It can be difficult to absorb, perhaps, both for consumers and employees, the full extent to which Amazon and its leadership have become instrumental to effectuating the state’s authoritarian projects. Perhaps events of the following days made it a little bit clearer.

The week after the ICE Out Amazon protest, Jeff Bezos, who in 2013 bought the Washington Post, laid off 30% of its staff. He eliminated the newspaper’s books and sports sections, gutted critical tech, climate, and international coverage, fired decorated war correspondents while they were still in a combat zone in Ukraine, and “reset” the paper to focus on national security and American politics, according to NPR. IE, subject matter areas that are less likely to offend or unduly complicate matters for Donald Trump. (There have of course been plenty of bleak jokes about the paper’s motto.)

The Post’s former top editor, Marty Baron, says he thinks Bezos’ layoffs stem from a single motivation and that motivation is appeasing the president. Here’s Baron on MS Now:

“Trump came into office again. He had promised vengeance against his perceived political enemies. Jeff Bezos was seen as a political enemy by Donald Trump for one reason and one reason only, and that was the coverage of the Washington Post.”

….Bezos feared “reprisal” against not just Amazon, but also against what the former Washington Post chief described as the “object of his passion,” Blue Origin, the private space company that holds significant government contracts. “And so he has sought to navigate this administration during the second term.”

Bezos has done this navigating much the way the other tech oligarchs have, with obsequious gestures of ring-kissing and flattery and ample naked transactionalism. With Amazon’s role in ICE operations under greater scrutiny and Bezos’ dismantling of the organ that once proudly declared itself on being a defender of democracy, it’s worth recounting and examining just how closely intertwined Amazon, Trump, and the federal government have become—and how closely aligned their projects are.

Amazon donated $1 million to Trump’s inaugural fund; a symbolic gesture of goodwill. It also made an in-kind donation worth $1 million by livestreaming the inauguration on Prime. In the run-up to the election, Bezos intervened to kill the Post’s endorsement of Kamala Harris, and then reorganized the paper’s opinion section to focus exclusively on subjects that championed “personal liberties and free markets,” both moves seen at the time as aimed at placating Trump.

The same is largely assumed to be the intent behind the $40 million that Amazon spent for the Melania vanity documentary project—a full $26 million more offered by the next-highest bidder, Disney. Amazon then spent $35 million conspicuously marketing the film; more than it has budgeted for any other documentary. The day after Alex Pretti was shot and killed by federal agents in Minneapolis, current Amazon CEO Andrew Jassy attended a private screening of the film at the White House, with other tech elites like Tim Cook. The company issued no statement.

Amazon’s entreaties have worked; government contracts have been signed, Amazon execs and Bezos have been regular attendees at White House events, and both sides have seen benefits to working in tandem. When Amazon leadership threatened to list the additional cost of products incurred by tariffs, a phone call from Trump was all it took to dissuade them. (“Jeff Bezos was very nice. He was terrific,” said, per CNN. “He solved the problem very quickly. Good guy.”)

As the former Post editor Marty Baron pointed out, part of this favor-trading is aimed at staying in Trump’s good graces to advance Bezos’s personal projects—Blue Origin has continued to reap contracts and favorable treatment—but perhaps a larger part is to advance Amazon’s material business interests. The federal government, after all, is an enormous purchaser of Amazon’s services.

In September 2025, Amazon signed the aforementioned $25 million contract with ICE to help run the agency’s cloud services. As Forbes put it, “under the second Trump administration, ICE has spent more on cloud services from Amazon and Microsoft than ever before, according to federal contracting records.” Under Trump, Amazon Web Services also entered into a deal worth $1 billion to help manage other civilian government services. AWS also hosts the software run by Palantir—perhaps the biggest ICE contractor in tech.

That’s pennies, however, compared to Amazon’s other contracts with other federal agencies. In 2021, during the Biden administration, Amazon inked a 10-year, $10 billion deal with the National Security Agency. The NSA, of course, is the spy agency that was marred by scandal in 2013 when Edward Snowden revealed it had illegally been collecting and storing extensive phone and online data from American citizens. Along with Google and Oracle, Amazon has a $9 billion contract with the Pentagon to operate the Joint Warfighting Cloud Capability program. Amazon Web Services manages many other smaller contracts for the government as well, including with the CIA and the Navy; those mentioned are just the largest.

