Critical takes on tech - BlogFlock

OpenAI and Google's dark new campaign to dismantle artists' protections - Blood in the Machine

2025-03-15T05:57:05.000Z

Greetings all,

So I spent much of the week traveling, and the rest of it sick. But I’m back from a long and good and productive SXSW, where I did a featured talk with the great crypto skeptic Molly White, a chat at the LightHouse about generative AI and labor, and a talk with the 404 Media folks about AI slop at the Fediverse House. If video for any of those talks surfaces, I’ll share them. I also wrote a big and probably overlong response to all the AGI talk going on right now, but given the exhaustion and the brian fog I figured I’d wait to give the thing an edit; look for that early next week.

Thanks as always to everyone who supports this work—you alone make this writing, reporting, and research possible. If you’d like to help ensure I can keep at it, please consider subscribing for $6 a month; a cheap beer or a higher end cup of coffee. Thanks again.

Subscribe now

One of the biggest hurdles to generative AI’s dominance—and one of working artists’, writers’, and creators’ only tools to protect their livelihoods from its creep—is copyright law. And the two biggest AI companies in Silicon Valley just took a big, well-calculated swing aimed directly at breaking it down this week.

The Trump administration is currently soliciting public comment on its AI Action Plan, whose aim is to “sustain and enhance America’s global AI dominance.” OpenAI and Google cannily took the opportunity to try to get the Trump admin to help them remove one of the biggest albatrosses from their necks.

Image: elizal, via Flickr. CC BY SA 2.0

Along with proposing that Trump adopt a hands-off regulatory approach and implement policy that promotes the export of American AI systems, OpenAI proposed that the administration officially enshrine AI companies’ practice of using copyrighted works in their training data as fair use. Right now, the legality of that practice is being hotly debated in the courts, and artists, authors, and journalists have sued the AI firms for ingesting their data, using it to train AI models, and producing commercial output with it—all without the rights holders’ consent or compensation.

Last month, Thomson Reuters won the first major copyright victory against AI companies—though notably not generative AI firms, and the lawsuit was filed before the rise of ChatGPT—on the grounds that the firm violated fair use laws. The output of the AI models competes with the materials it was trained on, the judge found—a similar contention that is made by claimants like the New York Times in its case against OpenAI.

Meanwhile, an ongoing class action lawsuit brought by artists including Karla Ortiz—which AI firms had pressed to get dismissed—was allowed to go to discovery. The AI firms certainly hoped the case wouldn’t make it that far, and as of now they face a real possibility that their practices violate current copyright law.

Last year, the artists—those organizing against the use of AI in their workplaces, and those waging the class action lawsuits against the AI giants—were gaining ground. Now all that is at risk of being wiped away.

Which is why OpenAI is going scorched Earth on the matter, and appealing to Trump and Vance’s freshly imperialist approach to AI—touting the need to secure US AI dominance at all costs, and casting China as a foe; pointing to the widely discussed DeepSeek in the process.

In its lengthy proposal document, OpenAI argues that, “if the [People’s Republic of China]’s developers have unfettered access to data and American companies are left without fair use access, the race for AI is effectively over. America loses.”

OpenAI is certainly reading the room here—this is exactly the kind of rhetoric the Trump administration has been embracing around AI. A month ago, in his first foreign policy speech as vice president, JD Vance declared that an age of American dominance in AI was beginning, that safety talk would no longer be a concern, and that nations had a choice; whether to partner with the US, or with China.

And here’s the language in the Trump admin’s Action plan:

The AI Action Plan will define priority policy actions to enhance America’s position as an AI powerhouse and prevent unnecessarily burdensome requirements from hindering private sector innovation. With the right governmental policies, continued U.S. AI leadership will promote human flourishing, economic competitiveness, and national security.

OpenAI is using that framework as a means of advancing its case for killing creators’ copyright protections—it’s a shrewd and disturbing move, and one that’s designed to solicit the approval of the Trump admin’s hawkish approach to AI.

Google, for its part, isn’t quite as aggressive; it only mentions China twice in its own lengthy proposal document, but does make sure to name-check Vance and his Paris speech. Its first ask is for energy policy that ensures data centers have ample supply, but Google too seeks to end AI’s copyright complications.

From its proposal:

Balanced copyright rules, such as fair use and text-and-data mining exceptions, have been critical to enabling AI systems to learn from prior knowledge and publicly available data, unlocking scientific and social advances. These exceptions allow for the use of copyrighted, publicly available material for AI training without significantly impacting rights holders and avoid highly unpredictable, imbalanced, and lengthy negotiations with data holders during model development or scientific experimentation.

Google wants an exception granted to AI companies, like itself, in copyright law, in large part to avoid “unpredictable… and lengthy negotiations” that might, in other words, require it to compensate creators for the work it uses to train its models.

The difference in the tenor of both documents is interesting as well, as a reflection on the two tech companies’ stature. Google, as a search monopoly with dominion over vast stretches of web infrastructure, is dull and workmanlike in its proposal; clearly it would love to do away with a copyright rule that proves a minor thorn in its side. But life would go on if the Trump camp was unpersuaded, and the courts ruled the other way. For OpenAI, whose business model is already volatile and uncertain, a ruling that its practices violate fair use is more of an existential-level threat; read both these proposal documents back to back, and the difference in gravity is clear.

But either way, this is dark stuff: A $160 billion AI company and a $2 trillion tech giant invoking the need to maintain technological—and implicitly, military—superiority over China, the former casting it as a foe, to justify eroding artists’ already meager rights and protections. Perhaps AI really has entered its empire era.

Nixon Called - Cybernetic Forests

2025-03-12T22:19:27.000Z

Over at Tech Policy Press, I wrote about the government commission that lead to the creation of the 1974 Privacy Act, and how an expanding AI state puts the values of privacy from government surveillance at risk.

The Privacy Act was created as a response to the growing presence of computers in government agencies, which lead to an expansion of the types of data that could be collected and stored about Americans. Fearing the growing capacity to generate computerized intelligence dossiers on American citizens – and fearing the risks of data-sharing between agencies who had no need to access certain activities – the privacy act would go on to establish a firewall between which agencies could access personal data, under what circumstances, and with what oversight.

As DOGE rolls into the Department of Veteran's Affairs, and the Social Security Agency, and others, we are seeing an expanded risk of leakage – especially when DOGE operatives are said to be living together in a GSA office. In the meantime, Elon Musk and others in the operation have indicated a desire to build an AI chatbot on government data. If that is understood as personal data, then we are seeing a violation of the Privacy Act to build a unified government database of private and sensitive information about American citizens – and quite possibly seeing it linked to Grok, Elon Musk's Large Language Model, which was trained on X posts.

The links are an unprecedented selloff of government data in ways that could be mobilized to stifle free speech and the rights to privacy that were designed to protect democracy.

What's the point of AGI? - Cybernetic Forests

2025-03-09T14:38:11.000Z

It's been a busy few weeks, but I'm on a panel for the latest podcast of Tech Policy Press' "Sunday Show" alongside Borhane Blili-Hamelin and Margaret Mitchell to discuss a paper we co-authored – with a slew of additional authors – called "Stop Treating AGI as the North Star Goal of AI Research." It's an examination of the pressures and incentives that the AGI frame places on Artificial Intelligence research.

Check It Out Here

If you aren't sure what AGI is, join the club. Loosely framed as "Artificial Intelligence that can do what humans do, but better," the entire concept is weakly defined – and that's just one of the problems with using it as a strategic goal for tech development. With many pundits suggesting that "AGI is right around the corner," it's worth digging into what that means, exactly – because a close look beneath the surface tells us, it can mean anything anybody wants.

While that paper was a consensus view created with lots of input with various people in AI and social research fields. In the podcast, some of us get to channel our own interpretations from that research project, which should be taken as our own views and not that of the collective authors – which is a diverse group consisting of Borhane Blili-Hamelin, Christopher Graziul, Leif Hancox-Li, Hananel Hazan, El-Mahdi El-Mhamdi, Avijit Ghosh, Katherine Heller, Jacob Metcalf, Fabricio Murai, Andrew Smart, Todd Snider, Mariame Tighanimine, Talia Ringer, Margaret Mitchell, Shiri Dori-Hacohen, and myself.

Told you it was a lot.

Go check out the podcast on Apple, Spotify, Amazon, Pocket Casts or anywhere else.

It has been a hectic few weeks, and I apologize for silence from the newsletter! More to come soon, I hope.

So the LA Times replaced me with an AI that defends the KKK - Blood in the Machine

2025-03-08T17:14:05.000Z

Greetings all — I’m in Austin at SXSW for the weekend; if you’re around give a shout. Yesterday, I had a great chat with crypto skeptic Molly White; tomorrow I’ll be talking generative AI and labor at the Lighthouse. Monday, I’ll join the 404 Media folks to talk about AI content and the state of the internet. Thanks as always to readers and subscribers who make all of this work possible.

Subscribe now

My former employer got into some (more) hot water this week, when its new AI tool came to the defense of, I shit you not, the Ku Klux Klan. The AI feature, called Insights, is, for some reason, designed to evaluate the political orientation of opinion articles and then artificially generate countervailing points for the reader’s consumption. As my former boss, LA Times owner Patrick Soon-Shiong, explains in his introduction to the feature, Insights “offers an annotated summary of the ideas expressed in the piece along with different views on the topic from a variety of sources.”

In this case, the AI responded to a piece by my former columnist colleague Gustavo Arellano, which argued that his hometown of Anaheim shouldn’t forget the KKK’s reign of terror there. The AI Insight then informed readers that, actually, as the New York Times’ Ryan Mac pointed out, the Klan may simply have been “responding to societal changes rather than an explicitly hate-driven movement,” which is an objectively insane thing to say about one of history’s most obviously hate-driven movements.

This feature had already been derided for automating one of journalists’ least-favorite editorial imperatives, both-sidesing a story. Now it was automating the revision of history and the dulling the realities of racism, too.

I admit that when I first heard about the project, I had just rolled my eyes at this thing. There’s a lot going on, and sure, it seemed quite dumb, and to embody a wide variety of AI tools’ goofier impulses—it’s an ‘innovation’ nobody asked for, its output presents the tool as an authority over subjects (including political ideology) on which it categorically is not, and it creates more slop content that people have to sort through. It’s dumb, in other words, in a classic kind of ‘upper management was asked to bring three ideas about how to use AI to the table each and this was the one the boss liked best’ kind of way. But at first blush it didn’t seem orders of magnitude dumber than, I don’t know, the way Pitchfork music reviews perform suggest scientific rigor in a decidedly subjective arena by handing out scores down to the decimal point.

Now it’s clear that it is in fact orders of magnitude dumber than that; as far as I know Pitchfork never awarded an 8.3 to the soundtrack of the Triumph of the Will. This should be disqualifying for the tool, which, again, nobody seems to want or like, and which is appearing in the pages of a newspaper, whose ostensible goal is to be provider of reliable and dependable information to the public.

But the debacle gnawed at me beyond even all that. The week before the AI’s KKK incident, the Times accepted the buyouts of 48 journalists and staffers. This a mere year after layoffs hit 120 or so people, including yours truly—nearly a third of the paper’s staff. Those layoffs followed even more, just the year before. Into this void comes the dumb auto-both-sidesing AI feature. The AI tool, in other words, follows the mass layoffs.

Now, no one at the paper’s management would ever make the case that it is explicitly trying to replace writers or staff with AI; they would say that it is a feature that’s supposed to make the paper feel like it’s on the cutting edge, like it’s not falling behind, and so on. (They would probably pointedly not say that it is an effort imposed by a conservative, Trump and Musk-supporting billionaire newspaper owner to blunt his staff’s liberal leaning opinions.) My former bosses did not sit down and say, “I bet we can replace our tech columnist Brian Merchant with this highly dubious AI technology.” But that AI *is* also supposed to do is increase the time spent on page at as little cost as possible. It’s generating value that formerly would have been generated by human writers and editors. It’s also normalizing the use of AI in spaces formerly dedicated entirely to human voices. Its mere existence advocating a technological solution to a human labor issue.

It’s a similar trend that I noticed and wrote about, perhaps ironically, in a column for the LA Times: When BuzzFeed announced that it would be using AI to create content, games and quizzes, around the same time that CEO Jonah Peretti laid off the entire News division. Peretti and I got into a long debate about what was going on there: He argued he wasn’t using AI to replace any working journalists, that his AI strategy was an entirely different beast. I argued that he was still essentially trying to make up for the value lost by human journalists with AI features.

The point is that it’s rarely a case of one-to-one replacement of human roles with AI automation. AI features can convince management that they can make do with fewer workers, that some if not all of their value or production can be made up for—even if it can’t, and even if that AI tool might defend the KKK. And AI and automation are especially positioned to impact troubled industries—like journalism and writing. Take the example of Sports Illustrated, which only started pumping out the AI-generated content (the subject of another column!) after decades of decline, ad revenues cannibalized by big tech, and mismanagement.

This is what galls me, then. Writers and journalists are being ‘replaced’ not wholesale, not entirely or directly but in kind, by automated gimmicks and features. And rather than confront the tech sector that’s landed most of the existential body blows to journalism, management is once again trying to cut deals with AI companies, to build engagement-generating features, in hopes of wringing out a slice of revenue or relevance in darkening skies; meanwhile more and more journalism jobs disappear every year. The Wall Street Journal just laid off its tech reporters!

To its credit, Times management did support the push to get Google and Meta to pay a share of the ad revenues in California—an effort centrist-pivoting Gavin Newsom apparently killed with a veto threat. But I can’t help but despair a little when I see mass layoffs and new AI features unleashed back to back. We absolutely need to be disabused of any notion that AI is in any sort of solution for declining newsrooms and journalism, and think long and hard whether we want to live in a world with more reliable reporting—or more automated bots that defend the KKK.

On that note, if you would like to help support journalism that is 100% human powered and guaranteed AI-free, and to make more pro-human writing, reporting, and analysis possible, you can do so by becoming a paid subscriber. Just this week, I’ve reported on DOGE’s mass firing of 18F, the widely respected team of government tech workers, on a new study that demonstrates workers aren’t falling for Silicon Valley’s AI hype, and written about the great horror film that predicted our post-truth politics. All that’s made possible by paying subscribers—thanks so much.

Subscribe now

Workers know exactly who AI will serve - Blood in the Machine

2025-03-06T19:35:39.000Z

It’s been two and a half years since generative AI has become Silicon Valley’s consensus product, and the industry’s standard line in promoting that product goes something like this: AI is powerful and even scary, but it’s going to make our lives easier, do work we don’t want to do, and pave the way for a world of abundance. OpenAI even began that period, way back in the heady days of 2022, as a nonprofit that claimed it was dedicated to ensuring all of humanity would share in that abundance.

Now, in 2025, OpenAI is vying to complete its transition into a fully for-profit corporation, Sam Altman has become one of the richest men in the world, and one of the biggest markets for generative AI is enterprise software, where OpenAI, and peers and competitors like Anthropic and Microsoft are selling AI as an automation service. Meanwhile, the companies touting the transformational power of AI in the workplace as loudly as ever. The question is, where do workers stand on all this?

