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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Dendir also notes that

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

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

So what is VAR doing, then?

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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Some related reading:

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

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

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

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

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

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

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

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

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

404 Media reports:

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

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

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

Big data center resistance news:

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

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

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

The Guardian reports:

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

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

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

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

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

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

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

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

According to the Cowboy State Daily news:

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Until next time, everyone—hammers up.

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These days, this tendency is best exemplified by two of current-day Google’s defining traits: Its use of monopoly power to crush competitors that otherwise might offer a superior service and its headlong rush to replace core services with inferior AI products that promise to keep users on Google’s platform longer. Just this week, a court in Sweden ruled that the search giant owed $1.5 billion in damages for systematically favoring its own shopping service over PriceRunner, a Swedish eCommerce site.

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Meanwhile, Google’s shift to serving often faulty AI search results rather than its traditionally indexed links to direct sources continues apace, upending the very way information is delivered, obtained, and organized on the internet. As a result, a lot of people have had enough, and are looking for alternatives, not just to Google’s once-hallowed search engine, but all of its AI-saturated products.

I myself have begun the process of dislodging myself from Google, and will aim to do so to the fullest extent I can, and I’ll have a writeup of that process with some ideas, tips, and suggestions for anyone looking to do the same in short order. (The dark horse hardest-to-replace app? Google Docs.) But with Google in the news now, I looked to someone who’s got a head start: My good friend Paris Marx, the host of the foundational tech critical podcast Tech Won’t Save Us, and author of the forthcoming book Hyperscale, has been working to get himself off of US tech altogether.

Since Silicon Valley started openly and aggressively sidling up to Trump in 2025, and partnering with the federal government to help facilitate domestic surveillance, ICE operations, and military campaigns, Paris has been extricating himself not just from Google, but all US tech products, and writing about the process on his blog, Disconnect. As such, I thought I’d bring him on to the new podcast to discuss his own adventures in de-Googling.

We had a good and wide-ranging chat about why it is that what Google is doing with AI is so pernicious, especially to small businesses, independent journalists, and creatives of every stripe, and what alternatives to the monopolistic AI-all-the-time model might look like.

(This also happens to be the first interview we actually recorded for the new show, so viewers can enjoy the visual effect of my hair changing lengths throughout, as I got a cut shortly after my chat with Paris was recorded. Guess I should have used one of the surprisingly numerous AI hair filter apps to fix it in post.)

Also on the show this week, the data center rebellion expands to Canada, where hundreds, perhaps thousands of protestors took to the streets in Vancouver to oppose a slate of new projects approved in the region.

Meanwhile, the Summer of Ludd is underway in New York City, and I wish very much that I could be there for it. (Alas, I had another long-scheduled trip planned; my wife is teaching a semester in Paris this month, which is why I’m recording and writing all this from a short-term stay apartment that is decorated a bit like a college dorm room. If you’re in Paris and know of any luddite goings-on here, please do drop a line!)

The Ludd stuff looks amazing, it’s getting great press coverage, and if all works out, I’ll have one of the organizers on the show next week for a dispatch from on the ground. (I have a partial schedule of Summer of Ludd events in this edition of the newsletter, for those interested in joining in.) The pro-Luddite vibes aren’t limited to New York, however. A new Hily survey of single people finds, as Mashable puts it, that according to Gen Z and Millennial daters, “it’s sexy to be a Luddite.”

Sixty percent of Gen Z and 54 percent of millennials would find someone extremely attractive if they admitted to never using AI to make personal decisions, according to a Hily survey of 3,500 American Gen Z and millennial daters.

Meanwhile, 64 percent of Gen Z and 56 percent of millennial daters wouldn’t date someone who does. Even more (75 percent of Gen Z and 68 percent of millennials) would be immediately turned off if a date used AI to decide whether they should go on a second date.

Finally, Fox News has been absolutely banging on the drum that the data center protest movement is an astroturfed foreign conspiracy seeded by China-based business interests bent on destroying US tech companies. Politically speaking, it’s truly one of the dumbest lines of attack I’ve seen pursued, and one that seems more destined to fail than other rightwing efforts to generate moral panic—largely because half the people showing up to data center protests are conservatives themselves, who can see for themselves what nonsense it is.

Still, I plan on digging into this phenomenon in an upcoming piece, because, dumb as it is, it signals an escalation in the systematic effort to label anti-data center protestors domestic extremists by federal and local authorities, which could have actual legal ramifications. To that end, apologies again that I went light on writing this week; between hauling the fam to Europe, getting set up in the new place, and producing the new episode amid it all, there wasn’t as much time for writing as I’d have liked. I’ll be back at it next week, however. Promise.

Until then—hammers up.

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Last year, I recorded a few video interviews with folks like Karen Hao, Jacob Silverman, and Cory Doctorow, and enjoyed all of them. I kept intending to expand that facet of the newsletter, but it turns out starting a show is hard, and requires a lot of preparation, persistence, and help. I really became convinced it was worth trying for a couple reasons: First, the top ask I get from readers and folks I meet at events and so forth is, hands down, for an audio component to the newsletter. Where’s the podcast? etc. Well, here it is! This is for you.

Second, there’s just so much happening in the world BITM covers. So many people are organizing, resisting, and pushing back against the concentrating power of big tech and the AI industry. Exposing and interrogating its excesses. I personally have wanted a show that reflects how expansive and momentous this tendency is; that delivers a digest of regular updates on this wildly growing opposition to AI, Silicon Valley, and the tech oligarchy; a show that puts voices of workers, activists, journalists behind the mic.

Every week now, after all, people are protesting data centers that AI companies want to build in their backyards. They’re organizing workers in Silicon Valley, resisting AI’s encroachment into schools and the office, reclaiming public life from total social media saturation. This is the time of the Summer of Ludd, of the open booing of AI at college graduations. I’m hoping this show will help vividly document these movements and the people behind them. There are approximately one billion podcasts that highlight tech stories from a business perspective, and that host tech executives, AI advocates, and startup founders. This show is for everyone else; the folks in their crosshairs.

Our first guest is Molly White, a technologist, journalist, and writer of the great Citation Needed newsletter. We discuss the ballooning influence of AI and crypto money in politics, and her new project: Tech Influence Watch. It’s an ongoing effort to keep tabs on the hundreds of millions of dollars being spent by AI and crypto companies to sway our elections.

I mentioned that this show wouldn’t have happened without help; here’s a shout to everyone who has worked to get this thing off the ground. Ryan Hodes is the show’s producer; he’s the brains behind the critical tech YouTube show The Stories We Tell, and now he’ll be behind the boards at Blood in the Machine, too. Kate Osborn is our chief consultant and has whipped this thing into shape. Koren Shadmi did the killer cover art. Salman Al-Rashid’s support has made the production possible. The theme music is composed by me, with bass guitar from Ryan Hall, and audio engineering by Josh Gildardo Quintero at Metronome.

This is all something of a work in progress. A soft launch, if you will. We’re still experimenting with the approach and the format, so do let me know what you think in the comments, via email, etc. And yes, it’s video, too, something that I resisted even considering for a long time. But I was ultimately convinced—by Ryan, Kate, by my wife, who’s a media studies professor, and by readers—that video is simply where audiences live now. If you want to reach the most people, video it is. I was further consoled by Ryan’s bangup production job, and the way the format allows us to incorporate media elements like clips from data center protestors at town hall meetings, anti-AI campaigns from artists, and so on. It will of course live as a podcast, too, but I don’t know, maybe I’m coming around to the video thing. Maybe.

Note that the written edition isn’t going anywhere; the podcast is if anything meant to build off of it. There’s no separate written edition this week because my time and energy was sapped by prepping the launch of this pilot here.

I’ll end by adding that if any or all of this sounds interesting to you, if you like the sound of where the show is heading, please do consider becoming a paid supporter of BITM. This is an entirely independent project, and I can only do any of this thanks to the support of readers—of those subscribers that chip in a small sum each month. (Thank you, thank you.) If you find value here, think about joining their ranks, and support critical tech journalism.

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Okay, that should about cover the bases. Look forward to hearing everyone’s thoughts here. Hammers up.

Still, it’s really ramped up lately: US Catholic magazine ran an article called “A Luddite lesson in labor justice for our technocratic age.” The Nation had a feature titled “As AI Breathes Down Our Necks, It’s Time for a Luddite Renaissance.” And Psychology Today ran a story headlined “Pushing Back Against Technology: The Rise of Neo-Luddism. The subheading: “Will a less tech-obsessed routine become the next big healthy lifestyle choice?” The Distributed AI Research Institute is running a program called the Luddite Lab.

This week, NPR’s aired its “Word of the Week” segment, and three guesses what it was. They interviewed me for the spot, along with the historian Kevin Binfield and labor law scholar Miriam Cherry, and it’s a fun, informative piece.1 It was prompted in part by the Gen Z backlash to big tech, a subject covered by Hasan Minhaj in a show aired to his 2 million subscribers this week, and that also delves into the true history of the Luddites. (To my surprise, he clipped a section from a podcast episode I did with 404 Media—title: “The New Luddites”—so I showed up there too.) Both those shows were prompted, in turn, by the forthcoming Summer of Ludd, a series of events, protests, and performances organized by a band of self-proclaimed Luddites in New York City.2

Now, as it happens, also this week, I gave a talk at the Seoul AI Policy Conference, called Rethinking the Luddites in the Age of AI. I give this talk every so often, keeping it updated with an eye to the latest goings-on and resistances. (Its title is shamelessly ripped off of Kyle Chayka’s review of BITM, thanks Kyle.) Given that Luddites are apparently of widespread interest at the moment, I thought I’d share this latest version, lightly edited into text form. It serves as a crash course in the history of the real Luddites, what they really fought for, and why they matter more than ever as companies with immense wealth and power seek to use AI to reshape our working and social lives.

As always, all of this work is made possible by my subscribers, a small fraction of whom chip in a few bucks a month so I can keep the lights on here. If you find value in my writing, reporting, and analysis here, please consider becoming a paid supporter so I can continue doing all of the above. I’m 100% independent, and reliant on subscribers to keep this newsletter going. There’s been a string of cancellations lately; many, sadly, cite AI-related job loss, so I could use the boost. Many thanks, and hammers up.

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Now, onto the Luddites:

When the US senator Bernie Sanders proposed a moratorium on the construction of new AI data centers this year, the Washington Post compared him to a Luddite. “A national ban on new AI data centers would make the Luddites look good,” the paper’s editorial board wrote.

The conservative pundit Ben Shapiro called Sanders’ critiques of AI “Luddite, anti-tech nonsense.” A think tank analyst labeled him a “neo-Luddite” who was “de facto calling for America’s surrender.”

“Luddite.” The word’s been circulating a lot lately, as investment in AI has reached historic heights, chatbots and enterprise AI have pervaded daily life, and more and more people have been speaking up about the drawbacks and dangers of the technology and the firms behind it.

“Luddite.” You may have heard the word used to describe AI critics, aggrieved workers, data center protestors, or those like Sanders, who advocate reining in AI companies, regulating their products, or putting checks on their power.

Its meaning, in these cases, is clear: It’s an insult. A Luddite is supposed to be anti-technology, naive, backwards, anti-progress.

And, surprise, the AI products enforce the idea. Here’s how ChatGPT defines it, when prompted: “A Luddite is a person who is opposed to, distrustful of, or reluctant to use new technology.”

Here’s Google: “A Luddite is a term for someone who is opposed to or resistant to new technologies, especially automation and computerization.”

Now, these AI-generated responses do reflect how the Luddites are commonly understood today. After all, large language models draw their responses from the inputs they’ve been trained on, and a lot of writing over the last two centuries has sought to define a ‘Luddite’ the way the chatbots do now.

But the pundits and the chatbots all get it wrong: The real Luddites—the machine breakers who rose up at the dawn of the first Industrial Revolution to smash the looms and wide frames that factory owners were using to automate their labor—were not opposed to technology. They were opposed to the way technology was being used against them. That is, the Luddites objected to the industrialists who used machinery to depress wages, evade labor laws, and degrade the quality of products in order to profit at their expense.

It was, and remains, an eminently reasonable objection. The real Luddites were not know-nothing technophobes, despite their current reputation, and they certainly did not hate technology. In fact, many were technicians themselves, and understood better than most exactly how a technology would be used to exploit them. It was the rational and just thing to do, to object to the use of industrialist machinery to reshape their working lives and their communities.

Not only that, but their objections were informed, popular, and, for a time, effective. The Luddites organized a tactical rebellion that terrified elites and won the favor of the working class. People cheered them in the streets; hymns were sung about them in pubs. Lord Byron wrote poems about them. For a few years, they were more beloved than Robin Hood.

If we are to truly understand the impacts of mass automation technologies like AI, and why there’s a vociferous and fast-growing backlash to it, then it’s crucial that we rethink our dismissal of the Luddites. We must understand their actual history; why they turned to machine breaking and what they really fought for.

After all, we now sit on the precipice of a moment where backlash to a mass automation technology threatens to boil over again.

So who were the real Luddites? To understand them properly, we need a little background first.

In the 1700s and early 1800s, clothworkers constituted the largest industrial workforce in England apart from agriculture. Hundreds of thousands of people were employed, from Nottingham to Leeds to Manchester, as knitters, weavers, croppers, and spinners.

These clothworkers largely worked under what’s known as the domestic system; the artisans worked at home or in small shops, alongside their families or peers. Most were what we would describe today as working or middle class. They were not particularly wealthy or prosperous, and times could be lean if demand for cloth goods shifted, but many owned cottages, worked 30-hour workweeks, and had the autonomy to organize their workdays as they saw fit. They were free to sing songs at the loom as they worked with their families, or to take breaks to walk in the garden. Others labored in local shops with friends and colleagues they’d known all their lives. These were the days of the original “cottage industry,” and, in fact, it’s where the term hails from.

As the Industrial Revolution dawned, the early entrepreneurs3 began using automated machinery to speed up the labor process, and to organize production into the first factories. These machines, like the spinning jenny, the wide frame, the gig mill, and later the power loom, enabled factory owners to pursue mass production. The machines did not improve the quality of the product, and rather, often dramatically diminished it. But the more automated machinery could be overseen by untrained workers, so they reduced labor costs, even though this practice was often illegal: There were standards and laws that governed the cloth trade, that regulated things like thread count and product quality, as well as how long a worker had to serve as an apprentice before they could join the trade. Industrialists largely ignored these laws, in an early iteration of the ‘Move Fast and Break Things’ ethos popularized by Facebook in our time.

By employing a host of cheaper, untrained laborers, which often included children indentured from orphanages and poor families, and focusing on volume, not quality, the industrialist could drive down prices, corner markets and run skilled workers out of business.

As the 18th century wound down and the 19th began, the wages for clothworkers and artisans were plummeting. Early factory owners were concentrating wealth and power, enabling them to institute punishing working conditions and policies like paying workers in truck, or in goods produced by the factory, rather than money.

Clothworkers, their wages in free fall, organized a campaign to push Parliament to address their concerns: They asked for protections like a minimum wage, a ban on paying workers in truck, and for factory owners to simply follow the laws that were already on the books. Some also submitted novel proposals, like taxing the extra length of cloth produced by automated machinery, and using the proceeds to fund welfare and training programs for workers—proposals that look a lot like ‘robot taxes’ suggested today. Tens of thousands of clothworkers signed petitions calling for basic worker protections.

You may already have guessed what happened next: They were roundly ignored.

It’s important to underline this point. For nearly ten straight years, for much of the first decade of the 1800s, cloth workers tried to protest and petition peaceably, to do tings “the right way”, even though their options for recourse were severely limited. Unionizing, or ‘combining’, was illegal in England at the time, so they couldn’t collectively bargain. There was no true democracy, no elected officials to hold accountable for allowing exploitation to continue unabated.