Suffice to say that the tech giant has insinuated itself rather deeply into the routine operations of the federal government through the management of a large swath of its digital infrastructure and database systems. Amazon is providing the technical architecture for the federal security state—for ICE, the NSA, the Pentagon, and many others—that is actively enabling that state to surveil residents of the United States, and to conduct its ongoing campaigns of violence. Remember, it’s not just databases of migrants the federal government is managing, but of American citizens marked as “domestic terrorists,” which includes an ever-expanding group of people, like Rene Good, who are community organizers, protestors, and legal observers. Tom Honan, Trump’s border czar, has called for the creation of databases of anyone opposing or interfering with DHS actions.

Amazon is providing the bulk of the cloud architecture to make all of that possible, and it’s making billions in the process.

But it’s not merely the technological architecture the state is implementing, but Amazon’s ideological architecture, too. This April 2025 report from a border security conference held in Phoenix the Arizona Mirror made the rounds last year, and it’s worth revisiting now:

The leader of Immigration and Customs Enforcement said that his dream for the agency is squads of trucks rounding up immigrants for deportation the same way that Amazon trucks crisscross American cities delivering packages.

“We need to get better at treating this like a business,” Acting ICE Director Todd Lyons said, explaining he wants to see a deportation process “like (Amazon) Prime, but with human beings.”

This is what Bezos or one of his remaining sufficiently ideologically restricted opinion writers might call a free exchange of ideas: Jeff Bezos has learned that he can submit the free press to authoritarianism to serve his interests, while the authoritarians have learned they can behave more like Amazon to serve theirs.

The convergence makes sense. Amazon fueled its rise by dehumanizing its own workforce, demanding machine-like productivity from workers and so relentlessly surveilling and tracking their movements and time-on-shift that some famously felt they had no choice but to pee in bottles to avoid being penalized. ICE’s project is of course predicated on surveilling and dehumanizing immigrants and political opponents, and it’s little wonder it finds Bezos’s regimen so appealing. Or that Amazon is letting ICE raid its facilities across the country, helping to move those workers it does not see as human from one assembly line to another.

All that’s standing in the way, as in Minneapolis, are peers; ordinary citizens, neighbors, and coworkers. Which brings me back to the hundreds of people—high school students, Santa Monica moms, DSA members, tech workers, and everyone else—who turned up at the ICE OUT AMAZON protest last week.

“You know, a key part of fascism is the alliance of corporations and the state, and a mutually beneficial relationship of them profiting off of the government’s cruelty, which is exactly what we’re seeing here,” the organizer Carter Moon said. “I don’t know how much leverage we have to get Congress to get their act together, but I do think we have leverage to pressure places like Amazon to drop their contracts. You know, they need our Prime subscriptions. They need us to keep shopping at Whole Foods.”

In that vein, actors from across the political spectrum, from activists in the Nation to the business professor and podcaster Scott Galloway, are calling on people and consumers to boycott Amazon (and the other tech companies enabling ICE operations). Consumer boycotts are of course a notoriously challenging protest tactic, but anti-ICE sentiment is through the roof. And realistically, it’s going to take all hands on deck at this point.

“In the grand scheme of things, I don’t think that Amazon will ever cut contracts with ICE or anything like that,” the protestor Levell said, “but I do ultimately think that the workers within Amazon can do a lot to prevent Amazon from being able to facilitate this stuff.” Even before the ICE out event, last year, small groups of Amazon workers were organizing rallies calling for the company to cancel its ICE contracts. We can only expect those calls to grow. Just today, as I was wrapping this post, news broke that 800 Google workers had formally demanded that their company drop its ICE contracts. It was organized by No Tech for Apartheid, a group of Amazon and Google workers who had previously protested their companies’ military contracts.

(This is the kind of thing that the Washington Post’s tech reporters might have covered, had they not been fired. Among those let go were Nitasha Tiku, one of the very best critical tech reporters working today, and, of course, the great Caroline O’Donovan, who covers, you guessed it, Amazon.)