Blood in the Machine is 100% funded by readers. If you find this kind of writing, reporting, and analysis valuable, consider becoming a paid supporter so I can continue doing it. Many thanks.

Subscribe now

According to a new study published FGS Global, they see a technology that will primarily benefit large corporations, be used to surveil them and invade their privacy, and over which they will have little power. FGS interviewed 800 union workers, 800 nonunion workers, as well as industry and political leaders. (Disclosure: The study was commissioned by the Omidyar Network, where I was previously a reporter in residence.)

Workers are excited about the potential productivity benefits the technology enables, but are also keenly aware that as it stands, those benefits will be captured by management, and that they will have little control over how AI is ultimately used in the workplace.

In other words, I would say that, by and large, workers are seeing right through Silicon Valley’s hype, and AI for what it is. They get it.

All slides and graphs from FGS Global.

Now personally, I’d rank government lower — unless your rationale was using AI DOGE-style, to justify eliminating government — but otherwise, seeing as how, in a workplace context, AI is primarily an automation tool that management will use to cut labor costs, that’s about how I’d rank who stands to benefit from AI, too. Corporations, execs, and startup founders selling the stuff at the top, workers at the bottom.

This list of fears of how AI will be used in the workplace is pretty spot on, too; workers are aware of and educated about the litany of risks posed management foisting AI tools on them.

However, when asked about the most concerning impacts about AI in general, job loss falls a couple slots—workers are more broadly concerned about job loss as a general phenomenon than the threat AI poses to their own roles. Once again, they’re well aware of the complexities of their work, and of the limitations current AI systems possess.

Depending on which field you’re in—if you’re an artist or a copywriter, the employment threat posed by managerial AI is more existential—privacy concerns and surveillance is perhaps indeed a more uniform risk to workers. It’s interesting, and surprising to me, that so many workers placed AI’s threat to children’s ability to learn so high; I do think that threat is real, and perhaps it’s a vestige of witnessing the impacts of social media, the last generational tech trend to adversely impact youth.

Just wanted to pull out this slide, too, that shows how overwhelmingly workers are concerned about AI’s impact on privacy—these are workers who have past experience with exactly how mandatory digital systems affect them at work:

Finally, here are the benefits workers see in AI…

… *if* they could use it in a way that wasn’t dictated solely by management.

Only a third of non-union workers and 39% of union workers think they’d be in control of the technology at work:

Most workers want regulations and safeguards, and measures to prevent AI systems to be used against their interests—and, of course, from being used to erode working conditions.

“Workers don’t think they will benefit the most from the growth of AI tools in the workplace—with productivity gains accruing to those in charge,” Graeme Trayner, a partner at FGS and a co-author of survey, tells me. “This has the potential to further exacerbate frustrations around income inequality.”

“Workers do bring a healthy skepticism to AI but see the positive impact it might have on their roles,” Trayner added, “particularly the potential to give all workers access to the same expert knowledge. However, this optimism could easily erode if the technology isn’t properly guided.”

Trayner expects that workers will increasingly demand more transparency and guardrails around how and when AI is used in the workplace, especially around automation and privacy matters. “We were also struck by how fears of AI are driven by concerns over data privacy and security, more so than fears over job loss or displacement,” Trayner told me. “Workers express deep misgivings over how AI may infringe upon their own digital rights.”

Indeed—as tracks with historical precedent, workers tend to know best how managers and bosses will use technology designed to enhance productivity in the workplace. Typically, it will be in service of speeding up their work, surveilling their behavior, and automating their tasks (or jobs) for saving on labor costs. The hype around AI may be louder than usual, the stories about its implications more dramatic, but workers know the score. If they want to capture the benefits of a technology—or merely to ensure it isn’t used to squeeze them—as usual, they’re going to have to fight.

Subscribe now

The mass firing of federal tech workers at 18F is one of DOGE's most extreme political acts yet - Blood in the Machine

2025-03-04T14:14:33.677Z

The jarring news that every single employee of the widely respected 18F team was laid off over the weekend has already begun to recede from view. Or more accurately, it’s already become obscured by other disasters and indignities. But it’s worth pausing to fully grasp what just happened. The wholesale elimination of 18F, a uniquely diverse, skilled, and inclusive group of federal workers, is one of DOGE’s most overtly political maneuvers yet: One designed to punish such a group by erasing it from the government entirely.

Before we go on, a brief reminder that Blood in the Machine is 100% funded by readers. If you find this kind of writing, reporting, and analysis valuable, consider becoming a paid supporter so I can continue doing it. Many thanks.

Subscribe now

Late Friday night, the messages from federal tech workers started hitting my phone. It had finally happened: At midnight, every employee of 18F, a team of technologists, engineers, and designers in the Technology Transformation Services department that develops open source tools and provides crucial digital support for agencies across the government, had been served a layoff notice. The website had been shuttered. And between 85 to 90 people were told they had been deemed “non-critical” in an email sent by Thomas Shedd, the former Tesla engineer-cum-DOGE operative who Elon Musk installed as the acting director of TTS. The impact would quickly be felt beyond 18F, too, with independent contractors and consultants who worked with the team losing their jobs as well.

“This decision was made with explicit direction from the top levels of leadership with both the Administration and GSA,” Shedd wrote. “There are no other TTS programs impacted at this time, however we anticipate more change in the future.”

The blow struck hard, even in a time when many are growing numb to the casual cruelty and wanton firings of federal workers. 18F was particularly beloved among many tech workers and federal employees, not just for the projects they made possible, but what they stood for. 18F was a diverse team staffed by people of color and LGBTQ workers, and publicly pushed for humane and inclusive policies.

“18F getting gutted is a huge moral blow to me and a disaster for govtech,” as one federal tech worker told me.

Naturally, the group’s diversity and its apparent progressive values made 18F an early target among conservative activists in Trump and Musk’s circles looking to rid the government of any and all traces of “DEI”—of nonwhite and openly queer employees—as noisily and cruelly as possible. And that’s exactly what they set out to do.

So, in January, shortly after Trump’s inauguration, rightwing activists looking to feed grist to Elon Musk’s DOGE mill converged on 18F. The Daily Wire writer Luke Rosiak proclaimed it “a far-left agency that viciously subverted Trump during his first term,” without providing any substantive evidence to back the statement up. In an X thread that’s been viewed over 13 million times, and that soon caught the attention of Elon Musk, Rosiak mocked 18F’s practices and politics—its efforts to cultivate racial diversity, its rejection of using facial recognition technologies, its resistance to return to office policies, and its transgender and nonwhite employees for existing.

In one particularly nasty post, Rosiak wrote “More of 18F's totally merit-based and nonpartisan employees” over a screenshot of nonwhite and non-gender conforming staff photos—implying they were unqualified “DEI” hires for being nonwhite and using pronouns.

Shortly after, Musk responded to the thread by saying “That group has been deleted.” That was not true at the time, but now it’s clear it presaged what was to come.

“In the beginning people were upset and confused,” a federal tech worker with knowledge of 18F’s operations told me. Now they’re stuck, feeling angry and helpless, but not wanting to give up the mission. “Torn between wanting to keep these jobs and fight for the American public and resignation.”

LinkedIn and Reddit lit up with posts and remembrances of 18F and its staff, with former employees, colleagues, and admirers eulogizing the agency.

“18F was the best place I ever worked,” wrote Carter Baxter, a former employee. “I’ve never seen such a broad and deep assemblage of talent, and every single one of them was absolutely driven to make government work better. For 10 years they were at the forefront of everything government got right. They were there, driving efficiency, saving taxpayer dollars and just flat making things work better across government.”

Many exclaimed how the agency was known for creating efficiencies and saving taxpayer dollars and time—precisely in line with DOGE’s purported mission—but it’s long been clear at this point that DOGE has little real interest in actually locating efficiencies; it’s aim is to hobble the regulatory state, pursue political objectives, and concentrate power.

In fact, in a telling turn of events, the post in which Musk declared 18F “deleted” was a response to one of his followers crowing about (and evidently misunderstanding) 18F’s role in creating Direct File—a program that let taxpayers circumvent the onerous, for-profit TurboTax’s filing software, and instead file taxes directly to the government online. This would improve taxpayer satisfaction, reduce reliance on an outside corporation, and streamline the process of filing taxes considerably—something that, if DOGE had any real interest in efficiency, would be an obvious boon.

Instead, Musk and DOGE were evidently more interested in firing people for what they looked like, all to get a little adulation from sneering posters on X. The result is unknown and potentially incalculable harm to the nation’s digital infrastructures, and to the people who maintained and sought to improve it.

“Personally holding up okay,” one tech worker effected by the cuts told me. “Difficult to see fed friends and colleagues laid off. Really fearful for what that means for all the services, products, platforms that we spent years building and improving.”

Of course, by now, such incalculable harms are being done to crucial departments across the government—thousands of employees overseeing critical systems, data, architecture, and services, from NOAA, to USGS, to GSA, to the Treasury, to just about everywhere at this point. But it’s worth underlining the particular cruelty at work in the destruction of 18F. Clearly, there are political motives when Musk and DOGE go after USAID, stripping funding and laying off staff because conservatives thought some of its programs sounded silly or woke, and financial ones when it dismantles the Consumer Financial Protection Bureau that created hassles for Musk’s billionaire buddies. But the killing of 18F is different. It’s the termination and removal of an entire office operating within the federal government on what appears to be the basis of its politics and its demography. No pretense made about performance deficiencies, or that this is about anything other than malice and punishment.

For its part, on March 1, 18F issued a collective statement in response. “We came to the government to fix things,” it read. “And we’re not done with this work yet. More to come.”

Subscribe now

The great horror film that predicted our cultish post-truth predicament - Blood in the Machine

2025-03-02T23:21:27.872Z

Hey folks,

Hope everyone’s hanging in as things oscillate wildly between bad and embarrassing and worse out there. As for me, I’ve been all over the place, which has not helped keep the head from spinning any less. The Friday before last, I gave a talk to a group of community college presidents about AI, and I think I managed to plant the grudging seeds of skepticism, especially about enterprise AI in higher ed. Who knows. Then I went up to the 50th anniversary of a biotech conference in Monterrey, where, among other things, biologists and engineers debated how or whether to regulate the use of AI in their fields. My good friend Paris was there, too, and you can hear us discuss the proceedings on System Crash. Finally, last Wednesday, I moderated a talk at Stanford between the great tech critic Evgeny Morozov, AI legend-turned-skeptic Terry Winograd, and optimist Audrey Tang, Taiwan’s first minister of digital affairs. The chat was held to celebrate the Boston Review’s AI issue, to which I contributed an essay. It’s worth checking out. Made it home by Friday for the kids’ choir recital, where the school sang, beautifully, We Shall Overcome. Sure hope so.

Just writing all that out has tired me out all over again. But somewhere in between it all I managed to watch a film that lodged itself very deeply into my brain; a classic horror movie that I think is somehow both under-recognized and over-referenced. It’s a film that feels darkly and depressingly prescient, given that it came out many decades ago, in the way that it examines how and why a society might abandon its respect for science and order—and give way to something more misogynistic and apocalyptic. Something more post-truth.

This will be the first installment of a series I might wind up calling Crisis Culture, or Blood in the Media, or Culture in Crisis—name pending I guess lol, but something like that seems to fit—in which I’ll write reviews and dispatches for paying subscribers, about the best and most relevant stuff I’ve been reading, watching, or listening to. Thanks again to everyone who subscribes and shells out $6 a month or $60 a year to make this writing, as well as much of the above, possible.

Subscribe now

First of all, this is a hands-down great film. There’s really nothing else like it. Second,

Reddit is letting tech companies target federal workers threatened by DOGE's AI with ads for AI - Blood in the Machine

2025-02-28T19:11:27.406Z

Like a lot of journalists following DOGE’s campaign to gut the government, I’ve been reading a lot of posts on r/FedNews and r/FedEmployees, the communities on Reddit where workers are sharing info, mutual support and solidarity, and ideas about how to deal with Elon Musk’s wrecking ball. And I’ve noticed a galling trend, given that DOGE has used AI to justify laying off thousands of people: The subreddits have been bombarded with ads from AI companies and influencers hocking AI services, products, and newsletters.

All screenshots taken from Reddit, r/FedNews and r/FedEmployees over the last two weeks.

So as federal workers read through harrowing accounts on r/FedNews and r/Employees of their peers and colleagues being villainized, pilloried, essentially told they’re replaceable with AI by Musk, DOGE, and the Trump administration—and then laid off en masse—they’ll see ads from AI startups and marketers like Superhuman AI, Upwork, Adaline AI, and Spotter Studio.

It has a ‘learn to code’ vibe, if you ask me, and further helps bolster this false assertion that AI *can* replace any of these workers jobs, or that they’ll need to embrace AI once they’ve lost them.

A brief reminder that this work is made possible entirely by paying supporters—a big thanks to all of you—and if you too find this reporting and analysis valuable, you can become a paid subscriber for $6 a month. That’s less than the cost of say, a ballpark hotdog. You can read more about my mission here—help me take Musk, DOGE and the tech oligarchy to task.

Subscribe now

Look—there’s so much going on right now, and on the list of indignities and anxieties facing federal workers, this probably doesn’t break the Top 10. But all these ads feel callous, given the importance of these subreddits to federal workers. As one representative post by an employee on the forum puts it: “Yes, I’m exhausted, but opening r/fednews gives me the mental fortitude to go to work tomorrow.”

And then AI marketers use the space to push automation tools.

Now, there are a lot of AI ads like this everywhere right now, so I initially thought it was just a harsh and shitty reflection of our moment in general—the mass firing of civil servants, scientists, and aid distributors taking place to a backdrop of the ongoing, if increasingly encumbered, AI gold rush in Silicon Valley, where the big sell remains a promise to cut labor costs.

And ads on Reddit can either be general or custom-targeted to specific subreddits, so the AI ads could have just been showing up randomly. But I reached out to Reddit ad support out of curiosity anyway—and nope, those ads, the rep told me, are probably being targeted directly to r/FedNews and r/FedEmployee.

“It seems like the moderator has set no restrictions, therefore people are able to target it,” the Reddit rep told me, and targeting such communities “would give you good engagement.” When I asked point blank if it looked like these AI ads were indeed being targeted, the rep told me that “considering that the community is quite good in numbers—yes.”

I reached out to a couple of the companies advertising on the subreddits, including Superhuman AI, which bills itself as “the world’s biggest AI newsletter for businesses and professionals,” and didn’t hear anything back—though I haven’t seen any Superhuman ads since I sent the note out.

I also asked a couple federal employees how they felt about all this.

“The indignity of being fed ads for the robots the AI companies claim will replace us is honestly not that novel anymore,” one said. “But as a federal worker whose friends have been fired supposedly cause AI can do their jobs better, knowing there's some asshole out there specifically targeting our communities is just piling on.”

That about sums it up.

Subscribe now

This wasn’t the only big AI news this week—far from it. I’m going to dive into some more of the major AI headlines and add some of my own reporting and analysis below. Again, this reporting, research, and writing takes many hours, and is only made possible by paying subscribers. If you’re able, please consider chipping in a few bucks a month to allow me to continue this work. Thank you.

Activision admits using AI for art, assets, and calling cards — months after I reported on this exact practice for WIRED last summer.

