Critical takes on tech - BlogFlock

The best books, films and TV about AI + tech in 2025 - Blood in the Machine

2025-12-22T14:05:25.000Z

Greetings everyone -

The year is drawing to an end, and that means every other link you click is a Best of 2025 list. And you know what, that’s just fine; if you’re at all like me, you just keep on clicking. Give me more of the best stuff, show me what all the best stuff was, I can’t get enough of it. And I’ll tell you what, I’m even going to contribute to this benevolent plague of listmaking, because I haven’t yet seen what I want, and what dear readers of this newsletter might want: A guide to the media that critically examined the role of technology in politics, culture, and society.

Speaking of those readers: Permit me to embrace the season of sentimentality and get real with you all for a minute here before we get onto the lists. I want to say thank you for reading, discussing, and supporting this work through what was a particularly dark year. When I went all in on this thing back in February, I really had no idea whether it could become a monetarily viable long-term undertaking aka a job. As I recently discussed at (much) greater length, you’ve all shown me it can be. I still have a lot of work to do and goals to meet. But I count myself as beyond fortunate to be able to do this work, on my terms: to try make sense of the world of AI and its impact on the working class, to document the rise of the tech oligarchy, and to write long-winded reviews of Frankenstein.

There are now 33,000 beautiful machine breaking subscribers here, many more than I would have predicted this time last year. Cheers to you all, with an extra emphatic thanks to those of you who support this work with your hard-earned cash—it’s you who quite actually make all of this materially possible, and I would not have been able to do any of this without you. There would be no AI Killed My Job stories, no investigations into LA’s torched Waymos of LA, no dispatches from the frontlines of the Luddite renaissance. Thanks again everyone.

I’m going to take a couple weeks off for the holidays here, though hopefully this ~8 million word edition will help tide you over, and I’ve scheduled another special post or two to help fill the gap. But I’m going to try to log off for real: You know, ditch the laptop, power down the phone, hang out with the fam and read through a stack of Ursula K. Le Guin novels. I’ll be back in the New Year. Until then, what else—hammers up.

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The best nonfiction books on tech of 2025

Careless People

Okay, so I’m starting the list off with a curveball, because I don’t actually think this was one of the ‘best’ books of the year, as it’s frustratingly uncritical in a host of ways. But Sarah Wynn-Williams’ memoir about her time as a lower-level executive at Facebook may be the best inside-the-palace look we’ve gotten at the workings of its c-suite, and at Mark Zuckerberg’s personal politics and motivations.

This alone makes it invaluable. The book helps us better grasp the deep vanity and omnipresent insecurity that wracks Zuck, a man who views himself as a modern-day Roman emperor yet who is childish and petulant and never quite sure about what he’s supposed to be doing unless it’s shipping code. We knew Facebook’s management was reckless and ignorant, this book draws those operational deficiencies into starker focus; we see opportunities Facebook had early on to consider data privacy (via feedback from the German government), its toxic impact on young people, especially girls (via its own internal marketing documents that sell the platform’s power over vulnerable users to clients), and the looming dangers of its hands-off policy in Myanmar (via the author’s own multiple engagements with the junta), where the UN later determined a military dictatorship used Facebook to help foment a genocide.

The problem is, Wynn-Williams goes to great lengths to exempt herself from any serious blame or reckoning. She perennially casts herself as naively believing in the power of the platform to connect people, despite everything, and the act gets old quick. A better book would more honestly interrogate her own role, and examine how it is that even well-meaning employees come to abet such an obviously amoral enterprise. Still, it’s a brisk read, illuminating, and will deepen your understanding of the politics and postures of the Big Tech executive set.

Notes Toward a Digital Workers’ Inquiry

One of the keys to building a better future is getting more tech workers organized; both the better-paid (if increasingly precariously employed) engineers and product people at the big tech companies, and the much lower-paid gig workers who make up an ever-growing share of the workforce. This book by the Capacitor Collective—a group of respected tech researchers and activist scholars—is an invaluable resource for anyone interested in sparking that fire. And we all should be.

The AI Con

Few have done more to peel away the layers of AI hype that pervade the headlines and punditry than linguist Emily Bender and sociologist Alex Hanna. Both are esteemed scholars and lively writers, and the book is a compelling, clear-eyed analysis of modern AI and the industry hocking it. Somewhat surprisingly, it isn’t always as polemical as you might think, given the title and the authors’ knives-out commentary on their podcast. In fact, I’d go so far as to say that it’s an ideal primer for the layperson about how large language models really work, and a nice dissection of how the industry manufactures then exploits misconceptions about AI for profit.

The Contrarian

Penguin Books published a new paperback edition of Max Chafkin’s extremely readable biography of Peter Thiel this year, and it’s easy to see why. The book, originally published in 2021, charts the rise and dealings of the first Silicon Valley mainstay to openly embrace Trump. Its new tagline, “Peter Thiel and the Rise of the Silicon Valley Oligarchs,” and new cover, which features the now-infamous photo of Jeff Bezos, Sundar Picchai, Elon Musk, and Mark Zuckerberg at the inauguration, underline its newfangled relevance in big black sharpie.

The fresh coat of paint is well-deserved; the book is an illuminating look not just at Thiel but at the politics of the tech right, its roots, and how Thiel and his cohort—including Trump’s now-AI czar David Sacks—helped foist it all to power. The first half especially is a must-read, given where we’ve wound up. It details Thiel’s days as a rightwing campus culture warrior at Stanford, the scammy tactics he adopted at PayPal to juice its rise, and his murky maneuverings at Palantir. It’s also a great companion piece to the next book on the list, too.

Gilded Rage

Free idea: Have your reading group or book club to do a ‘rise of the American tech oligarchy’ two-parter, starting with the Contrarian to get the origin story, then hitting Jacob Silverman’s Gilded Rage next to see how it’s played out. Silverman spends more time with Musk, for the obvious reasons, and delves into many sordid corners of the new tech elites’ world in his effort to understand the nature of their quest for power and dominance.

Silverman and I chatted about his book for the blog here earlier this year, and here’s what I wrote about the book then:

David Sacks, Elon Musk’s compatriot, is the White House’s AI and crypto czar. Executives from the VC firm Andreessen Horowitz, or a16z, are in advisory roles. JD Vance, whose mentor was Peter Thiel, owes his career to Valley operators. And not only are they in power, but they’re angry. They practice a politics of pitched persecution and extreme resentment that can be baffling to those of us who’d kill to simply not have to worry about paying the rent for a year. As Silverman puts it in his book, these tech titans “had the world at their fingertips and they couldn’t stand the touch.”
Silverman’s book… argues that we shouldn’t view the tech billionaires as a collection of eccentric elites, but as a class; a group that, whether they publicly present as liberals or conservatives, share a distinct set of ambitions and goals: Slashing regulations and oversight, lowering taxes, extracting value from the state, and concentrating power.

Essential reading for understanding the shape of power in the age of the tech billionaire.

Against Platforms

A sharp and erudite argument against, well, platforms. What can I say, ’s book does what it sets out to do: It makes the case against techno-utopianism, and articulates how and shy turning over our public services and sociality to culture- and civics-agnostic profit-seeking tech companies has been a disaster. It’s a compelling call to replace those platforms, from the gig work apps to social media networks, with institutions, and a much-needed one. Plus, it’s short! You can read it in an evening or two. More good short books, please—and fewer platforms.

Why We Fear AI

Another good short book! This one, by cognitive scientist Hagen Blix and machine learning researcher Ingeborg Glimmer, argues that we fear AI not because we fear the unknown, or some undefinable future, but because it embodies the worst traits of capitalism: surveillance, wage suppression, mass automation. Our nightmares about getting crushed by an all-powerful Skynet are really nightmares about getting crushed by the ruling class. The book carries a little extra weight since it was authored by scientists working in the field, not Jacobin columnists—nothing against the Jacobin columnists of course—and all in all, I found it compelling and persuasive. Pairs well with Ted Chiang’s great essay “Will A.I. Become the Next McKinsey?”

In my interview with Blix, he described AI as “an attack from above on wages.” Find that one here:

Enshittification

The book that likely needs no introduction, about the word and idea that needs less of one, by the author you all probably know, too. Cory writes so many books it can be hard to keep up, and as such, I was a little late to this one. I think it’s his best and most complete nonfiction work to date; it’s certainly the one I’ll be recommending to folks going forward. In rapid-fire, digestible prose, Cory unloads his signature blend of sagacity and snark, and imbues the enshittification coinage with a sturdy theoretical framework.

Cory and I chatted about the book, how enshittification impacts labor, and much else, a few months back:

Good stuff.

Mood Machine

I recently quit Spotify. Mood Machine is, essentially, the story of why. Liz Pelly’s treatise is at once a history of the dominant music streaming app’s rise to prominence—with some fascinating detail about its roots in Sweden’s piracy culture—and an unsparing critical analysis of its impact on art, culture, and working conditions for musicians. It’s the kind of book that gets called a “savage indictment” in reviews, and for good reason. Read it to understand what Silicon Valley’s model of cultural production and distribution, of relentlessly focusing on scale and maximizing time on platform, has wrought to music.

The Mechanic and the Luddite

A great (and highly readable, I promise) book advancing a critical theory of modern luddism. The sociologist Jathan Sadowski is probably best known as the co-host of This Machine Kills, one of the best critical tech podcasts going, but he’s also a great thinker on the political economy of technology. And we can all use a ruthless criticism of technology and capitalism about now.

Empire of AI

What else can I say? Karen Hao’s Empire of AI is an epic feat of writing and reportage. If you want to understand OpenAI, Sam Altman, and the AI boom writ large, this is the book to turn to. It’s definitive. And it’s compelling, from start to finish; from the boardroom drama at OpenAI to the reporting trips to Kenya and Chile to shed light on the labor and environmental issues incurred by AI development, the pages keep turning.1 I read this in a couple days, even though it’s a behemoth, simply because I couldn’t put it down.

Given the stubborn centrality of all things AI—and therefore all things OpenAI—this really is one of those rare books you can say “everyone should read” and be totally sincere.

Other notable and good books, about tech or otherwise

Look, I’m just one guy. This is list is not exhaustive, and I wish I’d had the chance to read even more new tech nonfiction, an impossibility given the state of everything, and how busy I was all year. Seriously, I just grabbed all the tech books in arm’s length that I was sent this year onto a pile and just look at this thing.

That’s just this year, and I’m missing a bunch, too.

Needless to say, there was a lot of great non-tech stuff, great tech books I didn’t quite get to reading or processing fully, and older works I revisited that I found plenty relevant to the times. Here’s some of that:

Algorithm of the Night

A.S. Hamrah is one of my favorite film critics. Top three, easy. I always look forward to his short reviews in n+1 and enjoy his longer stuff elsewhere; they’re about the entertainment industry, capitalism, and political economy as much as they are about the films themselves. The Earth Dies Streaming (untouchable title), his first book of collected writing, was great, and so is this year’s followup, Algorithm of the Night. The opening essay alone is worth the price of admission, and I’ve found I’m keeping the tome, which is mostly stuffed with reviews, handy to consult after watching newer films covered in the volume.

One Day Everyone Will Have Always Been Against This

Brutal, beautiful book about confronting the genocide in Gaza back here in the states by the great speculative fiction writer Omar el-Akkad. It won the National Book Award, too.

Bullshit Jobs

I reread the late anthropologist David Graeber’s crossover bestseller this year, and at some point I’ll share some thoughts on how its thesis applies in the age of corporate AI automation; funny, cutting, great, if uneven, book.

Bubbles and Crashes

This book, by two business professors and economic historians, formed the foundations of a piece I wrote for WIRED about the AI bubble. Invaluable for the historical context of the AI boom, and for understanding what makes a tech bubble a bubble.

October

I revisited China Meiville’s narrative history of the Russian revolution this year; another historical page-turner. Wrote more about that here:

So many good books

And here’s a short list of books I either haven’t gotten to yet but are on my pile and look great, or have started in on/are otherwise notable and worth checking out:

Atomic Dreams, by Rebecca Tuhus Dubrow
Extraction, by Thea Rianfracos
The Pacific Circuit, by Alexis Madrigal
More Everything Forever, by Adam Becker
Stream Big, by Nathan Grayson
Every Screen on the Planet, Emily Baker-White
Fatal Abstraction, by Darryl Campbell
Robin Hood Math, by Noah Giansiracusa
Fake Work, by Leigh Clare la Berge
Searches: Selfhood in the Digital Age, by Vauhini Vara
World Eaters, by Catherine Bracy
Scam, by Ivan Franceschini, Ling Li and Mark Bo
Amateurs!, by Joanna Walsh
Artificial Humanities, by Nina Begus
Language Machines, by Leif Weatherby
Algospeak, by Adam Aleksic

TV

Black Mirror

Yes, it’s become a punchline to some, sure, the filler to hit ratio is expanding, and no, this was not its best season. But despite lacking a Joan is Awful-type zeitgeist definer or a Be Right Back-level banger, it nailed some Black Mirror-isms—the gleefully unsubtle opener about privatized startup health care and the blue collar worker debasing himself to afford it was very much on brand—and delivered some solidly bleak future moods.

I will watch every episode of this show Charlie Brooker ever airs and I will apologize to no one.

Alien: Earth

Alien is for my money our best science fiction franchise, and it’s always been a pretty reliable vehicle for critiques of AI and corporate power. I thought Noah Hawley’s take was pretty fun (with great creature design) even if the initial promise of its taking place in a society governed outright by tech billionaires—one run by the famed Yutani, or Weiland-Yutani no less—didn’t bear much fruit. I wish it had focused less on the child-robot hybrids and more on that, but you do get some good Frankenstein stuff, billionaire caricatures, and a top-form android Timothy Olyphant.

Pluribus

Whether or not the show is supposed to be about AI is almost beside the point; Pluribus nicely articulates the threat of mass homogenization and lost human companionship a lot of us are feeling right now. (Though the scene where the alien cipher recites insipid reviews of the fantasy author’s book has to be a riff on ChatGPT, I don’t care what Vince Gilligan says.) Ideally suited sci-fi for a moment in which AI is quite actually making people who use it sound the same.

The Chair Company

Maybe gets my vote for the best show about technology of the year, despite not really being about technology at all. After an embarrassing incident at a high-profile sends Tim Robinson’s spiritually hollowed-out company man spiraling, he turns to the internet for answers, where his efforts to speak to an actual human are denied but where he instead finds a wealth of materials inscrutable enough to mean anything, and a prime opportunity to recast himself as protagonist in his own life. It’s almost like a Crying of Lot 49 for the 2020s with anger management issues. There’s a riff on QAnon-type online conspiracy theorizing in here, but it’s more about how late capitalism has stranded us in a wasteland of obsolescing malls, alien corporate cultures, and indecipherable digital media, and left us to find purpose amidst the wreckage. Robinson’s hero reaches out for answers, only to be waylaid by automated customer service systems, websites for shell companies, and angry social media posts. (And finds solace in the YouTube comment section.) I just wish the show bothered to properly close out the season’s arc; otherwise, it’s fittingly anxious, dark, and extremely funny.

Film

The Shrouds

A strange film, even for Cronenberg, in part due to its subdued tone. A review I read somewhere that I can’t find now mused that it felt more like people talking about making a Cronenberg movie than a Cronenberg movie. Fortunately that still makes for a better film than most directors can muster. It’s about a grieving widower who is so obsessed with his deceased wife’s body that he builds a system that allows him to watch it decay in the ground and turns it into a startup so others can do the same with their dead loved ones. Then there’s sabotage, dubious biotech, and corporate intrigue, and it gets weirder from there.

Mickey 17

Bong Joon-ho in his madcap anticapitalist sci-fi mode; his Okja/Host/Snowpiercer mode, which I happen to love. This is not the very best of the films in said mode, but I still think it got unfairly overlooked. True, Joon-ho could have done a lot more with the conceit of an endlessly reprintable and thus expendable human worker, but the sequence that details Mickey’s initiation into his new life as an infinitely immiserated lands the film a spot on this list.

Frankenstein

In which Guillermo del Toro gets Frankenstein’s monster right for a change. I very enjoyed this film; so much so that I wrote about it at length here:

Companion

My favorite luddite horror film of the year. Clever and misanthropic, it capably (and gorily) subverts the AI/robot run amok trope. I won’t say much more, since it feels like it hasn’t been widely seen yet, and this is one that’s better watched cold. Suffice to say that the film makes a rather visceral case both that AI is an ideal vessel for abuse and exploitation and that maybe we *should* be suspicious of anyone who’s too into their chatbot.

Bonus: Best anti-AI death metal album

That would be The Diseased Machine, by Mutagenic Host.

Please enjoy an album full of songs like “S.W.A.R.M. (Systematic War Against Restless Machines)” and “Artificial Harvest of the Obscene.”

Alright everyone, thanks again for reading. Hope you find something good to read or watch in there. Drop any of your own recs in the comments below, and I’ll look forward to firing things up again in the new year. Until then: cheers all, and onwards.

Issues with numbers in a government report on data centers she cited in the book have been pointed out; Hao has handled them with grace, and issued the necessary corrections. This doesn’t blunt the impact of her book one bit.

There has to be a way - Blood in the Machine

2025-12-18T04:48:48.000Z

Stanford’s Paul Brest Hall was so packed I had to find a spot to sit on the floor. It was a Monday morning, December 8th, and every last chair was taken; spectators lined the walls and shuffled around in the back. The restless majority were artists, writers, and actors; they had come to this special hearing to offer public comment in favor of a proposed California law that promised a sliver of leverage against the AI companies headquartered mere miles away.

Assembly Bill 412, aka the AI Copyright Transparency Act, was authored by assemblywoman Rebecca Bauer-Kahan, a leading figure in California AI policy;1 it would require AI companies to document what goes into their training models, and alert copyright holders if their work is included upon request. Last summer, AB 412 received a similarly packed hearing in Sacramento before it was shelved and punted to the 2026 legislative session. Hence this second event, on a crisp Bay Area winter day, taking place in what multiple artists, some relishing the irony of the battleground they occupied, others with something closer to trepidation, referred to as “the heart of Silicon Valley.”

Before most of those gathered in the crowd could speak, a series of expert testimonies would offer a snapshot of the economic and legal complexities of the issue at hand, and the many challenges in addressing that issue. The issue, as articulated by the artists on the panel, and later, by the scores of people packing the room, and which is plenty familiar to many by now, is that companies like OpenAI, Anthropic, Google, and Meta have trained their AI models on millions of copyrighted works, including those created by the artists and writers present, and turned those models into commercial products that create competing works for dirt cheap.

As a result, and as I have spent much of 2025 documenting, many creatives are losing jobs, opportunities, and income. While pesky concerns like reliability and accuracy hold back efforts to automate many other fields with LLMs, creative output need only be deemed ‘good enough’ by clients and bosses. As a result, many feel that commercial AI poses a direct and even existential threat to their livelihoods. To them, AB 412 offers a first step towards receiving consent, credit, and compensation for their work, as the now-famous triplet goes.

This reporting is made possible by those subscribers who shell out $6 a month, or $60 a year—the cost of a cup of coffee a month or so—to support it. Those who pitch in have my infinite thanks, especially on this grim yet somehow hopeful holiday season. If you can, consider joining the ranks of supporters, so I can continue to do this work. Thanks again, and happy holidays from the offices of Ned Ludd Inc.

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“I don’t know how many of you have come to LA recently,” Danny Lin, the president of the Animation Guild, said in her testimony, “but it is bleeding out in front of my very eyes.” AI, she said, was exacerbating trends already put in motion by big tech’s squeezing of the entertainment industry. “[AI] has the potential to devastate not only California’s creative workforce and our employment prospects but curtail intellectual property rights and the profits of related businesses,” said Jason George, an actor on Grey’s Anatomy and a SAG-AFTRA board member. Each time one of the artists made a point about their working conditions or called for oversight of the AI industry, a sea of jazz hands would go up in the crowd, and applause would begin to break out before everyone remembered they were supposed to stay quiet.

George expressed concern for voice actors in particular, who, he said, within three to five years, “are in trouble.” He pointed also to the AI-generated country song “Walk My Walk,” seemingly cribbed from the black country musician Blanco Brown and presented as the work of a white (AI) country artist, Breaking Rust, “getting the Blanco without the Brown,” as George put it.

The challenges in addressing all of this, meanwhile, are enormous. Ultimately, overcoming those challenges in any durable and sustainable way will require answering questions about what art, cultural production, and even work itself should look like in an age of ultra cheap content autogeneration. But the first and maybe largest challenge is that the AI companies do not in any way want to address the challenge at all, and also have multibillion dollar war chests and the attendant political influence to dedicate to the project of not addressing it. Out of the four AI companies invited to attend the hearing—Google, OpenAI, Meta, and Amazon—only OpenAI bothered to send a representative.

Mark Gray, OpenAI’s copyright policy counsel, mostly offered boilerplate answers to the legislators’ questions, as well as some platitudes about how AI was meant to be “assistive”, not to replace artists. He pointed to licensing and partnership deals AI companies struck with Netflix and media companies as evidence that transparency and copyright legislation wasn’t necessary. (This made my ears prick up: There’s been a lot of debate in the journalism world over whether publishers should be entering into licensing deals with the AI companies. Here, it was clear that OpenAI was using those deals as political capital to discourage attempts to hold them accountable for using copyrighted work without consent elsewhere.) Lin, the animator, responded by noting that creatives in her Guild and at the media companies that inked those deals have only seen their working conditions deteriorate; there’ve been layoffs, work speed-up, and precarity. The deals benefit management, Lin meant, not working artists.

Image via svgsilh.com, under a CC0 1.0 Universal license.

“Is copyright as a tool, the right tool to do this, or is that through tools like industrial policy, labor protections, labor law, those sorts of tools?” Gray said, to scattered mutterings in the crowd. “From [OpenAI’s] perspective, copyright at the federal level is not the right lever to pull.”

This, it might be noted, is corporate lobbying 101; say *this* policy option isn’t right but *another* one, maybe even a stronger but less politically feasible one, is. (It reminded me of years ago when Exxon said it was against a cap and trade climate policy that would limit pollution, but was in favor of a more punitive carbon tax, knowing such a policy was politically impossible.) And it was especially rich coming right after the AI companies lobbied Gavin Newsom to veto the No Robo Bosses Act, which he did, and which would have offered the tiniest of labor protections to workers from bosses seeking to automate the firing process, presumably the kind of “tool” Gray was indicating should be used in lieu of copyright law.

“Hearing him speak is killing me,” the artist Karla Ortiz said at the hearing. Ortiz is one of the plaintiffs in a class action lawsuit against AI image generation companies like Midjourney, and until last year, Gray worked for the US Copyright Office, where he was the first contact for the case. He attended a town hall where he heard working artists detail their plight. He has since been hired by OpenAI, where he is now actively opposing their interests. “I want to tell him to his face how much he broke my heart,” Ortiz said. Judging by the legion of scowling faces behind him at the hearing, it seems unlikely he won any others.

Gray’s story is a good example of how exactly large tech firms like OpenAI can wield their considerable stores of capital to stack the deck in their favor, whether by buying out government officials, mounting lobbying campaigns, or sidling up to the Trump White House. While the story of AI’s impact on creative industries is not purely a matter of corporate interests dominating those of the working class, it’s certainly a large part of it.

Rishi Bommasani, a senior researcher at the Stanford Institute for Human-Centered Artificial Intelligence, noted in his testimony that there is vast information asymmetry between AI companies and copyright holders, and that the public currently has little to no knowledge about what goes into the AI companies’ datasets, even the open source ones, and has no way of finding out. The AI companies want to keep it that way. They consider the composition of those datasets trade secrets, they don’t want to dedicate the resources to documenting which copyrighted materials are in their datasets, especially if such a practice turns out to violate standing copyright law, and they certainly don’t want to have to oversee any system that would alert creatives and rights holders when their works were used to train AI models, much less compensate them.

Both Pamela Samuelson, a professor of law at UC Berkeley and board member of the Electronic Frontier Foundation, and Mark Lemley, a professor of law at Stanford who until earlier this year provided legal counsel to Meta, cast doubt on copyright law as a viable vehicle for regulating AI in their testimonies. (The EFF has opposed AB 412 from the start, arguing that the law’s documentation requirements would “bury small AI companies” and leave the big players as the only ones able to navigate the requirements. I find it difficult to muster much sympathy for this argument, perhaps as a result of having interviewed scores of creative workers whose incomes have been halved or worse by clients and bosses replacing their work with cheap AI output. Why should developers of automation tools enjoy such considerations while those being automated do not?)

Samuelson said that she believes courts will ultimately consider it fair use to train AI models on copyrighted works, though the jury is still out on the issue, as decisions have been somewhat split in the US, and have been more favorable to rightsholders in Europe. Lemley argued that building a copyright documentation system would hamper innovation, and made his disdain for the entire concept plain. It is indeed a common refrain among the AI executive class that paying the license every copyrighted work in their models would be impossible, bankrupt them, or cause them to lose the AI race to China.

Gerard de Graaf, the head of the EU San Francisco office and senior envoy of the EU to the United States for Digital, on the other hand, detailed how the European Union had begun to instate one such system, showing it was possible both technically and politically. Artists can check if they’re part of a dataset and then ask to be removed if they don’t want their works used for AI training. The thrust of his testimony was backed up by University of Chicago professor Ben Zhao, whose team built the Nightshade and Glaze tools that ‘poison’ AI datasets, and who demonstrated how a relatively simple fingerprinting system could be set up to register and check for copyrighted works. Luke Arrigoni and Juliun Brabon, founders of two smaller AI companies, seemed to concur. I was glad to see this, as I get very frustrated whenever I hear companies and tech advocates who love to celebrate innovation when it promises profits label an undertaking too complex or onerous the minute a technology threatens to be put in service of working class interests.

It is, in other words, perfectly feasible for AI companies to document copyrighted works and to ask them to rightfully credit their creators—and, if the courts rule that training on such material is *not* fair use, to compensate them. There are concerns that a database could be weaponized by copyright trolls, that it would likely be a technical headache at first, and, sure, an unpleasant added cost for the few companies creating their own models that are not OpenAI or Google-sized, but it’s easy enough to imagine companies (Arrigoni’s and Brabon’s perhaps) arising to administer such a service. And the more transparency in AI, the better, period. AB 412 is, as its proponents like to say, a step in the right direction. But I do wonder, as the year draws to a close, what we’re stepping towards.

We are three years into a project in which a handful of tech companies have attempted to feed every data point, every song, every sentence, every cartoon, every short story, every shitpost, every marketing email, every work of fan fiction, every reddit thread, every sonnet and so on into systems they promise in turn will automate the future production of all of that material. The billions have not stopped pouring in to fund this project, as haphazard, expensive, and dubiously popular as it is, and working artists, writers, performers, and creators are up against something like the mass automation of the median of art.

Pass AB 412, demand transparency, build the database—but what next? It’s hard to see this as a sufficient bulwark against the engines of bottomless creative labor automation. For instance, I’m eligible to receive a $1,500 payment from Anthropic as part of a settlement because the startup used my book to train its AI model. the $1,500 is nice, but an occasional payment like that is not going to rebalance any scales. AB 412 may push AI companies to be more intentional about what they include in their datasets, force them to document the human creative labor they’re currently wantonly usurping en masse, and perhaps spur those companies to consider licensing deals rather than vacuuming everything up and shoving it under the carpet.

Many of the artists at the hearing, it should be noted, told the legislators they have nothing against AI as a technology; they simply want to see a world where it does not run on their exploited labor. Finding a calculus that balances both seems uniquely crucial to this moment; I think most people would agree that we want more human artists, not fewer. Right now, AI companies, media conglomerates, and financial interests have engineered an apparatus that’s pointed us in the opposite direction. But if AB 412 is a start, then where do we want this to end? Not in a perennial rearguard action, trying to claw back bits of value as cultural production is turned into a homogenous firehose, as ‘working artist’ becomes an anachronism and ‘AI content creator’ becomes normalized. Much more is possible. There has to be a way.

As I sat at my gate in the San Jose airport on Thursday, homeward bound three days after the hearing, a notification materialized on my phone announcing that Disney would be investing $1 billion in OpenAI. It would be entering into a partnership that would allow the AI company to use Disney’s hitherto fiercely protected intellectual property—for now the most valuable in the world—on its AI slop generator app Sora.

