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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

The human labor that make Waymos possible

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

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

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

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

Current: A lot?

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

The Future is Not Tech-Forward

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

Here’s a taste:

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

Read the whole thing:

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

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

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

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

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

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

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

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

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

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

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

First, a few more notable findings from the report:

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Other stories mentioned in the segment and the interview:

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

Heatmap’s latest data center sentiment poll.

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

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

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

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

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

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

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

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

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

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

Here are a couple more headlines, for good measure:

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

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

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

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

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

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

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

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

It’s a thing of beauty, really.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Thanks as always for reading and listening. Hammers up.

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

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

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

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

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

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

On the Texas data center pause

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

Via a press release from the state:

Audit Must Be Completed Before Any Data Center Project Moves Forward

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

The New York Times reports:

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

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

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

Is AI solving climate change yet?

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

From the story:

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

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

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

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

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

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

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

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

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

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

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

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

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

The historian Spencer McDaniels explains:

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Or, in English:

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

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

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

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

Or more colorfully:

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

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

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

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

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

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

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

A dispatch from the days of Ludd

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

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

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

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

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

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

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

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

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

Who should take this survey?

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

Why are we doing this survey now?

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Dendir also notes that

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

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

So what is VAR doing, then?

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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Some related reading:

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

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

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

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

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

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

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

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

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

404 Media reports:

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

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

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

Big data center resistance news:

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

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

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

The Guardian reports:

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

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

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

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

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

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

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

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

According to the Cowboy State Daily news:

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Until next time, everyone—hammers up.

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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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