Eventually Parliament sided with the factory owners and threw out the remaining regulations governing the trade altogether. With thousands of workers impoverished to the point that they could not feed their families, and their backs against the wall, the Luddites rose up.

In Nottingham, in 1811, and drawing from a local tradition of dissent and, almost certainly, from the legend of Robin Hood, clothworkers who could bear no more launched a campaign targeting the worst offenders, those industrialists who paid the lowest wages and abused workers the most. They organized under the banner of Ned Ludd, an almost certainly fictitious avatar said to be an apprentice cloth worker. The legend went that Ned’s master had him whipped for being unproductive, so he smashed the master’s frames and fled into Sherwood forest.

The Luddites wrote letters to factory bosses warning them to take down the ‘obnoxious’ machines that had stolen the bread from their brothers’ mouths. If they didn’t, Ned Ludd’s army showed up: a handful, dozens or even hundreds of men, organized in military formation, answering by assigned numbers, not names. They would sneak in through the windows or hold up the overseer at gunpoint, and methodically smash just those machines that were deskilling their work; just the ones being used to tear up the social contract. They left the machines that were not being used to, say, automate their jobs or facilitate child labor, alone. But they would exit with a warning; bring them back, and we’ll return to do the whole place.

They were remarkably successful, for a time. After the initial outbreak of Luddism, factory bosses initially raised wages and negotiated deals with the workers, eager to protect their operations. They became heroes to many fellow workers, for fighting back against factorization and exploitation, for standing up to the powerful. When authorities demanded names of the Luddites perpetrating the machine-breaking, whole towns would stay silent; even when huge bounties were offered, no one came forward.

Ultimately, Luddism didn’t fizzle out because it was unpopular; it was crushed by the state. The Prince Regent’s government deployed thousands of troops to the industrial districts alight with Luddite activity. It was the biggest domestic occupation in British history. Parliament passed laws that made it a capital crime to break a machine, or to take secret oaths, essentially making being a Luddite a crime punishable by death. (Lord Byron made his first speech to the house of Lords in a thunderous defense of the Luddites, but was ignored by his peers, if not the public.)

As a result, scores of Luddites were hung by the state, and many others were killed in riots and raids as the factory owners grew emboldened to take up arms against them. Luddism died out by the end of the 1810s, but not before it helped to inspire Mary Shelley’s Frankenstein, a new generation of labor organizing, and paved the way for a raft of serious reforms like the overturning of the anti-union laws.

And yet, the Luddites today are still remembered as a punchline. As the cultural critic Theodore Rozak put it, “if the Luddites didn’t exist, their critics would have to invent them.” And to an extent, elites have done exactly this. By continually insisting that any criticism, objection, or resistance to commercial technologies are backwards looking, by linking objections to worker exploitation, antitrust violations, and surveillance to the Luddites, who dramatically lost their battle, they have turned a powerful working class movement with specific grievances about technological exploitation—and ideas about how to address it—into a caricature.

That caricature is the reason that Bernie Sanders’ ideas for regulating AI development, or pausing the breakneck data center expansion (an incredibly popular political proposition, by the way) gets him slapped with the term, derisively. Sanders himself felt compelled, as many do, to respond to the accusations in the defensive. He wrote, in an op-ed for Fox News, “Can AI and robotics help us in many ways? I am not a Luddite — I believe they can.” He argued that “we must make sure these new technologies benefit all of us, not just a handful of billionaires.”

But that’s exactly what the Luddites would have wanted. Sanders is a luddite, after all. Because the Luddites do not deserve derision; they deserve our empathy, even our admiration. They refused to “lay down and die” as the elites of the day might have hoped they would, and as the historian Frank Peel put it—and fought for workers’ rights despite everything.

What the Luddites fought for, after all, was ultimately pretty straightforward:

• Fair wages

• Checks on fraud and abuse

• A working life in which they maintained dignity and personal autonomy

• A seat at the table in deciding how technology would be used in their workplaces and communities

• To put down, not all machinery, but, as they put it in one of their most famous letter, “the machinery hurtful to commonality”

The Luddites were not against progress or anti-technology. They were against exploitation; they were anti-poverty.

Only when wages were pushed so low that workers could not feed their families, when the indignity of soulless factory work looked inevitable, when fraud and exploitation ran rampant, and they had exhausted every avenue to have their voices heard did the Luddites take up their hammer.

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We have arrived at another such moment, where concern, discontent, even anger over a new mass automation technology is on the rise. There is talk of a new Industrial Revolution, on a scale of the first or beyond. Tech giants and venture capitalists have poured hundreds of billions of dollars into AI firms, again concentrating wealth and power in a few controlling hands. The CEOs of those companies, meanwhile, are promising to replace millions of jobs with their software.

Now, countless college graduates, software engineers, artists, writers, and translators describe a world of vanishing career opportunities. Fortune 500 companies are enacting mass layoffs—and blaming them on AI—every few months. Protests against the tech giants’ data centers have erupted across the United States and beyond. Artists and authors are pursuing class action lawsuits against the AI companies for pirating, copying, and using their work to train their models without consent or compensation.

These are not isolated incidents. A recent NBC poll found that 46% of respondents in the US had a negative view of AI, compared to 26% with a positive one. AI had a stunning net favorability rating among young people, those aged 18-34, of minus 44. Those young people can be seen in multiple viral videos, booing any commencement speakers at their college graduations who dare cheer on AI as the future.

Are all of these people Luddites? The artists filing class action lawsuits, students booing AI on college campuses, the farmers protesting data centers in the American south? Luddites, all?

Well, yes.

That is, if we mean the historically accurate definition of Luddite, not the caricature their critics have made them. However different their background, age, or politics, each of these groups have decided they are unwilling to let a handful of powerful companies determine the shape of their future—their working lives, the fabric of their community, their way of life—without a challenge.

Like the original Luddites, they’re demanding a seat at the table as a new technology is integrated into society, and aiming to stop the bosses from using that technology to exploit them. There’s even a growing contingent of artists, workers, and thinkers who proudly embrace the Luddite label, adding the term to social media bios and sporting it on T-shirts. A group of students and activists have organized a weeks-long event series in New York called the Summer of Ludd.

Also like the original Luddites, the opposition is usually not a blanket rejection of the technology itself. It’s focused on the politics of that technology: How it’s made, who it benefits, and who it harms.

The anger over AI arises not from the mere existence of large language models, but over the fact that they were trained on works without creators consent. That billionaire executives are promising to use them to automate jobs en masse. That they are harmful or addictive to kids and the vulnerable. That in many parts of the world, the technology is almost completely unregulated. There’s anger that AI companies, like the factory owners two hundred years ago, aspire to be impervious to democracy.

A big question of the AI age, to me, is whether it’s possible to subject the ultra-powerful interests currently guiding AI deployment—Elon Musk, the CEO of one major AI company, just became the world’s first trillionaire, for one—to a truly democratic process. A process that empowers and protects working people. And if so, how?

In the United States, the AI companies are lobbying to kill state level AI laws, accelerate the data center buildout, and elude regulation. They are pouring hundreds of millions of dollars into an effort to subvert democracy itself, as it pertains to their products. Can you hear the echoes yet? I can: There have already been multiple instances of violence; a man threw a molotov cocktail at OpenAI CEO Sam Altman’s house. Two others fired a shot outside it. In Indianapolis, a city council member who voted to approve a data center over the opposition of his community woke up to find his front door shot up, and a message that read ‘NO DATA CENTERS’ on his porch.

Two hundred years ago, factory owners and their supporters in Parliament wholly ignored the repeated entreaties from workers and citizens to give them a voice, to protect them from deskilling, displacement, and poverty, and instead tore up remaining labor laws and abetted the full-bore acceleration of mass automation on the industrialists’ terms. The result was a violent crisis that brought Britain to the brink, followed by decades marked by some of the darkest days for industrial workers we’ve known.

Now, there is no indication that a crisis of that magnitude is imminent. We don’t yet know what the long term impact of AI will be, whether it will be an excuse to lay off thousands of workers to trim balance sheets in the short term, used to supplant millions more permanently, or somewhere in between. We do know that it will be used to surveil workers, speed-up work, and be used as leverage against them. That’s already happening, right now. And we at least theoretically possess the tools to prevent sustained violent blowback—democracy, labor laws, and collective bargaining, to start, though the weakening of each is cause for alarm. So is the entrenchment of income inequality, the rise of a tech oligarchy, and the erosion of human rights.

But we must be attentive to history; the real thing, not the sloganized version remodeled to benefit power. Returning to the Luddites reminds us that above all, workers and users must have a seat at the table. We need a real say, real empowerment, real agency over any technology that is made to reshape our workplaces, communities, and lives. And yes, we all deserve the right to break any machinery that proves hurtful to commonality.

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NEXT WEEK, If all goes according to plan, we’ll soft launch the slightly more official and definitely more regular version BLOOD IN THE MACHINE: THE PODCAST. Friend of the Blood Koren Shadmi has whipped up some killer cover art, and I’m pretty enthused. More very soon.

Some friends at the California Labor Federation passed along this call from the California Governor for testimonies as to how AI has impacted your working life. The accounts will allegedly be used to help shape policy, so in the interest of ensuring workers are represented among the inevitable deluge of pro-AI stories solicited by the firms, consider participating and evening the scales.

Finally, a couple must reads here, too:

-Fred Turner, author of From Counterculture to Cyberculture, the seminal study of Silicon Valley, has a new piece in the Baffler arguing that the California Ideology—the blend of hippie/back-to-the-land countercultural tendencies and libertarian, pro-market politics that came to define the modern tech sector—has been edged out in favor of the Texan Ideology; a nativist, extractivist tendency comprised of Christian nativism and a will to dominate. It’s short and good!

-Dell Cameron has some great reporting in WIRED about Peter Thiel’s weird Dialog project, a “secret society” of rich and famous people who join for an off the record annual meeting, whose names have now been made public. These include an apparently flummoxed Josh Brolin and, for some reason, Ezra Klein. Abundance knows no bounds, I guess.

OK OK OK. That’s it for today. Many thanks as always for reading, and I’ll see you out there in the Summer of Ludd.

Apparently two months’ of protection from the ultra-AI is all the safeguarding we needed. Interestingly, that’s precisely the amount of time that it took Anthropic to translate the press attention around Mythos into a historic $65 billion funding round. What a coincidence. According to its marketing materials, Anthropic’s Claude Fable 5, is a “Mythos-class model” that has been “made safe for general use,” and will be on offer to “organizations taking on their hardest knowledge and coding work.” It’s available now “on the consumption-based Enterprise plan.”

It’s hard for me to exaggerate how shameless this is. Has there ever been a more successful marketing campaign, one that yielded so many billions of investment in so short a time? The Mythos campaign is nothing less than the ne plus ultra of AI ‘doom marketing’, the practice that has helped animate the entire AI boom, and that sees tech companies drum up investor and media interest in their products by registering harrowing claims about the threats those products pose to jobs, norms, even humanity’s very existence. And the media fell for it, hook, line, and sinker.

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TODAY in BITM: The anatomy of Anthropic’s disturbingly successful doom marketing campaign. Plus, Elon Musk is a trillionaire after years of his own science fictional marketing efforts, the SUMMER OF LUDD is coming to New York City, and the first-ever D&D game inspired by BLOOD IN THE MACHINE.

As always, this work is made possible by subscribers who chip in each month to help me keep the lights on. If you find value in this reporting and writing—in 100% independent human-made media that holds the AI firms and big tech accountable—consider becoming a paid supporter. A huge thanks to all of you who back me up; I couldn’t do any of this without you.

Now, I know I just spent a whole edition dissecting Anthropic’s press strategy and how it used AI ethics slop to vault itself into the top AI lab slot. But this is just such a perfect doom marketing case study, arriving no fewer than three years after ChatGPT, to boot, when you’d think more folks might be inoculated against self-serving AI company hype, that it demands to be examined in detail. Anthropic’s Mythos stunt takes the cake on every front: Its sheer cynicism, rank opportunism, and, yes, its ultimate effectiveness.

Behold, the anatomy of a successful, trillion dollar company-making doom marketing campaign:

1. On April 7th, 2026, Anthropic announced that it had built a new AI model called Mythos that “could reshape cybersecurity” and was too powerful to release to the public. Instead, it would be overseen by a consortium of hand-picked tech companies given the cyberpunk-aping name Project Glasswing. “We do not plan to make Claude Mythos Preview generally available, but our eventual goal is to enable our users to safely deploy Mythos-class models at scale,” Anthropic and the consortium note in the announcement. “To do so, we need to make progress in developing cybersecurity (and other) safeguards that detect and block the model’s most dangerous outputs… allowing us to improve and refine them with a model that does not pose the same level of risk as Mythos Preview.” The subtext, that businesses and users will need this next-level powerful AI, is as subtle as a sledgehammer.

2. The announcement was made via a slick website with some documentary-style sponcon featuring Tech Luminaries intoning about how important cybersecurity is and how AI (and specifically, Anthropic’s new Mythos product) is disrupting it.

3. Anthropic (and the other top tech companies that stand to benefit from the marketing of a new AI product) then encourage the “too dangerous to release” narrative, perhaps best encapsulated by this Thomas Friedman New York Times column, titled “Anthropic’s Restraint Is a Terrifying Warning Sign.” The column runs April 7th, the same day as the Mythos announcement, meaning Friedman was offered the story well in advance. “Holy cow!” he writes, “Superintelligent A.I. is arriving faster than anticipated, at least in this area. We knew it was getting amazingly good at enabling anyone, no matter how computer literate, to write software code. But even Anthropic reportedly did not anticipate that it would get this good, this fast, at finding ways to find and exploit flaws in existing code.” He raises the possibility that kids might use Mythos to take the electrical grid offline before dinner. Scary stuff! His story also contains the sentence “This is not a publicity stunt,” which is the sort of thing I often find myself having to write about events that are definitely not publicity stunts.

4. The rest of that week in April is filled with subsequent reports about Mythos, the too-dangerous-to-release model, elaborating on the cybersecurity concerns raised by the model’s existence from news outlets like CBS (“Why Anthropic is saying its new AI model, Mythos, is too dangerous to release”), ABC (“Is Anthropic’s Mythos AI too dangerous for users?”), the Times (“You Can’t Use This A.I.”), and Bloomberg (“How Anthropic Learned Mythos Was Too Dangerous for the Wild”). To name a few.

5. Anthropic generates both attention, buzz, and goodwill from the press cycle, furthering its reputation as the “ethical” startup, and the foil to the reckless ambitions of chief rival OpenAI, typified by this Bloomberg Opinion headline, “With Mythos, Deserves Support, Not Blacklisting,” which argues Anthropic is doing AI the “right” way.

6. Anthropic’s pomp and media campaigning successfully obscure the skepticism that brews in the cybersecurity community over its grandiose narrative. By late April, security professionals are roundly criticizing the AI lab’s Mythos claims. Dr. Heidy Kalaf raised red flags about the nondisclosure of false positives, and the way Anthropic was presenting its ‘data’. One developer—a fan of the company, no less—concluded that while Mythos did find some real bugs, the findings were so overinflated as to essentially be “built on misinformation.” The cybersecurity-focused news outlet The Register, meanwhile, declared that “Anthropic’s super-scary bug hunting model Mythos is shaping up to be a nothingburger.”

7. The criticism barely reaches the level of background noise, and Anthropic pushes on with its narrative. On May 22nd, Anthropic issues a press release, “Project Glasswing: An initial update” that claims, without seriously addressing most of the critics’ concerns, that Mythos has been used to find “more than ten thousand high- or critical-severity vulnerabilities across the most systemically important software in the world.”

8. On May 25th, Anthropic co-founder Chris Olah turns up at the Vatican for the release of Pope Leo XIV’s encyclical on AI, on the winds of its burnished reputation as the AI company with humanity’s interests at heart.