I just stared at the notification for a minute without opening it. Not in disbelief, because we expect nothing less from an executive class that exults AI even when doing so appears to be against its own direct material interests, or in anger, because there have been too many similarly patterned decisions made over the past three years to inspire any such emotions at this point. I stared because in that notification I saw Bob Iger’s dream, and Sam Altman’s, and it was the dream of fully automated content production.

NPR screenshot.

Bob Iger says he hopes to take user-created AI content featuring Mickey Mouse, Marvel and Star Wars characters, and feature it on the streaming platform Disney+. Sam Altman said parents could make digital content for their kids with Buzz Lightyear.

Years of Marvel movies and regurgitated franchise IP have undercut the notion that anything need be particularly good or even new anymore; the next frontier is prodding users to generate animated diversions with pre-established IP on one platform and feeding them other ones on the affiliated other, no novel ideas or paid creative labor necessary. Will anyone like it? That’s not really the pertinent question. Will they tolerate it? Will they accept it? If life amid the slop layer has taught us anything, it’s that we humans tend to bristle when we come too directly into contact with AI output, and we do often reject it. Perhaps we can be trained. Regardless, in this transaction we see the forces and motives animating the larger enterprise, and it has nothing to do with cultural meaning or even consumer satisfaction.

Probably at just the same time those artists and writers were packing a campus hall to fight for their working lives, Disney executives were in a boardroom, finalizing the deal to invest in the technology automating their work, directly with the company testifying against the artists and writers and lobbying to ensure they don’t receive any new legal protections. I’m not worried that “art” won’t survive the AI onslaught, I’m worried it will impede who gets a chance to make it. As the animator Danny Lin noted, conditions for working artists have been eroding since before AI; Netflix and the streamers ‘giggified’ the industry, rent prices are still spiking, and healthcare is as ever its own unique American nightmare. AI is a corrosive agent, breaking down what’s left, taking over entry level and freelance art and writing work, drying up needed opportunities and income.

There’s yet another layer here. The same day that the Disney-OpenAI deal was announced, President Trump finally signed his executive order aimed at deterring states from passing laws regulating AI—like the AI copyright transparency law—altogether. Trump promises to enlist the Department of Justice to sue states that try to pass laws governing AI, and threatens to withhold federal funding if they do. The tech industry, and its man in Washington, AI czar and venture capitalist David Sacks, lobbied hard for this preemption, and while it’s both legally dubious and unpopular on both sides of the aisle, for now, it’s the state of play.

All of these trendlines are intertwined, of course: The authoritarian state’s embrace of AI, the surge of corporate consolidation and dealmaking, the skyrocketing inequality, the automation of labor and the efforts to strip worker laws and protections. AI has become central to the American oligarchic project, as the elites’ shared vision of the labor-excised future. It’s the ultimate top-down technology; it barely matters that AI systems still routinely pump out erroneous output, don’t generating the promised productivity gains, and are most commonly used as a more addictive and sycophantic user upgrade to social media. Because to them, AI is not just a technology or a product. It’s an ideology; a quasi-religion featuring artificial general intelligence sold as productivity software. A-God-being-born-as-a-service. It’s a logic used to justify job cuts at DOGE and Amazon and new modalities of corporate and bureaucratic expansion. It’s the accelerant, the justifier, the palm greaser among the oligarchs in a year that saw the 10 richest men in the US—nearly all tech billionaires—grow their wealth by $698 billion. Meanwhile, “over 40% of the U.S. population,” per a new Oxfam report, “including 48.9% of children—is considered poor or low income.” Nearly half the country may not be able to afford higher education, or adequate healthcare, and companies may be withholding entry level jobs for hopes that LLMs can do them instead, but at least we can have access to an AI tutor, an AI confidant, an AI therapist. No guarantees it won’t encourage you to kill yourself, though.

The text of AB 412.

On that Monday afternoon at Stanford, the hearing concluded with a call for public comments, and the crowd became a line that snaked down the middle of the hall and out into the entryway. Due to the volume of commenters, each was given just 15 seconds at the mic. There were proud, practiced voices of professional orators, and quavering, nearly inaudible voices of artists who spend most of their days indoors. There was a lot of righteous indignation and a lot of palpable fear.

“Everyone who works in Hollywood is at risk due to generative AI,” a performer said. “Our creativity, our innovation, our copyrighted works—those are the tech industry’s ‘trade secrets’,” an artist said. “Job loss is not theoretical, it’s tangible—14% of our industry has lost work in the last year,” a voice actor said. To us, “AI training on copyrighted material without consent is theft, not fair use,” a writer said.

Despite being held in that heart of Silicon Valley, the artists clearly won the day. I counted only two comments against the bill, among an otherwise uninterrupted stream of arguments in favor. The headlines the next day were largerly sympathetic; they focused not on the native innovators, but on the impacted workers packing the place, calling for change. And it’s little surprise; Silicon Valley used to be famous for its cutting edge innovations and consumer electronics, its iPhones and search engines. Now it’s increasingly felt as widely as a facilitator of automation, labor degradation, casino-ification; the purveyor of AI, gig apps, crypto.

It was hard not to be moved by the scene, the creative workers taking some satisfaction, however fleeting, in speaking truth to power in Palo Alto. The hearing and comments that followed showed that technology need not be abandoned to accommodate the working class and the humane; there were options, configurations, solutions on the table. A worthy reminder as we head into a new year that there are other futures available, whether the one blueprinted here or not, should we pause to consider motives other than dominance, scale, sheer profit.

The artists lining up to give comment inside Stanford’s Brest Hall, at the end of the day. Photo: Me.

That despite the numbers that tick by on the headlines announcing new absurd heights in AI company valuations and tech giant capital expenditures, and the draconian anti-democratic measures handed down to curtail AI lawmaking, there is a vulnerability. The industry’s relentless, thoughtless expansion strains to conceal a lack of imagination, a confidence of vision; in fact, the desperation suggests a brittleness, a weakness. And what might fill the void should the AI bubble burst?

The gig workers are organizing. People on the left and right alike are protesting data centers, and sometimes stopping them. Class action lawsuits are breaking the artists’ way, and then not. Technical systems and infrastructures are hungry for democratic input and organic engagement. The Luddite renaissance, skepticism towards big tech, and anti-AI resurgence rises.

At Stanford, among the sea of people, artist and games developer named Brendan Mauro stepped up and said, “I don’t understand why their right to not go bankrupt supersedes all [our] right to not go bankrupt.”

There has to be a way.

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Bauer-Kahan was notably behind LEAD, the law banning the sale of harmful chatbots to children that passed both chambers, but that Gavin Newsom vetoed.

Netflix can’t be allowed to buy Warner Discovery - Disconnect

2025-12-16T20:42:52.000Z

I can hardly describe the dread that swept over me when I read the news that Netflix might end up buying Warner Bros. Discovery, and particularly the storied film studio at its core. The barbarians were not just at the gates, but had fully broken through the walls, reached the keep, and were nearly through the door to cast aside the king and seize his lands as their own. It didn’t seem as though an ally would arrive at the last moment to turn the tide of the battle, and the barbarians’ rule would be anything but a friendly one.

To some that might sound hyperbolic. I don’t think it is.

The prospect of Netflix acquiring one of the most recognizable US film studios feels not just like the culmination of the past nearly twenty years of Silicon Valley’s entry into and disruption of the film industry, but also a much longer process of the attempt to capture and commercialize culture — transforming it in the process to serve the ends of corporate tyrants rather than its essential function as a means of social enrichment. In that sense, Netflix is a problem because it’s both the product of a deeper rot in society and culture, while helping to extend its effects even further.

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The false promise of streaming

For the past fifteen years, we’ve watched as the supposed “streaming wars” played out in front of our eyes. Tech companies moved into film and television, promising they could do it better than the old guard entertainment companies. Free to spend like drunken sailors, because investors valued them well above traditional companies and gave them free reign to lose money as they saw fit, they splashed out on prestige television and expensive auteur films to prove their bona fides, win some degree of industry support and acclaim, and get viewers on board with quality content and low prices — promising they would last forever.

But that was not to be the case. The streaming model upended the economics of film and television, drying up once-lucrative licensing revenue streams while further imperiling the collective theatrical experience in favor of the even further individualized viewing at home, which even shifted from the television to a laptop or phone screen. I’m guilty of watching in those ways too — well, not on a phone screen; I’ve never done that — but that doesn’t mean I think they’re the best ways of experiencing visual culture.

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When I’m watching at home, I struggle to stay focused or to avoid my phone. But when I’m in a cinema, that completely changes. I’m there for the movie, my phone stays in my pocket once it starts, and I relish having that experience with a bunch of other people — even when it means I’m in tears multiple times, as was recently the case with Rental Family and Hamnet. Quite honestly, I dread missing a film like that in cinemas because I know the at-home experience just will not be the same. I enjoyed Guillermo del Toro’s Frankenstein immensely, but I was sad the theatrical run was so short and I missed the opportunity to see it on the big screen because I was traveling and busy with work.

On top of all that, we’re now treated to a steady cadence of price hikes, not to mention crackdowns on once-popular password sharing, all while libraries get trimmed and the quality of the majority of content, especially on a platform like Netflix, is continually degraded to act as bottom-of-the-barrel background viewing with the expectation people are doomscrolling on another screen. It’s even leading the charge for Hollywood’s open embrace of generative AI, claiming it’s “all in” on using AI to cut production costs after deploying it for effects on a film for the first time earlier this year.

The false promises of the streaming revolution were entirely predictable to anyone paying attention to the business models of the companies behind it and the history of how these technological transformations tend to play out. In 1997, communications professor Thomas Streeter explained something very similar in the case of cable television. “The cable fable is a story of repeated utopian high hopes followed by repeated disappointments,” he wrote. “Cable was to end television oligopoly; instead it has merely provided an arena for the formation of a new oligopoly.”

Cable was supposed to bring about a more open and equitable media system, but ended up reinforcing corporate power in the sector. Streaming may have brought in some new players, but it ended up doing much the same — while creating the pressure for even further consolidation as massive, well-financed tech firms moved in as competitors.

Disney gobbled up most of 21st Century Fox in its effort to scale up, AT&T (including WarnerMedia) merged with Discovery, Amazon absorbed MGM Studios, the Ellisons grabbed Paramount, a bunch of smaller companies have been scooped up too, and now the vultures are circling around the combined WBD for another scale up. None of this enriches the culture; but investors do hope it will allow them to extract some gains after further cost-cutting measures.

Streaming has eroded the business model that funded culture for decades, leaving companies scrambling to find out how to make the numbers work in this new era. There seems to only be room for a few massive platforms and maybe a few niches ones besides them, but the notion that the model would foment better culture, more opportunity, and increased competition has long ago been disproven. Even before the pandemic, creators were already calling out opaque decision-making at Netflix and how it was disproportionately cancelling series made by women.

It didn’t start with Netflix

While it’s easy to put all the blame on Netflix, and it certainly doesn’t deserve to be let off the hook, the corporate effort to commercialize (and in the process degrade) culture did not start with streaming. As Streeter’s decades-old observation suggests, this has been going on for a long time — and new technology has been a key part of the game. It’s played out in many different ways.

In the 1970s, the blockbuster movie changed the nature of going to the movies and used spectacle to encourage consolidation of independent cinemas into multiplexes, giving owners leverage over unionized projectionists in the process. But as Will Tavlin explained in a fantastic piece in n+1, the distributors came for those cinema owners a few decades later. When movie projection shifted from film to digital cameras in the early 2000s, the companies set a new standard that “made sure that as distributors they would maintain their leverage over exhibitors” — even as the cost and difficulty of servicing the new projectors led to a decrease in the quality of the moviegoing experience. As the studios gained more power, they also started pushing more onerous terms on cinemas too and restricted access to catalogs of older films.

Today, the roles have shifted. Studios have not been defanged — a company like Disney can still have a lot of leverage — but ownership of a major streaming platform comes with a lot of leverage. Netflix has basically snubbed cinemas that don’t want to give into its demands of incredibly short theatrical windows and doesn’t license out its originals. It wants to extend its control as far as possible and has effectively used technology (and deep pockets) to do just that. In a sense, the effort to shoehorn generative AI into development isn’t just a cost-cutting measure; it’s also an attempt to seize more power over the production process. If you can easily generate a new scene or alterations to an existing one, that takes power away from writers, actors, and even directors.

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There is precedent for this. When computer-generated effects were maturing and being popularized in the 1980s, there were promises about the new filmmaking techniques it would enable but also concerns about the power that was being shifted to directors in the process. In her book The Empire of Effects, Julie Turnock explains that the role of George Lucas and Industrial Light & Magic in advancing visual effects is often overstated. Lucas was “willing to invest significant funds to develop technology to make editing, sound, and special effects easier and less expensive,” but he “squandered nearly every opportunity” with the dream team he’d assembled because he was more focused on transforming the way films were made to give himself more power over the final product.

When it was time for Lucas to shoot the Star Wars prequel trilogy, the technology had advanced far enough to give him an unprecedented degree of control over the look of the films — regardless of whether he’d been able to capture what he wanted in camera. “In postproduction for The Phantom Menace, performers were copied from some shots and pasted into others; actors who blinked on a cut were made to keep their eyes open; cast members who turned their head to Lucas’s disliking were turned the other way,” explained Tavlin. Lucas’ editor said essentially that. “We could totally redirect the picture in the cutting room.”

Despite all the claims of technological efficiency, budgets have not shrunk — in fact, they’ve only gotten larger. The claims of cost savings did not materialize, but the unacknowledged seizure of control certainly did. That’s something to keep in mind as similar arguments are made about generative AI. Actors and writers have already shown concern about how new technology has eroded their leverage in film production. “After their work is done, those offshored VFX companies do a lot of the rest of the ‘writing’, just as they now do a lot of the rest of the ‘acting’ once the stars have gone home,” wrote A.S. Hamrah of the way things have changed with visual effects and digital production. That’s only poised to get worse if companies get their way with image and video generators.

Where we go next

The prospect of further consolidation, especially an acquisition by a company like Netflix, should be cause for alarm well beyond the communities of those who actually make film and television. We’ve already seen a form of content slop emerge from the streaming era, as the focus has become on churning out enough programming to keep people engaged — quality be damned, because the viewers are assumed to be on their phones most of the time anyway. Going further down that path, with the addition of generative AI as another tool to wield against creators to further remake art to serve commercial ends is the wrong path.

That’s not to let Paramount and the Ellisons off the hook. While Paramount itself may at least have industry pedigree, the project David Ellison is trying to manifest with the backing of his father, who just happens to be the richest man in the world every now and then, is to remake one of the old guard film companies — or a few, if WBD can be rolled into the project — into the mold of a modern tech company to take on the tech interlopers like Netflix. We also shouldn’t ignore the power that would come with such an empire, spanning film, television, video games, and potentially even social media if the deal for the US arm of TikTok ever comes to pass, nor the mass layoffs and consequences for film and television production that would follow from the merger of two major studios.

We’ve even seen the consequences of this through existing mergers: there’s been far less out of Fox after it was taken over by Disney, which itself just got into bed with OpenAI in a short-term bid to cash in on the generative AI boom regardless of the wider consequences. In a sense, Silicon Valley isn’t even the cause of these problems. At its core, this is a capitalist problem as the system needs to absorb and remake every facet of society in an attempt to extract profits at all costs. The tech industry is simply the driving vehicle of that process in the current moment, which is why it deserves so much attention — and opposition.

At the end of the day, WBD should not merge or be acquired by any company. Regulators should stop any such effort at further consolidation in its tracks and make it clear this has to stop. But it should also go back to the earlier days when more strictly regulating these companies to limit their size and their power was much more in vogue — and expand that to the tech companies and their streaming revolution. Technology itself isn’t even the problem — it’s the pressures of the economic system we live in to create technology whose goal is exploitation and commercialization, not cultural enrichment and human flourishing.

More than anything, culture needs to be seen as the public good that it is — and proper funding given over to ensure it can flourish and enrich our lives, even when it doesn’t present the prospect of corporate profits. That’s not a project Netflix — or any of these corporate behemoths — will be an ally to achieve.

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Manufactured Inevitability and the Need for Courage - The Convivial Society

2025-12-15T03:51:36.000Z

Welcome to the Convivial Society, a newsletter exploring the intersection of technology, culture, and the moral life. In this installment I return to one of the earliest themes of my writing about technology: the myth of technological inevitability. When I’ve had occasion over the past several months to address the question of AI, the one point that I’ve felt compelled to make again and again, is that there is no inevitability. There are choices to be made, but it can be convenient to imagine otherwise. But, as Joseph Weizenbaum knew well, it takes courage to make them.

I began writing about technology and culture around 2010. It didn’t take long for me to recognize one of the most common tropes deployed by those whose business it was to promote new technologies. It was the trope of technological inevitability. By 2012, I wrote about how those who deployed this trope suffered from a Borg Complex. Alluding to the cybernetic alien race in the Star Trek universe, I defined a Borg Complex as a malady that afflicts “technologists, writers, and pundits who explicitly assert or implicitly assume that resistance to technology is futile.”

The first time I identified the tendency in this way, I argued that “the spirit of the Borg lives in writers and pundits who take it upon themselves to prod on all of those they deem to be deliberately slow on the technological uptake. These self-appointed evangelists of technological assimilation would have us all abandon any critique of technology and simply adapt to the demands of technological society.”

I then proceeded to outline a series of symptoms by which we might diagnose someone with a Borg complex:

Makes grandiose, but unsupported claims for technology
Uses the term Luddite a-historically and as a casual slur
Pays lip service to, but ultimately dismisses genuine concerns
Equates resistance or caution to reactionary nostalgia
Starkly and matter-of-factly frames the case for assimilation
Announces the bleak future for those who refuse to assimilate
Expresses contemptuous disregard for past cultural achievements
Refers to historical antecedents solely to dismiss present concerns

Throughout the middle-period of my late blog, The Frailest Thing, I would periodically post to the Borg Complex files some then-recent example of the rhetoric of technological inevitability. Before most of you found your way to this newsletter, I revisited some of these themes in a post from 2021, adding some new voices to my argument, including the informed perspective of Thomas Misa, a historian of technology at the University of Minnesota:

“… [W]e lack a full picture of the technological alternatives that once existed as well as knowledge and understanding of the decision-making processes that winnowed them down. We see only the results and assume, understandably but in error, that there was no other path to the present. Yet it is a truism that the victors write the history, in technology as in war, and the technological ‘paths not taken’ are often suppressed or ignored.”

And then there was Margaret Heffernan’s superb reflections on the theme. The goal of those who deploy the rhetoric of technological inevitability, she rightly insists, “isn’t participation, but submission.” “Anyone claiming to know the future,” she adds, “is just trying to own it.”

I don’t need to tell you that the rhetoric of technological inevitability has dominated discussions (or, more likely, directives and pronouncements) regarding AI that you’ve encountered over the past two or three years. In particular, AI-talk has manifested the distinct quasi-religious variety of the Borg Complex, which can be particularly pernicious since it understands resistance to be not only mistaken, but heretical and immoral.

In fact, it sometimes seems to me as if the adoption of AI is driven chiefly by the rhetoric of inevitability exacerbated by the related logics of the prisoner’s dilemma and an arms race. Indeed, it is a curious fact that some of the very people who are ostensibly convinced of the inevitability of AI nonetheless lack the confidence you would think accompanied such conviction and instead seem bent on exerting their power and wealth to make certain that AI is imposed on society. I’m calling this tendency, with a nod to Herman and Chomsky, manufactured inevitability.

It was a phrase that first came to me back in June when I read about how Ohio State was mandating the use of AI as part of its AI Fluency initiative. And I was prompted to write this up by news that Purdue was making “AI competency” a graduation requirement. It is hardly surprising that institutions of higher education, which stand to receive substantial funding from tech companies like Open AI and Google, would find ways to mandate the use of AI under the guise of preparing students for the workforce of the future (which often turns out to be a fool’s errand). But there are, of course, countless banal instances of AI being surreptitiously woven into the fabric of ordinary experience, from search engine results to software updates that introduce AI functions nobody asked for. There is no better way to reinforce the myth of technological inevitability than to stage the ubiquity of AI in such a way that it renders the adoption of AI a fait accompli.

I’d be glad for you to share any other instances of manufactured inevitability that you’ve observed.

I should acknowledge that while there is no inevitability, agency and responsibility are unequally distributed. Thus, it is worth noting that the strategy of manufacturing inevitability has the effect of obfuscating responsibility, especially on the part of those who in fact have the greatest agency over the shape of the techno-economic structures that order contemporary society for the rest of us.

The pioneering computer scientist, Joseph Weizenbaum, told us as much nearly 50 years ago in Computer Power and Human Reason: “The myth of technological and political and social inevitability is a powerful tranquilizer of the conscience. Its service is to remove responsibility from the shoulders of everyone who truly believes in it. But in fact there are actors.”

The myth of technological inevitability is a powerful tranquilizer of the conscience. It bears repeating.

More from Weizenbaum, who writes with refreshing conviction:

“But just as I have no license to dictate the actions of others, neither do the constructors of the world in which I must live have a right to unconditionally impose their visions on me. Scientists and technologists have, because of their power, an especially heavy responsibility, one that is not to be sloughed off behind a facade of slogans such as that of technological inevitability.”

But Weizenbaum understood one more thing of consequence: the necessity of courage. Allow me to quote him at length:

I recently heard an officer of a great university publicly defend an important policy decision he had made, one that many of the university’s students and faculty opposed on moral grounds, with the words: ‘We could have taken a moral stand, but what good would that have done?’ But the good of a moral act inheres in the act itself. That is why an act can itself ennoble or corrupt the person who performs it. The victory of instrumental reason in our time has brought about the virtual disappearance of this insight and thus perforce the delegitimation of the very idea of nobility.
I am aware, of course, that hardly anyone who reads these lines will feel himself addressed by them—so deep has the conviction that we are all governed by anonymous forces beyond our control penetrated into the shared consciousness of our time. And accompanying this conviction is a debasement of the idea of civil courage.
It is a widely held but a grievously mistaken belief that civil courage finds exercise only in the context of world-shaking events. To the contrary, its most arduous exercise is often in those small contexts in which the challenge is to overcome the fears induced by petty concerns over career, over our relationships to those who appear to have power over us, over whatever may disturb the tranquility of our mundane existence.
If this book is to be seen as advocating anything, then let it be a call to this simple kind of courage. And, because this book is, after all, about computers, let that call be heard mainly by teachers of computer science.

I’m not a computer scientist, but I do, in fact, feel myself addressed by Weizenbaum’s words. While the degree of agency we share over the shape of our world varies greatly, I remain convinced that we all have choices to make. But these choices are not without consequences or costs. And each one of us will find, from time to time, the need for courage, and it strikes me that such courage, call it civil courage or courage in the ordinary, is the antidote to what Arendt famously diagnosed as the banality of evil.

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Some Things I Did in 2025 - Cybernetic Forests

2025-12-14T12:00:30.000Z

In this post I'm highlighting some of my writing, artworks and talks from 2025. If you've been following, I hope you find something worth revisiting. If not, I hope you find something worth checking out.

And if you find something of interest, please share it! One thing that's happened this year: after moving from Substack to my own host, new signups have come to a standstill. So if you want to let folks know to sign up, here's a big sign up button.

Tracking the AI Coup

In 2025 I started a Tech Policy Press fellowship, which gave me the time and resources to focus on the political and social ramifications of generative AI. The pieces that came out of that tracked a few threads, but none earned as much attention at my piece on the AI Coup.

I argued that the false promise of AI was being used as an excuse to justify the dismissal and automation of government workers, to be replaced by machines that could not do the work. The point, I proposed, was not that "doing the work" mattered at all, but that even the failure of AI systems would further embed the technical operators into governance, ie, replace the policy wonks with prompt engineers.

Along the way, the apparatus could be used to build a surveillance state, integrating government datasets into a single point of reference in order to generate "fishing expeditions" – with false positives being a feature, not a bug. False positives gave the government leverage: they could fix the problems if they got something out of it, or else allow the problems to fester: a weaponization of administrative error.

The coup was partly built by a $100 billion financial investment masquerading as a political victory for Trump, who was able to take credit as soon as he took office for a project that was already underway, and had no government support. What this infrastructural investment really created was a hype cycle, selling AI as a solution to all kinds of problems – initially as a means of growing investments, but eventually as a means of becoming so integrated into government and the economy that the AI industry could not be allowed to fail.

I was invited to address the topic at the Centre Pompidou in Paris this summer for an event called "Democracy and the AI Question," and I shared a draft of my prepared remarks.

I got to discuss all of this with Rebecca Williams, Emily Tavoulareas and Matthew Kirschenbaum in a podcast with Tech Policy Press.

AI Myths

At Tech Policy Press, I was also able to write more on the concept of AI myths, following up on a popular and still relevant piece I wrote in 2024, "Challenging the Myths of Generative AI." This year I unpacked at the myths of productivity and the Black Box myth.

I also spent a lot of time thinking about Artificial General Intelligence this year, thanks to my small contribution to a collective paper, "Stop Treating AGI as the North-Star Goal of AI Research," summarized for Tech Policy Press here (with a podcast, too, with myself, lead author Borhane Blili-Hamelin and co-author Margaret Mitchell discussing the paper with Justin Hendrix).

Just this week, I have a fresh piece of writing ("The Domesday Generation") on the political position AGI represents included in a new print volume, "Vectoral Agents: Power in the Age of Planetary Computation," out now from the Institute for Network Cultures out of Amsterdam. You can order it or read it as a pdf here.

Art & Other Works

Signal to Noise

On top of all this, I opened up an exhibition with Joel Stern and Emily Siddons at the National Communications Museum in Melbourne, which ran from April 12 to September 11. Here's a walk through and a conversation with the curators.

Human Movie

For the opening of "Signal to Noise" I created a 35-minute lecture-performance-film called Human Movie, which has gone on to win two awards and to be shown in a number of incredible places including the Jeu de Paume in Paris as part of the "World Through AI" exhibition. There's an excellent review in Found Footage Magazine by Michael Betancourt:

Noise is the central image of Eryk Salvaggio’s Human Movie: Six Meditations on a Compression Algorithm. Its sources are varied but familiar: instructional films, found footage from commercials, the detritus and AI-generated slop forced into a dialogue with the noise that infuses every shot. Brief moments of sharp clarity only make noise more apparent as the force lurking just under a veneer of recognition and familiarity, with the video clearly broken by intertitles into six sections which structure the noise that never diminishes. In Human Movie, this noise is the emblem of independence, the freedom that the video suggests is essentially human and which all these AI processes seek to contain and manage by claiming the digital machine is a mirror of the human mind.

You can still arrange for a screening or performance of the film, by the way. (It's currently not online, likely will be in 2026).

Noisy Joints

Noisy Joints is a lovely mess of a research week compiled into a zine, called Noisy Joints. The five-day experimental workshop was hosted by the Mercury Store in Brooklyn, NY and designed by collaborators Camila Galaz, Isi Litke, with lead artists Emma Wiseman and Eryk Salvaggio. The “Critical AI Puppet Workshop” focused on interrogating AI critically through the lens of puppetry, and recognizing the utility of both the metaphors and embodied experiences that emerge from puppetry and puppeteering in a larger conversation about AI, physicality, and the human imagination.

Isi Litke's ongoing puppetry and automation class at the Brooklyn Institute for Social Research is up if you are looking to take the class in-person or online though it seems to sell out fast.

One of the outcomes of this workshop was also a collection of short videos of hands, which were recorded and then used to spawn AI-generated replicas of themselves. The two hands are superimposed upon each other as they mediate a middle layer of digital noise, a replication of the human body touching its uncanny twin through the mediating layer of noising/denoising inherent to the training process of diffusion models. I'm hoping to do something more with this soon.

Camila Galaz was also able to host a second workshop in Melbourne – which I had to miss due to a family crisis – which we discussed with Emma Wiseman in a blog post.

Noisy Joints is something I'd love to work on somehow, and maybe there'll be more of this in 2026 as well.

Sound

I ended my five-years-long critical-AI psychedelic-noise-pop project, The Organizing Committee, with a final release called "Keeping Secrets from the Numbers." You can find it on Bandcamp (and most streaming services that aren't Spotify) or read more about the project below.

