Max Read

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two photos of mark zuckerberg taken one month apart. on the left, his chain is visible, on the right, his chain is hidden
If Weiss is exceptional, it's only in her knack for making a spectacle of the sort of things that slicker operators in media say and do all the time without causing too much of a fuss. When her CBS Evening News released "five simple principles" guiding its coverage, among them "We Love America," I thought back to the equally fatuous declaration by Weiss's old patron on the New York Times opinion desk, James Bennet, that the editorial page is "pro-capitalism." Bennet said this in a private meeting, a video of which was later leaked. CBS Evening News announced that it loved America in a thread on the Nazified shell of Twitter.
In some sense there is not much to say about this. The story isn't very good, but it superficially resembles a good story (as many people have pointed out, it reads a bit like a pastiche or parody of a certain kind of lyrical Anglophone global-south magical realism), which is both the kind of thing we might expect AI to be fairly at producing and also the kind of "good-shaped" bad story we might expect an inattentive or overextended editor or judge to reward. (Pangram, the company behind most reputable AI-detection software, claims that two of the other Commonwealth Prize winners from this year, and one from last year, are likely fully or partially AI-generated. The Commonwealth Foundation has declined to revoke any prizes, citing the unreliability of AI detectors and "legal parameters.") At best the events confirm what we already know, or should have known: One, it's very easy to produce short passages of competently arranged text with a chatbot but much harder to generate writing at length whose effects survive a close read; and two, literary and cultural institutions are not the well-resourced and unimpeachable pure meritocracies we might hope them to be. (We might add, three, that humans are also notoriously bad writers and readers; indeed, we invented "superficially good writing" and "shallow perfunctory reading" thousands of years before LLMs perfected these skills.)
There are many ways to look at The Drama: As a bit of glib provocation from a Euro bad-boy auteur (it’s not); as a deranged and highly successful rom-com (it mostly is); as an exploration of narrative and linguistic performativity in the Austinian sense (sure, why not); as a vehicle for a perfect 5-minute cameo from the great Jeremy Levick (100 percent). Personally, and surprisingly given its aggressive contemporaneity, I found myself thinking about The Drama in the multi-century lineage of Much Ado About Nothing, or (more provocatively) Dion Boucicault’s The Octaroon--“damaged-goods” dramas and comedies about weddings derailed by “terrible” revelations about the betrothed. (What it means that in this case Emma’s “damage” isn’t sexual impropriety or racial impurity but “school-shooterness,” a kind of potential for anti-sociality, is a fascinating question for more qualified people. Gotta go!) Above all else, though, The Drama is the best movie I’ve ever seen about the differences between Millennials and Zoomers.
I thought of Winter’s son’s “certification” in A.I. when reading 404 Media’s report this week on a new bipartisan bill proposing an N.S.F. grant to promote “AI literacy” in schools. Both partake of what I think of as the “forklift model” of A.I. education, so-called because it treats A.I. more or less like a forklift: a complex and potentially dangerous piece of industrial equipment whose use must be taught in a formal sense, and in whose practice students might become “literate” or “certified” to better their future chances of employment. This attitude toward the role of A.I. in education (or, really, vice versa) is a natural outgrowth not simply of institutional anxiety about the necessity of traditional education after the advent of the all-knowing, all-seeing, all-doing chatbot, but also of the increasingly pervasive idea of college as mostly an employability signal--rather than mostly an education--described by my friend Jay Kang in his recent New Yorker column about the post-A.I. uneases felt in higher education. One response to this kind of cynicism--now widespread, as Jay documents, among the college-aged population--is to embrace it. If college is already effectively a certification process, why not formalize it as such, and refashion the general-education program into a quasi-vocational one, in which students receive the white-collar equivalent of a C.D.L. or forklift certification?
What Tottenham have is a roster filled with explosive athletes who can run. Using their physical metrics, Gradient created an "athleticism" score that's a combo of endurance, explosiveness and speed that adjusts for position and size. It's on a 1-100 scale. Tottenham have seven players at a 90 or above and five of them -- Wilson Odobert, Lucas Bergvall, Archie Gray, Dominic Solanke, Conor Gallagher -- were signed after Johan Lange became the club's technical director in October 2023. The first four were the four outfield players signed during Lange's first summer in charge.