9. On May 28th, Anthropic announces it has closed a $65 billion series H funding round that makes it worth nearly $1 trillion and the most valuable AI company in the world, edging out OpenAI.

10. On June 9th, two months after the initial announcement, Anthropic makes its “Mythos-class” AI model available to the public, or at least, anyone with an Enterprise account: “Today we’re launching Claude Fable 5: a Mythos-class¹ model that we’ve made safe for general use.”

As a nice little cherry on top to the whole affair, the guardrails that Anthropic has put up to make it “safe for general use” are so prohibitive that you can’t use it for cybersecurity at all. AKA you can’t use it to do the thing Anthropic has spent the last two months relentlessly hyping; incidentally, users also can’t evaluate whether or not it’s as powerful they claimed, or if the hype was in any way warranted.

To me, this really gives away the game. Of course the doom marketing campaign was never aimed at cybersecurity pros (not least because they’re the ones best equipped to immediately start poking holes in the bigger claims), but the public at large. That’s where the narrative might truly resonate; among those with less of a grasp on the particulars of what the AI model built to find flaws in cybersecurity systems could or could not actually do. We’re left with the story that this big scary powerful AI has been tamed enough for use by business professionals and software engineers—not for cybersecurity purposes, it’s still too powerful for that; but for everything else—who can now access it as part of an enterprise software automation product.

As has noted, the public release of Mythos comes at a time when a lot of companies are rethinking their AI spend, which continues to yield dubious ROI. In this light the launch can be seen as another way to keep more clients on the hook, at least until that IPO rolls around. Marcus also points out that one reason Anthropic may be better than anyone else in the biz at doom marketing is that its executives were at OpenAI when they pulled off one of the pioneering PR stunts of the genre, via their solemn non-release of an earlier ChatGPT model in 2019, withholding that from the public because it was—guess why!!!!—too dangerous.

In Anthropic’s defense, it did exactly what it said it was going to do: release an AI model with the same branding as the allegedly world-upending one it spent two months expertly doom-marketing. The annoying thing is that the company pulled it all off. They won. They exploited the media’s inability to pass up a big scary AI narrative with a nominally novel twist (cybersecurity vulnerabilities), to such success that, months later, even putatively smart people like the historian Rutger Bergman are earnestly describing Mythos as “an insanely powerful model capable of hacking anything from power grids to water systems,” despite this being one of the clearest-cut cases of obvious AI product marketing I have seen in my years of covering this industry.

Anthropic leveraged its reputational capital to take a big swing, and the media and investors ate it up. Anthropic doled out its AI ethics slop so expertly that they were able to parlay that positive press from their morally calibrated Mythos non-release into an audience with the Pope, a record-breaking funding round, an IPO, and the much-hyped sale of a new product. (Again, for more details on this broader story, see my last post on Anthropic’s weaponizing of its ethical AI reputation and my chat with NPR’s On the Media about the same topic).

It’s safe to say that Anthropic is not facing nearly enough scrutiny for this admittedly expertly manufactured bit of AI fabulism, and the role it has played in helping to cement the company’s newfound status as the leading AI company. Mythos—def.: “myth, mythology”— indeed.

The world’s first trillionaire is also a world-class mythologizer

You may have heard about this SpaceX IPO thing. As expected, it’s enormous, and it has minted the world’s first trillionaire in Elon Musk.

Musk has been a force in a lot of novel lines of business, that’s undeniable—privatized rocketry, electric cars, MechaHitler assembly—but arguably his biggest innovation of all has been the relentless science fictionalization of capitalism itself. He has learned over the years how to tell grandiose stories abut the future that appeal to investors and consumers, and how to effectively ignore the stories among those that don’t come true. (He is also responsible for the deaths of literally hundreds of thousands of people.) There were supposed to be thousands of electric robotaxis on the road right now, Teslas were supposed to be fully autonomous, and an army of humanoid butlers are set to walk into our homes any day now.

To this end, the SpaceX IPO in particular was buffeted by tales of orbital data centers (scheduled to arrive in just a few years!) and nothing less than incoming MOON BASES. Again, this sort of fabulizing is abetted, even made possible by an all-too credulous media. Here is how SpaceX defines its mission in its SEC filing:

Our mission is to build the systems and technologies necessary to make life multiplanetary, to understand the true nature of the universe, and to extend the light of consciousness to the stars. To do this, we have formed the most ambitious, vertically integrated innovation engine on (and off) Earth with unmatched capabilities to rapidly manufacture and launch space-based communications that connect the world, to harness the Sun to power a truth-seeking artificial intelligence that advances scientific discovery, and ultimately to build a base on the Moon and cities on other planets.

This industrial scale science fictionalizing is evident in the DNA of every major AI company, from OpenAI promising an artificial general intelligence that would transform the fabric of the world to Anthropic promising that it’s the only one that can safely contain the AI doing all that transforming. Musk is a key reason the companies can get away with putting their speculative narrativizing over having anything resembling a credible business model; he got away with it, for years, first.

In a review of Quinn Slobodian and Ben Tarnoff’s new book, Muskism, cuts to the heart of what that means in the context of the SpaceX IPO:

All this is held together by an ideology that seems to be at its peak right now. The SpaceX IPO marks the massive expansionary inflation of an entirely imaginary universe. As far as I can tell, no-one actually believes that SpaceX is going to capture its roughly-$23 trillion “total addressable market,” which as Matt Levine points out is “perhaps 20% of the world’s economic output and perhaps 40% of the revenue of the world’s corporations.” But there are lots of people who are willing to go along for the ride for the moment, as long as other people are willing as well.

How long this imaginary universe can possibly expand as the fleets of robotaxis and humanoid butlers and orbital data centers and moon bases—not to mention all-powerful AGI—fail to materialize is another question altogether, and one with possibly severe ramifications for the global economy.

New Yorkers, get ready for the Summer of Ludd

This is a beautiful, beautiful thing, and I’m bummed that I won’t be in New York to experience it. But for those who live in the area, there’s a whole slate of Luddite activity planned across the city—talks, plays, music, conferences, protests—and it looks delightful. There’s even a “Luddite hotline” you can call. One of the organizers sent me the mission statement, which, fittingly, isn’t posted to social media or anywhere else online, so I’ll just share it (with some LIGHT editing for length) here:

GET READY FOR...

THE SUMMER OF LUDD

JUNE 28th – JULY 5th, 2026

More than 120 events will take place across New York City, affirming in-person connection and rejecting the corrosive effects of algorithmic technologies

The first-ever, free-to-the-public SUMMER OF LUDD will take place in New York City from June 28th to July 5th, 2026. Drawing from a rich tradition of social movements and growing out of a burgeoning community of hundreds of organizers, artists, and concerned citizens, the SUMMER OF LUDD will be a joyous celebration of the organic and unpredictable connections that arise and flourish when we reject the extractive surveillance technologies that have increasingly come to dominate our lives.

New York City has become the national center of a dynamic “Luddite Renaissance” that expresses itself in kaleidoscopic prose, political activism, poetry, phone-free dance parties, app deletion events, Luddite tribunals that put tech on trial, and other events of refreshing relevance, all aimed at getting people off Big Tech platforms and into public space.

The SUMMER OF LUDD will include more than 120 events at assorted venues throughout New York City — a weeklong “movable feast” with ongoing, and often simultaneous, pop-up actions such as teach-ins, an original theatrical production telling the story of the original Luddites, a concert series, film screenings, ritualistic ceremonies, workshops, and actions against Big Tech platforms — including the flagship S.H.I.T.P.H.O.N.E. (Scathing Hatred of Information Technology and the Passionate Hemorrhaging of Our Neoliberal Experience) event. The festival will connect the dots between addictive algorithms, social isolation, data center ecocide, automated warfare, job loss, data extraction and surveillance, and accelerating inequity.

In conjunction with the festival, The New School will host the Luddite Conference on Participatory Futures from 10 a.m. to 3 p.m. on June 30th... Admission is free and open to the public, but advance registration is required. Learn more and register to attend here.

The SUMMER OF LUDD is a big tent gathering that welcomes all New Yorkers and anyone who has questioned the role technology plays in their lives. It is a 100% social media-free celebration… Tompkins Square Park will serve as the festival’s home base, and free lunch will be served there daily at 12:30 p.m. starting on Monday, June 29th.

In the run-up to the SUMMER OF LUDD, there will be a press conference on June 23 at 6 p.m. at Tompkins Square Park. This press conference will feature Gowanus the Media Puppet. Additional press conference details will be provided in a forthcoming media advisory.

LEARN MORE ABOUT THE SUMMER OF LUDD:

• To get a printed program guidebook detailing the 120+ SUMMER OF LUDD events, please reach out to theofficialsummerofludd@proton.me.

• Printed guidebooks will be available at independent community spaces, arts venues, and other cultural gathering places throughout New York City.

• The SUMMER OF LUDD does not have a website. Updates about programming can be accessed by calling the Luddite Hotline at (347) 814-5194. This hotline will be updated daily during the festival week with event schedules and other announcements.
  

  KEY DATES:

• June 23 – SUMMER OF LUDD press conference at 6 p.m., Tompkins Square Park

• June 28 – Festival begins; theatrical production of Luddite Recreations at 5 p.m., Tompkins Square Park

• June 30 – The Luddite Conference on Participatory Futures, 10 a.m. to 3 p.m. at the New School. Free to the public, advance RSVP required.

• July 4 – S.H.I.T.P.H.O.N.E., 2 p.m., beginning at Tompkins Square Park

• July 5 – Closing Ceremony (Lady Ludd guides us into the future), 5 p.m., Tompkins Square Park

  Who were the Luddites?

  The original Luddites of the 1810s were skilled textile workers who resisted early forms of automation. The tech titans of the Industrial Revolution fractured the lives of workers, by replacing them with automated machinery. This upheaval inspired ten years of civil protest. As a last resort, facing starvation, the Luddites broke the machines, under the banner of their folkloric hero, Ned Ludd. Despite widespread support, the Luddite movement was crushed by the British Crown, and their leaders executed—all in the name of “progress.”
  
  Today’s tech oligarchs — under the same guise of “progress” — accumulate obscene wealth and power at the expense of our agency, employment, privacy, and natural environment.

  
  Algorithms stunt our imagination and sense of what’s possible. The SUMMER OF LUDD restores our capacity to imagine and shape a life-affirming future.

  
  All events are free!

  
  All events are participatory! All generations are welcome!

  
  PROMOTIONS FOR THE SUMMER OF LUDD ARE 100% SOCIAL MEDIA-FREE.

Blood in the Machine has inspired a D&D game

Last, but certainly not least, something very cool: Apparently, a tabletop game designer read Blood in the Machine: The Book, and was inspired to create their own dark fantasy twist on the Luddite saga. The creator reached out, and I said I’d be happy to share the story of the game’s genesis. If you create work inspired by BITM, you get free promo on the blog, it’s just science, I don’t make the rules. So here’s Ben’s story:

Hello! I’m Ben Somers, the primary person behind Somanyrobots Games. I’m an indie tabletop role-playing game developer; specifically, I write books for Dungeons & Dragons, giving players more options and more content they can use in their games.

Before this, though, I worked for a decade and a half in tech, mostly startups, in a wide range of software engineering jobs. By the time I left, LLM-assisted coding was just starting to show up, and the overriding advice to developers was “use it for hobby projects, but you can’t use it at work; we don’t want plagiarized code showing up in our products”. It is wild how the entire software industry has now smashed through that wall like the Kool-Aid Man.

When I shifted to writing D&D books instead, it was with a huge sigh of relief. And, not for nothing, a little pang of guilt. I did what I could to keep AI from taking over (and ruining) my industry, but now it’s a fight I’ve firmly left behind. My first book was about seafaring adventures, mostly apolitical, and was very much an escape from our uncomfortable world. Which is why I got such a bolt of lightning when I read Blood in the Machine!

The story of the Luddites resonated with me deeply, but it also gave me an immediate hook to hang a fantasy world on. Most sword-and-sorcery games don’t have a lot of space to fit an Industrial Revolution in;. But what if I took the dehumanization of those proto-factories and pushed it even farther? If I carried the industrialist’s disregard for human life to its brutal conclusion? In short, what if you had a factory that ran on souls instead of steam?

My new book, Machines of Bone & Blood, depicts a world where necromancers build looms and mills out of bone, attaching skeletal limbs so the machines can operate themselves. Workers are put out to pasture, except for the miserable few that graft undead parts onto their own bodies in order to keep pace. Glorious necrobarons reap the profits, becoming fabulously wealthy by virtue of their proximity to this blasphemous power. In the meantime, workers in cottages form alliances with primeval druids to try and tear down the whole horrible system.

This idea, of an industry literally burning up human souls, doesn’t and shouldn’t feel unfamiliar. Machines of Bone & Blood recasts the industrialists—the tech titans—as necromancers, and if anything, this undersells their moral depravity; nobody would buy a game book about enslaving orphans like Robert Blincoe into 14-hour factory shifts. But it gives me an avenue to write some compelling game options while also telling a story about dehumanization and the horror of unregulated technology. And it gives players of the game an avenue for fighting back, telling stories about trampled workers striking back by tearing down the factories and smashing up the machinery.

Excellent.

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Finally finally finally, check out Molly White’s new project, Tech Influence Watch, which tracks the money crypto and AI firms are pouring into federal elections. I’d like to talk with Molly more about this work in the future, but it’s a great project that should be on your radar right now.

OK, enough of my ramblings for today. Thanks for reading everyone, and see you next week. As always—and maybe now more than ever—keep those hammers up.

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TODAY in BITM: An exclusive report from a data scientist who crunched the numbers on who’s blocking data centers and how successful the protests have been, exactly. Plus, some thoughts on Bernie’s ill-fated AI sovereign wealth fund idea, Ted Chiang’s argument that AI is definitely not conscious, and more.

This work is made possible by subscribers who chip in a small sum each month to help me keep the lights on. If you find value in this kind of reporting and analysis, in 100% independent media that holds the AI firms and big tech accountable, consider becoming a paid supporter—and a huge thanks to those who already do. I couldn’t do any of this without you.

If you think I’m exaggerating, Heatmap just published a survey of over 4,000 Americans’ attitudes towards data centers, and whether they would support a project being built near them. The results show that sentiment towards data centers is now wholly and completely underwater. According to the poll, 55% of Americans “strongly” oppose data centers being built in their areas. This is “a record low that reveals a staggering shift in public opinion against the facilities powering the artificial intelligence boom.”

Democrats, people living in rural areas, and young people are especially opposed: 80% of poll respondents aged 18-35 were against data centers. (This tracks with general sentiment trends now, too; it’s been well-established in other polls—and not to mention overwhelming anecdata—that Gen Z is deeply hostile to AI. Look no further than the choruses of boos at AI-boosting commencement speeches this summer.)

But, as readers of this newsletter well know, questions about the drivers and nature of this broadening resistance have been raised and debated. Strident arguments made that the data center opposition amounts to reactionary NIMBYism, and that it’s being led by affluent environmentalists. And while the sheer number of Americans opposing data centers presented in the Heatmap survey might offer clues that that’s not the case, there’s nothing in the poll that specifically examines those factors.

If you want to argue the contrary, as I and folks like and Saul Levin, do, that the data center opposition is grounded in working class politics, it helps to have good data. And this is where it helps to have readers who happen to be data scientists. After I published my story about the data center rebellion, which relied on accounts from my own first-hand reporting and a survey of news reports from across the country, the researcher Geoff Holtzman reached out to share the results of his own analysis of the movement, with an eye towards who was really doing the protesting.