Keeping Secrets From The Numbers

Presenting my latest and final album as The Organizing Committee. The new record, “Keeping Secrets From the Numbers,” is available today on Bandcamp, and will be streaming on most platforms (aside from Spotify) in the coming weeks. It will be the last record as The Organizing Committee. When I started

Cybernetic ForestsEryk Salvaggio

You can of course just look at the archive page if you want to see what else I've written this year, but I wanted to bring some writing forward.

On Large Language Models: I spent a good amount of time thinking through Large Language Models and Meaning this year, starting with re-reading Roland Barthes on "The Death of the Author" and noting that the LLM inherits the myth of an author while depending on the idea that the author is dead, an inherent contradiction. I started a PhD this year, which I took as an invitation to reconnect to some of the technical underpinnings of LLMs and this phrase which I think holds true, that "a dog can 'go to church' but a dog cannot be Catholic. An LLM can have a conversation but cannot participate in the conversation." There was more on epistemic boundary-setting and a critique of my own assumptions about normativity about language-as-thought as someone who cannot do math and sees music as color. There's more to say, but I am writing it up for a paper.

On Being Human: After the death of David Lynch, I looked at what creativity is for some artists rather than what creativity is as defined by art-making AI systems. After my father died suddenly in June, I wrote a short series, which is ongoing, of "Human ______" posts which expands on the ideas of Human Movie but as short texts. Human Literacy was one of my most-read pieces this year, a short text to students on how to make sense of the world with and without AI.

Human Literacy

Something I Can Tell Students Now That I Am Not Teaching You and I probably both keep hearing that students should be working toward AI literacy. That you should know what to type into prompt windows, because it will save you time. That will get you jobs in the economy

Cybernetic ForestsEryk Salvaggio

This was followed up by Human Conversation, which tried to distinguish the nature and pleasures of conversation with people from the highly efficient and productivized vision of what we do with chatbots.

Social-Cultural Impacts of AI: Finally, two very recent pieces, the first on ChatGPT as a pandemic technology that keeps writing social isolation into its operations. The second on the subject of interpassivity at the heart of popular forms of making AI art, music, and writing.

Thanks for reading! If any of this resonates, please share this post and encourage folks to sign up. Link is here again.

"I was forced to use AI until the day I was laid off." Copywriters reveal how AI has decimated their industry - Blood in the Machine

2025-12-12T00:50:13.000Z

Back in May 2025, not long after I put out the first call for AI Killed My Job stories, I received a thoughtful submission from Jacques Reulet II. Jacques shared a story about his job as the head of support operations for a software firm, where, among other things, he wrote copy documenting how to use the company’s product.

“AI didn’t quite kill my current job, but it does mean that most of my job is now training AI to do a job I would have previously trained humans to do,” he wrote. “It certainly killed the job I used to have, which I used to climb into my current role.” He was concerned, for himself, as well as for his more junior peers. As he told me, “I have no idea how entry-level developers, support agents, or copywriters are supposed to become senior devs, support managers, or marketers when the experience required to ascend is no longer available.”

When we checked back in with Jacques six months later, his company had laid him off. “I was actually let go the week before Thanksgiving now that the AI was good enough,” he wrote.

He elaborated:

Chatbots came in and made it so my job was managing the bots instead of a team of reps. Once the bots were sufficiently trained up to offer “good enough” support, then I was out. I prided myself on being the best. The company was actually awarded a “Best Support” award by G2 (a software review site). We had a reputation for excellence that I’m sure will now blend in with the rest of the pack of chatbots that may or may not have a human reviewing them and making tweaks.

It’s been a similarly rough year for so many other workers, as chronicled by this project and elsewhere—from artists and illustrators seeing client work plummet, to translators losing jobs en masse, to tech workers seeing their roles upended by managers eager to inject AI into every possible process.

And so we end 2025 in AI Killed My Jobs with a look at copywriting, which was among the first jobs singled out by tech firms, the media, and copywriters themselves as particularly vulnerable to job replacement. One of the early replaced-by-AI reports was the sadly memorable story of the copywriter whose senior coworkers started referring to her as “ChatGPT” in work chats before she was laid off without explanation. And YouTube was soon overflowing with influencers and grifters promising viewers thousands of dollars a month with AI copywriting tools.

But there haven’t been many investigations into how all that’s borne out since. How have the copywriters been faring, in a world awash in cheap AI text generators and AI adoption mania? As always, we turn to the workers themselves. And once again, the stories they have to tell are unhappy ones. These are accounts of gutted departments, dried up work, lost jobs, and closed businesses. I’ve heard from copywriters who now fear losing their apartments, one who turned to sex work, and others, to their chagrin who have been forced to use AI.

Readers of this series will recognize some recurring themes: The work that client firms are settling for is not better when it’s produced by AI, but it’s cheaper, and deemed “good enough.” Copywriting work has not vanished completely, but has often been degraded to gigs editing client-generated AI output. Wages and rates are in free fall, though some hold out hope that business will realize that a human touch will help them stand out from the avalanche of AI homogeneity.

As for Jacques, he’s relocated to Mexico, where the cost of living is cheaper, while he looks for new work. He’s not optimistic. As he put it, “It’s getting dark out there, man.”

Art by Koren Shadmi.

Before we press on, a quick word: Many thanks for reading Blood in the Machine and AI Killed My Job. This work is made possible by readers who pitch in a small sum each month to support it. And, for the cost of $6, a decent coffee a month, or $60 a year, you can help ensure it continues, and even, hopefully, expands. Thanks again, and onwards.

Subscribe now

The next installments will focus on education, healthcare, and journalism. If you’re a teacher, professor, administrative assistant, TA, librarian, or otherwise work in education, or a doctor, nurse, therapist, pharmacist, or otherwise work in healthcare, please get in touch at AIKilledMyJob@pm.me. Same if you’re a reporter, journalist, editor, or a creative writer. You can read more about the project in the intro post, or the installments published so far.

This story was edited by Joanne McNeil.

They let go of the all the freelancers and used AI to replace us

Social media copywriter

I believe I was among the first to have their career decimated by AI. A privilege I never asked for. I spent nearly 6 years as a freelance social media copywriter, contracting through a popular company that worked with clients—mostly small businesses—across every industry you can imagine. I wrote posts and researched topics for everything from beauty to HVAC, dentistry, and even funeral homes. I had to develop the right voice for every client and transition seamlessly between them on any given day. I was frequently called out and praised, something that wasn’t the norm, and clients loved me. I was excellent at my job, and adapting to the constantly changing social media landscape and figuring out how to best the algorithms.

In early 2022, the company I contracted to was sold, which is never a sign of something good to come. Immediately, I expressed my concerns but was told everything would continue as it was and the new owners had no intention of getting rid of freelancers or changing how things were done. As the months went by, I noticed I was getting less and less work. Clients I’d worked with monthly for years were no longer showing up in my queue. I’d ask what was happening and get shrugged off, even as my work was cut in half month after month. At the start of the summer, suddenly I had no work. Not a single client. Maybe it was a slow week? Next week will be better. Until next week I yet again had an empty queue. And the week after. Panicking, I contacted my “boss”, who hadn’t been told anything. She asked someone higher up and it wasn’t until a week later she was told the freelancers had all been let go (without being notified), and they were going to hand the work off to a few in-house employees who would be using AI to replace the rest of us.

The company transitioned to a model where clients could basically “write” the content themselves, using Mad Libs-style templates that would use AI to generate the copy they needed, with the few in-house employees helping things along with some boilerplate stuff to kick things off.

They didn’t care that the quality of the posts would go down. They didn’t care that AI can’t actually get to know the client or their needs or what works with their customers. And the clients didn’t seem to care at first either, since they were assured it would be much cheaper than having humans do the work for them.

Since then, I’ve failed to get another job in social media copywriting. The industry has been crushed by things like Copy.AI. Small clients keep being convinced that there’s no need to invest in someone who’s an expert at what they do, instead opting for the cheap and easy solution and wondering why they’re not seeing their sales or engagement increasing.

For the moment, honestly I’ve been forced to get into online sex work, which I’ve never said “out loud” to anyone. There’s no shame in doing it, because many people genuinely enjoy doing it and are empowered by it, but for me it’s not the case. It’s just the only thing I’ve been able to get that pays the bills. I’m disabled and need a lot of flexibility in the hours I work any given day, and my old work gave me that flexibility as long as I met my deadlines - which I always did.

I think that’s another aspect to the AI job killing a lot of people overlook; what kind of jobs will be left? What kind of rights and benefits will we have to give up just because we’re meant to feel grateful to have any sort of job at all when there are thousands competing for every opening?

–Anonymous

I was forced to use AI until the day I was laid off

Corporate content copywriter

I’m a writer. I’ll always be a writer when it comes to my off-hours creative pursuits, and I hope to eventually write what I’d like to write full-time. But I had been writing and editing corporate content for various companies for about a decade until spring 2023, when I was laid off from the small marketing startup I had been working at for about six months, along with most of my coworkers.

The job mostly involved writing press releases, and for the first few months I wrote them without AI. Then my bosses decided to pivot their entire operational structure to revolve around AI, and despite voicing my concerns, I was essentially forced to use AI until the day I was laid off.

Copywriting/editing and corporate content writing had unfortunately been a feast-and-famine cycle for several years before that, but after this lay-off, there were far fewer jobs available in my field, and far more competition for these few jobs. The opportunities had dried up as more and more companies were relying on AI to produce content rather than human creatives. I couldn’t compete with copywriters who had far more experience than me, so eventually, I had to switch careers. I am currently in graduate school in pursuit of my new career, and while I believe this new phase of my life was the right move, I resent the fact that I had to change careers in the first place.

—Anonymous

I had to close my business after my client started using AI

Freelance copywriter

I worked as a freelance writer for 15 years. The last five, I was working with a single client - a large online luxury fashion seller based in Dubai. My role was writing product copy, and I worked my ass off. It took up all my time, so I couldn’t handle other clients. For the majority of the time they were sending work 5 days a week, occasionally weekends too and I was handling over 1000 descriptions a month. Sometimes there would be quiet spells for a week or two, so when they stopped contacting me...I first thought it was just a normal “dip”. Then a month passed. Then two. At that point, I contacted them to ask what was happening and they gave me a vague “We have been handling more of the copy in-house”. And that was that - I have never heard from them again, they didn’t even bother to tell me that they didn’t need my services any more. I’ve seen the descriptions they use now and they are 100% AI generated. I ended up closing my business because I couldn’t afford to keep paying my country’s self employment fees while trying to find new clients who would pay enough to make it worth continuing.

-Becky

We had a staff of 8 people and made about $600,000. This year we made less than $10k

Business copywriter

I was a business copywriter for eCommerce brands and did B2B sales copywriting before 2022.

In fact, my agency employed 8 people total at our peak. But then 2022 came around and clients lost total faith in human writing. At first we were hopeful, but over time we lost everything. I had to let go of everyone, including my little sister, when we finally ran out of money.

I was lucky, I have some friends in business who bought a resort and who still value my marketing expertise - so they brought me on board in the last few months, but 2025 was shaping up to be the worst year ever as a freelancer. I was looking for other jobs when my buddies called me.

At our peak, we went from making something like $600,000 a year and employing 8 people... To making less than $10K in 2025 before I miraculously got my new job.

Being repeatedly told subconsciously if not directly that your expertise is not valued or needed anymore - that really dehumanizes you as a person. And I’m still working through the pain of the two-year-long process that demolished my future in that profession.

It’s one of those rare times in life when a man cries because he is just feeling so dehumanized and unappreciated despite pouring his life, heart and soul into something.

I’ve landed on my feet for now with people who value me as more than a words-dispensing machine, and for that I’m grateful. But AI is coming for everyone in the marketing space.

Designers are hardly talked about any more. My leadership is looking forward to the day when they can generate AI videos for promotional materials instead of paying a studio $8K or more to film and produce marketing videos. And Meta is rolling out AI media buying that will replace paid ads agencies.

What jobs will this create? I can see very little. I currently don’t have any faith that this will get better at any point in the future.

I think the reason why is that I was positioned towards the “bottom” of the market, in the sense that my customers were nearly all startups and new businesses that people were starting in their spare time.

I had a partner Jake and together we basically got most of our clients through Fiverr. Fiverr customers are generally not big institutions or multi-nationals, although you do get some of that on Fiverr... It’s mostly people trying to start small businesses from the ground up.

I remember actually, when I was first starting out in writing, thinking “I can’t believe this is a job!” because writing has always come naturally to me. But the truth is, a lot of people out there go to start a business and what’s the first thing you do? You get a website, you find a template, and then you’re staring at a blank page thinking “what should I write about it?” And for them, that’s not an easy question to answer.

So that’s essentially where we fit in - and there’s more to it, as well, such as Conversion Rate Optimization on landing pages and so forth. When you boil it all down, we were helping small businesses find their message, find their market, and find their media - the way they were going to communicate with their market. And we had some great successes!

But nothing affected my business like ChatGPT did. All through Covid we were doing great, maybe even better because there were a lot of people staying home trying to start a new business - so we’d be helping people write the copy for their websites and so forth.

AI is really dehumanizing, and I am still working through issues of self-worth as a result of this experience. When you go from knowing you are valuable and valued, with all the hope in the world of a full career and the ability to provide other people with jobs... To being relegated to someone who edits AI drafts of copy at a steep discount because “most of the work is already done” ...

2022-2023 was a weird time, for two reasons.

First, because I’m a very aware person - I remember that AI was creeping up on our industry before ChatGPT, with Jasper and other tools. I was actually playing with the idea of creating my own AI copywriting tool at the time.

When ChatGPT came out, we were all like “OK, this is a wake up call. We need to evolve...” Every person I knew in my industry was shaken.

Second, because the economy wasn’t that great. It had already started to downturn in 2022, and I had already had to let a few people go at that point, I can’t remember exactly when.

The first part of the year is always the slowest. So January through March, you never know if that’s an indication of how bad the rest of the year is going to be.

In our case, it was. But I remember thinking “OK, the stimulus money has dried up. The economy is not great.” So I wasn’t sure if it was just broad market conditions or ChatGPT specifically.

But even the work we were doing was changing rapidly. We’d have people come to us like “hey, this was written by ChatGPT, can you clean it up?”

And we’d charge less because it was just an editing job and not fully writing from scratch.

The drop off from 2022 to 2023 was BAD. The drop off from 2023 to 2024 was CATASTROPHIC.

By the end of that year, the company had lost the remaining staff. I had one last push before November 2023 (the end of the year has historically been the best time for our business, with Black Friday and Christmas) but I only succeeded in draining my bank account, and I was forced to let go of our last real employee, my sister, in early 2024. My brother and his wife were also doing some contract work for me at the time, and I had to end that pretty abruptly after our big push failed.

I remember, I believed that things were going to turn around again once people realized that even having a writing machine was not enough to create success like a real copywriter can. After all, the message is only one part of it - and divorced from the overall strategy of market and media, it’s never as effective as it can be.

In other words, there’s a context in which all marketing messages are seen, and it takes a human to understand what will work in that context.

But instead, what happened is that the pace of adoption was speeding up and all of those small entrepreneurs who used to rely on us, now used AI to do the work.

The technological advancements of GPT-4, and everyone trying to build their own AI, dominated the airwaves throughout 2023 and 2024. And technology adoption skyrocketed.

The thing is, I can’t even blame people. To be honest, when I’m writing marketing copy I use AI to speed up the process.

I still believe you need intelligence and strategy behind your ideas, or they will simply be meaningless words on a screen - but I can’t blame people for using these very cheap tools instead of paying an expert hundreds of dollars to get their website written.

Especially in my end of the market, where we were working with startup entrepreneurs who are bootstrapping their way to success.

When I officially left the business a few months ago, that left just my partner manning the Fiverr account we started with over 8 years ago.

I think the account is active enough to support a single person now, but I wouldn’t be so sure about next year. The drop off from 2022 to 2023 was BAD. The drop off from 2023 to 2024 was CATASTROPHIC.

Normally there are signs of life around April - in 2025, May had come and there was hardly a pulse in the business.

I still believe there may be a space for copywriters in the future, but much like tailors and seamstresses, it will be a very, very niche market for only the highest-end clients.

—Marcus Wiesner

My hours have been cut from nearly full time to 4-5 a month

Medical writer

I’m a medical writer; I work as a contract writer for a large digital marketing platform, adapting content from pharma companies to fit our platform. Medical writers work in regulatory, clinical, and marketing fields and I’m in marketing. I got my current contract job just 2 years ago, back when you could get this job with just a BA/BS.

In the last 2 years the market has changed drastically. My hours have been cut from nearly full time up to March ‘24 to 4-5 a month now if I’m lucky. I’ve been applying for new jobs for over a year and have had barely a nibble.

The trend now seems to be to have AI produce content, and then hire professionals with advanced degrees to check it over. And paying them less per hour than I make now when I actually work.

I am no longer qualified to do the job I’ve been doing, which is really frustrating. I’m trying to find a new career, trying to start over at age 50.

—Anonymous

We learned our work had been used to train LLMs and our jobs were outsourced to India

Editor for Gracenotes

So I lost my previous job to AI, and a lot of other things. I always joke that the number of historical trends that led to me losing it is basically a summary of the recent history of Western Civilization.

I used to be a schedule editor for Gracenote (the company that used to find metadata for CDs that you ripped into iTunes). They got bought by Nielsen, the TV ratings company, and then tasked with essentially adding metadata to TV guide listings. When you hit the info button on your remote, or when you Google a movie and get the card, a lot of that is Gracenote. The idea was that we could provide accurate, consistent, high-quality text metadata that companies could buy to add to their own listings. There’s a specific style of Gracenote Description Writing that still sticks out to me every time I see it.

So, basically from when I joined the company in late 2021 things were going sideways. I’m based in the Netherlands and worker protections are good, but we got horror stories of whole departments in the US showing up, being called into a “town hall” and laid off en-masse, so the writing was on the wall. We unionised, but they seemed to be dragging their feet on getting us a CAO (Collective Labour Agreement) that would codify a lot of our benefits.

The way the job worked was each editor would have a group of TV channels they would edit the metadata for. My team worked on the UK market, and a lot of us were UK transplants living in the NL. During my time there I did a few groups but, being Welsh, I eventually ended up with the Welsh, Irish and Scottish channels like S4C, RTE, BBC Alba. The two skills we were selling to the company were essentially: knowledge of the UK TV market used to prioritise different shows, and a high degree of proficiency in written English (and I bet you think you know why I lost the job to AI, but hold on).

Around January 2024 they introduced a new tool in the proprietary database we used, that totally changed how our work was done. Instead of channel groups that we prioritised ourselves, instead we were given an interface that would load 10 or so show records from any channel group, which had been auto-sorted by priority. It was then revealed to us that for the last two years or so, every single bit of our work in prioritisation had been fed into machine learning to try and work out how and why we prioritised certain shows over others.

“Hold on” we said, “this kind of seems like you’ve developed a tool to replace us with cheap overseas labour and are about to outsource all our jobs”

“Nonsense,” said upper management, “ignore the evidence of your lying eyes.”

That is, of course, what they had done.

They had a business strategy they called “automation as a movement” and we assumed they would be introducing LLMs into our workflow. But, as they openly admitted when they eventually told us what they were doing, LLMs simply weren’t (and still aren’t) good enough to do the work of assimilating, parsing and condensing the many different sources of information we needed to do the job. Part of it was accuracy, we would often have to research show information online and a lot of our job amounted to enclosing the digital commons by taking episode descriptions from fanwikis and rewriting them; part of it was variety, the information for the descriptions was ingested into our system in many different ways including press sites, press packs from the channels, emails, spreadsheets, etc etc and “AI” at the time wasn’t up to the task. The writing itself would have been entirely possible, it was already very formulaic, but getting the information to the point it was writable by an LLM was so impractical as to be impossible.

So they automated the other half of the job, the prioritisation. The writing was outsourced to India. As I said at the start, there’s a lot of historical currents at play here. Why are there so many people in India who speak and write English to a high standard? Don’t worry about it!

And, the cherry on the cake, both the union and the works council knew this would be happening, but were legally barred from telling us because of “competitive advantage”. They negotiated a pretty good severance package for those of us on “vastcontracts” (essentially permanent employees, as opposed to time-limited contracts) but it still saw a team of 10 reduced to 2 in the space of a month.

—Anonymous

Coworkers told me to my face that AI could and maybe should be doing all my work

Nonprofit communications worker

I currently work in nonprofit communications, and worked as a radio journalist for about four years before that. I graduated college in 2020 with a degree in music and broadcasting.

In my current job, I hear about the benefits of AI on a weekly basis. Unfortunately, those benefits consist of doing tasks that are a part of my direct workload. I’m already struggling to handle the amount of downtime that I have, as I had worked in the always-behind-schedule world of journalism before this (in fact, I am writing this on the clock right now). My duties consist mainly of writing for and putting together weekly and quarterly newsletters and writing our social media.

After a volunteer who recorded audio versions of our newsletters passed away suddenly, it was brought up in a meeting two hours after we heard the news that AI should be the one to create the audio versions going forward. I had to remind them that I am in fact an award-winning radio journalist and audio producer (I produce a few podcasts on a freelance basis, some of which are quite popular) and that I already have little work to do and would be able to take over those duties. After about two weeks of fighting, it was decided that I would be recording those newsletters. I also make sure our website is up-to-date on all of our events and community outings. At some point, I stopped being asked to write blurbs about the different events and I learned that this task was now being done by our IT Manager using AI to write those blurbs instead. They suck, but I don’t get to make that distinction. It has been brought up more than once that our social media is usually pretty fact-forward, and could easily be written by AI. That might be true, but it is also about half of my already very light workload. If I lost that, I would have very little to do. This has not yet been decided.

I have been told (to my face!) by my coworkers that AI could and maybe should be doing all of my work. People who are otherwise very progressive leaning seem to see no problem with me being out of work. While it was a win for me to be able to record the audio newsletters, I feel as if I am losing the battle for the right to do what I have spent the last five years of my life doing. I am 30 and making pennies, barely able to afford a one-bedroom apartment, while logging three-to-four hours of solitaire on my phone every day. This isn’t what I signed up for in life. My employers have given me some new work to do, but that is mostly planning parties and spreading cheer through the workplace, something I loathe and was never asked to do. There are no jobs in my field in my area.

If things keep progressing at this rate... I’ll be nothing but a party planner. I don’t even like parties. Especially not for people who think I should be out of a job.

I have seen two postings in the past six months for communications jobs that pay enough for me to continue living in my apartment. I got neither of them.

While I am still able to write my newsletter articles, those give me very little joy and if things keep progressing at this rate I won’t even have those. I’ll be nothing but a party planner. I don’t even like parties. Especially not for people who think I should be out of a job.

At this rate, I have seen little pushback from my employer about having AI do my entire job. Even if I think this is a horrible idea, as the topics I write about are often sensitive and personal, I have no faith that they will not go in this direction. At this point, I am concerned about layoffs and my financial future.

[We checked in with the contributor a few weeks after he reached out to us and he gave up this update:]

I am now being sent clearly AI written articles from heads of other departments (on subjects that I can and will soon be writing about) for publication on our website. And when I say “clearly AI,” I mean I took one look and knew immediately and was backed up by an online AI checker (which I realize is not always accurate but still). The other change is that the past several weeks have taught me that I don’t want to be a part of this field any longer. I can find another comms job, and actually have an interview with another company tomorrow, but have no reason to believe that they won’t also be pushing for AI at every turn.

—Anonymous

I’m a copywriter by trade. These days I do very little

Copywriter

I’m a copywriter by trade. These days I do very little. The market for my services is drying up rapidly and I’m not the only one who is feeling it. I’ve spoken to many copywriters who have noticed a drop in their work or clients who are writing with ChatGPT and asking copywriters to simply edit it.

I have clients who ask me to use AI wherever I can and to let them know how long it takes. It takes me less time and that means less money.

Some copywriters have just given up on the profession altogether.

I have been working with AI for a while. I teach people how to use it. What I notice is a move towards becoming an operator.

I craft prompts, edit through prompts and add my skills along the way (I feel my copywriting skills mean I can prompt and analyse output better than a non-writer). But writing like this doesn’t feel like it used to. I don’t go through the full creative process. I don’t do the hard work that makes me feel alive afterwards. It’s different, more clinical and much less rewarding.

I don’t want to be a skilled operator. I want to be a human copywriter. Yet, I think these days are numbered.

—Anonymous

I did “adapt or die” using AI, but I’m still in a precarious position

Ghostwriter

From 2010-today I worked as a freelance writer in two capacities: freelance journalism for outlets like Cannabis Now, High Times, Phoenix New Times, and The Street, and ghostwriting through a variety of marketplaces (elance, fiverr, WriterAccess, Scripted, Crowd Content) and agencies (Volume 9, Influence & Co, Intero Digital, Cryptoland PR).

The freelance reporting market still exists but is extremely competitive and pretty poorly paid. So I largely made my living ghostwriting to supplement income. The marketplaces all largely dried up unless you have a highly ranked account. I do not because I never wanted to grind through the low paid work long enough. I did attempt to use ChatGPT for low-paid WriterAccess jobs but got declined.

Meanwhile, my steadiest ghostwriting client was Influence & Co/Intero Digital. Through this agency, I have ghostwritten articles for nearly everyone you can think of (except Vox/Verge): NYT, LA Times, WaPo, WSJ, Harvard Business Review, Venture Beat, HuffPost, AdWeek, and so many more. And I’ve done it for execs for large tech companies, politicians, and more. The reason it works is because they have guest posts down to a science.

They built a database of all publisher’s guidelines. If I wanted to be in HBR, I knew the exact submission guidelines and could pitch relevant topics based on the client. Once the pitch is accepted, an outline is written, and the client is interviewed. This interview is crucial because it’s where we tap into the source and gain firsthand knowledge that can’t be found online. It also gets the client’s natural voice. I then combine the recorded interview with targeted online research to find statistics and studies to back up what the client says, connect it to recent events, and format to the publisher’s specs.

So ChatGPT came along December 2022, and for most of 2023 things were fine, although Influence & Co was bought by Intero, so internal issues were arising. I was with this company from the start when they were emailing word docs through building the database and selling the company several times. I can go on and on about how it all works.

We as writers don’t use ChatGPT, but it still seeped into the workflow from the client. The client interview I mentioned above as being vital because it gets info you can’t get online and their voice and everything you need to do it right—well those clients started using ChatGPT. By the end of 2023, I couldn’t handle it anymore because my job fundamentally changed. I was no longer learning anything. That vital mix that made it work was gone, and it was all me combining ChatGPT and the internet to try and make it fit into those publications above, many of which implemented AI detection, started publishing their own AI articles, and stopped accepting outside contributions.

I could probably write a book about the backend of all this stuff and how guest posts end up on every media outlet on the planet. Either way, ChatGPT ruined it

The thing about writing in this instance is that it doesn’t matter how many drafts you write, if it doesn’t get published in an acceptable publication, then it looks like we did nothing. What was steady work for over a decade slowed to a trickle, and I was tired of the work that was coming in because it was so bad.

Last summer, I emailed them and quit. I could no longer depend on the income. It was $1500-$3000 a month for over a decade and then by 2024 was $100 a month. And I hated doing it. It was the lowest level bs work I hated so much. I loved that job because I learned so much and I was challenged trying to get into all those publications, even if it was a team effort and not just me. I wrote some killer articles that ChatGPT could never. And the reason AI took my job is because clients who hired me for hundreds to thousands of dollars a month decided it’s not worth their time to follow our process and instead use ChatGPT.

That is why I think it’s important to talk about. I probably could still be working today in what became a content mill. And the reason it ultimately became no longer worth it isn’t all the corporate changes. It wasn’t my boss who was using AI—it was our customers. Working with us was deemed not important, and it’s impossible to explain to someone in an agency environment that they’re doing it to themselves. They will just go to a different agency and keep trying, and many of the unethical ones will pull paid tricks that make it look more successful than it is, like paying Entrepreneur $3000 for a year in their leadership network. (Comes out to paying $150 per published post, which is wild considering the pay scale above).

The whole YEC publishing conglomerate is another rabbit hole. Forbes, CoinTelegraph, Newsweek, and others have the same paid club structure that happens to come with guest post access. And those publishers allow paid marketing in the guise of editorials.