The lines have been drawn, and Amazon has chosen its side. It’s going to take this kind of ground-up organizing and protest, and much more of it, to challenge its entrenchment with the state. Jeff Bezos and the executives at Amazon are transforming the institutions they control into willing instruments of authoritarianism. And calls are rising for white collar Amazon workers to step up.

“Many of the people who work here are ultimately neighbors in this community,” Levell said, gesturing at the Amazon Studios buildings behind her. “And they should know that the neighborhood knows that they’re complicit in the kidnapping of our other neighbors.”

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Another bad week in the books, eh. There was a bright spot, I should mention—on Tuesday, I traveled to Sacramento to speak at a conference put on by the California Federation of Labor Unions, called Taking on Tech. There were lots of talks and great conversations with some of the smartest folks working on this stuff today, and reason to think that unions are starting to more forcefully mobilize around AI, job, and workplace impacts.

Alas, I had to jet back home and missed the second day, due to the norovirus absolutely ripping through the household back home. The kids were home sick from school most of the week, puking away; my poor guys. (This, I will add, is why this week’s edition is so late. Sorry! I’m scrambling to publish before I succumb to it as well.) At least I got to catch some of Porco Rosso, a delightful and anti-fascist Studio Ghibli film I’d never seen before.

Things I’m looking forward to reading after I come up for air:

-This whole exchange of essays between Evgeny Morozov and Aaron Benanav in the Ideas Letter, over how to approach AI.

-This letter from Senator Ed Markey to autonomous car companies about their business practices, safety policies, and labor impacts. Waymo is in especially hot water after hitting a kid outside an elementary school and not stopping for school buses in Austin.

-Move Slow and Upgrade, a book by the philosophy professor Evan Selinger and Albert Fox Cahn, the Surveillance Technology Oversight Project's founder and executive director.

While I’m assigning homework, consider checking out and signing this petition—the California State University system is currently spending millions on OpenAI contracts while laying off human faculty:

And finally, a little further reading on the Washington Post debacle:

-How Jeff Bezos Brought Down the Washington Post, by former Post reporter Ruth Marcus in the New Yorker.

Fun/bleak one from friend of the blog :

The Future, Now and Then

Jeff Bezos, Moral Cretin

There is one thing I want to say about Jeff Bezos’s decision yesterday to fire 300 journalists from the Washington Post yesterday…

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3 months ago · 40 likes · 7 comments · Dave Karpf

Okay, that’s it for today. Thanks as always for reading, and a short reminder that paid subscribers make this entire project possible. It’s your backing that allows me to head out to cover ICE and Amazon protests, to interview tech workers and activists, to travel to labor conferences to talk to leadership about AI—these are unpaid gigs—and to take time off to take care of my kids while they are in the throes of sweaty delirium yet still finding the will to bicker with each other over what movie to watch.

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Thank you all, and hammers up.

Despite the authoritarian headwinds, there are of course those working to keep democracy functioning. To that end, I was invited to speak at a meeting of California’s Legislative Progressive Caucus—a group of dozens of elected state assembly members—in San Francisco last week. The caucus is crafting its approach to its next legislative session, and I was asked to discuss AGI, labor, and tech policy in the age of Trump, along with co-panelists Emily Bender, the computational linguist at the University of Washington, computer scientist Margaret Mitchell, and AI researcher Deborah Raji. I thought I’d share my remarks with readers here, in case they’re of interest. I also wanted to note that I’m only able to do things like this thanks to my paying subscribers. Taking trips and preparing talks like this are entirely unpaid labor, and it’s only because I think it’s important to advocate for the worker, the human, and the user in the age of AI and big tech, that I undertake them. And subscribers make that work possible. Thank you.