Earlier this winter, Activision got caught using AI-generated art on a loading screen, displaying a zombie Santa Claus with the telltale six fingers, and it caused a uproar among fans. That followed my reporting in WIRED in July, which revealed that AI-generated art was already being sold on the Call of Duty store.

Now, due to the Steam platform’s new disclosure rules, Activision was finally forced to admit that yes, it indeed uses generative AI to create art and assets. But a worker I spoke to said that understates how rampant the situation is: AI use has become more routine in many parts of the company, and managers are asking for more AI production, he told me, confirming critics’ fears. Artists and designers are being asked to set companywide goals for AI production that could affect their performance evaluations.

So if fans were hoping to see less, not more AI slop, they’re going to be disappointed—it seems that Activision is only ramping up AI-generated art production, normalizing the process internally, and disregarding fans who find that the stuff devalues the game. Because, remember, folks really don’t like this stuff.

"Disappointingly, I just grinded for an AI generated calling card," wrote Redditor Poodonkus, in a comment spotted by PC Gamer. "I had heard of a cool pin-up style calling card for completing this challenge, but I wasn't expecting to find out after trying to figure out what was supposed to be on her belt (surprise, just shapeless artifacts of a neural network image generator), that there are glaring hallmarks of an unrefined AI-generated image."

Buckle up, gamers, there’s more where that came from—the AI slop era is already underway.

Microsoft cancels some data centers and CEO Satya Nadella makes some bearish remarks on AI. More signs that the bubble is bursting?

Take all this with a grain of salt—Microsoft is still one of the biggest players in the AI space, but it’s at the very least interesting. Bloomberg reports that Microsoft has bucked the trend of buying up more and more data center leases, and has in fact canceled some of those leases, voiding a couple hundred megawatts of capacity.

Per Bloomberg:

Microsoft Corp. has canceled some leases for US data center capacity, according to TD Cowen, raising broader concerns over whether it’s securing more AI computing capacity than it needs in the long term.
OpenAI’s biggest backer has voided leases in the US totaling “a couple of hundred megawatts” of capacity — the equivalent of roughly two data centers — canceling agreements with at least a couple of private operators, the US brokerage wrote Friday, citing “channel checks” or inquiries with supply chain providers. TD Cowen said its checks also suggest Microsoft has pulled back on converting so-called statements of qualifications, agreements that usually lead to formal leases.

This is notable because it’s one of the scant few examples of *any* tech giant publicly appearing to consider whether it’s over investing in data center capacity—the trend has up until now been almost totally the opposite, Microsoft included. Last year, after all, it bought a power purchasing agreement with Three Mile Island, the infamous nuclear power plant. Does this public example of caution signal the winds are beginning to change?

A number of folks wondered if the DeepSeek news might lead the tech giants to reevaluate their strategy—which is essentially ‘get more data, more compute, more power’—and this is at least a glimmer that maybe the Chinese startup had more impact than initially met the eye. After all, in a podcast appearance, Satya Nadella also made some noise that could be interpreted as the Microsoft CEO is somewhat unimpressed with generative AI’s economic gains thus far. He wants to see real growth on the level of the first industrial revolution, which has distinctly not manifested yet.

It’s too early to claim the AI bubble is bursting as we speak—but these are more signs of stress on a top-heavy, money-losing sector facing a mounting series of hurdles. I’ve been bracing for at least a deflation since last summer, and these are more signs that that’s on the way.

Alright! That’s it for now—until next time; hammers up.

Subscribe now

What's really behind Elon Musk and DOGE's AI schemes - Blood in the Machine

2025-02-25T20:36:27.205Z

The “What did you do last week?” emails were bad enough. Sent out at the behest of Elon Musk’s DOGE team, the terse note exhorted two million government workers to justify their jobs with a list of five “bullets” of things they accomplished, or, per Musk, face termination. The federal workers I spoke to found the note either anxiety-producing or infuriating, and the agency-to-agency confusion over how or whether to respond only heightened the intensity. Then, on Monday, NBC broke the news that DOGE planned on feeding the responses into large language model, to use AI to determine whose jobs were “mission critical.”

The whole spectacle is an insulting and dehumanizing display of power, lazily coated in the aesthetics of AI and technological progress—in other words, it’s government by Grok. Because look, of course it’s ridiculous. There is no AI system in existence that can analyze a single email and credibly determine whether someone’s job is necessary or not. It’s a fiction, and one that, given just a little bit of scrutiny, collapses under the weight of reality.

“The inescapable reality of any human organization is that everyone is doing unique stuff in response to unique circumstances,” the computer scientist and anthropologist Ali Alkhatib says. As such, “you can't systematically evaluate people, or their work, like this. I'm not saying you can't evaluate people at all, but you certainly can't throw everyone's answers to this nonsensical question ‘what did you do last week’ into a an algorithmic woodchipper and meaningfully compare their answers against each other.”

Elon Musk at CPAC 2025. Photo by Gage Skidmore, via Flickr. CC BY-SA.

But, stupid or not, it’s a powerful fiction. It joins the echelon of other AI projects helmed by Musk and his cohort, like the “AI-first strategy” DOGE is implementing, the government chatbots they’re building, and the systems designed to automatically remove pronouns and DEI verbiage from government websites. The very idea that DOGE’s AI can streamline and automate the government is already being used to justify the hollowing out and the reshaping of the federal workforce. Leaning into the reputation of generative AI, which has been touted as the so-powerful-it’s-terrifying future by Silicon Valley and the media, and into his meme-agency’s mission of locating efficiencies, Musk has sold his operation as the future, and he has done so emphatically enough that GOP is more than happy to run with the charade.

After all, the “AI systems” bit gives the DOGE enterprise plausible deniability. Fury is mounting over the mass firings even in red districts, where voters are railing against GOP politicians at town halls. And the broader fantasy of autonomous DOGE AI systems, the most recent included, can be seen as a means to justify the cuts while obfuscating or deflecting blame from Musk or the Trump administration.

Which is why, despite the laziness and stupidity of these projects, I do think it’s crucial that we understand *why* Musk and DOGE are going on about AI-first strategies, building agency-specific AI systems, and promising to use AI to decide who gets to keep their job and who doesn’t. The question isn’t: Aren’t these systems totally unequipped to do the work DOGE says it can do with them—and thus isn’t it a dumb idea to use AI for government?—but why, given that both those things are true, Musk and DOGE want to use them anyway.

A brief reminder that this work is made possible entirely by paying supporters—a big thanks to all of you—and if you too find this reporting and analysis valuable, you too can become a paid subscriber for $6 a month. That’s less than the cost of say, a ballpark hotdog. You can read more about my mission here—help me take Musk, DOGE and the rising tech oligarchy to task. Thanks again, and hammers up.

Subscribe now

Here’s how the DOGE AI rhetorical machinery works in practice: Elon Musk or his team make splashy announcements or proclamations on X (The Everything App) or directly to the government agencies they’re intent on downsizing. The GOP leadership absorbs these talking points in meetings with Musk, or through his X feed, which is by now required reading of every working Republican party member, factotum and aspirant.

A good recent example: Mike Johnson, the Republican Speaker of the House, just said on C-SPAN that Musk’s technology was discovering programs that were “hidden” within the bureaucracy, rooting out waste with cutting-edge acumen. "Elon's cracked the code,” Johnson said. “He's now inside these agencies. He's created these algorithms that are constantly crawling through the data and as he told me in his office, data doesn't lie. We're gonna be able to get the information. We're gonna be able to transform the way federal government works at the end of this, and that is a very exciting prospect. It’s truly a revolutionary moment for the nation."

Johnson’s monologue is, of course, also a fiction. He’s one of those rare guys that seems to actively relish performing the fast-talking, obviously duplicitous caricature of a TV politician. He well knows that the records of all the “waste” DOGE is uncovering was perfectly visible in widely accessible documentation that every department is required to publish. The GOP was able to get the information at literally any time; but, like DOGE’s sham AI job evaluator, the point isn’t functionality; it’s the fiction of apolitical automated machinery, at work on behalf of the people. In reality, it’s a pretense-generator. If “data doesn’t lie” then the system can be made to fire whoever you want.

“There’s been a long historical pattern in many industries of using new technologies not just to automate tasks but to simultaneously insulate management from having to take responsibility for their decisions, particularly their anti-labor ones,” Mar Hicks, a historian of technology at the School of Data Science at the University of Virginia, tells me.

Hicks continues:

“In fact, there are examples where automation has been brought in specifically for this purpose even when it’s clear that automation isn’t working as expected or intended, or isn’t fit for the purpose. But by the time workers and ordinary people have fought it out and gotten the faulty systems out of the way, it’s too late: the damage has been done—or perhaps more accurately the systems have provided cover for management in exactly the way intended.”

And look at the timing here. Musk and DOGE already successfully fired some 20,000 federal workers—the bulk of which were still in their 1-year probationary periods, and thus easier to legally fire—and offered buyouts to 75,000 more. Now the cuts are not only protested by constituents, but less straightforwardly legal; mass layoffs must be carried out under a reduction of force (ROF) and others must be performance-based. So it would be handy if someone intent on firing tens of thousands of people had a system that could carry out performance reviews with the push of a button, and which might lend the illusory appearance of justifying them.

Subscribe now

It is illusory, too—that point could not be more crucial.

“These kinds of systems only barely work when everyone involved really deeply appreciates how carefully they need to tread when they make decisions based on the output of this system,” Alkhatib says. And care, of course, is the furthest thing from the equation right now; obviously we can expect no meticulous, participatory collection and examination of data in any DOGE office.

If they do persist in using the AI, Alkhatib says, “these systems will still spit out crap, and if you're determined enough to soldier through with all the chaos it produces, you will churn out workers and churn in new employees who know how to write Mr Beast style summaries of their week. And to a half-awake middle manager like Musk, the system will seem to be working.”

The point is not to build a system that leans on institutional knowledge to create a futuristic, more efficient automated government. The point is to use the very notion of AI and automation as instruments of disruption, and of consolidating control.

Meanwhile, Hicks points out that tech CEOs and AI advocates have repeatedly underlined AI’s capacity to automate work and output in a “morally autonomous” way that nonetheless is designed to profit them directly:

Even though what we’re seeing right now with AI and rogue billionaires influencing the federal government is an extreme example, it’s not without precedent. Most of the “thought leaders” and investors in the generative AI and “AGI” space have been pretty up front about how they see these technologies as morally autonomous in ways that insulate the people who deploy them from critique and liability, despite being the people deploying and profiting off the systems.

Hicks notes that, “We saw this with how they used (and arguably stole or misappropriated) the copyrighted texts used to train the models, and we’re also seeing it with the deployment as well.”

We need to think long and hard about the role that Silicon Valley and the generative AI boom it’s encouraged have played in leading us to this moment—where the Speaker of the House of the United States is endorsing a tech billionaire’s phony technologies as a means of auto-gutting the government, and AI is touted at every level of the DOGE operation, which still has the full backing of President Trump.

We’re now in year three of the tech sector’s full court press exhorting generative AI as the vessel that will deliver us Artificial General Intelligence, which will be able to automate every manner of job. And it’s entirely feasible Musk and co would have been able to invade the federal government, promising techno-fantasies of automation and efficiency, without the broader social imaginary of a looming hyper-powerful AI; without generative AI being on the tips of everyone’s tongues. But the AI hype, from which DOGE borrows its logic and ideas, has made Musk’s fantasies seem all the more plausible and eroded potential resistances. It’s made Musk’s campaign to gut the government a lot easier. In order to halt his campaign of governmental destruction, we have to dismantle the idea that AI can or should replace government workers’ jobs.

Subscribe now

Thanks for reading, and if you’re a paid supporter, for making this writing possible. Very much appreciate it. I also wanted to quickly note a couple forthcoming events. If you’re in the Bay Area tomorrow, Weds 26th, I’ll be at Stanford, moderating what is sure to be a fantastic talk, The AI We Deserve, with Evgeny Morozov, Audrey Tang, and Terry Winograd.

I’ll also be heading to SXSW the following week, where

On March 7th, I’ll be interviewing the great crypto critic Molly White in a featured event.

On March 8th, I’ll be at the Light House, talking about AI, labor and the future of work with the Tech We Want.

On March 10th, I’ll be joining the venerable 404 Media crew to chat about AI slop and independent media.

Hope to see you there, cheers — and hammers up.

'AI is in its empire era' - Blood in the Machine

2025-02-20T22:41:27.203Z

Last week, when J.D. Vance delivered his first foreign speech as vice president at an international AI summit in Paris, he took the opportunity to put forward what the New York Times called a “vision of a coming era of American technological domination.” The Times is soft pedaling what Vance really articulated: AI’s imperial age has arrived, and the US is calling the shots.

It was a dark, loaded, even threatening speech, and I’d hoped to write about it sooner, but I was interviewing federal tech workers for a piece on the chaos unfolding at home. And then you all left me a little slack-jawed and useless with all the kind words, encouragement, and support after I announced I was officially launching this newsletter as The Job. Seriously, thanks so much for all that. This is a dark time, and this is the best way I know of to pitch in. And all that support has made it clear this is a swing worth taking. I have a lot of ambitious stories in the works right now, and that backing means those really will happen. If you’d like to support this work, too, and you’re able, you can do so below. Thanks again, I’m honestly blown away.

Subscribe now

“The Trump administration will ensure that the most powerful AI systems are built in the U.S. with American design,” Vance declared on stage in Paris. “The AI future is not going to be won by hand-wringing about safety, it will be won by building—from reliable power plants to the manufacturing facilities that can produce the chips of the future.”

It was as bellicose a speech as one could make about an industry currently best known for chatbots—American AI will reign supreme, Vance insisted, so Europe, India, and everyone else should get in line and forget about irksome regulations—and yet the diatribe has mostly gone under discussed by those outside the AI world. It was, after all, overshadowed almost immediately by Vance’s visit to Munich, where he scolded European nations over their speech and immigration laws and sat down with the far-right German party AfD.

But the speech, with its saber-rattling, its calls to end oversight and regulation, its declaration of intent to further concentrate power, and its equating of American might with industrial AI supremacy, stuck with me. It echoed what was (and is) unfolding back home, where Elon Musk and the DOGE boys are at work excitedly gutting the federal government under the auspices of an “AI-first strategy.”

And it sounded the death knell for a measured approach to AI governance by the US—or any approach to AI governance at all, really. The conference itself, which had aspired to locate an international framework for the future of AI development; well that was left in disarray, too. The US and the UK refused to sign even a non-binding declaration pledging to develop AI responsibly and sustainably.

“The AI Summit ends in rupture,” Kate Crawford—a leading AI scholar and the author of Atlas of AI, and who was in attendance in Paris—tweeted as it did. “AI accelerationists want pure expansion—more capital, energy, private infrastructure, no guard rails. Public interest camp supports labor, sustainability, shared data. safety, and oversight. The gap never looked wider. AI is in its empire era.”

AI is in its empire era. That feels indisputable to me. When Vance and the industry leaders like Sam Altman or Elon Musk or the DOGE lieutenants talk about “AI”, they are hardly talking about innovation anymore, they are talking about a project whose aim is to consolidate as much power as possible. AI is a twelve-figure, semi-fictive Stargate project in the Texas desert designed to inspire awe and further investment. AI is more data centers, more training data, more, more, more—despite non-American competitors like DeepSeek demonstrating that other routes are possible. They’re possible, but they’re not desirable, because the American approach to AI is empire-building.