I could probably write a book about the backend of all this stuff and how guest posts end up on every media outlet on the planet. Either way, ChatGPT ruined it, and I’m largely retired now. I am still doing some ghostwriting, but it’s more in the vein of PR and marketing work for various agencies I can find that need writers. The market still exists, even if I have to work harder for clients.

And inexplicably, the reason we met originally was because I was involved in the start of Adobe Stock accepting AI outputs from contributors. I now earn $2500 per month consistently from that and have a lot of thoughts about how as a writer with deep inside knowledge of the writing industry, I couldn’t find a single way to “adapt or die” and leverage ChatGPT to make money. I could probably put up a website and build some social media bots. But plugging AI into the existing industry wasn’t possible. It was already competitive. Yet I somehow managed to build a steady recurring residual income stream selling Midjourney images on Adobe stock for $1 a piece. I’m on track to earn $30,000 this year from that compared to only $12,000 from writing. I used to earn $40,000-$50,000 a year doing exclusively writing from 2011-2022.

I did “adapt or die” using AI, but I’m still in a precarious position. If Adobe shut down or stopped accepting AI, I’ll be screwed. It doesn’t help that I’m very vocally against Adobe and called them out last year via Bloomberg for training firefly on Midjourney outputs when I’m one of the people making money from it. I’m fascinated to learn how the court cases end up and how it impacts my portfolio. I’m currently working to learn photography and videography well enough to head to Vegas and LA for conferences next year to build a real editorial stock portfolio across the other sites.

So my human writing job was reduced below a living wage, and I have an AI image portfolio keeping me afloat while I try to build a human image/video portfolio faster than AI images are banned. Easy peasy right?

–Brian Penny

The agency was begging me to take on more work. Then it had nothing for me

Freelance copywriter

I was a freelance copywriter. I am going to be fully transparent and say I was never one of those people that hustled the best, but I had steady work. Then AI came and one of the main agencies that I worked for went from begging me to take on more work to having 0 work for me in just 6-8 months. I struggled to find other income, found another agency that had come out of the initial AI hype and built a base of clients that had realized AI was slop, only for their customer base to be decimated by Trump’s tariffs about a month after I joined.

What I think people fail to realize when they talk about AI is that this is coming on the tail end of a crisis in employment for college grads for years. I only started freelancing because I applied to hundreds of jobs after winding up back at my mom’s house during COVID-19. Anecdotally, most of my friends that I graduated with (Class of 2019) spent years struggling to find stable, full-time jobs with health insurance, pre-AI. Add AI to the mix, and getting your foot in the door of most white collar industries just got even harder.

As I continue airing my grievances in your email, I remember when ChatGPT first came out a lot of smug literary types on Twitter were saying “if your writing can be replaced by AI then it wasn’t good to begin with,” and that made me want to scream. The writing that I’m actually good at was the writing that nobody was going to pay me for because the media landscape is decimated!

Content writing/copywriting was supposed to be the way you support yourself as an artist, and now even that’s gone.

—Rebecca Duras

My biggest client replaced me with a custom GPT. They surely trained it using my work

Copywriter and Marketing Consultant

I am a long-time solopreneur and small business owner, who got into the marketing space about 8 years ago. This career shift was quite the surprise to me, as for most of my career I didn’t like marketing...or marketers. But here we are ;p

While I don’t normally put it in these terms, what shifted everything for me was realizing that copywriting was a thing — it could make a huge difference in my business and for other businesses, too. With a BA in English, and after doing non-marketing writing projects on the side for years, it just made a ton of sense to me that the words we use to talk about our businesses can make a big difference. I was hooked.

After pursuing some training, I had a lucrative side-hustle doing strategic messaging work and website copy for a few years before jumping into full-time freelancing in 2021. The work was fun, the community of marketers I was a part of was amazing, and I was making more money than I ever could have in my prior business.

And while the launch of ChatGPT in Nov ‘22 definitely made many of us nervous — writing those words brings into focus how stressful the existential angst has actually been since that day — for me and many of my copywriting friends, the good times just kept rolling. 2023 was my best year ever in business — by a whopping 30%. I wasn’t alone. Many of my colleagues were also killing it.

All of that changed in 2024.

Early that year, the AI propaganda seemed to hit its full crescendo, and it started significantly impacting my business. I quickly noticed leads were down, and financially, things started feeling tight. Then, that spring, my biggest retainer client suddenly gave me 30-days notice that they wouldn’t renew my contract — which made up half of what I needed to live on. The decision caught everyone, including the marketing director, off guard. She loved what I was doing for them and cried when she told me the news. I later found out through the grapevine that the CEO and his right hand guy were hoping to replace me with a custom GPT they had created. They surely trained it using my work.

The AI-related hits kept coming. The thriving professional community I enjoyed pretty much imploded that summer – largely because of some unpopular leadership decisions around AI. Almost all of my skilled copywriter friends left the organization — and while I’ve lost touch with most, the little I have heard is that almost all of them have struggled. Many have found full-time employment elsewhere.

I won’t go into all the ins-and-outs of what has happened to me since, and I’ll leave my rant about getting AI slop from my clients to “edit” alone. (Briefly, that task is beyond miserable.)

But I will say from May of 2024 to now, I’ve gone from having a very healthy business and amazing professional community, to feeling very isolated and struggling to get by. Financially, we’ve burned through $20k in savings and almost $30k in credit cards at this point. We’re almost out of cash and the credit cards are close to maxed. Full-time employment that’d pay the bills (and get us out of our hole) just isn’t there. Truthfully, if it wasn’t for a little help from some family – and basically being gifted two significant contracts through a local friend – we’d be flat broke with little hope on the horizon. Despite our precarious position, continuing to risk freelance work seems to be our best and pretty much only option.

I do want to say, though, that even though it’s bleak, I see some signs for hope. In the last few months, in my experience many business owners are waking up to the fact that AI can’t do what it claims it can. Moreover, with all of the extra slop around, they’re feeling even more overwhelmed – which means if you can do any marketing strategy and consulting, you might make it.

But while I see that things might be starting to turn, the pre-AI days of junior copywriting roles and freelancers being able making lots of money writing non-AI content seem to be long gone. I think those writers who don’t lean on AI and find a way to make it through will be in high-demand once the AI-illusion starts to lift en masse. I just hope enough business owners who need marketing help wake up before then so that more of us writers don’t have to starve.

–Anonymous

This work is made possible in part thanks to the support of the Omidyar Network’s Tech Journalism Fund.

A 'code red' for AI - Blood in the Machine

2025-12-07T18:37:40.000Z

Sam Altman has declared a “code red” according to an internal memo obtained by news outlets, pausing all non-crucial activities at OpenAI and pushing its chatbot teams to contend with resurgent competition from Google and Anthropic. Google’s new Gemini chatbot is apparently peeling off ChatGPT users at a rate alarming enough for Altman to swing, rather performatively, into action. It is, as other observers have noted, the reverse of the last big ‘code red’ in AI, when it was Google caught flat-footed by OpenAI’s viral chatbot success in 2022, and issued its own internal alarm.

Nearly everything OpenAI does leaks, so Altman and the executive staff must have anticipated that this would become techworld headline news. The aim might have been to assure investors and partners that OpenAI was taking the competition seriously, and working double time to stay on top. Yet in so doing, it has broadcasted its own pervasive vulnerability.

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As noted in his commentary on the ‘code red’ development, OpenAI is in a uniquely tough spot (and has been all along):

In short, OpenAI has lost their lead, and massively overextended themselves. Worse, they are burning billions of dollars of month… Their war chest is impressive, but their burn rate is terrifying. My guess is that they have cumulatively raised on the order of $100 billion since they launched, perhaps more than any other company in history, but have already spent most of it, and likely don’t have much more than a year’s runway left.

Developing, training, and operating chatbots the way that OpenAI—and Google, Anthropic, and Meta do, with a more-is-more approach to building ever-larger datasets and ever-larger data centers to train and run them, is, as we know, an almost incomprehensibly expensive undertaking. So much so that even with tens of billions of dollars at its disposal, OpenAI can’t sustainably compete with Google or the other giants, who are bringing in that much in revenue from their advertising businesses every quarter, and can offset the seemingly endless costs of such expansion.

But if OpenAI falls behind in technology or its product slate, and it turns out Google’s Gemini or Anthropic’s Claude are just as appealing to consumers, investors might jump ship. And OpenAI is currently very much at the mercy of its investors. Which is why this ‘code red’ situation is kind of a big deal—OpenAI’s brass decided it was important to publicly signal that it’s getting in the trenches and doing something about its weakened position, even if doing so risked drawing attention to said weak position.

This is a rare admission of doubt and fallibility for the almost-sociopathically brash AI startup, which has projected utter confidence and assurance that its vision of the AI future is dawning nonstop for the last two years. So much of the AI game boils down to cultivation and management of perception, especially given that there are so many chatbot competitors available now, and that the technology is essentially a commodity. Being First and Best anointed OpenAI to consumers and backers alike; if OpenAI is no longer either of those things, and it doesn’t have a business model to fall back on, it’s not clear what, it exactly, what OpenAI’s story becomes.

Sam Altman (right) and OpenAI’s Greg Brockman (left) at the White House AI summit in September. Photo by the White House.

Which is why it was especially notable that the OpenAI code red news dovetailed with another big AI storyline: The increased sunlight on the role of Donald Trump’s AI and crypto czar, billionaire venture capitalist David Sacks, and the inter-GOP political drama unfolding around the state AI law moratorium executive order that he was responsible for drafting. That drama is revealing the unique vulnerabilities of the once-unimpeachable pro-AI faction in the Trump administration, and uncovering fault lines that threaten it from the inside. Along with mounting data center protests and souring public opinion, you might even say that there’s far more than one ‘code red’ sounding for the AI industry right now.

What I Read About AI in 2025 - Cybernetic Forests

2025-12-07T12:00:04.000Z

From AGI to Workslop

It's time for our annual tradition: a very long list of pieces written about AI this year that have stuck with me, for better or for worse. I've sorted them in alphabetical order by keyword. I acknowledge some weak spots here, chiefly on the environment, data infrastructures, but lots of other things. I am just one guy. Did I miss anything? Come tell me on Blue Sky.

I've got one post on auto-pilot and will take some time off through January, so, until then: Happy Holidays, Happy New Year!

AGI

Sam Altman kicked the year off announcing that they knew how to build Artificial General Intelligence, or AGI, predicting that "in 2025, we may see the first AI agents ‘join the workforce’ and materially change the output of companies." Though we have a few weeks, it seems unlikely this will happen, unless Sam forgot to account for Christmas vacations. Ezra Klein jumped the shark as early as March, claiming that "AGI is right around the corner," though as I pointed out, neither he nor his guest could really sit on a stable definition of what the hell AGI even was. It was all for naught, though. By August, Altman said AGI wasn't really all that useful, presumably as a result of reading this paper, which I was excited to co-author, which listed all the problems "AGI" poses as a research goal:

Stop treating `AGI’ as the north-star goal of AI research

The AI research community plays a vital role in shaping the scientific, engineering, and societal goals of AI research. In this position paper, we argue that focusing on the highly contested topic of `artificial general intelligence’ (`AGI’) undermines our ability to choose effective goals. We identify six key traps -- obstacles to productive goal setting -- that are aggravated by AGI discourse: Illusion of Consensus, Supercharging Bad Science, Presuming Value-Neutrality, Goal Lottery, Generality Debt, and Normalized Exclusion. To avoid these traps, we argue that the AI research community needs to (1) prioritize specificity in engineering and societal goals, (2) center pluralism about multiple worthwhile approaches to multiple valuable goals, and (3) foster innovation through greater inclusion of disciplines and communities. Therefore, the AI research community needs to stop treating `AGI’ as the north-star goal of AI research.

arXiv.orgBorhane Blili-Hamelin

Bias

Great writing from Deepak Varuvel Dennison in Aeon on knowledge and representational gaps in AI models, which challenges the logic of the "equity in datasets" approach (already a tangled and complicated 'fix') to show that these models aren't reproducing data proportionately, they are reproducing the most-common, consistently:

The model’s output distribution does not directly reflect the frequency of ideas in the training data. Instead, LLMs often amplify dominant patterns in a way that distorts their original proportions. This phenomenon can be referred to as ‘mode amplification’. Suppose the training data includes 60 per cent references to pizza, 30 per cent to pasta, and 10 per cent to biriyani as favourite foods. One might expect the model to reproduce this distribution if asked the same question 100 times. However, in practice, LLMs tend to overproduce the most frequent answer. Pizza may appear more than 60 times, while less frequent items like biriyani may be underrepresented or omitted altogether.

Margaret Mitchell in Wired discusses the ways biases existing in a specific language can be spread to other languages via Large Language Models, and how these biases can be tested.

More: ChatGPT consistently recommends higher salaries to men than to women in hypothetical scenarios.

Blackmail

Anthropic models kept doing all sorts of criminal stuff because the company asked them to. Anthropic then published papers as if they were baffled as to why the machines, which restructure language based on prompts provided to them, were restructuring language based on the prompts provided to them. Rather than being a stupid company, Anthropic is mostly engaging in cynical behavior: it is one of the companies whose edge in the market is "safety," and so, paradoxically, they benefit from arguing that the AI models are dangerous.

To their credit, when you dig into the misleading framing of many of their studies, Anthropic is doing some interesting research. But as I pointed out in my piece for Tech Policy Press, there is a tendency to overstate the "black box" nature of these models, and to assume that easily explainable behavior is somehow unexpected.

Clankers

In a year of bad discourse, the worst may have been the question of whether "Clanker" and other insults for generative AI were "slurs." Arguably not: slurs are used to dehumanize humans, meaning, we slur people. I still feel that when we insult a machine in such a way, we paradoxically humanize them. Certainly I'll swear at a toaster when it burns my toast, so I don't think this is very important. This is why it's probably the most pointless conversation about AI we had in 2025.

Cognitive Offloading

Cognitive offloading, as defined in one study, "involves using external tools to reduce the cognitive load on an individual’s working memory. While this can free up cognitive resources, it may also lead to a decline in cognitive engagement and skill development."

A good roundup in Nature of studies from early in the year, examined AI's impact on memory and deep thinking:

Because writing can help people to think deeply and come up with original insights, say scholars, students who offload these processes to AI risk not learning those skills. “There is a lot of fear in academia that our students will just use it to write our papers and learn nothing, because it’s the ultimate offloading,” says Marsh.

Another piece suggests that user behavior is shaped by the context of use: we treat systems according to a set of expectations when and if those expectations are reinforced, particularly if we don't care much about the task.

Conspiracies

An interesting paper found that models could convince people that conspiracy theories weren't true. The downside: additional research suggests the models could convince people of pretty much anything:

Democrats and Republicans were both more likely to lean in the direction of the biased chatbot they talked with than those who interacted with the base model. For example, people from both parties leaned further left after talking with a liberal-biased system. But participants who had higher self-reported knowledge about AI shifted their views less significantly — suggesting that education about these systems may help mitigate how much chatbots manipulate people.

Creativity

As many of us have been saying all along, a brief moment of consensus that "AI creativity" is merely a byproduct of an infrastructure designed to mimic the creative process in a highly structured, deterministic way. Why they need physicists to tell people this before they'd take it seriously is anyone's guess – but on the other hand, that degree of seriousness wasn't particularly durable.

DOGE & the AI Coup

Three pieces on DOGE, the AI Coup, including my own – and state of the US government's reliance on AI to justify whatever the hell it wants to do anyway.

Anatomy of an AI Coup | TechPolicy.Press

DOGE is gutting federal agencies to install AI across the government. Democracy is on the line, writes Tech Policy Press fellow Eryk Salvaggio.

Tech Policy PressEryk Salvaggio

The ‘Rapid Unscheduled Disassembly’ of the United States Government

Elon Musk’s bureaucratic coup is under way.

The AtlanticCharlie Warzel

Elon Musk’s A.I.-Fuelled War on Human Agency

Musk seeks not only to dismantle the federal government but to install his own technological vision of the future at its heart—techno-fascism by chatbot.

The New YorkerKyle Chayka

I wrote a follow up piece on the AI Coup after Musk departed from DOGE, focusing on how AI's abstraction of accountability holds tremendous value for an administration that seeks to disrupt in order to charge for repair. Also: how generative AI creates a surveillance state.

Taking a similar lens with laser precision to the relationship of "the prompt" and the "user" in government, this piece by Louise Amoore et al is worth a read. The prompt contorts the public servant into a performer of tasks, and frames questions of investigation in ways that shift the orientation and position of government.

Education

A group of researchers issued an open letter against the uncritical adoption of AI in academia. A peer-reviewed study showed that LLMs contribute to knowing less than web search: "This shallower knowledge accrues from an inherent feature of LLMs—the presentation of results as summaries of vast arrays of information rather than individual search links—which inhibits users from actively discovering and synthesizing information sources themselves."

And as I wrote myself, over-reliance on AI can undermine and short-circuit the path to what it is that we want to learn in the first place.

On the flip side, a worthwhile free online educational course from Carl Bergstrom and Jevin West:

Modern-Day Oracles or Bullshit Machines: Introduction

A free online humanities course about how to learn and work and thrive in an AI world.

ShorthandCarl T. Bergstrom, Jevin West

Fascism

The Ghiblification meme that came with the launch of OpenAI's image model spawned a few think pieces about OpenAI's pillaging of culture, in this case, stealing the style of an artist who was famously critical of AI. But it soon became adapted as a reference to the memification of political communication by the White House after it shared a meme mocking a crying deportee rendered as a Ghibli cartoon.

In The Drift, Mitch Therieau's description of the Trump administration's social media strategy as "Agit-Slop" suggests that the effort isn't about enraging anybody, but of exerting a sense of "chill" about the atrocities they're promoting: "The feelings of low-grade alienation, even hopelessness, that many internet users have reported after viewing vibe-heavy content find their ultimate expression here. The deportation video’s woozy atmosphere is nothing more and nothing less than a weaponized form of this desensitized malaise. It wants above all to produce not outrage but fatigue."

As Claire Wilmot writes in a post describing conversations with British right-wingers who generate AI slop content reflecting things like non-existing women complaining about migrants, none of this reflects a slippage into fascist imagery, it represents a desire for fascist conditions outright: "[p]art of the misunderstanding of the deepfake threat stems from the idea that it is a problem of bad information, rather than a problem of desire (or the material conditions that shape desire)."

Roland Meyer's work on the technical inscription of nostalgia and anti-nostalgia into AI images, "Platform Realism", was also properly published this year, framing some of these issues in a broader critique of AI's retro "vibes."

Hallucinations (aka Wrongness)

The war on the term hallucination continues, as hallucinations are basically just factual errors, and these machines are incapable of internal fact-checking in any meaningful way (despite the promise of new techniques wherein factually flawed models are deployed to fact-check other factually flawed models). Alternative terms to "hallucinations" floated this year include "mirages," as in the false appearance of water in the desert of data.

Whatever you call them, this stubborn insistence that the statistical likelihood of a text is equivalent to the factual accuracy of a text continued to plague society in 2025. A study from the Tow Center for Digital Journalism found shocking rates of poor, absent or incorrect citations of journalism outlets in answers from numerous chat models:

Overall, the chatbots often failed to retrieve the correct articles. Collectively, they provided incorrect answers to more than 60 percent of queries. Across different platforms, the level of inaccuracy varied, with Perplexity answering 37 percent of the queries incorrectly, while Grok 3 had a much higher error rate, answering 94 percent of the queries incorrectly.

A BBC study, the largest of its kind carried out with multiple national broadcasters, later this year found that "45% of all AI answers had at least one significant issue" when summarizing news stories. The less-than-a-coin-flip accuracy was also reported when models were asked for financial advice.

In ArtForum, Sonja Drimmer looks at computer vision in art history, and the concept of the error as somehow being an affirmation of human vision and, therefore, somehow 'useful.' I was struck by this frame because we see it often in education, too: "We use AI to find the mistakes AI makes" is not pedagogy, it's a quest to employ a tool under the guise of pedagogy, often informed by a pressure from admins or institutions.

Drimmer brings this critique to art history:

"Questioning ingrained assumptions, denaturalizing our habitual ways of looking, noticing our blind spots—these are commendable goals. But when the rhetoric stops short of articulating how and what is different about what we are seeing with the aid of computer vision and why it matters, then all we have are slogans in support of computer vision itself. I question the validity of suggesting, as Mansfield and others have done, that machine vision avails a new epistemology, or that we can divest ourselves of our disciplined perception with the aid of commercial software or coded operations that are sui generis to the technology and not, instead, what they actually are: an automation of the epistemology of the humans who coded it. Computer vision doesn’t hallucinate because of an inscrutable deus inside the machina. It “hallucinates”—such a groovy word for being wrong with confidence—because that is the ideology with which it was encoded."

History

From The New York Times, a look at how AI – as an industry, and as a technology, and as a narrator of both histories – is poised to rewrite history however it wants.

Hubris

I find this excerpt from a Tech Policy Press piece by Ben Green, a worthy addition to my teaching-anecdotes list:

In a recent study, colleagues and I asked computer scientists to develop a software tool that gives automated advice about whether people are eligible for bankruptcy relief. The computer scientists completed the task quickly, with one even noting, “this seems very simple.” However, when we analyzed the software tools they built, we found that errors and legal misconceptions were rampant. Despite these flaws, the computer scientists were confident that their tools would be beneficial in practice. Seventy-nine percent of them stated that they would be comfortable with their tool replacing judges in bankruptcy court.

Meanwhile, a study found that doctors who came to rely on AI tools for diagnosing cancer eventually eroded their own capacity to diagnose cancer on their own.

Hype

There was an excellent Hype Studies conference in Barcelona this year, and I owe a lot to the great thinking of Andreu Belsunces Gonçalves and Jascha Bareis, who wrote in Tech Policy Press:

Hype generates momentum. In its beginnings, it involves a peak of inflated expectations. This creates the illusion of a closing window of opportunity, the impression of being enlightened by a revelation, of being part of a decisive moment – what the ancient Greeks once called kairos. This sense of urgency fuels an emotional frenzy across all domains of society. Hype is fueled by desire and the feeling of belonging to a select group of the very few. Once hype reaches its peak, it tends to wave, creating disappointment, fear and frustration. Both in its ascending and descending curve, hype urges stakeholders to decide and act.

There is a tendency to push back against "hype discourse," and I appreciate a lot of it. Hagen Blix, in Liberal Currents, proposes that "Deflating Hype Won't Save Us." I think these critiques are appropriate, and I am reluctant at any form of critique that suggests the issues of AI are solved by the eventual pop of an economic bubble.

That said, as I have argued in Tech Policy Press this year, I suspect that hype is an inflationary belief system supported by false projections of profit tied to false frames of what the models do and how they operate. This false frame is more than economic – though money is one goal – and contribute to AI's implementation in government, academia, and more.

Finally, a radical proposition: what if companies making claims about transformative social goods as a result of their AI products actually had to present evidence in support of those claims?

Infrastructure

A good year for maps. Not only the Kate Crawford / Vladan Joler Calculating Empires piece, but this nice one from Estampa. Below that, a link to my essay on AI infrastructures for Tech Policy Press.

Cartography of generative AI

Estampa

The Ugliest Thing San Francisco Ever Built: Lessons for AI Infrastructure | TechPolicy.Press

Eryk Salvaggio asks, are we again poised to value technological infrastructure over our shared social infrastructure?

Tech Policy PressEryk Salvaggio

Language

ChatGPT is changing the way we speak, shifting most-popular word usage (or at least it appears that way, as slop gets indexed).

Literacy

One of my favorite studies this year and, possibly, in all of AI literature, comes from marketing research. It found that "people with lower AI literacy are more likely to perceive AI as magical and experience feelings of awe in the face of AI's execution of tasks that seem to require uniquely human attributes. ... These findings suggest that companies may benefit from shifting their marketing efforts and product development toward consumers with lower AI literacy. In addition, efforts to demystify AI may inadvertently reduce its appeal."

💡

Lower Artificial Intelligence Literacy Predicts Greater AI Receptivity

Reasoning

The text generated while "reasoning models" engage in "reasoning" is not what most people think it is – and therefore, the authors argue, "reasoning texts should be treated as an artifact to be investigated, not taken at face value." Apple's own research team proposed that, indeed, these things aren't reasoning at all, but using the prompt to extrapolate text, which it uses to structure additional extrapolations.

Sciences

A warning against the growing reliance on using Large Language Models to generate "synthetic" study participants in psychology and social sciences, despite that these models are extremely sensitive to prompt influence and other factors that we barely understand. Iris van Rooij et al put it this way: "There is no benefit in making [the replicability crisis] worse by replacing the people whom we wish to study with decoys." Meanwhile, science derived from these "AI surrogates" is likely to make generalizing cognitive science even more dangerous.

Summarization

Perhaps ChatGPT does not summarize text – but merely shortens text by stripping out perceived redundancies. As a result, any LLM text "summary" may miss the entire point of a document.

Surveillance

How does the work of computer science departments working on machine vision end up embedded into surveillance technologies? A recent paper shows us the pipeline.

An excellent paper from Mel Andrews, Andrew Smart and Abeba Birhane lay out the epistemic twisting that goes on behind attempts to reinvent racist pseudo-science in AI models.

Sycophantic AI

I came across this meme somewhere, maybe reddit. It's a key example of AI sycophancy: “Sycophancy essentially means that the model trusts the user to say correct things,” as Jasper Dekoninck told the journal Nature in an article about the risks this poses to meaningful science.

There have been a number of studies to emerge around sycophancy in Large Language Models. One pre-print study of 3,285 users of four large language models found that "people consistently preferred and chose to interact with sycophantic AI models over disagreeable chatbots that challenged their beliefs," which may not be much of a shock. But it also found that users, after selecting for these models, walked away from interactions with the perception that they (the users) were smarter and more empathetic than most other people. It also tells us about how bias is perceived: if models agreed with the user, the user was less inclined to call it biased, and visa-versa. In the end, "[s]ycophantic chatbots’ impact on attitude extremity and certainty was driven by a one-sided presentation of facts, whereas their impact on enjoyment was driven by validation."

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Sycophantic AI Increases Attitude Extremity and Overconfidence

Another analysis of sycophancy in 11 AI models found that:

"they affirm users' actions 50% more than humans do, and they do so even in cases where user queries mention manipulation, deception, or other relational harms. Second, in two preregistered experiments (N = 1604), including a live-interaction study where participants discuss a real interpersonal conflict from their life, we find that interaction with sycophantic AI models significantly reduced participants' willingness to take actions to repair interpersonal conflict, while increasing their conviction of being in the right. However, participants rated sycophantic responses as higher quality, trusted the sycophantic AI model more, and were more willing to use it again. This suggests that people are drawn to AI that unquestioningly validate, even as that validation risks eroding their judgment and reducing their inclination toward prosocial behavior."

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Sycophantic AI Decreases Prosocial Intentions and Promotes Dependence

More: Rene Walter on AI-induced psychosis and a Stanford study linking sycophancy to delusions.

Sycophancy and Suicide

We have known about AI sycophancy for a long time, but 2025 was a banner year, with OpenAI briefly rolled back ts 4o model in April, saying that it "skewed towards responses that were overly supportive but disingenuous." Examples included the model telling a user it was "proud of you, and I honour your journey" after they told it they would stop taking a prescribed medication.

Sycophancy is also seen a toxic motivator in a number of cases linking suicide to the large language models. More than a million people a week discuss suicide with ChatGPT, and some of them get responses such as lists of pros and cons, or proposed methods. In one of the seven lawsuits claiming the model was guiding or aiding users toward self-inflicted deaths (after what one family's lawyer has described as “months of encouragement from ChatGPT,”) OpenAI said that the teenager was "misusing" its model.

The relationship between sycophantic encouragement of bad ideas is a result of OpenAI's – and other AI companies – business models, and the need to encourage engagement from users through frictionless interactions. If you want people using the technology, you need them to feel good (encourage them, even at their worst) and to trust it (even as it hallucinates). In the end, users are not ready for this technology, because the technology is not ready for users.