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I’m also pleased to report that I was impressed by the defiant attitudes and outlook of many members of the progressive caucus I spoke with.Tthey made calls for showing up in the streets for their communities and protesting ICE alongside them. They laughed off the Trump administration’s efforts to ‘ban’ AI lawmaking via executive order. Shortly after the meeting, assemblyman Alex Lee, the head of the progressive caucus, introduced legislation to eliminate tax breaks for companies that contract with the ICE or the Department of Homeland Security. Isaac Bryan, who I’ve actually interviewed in these pages before, about his No Robo Bosses bill, sponsored legislation to ban police officers from taking secondary employment with ICE. Unlike too many Democrats at the federal level, they appeared to have no intention of standing down.

Hello -

Thanks for having me, and for convening this listening session. I’ve been been reporting on the tech industry for over 15 years, and for the last five, I’ve been focusing on technology and labor. I wrote a book called Blood in the Machine about the history of worker resistance to automation, and the perennially misunderstood Luddite uprising.

With that in mind, there are a few points I want to hit on:

First, that the history of automation technologies can teach us a great deal about the present. From the power loom to the robotized assembly line to artificial intelligence, he ways that automation technologies impact working people tend to follow similar patterns.

One key lesson is that stories about the incredible power of a new technology have historically been used by entrepreneurs, bosses, and elites to override norms, standards, and laws, or bend them to their favor. Factory owners who adopted mechanized looms in the early 1800s argued that the rules on the books shouldn’t apply to them because they were using new and improved technology. On those grounds, they eventually convinced British Parliament to tear up most of the laws protecting cloth workers altogether. Decades of immense working class suffering ensued.

Today, a lot of tech CEOs right down the street from here are arguing much the same thing, calling for a moratorium on AI laws and deregulation—arguing that AI technology is so new and powerful it shouldn’t be beholden to any state laws at all.

A key to this agenda is the idea that artificial general intelligence, or AGI, is about to arise and unleash untold economic and social benefits. This, too, I might note, is not new. Pro-business interests have been claiming that full automation is right around the corner for no less than two centuries. The inventor of the early computer, Charles Babbage, and the writer Andrew Ure notably did so in the 1800s, when they claimed autonomous, human-free factories were incipient—in part to rebut growing concerns over the brutal working conditions in real-world factories.

Now, generative AI is undoubtedly on many counts, novel, and technologically impressive. But I bring up all this historical context to remind us that we’ve been here before, with powerful interests using the specter of world-changing technology to concentrate power, justify trampling workers in the short term, and distract from the more immediate harms and impacts.

So that’s the second thing I want to underline here:

AGI, or an AI super intelligence should, in my opinion as a tech reporter and something of a historian of automation, be understood primarily as Emily Bender have described it: A marketing device. There are plenty of AI researchers who truly believe we are on the cusp of realizing an AI super intelligence, and there are plenty who do not. But figures like Sam Altman have realized that AGI makes for the ultimate story to sell partners and investors on his company and products.

OpenAI defines AGI as, and I quote from its official charter, still online today, “highly autonomous systems that outperform humans at most economically valuable work.” This is what it’s selling to enterprise clients around the world, and why so many companies have FOMO; no company wants to risk missing out on the ‘eliminate all labor costs’ machine. That’s ultimately why we have an AI bubble right now.

In fact, in researching a report for the AI Now Institute, I analyzed AI CEOs’ public usage of the term ‘AGI’, and found that it tended to correlate almost exactly to when they needed to raise a new funding round or distract from a PR scandal.

The third and last point I want to make is that, just as the dreams of the fully automated factory helped obscure real-world problems with factory conditions and child labor abuses in the 1800s, the AGI story is obscuring the fact that AI is causing a litany of real-world problems right now.

For one, it’s a motor behind the often reckless data center buildout that’s raising electricity bills, threatening water supplies, and impacting communities across the nation. But that’s all worth it, the AI companies say to states and municipalities eager to stay ahead of the curve, because AGI is around the bend.

Furthermore, many companies that buy AI firms’ enterprise software are buying into the AGI dream, too, and have indeed begun replacing workers’ jobs and tasks with AI, regardless of whether the technology is truly up for the task. So far, it’s usually not; the AI does a worse job than the human in nearly every case. But the AI is cheaper. So what you see happening a lot is firms executing layoffs—Salesforce, here in SF, for instance, cited AI as a driving force behind its most reason round of firings, as did Amazon recently—and then the remaining workers have to work extra hours to pick up the slack. In fact, after Amazon’s corporate leadership attributed its layoffs to AI, Amazon tech workers took the extraordinary step of issuing a public statement saying internal AI tools were not capable of doing their work, and that AI was an excuse to cut headcount.