I rang Crawford after the summit, to see if she might expand on her reaction, as it struck me as key to understanding this moment.

“Comparing it to the last two summits which have had a really strong focus on risk and safety, this really shifted into a different register,” Crawford told me from New York. “This was much more about, not only technological inevitability—so no questioning whether AI is useful and helpful—but really moving towards something more like a foreign investment paradigm. It’s a shift towards something which is much more accelerationist, and about maximizing profits for the private sector.”

Vance is ideally suited to making this case, both representing the relentlessly pro-business Trump administration, and his former VC circle in Silicon Valley. Recall, Vance himself has invested in AI startups. And this was what led even many in the AI world to despair over the summit’s conclusion—AI safety experts were aghast at Vance’s broad sidelining of the entire movement.

“You’re aware of the alignment problem, as it’s referred to in the AI world, which is that an individual AI system might become misaligned with human values and ethical values and intentions,” Crawford told me. “What we saw at the summit was a different type of alignment problem, which was a misalignment from very concentrated corporate power and the interests of civil society in general.”

“That’s my big concern,” she added. “That’s the real alignment problem: This enormous transfer of wealth to the AI private sector—without guardrails, and without a commitment to governance—represents a very serious problem to the world and everyone who lives in it.”

Whether consciously or not, Vance's speech posed a version of this "alignment problem," with the Trump-Vance regime proffered as its solution, naturally. criticized “hostile foreign adversaries”—read: China—that “have weaponized AI software to rewrite history, surveil users, and censor speech.”

He continued, warning the world not to partner with such “authoritarian regimes”:

I would also remind our international friends here today that partnering with such regimes never pays off in the long term. From CCTV to 5G equipment, we're all familiar with cheap tech in the marketplace that's been heavily subsidized and exported by authoritarian regimes. But as I know, and I think some of us in this room have learned from experience, partnering with them means chaining your nation to an authoritarian master that seeks to infiltrate, dig in, and seize your information infrastructure.

Of course, at the very moment Vance was uttering those words, back in the United States, Elon Musk’s Department of Government Efficiency was, often in violation of the law, infiltrating, digging in, and seizing the information infrastructure of the United States government. And DOGE set loose automated AI programs on government IT systems, removing pronouns from email signatures, wiping words from government records like “racial justice” and “transition” that the administration found to be too related to “DEI” or “wokeness”—quite literally censoring speech and rewriting history.

It probably does not really need to be said, but Vance's faux concern about AI under an "authoritarian master" is a joke. He is entirely comfortable with the overtly authoritarian uses of the technology being deployed at home, on his own countrymen. He routinely shouted down the idea that AI should be regulated or constrained from being put to such uses in any way in the very same speech. His true allegiance is to an imperial AI, one that allows those in power to concentrate more of it; whether his friends and mentors in Silicon Valley, or his allies, and his boss, in the state, which his party now controls.

“The word that he used, which I thought was particularly revealing, was ‘handwringing’,” Crawford says. “We don’t want any more handwringing, about safety and risk, this image that it’s been fretting over nothing, when what we really need is to build profitable systems. This is about, effectively, increasing corporate profits at the cost of protecting the populations that will be subject to these systems.”

As for her comment that AI had entered its empire era, she says there were two dimensions there. First, Emmanuel Macron announced a $109 billion euro infrastructure spend on AI, following the US’s lead in taking an expansionist, imperial approach to AI development. “This is about rebuilding the French empire around AI — up to this point of course it’s very much been a duopoly between the US and China,” Crawford says. “In a very literal sense, it’s a play for empire-building in France.”

In a more general way, she says, it pertains to how empires have concentrated technological power throughout history. Crawford and a colleague, Vladan Joler, recently published Calculating Empires, a project that “traces technological patterns of colonialism, militarization, automation, and enclosure since 1500” to show how technology has been centralized by empires throughout history. It winds on through today, when, according to the authors, “industrial transformations in AI are concentrating power into even fewer hands, while accelerating polarization and alienation.”

Calculating Empires. Crawford, Joler.

“A technology is developed and then it’s enclosed,” Crawford tells me, “so you see these big enclosures to try and keep particular technologies in very few hands, moving towards highly concentrated industrial power, or in the case of previous centuries—empire power. This very much looks like that.”

It’s all there: Silicon Valley’s takeover of DC, Vance and Trump’s ascent to power, and Musk and his team’s embrace of AI as a tool of statecraft. If Vance’s speech doesn’t officially mark the beginning of the imperial age of AI, then it’s as good an indicator as any that that’s where we’ve wound up.

“It was quite a window into where we’re at,” Crawford says, “and it reveals the playbook of what the US is going to be doing for the next few years.”

Subscribe now

The tech oligarchs and their AI are taking over. Let's fight back. - Blood in the Machine

2025-02-18T17:56:27.018Z

Greetings all,

Quick announcement time: I’m going all in here. This is it, this newsletter is going to be The Job.

I’ve been torn over whether to commit to doing Blood in the Machine full time ever since I left the LA Times, where it turned out being a columnist who criticizes tech billionaires was perhaps not welcome at a newspaper owned by a tech billionaire. I’ve idly had paid subscriptions open for a while, but haven’t paywalled more than a post as an experiment or really committed to the newsletter. Going independent is a risky venture, these are risky times, and I’ve got two little kids at home and all that.

But if there ever was a time to dedicate myself to a project whose aim is to take big tech to task, to report on AI, Silicon Valley, the new oligarchs, and their abuses of power, to center the humans, users, and workers—the blood in its machine—who must grapple with it all, well I think it’s safe to say that time is now.

Subscribe now

Look, it’s all somehow gotten worse than expected, and faster. I haven’t been sleeping much. The federal government is being pulled apart by our richest and cringiest tech billionaire, Silicon Valley has gladly trekked to Mar-a-Lago to embrace Trumpworld, and Elon Musk and Facebook alike are instituting mass layoffs in pivots to AI. Venture capitalists have been installed at the highest levels of government, the tech oligarchs are ascendent, and one of the world’s largest social media networks has become a blaring propaganda organ. Meanwhile, the Valley has doubled down on a grow-at-all-costs approach to AI, sinking hundreds of billions into a technology that will automate millions of jobs if it works, might kneecap the economy if it doesn’t, and will coat the internet in slop and misinformation either way.

As a longtime tech journalist—I was the technology columnist at the LA Times, a senior editor at VICE’s Motherboard, and I’ve written for places like the New York Times, WIRED, and Harper’s—and the author of a book about the Luddites and the first rebellion against the tech overlords (from which this newsletter gets its name), I’ve been doing my best to make my experience and research useful in the face of all of the above. Mostly, that’s meant documenting, dissecting, and distilling the chaos in DC and the Valley, with an eye to the history of technological oppression. Most recently, I’ve reported on the federal tech workers facing down DOGE’s campaign of governmental destruction, broken down Elon’s intention to install government by Grok, and kept tabs on OpenAI’s ever-expanding ambitions. And let me tell you: The always misunderstood Luddites, who fought back, not against technology, but against the titans who used technology to exploit ordinary people—against the “machinery hurtful to commonality”—are more relevant than ever.

Art by Diego Mallo, from the NY Times book review of Blood in the Machine. I’ve always loved this art.

And I’ve found that my reporting and writing can absolutely have an impact without being attached to a legacy outlet. Since writing here, I’ve heard from students, gig workers, academics, folks whose jobs are threatened by generative AI, sources in the federal government looking to push back on Musk and DOGE, from artists, writers, and creatives seeking to stand up to big tech. The community that’s sprung up here—so far, 12,000 strong—has been perhaps the best part of embarking on this newsletter experiment. But it can leave a mark in the legacy world, too: BITM has been cited in the New York Times, Slate, and the Guardian, it’s been syndicated in outlets like Defector and Fast Company, and I’ve discussed the pieces I’ve written here on TV, podcasts, and the radio.

It’s having an impact, in other words, and I expect that to continue and even pick up steam as I dedicate more time here. But I’m going to need your help.

The kind of reporting, research, and writing that’s necessary to do this work is time consuming. It means staying up late on Signal with sources and wading through earnings sheets and obscure academic papers. It means dipping into newspaper archives to confirm the historical precedent, traveling to speak with workers impacted by AI, and interviewing key experts. It’s a lot, and if you find value here, if you’ve been reading along for months, and you’re able to, here’s where I ask you to chip in to make it possible for me to continue on, and to do even more. (And where I say a massive thank you to all of you who are already doing so, even without getting much in the way of concrete benefits in return).

Subscribe now

I’m asking $6 a month, about the cost of a good cup of coffee plus a tip, or $60 a year. That will get you full access to the archives, access to any and all future paywalled posts, and to a biweekly office hours chat—either here or on Discord—where we can talk about anything you’d like; OpenAI, publishing, Luddism, journalism, DeepSeek, death metal, the new season of White Lotus, whatever. It will also help me bring this work—criticism, accountability journalism, labor reporting, and more—to all those that can’t afford to pay. I frequently get asked to speak to workers, unions, and policymakers, often without payment—your support will also make it possible for me to do more of this, to advocate for those under big tech’s thumb.

And I have big plans. I’d like to host a series of virtual meetups for workers impacted by AI, for instance, and I have some longer investigative stuff to get cracking on, and a tech project or two to designed to keep tabs on the tech oligarchs. I’d like to be able to bring on an editor, even feature other writers. Going forward, I’m going to commit to writing two stories a week. I’m never going to put my reporting behind a paywall, but roundups, cultural commentary, and my monthly Critical AI report may be. I’m going to have to experiment, and see what works for everyone.

I know I’m never going to get rich writing critically about Silicon Valley. If you look at the top 10 tech SubStacks, they’re all aimed at the industry insider; news for VCs, investors, the wealthy. An AI SubStack blurbed by the Spotify CEO! This is not intended (entirely) as shade against them—if you are thinking about a newsletter as a business, that is clearly the smart thing to do! Meanwhile, the one time I paywalled a post, I did so with a note that I’d offer free access to anyone who couldn’t afford it. I got a bunch of queries—from phD students, translators and writers whose livelihoods have been hollowed out by AI, an artist who maintains a repository of information for other artists concerned about AI, an environmentalist, even a farmer in Southeast Asia.

Those requests filled me with pride. I did not become a writer or a journalist to be a stenographer for the rich and to fawn over their machinery. I’m writing precisely for those who are thinking long and hard about what big tech is doing to society, to them, personally, and who are trying to push back. I’m writing for the people Silicon Valley is happening to—which, increasingly, is all of us.

And the way I see it, if there isn’t loud, informed, and dedicated opposition to the tech elites right now, we risking losing so much. The free press, good jobs, crucial public institutions, I could go on—it’s hard to understate what’s at stake.

SO. While I’m going to continue to write the occasional story I think will benefit from a broader audience at WIRED, and you can tune in to listen to discussions of many of the subjects covered in these pages at System Crash, the podcast I co-host with Paris Marx, BLOOD IN THE MACHINE will be my home, if I can get the support. Let’s take on the tech titans, the DOGE apparatus, and those who’d drown the world in bad AI. I’m taking a swing, and I hope you’ll join me.

Long live General Ludd. Hammers up.

Subscribe now

Einstein Gazing at the Water - Cybernetic Forests

2025-02-16T12:01:28.385Z

On AI & Pollen Landing on the Surface of Lakes

(Look, it’s been a hell of a few weeks and I am posting about art today, but a heads up that my latest piece in Tech Policy Press has some of your “it’s been a hell of week” covered).

Pollen was once imagined to have agency, because it moved above the surface of water as if by its own intention. In 1827, a scientist named Robert Brown baked some pollen – killing it – and dropped it into water, to see if it still moved. It did. Sentience was off the table.

In 1905, Albert Einstein went for a walk along a lake and observed pollen on the water's surface. His realization that what had once been deemed "intelligent behavior" from pollen was the result of complex flows of unseen bits called molecules. That insight would lead to his first major scientific publication. He called this idea – that pollen and other particles spread out further over time – a diffusion equation.

In generative AI there are diffusion models, and they're tangentially related. In AI, diffusion models refer to the spreading out of noise within an image in a process that moves information further from the source in every step. AI borrowed science for a metaphor, as it always does, to explain this spreading of noise throughout the images used for training data. Knowing how it spread, you could denoise that spread to restore the image. Start with random noise, and it would correct the noise to make new images out of related concepts.

Noise, in computer systems, creates an illusion of liveliness. Perlin noise is used in video games and CGI to procedurally generate "clouds, fire, water, stars, marble, wood, rock, soap films and crystal." Gaussian noise is more scattered.

Noise pollinates the image set, giving the model a sense of agency. Start with the same image of noise and ask it for different things, and you get similarly structured different things. Below you can see a seed generated by Stable Diffusion (left) and two images that come from that seed.

On the left, the first stage of noise from a diffusion model. To the right, the same noise shaped by the prompt "small dog" or "small cat." Similar patterns of color and position can be implied, shaped by the structure of the noisy image to the left.

When you adjust the "temperature" of an LLM to include more variety, you are essentially expanding the acceptable threshold of noise in the system. With images, you are literally adding noise to the image in order to find new possibilities, constrained to any instructions you provide.

Ask for a new image of a small cat or a small dog, and you generate a new seed. Keep the same seed, you get the same cat, same dog. The noise structures the picture.

Pollen and noise have this relationship to each other: an illusion of liveliness, which is one thing when alighting on ponds to be observed as a choreography of molecules, and another when an AI system is mistaken for imposing creativity into a jpg. Of course, each of these is worthy of appreciation: diffusion models are elegant, even if the business models, and the purposes to which they are used, undercuts the awe that many of us might otherwise feel.

Art, Pollen, Noise

I've written before about my relationship with AI as being adversarial – to paraphrase Nam June Paik, "I work with generative AI in order to hate it properly." As The Algorithmic Resistance Research Group, I (along with Steph Maj Swanson and Caroline Sinders) premiered a number of works at the hacker convention DEFCON 31 that looked at the early potentials of glitching and hacking AI systems.

I always described my work as trying to take imagination out of AI, in contrast to the many AI artists who aim to build on top of these corporate imaginations. My theory of change was recently confirmed in a bit of business research: "efforts to demystify AI may inadvertently reduce its appeal, indicating that maintaining an aura of magic around AI could be beneficial for adoption." That is to say, the less you know about how these systems work, the more impressed you will be.

I create work as a form of research into these tools. I accept a certain degree of complicity. Sometimes it feels shallow and complicit to make work the way I do and sometimes it feels really necessary. The issue of complicity is centered in my work, though not always clearly. Addressing complicity makes stronger work because complicity with the tech industry is part of what it has meant to be American.

We use systems that fund bombs, we agree to share data that is used for surveillance — the house tech has built has a lot of rooms and very few of them don’t have peepholes. For that reason, using AI to attack the foundational logic of AI is, on one level, just about the same as using Google Maps to navigate my way to a political protest, or posting anti-tech threads on X.