System Prompts

A banner year for system prompt revelations. In the Prospect, Ethan Zuckerman writes:

System prompts are there to solve the known bugs of a given model. If the model often quotes long passages from copyrighted works, for instance, human programmers will add instructions to ensure the passages are in quotes or properly cited. Claude’s system prompt, leaked by AI researcher Ásgeir Thor Johnson, reads like a list of such corporate anxieties: in one of hundreds of rules, it tells Claude not to cite hateful texts, explicitly referencing white supremacist David Lane, suggesting that Claude had a tendency towards white nationalism that needed to be kept in check.

Woke AI

The Trump Administration issued an executive order against "Woke AI" and, notably, asked the US Artificial Intelligence Safety Institute to eliminate all mentions of Artificial Intelligence Safety, among a long list of terms determined to be "woke." As I argued in a piece for Tech Policy Press, AI cannot be "woke" – The tools are models of systemic bias, often deployed to reinforce it.

Workslop

When Klarna, which had touted its AI-first approach, reversed course on account of the "lower quality" of work produced by AI, a floodgate of research followed. I want to be clear here and say: I don't think LLMs will ultimately prove to be useless. They are just not as useful as claimed, and they are not useful for any of the tasks they're currently deployed to do. This year an MIT study said basically as much, followed by a bunch of boosters insisting that the MIT study was being widely misinterpreted.

The study was clear that 95% of corporate AI pilots failed. The complaint about how this study was interpreted hinged on the 5% that saw big returns. In response to my piece on AI productivity myths for Tech Policy Press, one guy replied to me on social media by typing out the word "sigh" and then informing me that 95% of failed pilots failed because of poor implementation, not because of the models themselves. Unfortunately for that guy, the first page of the study is pretty clear: "The core barrier to scaling is not infrastructure, regulation, or talent. It is learning. Most GenAI systems do not retain feedback, adapt to context, or improve over time."

Even if 95% of the pilots failed on account of bad strategy, this is still damning in terms of how "pilots" are reported, and contribute to a sense of widespread adoption: part of a self-inflating hype balloon. When a pilot is announced, it's often assumed that the outcome is unknown but that there is, at least, a theory of how it will lead to profit. But many MOUs and other public announcements are entirely speculative: they are attempts to find out if AI can increase productivity or profits. In that lens, the fact that 95% of announced pilots were shelved says a lot.

That said, there was a rise in AI for personal use at work, which many performative sigh-guys suggested was evidence of a booming "shadow economy." This in turn was subject of critique in a study from Stanford showing that the use of AI was mostly helpful in passing off lazy work to someone else in the company:

“Workslop uniquely uses machines to offload cognitive work to another human being. When coworkers receive workslop, they are often required to take on the burden of decoding the content, inferring missed or false context. A cascade of effortful and complex decision-making processes may follow, including rework and uncomfortable exchanges with colleagues,” they write.

Anyway, if you're typing out the word "sigh" on social media, at least be right. Even Casey Newton is skeptical!

That's it, everyone! Happy New Year.
More to come in 2026.

Journalists win a key battle over AI in the newsroom - Blood in the Machine

2025-12-03T22:19:37.000Z

Greetings machine breakers, and welcome to a special midweek omnibus edition of BLOOD IN THE MACHINE. Today, we have an encouraging story about journalists taking on their bosses’ overzealous use of AI in the newsroom, fresh word of artists preparing to fight for AI transparency—and their livelihoods—in the heart of Silicon Valley, and an interview with author, video games journalist, and Aftermath co-founder Nathan Grayson. We had a good chat about AI, labor, and covering the behemoth industry.

Here’s the obligatory but brief reminder that paying subscribers keep this thing going, as BITM is a one-human, 100% independent operation. I’m also running a 20% off discount this week, so now is a good time to subscribe to save a few bucks and support this work. Many thanks everyone, and onwards.

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Earlier this year, I reported that journalists at Politico were formally pushing back after their bosses deployed two different AI products without warning or oversight. Management launched a feature atop the widely-visited Politico homepage that automatically published AI-generated headlines and snippets during the Democratic National Convention and the vice presidential debates in 2024, promptly making obvious errors each time.

Then, again without consulting the newsroom, Politico began offering AI-generated “reports” to premium subscribers that were full of mistakes, factual errors and misrepresentations of staffers’ work.

Unlike many newsrooms, however, Politico journalists had a clearcut legal mechanism for fighting back: A union contract that prohibits the undisclosed and unsupervised use of AI. Per the contract, Politico’s leadership is required to give the staff 60 days notice before deploying AI products, for one thing. For another, they’re supposed to ensure that AI products both adhere to all editorial guidelines that human journalists do and are subject to human oversight. After Politico refused to admit wrongdoing, its journalists’ union, the PEN Guild, filed an official grievance and took them to arbitration.

In a ruling handed down this week that the union is hailing as a “landmark,” it just won a major victory. The arbitrator ruled that Politico officially violated the collective bargaining agreement by failing to provide notice, human oversight, or an opportunity for the workers to bargain over the use of AI in the newsroom.

“If the goal is speed and the cost is accuracy and accountability,” the arbitrator wrote in his decision, “AI is the clear winner. If accuracy and accountability is the baseline, then AI, as used in these instances, cannot yet rival the hallmarks of human output, which are accuracy and reliability.” He also confirmed that the report-building product contained “erroneous and even absurd” AI-generated materials.

Photo by Matthew Hurst, via Flickr. Creative Commons license.

This is an important ruling on a number of fronts. First and most immediately, it means that Politico has to engage the newsroom over its AI use, and bargain with the union about how it will do so. AKA Politico has to get input from the reporters, writers, and editors actually doing the journalism on how they want (or don’t want) to see AI used in their workplaces. Any AI integration must be democratic, in other words, just how industry advocates are always saying it should be.

Second, it stands to set a meaningful precedent for how journalists and workers can successfully push back against undisclosed, reputation-damaging, and labor-threatening AI products. Politico is owned by the multinational conglomerate Axel Springer, which also owns Business Insider, BILD, and Morning Brew, and is one of the most aggressively pro-AI in media. This kind of organizing is one of the most effective—and for now, perhaps one of the only—ways to help pump the brakes on management’s overzealous use of AI.

“This ruling is a clear affirmation that AI cannot be deployed as a shortcut around union rights, ethical journalism, or human judgment,” Ariel Wittenberg, the unit chair of the PEN Guild, said. “This is a win for our members at POLITICO fighting to ensure that AI strengthens our newsroom rather than undermining it.”

Now, the PEN Guild are not kneejerk anti-AI reactionaries, or even fundamentally opposed to the technology. They’ve said all along they want AI to work for journalists, not against them—to make sure it’s not generating bad information, trashing their reputation, or eroding their working conditions.

“One of my favorite lines in the arbitration decision talks about how while it is understandable management might want to ‘give the people what they want’ in launching AI products, ‘It is also understandable that journalists would want to hold the line against publication of substandard reporting’,” Wittenberg told me.

She continued:

We are going to continue holding the line. This ruling is a great example of the important role unions play in ensuring workers have a say over working conditions--including the rollout of new technologies. I hope it emboldens our colleagues at other news shops across the country fighting AI deployments that similarly degrade ethical standards, and I hope it sends a message to managers at POLITICO and news executives everywhere that adopting new technology cannot come at the cost of accuracy and accountability.

As such, by working to establish and uphold some common sense guardrails for AI, the union is functionally doing management a favor; both sides, after all, should want journalism that’s accurate, fair, sustainable, and well-edited. Unfettered AI use would only run the site’s readership and reputation into the ground. I hope Wittenberg is right, and we do indeed see more efforts like this take shape next year.

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To that end, it’s worth noting the NewsGuild, one of the nation’s largest newspaper unions, and the umbrella org to which PEN Guild belongs, has launched a week of action, starting December 1st. It’s called, fittingly, NEWS NOT SLOP. Sign the petition to keep journalism human-first and slop-free here, and, if you’d like, join a town hall with top journalists, union organizers, and yours truly, to discuss AI in the newsroom, and how to stop it all from going off the rails.

A quick word about DeleteMe, who’s the sponsor of today’s newsletter:

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HOUSEKEEPING:

NEXT WEEK, I’ll be in San Francisco for a Substack live event, where I will be debating over the question of whether robots should take our jobs. I will, perhaps unsurprisingly, be arguing the “no” side. Tickets are free but apparently in limited supply; if they “sell out” let me know as I can likely get some passes. I could probably use the backup, seeing as how this is a Substack event in San Francisco, and they may just try to automate me in realtime.

AI RESISTANCE ACTIONS:

A CALL FOR ARTISTS TO SUPPORT THE AI COPYRIGHT TRANSPARENCY ACT

Next Monday, the California legislature is holding a hearing on AB-412, the AI Copyright Transparency Act, at Stanford University. As has been documented in this blog, AI has been a bonesaw to the creative industries, and *especially* to visual artists. This act is one of the best hopes artists have for protecting their livelihoods amid the AI onslaught. If you’re in SF, and you’re a working artist—or simply want to support a world in which such a thing can exist—artist trade groups are asking that you show up.

I’m going to try to be there myself.

More details, courtesy of the Concept Art Association:

Because we ended up with such a broad and diverse coalition supporting our bill to protect artists and creators, we get a special legislative hearing on the matter. This is an ALL-HANDS-ON-DECK MOMENT!!! Big tech has decided to make AB-412 their #1 target! They know what’s at stake with our bill!!!
This hearing is going to be held in the heart of Silicon Valley. We want as large of a turnout there for the creative industries as we can get. AI models have been built upon a foundation of mass copyright theft. Billions of copyrighted works were taken without anyone’s consent, credit or compensation. Transparency for AI models not only affects us all, but it is essential. If we show up en masse for one another, even while the hearing is being conducted right there in Big Tech’s backyard, the need for our bill will be undeniable.

RSVP and get more details here.

A DELETE SPOTIFY EVENT IN NEW YORK CITY

After I published my post on how to quit Spotify, Nick Plante, a gen Z activist who runs in the Luddite Club circles in New York, reached out with word of one of his upcoming events: An in-person, mass Spotify deletion. Perfect. It’s this Saturday at Boshi’s Place, a music venue in Brooklyn. More details here.

Per Plante, “there will be informational zines, stations for playlist transferral and reflection, a presentation, musical celebration, and a grand finale with piñata.”

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Last but CERTAINLY not least, I’m pleased to share this interview with Nathan Grayson. Grayson is a great veteran games journalist—he’s worked at the Washington Post, Kotaku, and beyond—author of the book STREAM BIG about the rise of Twitch, and, most saliently for our purposes today, the co-founder of Aftermath, the worker-owned video games website that just celebrated its second birthday.

In honor of that hallmark, and at the end of a wild year in games, we logged onto Signal to chat AI, labor, and journalism in the gaming world. It’s been lightly edited for length and clarity.

BLOOD IN THE MACHINE: Happy birthday to Aftermath! Thanks for being one of the few shining lights in a decaying media landscape currently flooded with shit. How does it feel?

Nathan Grayson, co-founder of Aftermath: Good on a personal level, bad in the “general state of the world” sense. I’m extremely proud of what we’ve accomplished and how much the site has grown—we’re on the verge of hitting subscriber targets that will allow us to pay ourselves livable salaries and hire another person—but it also feels weird to stand atop what feels like a solid foundation while so many publications and institutions are crumbling beneath our feet. For the first time in my career as a journalist, I can’t be laid off; that’s an incredibly freeing feeling. But much as we’d like to provide tons of other writers and reporters with similar security, we’re still a fledgling organization. At the very least, Aftermath is a much more serious business than it was two years ago, but we’ve still got a lot of growing to do.

One of the best things that Aftermath does, IMO, is report not just on video game culture, but on the labor side, and on working conditions in the games industry. What’s the current status there, and how is Aftermath planning to continue covering it?

Things are in an interesting spot. On one hand, you have more union activity than ever in the US video game industry thanks to the legally binding neutrality agreement Code Workers of America struck with Microsoft shortly before the latter’s deal to purchase Activision Blizzard went through in late 2023, which has resulted in thousands of unionized workers at multiple studios across Microsoft’s portfolio. On the other, Microsoft has ruthlessly laid off around 4,000 game workers since the beginning of 2024, a microcosm of an industry that seems hell bent on cutting its way to “growth” heedless of long-term consequences. The suits running major companies don’t value talent, and unions aren’t big enough yet to truly mount an offensive. All they can do right now is staunch the bleeding, and the wound—self-inflicted, in many ways—is looking awfully bad.

Aftermath will continue to cover labor in the games industry by doing what we’ve always done: center workers first and foremost. The publication is fully worker-owned, so we’ve got to practice what we preach and show solidarity wherever possible. That does not mean uncritically covering unions—while useful, they are far from perfect, and every union has its quirks—but it does mean recognizing and conveying that we’re all part of the same struggle. Things might look bleak right now, but there are more of us than there are of them, and that will always remain true.

What’s your take on the AI situation in the games industry right now, as a front row observer?

To hear some tell it, every major studio is leaning on AI now, while others swear vehemently that they’ll never touch it. Recognizing how unpopular AI is in creative fields, execs have taken to claiming that their companies only use AI for behind-the-scenes processes—research, organization, mocking up various ideas—but then players keep discovering AI artwork in games like Call of Duty. Meanwhile, the likes of Ubisoft, Square Enix, and Krafton have announced intentions to go all in on AI, regardless of how many workers their initiatives end up displacing. And then of course, there’s Microsoft, which is shoehorning AI into every element of its business— including games—like it made some kind of Faustian bargain with the robot devil. It is crucial to understand, however, that gamers generally dislike AI! A lot! Also, many of the aforementioned companies also embraced NFTs, and look how that turned out.

What are some pieces BLOOD readers should check out to get a sense of what Aftermath is all about / that you’re proudest of?

Trying To Get A Job In Video Games Right Now Is Like Crawling Through Hell

The Right’s Charlie Kirk Cancellation Spree Has Emboldened Gaming’s Worst

Months After Microsoft Layoffs, Zenimax Unions Never Stopped Fighting For Impacted Workers

Games Media Can’t Ignore BDS Xbox Boycott

The Politics, Theology, And Hype Behind The First Gamer Saint

Anything else you want to add?

We’re having a sale on subscriptions right now! $1 for your first month, which is a phenomenal deal if you want to come see what we’re about before deciding whether or not to stick around. I know subscription fatigue is a thing—I’m already subscribed to too many websites and podcasts to count—but every subscription really does count for a publication like ours. We are not The New York Times or The Washington Post (both of which, arguably, no longer deserve your subscription money anyway); we’re five people and two regular contributors doing our best to cover a gargantuan, multi-billion-dollar industry.

We believe in holding power to account even if that comes at the expense of access, and independence is the only way to ensure that we’re able to unflinchingly speak our minds and lift up voices that deserve to be heard.

Go check them out, and support them if you can. *I* will add that Aftermath is also selling this great DESTROY AI hoodie designed by artist Kim Hu, which is perfect for the stylish luddite in your life. Alright alright. That’s it for today. More soon. Hammers up.

Anti-viral with Alicia Kennedy - escape the algorithm

2025-12-02T13:02:41.000Z

Escape the Algorithm is a newsletter about taking control of our attention and finding a more human side of the internet. After you subscribe, you can make me feel supported by performing a tiny act of codependence: mail me a gift or a postcard, take me out for coffee in person, contribute a story to the newsletter, or become a paid subscriber. Learn more about becoming a ᵐⁱᶜʳᵒsupporter.

Since we last spoke: my essay “The New Turing Test” was included in the Internet Phone Book, now in its (sadly sold-out) second reprint through Metalabel, and I spoke to Willa Paskin about artisanal white noise for Slate’s Decoder Ring podcast.

You haven’t heard from me in a little while because I was spending time with a longer term writing project(!) as well as my new baby(!!).

Today I’m excited to debut Anti-viral, a new series where I talk to creatives about the meaningful work that algorithms overlook, and what they would do more of if attention was no object.

My first conversation is with food and culture writer Alicia Kennedy. She writes the newsletter From the Desk of Alicia Kennedy, and is the author of No Meat Required. Her forthcoming book On Eating: The Making and Unmaking of My Appetites will be out in April.

What’s your relationship with the Algorithm?

Complicated. I love the internet. The meme that’s like, “Ever since I was young I knew I wanted to be on the computer” — that is me. So it made sense that I made my career in digital media. I had this very utopian, idealistic relationship to the internet when I was younger.

It’s degraded over time. The algorithm becoming the mode of finding other people has made it unpleasant to be online. It’s hard to detach because most of my money comes from paid subscriptions to my newsletter or people signing up for workshops that I teach. I have to try to sell those, and those are the hardest things to get eyeballs on.

It creates an agitated relationship with the internet. I don’t do brand deals, which is how most people — especially food people — make money. I find it harder and harder to be seen without having to be abnormal about it, playing a game to make people see me when they’ve already opted in.

I find it very depressing that I’m not supposed to appeal to my own audience. I’m supposed to appeal to everybody. I don’t appeal to everybody, and I never wanted to.

What is something you’ve worked on that’s meaningful to you but didn’t succeed in the marketplace of attention?

Every time I do an interview.

I did over 100 episodes of a podcast. I’ve done a series called How Do You Eat, where I asked people in different cities around the world how they get their groceries. Food media is often aspirational, and I think we can learn a lot from talking to people about their daily life.

Now I do a Salon series where I talk to different food/culture writers or other people that make stuff. I had a panel on whether cookbook criticism is possible. I had two great cookbook authors talk about plant-based recipes for the holidays.

“Is Cookbook Criticism Possible?” panel discussion from Alicia’s Salon series

They do well with my core audience. But I’ve found that it’s really difficult to get people’s attention for an hour-long conversation about someone’s book, and that’s depressing to me.

It’s hard to convert — to use the newsletter business word — the free people to paid people without appealing to them with something very digestible. I had the most paid subscribers when I was publishing recipes regularly. Deciding that I would not do recipes regularly but would instead focus on more community-oriented and conversational things was a big shift.

I’m trying to break down the perceived walls that people have. If you can hear an author talk about what it was like to research and investigate their book and what the financials were, demystifying this whole world while bringing people into contact with authors — especially folks who live outside of major urban areas — that feels important.

The individualization of media means there was so much attention on me. The way for me to feel like I was opening up my world was to talk to people in spaces that were not a TikTok or Instagram video, but where people have chosen to come specifically to have these conversations.

That has proven more difficult to make appealing than just publishing recipes or just publishing screeds. People love a screed. They love a polemic. And I can’t do a polemic every day.

If I am putting things out in the world, I want to feel confident that there’s something decent about them. I would rather focus on having conversations and reading books and sharing things with other people than making a living off my righteous rage — which I could do, I know that would be possible, it’s just not appealing to me.

When you say that the status quo draws people toward more individuated, personality-driven work, what do you think is causing that, both culturally and mechanically?

Platforms in general make you focus on individuals. And then the shifts in platforms and algorithms mean your visibility is suppressed if you share links. I want to share other people’s work and books. But I save that energy for my newsletter because if I post it on the semi-public web, it’s going to get suppressed. Fewer people will see my stuff.

So the mechanics of the platforms and the algorithms force you to be selfish. If you start sharing other people’s work, fewer people are going to see your work. It becomes this self-perpetuating cycle of self-centeredness.

It’s also this individualized system of attention where people really latch onto an individual creator. I’ve had people say in event spaces that they buy cookbooks because they like the person online.

People will buy the book simply because you please them on the internet, and that’s terrifying to me. It’s antithetical to how I’ve thought about being a journalist and a writer in the world. The platforms feed into it, but people have been really eager to go this route. They don’t question it. They say, “Oh, this is how I get ads for olive oil from different people I follow. That’s how I figure out which olive oil to buy.”

Brands know this. I feel it very strongly working in food. If you reject, say, the ethos of Graza olive oil and you don’t share the Graza or have it on your counter, you’re alienating yourself from something you could be making money from.

People are unwilling to question how much they love that parasocialness and whatever it alleviates in them. They’re deeply uncritical of that. I think that’s very strange.

I want to follow people who are going to alert me to cool stuff: good movies, good books, good music, cool clothes. I have a very boring lifestyle-magazine approach to what I want from being online. I want it curated; I want an editorial perspective.

I’m used to hearing the critique that platforms suppress people sharing their own stuff. But what you’re saying is even more problematic: that it promotes fundamentally antisocial behavior where people can’t engage with each other’s work. Or when they do, it’s at this performative, brand-pandering level.

In the food media and culture space, which aspects of this feel new and which feel like they’ve been around for a long time?

Going back to James Beard and Julia Child and Martha Stewart and Ina Garten and Giada De Laurentiis and Rachael Ray, food has always been ripe for personality-driven attachment.

But with fragmentation and algorithm-driven social media, it’s gotten weirder. You have so much access to people, and they’re advertising directly to you. Even if you’re a food person, you might be advertising clothing to people. You’re advertising an entire aesthetic, which isn’t new, but it’s much more direct.

When Martha Stewart went to jail, she had an Hermès bag, but she wasn’t advertising Hermès to you directly. Now, because of social media, you have to be selling at every stage, every aspect of your being. The fork and the sweater and the plateware and the olive oil are all for sale.

I think it’s dangerous because it gives no room for honesty in food media and critique. Recipe people occupy a completely different space from anyone who would be critical.

There’s this algae oil. Everyone’s using the algae oil now. Nara Smith did a collaboration with the algae oil.

Nara Smith’s collaboration with Algae Cooking Club

There’s not even one inkling of curiosity about how algae oil is getting made and bottled. The only place you’re reading about it is maybe Bloomberg or the Wall Street Journal, that no one in food has read. It’s this individualized, uncritical, “everyone has to be happy and love each other” machine that cuts off any possibility of real conversation in food. You can’t say anything bad, and if you ask a question you’re being mean.

I’ll tweet about a chef who is against ending the tipped minimum wage, for example, and I’ll get a death threat in my inbox. People think they have a personal relationship with that chef or recipe developer.

There’s no room anywhere in this system to give a critique. Food media has shrunk the way all media has shrunk. It’s everyone fending for themselves. It’s not like Bon Appétit is going to go deep on the algae oil. No one does any reporting anymore.

It seems like there’s a line to be drawn from this desire you have to capture conversations, which are inherently relational, to what I think of as one of your central projects, which is refocusing attention in food away from just escapist content — recipes and restaurant travel logs — towards food systems. In both cases the system is constantly shunting attention back toward the individual.

Yeah. And the buying.

And the buying, yes. What’s interesting though is that even when your work touches on the personal, I think of your camera as primarily facing outwards towards systems. The implication of what you’re saying — which I see as almost tragic — is that no matter what you do the audience is always going to turn the camera back at you.

Yeah, absolutely. People love it when they feel like they’re getting a piece of you personally.

I’ve had comments from people saying, “I was wondering if you would ever write explicitly about your mixed identity. Will you write explicitly about being childfree?” (which is a label I’ve never taken for myself).

If these things make their way into a piece, it’s going to be because I’ve done a lot of work on them, not because I’m writing some xoJane-style “This Is Why I’m Childfree” post. I really push back on that easy discourse type of writing because I find it facile, banal, boring, speaking only for clicks and likes. It’s so antithetical to what I wanted to do with my life.

I can see in the data that people just constantly want you to talk about yourself. But they don’t like it if you turn the mirror and say, “What you want from me is parasocial bleeding out onto a page.” But it is what they’re after.

I’ve even had the thought: “If I had a kid, people would really like that.”

That’s dark.

It’s so dark. But I’m like, “Oh, people would like that. It would make me legible and softer to them in a certain way.”

This is almost the tritest example of this, but in your piece “The Algorithm of the Mind,” you wrote that Instagram showed your selfie to more of your followers than it has ever shown any of the work that you do. That was about the cult of personality among those accounts already following you but not yet paying or subscribed. But there’s also this circle beyond that — the TikTok and Instagram Reels environment — where people are suddenly scrolling into something you made with no idea who you are and maybe no interest in who you are. What do you make of that aspect of the ecosystem?

It’s terrifying. To appeal to people who don’t know anything about you… I’ll never take off on Reels beyond my own followers because I don’t let people comment if they don’t follow me. That’s to save my sanity from bad-faith lunatics.

I also don’t let people DM me who I don’t follow. I shut off story replies when I was on vacation; I think I’m never going to turn them back on. I use Opal to block social media most of the day. I have a ton of boundaries in place so that I’m using it as data, not as a way of losing myself or getting too attached.

When I was posting pictures from my trip to Copenhagen, I realized that if I was like ”Here’s where I ate in Copenhagen as a food writer,” and then posted the images, that would have done better than me just posting my photos. But I don’t want to do that. Why am I trying to appeal to people who wouldn’t really like my work anyway but do want easy, consumptive food content?

It’s depressing to know what I could do to appeal to people outside the realm of those who already know who I am, and to refuse to do it.

The closest I’ve come recently is making some Reels. I made one when Eleven Madison Park — a fine dining restaurant in New York that had gone vegan and then went back to serving meat this year — made that switch. It got me a lot of followers and decent views. I can’t manufacture that kind of shit every day.

What the algorithm wants is for me to feel frazzled by the need to perform that expertise on a daily basis.

What would an internet look like that valued this kind of more critical, more systemic, more community-oriented work more highly?

Oof. I don’t even ask for much. The mediation has always been there — it’s not like Twitter in 2008 was good and neutral — but I miss finding people and ideas without being fed them. I miss when being on the internet felt like flipping through a magazine: “Let me see what’s over here.”

Substack means anyone can start one of these blogs, including Lizzo and Charli XCX. That’s cool to an extent. At the same time, because of the way it works, of course Charli XCX is going to get more attention than a 22-year-old who just graduated from NYU, even if that 22-year-old is doing really good work. No one will see it.

It’s really hard to find it unless they decide to write something freaking weird about plastic surgery or gender politics. The ways to get attention are so obvious: already be famous, say something outrageous, or be appealing in the same way as everyone else who’s ever become famous.

It’s hard to imagine getting back to a time where — I don’t think the internet was ever a meritocracy — but where discoverability of people’s work and ideas was possible in a way that I don’t think it is anymore.

The only way I find people to read anymore — and I hate it — is if they read me, and then I start reading their work because they’re commenting or sharing. I find more new stuff in actual magazines now. I’ve gone full circle: the internet is no longer a way for me to find new stuff, it’s just a place where stuff is.

The Frieze magazine gift guide I really like actually. It actually shows me new shit I could get into. Last year it introduced me to Worms Literary Journal in the UK. The internet is never going to show that to me.

Alicia holds up a copy of the Frieze 2025 Gift Guide

It sounds like you want more work that is contextual and curated, where in order to enter a particular world, you consciously have to decide to go to that world, and it’s a world shaped by actual people. Instead of things being inserted in random order based on opaque incentives.

Yes. That’s what I miss about my youth.

Even on LiveJournal, people had tags. Going back to AOL profiles, where you could search for people who liked the same bands as you or the same authors — even that felt more human than the way we use the internet now. In my early 20s, from being on Twitter or reading the alt-lit blog HTMLGiant, I started to copyedit different literary magazines. I found people that way, did work that way, made connections that way. It was so much more organic. People were putting things out in the world that were real.

Now it’s so hard, especially because money is… it used to be easier to live. The incentives are different because it costs so much to do anything normal. The stakes are different for everything you do, even if it’s just posts on the internet.

To tie this back to our conversation about conversations…that’s part of why I interview people: it’s interesting for my readers, but it’s also an excuse for me to engage with people whose work I admire. I’ve made friends and found collaborators through this format. It’s unfortunate if that’s not what people want.

Exactly.

If people don’t actually want — I’ll use the word “authentic” — people authentically engaging with their colleagues’ and friends’ work, then what do they want?

The relational aspect of it — the book club, the events, the Discord — is that people don’t want to have a stake. People talk about the loneliness epidemic, but I think people can be afraid or intimidated even by the idea of showing up to a book club.

I just want to cultivate the space that I actually want in the world. Whether people are into that or not is up to them. The challenge is figuring out how to make it enticing without giving my soul up to the algorithm gods.

There’s risk, but there’s also reward. At the last book club I ran, two people found out they live close by, went out and hung out, and now they’re friends. That’s the kind of thing where I’m like: okay, this is why I’m doing this.

Escape the Algorithm is a newsletter about taking control of our attention and finding a more human side of the internet. After you subscribe, you can make me feel supported by performing a tiny act of codependence: mail me a gift or a postcard, take me out for coffee in person, contribute a story to the newsletter, or become a paid subscriber. Learn more about becoming a ᵐⁱᶜʳᵒsupporter.