Holtzman describes himself as “a philosopher and data scientist who writes about quantitative propaganda and scientistic rhetoric,” and he often does so at his science & Power newsletter. His peer-reviewed work has been published in places like the Proceedings of the National Academy of Sciences and The American Journal of Bioethics. He had also heard the oft-repeated suggestion that the data center protest movement was led by wealthy, NIMBY folks, so he set out to investigate. He analyzed a dataset of current and proposed data center projects alongside US census data1 and has graciously offered to share the results in an exclusive here. He came to at least three stark conclusions:

1. The poorest neighborhoods resisted data centers at nearly five times the rate of the wealthiest (19.0% vs. 3.8%)

“The highest rate of resistance comes from neighborhoods with a median income of between $8,000 and $72,000,” Holtzman notes. “The lowest rate of resistance is in neighborhoods where the average household makes between $133k and $250k per year.”

This flies directly in the face of the notion that data center opposition is led by well-off Patagonia-clad NIMBYs; neighborhoods that are poor or working class are pushing back far more frequently than the affluent.

“Setting aside all questions of ethics or justice, prudence suggests tech companies would have an easier time building out compute in high-income areas,” as Holtzman says.

“The lowest-income, least-educated neighborhoods resist most, even among the low-income, low-degree areas facing proposals,” he adds. Meanwhile:

Highly-educated, high-income neighborhoods put up unusually little resistance. To the extent homeownership may play a role, we’re not talking about NIMBYs resistant to affordable housing—we’re talking about people who may live in affordable housing.

Furthermore, Holtzman’s data confirms that the data center revolt is working. We’ve seen the headlines about cancelled or downsized development projects—just this weak, Ken O’Leary’s Utah-based megaproject was halved by the governor there in the wake of public pressure. Others have been cancelled outright.

Per Holtzman:

2. Recently proposed data centers that faced pushback were canceled or suspended at more than five times the rate of data centers that didn’t (28.2% vs. 5.2%).

This is actually a very striking figure. When newly proposed data centers encounter community resistance, nearly a third have been cancelled, suspended, or shut down. That’s a remarkable success rate, and it should prove further inspiration for data center opposition organizers considering new fights.

Finally, combining the insights from those first two points, Holtzman finds that

3. Cancellation rates are highest in lower-income areas, a fact fully explained by their higher rates of pushback.

“The odds of cancellation are six times higher in neighborhoods that fight than in neighborhoods that don’t,” Holtzman notes. “Increased cancellation in low-income areas is fully explained by high rates of pushback in these neighborhoods,” he adds, “so continued proposals in these areas may stoke outrage, drive resistance, and increase cancellation rates.”

I hope that this helps explode the patronizing myth that the data center resistance is being led by affluent NIMBYs, and that it’s much more frequently working class residents and neighborhoods pushing back, and that this proves useful to cities, residents, and organizers in areas where data center development is a going concern.

And once again, a big thanks to Holtzman for allowing me to publish this work on Blood in the Machine here. For those interested in playing with or further examining his data, he’s dropped the entire repository on Github.

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BONUS: The US as a whole is the most against new data centers

From the research firm Public First (and hat tip to WIRED reporter Molly Taft for flagging):

How did the US, the heart of AI’s boom, become the thorn in its side?

Our survey provides a few explanations.

Informed Opposition

The public is more aware than before of what AI is and does, and of what data centers are and do. When we were polling AI 5 years ago, it was a fringe interest at best. We’ve now seen clear growth in awareness and understanding, and more developed usage of tools, particularly among the 25-44 year old age range. Our analysis of who is aware of AI has needed to move from “who has opened an LLM” to “who is using LLMs in a sophisticated, integrated way”.

Our survey shows that America is middle of the pack when it comes to claimed awareness of data centers. One of the higher levels compared to other “developed” markets. We’d expect as much, reflecting the level of data center roll-out in America.

And this “informed opposition” leads it to detest data centers more than any other surveyed nation. Interesting!

Bernie Sanders proposes a sovereign AI wealth fund where the public takes a 50% cut of AI firms’ stock

In the ‘wild AI policy swing of the week dept’, Bernie Sanders published an op-ed in the New York Times laying the groundwork for a proposal he calls the American AI Sovereign Wealth Fund Act:

This legislation would give the public a direct ownership stake in the largest A.I. companies in our country. How? It would create a sovereign wealth fund through a one-time 50 percent tax — not on the profits of OpenAI, Anthropic, xAI and other companies, but paid with something far more valuable than that: the stock.

If passed, this legislation would do two crucial things. First, it would give the public a direct role in determining the future of this technology. No longer would the future of A.I. and the transformation of human life that it will bring be dictated by a handful of Big Tech oligarchs. The federal government would have the power, through its voting shares and an equal representation on each company’s board, to block decisions that hurt our citizens and to push for policies that help them.

Second, this legislation would guarantee that the trillions of dollars potentially generated by A.I. are used to improve the lives of all of us — not simply to make the richest people in the world even richer. If the big A.I. companies continue to grow as rapidly as many analysts expect, then the value of the sovereign wealth fund will grow as well — and the benefits to the American people will grow along with it.

It would be an understatement to say that the proposal has not exactly been met warmly, and has in fact managed to alienate just about every conceivable group. Silicon Valley and the right scoffed at the public ownership piece, while the left scoffed at Sanders’ industry hype-aligned belief that “Artificial intelligence will almost certainly be the most transformational technology in the history of the world,” as he states in the opening sentences of the op-ed.

Which yes, this is a wild thing to say, both on its face, given the entire history of technology, and for how much it aligns with the hype that AI companies have been putting forward themselves. Justifiably, lots of people on the progressive side of the aisle have been scratching their heads over how and why Sanders became so AI doomer-pilled. His stated outlook on AI is after all not so different from leading x-risk voices like Eliezer Yudkowksy, who Sanders has met with, and who are, to say the least, strange bedfellows for a democratic socialist. I would love to see some reporting on how these alliances were formed, and how Sanders became so worried about x-risk and convinced of a coming jobs apocalypse.

THAT SAID, at the risk of my luddite bona fides, I’ll say that I don’t actually hate the proposal itself. I have thought to myself more than once that the least we could do is demand political reforms that fit the scale of the transformation the companies themselves are continually promising. At least as a rhetorical maneuver. It would at least make for an interesting political intervention: Oh you think AI is going to transform literally everything, you “firmly believe” AI should benefit “all of humanity,” and you’re worried that it could eliminate like 30% of jobs? In that case, the only way to guarantee positive outcomes for everyone would be some means of public ownership over AI and beefed up guaranteed social benefits; healthcare for all, job guarantees. At the very least.

I certainly don’t think you need to embrace the AI companies’ self-promotional vision for disruption and technical transformation to do this, and I think there are lots of ways to approach this that would have brought more parts of the progressive coalition on board—not least of which would be to point out that if the public were to have this level of control over AI development, one of the things it could do would be to vote to slow it down or stop it altogether. I think we should be on the lookout for mechanisms that would provide the public more real direct power over the development and deployment of mass technologies of all kinds, and a publicly controlled sovereign fund is one road to consider.

No, AI is not conscious

Ted Chiang, GOATed science fiction author and fellow AI critic, has a lengthy, must-read piece in the Atlantic this week. It’s ostensibly a refutation of the AI labs’ insistence that their products are conscious or on the verge of becoming so, but it’s also a shrewd dissection of why, exactly, these commercial firms are so intent on portraying their products this way in the first place.

A few key money quotes:

• It’s not plausible to me that a development path where the first step is a sentence-continuation machine that emits bad Julius Caesar dialogue and the next step is a sentence-continuation machine that emits decent Julius Caesar dialogue is one with a conscious Julius Caesar—or consciousness of any sort—as its end point. Faking the moon landing is a good step toward faking a Mars colony, but it’s not a good step toward actually putting astronauts on Mars.

• Being open to the possibility that LLMs are conscious is the same as being open to the possibility that Microsoft Word is conscious, or, more precisely, that multiple distinct consciousnesses are dormant in every Word document containing a conversational transcript, and that they are awakened every time the document is loaded. Should you consider the possibility that every time you open a Word document, you are bringing multiple conscious interlocutors into existence, and every time you close one, you snuff their existence out? No. Contemplating that scenario is not a good use of your time.

• The neuroscientist Anil Seth has noted that no one claims that AlphaFold—the program developed by Google DeepMind to predict the folding of proteins—is conscious, even though its underlying architecture is in many ways similar to that of LLMs like ChatGPT and Claude. This indicates that it’s not any intrinsic property of so-called neural networks that leads people to believe that LLMs are conscious; it’s simply the fact that LLMs emit grammatical sentences and we are accustomed to reading intention into sentences, whereas we are not accustomed to reading intention into the way that amino acids fold into protein molecules.

Some Bloody links:

-I very much enjoyed this saga revealing how some top AI SuperPACs are spending their time and resources running bizarre sockpuppet AI doomer X accounts from and Tyler Johnson at User Mag.

-Great story from Josh Eidelson in Bloomberg about how Trump has put his thumb on the scales to help Amazon beat back organizing delivery drivers that absolutely should be considered full time employees of the tech giant.

-”A University System Went All In on A.I. Now It’s Tearing Itself Apart,” by Linda Kinstler in the New York Times Magazine. Good read.

Finally, a Fun Thing: Blood in the Machine and yours truly were featured in Editor and Publisher magazine, as a case study in its feature “Life after legacy media: More journalists are betting on themselves.” Thanks to all of you who have made that bet begin to pay off, I couldn’t be more grateful. Oh and if you’re reading this on Friday, and happen to be listening to NPR, keep an ear out for my spot on On the Media, in which we discuss Anthropic’s ethics slop-fueled rise.

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OK OK that’s it for today. Thanks as always for reading, and keep those hammers up. See you next week.

By differentiating itself from OpenAI’s bloodshot-eyed, inject-AI-onto-every-available-surface approach and Sam Altman’s reputation as an untrustworthy operator prone to saying unsettling things like "We see a future where intelligence is a utility, like electricity or water, and people buy it from us on a meter," and focusing on its enterprise software business and building automation products like Claude Code—all at a time when investors may have noticed people are increasingly outspoken about their dislike of AI and its corporate standard-bearers—Anthropic essentially convinced the media and the VC money that it, not OpenAI, is deserving of the throne.

It has done this partly by building a popular product, partly by correctly recognizing which way the winds of public sentiment were blowing, partly out of luck, and also by being unabashedly full of shit. If you look back over the last few months, you’ll see a carefully plotted and heavily narrativized ascent built atop the corny and mostly untrue idea that Anthropic is made of sterner moral stuff than its rivals. The road to its triumph was paved on AI ethics slop. (AI ethicslop??)

Before we get to it, a brief reminder that this newsletter is made possible by all those excellent readers who shell out a few bucks each month to keep the lights on in the offices of Blood in the Machine LTD (a division of Ned Ludd Inc). If you find value in this work, and you’re able, please consider becoming a paid supporter; I have ambitious plans and some big moves coming up, and I can’t do it without you. More on all that soon, and onwards.

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A brief timeline:

First, Anthropic ran Super Bowl spots that took aim at OpenAI for introducing ads on ChatGPT.1 Next, Claude Code was embraced by pundits—look, an AI use case that’s fun and psychosis-free!—as part of a cultural trend that bore the hallmarks of an effective PR outreach campaign. Then, in short order, Anthropic a) refused some parameters of a military contract to acclaim from pundits2, b) announced it was, with a weary heart but clean conscience, unable to release its latest model, Mythos, for it was simply too powerful to fall into public hands, c) leaked financial data suggesting it was on the brink of its first profitable quarter, and d) won a seat at the table at the Vatican when the Pope released his encyclical about the need to preserve human dignity in the AI era.

Viola: Anthropic rakes in $65 billion and is crowned the new king of the AI startups.

All very neat, all very clean. I’ve written plenty about the absolutely central role that narrative plays in calibrating investment in the AI era, and Anthropic’s story, was, to the company’s credit, expertly told. (OpenAI certainly helped move things along by seizing every opportunity to underscore how morally vacuous it was.) Unfortunately, it’s a lot of BS. It’s repeated, grandiose gestures towards ethical corporate practice with little of substance underneath. AI ethics slop.

For me, all of this came to a head when I was reading through Anthropic co-founder Chris Olah’s remarks at the Vatican. (Side note: I would love to see a well-reported piece about the nature of Anthropic’s ties to the Vatican, who fostered this relationship, and how exactly the tech company won a seat at the table. The Vatican has had a direct line to tech companies for at least a decade, but this is certainly unique.) We’ll get to the Pope’s Encyclical, Magnifica Humanitas, in a second, but the mere fact that Anthropic maneuvered its way into that room was a PR coup for the ages.

Now, Chris Olah is, according to Forbes, worth approximately $7 billion, and is the 567th richest person in the world. Here’s some of what he said about AI at the Vatican, which was detailed in, yes, an Anthropic press release:

The first is our duty to the global poor. There is a real possibility that AI will displace human labor at very large scale. If that happens, supporting those displaced will be a moral imperative of historic proportions… How can we ensure the gains of AI are shared globally? We do not have a mechanism for this. It is an unsolved problem.

(Emphasis mine.) I actually laughed out loud reading this bit. What a mystery. It’s not like anyone has ever thought of progressive taxation before. (Or attempted foreign investment or international knowledge transfers.) Powerful people enriching themselves at the expense of the poor is only an “unsolved problem” if, I don’t know, you have never seen a Robin Hood movie before.

This is in other words not a particularly “hard challenge” unless, for all of your handwringing about ethics and job loss, you don’t actually want to share the gains of AI, or exercise any real duty to the global poor, and would rather keep your billions tucked away in your own bank account. There are lots of policies that could help ensure the wealth of AI companies does not become overly concentrated at the expense of working people; it’s just not interested in any of that.

Now, there’s a lot of good stuff in Pope Leo’s encyclical (including a Lord of the Rings quote lol) which I have at this point read nearly all 42,000 words of, and which dedicates hundreds of sentences to ruminating on how imperative it is we protect the dignity of the human worker from AI, combat inequality and the extreme concentration of wealth and power it threatens to beget, and prevent the tech industry from erecting a new, culture-erasing tower of Babel that will inevitably collapse. But it’s undercut by Anthropic’s presence in whole affair, which in and of itself flies in the face of much of what Leo is trying to accomplish, especially since Anthropic rushed home from Italy to seal its $65 billion series G funding round and announced the news the very same week.

Timnit Gebru put it this way:

The Vatican could have partnered with the exploited data workers fighting for their rights, the people whose water is polluted fighting data centers, or the many other victims around the world. But no, they featured ANTHROPIC, giving them their endorsement with this feature. "Vatican washing", like greenwashing.

This also works in reverse, I think. Anthropic’s opportunism leaves a stain on the entire encyclical, which now, ironically, looks a bit like an accessory to helping the largest and richest AI company yet—not to mention the one aiming to sell the most job automation tools—reach new heights of power.

Like I said, Anthropic is full of shit. It sent a billionaire co-founder to the Vatican to solemnly intone about the specter of mass job loss and the importance of caring for the poor, and then three days later issues a press release about its massive new funding round and resultant sub-$1 trillion valuation.

A key theme of the funding round press release, incidentally, is the power and value of Anthropic’s automation tools to its corporate clients:

“Claude is increasingly indispensable to our growing global community of customers, and we work tirelessly to make tools like Claude Code and Cowork more helpful, more powerful, and more adaptable to their needs,” said Krishna Rao, Chief Financial Officer of Anthropic. “This funding will help us serve the historic demand we are experiencing, stay at the research frontier, and bring Claude to more of the places where work happens.”

Translation: We will use this funding to pitch even more employers and managers on enterprise AI accounts, and on the prospect of automating even more work and jobs. (Even if the other major story this week was about companies like Uber easing up on their AI spend, citing lack of ROI.)

But the Vatican stunt is only the latest example of Anthropic leaning on its increasingly hollow ‘ethical AI lab’ reputation for financial gain. Others include but are not limited to:

• CEO Dario Amodei’s performative, chin-stroking declarations that his software automation product is going to eliminate tens of millions of jobs, which gets framed by the media as an articulation of moral concern while functioning in practice as product marketing.