There’s a responsibility that comes with it though, and navigating what complicity requires is a big part of why making work in this way helps me to think lucidly about what AI does and how so many assumptions behind it need to be dismantled.

So I try to counteract the myths and assumptions that lie at the heart of AI models. To challenge that aura of magic, I try to understand what they really are and do, and make work that points to its own sources. In this way, I hope we can counteract the spectacle of AI.

Much of the work that I make was an artifact of a research practice. AI-generated images of visual noise circumvent part of the image generation process that references datasets of any kind. They create bizarre and unexpected abstractions through short-cutting the internal image recognition systems these tools used to compare your image to the prompt used to shape it. Through the prompt window, I would trigger a loophole that circumvents the training data.

Gaussian Noise, 2022.

In the image above, I have asked for an image of a certain kind of noisy digital image. The seed is created, and an internal vision model is tasked with assessing whether the image contains the prompt. "Is this a dog? Is this a cat?" In those cases, the vision model would say no, there is no dog, let's refine this.

Instead, this image and prompt poses the question: "Is this noise?" The answer is an immediate yes. From there, the KSampler takes the image and refines it according to the number of steps, making it "a clearer image of noise," whereas the image recognition system cannot offer any refusal: the image is always noise.

The Noise of Pollen

Pollen Series, 2024. Eryk Salvaggio with Public Diffusion.

I've been thinking about pollen while beta-testing Public Diffusion / Inference since mid-December. This noise process doesn't work: it doesn't rely on CLIP. However, I wanted to make the most of the freedom of Public Diffusion as a tool: I don't actually have to "defeat the system." There is no data in the model that undermines artists, no child abuse imagery to haunt my experience of prompting.

I used existing glitches I'd produced and used them to image-search the training data inside PD, a 12-million-images assortment of public domain images. The search engine gave me a series of images from history that resembled such noise: many of them were marbled book covers; damaged photographic prints, scientific images from labs; and yes, stray glitched images and static.

Taking these as a source, and then requesting the model to work with them as a seed for creating images of pollen, gave me these. They are probably not what most people would do with an image generation tool, and so these images, as a "product demo," probably don't do much. I'm ok with that. I will say, the textures and richness of these images surprised me.

I am very happy with these images, and the process of working with a source in an attentive, careful way. There is something satisfying about connecting this idea of noise, pollen and diffusion to the archives and the outliers of the public domain.

The glitch images I've made with Stable Diffusion challenged the machine to produce something without reference. In these images, I am generalizing the visual vocabulary of the outliers in the archives. The debris of visual culture landing like pollen on the surface.

Pollen Series, 2025. Eryk Salvaggio with Public Diffusion.

I intend to print these on paper to complete them: turning scanned paper archives back into paper feels like karmic regeneration, in a skillful sense of thoughtful re-engagement and re-contextualization, as opposed to non-consensual exploitation. To that end, if anyone is interested in showing a broader selection of these works, please let me know.

💡

These images were created in an artist's beta. PD/Inference is not limited to abstract images; that's just what I happen to make.

Phantom Power Podcast

Really happy with this discussion of AI, art, music and noise on Mack Hagood's Phantom Power podcast on sonic culture. Video is above, but you can find the audio version wherever you get your podcasts!

AIxDesign Fest!

Excited for the upcoming AIxDesignFestival: On Slow AI which will happen in real life in May in Amsterdam! I'll be a speaker at the event and I am really excited for it. Right now they're also raising funds to support a livestream of the event – if you want to help support it, you can score some swag and the money will go toward your ticket!

Bluesky Things

If you're on Bluesky, I've got some things that may be interesting for you.

A starter pack of Critical AI thinkers from all kinds of perspectives, which I've promoted here for a while. But there's an expanded pack, with even more Critical AI folks, which is well worth a look.
A similar starter pack for Artists working in Technology.
A custom feed that shows you good, no-hype tech journalism. Pin this, and you'll have a tab on your Bluesky account that gives you access to tech journalists - minus the product launches and video game news.
Clicking on any of those links will ask you to set up an account if you haven't already.

A Note to Subscribers

I recently cleared out a large number of accounts that subscribed to this email list but never read it, or had bouncing emails. It was a bit of a blow to the old ego. If you're a fan of the newsletter, please recommend it to someone who might dig it!

Here's a link to the archive, where people can subscribe. You can also sign up below!

The federal tech workers facing down DOGE - Blood in the Machine

2025-02-14T20:16:27.039Z

Over the last few weeks, as Elon Musk and DOGE have infiltrated government agency after government agency, proclaiming their intent to slash budgets, cut jobs, and embrace AI, we’ve watched a brazen, extralegal effort to hollow out the state unfold in real time. Now up to 200,000 workers are being targeted in mass layoffs. Much of the collective horror has stemmed from the broader implications this campaign—orchestrated by an unelected tech billionaire who has enriched himself with government contracts—has for our democracy. It has after all been carried out with no congressional oversight and often in stark defiance of judicial orders. It’s been called a coup, or an autogolpe, a coup from inside, or American authoritarianism.

But it’s also happening to real people, who are experiencing it all in excruciating, real-time dread. For the last couple of weeks, I’ve been talking with federal tech workers about what’s happening, how they’re processing it, and how they’re pushing back. I’ve spoken to workers representing the full spectrum: From 10-year veterans to first-year tech workers in their probationary periods—and thus more vulnerable to termination—and from different departments across the government.

I wanted to share some of their stories, with their permission, because they help illuminate what’s going on at the personal level—even while we’re justifiably preoccupied with the ramifications for democracy writ large and the assault on our institutions. (I am, for the obvious reasons, keeping them all anonymous here, but have individually confirmed each of the sources.)

“I think maybe the thing that's not coming across in all the narrative so far is that federal workers are not just federal workers,” one veteran federal tech worker told me. “We are citizens and voters too, and we are targeted in many ways beyond just our work lives.”

Daniel Huizinga. Flicker, Creative Commons.

Blood in the Machine is 100% funded by paying subscribers. If you find this reporting and analysis valuable, consider becoming a paid supporter to make more of this work possible. And thanks as always for reading.

Subscribe now

The cuts and the intrusions are affecting federal workers of every stripe, but tech workers have often been on the front lines, the first to be approached by DOGE agents as the caretakers of our federal digital infrastructure and the operators of our information systems.

“Right now it feels like we're being hacked from the inside,” one federal tech worker told me. “Like the ‘HR’ emails we get that have to be manually marked as not spam by IT. And they insist on immediate action, which is also a warning sign of a phishing email. Then people wanting privileged access to systems they don't have rights to, without proper (or indeed any) credentials.”

I ask another how he’s doing—an admittedly dumb question, but what do you say?

“Oh you know, watching an autogolpe from the inside,” he replies. “Feeling ten years of painstaking work to build up culture and credibility around digital transformation in the government get burned to the ground in less than three weeks.”

“Fearing for my job, fearing for my family's safety,” he says. “You know, the usual.”

That anxiety is omnipresent.

“[It’s] a very scary time. I'm gonna work on a private sector resume this weekend,” one junior federal tech worker told me.

That fear is being compounded by multiple factors. There is of course the DOGE directive to cut as many jobs as possible—most recently, WIRED reports that DOGE has attempted to lay off every single technologist at the Consumer Financial Protection Bureau, and are trying to push cuts through the Department of Education, the General Services Administration, and beyond. All this is leading to chaos and confusion on every level: Some employees who were told they were going to be fired have still received no official notice, workers who’ve taken the ‘fork in the road’ offer of 8 months paid severance are unsure whether they’ll ever see it, and not even DOGE seems to know (or care) if what it’s doing is legal.

“I will also say that as the Thursday deadline [for the initial fork in the road offers] approached OPM sent out these increasingly desperate emails that felt like nothing so much as a Democratic candidate at a fundraising deadline,” one worker told me. He says his team of over a dozen will soon be down to just a handful of employees. Another tells me that people of color are disproportionately being targeted for layoffs in their department. But DOGE is also trying to winnow staff through other means, too: Demanding a return to office, even for those hired as remote workers and who have never stepped foot in a government office, while at the same time, instructing the GSA to sell off or close federal buildings—making it even harder for employees to find an office to come into.

It all underlies the callousness at the heart of DOGE’s campaign, and the fact that this is an effort to hollow out the state, the firings unfurling often regardless of what a person or department really does.

“I am not a career-long gov employee by any means but even I can feel how the bedrock assumptions of what we do are being swept away,” a federal technologist told me. “Like clearly the people in charge have no interest in the missions of the agencies and there isn't any recourse to stay the courts, as far as we can tell.”

“If they even sweep away USAID, the velvet glove of US imperialism, because they occasionally piss off Putin and Orban,” he adds, “then it's not clear how much hope there is for things like clean air and food stamps.”

“I had BigBalls in a meeting,” another worker told me. "When I saw him I balked, and I thought 'Oh hey, someone brought their teenaged son to work today.' He showed up along with some others, and was not introduced as anything but an advisor." In fact, that was one of the leading DOGE officials, wielding significant power over the US government.

“It really feels like all of the work that we do as feds is so undervalued,” a junior tech worker says. “It's incredibly demoralizing to see outsiders come in and completely trample norms.”

DOGE agents really do appear to believe that many if not most of these jobs can be done by AI. “AI is one of the things the new management,” a federal tech worker says, “sees as a priority for our technology funding. It comes up often. They all see it as the way to do government without people, and I'm sure you can imagine how I feel about that.”

This week, Musk and Trump notched up the pressure. Trump signed an executive order (EO) that expanded DOGE’s powers, and ordered nonmilitary agencies to submit plans for mass reductions in force (RIFs). On Friday, February 14th, the RIFs began. But all this is happening, the workers emphasize, alongside an assault on trans rights, migrants, public education, and more. And this is what one federal worker tells me is the worst of all. I’ll quote them at length here, because this story, if I’m being honest, just about broke me:

My work life is subject to the EOs involving DOGE and RIFs, sure. And there's cartoonishly clumsy and evil people carrying out those orders in ways that defy the law, and also logic, and claim they're saving tons of money and finding tons of waste, fraud, and abuse when the reality is that they're inflicting it.
It would be one thing if "put them in trauma" as Russ Vought said, was only happening at work. But I have a teacher wife, and a teenage trans son.
So there's the school EO that paints my high school English teacher wife as a radical gender ideology indoctrinator, because she makes her class a safe place for trans kids to be themselves and learn, and suggests that she should be driven out of the profession.
And then there are... how many... 7? 10? EOs referencing trans issues, starting from the very definition of gender itself, that seek to drive my son out of public life.
Health care? No. Jobs? No. Passports? No.
These resemble the Nuremberg laws that steadily stripped Jews of their citizenship and finally personhood.
We are a family of Jews. The lessons of the Holocaust are burned into us at an early age.
So while I'm feeling the trap closing at work, I'm also feeling it close around the country as a whole.
My son happens to have his SSN, birth certificate, and passport all saying he's male; that took a couple years, and at the end we expedited the passport and got it right before inauguration. OK, fine, at least it doesn't say X for gender on his passport, so that's good right? But there are records that the change was made.
How long will it be before he's no longer allowed to use that passport?
What about healthcare?
Well, my son was bullied, suicidal, and hopeless for a couple of years in high school before we pulled him out, and after a miserable year in an online high school, he took a high-school equivalency exam in CA that let him move on and figure out what's next. The only reason we got this far was that we also started him with gender-affirming care: Therapy, medication, and yes, hormone-replacement therapy.
Why were we able to do that? Because my generous federal health insurance, the only insurance we have, covered gender-affirming health care.

And now all that hangs in the balance.

If there’s a silver lining, it’s that by all counts, the assault on federal workers has inspired a surge of interest in organizing—everyone’s talking about it, the tech workers tell me. There are Signal chats lighting up, a spoon revolt—where federal workers used spoon emojis to mock the fork in the road emails—and harried efforts to formally unionize among those who have not yet done so, and to find the right union reps through which to push back. The American Federation of Government Employees (AFGE) says that its membership has risen to the highest levels in its history. In response to the mass layoffs, its president, Everrett Kelley, issued a statement condemning the Trump administration’s actions:

"Despite OPM's guidance earlier this week advising agencies not to engage in sweeping terminations, the administration has plowed forward. Employees were given no notice, no due process, and no opportunity to defend themselves in a blatant violation of the principles of fairness and merit that are supposed to govern federal employment…
"AFGE will fight these firings every step of the way. We will stand with every impacted employee, pursue every legal challenge available, and hold this administration accountable for its reckless actions.."

Elsewhere, federal workers are engaging in lower key acts of refusal and resistance; declining to let DOGE officials access systems, and throwing up whatever roadblocks are possible to stop them from ingesting private information.

What’s especially galling about much of this is that many of these tech workers are there because they believe in the now-erstwhile mission of improving the ways that government can serve the public, because they love the work, and their country—and they gave up much higher salaries of the sort they could find in Silicon Valley and the private tech sector to do it.

“This has been the best job I've ever had; every sacrifice was worth it because I found my people,” one tech worker told me. “People who also cared to make the government work better for people and had explicitly chosen this path. It's crushing to see how quickly it can be shredded by people who cannot even understand the concept of public service, or why anyone would choose it.”

And the toll is already wearing on many. According to the Trump administration, 75,000 workers have already agreed to the fork in the road offer. Others are all but sure they’ll be forced out, too.

“It's just exhausting and even though I'll be able to muddle through a moderately lengthy period of unemployment it's crappy to be in my mid-50s contemplating another career change,” one tech worker told me. And this happening all across the nation, at nearly ever department of the federal government. The point, many are sure, is to shrink it, even to kill it.

“It seems increasingly likely that they will continue to make the job harder and more miserable,” the tech worker says. “At a certain point with these guys it may be that working to make the gov work better isn't a positive thing.”

Subscribe now

The real reason Meta's bleak 'AI vision' is winning out - Blood in the Machine

2025-02-12T01:56:28.532Z

Last month, Meta announced that it was going to begin firing thousands of “low-performing” workers as it shifted to a strategy that focused on AI. When the DeepSeek launch upended other American competitors and sent Nvidia shares downward, investors noted that Meta too has an “open source” approach to its AI model, Llama, even though its Meta AI is rarely in conversation with OpenAI’s ChatGPT or Anthropic’s Claude as a leading consumer product. Meanwhile, revelations surfaced that Mark Zuckerberg had likely personally OK’d the pirating of vast troves of data to train that model. On Monday, the layoffs began.

Here’s how the stock market has responded. Per Bloomberg, Meta shares saw

a rally of 16 straight sessions, the longest streak of any current Nasdaq 100 Index company going back to 1990. The stock added more than 17% over the surge, bringing its market capitalization above $1.8 trillion.

That story is headlined, “Meta’s 16-Day Winning Streak Is Victory for Zuckerberg’s AI Vision,” and that is indisputably true, if you consider “own a monopoly social media network and web infrastructure that is so large you can do anything you want on it” plus “do crude identity politics to placate the new president” as an “AI vision.”

But it is important to understand why it is that investors are cheering Meta, while OpenAI is facing more and more hurdles, its broader picture getting bleaker by the day.