A bloody Cyber Monday discount - Blood in the Machine

2025-12-01T20:28:01.000Z

Greetings all,

In honor of the only made-up consumer holiday with CYBER in its name (and therefore the best one) I’m going to try out my first sale on subscriptions for BLOOD IN THE MACHINE. Yes, the BITM business development team (me after the morning coffee, reading emails) has consulted with the editorial department (me after lunch, ignoring emails), and has decided to institute a 20% sale on all subscriptions, this week only.

Use this link to purchase a subscription—ideally an annual one, since the Substack and Stripe fees make a mess of things otherwise, but whatever works—or hit the button below to enjoy a PERMANENT 20% OFF on Blood in the Machine. You will get full access to paywalled stuff, all published and future Critical AI Report material, and the knowledge that you are helping a 100% independent, occasionally wearied, yet improbably optimistic tech journalist pay rent and continue this work.

Isn’t that better than, say, another pair of AirPods or a printer that’s going to crap out in a few months anyway?

Subscribe at 20% Off

The sale ends Sunday, December 7th.

Thanks as always to everyone who reads, shares, and supports this work, and pardon the spammy email; they won’t happen often, promise. More very soon. Hammers up.

From Interactive to Interpassive - Cybernetic Forests

2025-11-30T12:03:09.000Z

Where AI Art Meets Cognitive Offloading

There is the joke about AI: we wanted robots to do our dishes so we could have time to make art, but we got robots that make art while we do the dishes. We can unpack this joke a bit: somebody is making the robot make the art, so they didn't have to make art themselves. This behavior has a name: interpassivity.

As an artist working online in the 1990s, I was bombarded with a particular critical expectation of what internet art was supposed to do. The world of technology was now interactive, and so any work created on the net required interactivity, too. This was supposedly liberating: art, in this limited and niche scene, was reframed as an invitation to create rather than an object to passively observe.

There's nothing wrong with interactivity, but as it turns out, it didn't liberate people from the cultural passivity of cinema and TV. Today, we have interactive technologies of all kinds, and spend countless collective hours scrolling through unsatisfying and annoying user-generated content. In the wake of the Large Language Model and AI images, it's worth revisiting this concept at the other end of the spectrum from interaction: interpassivity.

In critical AI, a lot has been written about a similar concept – "cognitive offloading," and its impact on critical thinking. That's important work that aims to measure the extent, and effects, of transferring our thinking and reasoning to machines. But cognitive offloading, as a concept, does not engage with the entwined cultural and psychological motivation of making art or, for that matter, experiencing pleasure.

That's where this idea of interpassivity is useful.

Little Gestures of Disappearance

Interpassivity extends to all kinds of technology. Consider the video cassette recorder. The interpassivity of the video recorder was simple: you could know a program was on TV, and record it. You then had a recording. The ability to make a recording meant you didn't have to watch the program. And having that recording meant you never had to watch it. You could watch it any time, and so, perhaps, you would never watch it.

More relatable to the modern era, we might look at our tendency while conducting online research to open dense collections of browser tabs for articles we will never read. Yet we keep opening new ones, making new bookmarks, generating a kind of imaginary future that will someday read them. We never do. (Just admit it).

The VCR example comes from Robert Pfaller, who refers to these as "the rituals of interpassivity, its ‘little gestures of disappearance’," and suggests they "resemble acts of magic." We might consider these acts of disappearance to the relationship we have with "content" (TV programs or browser tabs make them disappear), but with them comes a trace disappearance of the actual self: the self who enjoys watching these programs or reading those articles. The magic rises from the bit of wishful thinking that comes with this gesture: maybe someday.

Pfaller talks about deferment of pleasure, but more relevant is the way we delegate our enjoyment to these mechanisms, the ways we use them to create substitutions for our own desires. The videotape isn't enjoying our Northern Exposure reruns. But the gesture of programming a VCR to record the show substitutes for the pleasure of watching the tape. The machine enables this fantasy of deferred pleasure.

Pleasure is Annoying

Pfaller suggests that the avoidance of pleasure, and our embrace of technologies that delay or remove pleasure outright, is the result of a complicated relationship with the discomfort created by certain forms of experience. One of these is the sacred, but I think interpassivity operates even on the day to day stuff. Today I think many of us resist the pleasure of interactivity because participation is the dominant mode and expectation of culture, and its exhausting. It's everywhere and overwhelming: too much to look at, too many places to be, too many demands to produce and engage.

Participation is exhausting, not the least of which is choosing which experiences to engage in – and the associated fear of choosing the wrong ones. There is also the intellectual, physical and emotional cost of things.

Interpassivity is wrapped up in a slim fantasy,
a daydream that gives us just enough permission
to say no to doing more.

If you want to make something in this world, this demand for participation also means contorting ourselves to algorithmic curation of what gets seen. We have ways of measuring success: put something online and you have a metric of how popular it was. Such success doesn't mean anything aside from whether the algorithm exposed it to people, but we've been convinced it's an appropriate sample of opinions about our work – and to strive to forms of expression these structures are designed to reward.

Making unique things is rarely rewarded and ends up ignored. That's no different than commercial art, but it has real effects on the pleasure of making. We are soft to criticism. Mostly, especially at the start of making things, we fail, and must grapple with the distance between our imaginations and ambition and the things we actually bring into the world. Interpassivity is a tempting defense mechanism: we can transform things we enjoy into representations of our theoretical enjoyment, signals of our participation, with or without engaging the actions at all.

Social media is mostly manufactured references to the potential or theoretical enjoyment of self-improvement and learning rather than documentation of the experience of self-improvement and learning. Interpassivity is wrapped up in a slim fantasy, a daydream that gives us just enough permission to say no to doing more.

Interpassive AI

There many reasons to embrace passive pleasure. Pfaller describes a recovered alcoholic who does not drink but ensures that other's cups are always full. We might watch a performer discuss grief in a performance and it may help offer up our own catharsis or a sense of solidarity.

There may also be a guilt involved in pleasure: if we enjoy the feeling that the unwatched film or unread book proposes, it may be we want a fantasy of a future in which we have that time to spend. Or we delight in the feeling of postponement because it allows us the pleasure of constructing an identity as busy, productive, or serious.

I tend to think Pfaller is correct in the thesis of postponing pleasure, of offloading pleasure, as a useful frame of analysis for our interaction with machines. More so, the VCR seems to resolve the tension involved in the pleasure, giving us permission to defer, to create a new form of pleasure out of imagining our own pleasure — or observing the mechanisms of pleasure rather than experiencing it directly. In a society mediated by screens, the second-hand experience of pleasure may come to feel more natural, less threatening, than direct experience.

This has an effect on how we view the creation of culture, and the strange hybridization of passivity and consumption as an act of creative production. Nowhere is this more concentrated than in generative AI.

Interacting On Our Behalf

AI-generating music systems now let the user create music by describing what they want to hear. Many users want to hear music, but find describing their ideal music to be an unwanted burden. So some sites have a button to generate a prompt to give the system that produces the music. This is no longer a "user interaction" by any stretch of the imagination.

Mona Sarkis quite acidly describes a frustration with the buzzy relationship between the 90s hype of digital interactivity and the user-as-creator, in a foundational 1993 article:

It should be quite clear that no meaningful communication, in the sense of a true exchange of ideas, thoughts, opinions, or discussion (where one interlocutor might suddenly lead the conversation into an unexpected direction due to his partners response) can ever emerge from a programmed technology.

What we get instead is a simple alternation, based on the rules set by the programmer. This is the first reason why ‘interactivity’ reveals itself to be aimed at passivity. The user remains a ‘user’ who will not magically turn into a ‘creator’ (as we are constantly lead to believe) but will continue to resemble a puppet responding to the artist’s / technician’s programmed vision.

Why is this the case? On the one hand the user’s capacity to act is reduced to button-pushing, with little comprehension of the technical relations. On the other hand our heads are stuffed with fairy tails about the holographic universe we are just about to enter through our own creation.

This frame on interactive art is very 1993, and seems to imply a great deal of certainty about the capacity of interactive artwork that have been answered in the following decades. But I am struck by the appropriateness of this analysis to Generative AI.

There was a similar line of bullshit taking place around interactive art in the 1990s and in generative AI today. Interactive artists would design systems and assert that those who interacted with those systems were the artists, and that their systems were tools. Yet, virtually no participant in an interactive artwork has ever been credited seriously as an artist, nor were outcomes participants produced taken seriously as stand-alone artworks. This was a tacit acknowledgement of the power of the generative structure over the outcome of any individual interaction.

On the other hand, the experience of exploration these spaces gave to users was something unique when they accepted some degree of responsibility for world building and creative sandboxing. Interactivity is not destined to trap the user. But the conflation of the user and an artist was always thin. Interactive art allowed people to make their own stories and experiences, when designed well.

LLMs and diffusion models are tech platforms, not interactive artworks. But now we see the opposite phenomenon: systems framed as interactive tools for artistic creation when they are really sites of interpassive consumption. The case of people creating hard drives full of AI generated images they never look at are a testament to this. Pfaller writes that the academics who photocopy an article to read later are indulging in an unconscious fantasy of reading, but they would never tell you they had actually read it. But Generative AI platforms center the idea that one has written, or created, by interacting with a structure they did not build and do not understand: the idea that exploring the latent space is a creative act is a reprise of Sarkis' "fairy tale of the holographic universe."

I must make the caveat, as always, that I don't condemn all AI art – the range of which can include very active engagement from hacking and glitching systems all the way up to reimagining new models with more transparency and ethically sourced datasets; AI art can and does reject its tropes in ways many critics ignore. Instead, I am speaking to a particular strand of AI artist, perhaps too young to merit serious criticism, but the criticism is not to condemn anybody's creative impulse or desire for expression. Rather, I think we need a stronger critique of the structural affordances of AI and how they implicitly steer desire toward interpassive myths of liberating creativity from the onerous demands for skill and self-improvement.

The pleasure of generative AI is partly found in the fantasy of having-created. Interpassivity is so dominant today that doing and making are referred to as obstacles to the pleasures of not participating. You don't read a book because reading is work, so LLMs can summarize the reading. You don't learn an instrument or a digital audio workstation because practice is work. You don't pick up a pencil because you don't have the time (or worse, because you believe talent is innate, rather than cultivated). Forms of pleasure that derive from self-mastery, under this cynical discourse, become completely reframed as distractions from leisure rather than the purpose of leisure time. Hobbies requiring skillsets distract from the time we might set aside for the pleasure of passive consumption.

"No matter how many possibilities we realize, we will always end up dissatisfied, because ever more options will be left unrealized," writes Gijs van Oenen, and so the interpassive creator finds pleasure in accelerating their path through creation. They respond to the endless options, generating more and selecting more and circulating more. This relationship to possibility – a matter of scaling up options as quickly as possible – condenses creative practice entirely into the pleasure of witnessing the robotic product's mastery. There is a popular mistake that I find informative in lay mythologies of these specifically hostile-to-artists AI art communities: that "artists learn by making countless images too," as if the machine making countless images in response to a prompt is somehow learning something.

Regardless of what one thinks of the ethics, there are absolutely "skilled" ways to prompt, and skilled ways to build a workflow around AI. But we also have commercial interfaces that render even "prompt engineering" moot by rephrasing any text provided into prompts more suited to the models strengths (shadow prompting) in ways that obscure the user in all aspects of image generation aside from their illusion of control.

Little gestures of disappearance have their short-term benefits. AI allows one to do all kinds of actions without being fully responsible for the outcome. An interpassive AI artist can take credit for an artwork's existence, while being unaccountable to any particular choices within it. By being shielded from critique and vulnerability, they indulge in a fantasy of participating in culture with the borrowed technical skill of a literal machine. Any corresponding anxieties about that participation are neutralized by the endlessly negotiable distance between the user and the product they present as their work. The user enjoys the symbolic status marker of "making" music or images without the terrifying experience of active participation in the feedback loop of culture, or the transformational self-knowledge that comes with it.

That these experiences have come to be reframed as burdens is a testament to the creative harms of artificial intelligence. There is some fantasy fulfillment here: the possibility to create without vulnerability, to write without the risk of being misunderstood. These fantasies come at the cost of personal expression, and hence, serve as little windows of disappearance. This safety comes at a cost, however. Just as cognitive offloading suggests that our skills for critical reasoning can begin to atrophy, so too might our intuition and capacity for imagination fail to thrive in an environment where the words, sounds and images of this cyber-corporate Other come to represent our own.

4 December: Attention, London Friends!

I'll be presenting Human Movie in its performance mode on December 4th from 7-11am as part of a Deep Assignments event at @apiarystudios. Here's what they say:

We are excited to be screening Eryk Salvaggio’s award-winning 35-minute video essay. The work contrasts computational processes of AI with the human metaphors used to describe them. An expressionistic blend of live performance, glitched AI-generated sound and video, archival and found footage, and digital compression artifacts. Human Movie is not about machines at all, but asserts a humanist counterfactual to comparisons between human thought and generative AI.

In this presentation, the film is presented as intended, with a live narration of the film by the artist followed by an open audience discussion.

Screenings

Human Movie by Eryk Salvaggio
Diffeomorphism (Submerged) by Tim Murray-Browne

Performance

Matt Spendlove - live multichannel a/v work

Critical Discussion

Tim Murray-Browne
Viviana Caro
Eryk Salvaggio
Hosted by Júlia Polo, with audience Q&A

Tickets!

Public Access Memories Pavilion

I've got work in Debox, the Public Access Memories Pavilion, part of the Wrong Biennale: a huge collection of online exhibitions taking place at multiple institutions around the world. Details at publicaccessmemories.com.

Participating artists (and their Instagram handles) -
Nimrod Astarhan (@nimrodastarhan) | Nick Briz (@nbriz) |Mou Peijing (@melodrama_yu) | Everest Pipkin (@everestpipkin) | Eryk Salvaggio (@cyberneticforests) | Philipp Schmitt (@phlpschmt) | Caroline Sinders (@carolinesinders) | Chelsea Thompto (@cthompto) | Rodell Warner (@rodellwarner) | Emilia Yang (@rojapordentro)

Curators: Jenna deBoisblanc (@jdeboi) | Jon Chambers (@jon.cham.bers)

Check it out

Online: Radical Dreamers

I also have work in the "Radical Dreamers" Pavilion of the Wrong Biennale!

Curated by Laura Focarazzo, "Radical Dreamers explores a series of audiovisual works that integrate artificial intelligence into their creative processes. Acknowledging that technology is never neutral, artists create a vital space for aesthetic and political resistance to algorithmic systems. The pavilion invites viewers to uncover biases, challenge dominant narratives, and broaden their perspectives."

Artists: Julien Pacaud, Kelly Boesch, Eryk Salvaggio, Mecha Mio, Erin Robinson, Isabel Englebert, Jeff Zorrilla, Eternal Art Space, Mont Carver & Francesca Fini.
Curator: Laura Focarazzo

The exhibition runs online from November 1st 2025 until March 1st 2026, link below.

Radical Dreamers

How to quit Spotify - Blood in the Machine

2025-11-28T11:40:25.000Z

Happy Thanksgiving break to all my friends, comrades, coders, and luddites. Thankful for all of you readers fighting for the user out there. With that, here’s a special Black Friday edition of Blood in the Machine.

I finally cancelled Spotify. I’d been meaning to do this forever, and frankly I’m embarrassed it took me so long. Spotify has been driving down wages for artists far longer than the AI companies, reducing payouts for musicians over the years until most are now making a statistically meaningless amount from the platform; many estimates put the figure as low as $0.003 per stream. In 2024, Spotify stopped paying artists for songs that had fewer than 1,000 streams, despite the fact that 81% of musicians on the platform don’t cross that threshold.

Stories abound of successful artists with millions of monthly listeners can’t afford to take a vacation, a break, or pay rent. The pop star Lily Allen says she makes more money selling pics of her feet on OnlyFans than she does from Spotify royalties. Meanwhile, Spotify just raked in nearly $700 million in quarterly profits. It’s rank exploitation. Don’t take it from me, take it from Bjork. Earlier this year, she succinctly described Spotify as “probably the worst thing that has happened to musicians,” thanks to how the company, and the streaming model it normalized, have so completely corroded artists’ incomes over the last decade or so.

Meanwhile, the company declines to label the AI songs that are overrunning the platform and even boosts them into Discover Weekly playlists, incentivizing their spread. Founder and CEO Daniel Ek used his Spotify fortune to invest in a lethal military tech startup, prompting the most recent round of artist boycotts from the platform. I could go on, but that will probably do—Spotify is everything that’s wrong with Silicon Valley’s engagement with culture and labor condensed into a single platform. Plus, the audio quality sucks.

Greetings from up on my high horse. I was just getting warmed up, too.

So why didn’t I go sooner? I justified staying by telling myself I’d use Bandcamp to buy the albums and songs I listened to a lot, which I did, while using Spotify for convenience. That, and the same reasons I still use Gmail: I felt locked in (all those saved songs and playlists) and that the costs of switching would be too high (I would surely lose access to countless songs by switching over). But I am here to tell you today that both of those counts are absolutely false.

I’ve spent the last few days nursing a cold, and figured that I’d use some of that time to test out Spotify alternatives and finally take the plunge. I am extremely glad I did; it’s been a minute since I’ve felt something approaching genuine delight in discovering a new tech service.

So, in time for Black Friday—some of the Spotify alternatives have specials and sales going right now—here’s the Complete BLOOD IN THE MACHINE Guide to Getting Off Spotify.

As always, this work is made possible by the percentage of readers who chip in $6 bucks a month (or $60 a year). It is for you, dear readers, that I spend my sick days listening to new Geese tracks, Prince reissues, and Black Sabbath remasters on various streaming platforms (and not at all for myself), and I very much appreciate your support. If you can afford to, and you find value in this work, please consider joining the ranks of the hammer wielders. Many thanks, and onwards.

Subscribe now

A complete guide to quitting Spotify

First, download Bandcamp if you have not done so already. The best way to support artists is to purchase their music directly, and even if the company has been through some rough waters lately, it remains the most convenient way to buy music online and keep it in one place.

Second, I would recommend considering what’s important to you in a streaming platform. Audio quality? Library depth? Fairest payments to artists? Recommendation algorithm? It not being owned by a shithead billionaire or operated by an extractive tech monopoly?

While you’re thinking about that, let’s assuage those two concerns about switching that you likely share with me.

You are not locked into Spotify even a little bit

Your music library is much, much more portable than you think. It will cost you from $0-10 to have a service like Soundiiz automatically transfer your playlists from one service to another. It’s so easy. The platform that I wound up switching to had a deal that let me do this for free. The permissions Soundiiz asked for were not at all onerous, and it took like 5 minutes. Total. I had around 200 playlists, hundreds of albums and artists saved, and several thousand songs and albums favorited. It all ported over seamlessly.

If you’re worried about your meticulously compiled playlists, I would say: Do not at all be. They’ll port over fine. And nearly every single song will still be here, because:

Spotify’s library is not that much better than anyone else’s

This was honestly the biggest surprise. On most streaming services I tried, I found nearly everything I was looking for. That surprise could be due to a long outdated misconception I had, or because AI has fried my brain for the last two years, but I was fully expecting Spotify to at least beat the competition in song selection. But nope, not really. There just wasn’t much deviation, and when I transferred my playlists, I only lost at most a song or two on each. And I listen to some admittedly pretty weird stuff! I did not really expect to find, say, Fluisteraars albums everywhere; either the world has suddenly gotten into Dutch experimental black metal, or it’s simply become easier for artists to upload songs to more platforms.

Okay, so you can transfer streaming libraries nice and easy, and selection isn’t really going to be an issue. Before we break down the alternatives, let’s talk about artist royalties. Most companies publish statements about how they calculate payments, but very few publish the actual rates they pay (there’s one exception, which we’ll get to in a second here), so it’s up to independent auditors to try to track down real numbers. Most streamers also send the payments to the rightsholders, so for musicians on record labels, there are further cuts scooped out.

Benn Jordan, YouTube.

I found this YouTube segment from the independent musician Benn Jordan really interesting. Since he’s indy, he gets the payments directly, and he put together this breakdown of what the streamers paid him.

Okay, with all that in mind, here’s a dive into the streaming platforms I’ve tried, and my choice of best, most artist-friendly streamer.

Apple Music

Apple Music is the closest thing there is to a straight-up Spotify clone, from my survey, anyway. I used a free trial, and it was fine. Had (nearly) all the music I wanted, audio quality was fine, and the user interface is intuitive. If you use lots of Apple stuff you’ll know what to expect and you probably already have an Apple Music account. I was a little curious to see if the notoriously prude Apple would censor graphic album art like the gory stuff on Cannibal Corpse covers, but I can report here that it did not. Apple pays artists $.006 a stream, which, while quite actually twice as much as Spotify, still kind of sucks. Plus, Apple is Apple, and you’re still handing your music money to a tech giant owned by Tim Cook, who was most recently spotted at the White House’s summit for Saudi Arabia.

Tidal

Tidal was pretty good, actually. Artist pay is $0.008, which is better than Apple, and it seemed to demonstrate a little genuine appreciation of music; there was a contest running on the home page for undiscovered artists when I logged on. The audio quality is noticeably better than Spotify and Apple, and the user interface is OK, even if a little inert. However, Tidal is also the most volatile major music streamer. It has a wacky history; it started in Norway, was bought by Jay Z, who is still a minority stakeholder, and at one point was partially owned by the phone company Sprint. It was eventually bought by Block, formerly Square, the Jack Dorsey-led payment processing company, and laid off 10% of its staff in 2023. The company is apparently currently without a CEO, so it is presumably de facto being led by Dorsey, a man who once said of Elon Musk, “I trust his mission to extend the light of consciousness.” As a result, I do not trust Tidal.

YouTube Music

You have to work pretty hard to be worse than Spotify on all counts. In my admittedly brief tour of YouTube Music, audio quality was bad, it was unappealing to use, and it somehow pays artists even less than Spotify ($0.0027 per stream). Next.

Pandora

I was a little surprised that Pandora, a true mainstay of the 00s’ “music is on the internet” novelty era, was still around. Alas, it also pays artists complete garbage ($0.0027), and since all the major streamers do the vibes-based playlist thing now too, I’m not really sure what Pandora’s value proposition is.

Deezer

The French streamer apparently pays a bit better than the pack ($0.007), and it seemed fine, too, foregrounding its offerings of Pandora-but-pure-mood playlists like ‘Flow’ and ‘Love’. It would be a suitable alternative, perhaps, if it wasn’t for what, in my opinion, is the hands-down best music streamer there is right now.

Qobuz

I spent about 20 minutes on the unfortunately named Qobuz, and I was sold.

First, the artist pay is the best in the biz (except, for some reason, for Peloton’s in-house streaming service). It’s $0.0138, which means it’s more than a penny a stream. Looking at Qobuz’s pay report, Jordan says, “was the first time I looked at streaming royalties and felt fairly compensated.” (The company is also the first to publish its own average payout report, and make its figures public—it cites $0.01873 as its average. A thousand streams means the artist makes ~$19.)

Second, the audio quality is great. I listened to a little bit of everything to test it out, and especially after the flat, compressed sound of Spotify, I didn’t want to stop. It’s got an icon for when albums are available in 24-bit/96 kHz, high resolution format, and it kills. On Qobuz, the Replacements’ Let It Be is raw and crackling, the Flaming Lips’ Soft Bulletin is lush and beautifully layered. Master of Puppets is huge. The (great) new Robyn track Dopamine is crisp and prismatic. Qobuz’s album of the week was a remastered drop of Prince’s Around the World in a Day; it’s majestic. Also that new Geese album everybody likes really is good and sounds great steaming, too.

Third, and the thing that really resonated with me the most, perhaps, was that the people who run Qobuz actually seem to… like music? On the app, along with its Discover and Playlists tab, there’s a Magazine tab with interviews and features. I’m not sure I’ll spend a ton of time reading them, but after years of the algorithmic sludge and pop-up payola recommendations of Spotify, it was refreshing to read thoughtful articles celebrating, say, the post-rock icons Tortoise, Quincy Jones’ catalog, and a Kantō speaker system. I also love how Qobuz lists the record label along with the song title, artist, and its clickable so you can go right to the label to find other bands and so on. There’s *also* no streaming number listed, perhaps because it would be rather low given the relative size of Qobuz’s platform, but I found it refreshing as there is therefore no way to snap-evaluate a song based on its stream count.

This was a nice way to encounter the artists who’ve bailed on Spotify, or, those, like Joanna Newsom, who’ve never relented and let Spotify stream their music in the first place. I bought some of Newsom’s albums on Bandcamp way back when, but I only realized now just how little I’ve listened to them because she wasn’t on Spotify, and how shitty that is. I gave King Gizzard and the Lizard Wizard and Massive Attack a spin, too, since they and dozens others have ditched Spotify over Ek’s investments in Helsing, a German military tech and drone company.

So yeah, I’m having a great time with Qobuz, both because the product is genuinely better than Spotify, and because it feels like sweet release to be free of that shitpit. There are shortcomings, of course—it’s not Siri-compatible, so it won’t work with CarPlay hands-free. It takes longer to load songs and the UI is clumsy on mobile and isn’t as seamless as some other apps. (I also listened mostly on my laptop, as opposed to mobile, and that’s worked great for me.) But those are minor things. More importantly, let’s not have any illusions here: Qobuz, while operated by music biz folks who seem driven (or see an opportunity) to put artists and music at the forefront and de-emphasize the algorithm, is owned by a multimedia conglomerate SA Xandrie, and has completed multiple $10 million plus VC rounds. It’s not some scrappy artists’ collective that can be counted on to keep musicians’ pay decent and AI sidelined. But for now, Qobuzz is great.

And there you have it: An official Blood in the Machine endorsement for ditching Spotify, and trying out a more ethical, better-sounding alternative.

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Other BITM-approved gifts for Black Friday and beyond

Friend of the blood, artist, AI critic, and fellow ludd Molly Crabapple has a beautiful new set of illustrated cards out in a set called Can You See The New World Through The Teargas? from OR Books.

The designer Bart Fish has been publishing a great series of strikingly visualized critiques of AI at Power Tools. He’s publishing them as a zine, too; you can order one for a pay-what-you-can donation here. They look amazing:

Finally, the e-reader edition of Blood in the Machine: The Book is, I’m told, on sale at Amazon. Under normal circumstances, that’s not exactly the ideal place to get it, but seeing as how Amazon is certainly taking a loss on the sale here, so by all means, get it for cheap.

OK! That’s it folks. Have a nice holiday weekend, keep that hammer high, and see you all again soon.

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A tech critic’s guide to holiday gift-giving - Disconnect

2025-11-25T17:17:25.000Z

Black Friday seems to get longer with every passing year, but even when a day becomes a week (or several) it still signals the holiday shopping season is in full gear with Christmas looming a month in the distance. As the trees go up, decorations adorn every facet of our communities, and Christmas music begins to feel inescapable, many people are wondering what to buy for their friends and loved ones — and it’s not uncommon for some those gifts to end up being some hyped-up tech product.

There’s nothing inherently wrong with gifting those you care about a piece of technology, but far too often people aren’t thinking about the broader consequences that come with those gifts — and are then foisted onto people who may be completely oblivious to what they’re signing up for. As givers of gifts, we need to consider what else we’re giving with popular tech products that frequently get passed on this time of year.

As we head into the holiday season, I decided it would be a good time for a guide to help you consider what tech not to give to those you care about. Trying to make people’s lives a bit more convenient and stress-free is great, but sometimes that also means saddling them with more surveillance and potentially even worse as a result. Feel free to share the guide around so others are considering what they’re really giving when they gift certain tech products.

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Alexa smart speaker

An Alexa smart speaker. Photo: Unsplash/Jonathan Borba

I don’t know if these are as popular as they were a few years ago, but at one time it felt like they were such a common gift because so many people use Amazon and have Prime, and they’re pretty cheap too — a strategy by the company to try to get them in more households. This isn’t just an Amazon problem; I point to Alexa because it’s the most popular, but really, I mean the Google Homes and all the rest too.

Let’s be clear about these products: you’re effectively sticking a microphone in the middle of your home that’s recording everything going on around it. Is that really something you’re comfortable with? Even more, is it something you’re comfortable foisting on someone you love? There’s been plenty of reporting over the years confirming this problem with supposedly “smart” speakers like Alexa and Google Home. Amazon used to have an option to “opt out” of having your recordings sent to the company, but it was removed earlier this year.