For all the revolutionary, transformational promises of A.I.--for good and for ill--the problems it causes all seem quite familiar. My perspective on this is admittedly shaped by a 17-year career in digital media that I would describe as “de-sentimentalizing,” at a minimum. To work as a journalist online over the past decade has generally meant--with only a few exceptions--to be producing text inside a system that prioritizes speed, volume, and attention over any other attribute, including and maybe especially those you’d associate with “quality.” At some publications, institutional identities and imperatives can militate against sloppiness, unreliability, and banality. But the external pressures and incentives toward slop are enormous and un-ignorable. And that has been true for many years, since well before A.I. offered a tantalizing push-button interface for high-volume content production. All the problems of A.I. writing--inaccuracy, misinformation, plagiarism, misrepresentation, and, above all, hack work--were widespread in the early days of blogs¹ and throughout the digital media boom years, accelerated by the Facebook News Feed and other platform distribution schemes.
Sim Latina
Alex Rain (Olivier Gruner) in the 1992 sci-fi actioner NEMESIS
This is not a particularly satisfying set of findings insofar as it validates neither the A.I.-booster “it’s so over, A.I. writing is better than human writing” side nor the A.I.-skeptic “A.I. can never write like a human” side. What we can say is that people mostly can’t identify A.I.-generated text as A.I.-generated (crowd boos), but they can sometimes distinguish between it and human-authored text (crowd cheers); it’s just that they tend to think the A.I.-generated text is human (crowd boos), maybe because human-generated text is stranger, worse, or more difficult (crowd hesitantly cheers), which readers mistakenly believe is more typical of A.I.-generated text (crowd silent now) and thereby disprefer (crowd sort of murmuring confusedly), unless you tell them it’s actually human, in which case they change their minds and like it (crowd has mostly left at this point).
This hadn’t gone exactly how they’d like. In December, Bloomberg reported recently, “a senior US defense official posed a hypothetical scenario” to Amodei: What if a nuclear-armed intercontinental ballistic missile were hurtling towards the US with only 90 seconds to spare, and Anthropic’s AI were the only way to trigger a missile response to save the country, but the company’s safeguards wouldn’t allow it, the senior official mused in a December phone call. “Call me,” was how Pentagon officials interpreted Amodei’s answer, according to another senior defense official briefed on the discussion, who described being astounded by the billionaire’s response. LOL. Our beautiful generals have many medals and some even have battlefield experience, but I can say with some confidence that they have never engaged with a Rationalist online and are deeply unprepared for what it means to pick a fight with one.
What this does to military A.I. capabilities is beyond the brief of this newsletter, except to say that I think it’s “bad” for Grok, the pedophile mechahitler A.I., to be involved with weapons in really any way. What I am interested in, here, is what this reveals about the state of politics in Silicon Valley. In a sentence, I think what’s happening is (1) basic (i.e. normal) cutthroat competition between rival firms for government contracts, which is both driving and being driven by (2) an open and ongoing political-ideological dispute between two factions of Silicon Valley capital, which is in turn informing and being informed by (3) an almost religious disagreement about the nature of the god being built on the computer.
This time last year, at the height of the backlash-to-the-backlash, “artificial general intelligence” was on the tip of every booster’s tongue and everyone was (reportedly) asking each other “can you feel the A.G.I.?” This time around, “A.G.I.” doesn’t seem to be coming up as much, despite the fact that the current state of the technology makes a much greater claim on the idea. Instead, the operative framework for understanding where A.I. is headed is “remember the week that the N.B.A. shut down?” The pandemic is not a cheery metaphor, precisely, but it is a practical one: An experience everyone participating in the discourse has lived through. The world on the other side of the pandemic is different--worse--but not unrecognizably so. For all that the “it’s February 2020!” claim is meant to alarm and disquiet its readers, it’s not really a messianic or eschatological fable but a social and economic parallel, and I think its popularity is, counterintuitively, an admission that even as A.I. continues to make impressive advances, the range of credible futures is narrowing.
I wouldn’t personally endorse it, but “The Flight 93 Election” has been useful over the years for understanding a rational core of MAGA. For people like Anton, voting for Trump is a logical, justifiable, even sane choice: the high-risk unknown outcome over the guaranteed bad one. I’ll admit, as an argument, it’s overwrought and hysterical, and in real life Flight 93 did crash and kill everyone on board. But it’s a metaphor, right? The point is that Trump offers a high-risk alternative to a deadly flight path, not that it would be cool and heroic to crash a plane in the middle of a field and die… … Right?