Before we dive into that, however, a brief note that paid subscribers make this newsletter possible—it takes many hours to research, report, and write these columns, and I have some big projects coming down the pike. But I can only keep it up under this model if folks like you support the work; if you find any of this valuable, please chip in for the cost of a coffee a month to keep the lights on here. Many thanks, and onwards.

Subscribe now

As the Great DeepSeek Event made clear, OpenAI’s (and Anthropic’s, and other AI model-making companies’) biggest issue now is that AI chatbots are on the brink of becoming a commodity, if they haven’t already. Building AI models, like OpenAI does, is suddenly a pretty bad business to be in. It’s expensive, and for all but the most invested users, the experience of using most chatbots on the market is becoming less distinguishable.

This is why OpenAI is focusing more and more on its ChatGPT app, which is popular, but still incredibly expensive to run, its enterprise businesses, and government contracts. It’s also why, despite being valued at whatever hundreds of billions OpenAI currently is, pending Softbank investment, the startup is in a somewhat precarious spot. If the ChatGPT app isn’t profitable, and the enterprise business is still unproven, and government contracts are now subject to first buddy and Sam Altman’s personal nemesis Elon Musk, the future of robust federal contracting for OpenAI may not exactly be robust.

In fact, Musk has just thrown up another roadblock to OpenAI; he formed a consortium to offer a $97.4 billion bid for control of the company. (Admittedly, this is a pretty expert bit of corporate trolling; OpenAI, as you may know, has a uniquely labyrinthine governance structure born out of the original promise to benefit humanity and remain profit-free, in which the now-for-profit-company’s assets are controlled by a nonprofit entity. Altman is trying to ditch the nonprofit structure to solicit further investment, which means purchasing its assets; previously, he was slated to do so at $40 billion; Musk’s ‘offer’, which Altman has already declined, essentially raises the market value of the restructuring—the nonprofit board has a fiduciary duty not to undersell its assets—and gives OpenAI a major headache at the least.)

Furthermore, OpenAI’s first enterprise contract with the federal government was with… USAID. Given that Musk and his lackeys are tearing the copper wiring out of the agency at the moment, and the nature of Musk’s feud with Altman, it seems unlikely that the contract will remain intact for long, if it hasn’t been cancelled already. It also raises the question of whether Musk’s adventuring at the foreign aid agency began in earnest in the first place in part because OpenAI—which Musk despises—was doing business with the department. These are the things we now have to consider! Given the scale and nature of Musk’s power over the government, his volatile temperament, and well-known vindictive tendencies, etc.

But I digress; back to Meta.

Cristoph Scholz, CC 2.0 license, Flickr.

Now it’s not exactly that the relations between Meta CEO Mark Zuckerberg and Musk are miles better—it was what two years ago that the two were threatening to do a public cage fight—that Meta’s in a better position. It’s that Musk can’t really touch Meta or its products. And that, to circle things back to Meta’s “AI Vision,” is why investors love it too.

Let’s return to the Bloomberg piece that listed all the things that have allegedly fueled Meta’s historic, 16-day rise to a $1.8 trillion market cap over the last couple of weeks:

First, CEO Mark Zuckerberg said the company plans to invest as much as $65 billion in AI projects this year, more than had been expected — reinforcing the perception it is spending from a place of strength.
Then, the stock bucked the tech selloff sparked by the emergence of DeepSeek, a Chinese AI startup that claims to be lower cost. Investors took DeepSeek’s success as a validation of open-sourced models, as Meta’s Llama employs.
Meta’s results have also underlined how AI is flowing through to its financials, improving how ads are targeted to its billions of users. Zuckerberg fanned the enthusiasm, saying 2025 would be a “really big year” for AI.
It also hasn’t hurt that Zuckerberg has moved closer to President Donald Trump, potentially giving the company a bit of breathing room from tighter regulation. The stock has risen every day since Trump’s inauguration on Jan. 20.

Notice that absent in any of the above reasons for Meta’s soaring valuation is “it made a great or popular AI product that people are flocking to or even just using a lot.” No, it boils down to the fact that Meta owns the largest slabs of digital real estate on the web—Facebook, Instagram, WhatsApp—and it has paid lip service to investing heavily in the trend that is still Silicon Valley’s north star, which is AI. Remember, Meta made a big show of investing a similarly enormous figure in the metaverse, and that has decidedly not paid off, so it’s not like Wall Street is even expecting a great product to emerge from that firehose of cash.

Subscribe now

No, what really matters to the money is simple, and same as it ever was: Meta is an all but intractable monopoly, and the fact that it’s outwardly keeping pace with new entrants is more than good enough for them, at least in terms of dollars invested. It has positioned itself to minimize any potential regulatory confrontations with the new administration. Better still is that the company is seriously trimming its workforce, firing costly engineers as it pivots to AI.

And that’s really about it. If investors honestly think generative AI is improving ad delivery on Meta’s networks, I have no idea what they’re looking at. Meta has long used automated systems to track user preferences and data and to then deliver personalized ads accordingly, but that predates generative AI or their product-side use of large language models. These tools, and Facebook’s presentation of them to investors, has perhaps benefitted from the AI effect of the last few years, lifting in stature features that can loosely be called ‘AI’ via the halo glow of buzz, but that’s about it as far as I can tell.

No, if anything, most users seem to actively dislike the AI that’s been introduced on Meta’s platforms—people find the stuff weird and alienating. I’m not sure who, besides the errant content farm operator, is actively enjoying the reams of spammy AI shrimp Jesuses or automatically generated images of suffering children. Or the bizarre AI-generated images of users served to themselves on Instagram. Or the unwelcome AI characters and bots showing up in Facebook groups uninvited, leaving odd comments. On the product side, I think most people who are familiar at all with what the company’s been up to would say that Meta’s AI plays have been a muddled disaster. (And on the model architecture side, there’s the piracy scandal, so that’s not great either.)

As the tech PR CEO and commentator Ed Zitron points out in his latest newsletter, Meta, Google, and Microsoft all took in tens of billions of dollars in profits last quarter, despite becoming increasingly hostile to their own users. He writes, “software has, for the tech industry, become far more about extracting economic value than it has in providing it.” After all, Google’s forays into AI have been as dispiriting as Meta’s, despite the huge research, product, labor, and ad spends, and yet its stock continues to rise, too. Microsoft’s as well—does anyone out there like AI Bing or stan for Copilot? Maybe! Though I haven’t met many avid fans.

So it’s important to stress just how little any of the above matters, to say nothing of piracy scandals and copyright lawsuits, and how relatively simple it is to articulate what does: That you are one of the handful of monopoly platforms that is large enough to reliably extract rents from your users, and to run experiments that those users may find unpleasant but will tolerate because the opportunity cost of leaving is too high. That you are large enough to invest in locating ways AI might extract more rents from users on your platforms in the future. And that you are willing to cut jobs and labor costs to maximize profits, and bonus points if you say you’re doing it because of AI.

That’s why it’s so bleak that Meta’s “AI vision” is prospering right now. There *is* little vision, as far as I can tell, apart from loading its platforms with AI bots and content, which users don’t seem to much want. It is largely interchangeable with Zuckerberg’s metaverse vision, and the crypto vision (remember Libra?) before that. But if Nvidia is the AI gold rush’s big winner so far because it’s selling the shovels, then Google and Meta stand to profit by owning the real estate on which AI might someday generate profits. OpenAI is, at core, a model, an app, and some enterprise services; even if it does have 300 million monthly users, that’s a fraction of the giants’ base, and it’s burning cash fast.

OpenAI at least had a novel product people were and are enthusiastic about—that it soon got catapulted into Big Tech-era logic necessitating rapid and immediate expansion at all costs just to compete says as much about the economics of our technological moment as Sam Altman’s titanic ambitions, and well, here we are. With our largest social media platform, whose existence was once predicated on connecting people, shoveling AI into every pore, hoping to automate the essence of those connections away, while Wall Street thrusts money into its maw.

And this is what I’ve long said about the AI boom: Ultimately, it boils down to automation. In the AI features stuffed into Google and Meta products, in, of course, the enterprise contracts Anthropic and OpenAI are inking, with image generation, even in the rise of government by Grok in DC under Musk’s direction, we have entered a new era governed overwhelmingly by big tech and its refreshed automation logic. Mark Zuckerberg and Meta are “winning” the way the leaders of so many of our institutions, online and off, seem to be “winning” these days, by leveraging institutional power, trimming headcount, and promising to dully automate what likely does not need to be automated at all.

There is, however, a ray of good news, too, today: Reuters won its lawsuit against the tech company Ross Intelligence, in the first major copyright victory in the AI era.

WIRED reports:

In 2020, the media and technology conglomerate filed an unprecedented AI copyright lawsuit against the legal AI startup Ross Intelligence. In the complaint, Thomson Reuters claimed the AI firm reproduced materials from its legal research firm Westlaw. Today, a judge ruled in Thomson Reuters’ favor, finding that the company’s copyright was indeed infringed by Ross Intelligence’s actions.

The big deal here is that the judge found that Ross violated fair use, and pointedly because it generated materials that could be used to compete with Reuters’ own original material. This is a contention of many of the claimants in the ongoing copyright lawsuits against bigger AI companies, and a promising sign that creators’ works may be protected by copyright law after all.

Subscribe now

Okay okay, that’s it for now. I’ve got the stirrings of a cold, and I’m working on, let’s see, three separate longer form pieces right now and need to rest up a bit. So until next time—hammers up.

Anatomy of an AI Coup - Cybernetic Forests

2025-02-09T12:01:28.485Z

Not with a bang.

My latest for Tech Policy Press argues that the reported actions of Elon Musk and DOGE are not at all about efficiency, but about centralizing power to a small group of technical elites. A sample:

"While discussing an AI coup may seem conspiratorial or paranoid, it's banal. In contrast to Musk and his acolytes' ongoing claims of "existential risk," which envision AI taking over the world through brute force, an AI coup rises from collective decisions about how much power we hand to machines. It is political offloading, shifting the messy work of winning political debates to the false authority of machine analytics. It's a way of displacing the collective decision-making at the core of representative politics."

Read It

Things I've Been Up to This Week

Academic Pre-Pub:
"Stop Treating AGI as the North-Star Goal of AI Research."

How can we ensure that AI research goals serve scientific, engineering, and societal needs? What constitutes good science in AI research? Who gets to shape AI research goals? What makes a research goal legitimate or worthwhile? In this position paper, we argue that a widespread emphasis on AGI threatens to undermine the ability of researchers to provide well-motivated answers to these questions.

I'm part of the team behind this preprint of an academic paper from a supergroup of ethical / critical AI researchers. In it, we argue that setting sights on "general intelligence" – a term that is vague and undefined – is a fundamentally flawed strategy. We explain six reasons why, and then propose an alternative.

It's an academic paper, but I did a very informal summary from my own perspective in a thread over at Blue Sky.

Shout out to Borhane Blili-Hamelin, Christopher Graziul, Leif Hancox-LiHananel, Hazan El-Mahdi El-Mhamdi, Avijit Ghosh, Katherine Heller, Jacob Metcalf, Fabricio Murai, Andrew Smart, Todd Snider, Mariame Tighanimine, Talia Ringer, Margaret Mitchell and Shiri Dori-Hacohen.

Read the Pre-Print

Read the BlueSky Thread

Phantom Power Podcast

AIxDesign Fest!

Helpful Bluesky Things

If you're on Bluesky, I've got some things that may be interesting for you.

A starter pack of Critical AI thinkers from all kinds of perspectives, which I've promoted here for a while. But there's an expanded pack, with even more Critical AI folks, which is well worth a look.
A similar starter pack for Artists working in Technology.
A custom feed that shows you good, no-hype tech journalism. Pin this, and you'll have a tab on your Bluesky account that gives you access to tech journalists - minus the product launches and video game news.
Clicking on any of those links will ask you to set up an account if you haven't already.

Government by Grok - Blood in the Machine

2025-02-05T23:41:27.050Z

Well, nothing’s going to slow down for the foreseeable future, is it. Alas. Before we get into Elon Musk’s quest to automate the government, a quick programming note: This newsletter is made possible by readers who chip in a few bucks a month to make it possible (thank YOU). We are quite clearly moving into dark and uncertain times, ruled over by tech oligarchs and their dreams of AGI—I plan on using this space to investigate, document, and break down what they’re doing. I can only do that with the support of readers like you. If you find value in this writing and analysis, and are able, consider becoming a paid supporter, so I can keep at it. And share this with other interested humans, too—it’s all much appreciated. And with that, onwards!

Subscribe now

Over the last week or so, a freshly empowered Elon Musk and his now-infamous intern squad at DOGE led a breakneck incursion into a number of federal agencies—the foreign aid-distributing USAID, the federal infrastructure-managing General Services Agency, and, perhaps most alarmingly, to the Department of the Treasury, where Musk and co now have direct access to the nation’s payment system and to the private information of millions of Americans.

Some key developments among the blitz:

-8,000 government websites were taken offline, many from the CDC and the Census Bureaus. “The purges have removed information about vaccines, veterans’ care, hate crimes and scientific research, among many other topics,” the New York Times reports.

-Millions of federal workers have received “fork in the road” emails, offering them 8 months of severance if they resign by Thursday, February 6th.

-An automated system is now scrubbing pronouns from government email signatures.

-In a Monday morning meeting, ex-Tesla engineer Thomas Shedd, the newly appointed director of the GSA’s Technology Transformation Services, told the department that it would be pursuing an “AI-first strategy.”

Got all that? What’s happening at federal government agencies is, among other things, a stark portrait of why power seeks to automate—and why, in enterprise AI, it has found an ideal vessel for corporate and administrative automation.

It’s not just about displacing labor, although that is of course a key thrust—in this case DOGE is seeking to winnow the federal workforce by driving out nonpartisan workers with the lowest tolerance for the new, ideologically motivated regime, and promising to replace the bulk of their tasks with AI. The Musk lieutenant Shedd emphasized that “AI coding agents” would be prioritized and made available for all agencies. WIRED reports that “Shedd made it clear that he believes much of the work at TTS and the broader government, particularly around finance tasks, could be automated.”

Elon Musk with a Neuralink Machine. Photo: Steve Jurvetson, Wikimedia Commons.

It’s also, and perhaps above all, about control. Automation necessitates the narrowing of scope, of information input into a system, of possibility—so that a job or a task or work can be more predictably and repetitively performed on behalf of an administrator. In DOGE we see the logic of automation—of enterprise AI—being imposed by a nascent oligarchic state. We thus see less information available to the world, fewer options available to the humans working to provide it, fewer humans, period, to contest those in power, as that power concentrates in their hands.

This, in short, is why Elon Musk is trying to automate the federal government.

There was a somewhat lazy joke I took to making in the purgatorial period between Trump’s election in November and his taking office in January, when few yet knew how seriously to take DOGE or Elon Musk’s role in the forthcoming administration. With Musk’s incessant proclamations about cutting trillions from the federal government on X and in the Wall Street Journal’s op-ed pages, and his obsession with AI, it seemed to me that a core assumption undergirding the moves was that AI might be made to perform federal workers’ jobs—and hey, he owns an AI company, and knows a thing or two about securing big federal contracts. We were about to see the rise of government by Grok, was the joke.

Ha, ha.