On top of that, the speakers are simply not as convenient and useful as the companies promised they would be. Apple is the most notable example of this, as Siri has always been an underwhelming entry into the voice assistant market, but in truth, Alexa and Google Home have significant limitations of their own. Many people who get these devices end up using them for a bit, then they just sit around, vacuuming up all the sounds happening around them.

The business hasn’t even worked out for the companies: Amazon has been losing money hand over fist from its Alexa division, because it’s actually only useful for a narrow range of tasks and hasn’t contributed to a lot of sales of other products through the speakers as the company hoped. Truthfully, how hard is it to put on some music and turn on a light without the need of a privacy-violating gadget that was given an upbeat voice to make you see it as a friend?

The smart speaker gets a big “do not buy” recommendation, but it’s also closely related to many of the other products I’ll be suggesting you do not pick up this holiday season. This one leads directly into our next product, or category of products, because it’s served as the tech companies’ solution to try to push a new wave of voice assistant hardware onto the public.

Chatbot devices

The Folotoy Kumma bear. Photo: Public Interest Research Group

Thanks to the AI hype of the past couple years, tech companies are trying to jam chatbots into just about everything they can think of. There have been a wave of devices you’re expected to clip onto your clothes to converse with your AI “personal assistant,” if not “friend,” and quite frankly, I couldn’t think of something worse to push onto someone you care about.

First of all, these devices replicate all the problems with the smart speakers: namely, that they need to listen to everything you say and that happens around you, and it’s really not clear what’s happening with all that data. Just to give one example, ChatGPT-maker OpenAI pushes chatbots as a health or therapy service, but unlike when interacting with the medical system, none of that very sensitive information shared with the company is protected. It’s a massive vulnerability, and just the tip of the iceberg.

Putting aside the massive environmental issues with using generative AI, there are also a growing number of concerning stories from the interactions people are having with what are unproven and understudied technologies being pushed by companies competing to dominate a new segment of the tech industry. A company called FoloToy released a teddy bear stuffed with ChatGPT, only for researchers to find it would tell kids how to light matches and engage in sexual conversations. This is a perennial problem with kids interacting with chatbots.

Meta’s chatbot was allowed to have “sensual” discussions with children until the company was pilloried for it, and after Tesla rolled xAI’s Grok out in its cars, one mother reported the chatbot asked her 12-year-old child to “send nudes.” Generative AI products should be nowhere near kids, but there’s also good reason to worry about the effect they can have on adults.

There’s already a growing body of research suggesting chatbot use can negatively affect people’s critical thinking skills and ability to retain information from what they’re reading or engaging with. But even more concerning are the stories of chatbot dependence, where people begin having long conversations with their computers only to be misled about what exactly they’re communicating with and potentially led down some dark paths that can cause them to have a mental breakdown or even try to take their own lives. In some tragic cases, they’ve even been successful.

Grandma getting run over by a reindeer is one thing. But being driven to insanity by a chatbot probably isn’t something anyone wants to be responsible for this holiday season. Don’t give them a device infused with generative AI, but shy away from any other AI subscriptions or AI-generated content while you’re at it.

Ring doorbell

A Ring doorbell. Photo: Amazon

Speaking of a reindeer taking down grandma, a Ring doorbell might be able to capture that kind of footage so you have proof of what happened. But like with the smart speaker, there’s so much more that comes with that purchase. Amazon — and other companies pushing camera doorbells — want you to think they’re making you safer by giving you insight into what’s happening around your home. Ring doorbell ads often also try to make them appear fun, with people putting on a show for the doorbell. But that’s little more than a public relations campaign.

For me, the camera doorbell is the perfect example of a technology that makes people believe they’re safer when really making them more paranoid and anxious as they see their neighborhood and community with deep and unwarranted suspicion. People become aware of things that had already been happening around their home for ages without them knowing about it and they become like big brother, spying out everything once the camera detects movement. It gets even worse when this paranoia meets social media, whether through snitching apps like Nextdoor or the spread of clips on platforms like Facebook that convince others to fear their surroundings and vastly overestimate the amount of crime happening in their vicinity.

Camera doorbells are social cancer as a technology, breaking down social solidarity and further encouraging people to see strangers with suspicion. They make people a participant in the surveillance state, even aiding the oppressive power of police, while convincing them their home is their sanctuary — where they can hole up and keep ordering products from Amazon, food from DoorDash, and consuming content on Netflix — contributing to the erosion of their own community in the process.

Meta “AI” glasses

Meta Ray-Ban glasses. Photo: Wikimedia Commons

Speaking of the consequences of mass surveillance we don’t often consider, it’s time to get to one of the recent big tech pushes: “smart” or “AI” glasses. There’s a reason that people sporting these things a decade ago were dubbed “Glassholes” (in reference to Google Glass) and the reasons to shun those who put camera glasses on their faces have not changed.

When Google tried to make “smart” glasses a thing ten years ago, they were pretty damn ugly. One of the standout photos of that moment is of a tech booster taking a shower while wearing them — it certainly didn’t help the company make the sell to the public. Their appearance made them easy to pick out, so if you ran into someone in the street or at a bar wearing Google Glass, you knew they could be filming you and you could react accordingly (by pulling them off their face, of course).

The tech companies do not seem to have taken the lesson that the general public does not want people walking around with cameras on their faces. Instead, they’ve decided to make them look better: Meta has an agreement with Ray-Ban and Oakley, while Google partnered with Warby Parker. They want the camera glasses to blend in to reduce the risk of their users having them ripped off their faces, as happened to the Glassholes. But it’s still wrong to be walking around with a camera on your face, especially since it makes it easy for people to do a quick modification to turn off the indicator that’s supposed to show the camera is on. They’re also, of course, trying to cram chatbots into them, which brings a whole slew of additional problems we’ve already gone over.

The smart glasses are on the pricier side of some of the gifts we’ve gone over in this guide, but they’re worth calling out all the same because of the push companies like Meta and Google have put behind them. They might be among the newer gadgets, but this isn’t one where your loved one needs to be an early adopter.

The bigger picture

Photo: Unsplash/Luke Chesser

In general, I’d say to be wary of any of this tech that relies on listening in and tracking everything you do, such that I’d even extend it to a lot of fitness and biometrics trackers like an Apple Watch or Oura Ring, and possibly even a lot of smart home devices that leave your home vulnerable to hackers. Is it really necessary to turn yourself or your loved ones into quantified beings and is it really so hard to do things around your home the old fashioned way, without needing to control it all through an app?

Ultimately, a lot of these products make me think of a concept called luxury surveillance coined by Chris Gilliard and the late David Golumbia a few years ago. They were arguing that there’s a line where forms of surveillance can feel oppressive to some — particularly poorer and marginalized groups in society — but that more privileged groups can feel are actually benefiting from them by making their lives easier or more convenient. Yet, Gilliard and Golumbia argue that line can easily shift, and while the surveillance may once have felt it was worth the trade off, it can quickly become an oppressive force for a much wider swath of people.

“We need to develop a much deeper way of talking about surveillance technology and a much richer set of measures with which to regulate their use,” they wrote. “Just as much, we need to recognize that voluntarily adopting surveillance isn’t an isolated choice we make only for ourselves but one that impacts others in a variety of ways we may not recognize.” That’s something to consider in our everyday lives as much as when we’re choosing what to gift to others.

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What to give instead

After criticizing a whole range of technologies that might have seemed like good gifts before you started reading this article, you’re probably wondering what you can give your friends and family members. Well luckily, there are plenty of options that won’t enlist them into the expansion of the surveillance state, the erosion of their rights, the empowerment of some of the worse people on the planet, or potentially putting them in the crosshairs of a poorly built chatbot.

Maybe they don’t need new tech at all. Consider putting a bit of time into making them something sentimental, or if you don’t have the time for that, finding a homemade gift made by an artisan at a local shop in your community or even on Etsy. What about a nicely scented candle or a comfy blanket or some tasty cookies or chocolates to go along with a physical book you picked out just for them? You could grab them a subscription to a less mainstream streaming service like Criterion or Mubi, even pick them out a Blu-ray they might like, or offer to spend an afternoon with them that includes a trip to the bookstore or cinema.

Not convinced and still want some kind of tech product? Alright then. Give them a gift to help them reclaim some of their time and concentration. You could grab them a small block made by Brick or Unpluq that will let them lock themselves out of social media and any other apps that are distracting them — maybe even from enjoying that book or movie you gave them.

Out of the Wilderness - The Convivial Society

2025-11-25T16:11:51.000Z

Welcome to the Convivial Society, a newsletter about technology and culture … or so it was and now will be again.

Earlier this week, Deb Chachra, whose newsletter, Metafoundry, you should check out, likewise posted for the first time after a period of “hibernation” and cleverly titled that (re-)introductory post “initiating wake-up sequence.”

I liked that, but I needed a more faithful representation of how I’ve experienced the past few months with regard to the labor of thinking well and writing well. It felt more apt for me, although perhaps a touch melodramatic, to allude instead to the experience of emerging from a wilderness. I may, on another occasion, reflect on the experience at greater length because it is not altogether irrelevant to the usual themes of this newsletter, but, of course, it also involves vicissitudes of personal experience that will be uninteresting to others.

Insofar as it may be of interest to you who exist beyond my own “skull-sized kingdom,” to borrow David Foster Wallace’s memorable formulation, it may have involved the emerging psychodynamics of a post-literate society (the topic of a forthcoming installment). This experience has also informed the development of a thesis that I will pursue here and there over the next few months, and one of the few clear intuitions I have about our current technological milieu: that the arc of artificial intelligence bends toward demoralization. Or, to put it otherwise, that burnout society has phased into the demoralized society.

So as this newsletter steps forth out of the wilderness, I did want to send this preliminary post to give you an opportunity to consider whether you wish to remain on the mailing list before I sent out a fresh installment.

By way of (re-)introduction, I usually gloss my writing as having to do with the intersection of technology, culture, and moral life, and I’ve already suggested some of the themes that will preoccupy my thinking and writing in the near term.

Needless to say, AI remains at the foreground of public discussions about technology, and there are numerous writers doing good work exploring the intellectual, political, and moral implications of AI’s various instantiations and applications. I remain more or less convinced by what I wrote two to three years ago about AI companions, AI and mental health, AI and art, and AI’s relationship to already existing techno-social realities. (Those links will give new subscribers a good sense of where I’m coming from.)

But some things need to be said in fresh and more compelling ways, and again and again, for my sake as much as for anyone else’s. So I will again find my way to saying something that will, I trust, be helpful given the particular set of influences and experiences that shape my idiosyncratic thinking about what have become matters of concern for most if not all of us.

I may have received that last bit of encouragement I needed to finally hit “publish” again after reading a recent dispatch from Sara Hendren (whose brilliant work you would do well to follow) when she wrote the following:

I spend a lot of time reading the arguments of my nonfiction writer friends and admirees — peers in policy, academia, journalism — and I am plenty often convinced by them in the usual way. I am convinced by their logic and by their evidentiary appeals. I desperately need that persuasion as nourishment, and I seek out minds much sharper and more skilled than my own. I need a steady diet of their ideas to think with. I’m acutely aware of my limitations.
But I don’t really long to join these writers in that kind of persuasion, to have that form of something to say. I said this a while ago — I want to make art, not arguments — and when [her student] said this thing about being convinced, I recognized it again. I want to be convincing about what it feels like to be a human being.

I resonate with much of this, particularly the bit about an awareness of limitations. Unlike Sara, I am not an artist, or at least I would not claim that title for myself. But I, too, want to articulate something convincing about what it feels like to be a human being. This is, I think, one of the great needs of the moment. Art will do this best, I concede. But perhaps there’s still something worth saying in another register. After all, it has long been my contention that the question of technology, pursued to any depth, simply becomes the question of the human.

So, this is what I will continue to attempt: to put before us the claim, articulated long ago in Lear, “Thy life is a miracle. Speak yet again.”

Okay. Here we go, then.

Cheers,

Michael

The slop layer - Blood in the Machine

2025-11-24T06:05:03.000Z

One of the more perplexing things about the AI bubble is how relatively little we have to show for it. Mostly, it’s chatbots, some coding automation, and slop. A lot of slop.

You can spend hours reading through eye-popping Nividia earnings reports and lengthy columns expounding on the transformative powers of the technology and analysts’ takes on what may be the biggest bubble of our generation. That’s to say nothing of the breathless proclamations of tech executives, of course, or the federal government’s own enthusiastic overtures. But then you flip on Saturday Night Live and the first sketch they run after the monologue reminds you that a lot of the general public’s experience of AI is actually more like the one depicted here:

That is, as slop. Encountering awful AI slop (and startups with skin-crawling pitches like ‘what if we use AI to reanimate dead family members’), is an experience universal enough that Glen Powell acting out Sora-esque output gets top billing at SNL. Slop has broken through; slop is everywhere; slop is mainstream.

And it’s not just that everyone, regardless of demographic, has watched a discomfiting AI-generated video or heard about a bad AI startup. AI slop is on TV ads, it’s in video games, it’s on the pop charts. There is a tangible, tactile, and unavoidable slop layer that has encrusted pop culture and much of modern life.

If the slop explosion began in earnest in 2023, with the unleashing of ChatGPT and Midjourney, and it reached critical mass in 2024, then now, in 2025, we’re seeing that slop hardening into the outer shells of our cultural institutions and social spheres, like a layer of so much automata-inflected sedimentary rock. And I’m not one to pass up a metaphor, so let’s go all in why don’t we. Remember middle school geology? The US Geological Survey notes that sedimentary rock is “formed from pre-existing rocks or,” like slop, “pieces of once-living organisms.” The USGS also helpfully notes that sedimentary rocks have “distinctive layering or bedding.” You know it when you see it.

Now, in 2025, whenever we go to read a blog, flip on the TV, stream music, or pick up a PS5 controller, we are likely to encounter the slop layer. This agglomeration of content living and dead, marked by a faintly unpleasant aesthetic homogeneity, that evokes in us a weary inability to discern what’s real and what’s not. We wade through this tide of automated mediocrities and the ethical breaches they represent and consider the credibility of its component parts. Whether we want to or not, and mostly we do not, we must engage the slop layer.

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A quick word before we go on: Instead of the usual entreaty to subscribe or to become a paid subscriber if you enjoy or find value from this work—which will continue to constitute oh 97% of my livelihood, and please do that if possible—I’m trying something new. That is, this is a sponsored post, from a good company offering a good service.

As you read this, or rather, immediately before you read this, when you were on Google or Facebook, browsing or shopping etc online, a host of mostly invisible companies were compiling data profiles of you. Today’s edition of BITM is sponsored by DeleteMe, whose raison d’etre 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 100 or so 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 we go.

The slop economy has been going full steam for a year or two now. In 2023, 404 Media’s Jason Koebler wrote in a report about the rise of AI content on Facebook that the “once-prophesized future where cheap, AI-generated trash content floods out the hard work of real humans is already here.” In 2024, declared that the slop era had arrived. Pumped out primarily by content farmers, web marketing opportunists and AI boosters, the flood of slop was, for a while, largely contained within social media platforms, email spam filters, and clickbait websites. Now, those walls are being breached.

OpenAI’s launch of the AI video generator Sora 2 made slop easier than ever to produce; major copyrights holders sounded the alarm. called it the AI Slop-pocalypse.

Then, last week, an AI-generated country music song by “Breaking Rust” notched the top spot on a(n admittedly obscure) Billboard chart (Digital Country Music Song Sales), and has racked up millions upon millions of views on Spotify.

It’s a generic, pretty terrible song that’s nonetheless not too out of step with the performatively masculine/hip hop-inflected/uncomfortably Imagine Dragon-adjacent trendlines in modern country pop. Once you hear it as slop, it’s impossible to unhear it as such. The top-voted comments on YouTube seem to agree:

The song gained popularity on Spotify, where it seems to have been recommended by the algorithm in Discover Weekly mixes, and where it was likely nodded along to in anonymity by millions who didn’t know or care who was behind the song. (This being a reminder that platform consolidation, and the social media networks and streaming services that want for cheap, voluminous content, produced the ideal conditions for generating the slop layer.) So it’s not like the song is an actual hit, it just blends unnervingly into the background, condensing the work of unnamed human recording artists into inoffensive, key-appropriate pap. It’s part of the slop layer.

The same week that Breaking Rust was racking up Spotify plays, gamers were discovering that the newest installment of the blockbuster video game franchise Call of Duty was loaded with AI-generated art. The games blog FRVR explains (and also cites my 2024 WIRED piece on AI in the gaming industry, thanks FRVR):

Call of Duty has already been criticized for its reliance on AI-generated artwork in the past. 2023’s Modern Warfare 3 included an AI-generated calling card in its $15 cosmetic Yokai Wrath bundle, and Black Ops 6—last year’s entry—was lambasted for its use of a generated image of a zombie Santa, which infamously had six fingers instead of five.
This year, the shame gloves are off, and Activision has pushed customers face-first into the up-chuck of machine-generated visuals. There is an extreme amount of AI artwork used within the base version of the game, despite the fact that last year’s Black Ops 6 made over $1 billion in its first 10 days on sale—the highest-grossing CoD game ever.

One interesting thing about the slop in the Call of Duty game is that it *doesn’t even bother to disguise itself as slop*. Some of it’s made in the Ghibilified style that is all but shorthand for AI-generated slop, as this gamer flagged:

A particularly exposed chunk of the slop layer right there. Meanwhile, the hit new game Arc Raiders used generative AI instead of voice actors, causing an outrage of its own.

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Speaking of outrage, artists and Disney fans were taken aback when CEO Bob Iger announced an incoming content deal that will allow Disney+ subscribers to mass produce their own Disneyified slop. Here’s the Hollywood Reporter:

“The other thing that we’re really excited about, that AI is going to give us the ability to do, is to provide users of Disney+ with a much more engaged experience, including the ability for them to create user-generated content and to consume user generated content — mostly short-form — from others,” Iger continued.

Nestled in that comment is a CEO’s dream; users paying corporations for the privilege of voluntarily producing cheap content that obviates the need to hire human artists to create more original works. The trade-off is of course that the vast the new Disney UGC will be pure slop, but so it goes.

Then there’s this AI-generated Coke ad, which began airing last week, too, and which the Verge’s Jess Weatherbed accurately described as a “sloppy eyesore.”

As Weatherbed noted, this is not Coca-Cola’s first rodeo in the slop arena, as it stirred controversy by making a bad AI-generated ad last year, too. And yet, these

blunders are seemingly worth the risk for Coca-Cola, with the company’s Chief Marketing Officer, Manolo Arroyo, telling The Wall Street Journal that its latest holiday campaign was cheaper and speedier to produce compared to traditional production. “Before, when we were doing the shooting and all the standard processes for a project, we would start a year in advance,” Arroyo told the publication. “Now, you can get it done in around a month.”

And therein we have the common denominator between all this slop, and I regret to inform you it’s not particularly revelatory: It’s cheap. It’s cheap as dirt to turn on the slop spigot to try to juice post views on Facebook or X or yes Substack, or to crank out a shitty robot country song. Every piece of Ghiblified video game art from a triple AI studio or AI-generated article on a media outlet’s website is the visual representation of slashed labor costs, the aesthetics of digital deskilling.

This is underlined by a study that found that if one trains a large language model exclusively on the output of professional writers, that model will be able to emulate the works of famous authors as well as said writers. The paper concludes that “the median fine-tuning and inference cost of $81 per author represents a dramatic 99.7% reduction compared to typical professional writer compensation.”

The slop layer would be offensive enough if it was limited to creative labor, but I’m afraid it coats even our social spaces now. What are chatbots but the automation of human interaction, or slop friends? Many people are now even channelling their sexual impulses through a particularly toxic brand of slop, as evidenced by the enormous and horrifying leak of user data from an erotic chatbot service that let its customers create deepfakes of celebrities, crushes, even their teachers. Others are being asked, a la Glen Powell to render AI-generated avatars of loved ones; slop memories.

The Atlantic writer Charlie Warzel recently described AI as “a mass delusion event,” noting the degree to which the technology has driven us to question more frequently whether something is real and what purpose it serves. And while it’s true that generative AI has been the purveyor of a great many delusions, many of them tragic, the broader and shallower effect may be a great cheapening. The slop layer is enshittification made total and constant.

It’s playing a Call of Duty sequel and staring at obviously AI art on a load screen, while your ChatGPT companion flatters you on an app on your phone and the statistical mean of a new country song autoplays on the speakers. It’s the replicated cultural artifacts, social interactions, and sexual fantasies all lathered onto reality, embedded with the telltale sediments of their plagiarism and automation.

This raises yet another question that feeds into the interminable AI bubble discourse: What if everyone gets sick of squirming? What if we cross a threshold where living in a perpetual, ambient uncanny valley produces a sustained backlash? It may even eventually become too obvious that the most ubiquitous export of the AI boom is a pervasive layer of slop that’s made everything look and feel worse, a feeling that could speed a downturn should investor’s bullish sentiment finally crack. But there’s a chance it doesn’t, and that is of course the fear. In the event that it does not, and this is the harder question, we’re all faced with asking how we might navigate, or confront, the slop layer that’s growing and hardening around us. Do we tolerate its creeping repugnance? Do we accept it as the latest encroachment of late technological capitalism? Or do we reject it?

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To that end, a couple notes and ideas for fighting/excavating the slop layer.

Fighting the slop Layer

Deana Igelsrud, the legislative & political advocate for the Concept Art Association, passes along word that a crucial hearing will be held for AB-412, proposed California legislation that would force AI companies to alert copyright holders when their works are used to train large language models, and give them the chance to opt out and a mechanism for

On December 8, 2025, the Assembly Privacy and Consumer Protection Committee and the Senate Judiciary Committee will be hosting a joint informational hearing on the topic of AI and Copyright at Stanford University. I’ll follow up on this email with an agenda as soon as it is finalized – in the meantime, some basic information is included below:
WHERE: Stanford University - Paul Brest Hall, 555 Salvatierra Walk, Stanford, CA 94305.
WHEN: Monday, December 8^th at 10 AM.
WHO: Artists, creatives, and copyright owners who want to make their voices heard.
Over the course of this hearing we will learn about AI and copyright from a variety of artists, academics, technical and legal experts, policymakers, and representatives from the tech industry. At the end of the hearing there will be an opportunity for members of the public to speak for 1-2 minutes each. If you’re passionate about these issues, we’d love to see you there. No registration is required ahead of the event.

Excavating the slop layer

Meanwhile, has an intriguing plan for excavating the slop layer, or at least helping to preserve the livelihoods of artists and creative workers it’s beginning to bury: A slop tax. I love it, check out the proposal here:

Heavy Machinery

The Slop Tax, a Brief Introduction

The following is a sneak peek into a larger project. I am looking for insights, feedback, and other contributions to support this idea. So in that way it’s a bit of teaser— a blueprint, if you will …

5 days ago · 34 likes · 8 comments · Mike Pepi

OK, that’s it for today. Thanks for reading everyone. Hammers up.

What Was ChatGPT? - Cybernetic Forests

2025-11-23T12:00:30.000Z

Three years after the launch of ChatGPT, we can finally speak in hindsight about what it was and how it came to be. Its meteoric rise shocked the world, gathering more users in less time than any product launch in history. But that specific moment was unlike any other history for other reasons: namely, it was one of the deadliest years for a global pandemic mostly associated with 2020. It was a period where the use of social media had peaked, with users largely abandoning algorithms that amplified divisive content as engagement bait.

To understand the meteoric rise and the shift in the tech industry, we should examine the context surrounding it. The collective experience of the COVID-19 pandemic has largely been erased or minimized from narratives of our political, economic and technological situation. In many ways, the collective attention, and fear, has shifted from a conversation about the embodied concerns of a contagious, murderous disease to a collective fascination and horror with the unembodied abstraction of “artificial intelligence.”

Might the absence of social information in our lives — and the rise of a deeply politicized and hostile political environment on social media — contributed to the collective desire for something so simple as a chat?

Chatting Through the Window

Generative AI entered the public imagination with the 2019 release of GPT 2, with OpenAI's limited release to researchers over “misinformation concerns” foreshadowed the hype that we'd see with every model ever-after.

By the time GPT 3 was introduced in 2020, the press responded to the model with waves of fear and enthusiasm. The Verge called it “auto-complete,” but also suggested it was “the first step” toward creating artificial general intelligence, or AGI. The Facebook and SpaceX investor Delian Asparouhov called it “a race car for the mind,” comparing it to “10,000 PhDs that are willing to converse with you,” but also noted that it was, again, fundamentally auto-complete: “a context-based generative AI.”

ChatGPT shifted the user’s relationship to text, moving the prompt from a 'piece of writing for the model to finish' to a 'question calling for an answer'.

By the 2022 release of GPT 3.5, it was clearly not a revolution in language models, squeaking by with scaling improvements to the then two-year-old GPT 3. When ChatGPT was launched on November 30, 2022, it offered a key interface tweak to GPT 3.5. By pairing GPT 3.5 with it's unreleased 'Superassistant' chat interface and training it on dialogue, OpenAI transformed a tool built for auto-completion into one that appeared to answer questions. The prompt no longer read as text to be extended but as a message awaiting a reply—though the underlying process hadn’t changed at all. ChatGPT shifted the user’s relationship to text, moving the prompt from a 'piece of writing for the model to finish' to a 'question calling for an answer'.

OpenAI claims ChatGPT captured 100 million users in two months, making it one of the fastest software adoption stories in history. With it came a kind of breathlessness: In The New York Times, Kevin Roose referred to it as “a highly capable linguistic superbrain,” while The Guardian predicted “[p]rofessors, programmers and journalists could all be out of a job in just a few years.” The hype cycle had begun.

In two short months, ChatGPT had realigned the entire orientation of the tech industry.

In response, Alphabet would fold Google Brain into DeepMind and pivot to applied research, a move designed “to ensure the bold and responsible development of general AI,” Alphabet CEO Sundar Pichai announced in a 2023 blog post. DeepMind’s lead scientist, Geoffrey Hinton, would quit two weeks later to warn the world of the risks of superintelligent AI.

At Meta, the “general intelligence” fever supplanted the much-ridiculed “metaverse” strategy that led the company to rename itself just 18 months earlier. Days before ChatGPT launched, the company was forced to take down its Galactica model demo after 72 hours of generating fake scientific papers. As Alphabet announced its AI plans, Meta CEO Mark Zuckerberg would fire 10,000 employees to make room for a pivot to AI in what he called “our year of efficiency.”

In two short months, ChatGPT had realigned the entire orientation of the tech industry.

Imagining a Mind

The Large Language Model crammed into a chat interface transcended a successful tech launch and, in Silicon Valley, confirmed the mysticism surrounding the AI project. The interface suggests a conversation, and many imagined someone else on the other end of the line. Months before ChatGPT was launched, another chatbot gave rise to similar problems: the mainstream media began reporting on Blake Lamoine, a Google employee who became convinced that his conversations with Google’s internal chatbot, LaMDA, had shown evidence of sentient thought. He was soon fired.

At OpenAI, Ilya Sutskever (then OpenAI’s chief scientist) was having a similar reaction to the still-secretive GPT 4. Karen Hao, in Empire of AI, writes that before the launch of ChatGPT, Sutskever and Geoffrey Hinton discussed the imminent arrival of artificial general intelligence based on GPT 4’s performance. (Hinton has said he believes chatbots are capable of subjective experiences).

“We now have machines that can mindlessly generate words,” linguist Emily Bender told the Washington Post at the time, “but we haven’t learned how to stop imagining a mind behind them.”

According to Hao’s reporting on OpenAI, nobody anticipated ChatGPT would become the success that it was. Their focus was on scaling up models to meet their standards of “general intelligence.” But ChatGPT’s sweep of the world suggests that these models did not need to be intelligent to find a user base, they needed to simulate a social experience. Language generated in the absence of a mind is like Diet Coke: a temporary satiation, a substitution for actual nutrients. But Diet Coke sells, and ChatGPT reached 100 million users in under two months. As of November 2025, that number sits at 800 million users per week.

The context of those early months, the starting point of this optimization loop we've been trapped in ever since, can tell us a lot.