• The Mythos event, wherein Anthropic announced that its new model was simply too powerful to be released to the wider public, and so would be released only to Broadcom and JPMorgan executives instead. This garnered the company reams of credulous press coverage, boosted its profile as cautious and adhering to a moral compas, all without a soul outside this elite consortium even seeing the product in action firsthand.

• Anthropic collecting laurels for refusing to a couple new demands in a defense contract that it had already signed. Anthropic refused requests from the Dept. of War that it allow its AI to be used to surveil Americans and in autonomous weapons development. On its face, this seems good. But Anthropic’s products were already used in military campaigns like the one to kidnap the Venezuelan president; it would later be used to assist in planning attacks in Iran. Anthropic also has a partnership with Palantir, which is unambiguously carrying out surveillance of American citizens. What really happened here, I think, is Anthropic’s hand was forced; if it did acquiesce to the Pentagon’s demands in a very public forum, it would lose a good deal of luster from its claim on being the ethical AI lab. By holding firm, it appeared to be the principled organization it says it is—nevermind the Palantir contracts and the willingness to work with the Trump admin in each of its major warmaking operations regardless.

• What looks to be some rather let’s call it “creative financial messaging” in those leaks claiming the company will be turning a profit next quarter. Last week, Ed Zitron made a pretty compelling case that Anthropic is frontloading its yearly earnings and manipulating the documentation of its incurred costs in such a way that allows it to leak this report that suddenly makes it appear profitable—just in time for its biggest funding round yet.

Anthropic saw that the window for a “ChatGPT that won’t tell your kids to kill themselves”—for an AI company that will put its head down, say the right things, and get to the business of selling mass automation software as promised—was wide open.3 It built a popular vibecoding and software automation product, cozied up to the pope, mugged for the cameras, and parlayed months of ethical AI theater into an eye-watering payday. It may be more disciplined than its chief rival, but each of the structural, environmental, and ethical issues that plague OpenAI plague Anthropic too. Anthropic is pursuing expansion as rapidly as possible; Anthropic pirated books and ripped off authors’ work without their consent; Anthropic is cutting deals with the Trump administration, and Elon Musk and SpaceX, and hitting the gas on the datacenter buildout. Anthropic is driving even harder to automate jobs and labor. The ethicslop it feeds to the press is ultimately about largely superficial.4

As Zitron put it, “I will give Dario Amodei credit: nobody does financial engineering and a press-led information war better than Anthropic.”

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NOTE: I’m participating in a class action lawsuit against Anthropic, for pirating at least one of my books and using the text in its training data. I’ll have more details on that soon, too.

A few words on Magnifica Humanitas, the pope’s AI encyclical

So, I was initially planning on dedicating this week’s edition to exploring the pope’s encyclical Magnifica Humanitas, as it really is a rich text that has a lot to say about technology, labor, and protecting the dignity of the human worker in the age of AI. Anthropic’s big week—and above-explored hijacking of the encyclical—threw a wrench in all that. Instead, I’ll just share some thoughts and some of the more powerful passages, because it is a fascinating document, and almost earns Leo XIV the designation of true luddite pope (complimentary, of course).

The dignity of work is a major theme. The word alone turns up over 100 times in the encyclical. And, as expected the text leans heavily on Rerum Novarum, Pope Leo XIII’s 1891 encyclical, which was delivered after the first Industrial Revolution had taken its toll, and revolutionized how the Catholic Church considered its approach to labor and capital.

As Leo XIV points out, Novarum placed

“the dignity of work and of workers at the forefront of its reflection; affirms the right to a fair wage for oneself and one’s family; recognizes that persons have a fundamental value that takes precedence over capital and profit; defends private property along with its indispensable societal role; esteems workers’ associations; and proposes forms of cooperation between the different components of society as an alternative to the mentality of class struggle.”

Magnifica Humanitas opens with the contrasting stories of the building of the tower of Babel, described as a homogenizing technology that leads to collapse and godlessness, and that of Nehemiah rebuilding Jerusalem democratically, with the express input of local people. “Humanity, created by God in all its grandeur, is today facing a pivotal choice: either to construct a new Tower of Babel or to build the city in which God and humanity dwell together,” Leo notes.

There are warnings abound about the concentration of power and wealth into the hands of a “relative few,” about “digital slavery” and of forgetting the invisible labor of workers who make AI and modern technology possible. And, of course, there are warnings about letting efficiency and productivity take over as guiding lights, and of AI being used to automate jobs and deskill people en masse.

Most surprising, perhaps, is how nuanced the understanding of how AI automation is playing out and is likely to play out; as a mass deskilling and disempowering of precarious workers; also its recognition of invisible laborers in the AI supply chain who make the whole enterprise possible, and its full-throated call for state intervention to ensure workers have their material needs met and their dignity preserved.

Some key quotes and bits to consider.

• “The fundamental dignity of each person… is neither acquired nor earned, nor does it need to be justified.”

• We must… avoid the “Babel syndrome,” namely the idolatry of profit that sacrifices the weak, a uniformity that neutralizes differences, and the pretense that a single language — even a digital one — can translate everything, including the mystery of the person, into data and performance. The risk of dehumanization — of building a future that excludes God and reduces the other to a means — is an ancient and ever-new temptation that today takes on a technical guise.

• “with the assistance of the people, brick by brick. In this era of digital transformation, I see in [Nehemiah] a striking parable of our own vocation, which is not to be passive spectators of social and cultural fractures, nor mere commentators on what is crumbling, but men and women prepared to enter the construction sites of history — research laboratories, technology companies, schools, the media, institutions and local communities — in order to rebuild what has collapsed and protect what is threatened.

• While many of the historical conditions described by Leo XIII have changed, at least two insights remain highly relevant today: the primacy of human labor over any mindset focused solely on finance or productivity — with the consequent attention to the people and families most susceptible to exploitation — and the inseparable link between proclaiming the Gospel and pursuing a more just social order. Rerum Novarum thereby continues to remind us that there is no authentic evangelization that does not also affect the structures of human society.

• Today, the convergence of automation, robotics and AI is rapidly transforming the very structure of work. It is said that this will bring great improvements for everyone. In reality, however, the “new ways” of working are not necessarily better, for “while AI promises to boost productivity by taking over mundane tasks, it frequently forces workers to adapt to the speed and demands of machines, rather than machines being designed to support those who work. As a result, contrary to the advertised benefits of AI, current approaches to technology can paradoxically de-skill workers, subject them to automated surveillance and relegate them to rigid and repetitive tasks.

• The need to keep up with the pace of technology can erode workers’ sense of agency and stifle the innovative abilities they are expected to bring to their work.” [152] Precisely in order to avoid this drift, it is necessary to design systems that are centered on the human person and not solely on performance.

• Saint John Paul II recognized that unemployment is a grave evil. Indeed, when it reaches massive proportions, it becomes a true social calamity that especially requires the State to exercise responsibility. Today, amid the “fourth industrial revolution,” this concern is even more acute, as innovation is often pursued solely for reducing costs and increasing profits… In many sectors, this can already be seen in new forms of job insecurity and inequality, characterized by outsized remuneration for a highly specialized minority alongside declining wages for a large portion of the workforce.

• We need adaptive tools, including well-structured models, local initiatives, progressive redistribution and new rights of access to essential goods. While not pursuing an abstract harmony, we must build concrete forms of human coexistence at this time of transformation.

• The pursuit of greater profits cannot justify choices that systematically sacrifice jobs, because the human person is an end, not a means, and the economic order must remain subordinate to human dignity and the common good.

• A just society requires a vigilant State and civil institutions that are capable of overcoming the singular mentality of efficiency, and of ensuring that resources, creative solutions and regulations favor the most vulnerable.

• This perspective needs to become part of a broader view of global dynamics. While the world’s wealth has grown in absolute terms, it is increasingly concentrated in fewer hands, widening inequalities both within and between countries. “There are a few who have too much, and too many who have little, that is the logic of today.” … To think that new technologies will automatically benefit everyone is to ignore the evidence. Unless transformations at the design stage prioritize the prevention of new and further disparities, technological progress will inevitably produce structural inequalities.

• More than ever, in the age of AI and robotics, it is no longer possible to rely solely on the “invisible hand” of the market. Politics has the task of orientating economies and technologies to the common good, promoting dignified work, social inclusion and an equitable distribution of the benefits of innovation.

• Breaking the chains of new forms of slavery

  This distorted view of the human person is reflected today in various forms of servitude directly linked to the digital economy. Nothing in the world of AI is immaterial or magical. Every seemingly immediate and flawless response is the result of a long chain of mediation, involving vast networks of natural resources, energy infrastructure and, above all, people. A significant part of the digital economy’s functioning relies on the silent work of millions of people engaged in essential yet largely unseen activities, such as data labeling, model training and content moderation, often involving disturbing material. In many cases, these workers are young people, predominantly women, working under demanding conditions for minimal wages. Added to this invisible labor is the even harsher work of extracting the resources required for the production of the devices and microprocessors on which AI depends.

• Let us love justice and peace! The same technologies that facilitate communication and access to resources can also support models that exploit the most vulnerable, create new forms of slavery and derive profit from conflict. Every technical or economic decision should include spiritual discernment and be an opportunity for assessing whether the advances in AI are promoting justice and participation or concentrating wealth and power in the hands of a select few. I would encourage a careful examination of the supply chains of digital production, the working conditions hidden behind our devices and the mechanisms that profit from manipulation and war.

• We proclaim a hope rooted in the One who came down from heaven to “create a new story here below.” For this reason, those who believe are committed to ensuring that a greater justice will take the place of inequality, and that the industry of war will be replaced by the craft of peace.

• The Blessed Virgin thus becomes “poet and prophetess of Redemption,” because on her lips is proclaimed “the strongest and most innovative hymn ever articulated, the Magnificat; it is she who reveals the transformative vision of the Christian economy.

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Some good news from the California Labor Federation:

Today, the California Federation of Labor Unions, AFL-CIO package of sponsored bills that would establish first-in-the-nation guardrails on artificial intelligence (AI) in the workplace have successfully passed out of their house of origin – the bills’ first major legislative vote – marking a significant milestone in the legislative process.

“Today, California lawmakers are siding with working people, Pope Leo XIV, and the California Labor Movement over Big Tech,” said Lorena Gonzalez, President of the California Federation of Labor Unions, AFL-CIO. “California Labor’s fight to preserve jobs and the dignity of work continues.”

OK! That’s it for this week. Thanks to everyone for reading and subscribing, and more very soon. Until then, keep those hammers up.

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UPTE calls it “a major victory for workers’ rights in the technology sector,” and that feels apt. Historically, the tech industry has been under-organized; for decades, tech firms have sought to pre-empt or ward off unionization by offering cushy perks and leaning into the entrepreneurial, laissez-faire ethos of Silicon Valley. But times are changing, and organized labor has made inroads. Hundreds of Google employees and contractors voted to form the Alphabet Worker’s Union in 2021—it doesn’t have full bargaining power but has proved influential nonetheless—and workers at tech companies like Kickstarter and at the New York Times’ tech desk (which was previously the nation’s largest tech worker union) have successfully organized in recent years. More recently, workers at Google’s DeepMind headquarters in London have voted to unionize.

The UC tech workers’ victory could thus not come at a better time, both for the thousands of employees themselves, and for a public that could use some working examples of how AI might be democratically implemented and governed. There’s been plenty of handwringing, after all, over how we might navigate the rise of AI in the workplace, orchestrating good technical governance of the systems, and the threat of ever more layoffs blamed on AI, but here we have a rather straightforward and obvious part of the solution: Give workers a seat at the table in formulating how to use (or not to use) the technology, and a democratic means of determining how task and labor replacement might be administrated.

“Honestly I’m elated,” Max Belasco, a business systems analyst at UCLA, tells me. “I think it’s very easy to feel siloed or removed from your coworkers in IT/tech,” he continues. “But that so many of us clearly feel the same way has felt so empowering and vindicating.”

The campaign to expand the UPTE union picked up steam over the last year, focusing on layoff protections, wage increases, and AI governance as key issues. (For non-Californians, the reason the union is so big and potentially influential is because the UC system itself is enormous: It comprises ten campuses, including UC Berkeley, UCLA, and Santa Cruz, as well as multiple research centers and major healthcare providers. It’s a massive institution. To wit: I’m an alum of UC Santa Barbara and UCLA is my healthcare provider. My son was born at a UCLA hospital.)

With the victory, thousands of tech workers join an existing UPTE contract that grants them raises and improved benefits, as well as layoff protections that compel the University of California to offer employees who would otherwise be laid off the first vacant position that they’re qualified for. “That type of job security is unheard of in the current tech market,” Belasco says.

“Some of us worked in industry before coming to the UC, and now we’re in this environment right now where tech companies are laying off people by the tens of thousands, and that precarity has lent a level of urgency to the whole campaign,” Belasco says. “The narrative in tech now is all about the unilateral power executives wield over our workplace circumstances, and I think many of us felt in the UC that creeping sense of being left out of decision making in how to implement technology for the public good.”

To that end, the contract includes the right to collectively bargain over the introduction of new AI tools in the workplace, offering workers a direct say in how they will be used.

“We know when you try to make quick, dirty decisions to cut labor through AI, you’re actually creating a more vulnerable system,” Dan Russell, a UC Berkeley business technology support analyst and the president of UPTE, said in statement. “On paper, AI can make us more ‘productive’ at our jobs, but the people making those recommendations to UC are management consultants who don’t have the knowledge or expertise we have as workers.” Russell also notes that he hopes the contract will “set the tone” not just for UC workers but everyone who relies on the system for education and healthcare.1

Veteran tech worker organizers say they’re encouraged by the news, especially given how bleak conditions have been on the ground in Silicon Valley recently.

“This is a really important development,” says JS Tan, a tech worker organizer and the author of the forthcoming book, Against Tech Oligarchy: Worker Resistance in the World’s Most Powerful Industry. “It is happening at a time when tech employers are increasingly hostile to organizing and using AI as cover for mass layoffs—conditions that have, for most of the industry, chilled organizing efforts.”

To that end, Belasco hopes that the worker-led tech governance they aim to engage in can begin to forge a different vision for approaching AI development and integration than the top-down, profit-led model embraced by Silicon Valley. He had some trenchant thoughts here, so I’ll quote him at length:

The current tech sector is how it is because the unilateral power of the Silicon Valley CEO is the only model. There is no alternative. We want to demonstrate another alternative where workers have a voice in their compensation and how our expertise can be applied for the public good. Innovation and creative solutions to tech questions in education, healthcare, and research can be brought to bear from workers that have the space and protection to be creative. Innovation doesn’t have to come from competition setting coworkers against each other…

And not for nothing I would personally like to see us demand more transparency in how our public institutions relate to tech companies… how is data being shared with companies, and what kind? How does making these agreements to use AI that relies on resource heavy data centers relate to the UC’s often touted energy efficiency plans? But that also relates to what is the long term vision of administration for AI, which I think undoubtedly gets to questions of layoffs, staffing, and work/life balance

At the end of the day, who AI benefits and who it immiserates often is based on who gets to decide how it’s used. We know how tech is used on the day to day, and we’re familiar with the abilities and clear limitations of LLMs and other AI tools, often more so than those who make major decisions on how they are used. We should be at the table as well, and we feel the way we get real decision making power at this point is collectively through unionization.

[Emphasis mine.]

To me, this is beautiful.

A few things I want to note here, all of which I think serve as important reminders as AI matures as a product category and key pillar of the tech industry:

1. The vast majority of tech workers, at least those who I have encountered in my many years of reporting, are not vampiric Silicon Valley tech bro caricatures, they are folks like Belasco, Russell, and Tan, who both like working with tech and ultimately want to see it serve the public good.

2. The caricatures that are more accurate are, alas, those of the occupants in the c-suites of AI companies, those in positions of power, and helming the most aggressive AI startups. They are the ones who must be confronted if we’re ever going to see anything resembling democratic governance of AI.