This is happening in a number of different fields, not just tech. I run a series on my website called ‘AI Killed My Job’ in which I ask workers to share stories of how AI impacted their workplaces. I’ve heard from hundreds of workers at this point. And it is clear that AI *is* doing some real damage, especially to our creative industries here in California. Artists who’ve lost half of their clients to Midjourney and can no longer afford to pay rent. Translators who’ve anxiously watched their work dry up and are scrambling to change careers late in life. Copywriters who are instructed by bosses to feed their writing into a program so an AI model can train to become their replacement.

One of the stories I thought I’d shared here was one I received was from a man named Jacques, who was the copy chief for a tech company’s website and support pages. He oversaw all the documents that helped users understand how to use its product, and how to troubleshoot when something went wrong. He sent me this story in early 2025. I’ll quote from him:

“AI didn’t quite kill my current job, but it does mean that most of my job is now training AI to do a job I would have previously trained humans to do. I have no idea how entry-level developers, support agents, or copywriters are supposed to become senior devs, support managers, or marketers when the experience required to ascend is no longer available.”

I followed up with Jacques six months later, and he told me his company had laid him off. “I was actually let go the week before Thanksgiving now that the AI was good enough,” he wrote.

None of the above cases are happening, it’s important to underline, because there’s an AGI that is suddenly better than humans at telling stories, writing copy, creating art. People overwhelmingly prefer the work of humans to AI, in fact. But as with every significant automation technology past, AI is alluring for the simple reason that it lets bosses cut labor costs and exert more control over their workplaces.

The concern is that this idea of AGI is helping to cover for the rote, mass automation of lots of jobs I think we really want people to be able to do; translator, artist, actor, writer, therapists, nurses, I could go on — and if we allow it to continue apace, society will be all the poorer, more polluted, and beholden to systems controlled by a relative handful billionaires in Silicon Valley.

Industry interests will always try to use new automation technologies to justify undermining labor. It’s a recurring theme through automation history. They will tell stories about its power, its exceptionalism, to try to escape scrutiny and accountability for what’s actually happening. But there is absolutely no reason that any technology should not be subject to democracy, should not be shaped by the very people who must live with it. Technology should be built to benefit everyone—not just the powerful.

A final note: People are not only anxious about AI but angry about how it’s being forced on them in their workplaces, and what management is using it to do to their livelihoods. You’ve probably heard form your constituents. I just want to relay that I hear it from my interview subjects, from workers, students, and members of civil society, nearly every day. There is a lot of political power to be found in building solidarity against extractive AI companies, big tech and in strong action to curb their worse impulses—even, sometimes, refusing it.

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Amazon is a major ICE contractor. Last year, it inked a $25 million deal to supply the agency with cloud compute services. As such, it makes for a compelling setting for a protest during tomorrow’s ICE out actions in Santa Monica. Details are below:

That’s it for this week. Take the day off tomorrow, and stay safe out there. Hammers up.

When ICE killed Rene Good, there was horror of a boundary transgressed. ICE was willing to shoot a white woman in the face, in broad daylight, for what amounted to a traffic violation, and the White House was willing to lie about it, lazily, in the face of all video evidence to the contrary. Still there was the dull shadow of relative novelty, the movements of a vehicle that could be willfully misinterpreted, the question of whether the administration would react to its overreach with any sort of correction, optical or otherwise.

With the execution of Pretti, there is horror of systematization. Horror that we are entering a new normal, of unaccountable, incontrovertible, open-air state-sanctioned terror. After Good’s death, the administration was explicit: federal immigration authorities would have “absolute immunity,” and now we know for certain that they will to use it.