The problem about making jokes like that at a time like this is that they are prone to come true rather quickly and become unfunny even faster. It doesn’t even matter if the notion itself—that millions of government workers can be replaced by AI systems that have trouble counting to 50, are still prone to hallucinations, cannot ably function in physical spaces, and have no institutional knowledge—is absurd on its face.

Per WIRED:

"This does raise red flags,” a cybersecurity expert … told WIRED on Monday, who noted that automating the government isn’t the same as automating other things, like self-driving cars. “People, especially people who aren’t experts in the subject domain, coming into projects often think ‘this is dumb’ and then find out how hard the thing really is.”

Or if the idea that anyone should treat the agency that manages the $500 billion in federal buildings and property as “a software startup” is functionally meaningless. WIRED again:

Shedd instructed employees to think of TTS as a software startup that had become financially unstable. He suggested that the federal government needs a centralized data repository, and that he was actively working with others on a strategy to create one, although it wasn’t clear where this repository would be based or if these projects would comply with privacy laws. Shedd referred to these concerns as a “roadblock” and said that the agency should still push forward to see what was possible.

These notions—AI can replace workers, the government should function like a startup—are not meant to describe reality; they are meant to create a permission structure for those in power to obtain more of it. Here, AI will either allow Trump and Musk to install more loyalists, hollow out the administrative state, or degrade the quality of services once provided; all outcomes that favor Trumpism, and, I guess, Muskism. The startup mentality, meanwhile, seeks to give license to break laws, in the name of progress, of disruption, of building the future.

Same as it ever was: Way back in the early days of the Industrial Revolution, early factory owners deployed automation to deskill workers, to justify employing precarious and child laborers, and as a means of circumventing long-held laws—all to produce more products at lower quality, and to concentrate profits, and power, in fewer hands.

Note that while many AI companies and executives try to pitch automation as making people’s lives easier, DOGE cuts right to the heart of it. This isn’t about making anyone’s working life better—in fact, it’s actually going to mean more work, for you, the worker.

Here’s Shedd again, this time from recorded audio of the GSA meeting obtained by 404 Media:

“as we decrease the overall size of the federal government, as you all know, there's still a ton of programs that need to exist, which is this huge opportunity for technology and automation to come in full force, which is why you all are so key and critical to this next phase,” he said. “It is the time to build because, as I was saying, the demand for technical services is going to go through the roof.”
“Which means things are going to get intense. Like across the board in every agency, the demand on all of us is going to go up,” he added. One employee asked if it is “currently illegal to work more than 40 hours a week. Is that going to change?”
“Unclear at this point,” Shedd said

Many have pointed out, quite accurately, that Musk is poised to do to the federal government what he did to Twitter—to strip it to the bone, hollowing it out so those who remain do so either out of necessity or ideological alignment, and not caring much when it breaks down. It’s going to be haphazard, and dumb, and maybe evne funny in a gallow’s humor kind of way, because it’s the actual federal government and not a Web 2.0 app. But we should be paying attention to where he builds on that metaphor, too—where Musk and his lackeys are using the logic of AI and of technological disruption to justify his further integration with, and control over, crucial parts of the state.

This is government by Grok, so to speak, and stupid as it all is, Musk is now in an unprecedented position to extract data, labor, contracts, and assume powers no unelected man has ever held over the nation. And that is why he automates.

Subscribe now

A quick final note: You may have noticed I linked an awful lot to WIRED and 404 Media in this piece, and that is because both of those outlets have quickly proven to be indispensable in fearlessly reporting on the Trump-Musk era. I heartily recommend subscribing to each, if you can. All the best out there, and hammers up.

Announcing the Escape the Algorithm ᵐⁱᶜʳᵒsupporter Program - escape the algorithm

2025-02-05T15:11:28.085Z

My little newsletter about taking control of our attention and finding a more human side of the internet recently surpassed 5000 subscribers! The good-little-newsletter-boy playbook dictates that I immediately launch a paid subscriber program and start sowing the seeds that will eventually allow me to quit my job and profit from the resulting media empire.

Here’s the problem: I have no aspiration for all of you to become my main source of income. I am privileged to have a full-time job that I enjoy and no offense but I’m pretty sure that if writing a newsletter was my full-time job I would hate it!

I don’t covet the economic pressures of paid subscriptions, but I do covet the mutuality: giving readers a way to say “we care about and value your work.” Money is only one way of doing that, and it may not even be the best way.

So starting today, if you would like to become a ᵐⁱᶜʳᵒsupporter of Escape the Algorithm, you can do so by performing a tiny act of codependence:

Send me a gift (something you’ve made, something with a story, or something you think I in particular would enjoy)
Write me a thoughtful postcard
Take me out for a cup of coffee in person when you’re in Philly
Contribute a guest post to Escape the Algorithm (pitch me!)
Support Escape the Algorithm financially, either through Substack or Buy Me a Coffee
A secret sixth thing (email me an idea, I’ll probably be down)

No matter which of the above you choose, I’ll mark you as a paid subscriber in my mailing list.

For now, the perks of support are simple:

Soften the para part of our parasocial relationship
Support my commitment to only sending out emails when 1) it brings me joy and 2) I have something to say

At some point I’ll take a ᵐⁱᶜʳᵒsupporter pulse check to see if there should be any other benefits (group chat? escape the algorithm workshops?).

All Escape the Algorithm posts will remain free.

If you’re new to Escape the Algorithm, here are some nice things that people have said about it:

“One of my very favorite newsletters and a continual source of incisive, lyrical observations about life online.”

Caitlin Dewey (Links I Would Gchat You If We Were Friends)

“It can seem that as our tech wizards conjure up new things for us to click, they're also magicking away the parts of the internet that I fell in love with. If you feel that way, too, then check out [this] incomparable newsletter.”

John West (Lead R&D Technologist, The Wall Street Journal)

[One of the people] quietly keeping the spirit of the human, personal, creative internet alive.

Anil Dash in The Rolling Stone

Subscribe now

The Critical AI Report, January 2025 - Blood in the Machine

2025-02-03T21:36:27.065Z

Greetings all,

Welcome to the second edition of The Critical AI Report, a monthly breakdown of the news analysis, academic research, investigative reporting, and key stories shaping critical thought around AI. And what a month it was. I could have comfortably filled this space with news, reports and analysis published in the last week alone, given the rapid-fire news cycle that careened from Stargate to DeepSeek to a market shock that’s rippled across the tech sector—but we take the long view here. And 2025 is off to a predictably chaotic and unsettling start, with plenty of crucial work to parse.

Subscribe now

In the AI policy community, there’s been, perhaps unsurprisingly, a lot of thinking about how to approach AI lawmaking and policy under the shadow of a Trump administration. Trump, after all, immediately rescinded Biden’s executive order calling for an AI Bill of Rights, and will likely be uninterested in regulating the American AI industry in any serious way.

Where the Blueprint for an AI Bill of Rights used to be. See: https://www.whitehouse.gov/ostp/ai-bill-of-rights/

To that end, in January, I attended a private gathering of AI policy experts and California lawmakers organized by TechEquity, where I spoke about the history of the Luddites, the politics of big tech, and AI’s impacts on the workforce. It’s clear now that if there *is* going to be any near-term policy that meaningfully protects American consumers and workers from the excesses of the AI industry, it’s going to be enacted on the state level. (The EU has already pursued AI regulation, which is one reason you often hear tech CEOs complaining about Europe.) And there are, despite everything, reasons to be hopeful on this front. A lot of bills are taking shape, aimed at protecting workers’ privacy, shielding consumers from AI-generated misinformation, and more. (And I do mean *a lot*—California legislators write tons of bills, and it was a running joke among legislators just how many AI bills were coming down the pike.)

Alondra Nelson, the who led AI policy in the Biden Administration, and who co-authored the AI Bill of Rights, was in attendance, and rather than despair over Trump’s AI policy wrecking ball, struck a tone of resilient optimism. Executive orders don’t last, she told me, and she knew this was coming. Yet the foundation of their work remains, and even a number of red states are beginning to adopt parts or all of the AI bill of rights, regardless of Trump’s stance.

California, recall, is the fifth largest economy in the world on its own—good laws here can set important precedents and shape global policy. Which is precisely why we need to keep thinking critically about AI, investigate its impacts, and push back when necessary, and possible. To that end! This month’s report will dive into the following:

Stargate vs DeepSeek: Why Silicon Valley will stay the course with a bigger-is-better approach to AI despite shockwaves from a Chinese startup

Five major privacy concerns experts have about generative AI

Does AI inhibit critical thinking? What one major study reveals

The UK is aiming to accelerate AI with pro-industry policies. How artists, creatives, and Paul McCartney are pushing back

AI is using so much power it may be putting your household appliances at risk

Plus, how Los Angeles residents used AI during the wildfires, how Meta’s use of AI bots on Instagram is unsettling users, and a new study that shows people with a lower AI literacy are actually more likely to want to use it.

Subscribe now

This report is for paid subscribers. It takes many hours to research, synthesize, and write, and I’ve been told I need to paywall some stuff if I’m going to get serious about this. Thanks as always to everyone who already reads and supports this work; you make it possible. If you haven’t upgraded to paid, and you find value in this work, I’d love to have your support, at the cost of a cup of coffee a month. And if you can’t afford to subscribe and would like access, just shoot me an email, especially if you’re a student, a worker impacted by AI, or an organizer. I’m happy to share. Onwards!

A Fork in the Road - Cybernetic Forests

2025-02-02T12:01:28.314Z

Type the word “Resign” into the body of this reply email. Hit “Send”.

So ended an automated email sent to all 2.3 million government employees at the end of January, part of the Trump Administration's effort to reduce the cost of government services by ending them altogether. If any of us wondered how government might maintain even the illusion of functionality, a clue to the future of government came between the lines of two other notable announcements.

The first was that OpenAI was launching ChatGPT GOV, a version of ChatGPT "designed to streamline government agencies’ access to OpenAI’s frontier models." ChatGPT Gov is hosted by government agencies who can customize it to their own security requirements. "Additionally," they note, "we believe this infrastructure will expedite internal authorization of OpenAI’s tools for the handling of non-public sensitive data."

This came just two weeks after OpenAI removed a reference to "politically unbiased" output from its policy doc. Politically unbiased AI is impossible; the real problem for the Altman gang is that their model has been targeted for being "woke" and untruthful. Elon Musk has accused these models of reflecting "woke, nihilistic" ideals.

Speaking of Elon Musk, his announcement that Optimus, its humanoid robot will be sold in 2026 for $20,000 alongside fully autonomous vehicles. If this seems unlikely, Musk notes, that is because "human intuition is linear" while "what we're seeing is exponential," which sort of makes sense if you're stoned. Optimus, he suggests, is a $10 trillion business for Tesla in the coming years, eventually arriving at "100 million being manufactured per year" at a pace wherein the robots will eventually outnumber human beings, which I assume he thinks is desirable.

If you recall, Optimus was initially launched by bringing out a dancer in a body suit that pretended to be a robot. In October, Optimus was still being trained to navigate "non-flat terrain," and all of the footage in a promotional video was sped up, at least twice, but often up to 10x, at which point the robot moved at the speed of a cautious human.

AI is an excuse that allows those with power to operate at a distance from those whom their power touches.

That is to say, none of this is ready to launch. But technological capacity is not the point. The point is to justify decisions about personnel and the workforce as if they were replaceable, and to use the technology as a means of pushing employees harder and demanding cheaper labor. It is a strategy rooted in delusion, being executed through confusion and fear.

AI is an Excuse

To that end, Musk has now taken access of the Treasury Department's payment system, which allows him direct access to stopping payments that violate Trump's execute order on "woke," circumventing Congressional oversight. Essentially, this is a vision of government as an algorithmic process, a set of codes that can be deleted or consolidated, and one that is designed to eradicate any semblance of addressing social issues in science.

Already, the National Science Foundation has frozen all payments to researchers receiving grants and issued a freeze on all scientific research being published by the CDC – because diversity, equity and inclusion are apparently such an incredibly urgent threat to the US that all science research must be stopped immediately.

It's about to get worse. From the Washington Post:

The sensitive systems, run by the Bureau of the Fiscal Service, control the flow of more than $6 trillion annually. Tens of millions of people across the country rely on the systems. They are responsible for paying Social Security and Medicare benefits, salaries for federal personnel, payments to government contractors and grant recipients, and tax refunds, among tens of thousands of other functions.

Typically, only a small group of career employees control the payment systems, and former officials have said it is extremely unusual for anyone connected to political appointees to access them.

This is all deeply connected to the idea of AI as an excuse, one that allows those with power to operate at a distance from those whom their power touches. As Musk is rambling about the "inflection point" on the horizon in which "the future will be different from the past," OpenAI is pitching generative AI to a workforce under siege. Both carry forth the logic of computation toward what I consider to be the truly "nihilistic" philosophy of Musk's ilk: that we can automate human decision making, better sealing obedience to authority even when it is deployed immorally or, as of today, unconstitutionally.

How Humanity Disappears

The most substantial threat of Artificial Intelligence has nothing to do with any conclusions it might independently arrive at and execute. AI cannot do this. Rather, the "doomsday trap" of artificial intelligence is the dehumanization that this technology makes possible. AI is not only a technology, it's a new excuse to try bad ideas again – a spectacle designed as pretext to resist empathy and create emotional distance from consequences.

AI can facilitate work that feeling people would otherwise reject.

The ideology of AI is foremost a technology for rendering people, and labor (and thinking, and creativity) into objects to be tallied and sorted. By creating distance between any decisions we make about the unique value of a human being, or the unique circumstances that constrain them, we move closer to indifference to human suffering and need. When we make such decisions at a distance, our conscience preserves a claim to innocence from the guilt induced by the sight of consequences.

When tapped to provide critical services, generative AI isn't used despite its inability to empathize or respond to unique individual circumstances. It is used because of that: to facilitate work that feeling people would otherwise reject. It ensures that any dehumanizing policy will be implemented uniformly, without a human being able to intervene on behalf of decency. If we worried otherwise, it would not be placed into these roles.

An Automated Autocrat

I don't worry that AI will destroy humanity so much as I fear it will destroy the humanity within us.

It's clear to me that Musk and DOGE will embrace a shift in how we use AI outputs. This will move AI outputs from prescriptive – recommending a course of action, based on an analysis of data, such as flagging an insurance claim for review – to autocratic: a singular source of authority, where the text it generates becomes directly actionable as a decision without human intervention, such as rejecting an insurance claim outright.

Generative AI is not even remotely appropriate for the first case. Using it for the second case is only rational if you want those failures embedded into the system.

Text emerging from a blinking cursor can never justify human cruelty.

When AI is in autocratic roles, it generates commands, or orders – and also generates the pretext through which people obey those orders. It creates an illusion of distance, as if those who choose to use them can pass off their agency and accountability for the inhumane enforcement of unjust rules. Like a trio of executioners with just one real bullet, it is easy to comfort oneself with the idea that any one executioner might be blameless. Today, the bullet is a flashing cursor.

But text emerging from a blinking cursor is never an excuse for human cruelty, nor does it disperse accountability. It's merely a pretext designed to preserve a fragile conscience.

