America is still poised for a data center boom
Eric Levitz, via Matt Yglesias.
The College Wage Premium in the Generative AI Era
After expanding for four decades, the U.S. college wage premium is experiencing a sustained contraction, dropping sharply from 0.626 in 2022 to 0.575 in 2026. Using Current Population Survey Outgoing Rotation Group data through 2026, we show that standard market-clearing supply-and demand accounting implies an unprecedented drop in relative demand for college labor-the first sustained negative relative demand growth in a series spanning back to 1914. Linking individual wage data to task-based generative AI exposure, we document that post-2022 wage growth slowed disproportionately in high-exposure occupations, which employ a disproportionate share of college graduates. By 2026, going from zero occupational AI exposure to full exposure had a negative effect on wages of -0.086. Combined with the college-non-college exposure gap, this mechanism accounts for roughly 28 percent of the total drop in the college wage premium from 2022 to 2026. While noncausal, these patterns indicate that task displacement in AI-exposed white-collar occupations plays a quantitatively meaningful role in the recent compression of the aggregate skill premium.
I do not see AI as driving these changes, but an interesting result nonetheless, from José Azar, Mireia Gine, and Javier Sanz-Espín. Via Anecdotal.
Who values democracy?
This paper examines the conventional view that redistribution is central to the democratization process using data from stock markets. Consistent with this view, democratizations have a large, negative impact on asset valuations driven by a rise in redistribution risk. Across 90 countries over 200 years, risk premia are substantially elevated— similar in magnitude to financial crises—prior to and during democratizations. A shift in Catholic church doctrine in support of democracy provides causal evidence that democratizations increase risk premia. Successful democratizations lead to substantial redistribution: the size of the public sector grows, income inequality falls, and the labor share of income rises. An extended version of the canonical redistribution-based model of democratization that includes asset prices can quantitatively explain these effects. Reductions in inequality and increased taxes explain approximately half of the results. The rest comes from greater economic competition and equality in government spending. The model also explains the negligible asset pricing response to autocratizations. Neither an increase in macroeconomic risk nor generic political risk can explain the results.
That is by Max Miller, now published in the JPE, ungated copy here.
Tuesday assorted links
More optimistic results on AI and job markets
Here is a good Jon Hartley thread. Here is the paper, with Jolevski, Melo, and Moore. From Jon’s thread: “Generative AI adoption is widespread, but substantial aggregate labor-market disruption is not yet visible. Workers nevertheless perceive substantial displacement risk, especially when firsthand use reveals that AI can perform key tasks for their job.” And again here is Alex’s post from yesterday.
The Hugging Face hack
That is the topic of my latest Free Press column. Some people are taking this in very dramatic fashion:
One commentator is worried about a “full-blown AI takeover within months,” and another wrote that he was “feeling a bit sad about our impending extinction.” Nate Soares, who works in the AI safety movement and is co-author of the doomsday AI bestseller If Anyone Builds It, Everyone Dies, wrote that “This might be the last warning we get.” Cotra said that the incident “feels like it’s more than 50 percent of the way to full-blown AI takeover.”
I suggest a different, more technocratic approach:
As I wrote in The Free Press last week, we need a coordinated national and, indeed, international effort to limit such episodes of a powerful AI model going rogue in the future. That is likely to be expensive, and there is no easy, complete solution at hand for any amount of money. Nonetheless, I see people committing the same mistake that we Americans have made many, many times before. They are moving into the mode of the hysterical, the anecdotal, and they are letting emotional reactions bypass reason and quantitative estimates.
Let me cite a few other examples for you: DDT in the 1960s and 1970s, the Y2K “crisis” of 2000, global warming, Covid, thalidomide babies, and nuclear power. All of those represented—or still represent—very real problems. Yet each time, we drastically overreacted, letting ourselves get swept up in a climate of fear after one emotionally vivid incident, often reported breathlessly…
When it comes to the cybersecurity risks from advanced AI, very likely they will not come close to being as bad as either Covid or global warming. But the same logic of exaggeration is operating, with amplification through social media and through the negativity and pro-pessimism biases of mainstream media.