But even beyond the demographic specifics of early Gawker, to be a regular commenter anywhere1 is to constantly put yourself in a subject position all but guaranteed to develop the kind of resentment that powers Trumpist politics: Your voice is (literally) suppressed, made subordinate, often hidden; your intelligence and expertise receives a fraction of the attention of the glib P.M.C. blogger you’re responding to, whose attention and approval you both scorn and desire. Among the altogether too many “unfortunate and stressful experiences I had at Gawker that in retrospect prefigured the political dynamics of the Trump era” was the Gawker Hack, in which chat logs between Gawker writers (among other proprietary information) were leaked to the press, including one in which Richard Lawson (now writing the great Premiere Party newsletter) referred to commenters as “peasants.” Any sane person who has ever read ten words of Richard’s writing could immediately and easily identify this as a joke--but many Gawker commenters, paranoid about their own position relative to the writers, neurotic about their emotional investment in a site that mostly ignored their contributions, took real and sustained offense. For years afterward,2 commenters would sometimes refer back to the gag with geniune hurt, seemingly imagining themselves as the Forgotten Men of the Gawker empire (such as it was), discarded and disdained by the haughty bloggers.
Where Musk’s real power lies, and what makes him politically dangerous to confront directly, is not (as may have been the case just a few years ago) in his charisma or his money, or even his control of the flows of attention on X.com. It’s that he’s made the site--the essential global reactionary communication and organization app--co-extensive to himself. Even as his personal popularity has plummeted and his political capital has vaporized, Musk remains a key man to the global right-wing project, because X.com would collapse (or be moderated out of useful existence) without him. Republicans and right-wing parties across Europe have no choice but to defend him to the death, for fear of losing an essential source of attention and parade of marks for their grifts. Unlike the Trump administration, which could survive a post-Musk world, X.com has no choice but to keep Musk in charge. But Musk himself is not popular, has no juice, no aura, no special ability. The fact that he is lashed existentially to X.com and therefore to the right wing at large is as much a liability for the site and the reactionary project it houses as it is a asset to him. His site, and its dedicated users, are breaking laws in dozens of countries, and his only response has been to joke about it. Someone should do something about that. There’s nothing to be afraid of and there’s no reason not to.
But I remain drawn to my original definition of slop, even as I acknowledge its weaknesses, because I think it correctly emphasizes the forms and conditions of slop consumption, rather than focus solely on the means of its production. “Slop” is probably better positioned as a symptom of “the feed,” the binge-watch, the subscription service, and an overall culture of convenient consumption than it is as a symptom of a particular technology. Put a little more directly, maybe we should start thinking of the technology of generative A.I. as a product of a culture of slop than the other way around.
One way of thinking about Twitter, especially in the Elon Musk era, is as the latest and most sophisticated version of the mailing lists that have powered the conservative movement, and the various scams and cons and schemes that constitute it, since the 1960s--in other words, as a huge and immediately accessible collection of suckers, waiting to have their avidity and paranoia exploited for cash. The predictions markets here are happy to play the same role with heavy X.com users as crypto scams and meme-stock hustlers did on the same site a few years ago, or as cash-for-gold ads did with Fox News viewers a decade before that, or as direct-mail get-rich-quick schemes did with Goldwater voters deep in prehistory.1 But the demand for dumb money created by the increasing annexation of our everyday social and cultural lives into casino-market hybrids like predictions markets (or, arguably, social media itself2) isn’t going to be satisfied solely by a pre-existing population of Birchite suckers. We talk a lot about the “male loneliness crisis” but in my estimation we don’t talk enough about the “male suckerfication crisis”: The process by which young men are continuously cultivated--by politicians, influencers, podcasters, sportscasters, and the very structure of social networks--as dupes and suckers, both for the enrichment and empowerment of Trumpist politicians and movements but also in service of the profits an ever-expanding roster of gambling and gambling-adjacent industries, among them app-enabled retail day-trading, crypto speculation, predictions markets, and of course, actual sports betting.