A nurse in the intensive care unit at a veteran’s hospital, summarily executed in the street, in front of a half dozen iPhones taking video. Another deliberate and brazen lie of a statement from Kristi Noem, Stephen Miller, and the White House that contradicts every shred of evidence collected from multiple angles. So this is how it’s going to be. All of the pieces were on the table already, and now they have all been slotted together. Trump says he’ll only take ICE out of Minnesota if they hand over the voter rolls. The lines have been drawn.

At the very least, this is instructive. Take a look online. Whether state officials or rightwing influencers or tech billionaires or anonymous X reply guys, those willing to deploy pretzel logic to justify the shooting in the back of a man who had never made an act of aggression, or to subjugate logic itself to their ideology and brush the killing aside, behold our modern state propagandists. These are the voices party to the rise of actual, dyed-in-the wool, American fascism. These are the individuals and groups lining up to embrace Orwell’s famous edict1, denying their senses because the party tells them to, or on behalf of their hate.

This can be clarifying, understanding finally and fully that there is indeed already a large network of powerful and public figures willing to support unalloyed authoritarianism, no matter the injustices it perpetrates. You cannot argue with these parties on grounds that the excessive force and summary killings and detainments of American citizens is antidemocratic or unconstitutional, they do not care. That is not their project. You will never convince them with argument or evidence that their side cannot kill its enemies at will, and that too is clarifying. The pro-monarchist, anti-democratic voices in Silicon Valley have at least been open about this.

In Silicon Valley, the silence from the tech industry over the last two weeks has been deafening. There have been a few left-field voices condemning the ICE occupation and the killings of Rene Good and Alex Pretti—VC Paul Graham and former Meta AI chief Yann Lecunn among them—but the leadership and CEOs of big tech firms have all been silent. Some, like Khosla Ventures VC Keith Rabois and Palantir co-founder Joe Lonsdale, have been actively fanning the flames. After the Pretti killing, Rabois said that "no law enforcement has shot an innocent person. illegals are committing violent crimes everyday.”

We have discussed at length in these pages the bond between Silicon Valley and the White House, and on those terms, tech’s silence is unsurprising. OpenAI, Google, Anthropic, Microsoft; all of these companies have lucrative contracts with the federal government, to say nothing of tech defense contractors like Palantir and Anduril.

But now that the lines have been drawn, these tech companies and those who work for them have a decision to make: Do you continue to help build the architecture of authoritarianism? Last year, when the tech CEOs flew to the inauguration to stand applauding in the front row, it was not yet entirely clear the precise nature of the project their wealth, services, and clout would help enable. Now it is.

(After hearing nonstop outcry from the terminally online Silicon Valley set online over a proposed tax on billionaires in California, the quiet is particularly grating. Sometimes the shape of this moment is made all too painfully clear.)

OpenAI, Meta, Google, and others worked with the Trump administration to push a moratorium on AI laws, all but announcing their contentedness with an antidemocratic program. They’ve all donated large sums of money. OpenAI’s president Greg Brockman donated $25 million to a MAGA Super Pac directly. That money is supporting a government overseeing the execution of American citizens in the streets, the detainment of children as young as five years old, the filling of concentration camps with families wailing “let us out.”

Americans everywhere must weigh their personal responsibility in this moment, and some must weigh their complicity. I would like to believe ICE agents who joined believing Trump’s lies about an invasion of violent immigrants are quitting in droves after realizing they have instead joined an agency rife with death squads. I would like to believe that. I know people in communities around the nation are seeking out their neighbors, sending funds to mutual aid groups, and putting their bodies on the line in places like Minneapolis. You can donate to some of those efforts here. Find your own closer to home. Talk to your neighbors. Even if you are not political, get political.

I will add that if you work in Silicon Valley, you likely already know that AI in particular is uniquely important to Trump’s project—if you are not okay with what is happening, it’s time to consider what you can do to help slow or dismantle that project.

The lines have been drawn. American fascism—or authoritarianism, or autocracy, or whatever you want to call its equivalent—has materialized. This does not mean it will be invincible, or even durable. But it’s not going to relent without organizing, without struggle, without a fight.

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Follow ’s reporting from Minneapolis here. Read ’s guide to doing politics as a nonpolitical person here. Stay safe out there. But keep those hammers up.