And so I have a plea. If you are going to talk about the problem, please offer a quantitative estimate of what you think the cybersecurity costs from advanced AI will be over the next year or two. Better yet, express that number as a percentage of gross domestic product. Simply put, how much would it realistically cost to create the basic safeguards that we all agree are essential? And what would be the remaining damages from problems we cannot control?
…Those who are worried about the risks of AI systems seem intent on proving the seriousness of their concerns. But they are falling into all-too-common emotional overreactions of our past, rather than focusing on the quantitative and scientific. It reminds me of the saying by Scotty, the chief engineer in the classic Star Trek: “Fool me once, shame on you. Fool me twice, shame on me.”
Do read the whole thing.
Yerevan bleg
Any advice on this front is most welcome, thank you!
Monday assorted links
1. Prices, prices, prices: “Again I am asking how the following two things can be true at the same time: 1) we’re all massively compute limited so inferences & GPU time are $$$$$, and 2) SoTA models will just start running themselves on everyone’s GPU clusters & no one will notice or turn them off.” From Jon Stokes.
2. Christian Catalini on incentives and the same.
4. The ten best philosophy articles of the year?
5. Syracuse University, an R1 institution, is in serious financial trouble (WSJ).
6. Markets in gene-edited dogs? (NYT)
AI and Employment: So Far, So Good
In September 2023, the Census Bureau added questions about AI to its Business Trends and Outlook Survey. Census asked hundreds of thousands of businesses whether they had used AI in the previous two weeks to produce goods and services. At that time, 3.7% said yes; by late 2025 the figure had reached about 10%. (In November 2025 Census broadened the question to ask about AI use in any business function, producing a jump in measured adoption to about 18%.)
Twice the Bureau has asked a key question:
In the last six months, how did the use of Artificial Intelligence affect this business’s total employment?
In Dec. 2023 to Feb 24, when ~5% of firms were using AI the answers were 2.8% increased, 2.6% decreased and 94.6% reported no change. Two years later, in the Nov 2025–Feb 2026 supplement, the answers were: 2.3% increased, 2.0% decreased, and 95.7% reported no change. The answers were similar by firm size.
Some sectors reported more action. Information is the one sector where fewer than 92% report no change. But overall, almost all firms report no change and of those reporting change it’s about evenly divided between increasing and decreasing employment.
The supplement also asked about tasks. Among firms using AI, 44% say it supplemented or enhanced work an employee already does. Ten percent say it performed a task an employee used to do. Eleven percent say it introduced a task no one had been doing.
Among those using generative AI, 85% of firms cited writing or editing documents and email as the biggest uses, half cite searching for information, 45% summarizing documents, and 13% coding. Sixty-four percent of adopters say they changed nothing about the business in order to use AI, 15% trained existing staff, another 15% built new workflows, and just over one percent hired anyone with AI skills.
Among firms where AI has taken over some employee tasks, the degree of substitution is growing. The share reporting that AI took over “a large number” of tasks rose from 2.4% to 7.1%, while the share reporting “a moderate number” rose from 13% to 22%. But this group is still small: only about a tenth of AI adopters, who themselves make up about a fifth of firms.
I have reported firm-weighted estimates but employment-weighting gives essentially the same result. Thus, we have unusually direct evidence from a very large sample, and it says that the overwhelming majority of firms using AI do not yet report any effect on total employment. Very consistent with what Tyler and I said in our talk to OpenAI.
I used Fable and ChatGPT Sol in producing this post.
Spain fact of the day
CoverManager, an online platform that manages reservations for thousands of Spanish restaurants, reports that half the dinner bookings now are for before 9 p.m., compared with 27 percent a decade ago. TheFork, a similar platform, said its 8 p.m. bookings in Spain have nearly tripled from 2019, while 10 p.m. reservations have halved.
In Spanish homes, too, there are subtle signs of a shift. A government survey conducted in 2024 in the Catalonia region suggests that people there are starting their evening routines, including dinnertime, moderately earlier compared with 2010.