This, I think, is the basic dynamic from which Platform Temperance evolves: a general, non-partisan, somewhat moralistic disgust at even the non-political outcomes of unregulated and unmoderated platforms and a dissatisfaction with both the “revealed preference” framework that justifies their persistence in Silicon Valley and the more rigidly behavioralist explanations that seem to exonerate the business model and blame externalities on bad actors. To this I would add environmental factors like: A perceived accelerating downward spiral with the advent of generative A.I., which both further debases the platforms and provides a possibly even more tractable and dangerous user experience itself; a generation of (middle-class) millennials, now raising children in a world dominated by slop and screens, coming into political power; a vaguely moralized sense of unease and distaste over the fast creep of gambling and gambling-like dynamics in financial and prediction markets; a recognition, in the wake of the reactionary turn of prominent tech executives, that Silicon Valley is not going to “fix” any of this itself; and a growing sense among liberals, Democrats, and anti-Trump Republicans that social platforms are inevitably corrosive to the liberal-democratic project. In response, Platform Temperance offers a focus on health, social welfare, and the idea of discipline and restraint in the face of unmoderated consumption--that is, temperance.
This burgeoning movement seeks to root criticism of (and response to) Big Tech in ideas of health (public, social, intellectual, and spiritual) and morality rather than size and power, positioning the rise of social media and the platform giants as something between a public-health scare and a spiritual threat, rather than (solely) a problem of political economy or market design. I see versions of this school of thought not just in speeches and op-eds from Auchincloss and Cox or blog posts from Thompson, but in Chris Hayes’ book The Siren’s Call and in the inescapable work of Jonathan Haidt. (You might broadly think of Hayes and Haidt as representing “left” and “right” tendencies of the broader movement.) Notably, all of the above-mentioned have found platforms on Klein’s podcast. Back in a January interview with Hayes, Klein offered up a kind of political vision or prediction rooted in this tendency:
In another Reddit post that year, Platner reflected on his life after his military service, saying he was “a vegetable growing, psychedelics taking socialist these days. After the war, I’ve pretty much stopped believing in any of the patriotic nonsense that got me there in the first place, and am a firm believer that the best thing a person can do is help their neighbors and live a loving life.” “Still got the guns though,” he added. “I don’t trust the fascists to act politely.” In his interview with CNN, Platner wanted to assure voters: “I’m not a communist. I’m not a socialist. I own a small business. I’m a Marine Corps veteran.”
If it works, then we might look back on Sora as the moment OpenAI settled in and allowed itself to be fully annexed by the social-platform sector--the A.I. boom ultimately less a regime change than the minor origin story for the latest entrant into small club of mega-platforms minting money from targeted advertising. But… will it “work”? What makes social-media platforms like Instagram and TikTok so wildly successful is the extremely favorable unit economics: The marginal costs of hosting and serving videos is negligible, while the cost of creating the content is off-laid to users, so the platforms can grow effectively unimpeded. Sora, by contrast, internalizes the costs of creation, which are still significant (if improving): Every new video generated by a user costs the company more money. There’s no easy way out of this dilemma. We’re a long way off from inference costs dropping so low that the marginal cost of generating videos is as insignificant as that of hosting or serving them. And, as the viral success of Sora over the more consumption-oriented “Vibes” suggests, the real attraction of this type of A.I.-video app seems to lie in the quality and versatility of what it can generate, not in the experience of raw-dogging a feed of slop. In which case we might look back on Sora as pivotal in another direction--a failed gambit to turn OpenAI into the next Meta, rebuffed by the economic logic of the tech itself.
This is a fantastic amount of money, and in other industries, or for other companies, the quickly growing revenue and falling costs might be enough. But this is Silicon Valley, and ChatGPT is the fastest-growing app of all time. This week Altman said that it has 800 million weekly active users, which probably puts it in spitting distance of Facebook for size--and yet Meta brought in $164 billion last year. In a strange sense, had ChatGPT grown more slowly, OpenAI might have trundled along as a straightforward subscription business with the expectation that eventually the revenue from its subscriptions would outpace the cost of providing its services. But in our universe, where Altman and his investors are seeing 800 million people hit the website every week--99.75 percent of whom aren’t paying for a subscription--different business models become attractive as well. Like, say, Meta’s: Why not build your model into a social feed, against which you can sell advertisements? (Certainly, Meta itself has had this same idea, hence “Vibes.”)