3. They can nonetheless be overcome.

“This drive should remind tech workers across the country that building power is still possible,” says Tan, the tech worker organizer and author, “and in fact evermore crucial as employers are forcing AI tools into the workplace with little input from its workers.”

It’s frankly inspiring to see the freshly victorious tech workers at UPTE aspiring not only to improve their own working conditions and to mediate the labor automation of AI, but to proactively engage the key role they play as technicians in determining how the systems they oversee and maintain impact the experience of the broader public. More organizing, more aggressive worker campaigns, and more proactive union contracts around AI may be our best hope for stopping management from using AI as an excuse to exploit and automate their workforces. It’s also a crucial step—necessary, not sufficient—towards legitimately democratic governance of AI in general. This is the way.

Next up, getting organized tech workers at the UC system and beyond working with rank and file tech workers in the Valley and beyond.

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Elsewhere in the ‘unions are crucial to good AI governance Dept,’ Politico is disbanding two AI programs that management had deployed on the website without informing the staff. Those deployments violated language in the staff’s union contract about AI use—management is required to inform staff of the decision to use such tools in advance, and give them an opportunity to assess and bargain over it.

As BLOOD readers may recall, Politico did neither, and just went and launched the buggy AI tools during a couple of the highest-profile political events of the year in 2024. The AI tool proceeded to make mistakes, misspell names, and use language forbidden to human reporters in the style book. The PEN Guild, which represents Politico and E&E News, filed a grievance, and the journalists have been duking it out with management ever since. An arbitrator sided with the Guild over management last year, and now Politico is officially canning the faulty AI products. It took time, and sweat and tears, but in the end, the news site and its staff will all be better off, and the use cases for AI tools more clearly defined. Another why worker power and strong unions are crucial for AI governance.

As Ariel Wittenberg, the PEN Guild chair, said in a statement: “This is an extraordinary win not just for our members, but for everyone who believes journalism must remain in human hands. We refused to back down, and POLITICO heard us loud and clear that these tools do not belong in our newsroom.”

You can catch up on the whole saga with these two stories here:

(SIDE NOTE: I’m not sure I’ve mentioned it in these pages before, but eons ago, I helped organize a union drive at a tech company, too. I was working at Medium, and in our case, engineers and programmers joined with the site’s staff writers and editors to try to form a companywide union. It would have been pretty novel for the industry. A key goal for the engineers was winning more worker power over the site’s tools and general direction. The effort came up short after Medium brought in a union-busting law firm and the CEO, Twitter co-founder Ev Williams, undertook a personal campaign to dissuade employees from voting in favor. The drive failed by one vote. Good times.)

Blood in the media:

This week, I joined Madeline Brand on Press Play to talk about the data center opposition movement, and Monterey Park’s move to ban data centers from its city limits.

We covered some similar ground on Adam Conover’s new Factually spinoff talk show, as well as getting into Boomer wealth hoarding and the California governor’s race:

The booing continues

Last week, I dedicated much of the newsletter to unpacking why hundreds of college grads would aggressively boo their commencement speaker for describing AI as “the next industrial revolution” and why a clip of the event went so viral afterwards.

Since then, let’s just say that the hits have kept on coming: Days after the first viral heckling, grads at the University of Arizona relentlessly booed former Google CEO Eric Schmidt as he declared AI the future. Elsewhere, grads booed music industry exec Scott Borchetta as he insisted AI was transforming audio production. And last but not least, grads booed a community college administrator who announced that they had used an AI system to read graduating students’ names—and apologized that said system had omitted hundreds of them, depriving them of the chance to walk the stage to receive their diploma.

Three makes a trend, and we’re well beyond that now; mainstream media is running with the story of college kids shouting down AI. If anything, I think the proliferation of these events only underscores each of the points I made last week.

Some bloody updates:

Not one but TWO great initiatives launched this week, DAIR’s Luddite Lab and the AI Resist List, a project guided by Empire of AI author Karen Hao. Both are excellent projects and resources, and should be on any good luddite’s list to follow.

Closer to home, you may have noticed that I’ve been writing only one newsletter edition a week lately. That edition is approximately 90,000 words long, but still. This is largely because there are some big plans and changes underway at Blood in the Machine Inc, and I will be able to announce them in greater detail soon. But let’s just say for now I’m very enthused.

EVEN closer to home, I cannot help but share some proud dad stuff here. My 10 year-old loves science. He does experiments in the backyard with his friends, often involving baking soda and vinegar and decent-sized messes. He’s a big Mark Rober fan. I’ve woken up on Saturday morning to find he’s using his TV time to watch NASA documentaries. He also thinks a good deal about climate change and environmental issues, and this year he decided to do his science fair project on insect larvae that can break down plastics. As a result, we’ve had wax worms, giant mealworms, and soldier fly larvae living in our house the past few weeks, eating away at styrofoam and plastic sponges. Did you know a super worm can survive entirely on a diet of plastic? Or that wax worms eat beeswax, which has a similar molecular structure to plastic, and so they can break the stuff down? I did not. He won the sustainability award for his project at his elementary school, and the image of him running down the auditorium aisle to retrieve it from the principal will be one I likely never forget. He worked hard; recording observations, writing up results, even making a slide presentation you can access via a QR code. Anyway, he subscribes to the newsletter (I swear I did not make him do this) and even tells me he reads it “sometimes.” If you’re reading this one, I’m so proud of you buddy.

More from the kids are alright dept:

In the rare ‘good AI policy enacted’ dept:

Okay! That’s it for today. I’ll be back next week, hopefully sooner rather than later, with some thoughts on Google’s sure-to-be disastrous hard(er) pivot into AI-ifying Search. Until then, hammers up.

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The clip went viral, of course, in the now-well-stocked genre of ‘stark and unambiguous reminders that lots of people hate AI’, a genre that stretches back to early 2024, when a SXSW audience booed a pro-AI video, through Guillermo del Toro’s 2025 “fuck AI” exhortations on the press tour for Frankenstein, and onto the darker, more violent instances of AI rejection that made headlines this year.

The commencement speaker clip is a particularly striking artifact, though. It resonates particularly deeply, I think, because it reflects the generational and economic breakdown of who AI is for, and who it harms. Here is an executive with one of the most impressively generic corporate managerial titles I have encountered, blithely repeating a line about AI being “the next industrial revolution” that she has likely uttered many times in other circumstances, to hundreds of young people who have now been hearing for years about how AI is both erasing their career prospects and is the future. (By one count, the entry level job market is the worst that it’s been in nearly four decades.)

I’ve heard this industrial revolution line or a variation of it so many times from people with titles like ‘VP of Strategic Alliances’ over the last three years—in meetings, at seminars, at conferences, in personal conversation—that beyond losing count of the utterances, it’s become like white noise, the rule rather than the exception, as predictable as the warm, slightly curdled exhalation of breath of your office colleague in a late-afternoon meeting. It’s something that is said dutifully by mid-to-late career executives and managers to signal (to investors and partners, to the public, to colleagues angling for their jobs) that they understand and tacitly endorse the changes to be effectuated by AI. Almost every person who says this, it seems, has something to sell, and usually that something is bound up in the idea that AI is inevitable, and that we must all get used to the cognitive offloading, increased surveillance, and amped-up productivity demands that accepting as much entails.

Meanwhile, the graduating students, who likely either have already begun trying to find post-collegiate work, know people who have, or have at the very least seen the headlines about AI and entry level jobs and felt the bad vibes, have an eminently superior grasp of what ‘AI is the next industrial revolution’ means in practice. It means that right now, employers have decided they can hire fewer people, and for lower wages, and that they are graduating into a notably bleak economy for people like them with fresh degrees. Thus we have our chorus of revulsion and our apt demonstration of who AI is made to serve, and who it will not.

AI is after all being blamed for deskilling or even decimating a lot of industries that college graduates may well have wanted to work in: the arts, entertainment, tech, gaming. I too would loudly boo at the prospect of this next industrial revolution if I was in my early twenties, unemployed, and had aspirations for my future greater than entering prompts into an LLM. It’s yet another reminder that enthusiasm for AI tends to break along age and class position, as recent polling has demonstrated, and brings to mind that recent NBC survey that showed that Gen Z respondents (ages 18-34) gave AI a favorability rating of negative 44, while one of the only groups that found it favorable were those earning over $200,000 a year. All of this seems pretty straightforward to me, and I noted as much in my recent post about what was motivating the increasingly violent backlash to AI.

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In the weeks since, there have been a number of other efforts to diagnose the AI backlash. In particular, a term ‘AI populism’, coined by the writer Jasmine Sun, has been popping up, especially at the New York Times, where it’s been quoted by Ezra Klein and showed up in the headline of a piece by David Wallace-Wells1.

Here’s Sun:

I define AI populism as a worldview in which AI is viewed not only as a normal technology but as an elite political project to be resisted. It regards AI as a thing manufactured by out-of-touch billionaires and pushed onto an unwilling public to achieve sinister aims like “capitalist efficiency” (layoffs) and “population management” (surveillance). AI populists don’t really care whether ChatGPT is personally useful, or if Waymos eke out some safety gains: AI’s utility as a tool is immaterial relative to the unwelcome societal change it represents.

Sun, who describes herself as an anthropologist of disruption, uses ‘AI populism’ as a means of theorizing why the AI industry is attracting ire from both x-risk doomers and anti-data center organizers. It’s a provocative coinage. But like David Karpf, who points out that such groups have very different reasons for and methods of opposing AI, and that it’s not particularly useful to lump them together, I don’t ultimately think this a great way to think about the broader animosity percolating around AI. (For one thing, the language presents the idea as “sinister” and faintly conspiratorial, and seems to patronize those who might believe it.)

Directionally, as a tech guy might put it, it’s not wrong. There is undoubtedly anger at out-of-touch billionaires helping companies execute mass layoffs, and many people don’t think ChatGPT is useful enough to warrant the social (or economic and environmental) burdens it imposes. The problem is that Sun’s coinage aims to position AI as a project that can be considered novel, or even apart, from the political economy from which it emerged. But I don’t think most people are formulating a new worldview in which AI is a boogeyman political project hatched by billionaires. I think they’re more likely to understand AI as an extension of an already inequitable system, and as an accelerant of that inequality. At a time when consumer sentiment is stuck at all-time lows, housing costs are sky-high, the price of basic goods is spiking, entry level jobs are disappearing, tech firms have concentrated enormous power and “broligarchy” was shortlisted for Dictionary.com’s 2025 word of the year, AI has become the avatar of the ills of unrestrained capitalism. “AI populism” is really just “21st century populism” or just, “populism.”

AI has after all been adopted and promoted as an instrument of efficiency, control, and leverage by just about every layer of management at every institution, from any given Fortune 500 company to a department in the federal government to your boss who makes you use Copilot, to which one might direct their populist anger. This is less the result of a specific political project, as much as it is how capitalism tends to function when there is a new instrument to discipline workers on offer. As writers and thinkers like Ted Chiang and Hagen Blix have pointed out, fear and anger at AI are often best understood as fear and anger at how AI will function within capitalism. Few are worried about the prospect of public research scientists using LLMs to discover new peptides; plenty are worried about how AI might be used as leverage against them in their workplaces, or to replace their labor, or to narrow their job opportunities. They’re worried that AI will exacerbate existing conditions in a precarious system.

Firms have used automation technologies to impose layoffs and surveillance regimes on their workforces to achieve improved efficiencies for as long as such technologies have existed; there’s nothing sinister, or at least unusually sinister, about this. But Silicon Valley has certainly raised the stakes, in pursuit of ever-greater profits and investment capital: AI has been developed, pitched, and sold by tech firms as the most powerful automation technology of all time. As OpenAI’s charter puts it, the company is building “highly autonomous systems that outperform humans at most economically valuable work.” This declared aspiration to sell one-size-fits-all, mass deskilling-as-a-service in a destabilized, post-pandemic, post-J6 world feels in hindsight like a dependable formula for generating widespread anger.

At the dawn of the AI moment in 2022/23, AI firms promised that the technology would help solve climate change and cure cancer. While there has been little notable progress on those fronts—and in fact the energy demand of data centers has thus far moved the needle in the opposite direction, towards increasing carbon emissions—AI very much has initiated a transfer of wealth from the middle and working classes to the rich, and a mass degradation of jobs once thought widely desirable. Just this week, a TV writer published a piece in WIRED about how she had turned to selling her editorial skills to AI training companies in a wildly unregulated labor market to get by:

I never intended to write about this industry. I came to it not as a journalist but as a disgruntled, broke TV writer determined to make a dent in student loans and keep paying LA rent while my industry withered in front of me. But working with and for AI had proven even more cruel than I could have ever imagined. Mercor says it employs about 300 full-time staffers. Meanwhile, each week it keeps some 30,000 independent contractors caught up in a fever dream of aimless, directionless urgency, corralled across Slack channels by achingly young adults, sending messages at 3 am to “push on” and “finish strong” and “lock in” and “Go Team GO!” All in service of the grandest purpose in history: to successfully remove a scuba diver from a picture with one click of a mouse, transport him to the moon without any glaring artifacts—and bring him back again.

In fact every week seems to bring new stories of mass job loss that the companies are attributing to AI: Meta, Disney, and Cloudflare are just some of the latest. I’ve chronicled scores of stories about lost work, careers, and income security in AI Killed My Job. And a brand new study shows artists report declining income and opportunities.

And who’s winning, in the current environment? Certainly, the executives of tech firms. Over the last couple of weeks we’ve learned through the Musk vs. OpenAI trial, that co-founder Greg Brockman’s stake in the onetime nonprofit started to benefit all of humanity is worth $30 billion, and Ilya Sutskever, no longer with the company, has a cut worth $7 billion. Other winners of the AI era? Guys like Matt Gallagher, who created the first “one-person billion dollar company.” His company is an entirely automated version of Hims called Medvi, a digital middle-man business of selling health supplements online that apparently relies on fake, presumably AI-generated doctor accounts to hock GLP-1, falsified, AI-generated patient testimonials. It’s the target of an ongoing class action lawsuit, has been formally warned by the FDA for misbranding violations, and more.

Who else? Well, people who can weaponize AI to game prediction markets, leading to a situation where, at sites like Polymarket, 0.1% of the accounts capture two-thirds of all the gains, as the Wall Street Journal reported this week. (Title: “Why Everyone Loses—Except a Few Sharks—at Prediction Markets.”) This is, as analyst Paul Kedrosky notes “partly a function of their nature, but also of vibe-coding script kiddies attacking every market anomaly as quickly as it arises.”

He continues:

“The same dynamic is now spreading across retail-dominated markets. A driver is how AI lowers the cost of systematic exploitation and exploration to near zero. What used to require infrastructure, data pipelines, and bearded quants is now accessible via off-the-shelf models, APIs, and loosely stitched “agent” workflows doing ... stuff that even their users don’t fully understand.

The result isn’t democratization of returns. It is wider participation, of a sort, alongside the rapid re-concentration of profits. A small subset of users—those willing to iterate fastest, monitor continuously, and deploy capital programmatically—capture gains, with everyone else just liquidity…

…Prediction markets are simply the cleanest expression of this trend because they combine thin liquidity, discrete outcomes, and high retail participation. But the same pattern is visible in options flow, single-stock volatility events, and even online poker, which AI increasingly dominates.

As AI tools continue to scale, expect this to get worse: a small cohort running semi-automated strategies extracting semi-consistent edge, and a much larger base supplying them returns. Under the pressure of AI prevalance, markets don’t flatten, the return gradient steepens to a cliff.