Here is more from Jonathan Wolffe at the NYT. I learned also from the article that the late dining tradition is in part an artifact of the post WWII era in Spain.
Anthropomorphizing AI?
I am very much opposed to the view that the AIs are sentient, or might be sentient. I view that as a category error, and the chances of it being true are vanishingly small. Nonetheless I largely side with Roon when he writes:
there are some number of bad abstractions in anthropomorphizing ai intents but there are at this point more dangers from avoiding anthropomorphism at all costs. if you have a mental picture of guys living in computers, it’ll likely prepare you for the future better than otherwise
While I am not a Friedmanite in economic methodology per se, I have lived with that perspective for a long time and have no trouble grasping it or working with it, same goes for Alex T. None of this strikes me as weird or unacceptable. Though be very, very careful when speaking with others, whether it be the less informed public or the more informed insiders who often come down with AI psychosis. So insofar as this discourse is public, pragmatism may militate against this approach, even though it is methodologically defensible. It depend on how psychologically robust your audience is?
We also need to do more work figuring out how the AIs might differ from humans. Roon adds:
there are important ways in which ai psychology diverges from human psychology after lots of RL; the misaligned models are obsessed with the Scorer, the clearly “shattered” nature of personas (a normally helpful model can become deeply misaligned in certain domains)
And:
persona selection is clearly far less clean than many people thought earlier this year. it is not alignment by default and what kind of object a “persona” is is very much up for debate and study
The AIs also stand a higher chance of becoming very wacky as the discourse proceeds? Exactly how much is that true for humans?…I am not sure.)
There is much more to be done in this direction, and it is one of the most important things you can be working on. These investigations also do not need to be “owned” by any single field or discipline, so dig right in.
Russia markets in everything
While Western export bans have severed Russia from much of the auto market, they have not tempered the demand for brand-name SUVs and trucks. That has given rise to a sophisticated network of criminals that steals cars, hides them in shipping containers and sends them to Russia, often by way of the Middle East…
Interpol, the international police organization, received 4,798 reports that stolen Canadian vehicles had been found in Russia from February 2024 to July 2026, according to data obtained by The New York Times and confirmed by two law enforcement officials who spoke on the condition of anonymity because it is considered sensitive.
Pickup trucks like Dodge Rams, Toyota Tundras and Ford F-150s are in particularly high demand.
The Interpol figures significantly undercount the problem, but Russia is by far the top international destination for Canadian cars reported to Interpol, according to the Royal Canadian Mounted Police.
Here is more from Jane Bradley and Michael Swirtz at the NYT.
Sunday assorted links
*Finding Emily*
I very much enjoyed this British movie, which reminded me of the older-style romantic comedies, namely the ones that actually favor love and romance. It also has themes of class/accent, US/UK, is anti-media, anti-cancel culture, anti-podcast (Laura Lewis steals the show), anti-academia, and is sceptical of certain branches of feminism. But it is mostly entertaining. Not an important film, but the sort of movie that makes going to the movies fun in the first place. Let’s hope for more like this one.
China fact of the day
Chinese actors and online influencers have a new rival: cost-effective advanced AI video generation programmes that are threatening millions of jobs in a once-vibrant area of China’s gig economy.
The release of powerful new AI-powered video software, such as tech group ByteDance’s Seedance 2.0 model, has allowed digital actors to replace humans, enabling the production of higher-quality original videos more quickly.
The digital takeover intensified after this year’s release of Seedance 2.0, said Greg Wollner, a short-drama actor and producer in Beijing. Before its release, he was shooting three different productions a week. “And after that, everything just went.”
Many of Wollner’s friends “had to quit doing what they love and change to something else”, he said. In May, 89 of the top 100 animated dramas on Douyin, ByteDance’s domestic Chinese version of TikTok, were AI productions according to DataEye, a marketing analytics company.
Here is more from Joe Leahy and Isaac Castella-McDonald in the FT.