Reaching for Digital Distance

Distance has been built into the history of computation from the outset. In 1936, Alan Turing proposed a Universal Machine based on his observations of the human "computers" engaged in solving arithmetic problems. In this work, Turing assumes a certain mechanized, rote action of human thought that could be automated, if only one could transform it into the scanning mechanism that could calculate even and odd sequences.

Later, Pitts and McColloch would apply the Turing Machine's logic toward modeling the human brain, viewing the neuron as a mathematical receptor that would reach a counting threshold before firing. This model of the neuron went on to become the basis of neural networks. Decades later, this path lead to today's artificial intelligence. But there is a central confusion here, and machines built on a model of the mind based on a mathematical approximation of thought became confused with the mind itself.

All of this is anchored in the belief that algorithms can sort the world in ways akin to human decision-making. But what each of these technological advances made possible was not merely complex mathematical tabulation. All technology creates a system of effects, rippling into the social world. Often, what technology makes possible is distance.

ChatGPT is not a decision-making technology, it is a decision-removing technology. It creates text to fill the space where a decision is needed.

ChatGPT and other Large Language Models are not a decision-making technology, they are decision-removing technologies. They generate text, but most powerfully, they generate pretext. It creates text to fill the space where a decision is needed.

The true power of artificial intelligence is not that it automates decision making with any greater discernment than a human case worker. It is that the powerful can cultivate an illusion of distance from the system. Government workers will be replaced by automated systems, and the remaining government workers will be beholden to those systems. Researchers have warned, over and over again, that these systems are unsuitable for the task.

If we are about to diminish government services to interactions with ChatGPT, and treat American labor as if it is on the verge of being replaced by robots that will never exist, then we are hopelessly disoriented from what it is that a nation, or a government, is meant to be.

The Case for Diversity in AI

The most crucial work in AI right now fits into the category of Diversity, Equity, Inclusion and Accessibility. Machinic bias is well documented. Whenever these machines are deployed, social biases enter into the technical operation of the system at the most base level. Facial recognition systems misrecognize black faces, particularly women of color.

Recognizing and correcting issues of computational bias (and the systemic bias that the computers reflect) can solve real, documented problems wherein AI systems more frequently block women and people of color from obtaining home loans, jobs, and educations. Why wouldn't we want to understand and solve those problems? Even if we sought a "color-blind" meritocracy, we have a set of machines that are nowhere near "color-blind" or "merit-based."

Research into Diversity, Equity, Inclusion and Accessibility in AI systems has been ordered to a halt this month by the Trump administration. By banning this research while elevating the role of AI-driven services and the fantasists behind them, it feels like we are abandoning the work of "a government committed to serving every person with equal dignity and respect" in favor of deference to a machine that has been proven to do the opposite.

Efforts to recruit, train and hire a diverse workforce benefit everybody. Right now, in the AI field, 62% of Computer Science PhDs are white and 83% of Tenure-Track faculty in AI are male. In a world where we know that race and gender have no impact on one's intelligence, this seems like an unlikely outcome. Something seems to be in play beyond pure chance. Much of that is the recruitment pipeline, and efforts to invite participation from more groups is ultimately the goal of diversity programs. Ask Trump and Musk, and they'll tell you these programs are handing out diplomas to random students, rather than trying to find ways to get talented people to apply.

DEIA adjacent research does not diminish dignity or respect for anyone. It is literally how we fix the problem.

In AI, DEIA adjacent research does not diminish dignity or respect for anyone. It is literally how we fix the problem. Diversity is a good thing. Equity is a good thing. Inclusion is a good thing. Accessibility is a good thing. The methods and systems we design to reach these goals can be contested, and in a democracy, they should be. The processes we put in place to reach these goals matter.

But these are a very standard, democratic set of values. They are not things to be afraid of or demonize. In working with AI, these ideas must be front and center at all times. The tendency for data to drift into generalizations – and then to operationalize those generalizations – is incredibly disruptive to real lives. We need to see things from as many angles as possible, not fewer.

It is self-evident that AI is not ready to do work that demands social accountability of any kind, especially unsupervised, autocratic work. To do so is not an effort to solve a problem. It's an effort to create a digital distance from the consequences of systems and the accountability of those who deploy those systems with full knowledge that they are reaching beyond the capacity of an algorithm.

But Silicon Valley thinkers have never been realistic about their technologies. Now, with $6 trillion in government funds at their fingertips, we're all about to discover the limits of their delusions.

Phantom Power Podcast

AIxDesign Fest!

Fun Bluesky Things

If you're on Bluesky, I've got some things that may be interesting for you.

A starter pack of Critical AI thinkers from all kinds of perspectives, which I've promoted here for a while. But there's an expanded pack, with even more Critical AI folks, which is well worth a look.
A similar starter pack for Artists working in Technology.
A custom feed that shows you good, no-hype tech journalism. Pin this, and you'll have a tab on your Bluesky account that gives you access to tech journalists - minus the product launches and video game news.
Clicking on any of those links will ask you to set up an account if you haven't already.

A Note to Subscribers

Here's a link to the archive, where people can subscribe. You can also sign up below!

The Great Undermining of the American AI industry - Blood in the Machine

2025-01-28T00:11:26.946Z

Well this week’s off to another wild start. The stock market is falling, investors are panicking, and some of the most valuable companies in the world, particularly Nvidia and the AI-invested tech giants, are seeing hundreds of billions of dollars erased from their valuations. (At one point Nvidia shed 17% of its value, or $568 billion, in less than a day, in a new record loss in market history—though, much like we see new hottest-year records smashed rather routinely thanks to climate change, we see these staggering losses more frequently these days, too, which one might argue is not great, but I digress.)

As always, thanks for reading and subscribing. If you find this writing and analysis valuable, please do chip in for oh the cost of a cup of coffee a month. This work is 100% reader supported, and I deeply appreciate all of you who make it possible.

Subscribe now

The catalyst, if you have not yet heard, is a Chinese company called DeepSeek that released an AI chatbot app that’s just about on par with the American companies’ products. (Remarkably, the company was spun out of an effort to build a stock-picking algorithm.) The catch is, according to the company’s researchers, DeepSeek trained its open source model for $5.5 million, compared to the $100 million Altman has said it cost to train OpenAI’s GPT-4. Roughly 1/50th the cost. And it’s popular, too. DeepSeek is the number one most downloaded app in the App Store, topping ChatGPT.

So what’s going on here? And why does this matter? I’ll have a bit more to say on this later, but essentially, as long as DeepSeek’s fundamentals are born out, the research paper the company published holds up to scrutiny, and the app stays popular (and is not say banned by the state like certain other high profile Chinese-made apps), then what we are seeing can be considered a Great Undermining of the American AI industry’s foundational assumptions. Yes, in all bold.

Take, for example, the big AI news of just last week: Sam Altman, Donald Trump, the massive investment firm Softbank, and other partners announcing Stargate, a $500 billion project to build out data centers and other AI infrastructure. (The project was largely already in place, pre-inauguration, though it did not have such an absurd price tag associated to it, and was under construction in Texas; the announcement was widely seen as a way to flatter Trump, and perhaps to jockey for now and future state support.)

The reason that the idea of spending $500 billion on data centers for training and running chatbots was not immediately laughed out of the room is that the largest American AI companies have spent the last two years advancing a very specific case. As I’ve documented in detail, both in this newsletter, in columns for the Times, and maybe most comprehensively in this report for AI Now, the modern AI industry, as led by OpenAI and Sam Altman, has always been dependent on a narrative, and the assumptions that undergird it: Generative AI is the future, it’s improving rapidly, and thanks to that we’re on the road to Artificial General Intelligence. AGI, in turn, will enable enterprise software to “outperform humans at most economically valuable work,” as OpenAI puts it in the company’s charter. Many executives and managers very much want this.

But the models need to be scaled first.

Those models need ever more data, they need more compute power, and they need more energy to run. This is why OpenAI says it’s raising historic amounts of capital, why it lobbied the Biden administration for support in building data centers, and why it says it shifted from a nonprofit structure to a for-profit one in the first place. It simply needed massive amounts of resources, and like its competitors, would need more and more for the foreseeable horizon, until the fabled AGI was brought to fruition.

The success of DeepSeek, if it holds, undermines these assumptions; assumptions which undergird essentially the entire American tech sector’s approach to AI. As the reporter Karen Hao notes in a long thread on Bluesky,

Much of the coverage has been focused on US-China tech competition. That misses a bigger story: DeepSeek has demonstrated that scaling up AI models relentlessly, a paradigm OpenAI introduced & champions, is not the only, and far from the best, way to develop AI.
Thus far OpenAI & its peer scaling labs have sought to convince the public & policymakers that scaling is the best way to reach so-called AGI. This has always been more of an argument based in business than in science.
There is empirical evidence that scaling AI models can lead to better performance. For businesses, such an approach lends itself to predictable quarterly planning cycles and offers a clear path for beating competition: Amass more chips.
The problem is there are myriad huge negative externalities of taking this approach - not least of which is that you need to keep building massive data centers, which require the consumption of extraordinary amounts of resources.

Now that a company has figured out a way to produce an AI app that’s just as effective at producing satisfactory output as the big American companies, at a sliver of the cost, a $500 billion data center facility in the desert suddenly seems like an offensive boondoggle. And it’s caught the stars of the AI tech world flatfooted, apparently. The typically noisy Sam Altman hasn’t tweeted for two days, at the time of this writing. Elon Musk has yet to mention DeepSeek, either.

It’s worth underlining a couple things here. First, generative AI long seemed destined to become a commodity; that ChatGPT can be so suddenly supplanted with a big news cycle about a competitor, and one that’s open source no less, suggests that this moment may have arrived faster than some anticipated. OpenAI is currently selling its most advanced model for $200 a month; if DeepSeek’s cost savings carry over on other models, and you can train an equally powerful model at 1/50th of the cost, it’s hard to imagine many folks paying such rates for long, or for this to ever be a significant revenue stream for the major AI companies. Since DeepSeek is open source, it’s only a matter of time before other AI companies release cheap and efficient versions of AI that’s good enough for most consumers, too, theoretically giving rise to a glut of cheap and plentiful AI—and boxing out those who have counted on charging for such services.

Second, this recent semi-hysterical build out of energy infrastructure for AI will also likely soon halt; there will be no need to open any additional Three Mile Island nuclear plants for AI capacity, if good-enough AI can be trained more efficiently. This too, to me, seemed likely to happen as generative AI was commoditized, since it was always somewhat absurd to have five different giant tech companies using insane amounts of resources to train basically the same models to build basically the same products.

What we’re seeing today can also be seen as, maybe, the beginning of the deflating of the AI bubble, which I have long thought to only be a matter of time, given all of the above, and the relative unprofitability of most of the industry. Just look at how these developments are shaking the whole industry. Here’s the New York Times:

“The market naturally will worry about demand growth in computing power,” analysts at Jefferies wrote in a note. DeepSeek’s apparent breakthroughs on cost and efficiency “could prompt investors to ask hard questions” of tech leaders about their weighty investments in chips and data centers, they added.
The turmoil also hit the stocks of utility companies that have opened new lines of business serving the voracious power needs of data centers. Constellation Energy plunged nearly 20 percent, partly reversing a long-running rally that has seen the power producer’s stock more than double over the past 12 months.
U.S. Treasury yields fell sharply, as they often do when investors seek havens during times of turbulence. Yields move inversely to the price of debt, meaning that the value of Treasuries jumped on Monday.
That weighed on the value of the dollar, which slipped against a basket of currencies of major U.S. trading partners. These moves faded somewhat in the afternoon as investors refocused on this week’s meeting of Federal Reserve officials, who are expected to pause their campaign of interest-rate cuts.

This is a truly fascinating moment. Things could go in so many different ways: Will tech stocks continue to tumble? Will it become clear that Silicon Valley is over-invested in a very resource-intensive strategy, perhaps needlessly? What then? Will the talk turn more pointedly Sinophobic, both within the industry and out, in an effort to try to demonize the company and its approach, as politicians, lawmakers, and industry insiders did with TikTok? Will Silicon Valley AI stalwarts like Altman be able to muster a convincing enough argument to keep the money flowing into their increasingly outsized enterprises? Will OpenAI and Anthropic press their case with the state and drive even harder to become too big to fail, angling for government contracts? What happens to the current construction of the AGI mythology, if it turns out a Chinese startup can make a serviceable AI clone for cheap? Does this puncture the armor of the AGI investment complex, and start to steer backers and partners away for real? Is the AGI fever breaking?

And why, we’ll be left wondering, regardless how the dust settles, with the vast majority of resources for AI research concentrated in the United States, was it a Chinese hedge fund’s side project that unearthed this leap in efficiency? Could it be that the major AI players were more interested in fortifying their approach of more-is-better, broadening the scope of their project, and accumulating power, than attempting to innovate in a way that makes AI more nimble, more democratized, to use one of the industry’s preferred terms, and more efficient? Could it be that Lina Khan was right all along to want to break up the tech giants to encourage innovation?

I guess we’ll see soon enough.

Critical takes on tech - BlogFlock

OpenAI and Google's dark new campaign to dismantle artists' protections - Blood in the Machine

Nixon Called - Cybernetic Forests

What's the point of AGI? - Cybernetic Forests

So the LA Times replaced me with an AI that defends the KKK - Blood in the Machine

Workers know exactly who AI will serve - Blood in the Machine

The mass firing of federal tech workers at 18F is one of DOGE's most extreme political acts yet - Blood in the Machine

The great horror film that predicted our cultish post-truth predicament - Blood in the Machine

Reddit is letting tech companies target federal workers threatened by DOGE's AI with ads for AI - Blood in the Machine

What's really behind Elon Musk and DOGE's AI schemes - Blood in the Machine

'AI is in its empire era' - Blood in the Machine

The tech oligarchs and their AI are taking over. Let's fight back. - Blood in the Machine

Einstein Gazing at the Water - Cybernetic Forests

On AI & Pollen Landing on the Surface of Lakes

Art, Pollen, Noise

The Noise of Pollen

Phantom Power Podcast

AIxDesign Fest!

Bluesky Things

A Note to Subscribers

Sign up for Cybernetic Forests

The federal tech workers facing down DOGE - Blood in the Machine

The real reason Meta's bleak 'AI vision' is winning out - Blood in the Machine

Anatomy of an AI Coup - Cybernetic Forests

Not with a bang.

Things I've Been Up to This Week

Academic Pre-Pub: "Stop Treating AGI as the North-Star Goal of AI Research."

Phantom Power Podcast

AIxDesign Fest!

Helpful Bluesky Things

Sign up for Cybernetic Forests

Government by Grok - Blood in the Machine

Announcing the Escape the Algorithm ᵐⁱᶜʳᵒsupporter Program - escape the algorithm

The Critical AI Report, January 2025 - Blood in the Machine

A Fork in the Road - Cybernetic Forests

AI is an Excuse

How Humanity Disappears

An Automated Autocrat

Reaching for Digital Distance

The Case for Diversity in AI

Phantom Power Podcast

AIxDesign Fest!

Fun Bluesky Things

A Note to Subscribers

Sign up for Cybernetic Forests

The Great Undermining of the American AI industry - Blood in the Machine

Academic Pre-Pub:
"Stop Treating AGI as the North-Star Goal of AI Research."