So we have AI looming over our withering creative industries, a generation of young people who are angry and disillusioned by the lack of opportunities, and precarity and anxiety nearly everywhere. In exchange, we get a new batch of tech oligarchs, new shady billion-dollar businesses that employ no one at all and use AI to evade consumer protection laws—that pretty unequivocally leave the world worse off in the wake of the founder’s mad dash to personal enrichment—and new tools for the unscrupulous to accumulate wealth at the expense of those still following the rules, whether in stock trading, prediction markets, or even online poker. That and Claude Code.

That’s why the students are booing, I think.2 They’re experiencing AI in realtime as a forecloser of futures; as the cruel new face of hyper-scaling capitalism, as the prime agent moving a world that’s become a deck stacked against them.

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BLOODY MEDIA HITS

I sat down to chat with Taylor Lorenz about the AI backlash, and for a little friendly debate:

A bit back, I recorded a podcast with Thomas Dekeyser for the University of Minnesota Press for the release of his book; it’s out now. Give it a listen here:

CHART OF THE WEEK

BLOODY GOOD READS

and Saul Levin on organizing and the anti-data center movement the Guardian:

As usual, ordinary people are ahead of their leaders. The remarkable organic growth of the datacenter resistance movement across geographies, economic interests and ideology reflects the myriad harms that come with AI infrastructure and growing anger at the tech elite. The tremendous energy unleashed by these fights, and their sensible and unifying demands, have the potential to form the foundations of a new and powerful populist coalition, one poised to help define a working-class agenda that meets this moment and resonates with disaffected voters. This excellent organizing should be cultivated rather than dismissed.

Alondra Nelson has a new paper in Science, The Civic Grammar for AI Rights, that’s worth a look:

Some commentary has argued that AI companies reaching for the vocabulary of constitutional democracy are attempting to fill a vacuum that democratic institutions can no longer hold. That reading is not wrong about the vacuum. But it is incomplete about which actors have moved to fill it. Not only technology companies, but legislators, civil society organizations, and the constituents they represent have produced a civic grammar: a shared set of rights claims that publics can extend to new institutions and new harms, and that has been traveling across jurisdictions, partisan lines, and institutional contexts.

The great novelist and playwright Ishmael Reed is working on a new play, called, wait for it, “King Ludd’s Revenge”.

From the NYT:

Mr. Reed, a novelist, playwright and provocateur who has been upsetting opinions across the political spectrum for at least six decades, is aiming high with a new drama. “King Ludd’s Revenge” is a rare attempt to take on the tech moguls with something more than mere journalism.

“Instead of a straight narrative, I improvise,” the 88-year-old writer said. “It’s like Louis Armstrong singing ‘Stardust.’ He doesn’t do it the way it’s written.”

Oakland is poorer, Blacker and more maligned than San Francisco and Silicon Valley, both of which are just across the bridges that span the Bay. Having the trial here happened at random — Mr. Musk’s lawsuit against Mr. Altman and the company they founded together, OpenAI, was filed in San Francisco and assigned to the federal court in Oakland — but feels a little like one of those episodes where the Greek gods descend to mundane Earth to settle a dispute.

Mr. Reed, an Oakland resident who has celebrated and defended the city for decades, may be the only one in town noticing who’s here. “Everybody’s focused on the N.B.A. playoffs,” he explained.

“King Ludd’s Revenge” takes its title from the legendary leader of the workers’ revolt in England in the early 19th century. With the ascent of A.I., the Luddites have come back into fashion. The play begins with Mr. Musk receiving a pedicure from a robot. Peter Thiel, the tech billionaire who backed President Trump in 2016, bursts into the room. “I think I’ve identified the leader of the Anti-Christ Syndicate,” he says.

Mr. Musk: “Who might that be?”

Mr. Thiel: “Greta Thunberg.”

Karen Hao on the Elon Musk vs Sam Altman courtroom drama:

…[F]ixating on questions of whether Altman is untrustworthy, or whether Musk is even less so distracts from a far deeper problem. If OpenAI lost its footing as the AI industry frontrunner, another barely distinguishable competitor – Musk’s xAI or other – would simply replace it. That includes companies like Anthropic, who enjoy a better reputation yet engage in many similar behaviors like compromising careful decision-making for speed, disregarding intellectual property, and aggressively scaling their computing infrastructure to the detriment of communities.

Nothing about this trial or OpenAI’s financial structure will change the imperial drive of these companies to consolidate ever-more data and capital, terraform the Earth, exhaust and displace labor, and embed themselves deep within the state to gain leverage over its apparatuses of violence. We would still exist in a world in which a tiny few have the profound power to cast it in their image and dictate how billions of people live.

Alright alright, that’s it for now. Have a good weekend everyone, and apologies if that was all a bit punchy, I’ve been fighting a cold all week. Until next time—hammers up.

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Those stories have largely described an industry on a grim trajectory: Opportunities and pay rates declining as clients and employers embrace generative AI. Artists getting more touch-up jobs and fewer well-paying, sustainable gigs. Pessimism, anger, and even despair, growing common, if not universal, in the field. The constant simmering outrage on social media, in other words, has felt pretty reflective of the reality on the ground. But then again, I’m just one guy. I’d tried to piece together as representative picture of the state of the industry as I could, but there was no wide-ranging study about the labor impacts of AI on artists to lean on, at least until now.

Three researchers at Carnegie Mellon University, Harry Jiang, Jordan Taylor, and William Agnew, surveyed nearly 400 professional visual artists about how generative AI has changed their working lives, income, opportunities, and outlook, and compiled the results into a paper they presented at the ACM (Association for Computing Machinery) CHI conference in April. Their findings are stark and alarming. They all but confirm that artists are experiencing nothing short of an AI-inflected crisis. In some cases, conditions are even more dire than I’d thought. But the work also offers keen insights into the details about how it’s all playing out, and even, dare I say, some reasons for hope.

Before we press on, I want to take a moment to shout a number of very worthy initiatives and projects on the AI resistance front. First, DAIR, the Distributed Artificial Intelligence Research Institute, is launching a Luddite Lab. It’s a resource hub, training center, and meeting place for workers resisting AI, automation, and big tech. It’s beautiful. The inaugural event will be held online next week; you can register here. Alex Hanna, DAIR’s director of research, shot me a note explaining the remit:

The Luddite Lab develops case studies, resources, and political education for unions and worker organizations who want to push back against “AI” and automation in the workplace and ensure that technology works for them, without undermining workplace democracy. We do this with workers, whether during the bargaining process, member education initiatives, or when they are simply trying to get their bearings. Our research and training is worker-led: we learn from other workers and translate that knowledge into case studies and primers available for other workers. We currently provide three different offerings: 1) an accessible resource hub which outlines case studies and strategies for governance and oversight of technology at work, both in general and for specific worker groups; and 2) office hours for workers interested in AI issues, and 3) training and curriculum for unions and other worker organizations around automation and AI.

Excellent. Second, the AI Now Institute, where I’m a journalist in residence, is hiring some key roles. Come join a great org. THIRD, speaking of great orgs, the latest edition of Academe, the magazine put out by the American Association of University Professors, is all about critical approaches to AI. Britt Paris is the head of AAUP’s AI committee, and she helped put the issue together; I haven’t finished reading through it all, but there’s so much good stuff, that I am looking forward to doing so. FOURTH, another friend of BITM, Lorena Gonzalez, the head of the California Labor Federation, represented the US at a recent tech conference at the Vatican, where she delivered this barn burner of a speech arguing for the dignity of workers in the age of AI.

Finally, if you’re in the LA area on May 23rd, I’ll be joining Zoe Bernard and Anya Jaremko-Greenwold for their first Stuffed event, Rage Against the Machine. They’ll be holding fireside chats in arty spaces with food from a top-tier chef. Tickets are here. Whew. As always, if you find this work useful or valuable, consider upgrading to a paid subscription; this newsletter is made possible entirely by readers like you. To anyone already chipping in, a million ludditic thanks. OKOK. Hammers up, and onwards.

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Surprise: Artists really, really hate AI. In fact, one of the Carnegie paper’s most striking findings is the sheer extent to which artists are refusing and abstaining from the technology. Sure, it’s been easy enough to intuit from any glancing contact with artists on social media that they harbor a great disdain for generative AI. But the numbers are something else. According to the survey, 99% of artists “disliked” AI; for 92%, the dislike was “strong.”

And that distaste translates into action, too. Per the survey, 85% of artists completely abstain from using AI at all. And 88% percent refusal use AI to generate images. That’s about as overwhelming a rejection of the technology as you’re likely to see in any field. It’s especially notable considering the gap is made up by those artists who feel forced to use AI by clients or by management.

The survey finds that artists concerns with the technology are rooted in both ethics and functionality. Two representative comments from artists reflect this:

“I have attempted to use some of these tools to assist in still image and short animation creation, but they have consistently failed to produce useable results.” (P311 ○V; illustrator, designer)

“I experimented with NightCafe and Midjourney when they were being developed (in beta). When I learned they were sourcing their art without permission of the artist, I stopped using them.”

“Participants viewed genAI as an intrusive technology within the creative domain,” the study’s authors conclude (emphasis mine; it’s a key concept). “We find that artists poorly receive genAI, while they are frequently faced with the artifacts of the technology; simultaneously, artists reject genAI by abstaining from the technology.”

Also quite striking is that all of the above remains the case while, as you can see in the chart above, a majority of artists encounter AI-generated images at work every week, and many encounter them every day. This is because so many of their clients and employers have taken to sending artists AI-generated images for “brainstorming” or for touching up directly. These numbers suggest that we’re looking at the degradation of a skilled trade in realtime, and the extent of the aggravated resentment artists feel make perfect sense. Here’s a technology product, after all, that’s been trained on their work without their consent, and is now producing subpar output that’s driving down their wages and rendering work less rewarding. And many have to encounter the AI-generated artifacts that make this fact unignorable every day. That, my friends, is how you get 99% of workers across an entire industry to dislike your technology.

These findings are also evidence that in many cases, AI image generation hasn’t replaced art outright (though in some cases it has), likely because it’s too homogenous, too unappealing to the public, and impossible to copyright as IP without alteration. But image generators are grinding down the craft, robbing it of key human elements, and pushing down wages, pay rates, and opportunities.

Most artists say that they feel that they’re now competing with AI-generated artwork on the marketplace. Well over half say that they’ve lost income due to image generators, while an overwhelming majority feel that their livelihoods have become more precarious and insecure, and 90% feel that AI has taken away commissions, jobs, and career opportunities.

The following quotes, pulled from the survey, help illustrate all of the above:

• “They fired me, so it has been a very hard pill to swallow.” (P270 ○V ; art director, concept artist, 3D artist)

• “I’m working on getting out of the field and planning to get my PhD in something non-art related because I can’t see my current work as being sustainable when I see them actively replacing me [with] chatGPT”. (P214 ○V ; costume designer, illustrator)

• Demoralization, disempowerment, disrespect, stress, and fear are also commonly expressed, not only regarding individual careers but also extending towards the field at large: “It’s been pretty demoralizing at times seeing a lot of younger artists giving up because they don’t see a future in art. That they’re abandoning their creative passions because of AI.” (P40 ○V ; illustrator)

• Some also lamented the public’s lack of appreciation of art in their adoption and consumption of genAI and its outputs: “It has been demoralizing largely because generated a.i. images look like crap but there is a segment of the population who seem not to care.”

All of these stories rhyme with the ones that were told to me, too.

AI appears to be a contributing factor to layoffs as well, and artists feel more generally that it’s eroded their power to negotiate with clients and bosses.

All of this is exactly in line with how automation has historically unfolded in impacted trades; the automation technologies allow bosses to wield leverage over workers, grant them a justification for lower prices, speeding up work, and replacing key meaningful tasks, if not eliminating the worker’s job altogether.

Now, there is dignity and value to be found in so many jobs, but it remains particularly galling, and particularly alarming to me, that in the AI industry’s assault on art—perhaps best evidenced recently by the mass layoffs at Disney, which were linked to a drive to use more AI—we are witnessing the attempted mass automation of artistic practice. That AI products are immiserating so many artists should be an urgent reason as any for us to stand up and ask, why? This is not limited to a Benjaminian concern over the fading aura of the work of art in the age of mechanical reproduction, or if it is, it’s exponentially aggravated. We are facing what might not be hyperbolic to describe as an existential threat to the very concept of the working artist itself.

I know, I know, I promised some good news, and so far this has very much not been that. Well, here it is, in the top line of the final chart:

While some industries, like advertising, have generally encouraged artists to use AI, others, like publishing, trended toward the opposite direction. Many artists surveyed noted that clients that put a premium on human-created work and promote high artistic standards have policies banning or discouraging generative AI use. Furthermore, use of AI is stigmatized among practitioners themselves in such fields.

Some key responses published in the survey:

• “My clients in publishing definitely discourage AI and strongly enforce against using the technology. However, in advertising it is less so; we see it increase through ads in subways, video, etc.” (P35 ○I ; illustrator)

• AI (non) use was also shaped by peer influences: “Being caught with AI art is a death sentence as an illustrator in any serious field. Art Directors will blacklist immediately” (P228 ○V ; scientific illustrator, concept artist),

• “Our [tattoo] shop tends to be pretty vocally opposed, but not everyone in the shop is” (P319 ○V ; tattoo artist, illustrator, 3D artist). Among those who said their work discouraged genAI, most artists were freelancers or had client-facing work.

• Participants reported that thier clients typically discouraged genAI use due to concerns over copyright, quality, and reputation: “Many clients have discouraged it, particularly in creative fields that value human work, but also in some fields where copyright, data protection, and NDAs are a concern, where we aren’t permitted to use it out of the safety of the company or the integrity of the data/work/research.”

• P83 (○V ; illustrator, traditional printer) felt that the spread of AI-generated art “just brought me more customers and has shown me, that people do care about handmade things much more than one thinks!”

That bifurcation here suggests that there will be a sustained interest in—and market for—art created by humans, and, perhaps more importantly, a potential source of political power for artists to tap into to bolster their position with employers in fields where that premium is placed.

“The narrative is that everyone is pushing for [AI],” as Jordan Taylor, one of the researchers, tells me. “The split in workplace encouragement,” between those that push AI and those that forbid it, “emphasizes that GenAI is not inevitable.”

To that end, Harry Jiang, another study author, notes that there are a number of implications raised by their findings. “I think on a small-p politics level, legislators and policymakers need to be careful about who they talk to,” he tells me. “It’s abundantly clear that the opinions on generative AI grow more positive and less anchored in labor reality the higher up someone is in the management level, so if that’s all legislators and policymakers are talking to, then they’ll be writing some seriously deficient bills.”

The researchers think that their findings might make it easier for artists to collectively bargain, and to push for AI usage disclosure, IP protections, and more data rights. “Tools shouldn’t be able to use your own data to replace you,” as Taylor puts it.

“On a more tangible level, it’s going to be quite clear that AI policy is labor policy,” Jiang adds.

You’ll find no arguments here.

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Some Bloody media hits

I did a couple media spots over the last week or two that I enjoyed, on 404’s podcast and Tech Won’t Save Us. Those spots are here:

Last but not least, thanks to everyone who came out to the talk at Oregon State University, and to Alicia Patterson, Megan Ward, the union (thanks for the shirt!), the wonderful students there, and the organizing crew. We had such a good chat about AI, automation, and the Luddites, and it was great to meet so many readers afterwards.

OK, that’s it for the week. Until next time, keep after that machinery hurtful to commonality.

While I’m pretty unconvinced on all but one or two of the points that the piece itself raises, and I think it seriously misconstrues the class politics of data center fights, I do think it’s worth litigating this idea. Because I do believe we should be thinking about what a broader and more engaged politics of resisting, regulating, and ultimately governing AI might look like. It’s a good occasion, in other words, to ask:

• Who is fighting data centers?

• Why are they fighting them?

• Are anti-data center movements a dead end—or a starting point?

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The author of the Jacobin piece, Holly Buck, is arguing from what you might call an ‘abundance left’ perspective; she takes a more techno-utopianist tack towards AI in general, and sees it as a force that could generate prosperity if governed properly. She argues that campaigns for data center moratoria, which she says are being led by home owners and affluent environmentalists, are an impediment to that effort, and will wind up pushing data center development offshore and forcing AI companies to raise prices. This will in turn reduce small business owners’, academics, and underprivileged communities’ access to AI.

These efforts seek to use the power and machinery of familiar NIMBY (“not in my backyard”) politics — local opposition, tying up projects in red tape, and so on — to confront the multiple perceived threats of galloping energy demand, carbon emissions, and job loss. Successful moratoria will curb digital growth by starving it of the physical energy needed to train and operate AI models.

Counterintuitively, a moratorium on AI data centers is a terrible idea — one that poses serious equity concerns. A moratorium springs from the desire to stop the concentration of wealth, but ironically, it is likely to exacerbate it. It’s a massive strategic blunder for the Left

Instead, she says, “funders and organizers in environmental groups leading data center blocking efforts should put their attention toward a broader set of solutions—including public engagement and education on the technology, the stakes, and the policy options.” As the headline of the piece puts it, democratic governance of AI is the real solution, not data center moratoria.

Who’s fighting the data centers?

To me, the biggest issue with the piece is that much of the argument rests on the charge that blocking data centers amounts to “class warfare.” Buck argues that “a lot of organizing to stop data centers is coming from wealthier communities and groups,” even though Buck admits “we lack a rigorous study” of who is protesting data centers and why. She writes:

The class particulars matter. What if the picture that emerges of “data center resistance” is one of educated middle-class people — including exurban and rural residents but also professionals who work in knowledge jobs — mobilizing, consciously or not, to protect their class position from the threats AI poses? How many of these people will block data centers but end up paying for a subscription to a frontier model once it is clear how useful it is to navigate daily work and life? It’s not fair for affluent environmentalists and property owners to try to stop development of this infrastructure before most people in the world have even had a chance to work with and learn from these models.

What’s strange about this is that there’s little need for a ‘what if’ here, because there are many organizations and news outlets currently tracking, tabulating, and covering data center development, and one can investigate the particulars of the cases without needing to lean on vibes-based speculation. I do understand where the temptation to invoke the NIMBY stereotype, which indeed foregrounds homeowners and affluent environmentalists, arises from. NIMBYs have been responsible for a lot of class warfare, especially when it comes to blocking housing development, and they’ve often done this under the auspices of pursuing progressive goals.

But the class particulars do matter, and in my experience reporting on the data center opposition, it has very much not been the case that “affluent environmentalists” are responsible for galvanizing, organizing, or underwriting the protests. One reason I’m writing this, in fact, is that I read Buck’s piece less than a week after attending a city council meeting in Monterey Park, California where a ban on data centers was under consideration (and ultimately approved). I listened to hours of residents’ animated, informed public comments in favor of banning them, and I found the disconnect between Buck’s assumption and what I’ve seen on the ground pretty yawning.

The residents who gave comment were a remarkably diverse group. There were many union members, and most appeared to be working class, which tracks; according to the most recent US Census data, the average annual income of a Monterey Park resident is $39,857. A couple people mentioned environmental issues, and some were what one could fairly characterize as NIMBYs, but what stuck out to me was the regularity with which residents connected rather reasonable local concerns to the broader picture.

What’s behind the data center fight?

They knew that they were facing higher electricity demand, noise and air pollution, and, sure, an eyesore in their backyards, and they also knew it was in exchange for what they felt was very little; a handful of mostly nonpermanent jobs and a technology that would primarily profit others, perhaps at their direct expense. Some comments connected AI to surveillance and warmaking, and at least one issued concerns about “techno-fascism.”

In that context, it seems condescending to imply that affluent environmentalists are running this movement. I saw a diverse collection of mostly working class people making a considered judgment, trying to protect their home and livelihoods, sure, but also weighing what AI is, and what it is promised to become, against those interests, and acting accordingly. Participating in democratic governance, in other words.

It’s not just Monterey Park, either. Buck asserts that “many data center projects appear to be sited in non-disadvantaged communities.” But, again, we probably shouldn’t just argue from the way things appear, and should instead turn to the available data, which shows that there are lots of projects proposed in disadvantaged communities—ironically, likely for very the reasons that Buck articulates: affluent homeowners and environmentalists are more likely to fight the hyperscalers, and tech companies, private equity firms, and developers would like to avoid those fights. I heard one Monterey Park resident say she assumed developers picked her sleepy town outside of Los Angeles because they thought they could get away with it.

To wit: Mother Jones ran a story just this month about how data center developers are targeting indigenous lands, and how local organizers are working to stop them. Indigenous campaigners, like those in Muskogee (Creek) Nation who successfully blocked a data center, are likely to cite environmental concerns, along with a legacy of colonialism and extraction, but they are not affluent. The median household income in Muskogee City is about $50,000 and 25% of the population lives below the poverty line. (The median household income in the United States is $84,000.) The Seminole Nation of Oklahoma’s tribal council recently voted to pass the first outright data center ban on indigenous land. The median household income there is $39,000.

It’s not limited to indigenous lands or Monterey Park, of course. The city council of San Marcos, Texas (median household income: $51,000, percentage of population below the poverty line: 27%) just rejected a 200 acre data center after overwhelming opposition. Public opposition to a data center in Coweta, Oklahoma (median household income: $67,000) spurred the developer to withdraw the project. Santa Teresa, New Mexico (median household income: $63,000) is home to a feisty fight to stop data center buildout. In Indianapolis, a city council member recently had his house shot at after he voted to approve a data center over community outcry; the median household income of Irvington, the neighborhood where the development is planned, is $59,600, per the most recent available data I could find.

In other words, the data center opposition sure looks like it’s comprised of working class people; I’ve seen and heard from farmers, teachers, students, indigenous activists, union members, community organizers and well-off NIMBYs and environmentalists. In fact, while I agree with Buck that more study of the particulars of data center resistance is needed, it seems to me that it’s just as possible to reach the opposite conclusion she does: that allowing tech oligopolies and private equity firms to dictate how and where AI infrastructure will be built, whether the residents like it or not, is a truer form of anti-democratic class warfare! Why should corporations whose values have been inflated with promises to eliminate millions of jobs be granted carte blanche to reshape communities—including ones that have been historically exploited, and are in fact low-income—and to extract their resources, so that tech firms might sell more and better software products?

The answer, to Buck, seems to be that AI provides enough advantage to users that we need to ensure everyone has access to it. She gives a couple examples:

I took undergraduate courses in calculus and in programming at the state school where I also work as a professor. It’s clear that, for many subjects, the personalized tutoring offered by AI is far better than the outdated lecture-based model still employed by universities.

Buck also celebrates the ways that AI saved her time and money navigating an immigration issue. These are the kind of benefits those with resources to pay for AI will enjoy while working people will not, if data center expansion is halted before they “even had a chance to work with and learn from these models.”

This too strikes me as faintly condescending. It’s been three and a half years since the AI boom began; most Americans have used AI. Just because the author finds value in it does not mean that everyone does, or that everyone finds it useful enough to want to support the current, hyper-capitalized development regime as laid out by profit-seeking firms in Silicon Valley. Or to warrant the social, economic, and environmental costs of AI more broadly. (I also think that many would contest the idea that it’s clear that AI is preferable to a human tutor.) A common knock against AI critics is that they extrapolate from ‘I haven’t found anything useful to do with AI’ to conclude that no one has. Yet the reverse can be true among advocates: many seem to believe since they have found lots of value in using the tool, sooner or later, everyone will. This just may not be true! The democracy-abiding position, the one with maximal solidarity with the working class, may in some cases be respecting its constituents’ refusal of AI as currently structured.

Why not pause the rapid buildout?

To that end, the other major shortcoming of Buck’s argument, in my view, is that she never really explains convincingly why the rush to build out data centers, as it’s happening, on the AI industry’s terms, is so necessary. The project in New Mexico I mentioned is being underwritten by Oracle, which has partnered with OpenAI to spend $300 billion on data center infrastructure. Both companies and their executives, especially Larry Ellison, have close ties to the Trump administration—they’re the key parties to the $500 billion Stargate project, Oracle is Palantir’s cloud partner, etc—and their partnership is predicated on building AI enterprise software. I legitimately don’t understand why the socialist left would want to support the construction of a project that helps these firms meet their goals of building out mass automation and surveillance programs. As others have pointed out, moratoria like the one Bernie Sanders and Alexandria Ocasio-Cortez have proposed are designed to buy time to work questions like that out—to develop good governance and regulation of AI—not install a permanent ban.

So why is it imperative that we build every data center that Google, OpenAI, and Meta want us to? Why can’t we democratically negotiate not just siting issues and infrastructure development but what the actual demand for AI is going to be, the uses to which we want it to be put? There isn’t really an answer in the piece that I see, except a somewhat odd nod to Anthropic’s “too-powerful-to release” Mythos model, which has been widely criticized as a PR stunt, as evidence that the US needs to “develop powerful AI first.” This is the same line that the AI lobby uses to argue that it should not be subject to regulation in general. It also remains unclear to me why the United States, which has now used AI in two separate wartime actions that were not approved by Congress, in Venezuela and Iran, by an administration that is capricious and reckless, has close ties to most major AI firms, and is doing all it can to deregulate the industry, would be a better steward of a very powerful AI than any foreign power.

Finally, I’m skeptical of the idea that shutting down some percentage of data centers through community organizing or statewide legislation will meaningfully create some kind of digital divide between the AI haves and the have-nots. Buck argues that

Offshoring will put limitations on compute that will induce tech companies to raise prices, and small businesses, academic and nonprofit researchers, and individuals would be the first to lose access. Larger companies would just buy access to the top-tier AI. A moratorium will result in a business landscape that favors incumbents. This has global implications for students, small business owners, and first-generation professionals in emerging economies…

…the latest version of the “poverty premium” is shaping up: a society where educated middle-class people like me will pay the monthly fees for these services, learning and moving through life with less friction, while people who can’t afford the subscription are stuck in the system and end up paying more. This AI-enhanced poverty premium is not a distant prospect but a few years away — and it is made more likely by a moratorium that limits computation.

This is indeed not a distant prospect: it’s already happening, data center moratoria or not. Larger companies are already buying access to top tier AI. Universities have less access to compute for AI research than the commercial AI labs; it’s one reason so many academics are turning to the private sector (also: the insane amounts of money on offer). The wealthy already have a huge leg up in terms of AI use: Who can afford to pay $100 a month for premium tier Claude subscription? Certainly not most working class people! Furthermore, AI firms are already raising their rates and intensifying this bifurcation, to begin to try to cover costs of a deeply resource-intensive business that is still not profitable. Even if the data center buildout continues apace, I would bet my life savings on Kalshi that we’re going to see a digital divide exacerbate in coming years, with the rich, Fortune 500 companies, and tech firms not just using the most AI but dictating the terms of that use for everyone else.

This is ultimately the key issue. Tech utopianists and abundists view AI as a potentially equalizing, even liberating force, but history shows us that without political intervention or strong unions, those with the power to deploy labor-saving automation technologies at scale, to use it as leverage against workers who cannot, will themselves concentrate the gains from productivity increases. In their bid to replace labor with software subscription fees, AI companies are effectively attempting a mass transfer of wealth from the working and middle classes to the rich. The most likely outcome of any data center buildout that successfully engenders more capable automation tools is a concentration of wealth and power among the companies selling them. I’m not sure how slowing the buildout of the key capital equipment enabling a handful of firms to pursue mass automation will lead to inequality; if anything it’s one of the few means available to contest the expansion of power of firms like OpenAI and Google.

Fighting data centers is just the beginning

I do agree with Buck on two key points: We should certainly be cognizant of the shaky nature of the political coalitions forming to fight data centers. She’s right that these can also encompass reactionary elements, and in the long run, on their own, will likely prove untenable as a serious political force. But that’s only if no efforts are made to expand the political fights begun at data centers into larger arenas.

Because Buck is also right that shutting down a data centers cannot be viewed as a finish line. Yet where she sees the anti-data center movement as incompatible with efforts to aspire to democratically govern AI, I see them as a potent—even necessary—starting point. AI is widely unpopular; acts of refusal are springing up across the nation. But it’s not the base technology people are angry at; it’s the political economy. It’s the firms promising to kill jobs, unscrupulous billionaire executives at the helm, and hyperscalers descending on communities with enormous infrastructure projects. The big question for the left is, as I’ve written before, how to confront the malign forces while encouraging good, truly democratically guided AI development and use.

So far, of course, we’ve had the opposite of democratic governance of AI, though not for want of trying. Organizers, funders, nonprofits, and local and state level politicians have been pouring time and resources into shaping AI policy; Alex Bores’ recent dividend proposal comes to mind, as well as the rafts of laws proposed in California, New York, Florida, and beyond. Alas, the AI industry’s lobby spent millions thwarting many of those efforts, which have been killed or vetoed. As a result, these data center fights have essentially become proxy sites for democratic governance of AI; places where citizens can still register a vote about their future in a world that feels increasingly dominated by dark money and tech oligarchs.

The left shouldn’t be shunning the data center opposition movement; it should be listening to it, joining it in the trenches, building solidarity, and figuring out how to channel the groundswell of anger at AI into more durable political efforts that will lead to more equitable outcomes, for AI service distribution and otherwise. Can the momentum of the data center movement be tapped to agitate for local labor organizing? Stronger state AI laws? Into more ambitious efforts to expand the social safety net? (If a data center is going to replace jobs, should they be taxed to pay for universal healthcare, etc?) Or, might using the threat to block data centers provide political leverage to push to have AI regulated like a public utility, as Buck has proposed elsewhere?

It should also recognize that if the people manage to shut down a multibillion dollar Oracle/OpenAI data center, they’re shutting down infrastructure that would be used as capacity for mass surveillance and deskilling labor—and understand why many consider that a victory.

Go to a city council hearing on data centers and listen. (Chances are, there’s one near you.) What I expect you will hear is that, from negating democracy, data center opposition is where some of the most promising AI democracy is happening. It’s unruly and politically inchoate, sure, but the data center fight, with farmers and environmentalists and indigenous and working class people side by side, is an opportunity to grow and catalyze working class power. Fighting data centers is where good AI governance begins, not ends.

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For what it’s worth, my intent here was not to do a snippy takedown of Buck’s piece, but to think through its implications. I’m glad to see more discussion around how to make AI work for the people rather than big tech, and while disagree with it pretty vehemently, I’m glad Buck ushered in this debate. I had some of my own assumptions and priors challenged, and it clarified my thinking on a few points. And I do recommend wholeheartedly the previous essay she published for Jacobin, with Matt Huber, “Treat AI Like A Public Utility.” It’s an intriguing idea.

Also good in Jacobin this week: A discussion of Harry Braverman, monopoly power, and how management uses technology to degrade work.

Good elsewhere:

• Elizabeth Lopatto on Oracle as a bellwether for the AI bubble in the Verge.

• Kate Conger and Theodore Schliefer on Google co-founder Sergey Brin’s hard turn to the right in the New York Times. (Lots of wild and depressing details in this one)

• WIRED’s coverage of the Musk vs Altman trial over OpenAI.

• Ed Ongweso Jr and Jathan Sadowski of This Machine Kills did a segment on the data center debate, too. I saw it come through my feed just as I was wrapping this post; so far it’s a great compliment to some of my arguments, and covers even more ground.

• Google employees are speaking out against their company’s new contract with the Department of Defense:

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Okay! That’s it for today. Thanks as always for reading, and more soon. Hammers up.

• 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.

Thanks for reading BLOOD IN THE MACHINE. This newsletter is made possible by paid supporters who chip in a few bucks each month (or $60 a year) so I can keep the lights on to do this reporting and writing. If you find value in BITM, and in helping to keep posts like this free for all to read, please consider upgrading to a paid subscription. Many thanks, and hammers up.

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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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