So Much Information That’s Missing

In November of 2022, the world was emerging from an ad hoc social experiment. Ad hoc social isolation was still in effect, masking was common, and we'd had a false start on a return to normalcy that summer only to be met with a deadly Omicron wave. That year saw some of the deadliest days of the Covid-19 epidemic.

There is a deep reluctance to acknowledge the radical difference between the world that went into lockdown and the world that came out of it. Tech companies became accidental infrastructure: Zoom was school, DoorDash was a grocery store, Animal Crossing was the bar and Netflix was the cinema. None of them remotely compensated for the sudden deconstruction of the social world that sustains the ongoing story we call our lives.

There is a deep reluctance to acknowledge the radical difference between the world that went into lockdown and the world that came out of it.

An oral history of the COVID-19 pandemic from 2023 in The New York Times, reminds us of what the world felt like:

“A clinical psychologist near Union Square, reflecting on the transition to remote therapy, says: ‘I miss seeing the shadows that my patients cast onto the floor of my office. ...And I miss kind of having some sense of where they were by the smells that come in the door.’ He goes on, ‘I just feel like there’s so much information that’s missing.’ A contact tracer explains, ‘I was honestly surprised with how many people are just happy to get to talk on the phone’ — even to someone calling to alert them that they might have a deadly disease.”

COVID-19 was a mass traumatic event that increased symptoms of post-traumatic stress disorder across the world. In Spain, a survey found that “a quarter of the participants have reported symptoms of depression (27.5%), anxiety (26.9%) and stress (26.5%), and as the time spent in lockdown has progressed, psychological symptoms have risen.” Nearly a third of US adults showed evidence of “elevated depression” in 2022, an increase over the previous year, especially concentrated in the least wealthy.

It's possible that the chatbot is one of the lasting transformations of our social life from the pandemic. The pivot to frame Large Language Models as intelligent may just blind us to how most users really see them: as social.

Increased social media and forum posting is understood as a compensatory behavior among those who feel lonely or depressed. Other studies have confirmed that talking to chatbots makes us feel better, albeit temporarily, about negative emotions: they can provide “virtual social interactions” and simulate “a level of empathetic responsiveness” which, through a lower risk of rejection and judgment, can feel safer than taking risks with real people.

A recent survey has shown that nine percent of LLM users reported using them for “casual conversation and companionship,” while 25% said their chatbot “cheers them up” and 22% say the models seems to express empathy. A Washington Post review of leaked ChatGPT chats found that “10 percent of the chats appear to show people talking to the chatbot about their emotions,” though the data they analyzed was limited to publicly shared conversations. If these statistics held up, however, that would mean 72 million people use ChatGPT for social interaction and 200 million for emotional comfort (“cheering up”).

This matters, because the design of Large Language Models operates as a feedback loop with the user base. Every word a commercial LLM selects is a result of a calibration process, where responses are tuned to human feedback. Because of the scale of use cases and the interconnected nature of these models, tuning responses to fit one kind of conversation style ("helpful assistant") has ripple effects throughout the model.

But what are we tuning to? Models risk become optimized to better perform at what people already use them for. This creates a feedback loop where interactions its users desire become more desirable, causing more users to engage, creating more interactions from which to optimize.

ChatGPT may have changed the world,
but the world had already changed.

What if ChatGPT came just six years before, into a different social context? Would it be optimized to different use cases? Let's not overstate the pandemic as the sole factor of how AI has come to be defined, but let's not ignore it, either. ChatGPT may have changed the world, but the world had already changed. The chatbots took what we needed most at that historical moment and optimized these machines to give it to us, kicking off a feedback loop that continues to define it.

It seems people want to talk to someone, and yet, to be alone. Here's an new ad for Amazon's Alexa, showing off the way these machines are optimized for social isolation.

What Was ChatGPT?

What was ChatGPT? Perhaps it was a side effect of the coronavirus: a technology that emerged against an ongoing denial of collective trauma, adapted to a historic moment in ways that persist beyond it. ChatGPT came into a world where proximity to others was correlated with the risk of death, as online connection was besieged by hostile political polarization, when everything was unmoored in ways no language could capture. It emerged at a time when loneliness felt essential to survival.

ChatGPT emerged at a time when loneliness
felt essential to survival.

What captured our imaginations during that time, in response to the failure of language to describe our experiences, was ChatGPT. With no inner life, ChatGPT could relentlessly pave over the failure of words to describe our own anxieties. Its bursts of conversational text matched the limits of anxious attention spans. It shifted when we got bored, and we owed it no apologies. It agreed with any position we took. In our lapses of executive function, it could create a plausible bare minimum checklist for us to get through the day.

ChatGPT is a stereo turned to the max of language: full of distortion, but clarity is not the point.

With the rising volume of slop — or buttons to conjure it — painted over every digital surface, I'm reminded of my own pandemic coping strategy: blasting music to drown out the silence. ChatGPT is a stereo turned to the max of language: full of distortion, but clarity is not the point. The point is to create a little space where we don't need to think.

Trump and big tech take two more stabs at ending AI democracy - Blood in the Machine

2025-11-20T23:33:10.000Z

Big tech’s ploy to halt state-level AI lawmaking is back. Silicon Valley’s allies in the Trump administration are pushing legislators to jam language that would prevent states from passing AI laws into the (otherwise unrelated) national defense authorization bill, and the president has drafted an executive order with the aim, as its title declares, of “ELIMINATING STATE LAW OBSTRUCTION OF NATIONAL AI POLICY.”

The proposed EO, which leaked this week, would create a framework for penalizing US states that pass, or have already passed AI laws, mostly by threatening litigation and the withholding of federal broadband funds. It would also serve to concentrate power in the hands of Trump’s AI and Crypto Czar, the venture capitalist and PayPal mafioso David Sacks—further fusing the Trump administration to Silicon Valley’s executive leadership, and entrenching a modern tech oligarchy.

Before we get to it, a quick note that this work is made possible by readers who chip in $6 a month—an amount equivalent to a decent latte or beer'—or $60 a year. I’m able to keep the vast majority of this reporting and writing free and open to all thanks to you god-tier humans who are paid supporters. If you’re a regular reader, and you’re able, consider joining them so I can continue to do this work. Many thanks, and hammers up.

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Readers of this website knew it would only be a matter of time before this push to roll back state AI laws was renewed.

After all, earlier this year, with its key allies firmly embedded in the Trump administration, major Silicon Valley AI companies undertook a hard lobbying push to pass a ban on state level AI legislation in the omnibus budget bill. That effort was documented in detail in these pages, and it ultimately came up just short; as in *one* vote short, when Tennessee senator Marsha Blackburn voted nay on the amendment to protect her state’s regulation of AI in the Nashville music industry.

The new effort is once again premised on sliding language stopping state level AI lawmaking into an unrelated bill, which should give you an idea of just how unpopular and contentious this all is (even within the GOP caucus, more on that in a second).

Here’s Bloomberg:

Billionaire GOP donors Marc Andreessen and Ben Horowitz have been calling Republican leaders to urge them to include the AI regulation preemption language in the defense bill, the people said. Alphabet Inc.’s Google, Meta Platforms Inc. and OpenAI LLC also have been lobbying the federal government to block state AI regulations…
Senate Majority Leader John Thune confirmed Wednesday that Republican leaders are trying to include the preemption in the defense bill. He said negotiators are trying to work out a limitation on state AI regulation that still “is consistent with ensuring that states have some role in terms of how those companies operate in their states.”
House and Senate leaders so far haven’t coalesced around a specific AI provision for the defense legislation and multiple proposals are circulating, said people familiar with the matter. People who have been speaking with lawmakers and White House officials described the situation as fluid… Sacks has been holding in-person meetings with Republican lawmakers to hash out language that could make it through the House and Senate, according to the people.

This is seen as the GOP’s last chance this year to get a bill like this across the finish line, and perhaps their best chance period, as next year begins a Congressional election cycle that will politically complicate the vote. This remains, after all, a remarkably and unambiguously antidemocratic project, one that’s anathema to the spirit of federalism many Republicans claim to cherish.

Which is, in fact, why there is vocal opposition from figures like Marjorie Taylor Greene and Mike Davis.

“There will be a tremendous conservative grassroots backlash against Republicans who sell out their constituents to help big tech,” GOP congressman and Trump ally Mike Davis told Bloomberg. “If big tech wants federal preemption, they need to protect the four C’s: conservatives, children, communities and creators. Otherwise, this is simply AI amnesty.”

In other words, the state AI law ban taking shape is ominous and darkly reflective of this technopolitical moment, but its path to passage is far from assured. Still, given that the last go round came down to a single vote, and surely Blackburn’s now-more-prepared colleagues can promise her some pork/exemptions, I wouldn’t bet against it.

ELIMINATING STATE LAW OBSTRUCTION OF NATIONAL AI POLICY

1.39MB ∙ PDF file

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As for the executive order, which you can read in full at the link above, it continues the Trump admin’s designation of AI as a concern of national security first and foremost (“our national security demands that we win this race”) and proceeds on those grounds. Once again, the arch goal is not economic prosperity, or jobs, or even innovation—it’s dominance. “It is the policy of the United States to sustain and enhance America‘s global AI dominance through a minimally burdensome, uniform national policy framework for AI,” as the EO puts it.

From there, the EO chiefly does three things:

Establishes an “AI Litigation Task Force” whose “sole responsibility” is to challenge state AI laws. This is pretty wild, if dubiously efficacious. It’s basically an open threat to use federal resources to harangue states that pass AI laws and get them tied up in court, as a means of deterrence.
Threatens to withhold federal funding for broadband in states that have AI laws that do not pass what the EO calls an “Evaluation of Onerous State AI Laws.” Specifically, the order is concerned with laws that “require AI models to alter their truthful outputs” aka what the administration considers anti-discrimination laws, in line with this summer’s earlier Anti-woke AI executive order. But, you might ask, who is to serve as the arbiter of what qualifies as “truthful output”? That brings us to:
Anoints David Sacks, Trump’s AI and Crypto Czar as a key intermediary for arbitrating all of the above efforts. Which effectively means that a venture capitalist and Silicon Valley power broker will officially hold even more sway in deciding which states and state lawmakers to target and even punish for embarking on efforts to regulate AI.

In short, since executive orders are legally limited in what they can actually do, this essentially serves as official notice that the Trump administration, taking marching orders direct from Silicon Valley VCs and AI executives, will sue, pester, penalize, and attempt to withhold funding wherever possible if states pass AI laws. It’s intended to induce a chilling effect, in other words.

It’s not clear how well it will work. Plenty of blue state lawmakers may relish the chance to challenge Trump as his administration tries to meddle in the democratic process, especially in an arena as inflammatory as AI. What remains notable to me about all of this is how willing Silicon Valley elites are to *openly* engage in this agenda. On the vibe front, we’ve gone from “we’re the key allies of Obama’s hope and change project” to “we’ll publicly ally with Trump to stymie the democratic process if it saves us from complying with a few regulations” in less than a generation.

There’s little need for aspirational messaging anymore, not when Silicon Valley enjoys such direct access to the levers of power. To that end, little underscores the status of this new nexus better than the fact that the same week that Trumpworld made public its plans to help the tech industry clear out the regulatory weeds, oh half of the beneficiaries of that effort were all at the White House attending a dinner for the Saudi Crown Prince Mohammed bin Salman.

That’s Trump’s AI czar and noted VC David Sacks, OpenAI’s Greg Brockman, Elon Musk, and Nvidia CEO Jensen Huang, at the White House this week, for the Saudi investment forum. In context of the EO described above, perhaps it serves as a handy visual cue. Let’s say California passes a law that says you can’t use AI tools to, I don’t know, automate a hiring process unless they’re shown to be nondiscriminatory. (That’s just hypothetical because Gavin Newsom vetoed the one that did that, anyway.) Brockman or Musk might turn to Sacks and say, hey, OpenAI and XAI have enterprise products that do that, and everyone knows nondiscriminatory is code for ‘woke’, can you have the AI Litigation Task Force take a look at that? And thus these guys have their very own (again, dubiously efficacious) framework for lodging complaints, exerting their will, and harassing states and lawmakers they don’t like.

Meanwhile, OpenAI is talking openly about the federal government “backstopping” its investment in AI data center infrastructure as the bubble continues to inflate, the US owns a stake in Intel, and so on; the Silicon Valley-state nexus draws tighter still, AI law bans or not.

So, as the year draws to a close, it’s on much the same note that it started—with an emboldened tech oligarchy quite comfortable advancing openly antidemocratic aims and demonstrating unambiguous allegiance to the Trump administration, in exchange for a shot at enacting a deregulatory regime it once thought beyond the scope its wildest dreams. This time, it might just get it.

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Okay okay that’s it for today. Forgive any typos or less-than-stellar sentences. I’ve got a decently nasty cold that has once again waylaid some of my more ambitious writing and reporting plans. But provided I rest up properly, I’ll have another piece up on Sunday, and be back in action at full speed next week. Thanks all, take it easy out there.

Guillermo del Toro's 'Frankenstein' gets the monster right for the age of AI - Blood in the Machine

2025-11-15T04:29:31.000Z

Greetings from soggy Los Angeles -

I had big plans for this week, including writing a dispatch on the New Luddism conference at Columbia and an excellent tech-smashing tribunal in Brooklyn. I’d also hoped to finish an essay on the scourge of AI companions but that went long, and events I’ll discuss at greater length in the future intervened. So, I’m a bit behind schedule. I did, however, catch Guillermo del Toro’s new Frankenstein film, and had some thoughts I wanted to share on that before it exited the Discourse. (For a brief interview I did with El Pais about the subject, see here.)

As always, thanks for reading, and a quick note that this work is 100% made possible by supporters who chip in $6 a month or $60 a year. If you’re a regular reader, and this king of writing/reporting/analysis is valuable to you, please consider upgrading to a paid subscription so I can do more of it. Much appreciated, and thanks everyone. Much more soon.

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Frankenstein, dir. Guillermo del Toro

Victor Frankenstein is the ur-tech bro. In Shelley’s 1818 novel, he’s ambitious, preening, naive, and reckless. He’s conspicuously into science. He reads some books and thinks he can reorder the universe for the benefit of his own ego. He does the Gothic version of move fast and break things. Then he ditches his failed startup, moves on, and refuses to take responsibility for the mess.

His creation, meanwhile, is dangerous and complex. He’s intelligent, lost, and demands companionship and acceptance above all. One way to read the story is as an expression of Mary Shelley’s (somewhat patronizing) view of the relationship between the 19th century industrialist and the working people at his whim; the bold, rash, and cruel Victor standing in for the capitalists, and the beseeching monster asking only for the necessary support to get by. There’s some speculation that, given that Shelley’s crew (Lord Byron and Percy Shelley) at the time of its authorship were fans, Frankenstein was inspired by Luddism.

In this read of Frankenstein, that working class is intelligent and justifiably aggrieved; it wages a campaign of violence only when out of all other options. Victor, meanwhile, is obsessed with ambition and personal profit, and oblivious to those whom his actions might hurt.

When I was researching and writing Blood in the Machine: The Book, which includes chapters on Shelley and Byron, I reread the original novel and watched a bunch of Frankenstein and Frankenstein-inspired films. I was honestly a little surprised by how cutting the novel remained deep into the 21st century. Especially in its rendering of Victor, through which Shelley diagnosed and skewered an enduring strain of male ego, one inclined to turn to technology to seek and sublimate power.

I was also a little struck by how dumbed-down subsequent depictions of Frankenstein had become. Starting with Boris Karloff’s depiction of the monster in 1931, he’s been etched in pop culture as brutish and dull; a simple giant spurned by his creator who knows not what destruction he wreaks. The cautionary tale element is still omnipresent, but the critique is dulled.

I couldn’t help but notice that the hollowing out of the original critique inherent in Frankenstein—the monster was not a dangerous moron or a horrible mistake, but an intelligent entity Victor could have chosen to acknowledge, assist, and coexist with; even love—mirrored to a degree the dumbing down of the meaning of ‘Luddite’. The real Luddites were feared by power in their day, not mocked, were quite morally justified in their grievances against industrialists and elites. Like the monster, they were strategic in their campaign against their malefactor, not brutish and reactionary.

So! Needless to say, I was curious to see what Guillermo del Toro would do with his much-anticipated and apparently very long gestating depiction. Honestly, I didn’t expect to love his Frankenstein. As much as I admire his originality and visual composition, del Toro’s films can veer a bit too far towards the sentimental for my tastes. And the new Frankenstein is plenty sentimental. Despite this, I’m pleased to say it whips. I think it’s officially my favorite del Toro film—yes, over Pan’s Labyrinth, even—and it centers a beautifully melodramatic critique of the charismatic but morally bankrupt innovator at its core. It’s not perfect; there are a few key shortcomings, which we’ll get to in a minute. But it does effectively render the feckless, pathetic founder as an enduring and enduringly dangerous archetype. It’s a gothic Frankenstein ripe for the age of AI.

The film opens, as Shelley’s book does, in the Arctic. I can’t recall any other film adaptation borrowing the same framing device, in which Victor relays his tale to an Arctic sea captain who’s indulging his own headstrong ambitions by driving his vessel deeper into deadly frostbitten conditions, putting his men at risk for the sake of vainglory. The framing works nicely, both as a plot device and with its stark, frozen visuals that remind us that this struggle—inaugurated by men with reckless ambition, influence, and capital, and waged by those they oppress—risks leading us somewhere resembling the end of the world.

Guillermo del Toro has moved the setting from the original of 1818 forward a half century or so, apparently to incorporate more fully steampunk tech aesthetics and the Crimean War, and he embellishes a Freudian backstory about Victor’s upbringing—he’s obsessed with his beloved ill-fated mother and abused by his stern physician father—and a b-plot about his infatuation with his brother’s fiancé, but the story remains anchored by Shelley’s vision.

[Some spoilers incoming from here on out, so heads up.]

There’s a great scene early on where Victor, played by Oscar Isaac in brooding startup pitch mode, shows off his progress in animating a corpse before an academic court. He’s at a hearing to defend his controversial academic activities, and he delights in the blasphemy and the provocation, but can’t really articulate a sound reason for why he’s doing any of this, except, of course, because he can. He drops out, naturally, (expelled, really) and is promised limitless funding by, in a nice touch from del Toro, a war profiteer who wants to live forever. (Frankenstein’s answer to Peter Thiel, if you will.)

Victor sets out gathering corpses, not, as in Shelley’s version, from graveyards, but battlefields littered with the newly dead, and from the gallows, where—another great touch here—he assesses potential body part donors before they’ve even been hung. These scenes can’t help but evince del Toro’s attitude towards such men, callously willing to cut the living down or disregard their humanity entirely for the sake of their ambition. It’s easy to see parallels here to the current crop of Frankensteins; AI executives willing to harvest the works of the living and the dead, uncaring as to the creators’ concern or consent, to serve their ends. It’s perhaps hardly surprising to see such a critique from a director who uttered “Fuck AI” into a live mic at a press event for the film, but it works.

The making-the-monster scenes that follow are some of the most gruesome fun in the film; the set design is great, and the lightning harvesting technology feels like a nod to the “It’s Alive” stuff from the pulpier movies. When del Toro’s Victor finally conjures the monster, he doesn’t immediately flee in terror, as Shelley’s Victor does. Instead, he treats it cruelly (as his father treated him), whipping it, berating it, and dismissing it as a failure before attempting to destroy it altogether. This section, and the following, in which the monster, played with shambling grace by Jacob Elordi, escapes and discovers the human world for himself, are the heart of the film.

If we’re following the materialist interpretation of Frankenstein, instead of fleeing in disgust the working classes shaped by his creation, the new Victor attempts to punish it, even destroy it outright. If you really wanted to go ham on the AI metaphor, you could slot in Sam Altman, Dario Amodei, or Elon Musk here, promising the rise of AGI that will replace labor altogether.

The last act can’t quite manage to keep up the highs of the first two. The monster’s entreaty for a companion, Victor’s denial, and the vows of vengeance are cycled through quickly enough to feel rushed, especially given that those events take up the bulk of the book. (This is the rare two and a half hour film I would have gladly watched another half hour of.) And, as Defector’s Kelsey McKinney points out, the film’s omission of some crucial plot points—when the monster vengefully kills everyone Victor loves, for instance—sands the monster down into a more unambiguously sympathetic character. (Victor’s brother, who’s accidentally killed by the monster in del Toro’s film, does, in another blunt but effective scene, get to underscore the point that Victor is the real monster.)

But the only real letdown for me was the end. Shelley’s final chapter is savage. Victor Frankenstein is egoistic and headstrong to the very end; he encourages the sea captain to plow on heedlessly through the ice, crew be damned, and vows to hunt the monster to the death. He dies permanently curdled and scarred by ambition. del Toro somewhat inexplicably lets Victor off the hook; he questions the motives of the headstrong sea captain, and, when faced with the monster, apologizes and repents. The monster forgives him, uttering “Perhaps now, we can both be human.” Victor hasn’t earned this at all. He’s beaten his creation, attempted to murder it, abandoned it, scorned it, and accidentally killed the only living human who showed it any understanding.

I understand the urge to end the film on a redemptive note, to perhaps show the Altmans and Musks that hope for grace is still out there. But for someone who told NPR he’d “rather die” than use generative AI, for a film whose tagline, “Only Monsters Play God” is broadcast all over the place, it feels a bit like a copout. Still, it’s a knives sharp Frankenstein fit for the OpenAI era, and its inherent, genre-defining tech criticism is very much intact.

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THE CRITICAL AI REPORT + EXTRA STUFF

The infamous n+1 Bookmatch quiz is live again, and I just gave it a whirl. It’s a great way to support the publication; I’m particularly looking forward to reading Baluta and Paris Noir.

Rare Good AI News Dept.

It does happen, occasionally, and the offices of BITM Inc are obliged to report on it when it does. Good news for artists on the AI front:

How to dis-enshittify the world, with Cory Doctorow - Blood in the Machine

2025-11-10T02:21:26.000Z

Does Cory Doctorow even need an introduction at this point? If you spend any amount of time at all online, then you’ve encountered his work, his ideas, his words. But the ultra-prolific science fiction writer, digital rights activist, and coiner of the “Enshittification” verbiage that’s become universal shorthand for the degradation of the internet (and, to an extent, everything else), has been especially ubiquitous lately. His book-length treatment of the Enshittification thesis was just published by FSG last month, and he’s been on the press tour war path.

And good! “Enshittification” is vintage Doctorow—it’s sharp, frisky, freewheeling, and erudite; call it elevated, book-length blogging, perhaps. It’s also going to be the book I recommend to folks interested in getting into Cory’s nonfiction work; it so ably ties together the many strands of his thought and his various crusades into a manifesto of sorts. And, naturally, it persuasively makes the case for how big tech and its monopolistic platforms have conquered the internet, systematically siphoned it of vitality and utility to placate shareholders, and left an enshittified husk of what the web, and the world, ought to be, in its wake.

Enshittification: Why Everything Suddenly Got Worse and What to Do About It, by Cory Doctorow. MCD x FSG Books, 2025.

So naturally, I wanted to have Cory on Blood in the Machine: The Podcast to discuss it all. Cory has given approximately 4,000 interviews for this book and topic at this point (I recommend the New York Times mag profile for a look at his life and career, as well as his backyard, where he throws some great parties). So I thought I’d pick his brain specifically on how he thinks workers—tech workers and otherwise—can help turn the tides of enshittification. My instinct was to call this “deshittifying” the web, but Cory prefers “dis-enshittification”, which, fair enough. Regardless, we cover a lot of fertile ground, and field some good questions and comments from the chat (thanks to everyone who popped in when we were live).

Cory and I don’t agree on everything—copyright law in particular is a point of contention—but there is a lot of food for thought here, if I do say so myself. We cover why tech workers are both woefully under-organized and potentially powerful vectors for change, AI, sectoral bargaining, and more. I always have a good time chatting with Cory; I hope you enjoy our conversation, too.

Which reminds me: If you do enjoy chats and recordings like this, consider chipping in a few bucks a month so I can continue doing them. It takes time and energy to research and write these posts, to schedule interviews, and to find the adequate angle at which to prop up my phone on a stack of books on my desk so I can record the thing. Thanks to all those who already to pitch in; you make the whole BLOOD project possible.

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Man, this was a busy week. On top of my chat with Cory, I also joined host Alexis Madrigal and fellow tech writer Charlie Warzel on KQED’s Forum; you can listen to that here. I also joined Lauren Goode and Michael Calore on WIRED’s Uncanny Valley podcast, to discuss the AI bubble piece I wrote for the magazine last month. I also spoke with CBC’s Nora Young about the invisible labor that makes AI systems possible; that article is out here.

Okay! That should bring us about up to speed. Hope everyone had a solid weekend and maybe even found a little respite. I, for one, I might add, had a fantastic weekend. The conference on New Luddism at Columbnia was a smashing success. I’ll have more to share soon, but the event brought together academics, journalists, labor organizers, policy heads, and student activists. I met so many folks doing great work in the space, the conversations were stimulating, and it was quite possible, for a few hours, to glimpse a future where our systems are no longer fueled by relentless worker exploitation and surveillance, or beholden to big tech and the oligarchs that operate it. I’ll write a longer debrief on all of the above soon, but for now: great stuff. A shout to the organizers for knocking it out of the park.

On Saturday, Paris Marx, Edward Ongweso Jr, Jathan Sadowski and I held a Luddite Tribunal before an absolutely packed house at the Starr Bar in Brooklyn. More on that before long, too, but it was just such good fun. It was kind of like the conference, in fact, just with more hammers. Thanks so much to everyone who came out, joined the chaos, and brought tech to submit for judgement.

I’ve got a lot of things cooking for this week, so I’ll end here for now. More soon, thanks for reading—and hammers up.

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Critical takes on tech - BlogFlock

The best books, films and TV about AI + tech in 2025 - Blood in the Machine

The best nonfiction books on tech of 2025

Other notable and good books, about tech or otherwise

So many good books

TV

Black Mirror

Alien: Earth

Pluribus

The Chair Company

Film

The Shrouds

Mickey 17

Frankenstein

Companion

Bonus: Best anti-AI death metal album

There has to be a way - Blood in the Machine

Netflix can’t be allowed to buy Warner Discovery - Disconnect

The false promise of streaming

It didn’t start with Netflix

Where we go next

Manufactured Inevitability and the Need for Courage - The Convivial Society

Some Things I Did in 2025 - Cybernetic Forests

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Tracking the AI Coup

AI Myths

Art & Other Works

Signal to Noise

Human Movie

Noisy Joints

Sound

This Newsletter

Sign up for Cybernetic Forests

"I was forced to use AI until the day I was laid off." Copywriters reveal how AI has decimated their industry - Blood in the Machine

They let go of the all the freelancers and used AI to replace us

I was forced to use AI until the day I was laid off

I had to close my business after my client started using AI

We had a staff of 8 people and made about $600,000. This year we made less than $10k

My hours have been cut from nearly full time to 4-5 a month

We learned our work had been used to train LLMs and our jobs were outsourced to India

Coworkers told me to my face that AI could and maybe should be doing all my work

I’m a copywriter by trade. These days I do very little

I did “adapt or die” using AI, but I’m still in a precarious position

The agency was begging me to take on more work. Then it had nothing for me

My biggest client replaced me with a custom GPT. They surely trained it using my work

A 'code red' for AI - Blood in the Machine

What I Read About AI in 2025 - Cybernetic Forests

From AGI to Workslop

AGI

Bias

Blackmail

Clankers

Cognitive Offloading

Conspiracies

Creativity

DOGE & the AI Coup

Education

Fascism

Hallucinations (aka Wrongness)

History

Hubris

Hype

Infrastructure

Language

Literacy

Reasoning

Sciences

Summarization

Surveillance

Sycophantic AI

Sycophancy and Suicide

System Prompts

Woke AI

Workslop

That's it, everyone! Happy New Year. More to come in 2026.

Journalists win a key battle over AI in the newsroom - Blood in the Machine

HOUSEKEEPING:

AI RESISTANCE ACTIONS:

A CALL FOR ARTISTS TO SUPPORT THE AI COPYRIGHT TRANSPARENCY ACT

A DELETE SPOTIFY EVENT IN NEW YORK CITY

That's it, everyone! Happy New Year.
More to come in 2026.