One Battle After Another is a political thriller, an action movie, and a family melodrama. It is also, unexpectedly but importantly, a car movie. By this I mean, on the simplest level, that it is a great movie through which to Remember Some Cars. I was thrilled, for example, at the sudden appearance of a 2005 Toyota Yaris1, driven by Willa Ferguson’s friends to pick her up for the dance:
Read Max: Let me start with how you pegged early on that this guy was not a Groyper.1 I mean, stipulating that we still don't fully know everything about everything, but it seems pretty clear, based on the indictment, that this guy had a different thing going on, which is what you’d been saying from the beginning. Why did you key in on this guy's particular online identity? Ettingermentum: Well, I'm 23 years old. That's why. That was the reason. I lived through the same kind of cultural, memetic era that he did, and the moment that I heard about the bullet casings, I instantly recognized what kind of person this was, because I knew them. I went to school with these kinds of kids. I was also active playing video games like everybody else my age when I was in middle school and high school, and I just instantly recognized the humor. It brought me immediately back to middle school and high school. It's kind of funny and a little embarrassing for the guy. Beyond all the other shit he has to be embarrassed about is the fact that all of his classmates remembered him as a “Reddit kid,”2 with this kind of corny internet humor. Not really confident enough to make his own jokes. I mean, I could describe it a thousand different ways. He's like--people know these guys as band kids, because they always happen to be in marching bands and stuff. Read Max: Okay. Right. I'm 39, “band kids” is familiar to me. That's a long-standing type.
But in general I think that in this case, and in many cases of “uncanny” encounters online, much of what is theorized as the strangeness of “A.I.” can more likely be chalked up to something like “culture clash.” Americans still underestimate how much of the internet is non-American, and even non-European; huge swathes of social media are Indian, Indonesian, Nigerian, and, yes, Brazilian. These countries have large, educated, English-speaking middle classes connected enough to share many cultural norms and references with American audiences, but also large and secure enough to also bring their own norms and touchstones to the table. For a variety of reasons, platform-content entrepreneurship is viable and attractive business proposition in many of these non-Western countries, but attempts by social-media entrepreneurs to capture American (or English-speaking) audiences will definitely come accompanied by rough edges--bad translations, misunderstood references, more condensed milk than Americans are used to. “Weird things you might encounter online” are not always, like, Terrifying Dark-Age A.I. Artifacts of our weird and uncanny future. Sometimes they’re just Brazilian!
Eons ago, I wrote a piece called “The A.I. backlash backlash,” about a pendulum swing, then occurring in what I suppose we’d call “the discourse,” against a previously dominant cycle of A.I. backlash (which itself was a reaction to a dominant cycle of A.I. hype that dated back to the debut of ChatGPT). At the time, L.L.M. chatbots had improved significantly over the preceding 18 months; many people had managed to incorporate A.I. into their work in ways that seemed useful to them; and the “vibe” in Silicon Valley, as New York Times columnist Kevin Roose wrote had the time, had “shifted” to anticipate so-called “artificial general intelligence” on a short timeline. In the hothouse hubs of A.I. Discourse (X.com, Substack, Bluesky), the hype was bubbling up, and the skeptics and critics seemed to be in retreat. But, as the man says, Want to feel old? That was March. In the five months since Ezra Klein wrote in his Times column that “person after person… has been coming to me saying… We’re about to get to artificial general intelligence,” Meta has announced efforts to reorganize and downsize its A.I. division; NVIDIA’s “tepid” revenue forecast is suggesting a wide slowdown; Sam Altman is warning that “investors as a whole are overexcited about AI”; and Gary Marcus, prince of L.L.M. haters, is on his fifth or sixth victory lap. The renewed hype has sputtered; the most fervent enthusiasts have become disillusioned; critics reign triumphant: The backlash to the backlash to the backlash has arrived.
In general, OpenAI has liked to present itself as anything but normal--a new kind of company producing a new kind of technology. Altman still likes to go on visionary press tours, forecasting wild and utopian futures built on A.I. Just this week he told YouTuber Cleo Abram that In 2035, that graduating college student, if they still go to college at all, could very well be leaving on a mission to explore the solar system on a spaceship in some completely new, exciting, super well-paid, super interesting job. But far from marking a break with the widely hated platform giants that precede it, the A.I. of this most recent hype cycle is a “normal technology” in the strong sense that its development as both a product and a business is more a story of continuity than of change. “Instead of measuring success by time spent or clicks,” a recent OpenAI announcement reads, “we care more about whether you leave the product having done what you came for”--a pointed rebuke of the Meta, Inc. business model. But as Kelly Hayes has written recently, “fostering dependence” is the core underlying practice of both OpenAI and Meta, regardless of whether the ultimate aim is to increase “time spent” for the purpose of selling captured and surveilled users to advertisers, or to increase emotional-intellectual enervation for the purpose of selling sexy know-it-all chat program subscriptions to the lonely, vulnerable, and exploitable: