Big Tech is about data politics. Time to bone up on it.

Tressie McMillan Cottom, Want to Fight Back Against Big Tech? Start Here. NYTimes, August 3, 2026. She begins:

In June, I wrote about how the data center revolts happening across the country get to the heart of our greatest political problems. Artificial intelligence is not just a market product or a scientific achievement. It is a political theory. And it is gobbling up our democracy.

The challenge this presents to a functioning democracy is immense. Democrats cannot just “win the midterms” and go back to life before Donald Trump and his army of tech bros upended our way of life. We can talk about reforming the Supreme Court, ending the filibuster, enshrining women’s autonomy in the Constitution and getting money out of elections. But those things won’t matter if we don’t change our laws and norms about what I am calling data politics.

All of the speculation and hype around A.I. is hiding the fact that the technology isn’t just large language models or agents or data centers. It is the backbone of a superstructure that merges regressive politics with unchecked economic power in the guise of technological innovation. Put simply, there is too much money, some of it too untraceable, giving a small group of unelected people too much power over the people. That’s data politics.

Data politics is the right’s answer to what’s next after Trump: more Trumpism, without the man who gave away the country’s store for personal gain. What should the left’s answer be?

She then goes on to list a bunch of books people should read.

AI populism and the rejection of robot overloards & their techbro minions

Ezra Klein, The A.I. Giants Weren’t Prepared for This, NYTimes, Aug 4. 2026

What is big, ugly and has united Republicans and Democrats at a time when it has felt like nothing else could? A.I. data centers.

Last August, a Heatmap News poll found that approximately four in 10 voters would oppose a data center being built where they live. By May of this year, opposition grew to seven in 10. Gov. Ron DeSantis, of Florida — a Republican, of course — proposed legislation that was known as an A.I. Bill of Rights.

Senator Bernie Sanders called for a national data center moratorium — one of more than 100 local or statewide moratorium proposals across the country. And here in New York, Gov. Kathy Hochul, not usually thought of as a hard-core populist, just imposed a one-year moratorium on data center construction.

So I wanted to get into the fight over data centers. How much of this is really about water or electricity or aesthetics, and how much is about A.I. and the companies that are behind it?

My guest is Jasmine Sun. Jasmine has been doing excellent coverage of both the culture inside the A.I. companies — an unusual culture — and the anger that is building against them in the rest of the country.

Here's one excerpt from a much longer interview:

You have a very influential definition of A.I. populism where you call it a worldview in which A.I. is viewed not only as a normal technology but as an elite political project to be resisted.

The phrase that you hear a lot from A.I. critics is: Why is this being shoved down our throats? Or with ChatGPT, it’s not that people are saying there is literally no use for ChatGPT, it’s people are saying: Why are you forcing me, at my job, to use A.I. to do something worse when I could do it better?

And so I think that a lot of the public backlash to A.I. that has arisen over the past six months is not explained by people thinking that the technology has no use at all. It’s not explained by their being worried about specific technical properties of large language models that might lead to rogue A.I. or misalignment or whatever, which are the safetyist arguments.

It’s A.I. as sort of an avatar for a small group of Silicon Valley billionaires’ ability to impose their vision of the world onto everybody else without their consent.

And I think that’s also what I hear echoed in these data center debates. It’s not just: It’s going to use this much water or that much water. I frankly think that even if there was no misinformation about water use, people would be just as angry about the data centers. [...]

Maybe it will make things better, but I really don’t know. I think that the costs are going to be very, very high for us relationally and economically. And so I’m very conflicted.

But do I want to live next to a data center? Yeah, no. [Laughs.]

Yeah. It’s totally different.

That’s easier — somebody is just making you do that.

I mean, one of the most interesting things — back to back, I went to this Abdul-Bernie-A.O.C. rally in Lansing, Mich., and then I went and saw the Saline activists the next day, and I was researching how the Saline Stargate project happened. And it was really interesting to see these echoes of the populist message manifest in this specific project.

When I’m at this rally, people are talking about the oligarchy. They’re talking about corporate billionaires, whether it’s Big Tech or Big Pharma or DTE — the utility companies — paying off politicians in order to screw the people over. And that’s why you need the people to come together and to get money out of politics, to prevent DTE from donating to these super PACs and paying off Michigan Gov. Gretchen Whitmer, or whatever.

And then when I learned how the Saline data center saga played out, what happened was the Saline Township board, unlike a lot of boards, actually voted 4 to 1 against rezoning their land for the data center. So this was a case where local government said: This is not our vision for our community. It’s not worth it to us.

And what happened? The data center developers sued Saline Township, a town of, again, a few thousand people, saying: Wait, no, this is exclusionary zoning. You can’t have no industrial use in your entire township. And when a town of that size is getting sued by a giant A.I. data center developer, they just settled.

They were just like: Fine, give us a few million for the fire department and for some schools, and this fight is not worth it to us. But that, to people, felt like a profound violation of little-D democracy.

It felt like the dark money in politics story, which is: You have some very rich companies show up with a bag of money to your politicians. They don’t tell anybody else what’s happening. The politicians aren’t allowed to tell their citizens and involve them in the decision-making process, and they themselves work out a deal — a deal that is fundamentally asymmetric because of the amount of money on one side — that will then transform the image of your community, your lived reality, into the world that these tech companies have decided for you.

And so I think that the data centers, in that sense, are a very visceral microcosm of the way that a lot of people feel that A.I. is showing up in their lives.

I would also maybe even take that a little bit further.

I think the way that, not all of the A.I. companies — and I think Anthropic has largely been a good actor here — but the way many of them have acted has opened up such a chasm between what they say and then how they act under pressure, so that one should be incredibly, incredibly skeptical of them.

And what I mean by this is, Sam Altman and all these different people, in front of congressional testimony and in interviews, will say: It should not just be us making these decisions. There should be a real, deep, small-D democratic role here in how A.I. rolls out, in what effects it has on communities and how it is governed.

And then when a community, or a politician who’s representing a community, tries to say: Well, we don’t want this data center here. Or: We want to impose these regulations — we have watched, repeatedly, these companies turn tremendous amounts of financial artillery against whoever is standing in their way. And use the expertise and the money and the power they are amassing to short-circuit that democratic voice.

Yeah. I mean, a couple things. I think one big gap I noticed between Silicon Valley and the folks in these communities I was talking to is: Silicon Valley does tend to think that money solves all problems — that if you just make the check bigger, everything is going to be OK.

And I think people have a sense for: I’m being bribed. This corporation is not offering me a free lunch or whatever. There is going to be something that I’m losing here.

And, in fact, sometimes the fact that the data center deals were bigger, or the amount of political spending was bigger, actually just makes people more suspicious. In the Abdul El-Sayed Senate race in Michigan, his No. 1 hit on opponent Haley Stevens is how much money she is getting from AIPAC, from DTE, from Big Pharma or whatever.

And so I think we’re in a political environment where making the numbers bigger and the amounts of money bigger makes people more suspicious, not less.

Another one I’ll just quickly mention is, I don’t even think Anthropic should be let off the hook for things like the labor market impacts. They are the ones simultaneously warning that we might see 50 percent of white-collar jobs lost by 2030. They’re saying: This is really important to us, we’re freaking out about it.

Anthropic C.E.O. Dario Amodei has written in his essays that we might see an underclass of people of lower intellectual ability. And Anthropic is building the agents — they are building the coding agents, the banking agents, the design agents — that they know are going to displace jobs, or they believe, at least, are going to displace jobs.

And I think that people feel that hypocrisy, as well, which is: If you are so worried about the inequality, why are you building the agents to do it? And when I ask executives and researchers and whomever at Anthropic this question, they don’t really have a good answer. Because it is true that their business model is fundamentally premised on the disruption that they say they are causing.

You did a big piece for The Times on the very widespread belief in Silicon Valley that they will create this underclass.

Yeah.

What does the underclass mean to them?

The idea of a permanent underclass caused by A.I. is basically a world where any job a person can do, either A.I. or a robot can do it for them. Which means that workers lose all the economic leverage they have, and capital owners — people with money — can simply pay machine labor to do all the work instead of paying workers.

What that means is anyone who earned their living by working is no longer able to do that. You end up with a world of runaway inequality, where the rich get richer and the working class gets poorer. Maybe they get some welfare checks, but fundamentally, it’s a loss of economic mobility in a society.

And when I ask folks in Silicon Valley: Do you think by default A.I. is going to increase or decrease inequality? I have not yet heard anyone say it will decrease inequality or keep it the same.

They might say the floor will get really high. They might say A.I. will bring the cost of consumer goods down, and so people’s lives are going to get cheaper, and everyone will be superhealthy, so it’s OK. But I have not heard a single person in the tech industry tell me that they believe that A.I. is going to decrease inequality.

In fact, many people are very worried that instead, most workers will lose their leverage and be on a kind of permanent welfare in the far-off future.

There's more at the link.

Maggie Haberman on Epstein

From a long interview with Ezra Klein in the NYTimes (July 31, 2026):

It started with Jeffrey Epstein last year, and we get into that extensively in the book. Right after the 12-day war is the Epstein crisis — and I’m calling it a crisis. What it actually is is a multi-administration failure to deal with a pedophile, whom people of both parties found entertaining or useful or whatever. But it was the MAGA movement leaders who had been talking about a need for transparency over many years leading up to Trump’s election in 2024.

Obviously there's more at the link.

The Trap of the Digital Double

Catherine Shannon, The Trap of the Digital Double, NYTimes, July 31, 2026.

Everything is strange. We work from home. We socialize online. Our private lives are increasingly public. People pretend to be brands; brands pretend to be people. We optimize our bodies until they break. And the more we know, the less secure we feel.

In this inverted world, we seek to understand what is real and what is true. To know the truth of ourselves, we begin at what feels like a natural place: the mirror. We wish to see ourselves as others do, and modern life gives us countless opportunities.

We are constantly confronted with our own image, whether we like it or not: on our phones, front-facing videos, selfies, public spaces (the communal mirrors in Aritzia’s dressing rooms come painfully to mind), our social media profiles, Zoom calls, FaceTime, Ring doorbells. But we can forget that mirrors both duplicate reality and reverse it. None show you exactly as you are. Everything is strange.

The historian Christopher Lasch wrote that “for the narcissist, the world is a mirror.” Almost 50 years later, this remains a tidy diagnosis, but it doesn’t quite capture the extent of the spiritual crisis that we’re now facing. I believe the room of mirrors that constantly surrounds us conjures something unsettling, something dark. It is a spiritual trap in which the imagined displaces the real: We choose a fantasy of ourselves over the reality of others. And that trap is baited and facilitated by technology.

Mirrors:

Let’s be honest: I shouldn’t know what I look like taking out the trash. But I do, because my Google Home security camera recently alerted me that there was a “Person Seen — Back Camera.” “Person” is a generous term for what I saw, which was a beleaguered, ghostly figure — greasy hair pulled back, hunched over a bag of trash like an old witch.

We are recorded constantly: in public, by the government, by private companies trying to sell us things, even by strangers. I shudder when I think about all the incidental pictures of myself that live on strangers’ phones. In my own personal horror film, there I am, eating a bagel, and some 17-year-old tourist zooms in on my pixelated face, screenshots it, and sends it to the family group chat — “this woman’s face lol” — and I become the inside joke that defines that New York City holiday for years to come.

It’s curious, especially given how little we looked at ourselves in the past, and how rare and imperfect mirrors were for thousands of years, that traditional wisdom teaches us to be wary of the act of regarding the self. The three major American faiths — the Abrahamic religions of Judaism, Christianity and Islam — all warn against the dangers of mirrors, vanity, pride and excessive concern with the self.

Mirrors are covered during shiva, the Jewish seven-day mourning period, both to encourage contemplation of the relationship between God and man and to discourage vanity and self-concern. The Book of Proverbs teaches that pride is spiritually deleterious: “Pride goes before ruin, / Arrogance, before failure.”

Many Christians believe pride is not only a sin, but the original one, and the worst of them. [...]

Islamic prophetic tradition (hadith) discourages the depiction of living beings in religious contexts.

The uncanny:

Inhabiting this mirrored, dual realm, this doubled existence, doesn’t feel natural. It doesn’t even feel neutral. Something is off, and when something is off, Freud has probably attempted to explain it. He called this “the uncanny,” a concept that by its very nature resists a clean definition, though if you’ve seen a David Lynch movie, you’ve experienced it firsthand.

Castration complexes and womb-fantasies aside, Freud does a pretty good job: The uncanny, according to his 1919 essay by the same title, “is that class of the terrifying which leads back to something long known to us, once very familiar.” It is easy for something new or unknown to frighten us, but the feeling of uncanniness relies on its being known to us in some way.

The uncanny is a dark twist on the familiar. It emerges when the boundary between imagination and reality begins to blur, when hidden mechanisms seem to be at work beneath the surface, and when something appears alive that should not be. (Or vice versa, in the case of influencers, who can have that dead sharklike look in their eyes.) It is marked by repetition, by a sense of something fateful and inescapable. Freud noted that the uncanny is often and easily produced when a symbol begins to take on the full force of the thing it represents. It is difficult to imagine a more precise description of life online.

The doppelganger:

Closely tied to mirrors and the uncanny is the idea of the double, or doppelgänger, a theme long explored in literature and film, from Dostoevsky’s novella “The Double” to Jordan Peele’s horror movie “Us.” In German and Eastern European folklore, the doppelgänger is an omen, a usurper, the shadow self, and a sign that identity is unstable. The self is split, haunted, mimicked and stalked by its own likeness.

Today, we treat our own image — both in the mirror and online — as something psychologically protective: a way of stabilizing our identity, managing our reputations and securing a coherent sense of self.

But all of this suggests the opposite possibility: The more we try to stabilize ourselves through repetition, doubling, self-observation and — I’ll say it — posting to the grid, the more uncanny and fragile we become. A preoccupation with the stable self produces instability. These days, we don’t approach our doubles with caution; we invite them, and go so far as to curate them.

There's more at the link.

NYTimes: AI needs human supervision in order to complete an entire job.

“While A.I. can excel regularly at complex tasks, it can be unreliable when put in charge of an entire job. It can certainly add value to certain areas of the work force, but for now, A.I. still needs a human boss.”

When AGI comes, we will stop reading stuff like that. But that…

— Gary Marcus (@GaryMarcus) July 25, 2026

From the NYTimes article linked in the tweet:

We gave an A.I. tool full access to a laptop with pre-configured apps and sought to answer a simple question: Can artificial intelligence do an office job?

Some corporate executives seem to believe it can. More than 200 tech companies have cut roughly 120,000 jobs this year, according to Layoffs.fyi, an industry tracking site; Meta, Oracle and others have all recently made substantial cuts to their work forces, citing A.I. as the driving force; and after laying off about 1,100 employees, the chief executive of Cloudflare said recently that he expected A.I. to replace workers in middle management, finance and marketing.

tweIn our experiment, we deployed A.I. “agents” to act as office workers and found that they were capable of performing some of the tasks we assigned, but not all of them. The agents, which can act autonomously and make decisions based on detailed instructions, excelled at problems they could solve by writing computer programs. But they struggled with understanding the nuances of human language and at navigating user interfaces like the Chrome web browser.

The article then has a series of nice quasi-interactive displays illustrating agent performance on three tasks. The displays include screen shots of various messages and documents.

About the tasks:

This task, and the others we assigned to the A.I., were adapted from papers and benchmarking tools published recently by researchers at Carnegie Mellon University and OpenAI. The researchers designed the benchmarks to test the performance of various models — like OpenAI’s GPT, Google’s Gemini and Anthropic’s Claude — in real-world environments, and compare them with one another.

General conclusion:

The results of our experiment roughly matched what researchers and companies have found as they have tested and used artificial intelligence tools. Scale AI, an A.I. training company, recently tested agents on real freelance projects, and the best-scoring model produced client-ready work only about 16 percent of the time.

While A.I. can excel regularly at complex tasks, it can be unreliable when put in charge of an entire job. It can certainly add value to certain areas of the work force, but for now, A.I. still needs a human boss.

* * * * *

Comment: Around the corner my colleague, Ash Jogalekar, has tweets like this one:

So here's a great example of where we are with agentic AI: Instead of just being an assistant, it's behaving more like a collaborator and creative scientist.

In a recent project, I gave the system a molecular design problem typical of the problems we encounter in chemistry. Two similar molecules were giving very different results.

He then runs through an account of what his AI collaborator did, concluding:

I think we have crossed the Rubicon. Agentic AI now no longer just processes tasks and automates workflows blindingly fast, but it can generate hypotheses, test them, test counter-hypotheses and go back and forth and course-correct if necessary, all with minimal to no human intervention. It's now embodying the general scientific method.

[I've copied another one of Ash's tweets to this post, A scientist reflects on what AI has done for him.]

What’s interesting to me, and very revealing, is that a complex set of tasks in scientific investigation seems to be on a level with routine office tasks, as though one were no more complex than the other. But humans require years of college education in order to perform the former while the latter requires no more than a high school education, if that. It seems that once they’ve been learned and compiled, all tasks or sets of tasks are on the same “level” in the brain. The educational prerequisites required to do such tasks for the first time or three get “compressed out” through repetition. Since AIs are trained on written records of what humans have said and done, they don’t have to go through the ordinary learning process. The compression has already taken place and is present in the documents on which they are trained.

The Boys [Media Notes 187]

David Colman, The Emmy Awards Are Afraid of This Vulgar, Gory, Brilliant Show, NYTimes, July 19, 2026.

Last week, a raft of intelligent, watchable, enjoyable shows were nominated for the Emmy Award for outstanding drama series, the TV version of the best picture Oscar. Each of these prestige TV shows made tart references to our current moment. “The Pitt” dealt with ICE in the E.R. “Slow Horses” and “The Diplomat” dramatized the dangers of cynical political expedience. “The Gilded Age” and “Paradise” produced two very different takes on oligarch-itecture. “Your Friends & Neighbors” wallowed in larcenous suburban finance dads in midlife crisis, while “A Knight of the Seven Kingdoms” jousted with how to transcend one’s “low birth.” The only show to truly depart from dramatic realism was “Pluribus,” a sci-fi show about a space virus that made virtually all humans highly agreeable zombies, making you wonder if this is what life will be like living in a world ruled by A.I. agents.

But in the end, none of them actually tried to capture the grand farce of a moment we’re in. They didn’t even come close. Each of them is too polite, too nuanced, too, in the end, moderate — centrist, even.

And then there’s The Boys, which captured our current moment, where it’s “as if we’re living in a burn-it-all-down age of greed, mayhem and corruption.”

There was one show, however, that hit this head-on — and it’s not “Industry,” HBO’s finance-and-cocaine drama that was also snubbed by the Emmys this year. It’s Amazon Prime’s “The Boys.” The superhero spoof, which ended its five-season run this May, received not a single Emmy nomination in a major award category. Despite the fact that it dared to land savage, serious and entertaining punches about everything warped in American culture — corporate greed, celebrity worship, moral hypocrisy and how they all fit together. [...]

For those unfamiliar, “The Boys” is set in an alt-present-day United States, where superheroes (“supes”) are real and abundant. But instead of renegades valiantly saving the world from doomsday plots, they’re more like substance-abusing superinfluencers: entitled, narcissistic pursuers of fame whose high-profile “saves” are frequently stage-managed photo ops. They often offhandedly end up killing bystanders. The supes — especially the elite supe group known as “The Seven,” a parody of DC’s Justice League — are controlled, weaponized and monetized by the company that came up with the chemical to create them: Vought International, a corporate octopus whose business interests range from Disney-style entertainment to pharmaceuticals to military contracts.

The gullible public laps up all the supe mythology — especially that of Homelander, the all-American, charismatic leader of the Seven whose authoritarian megalomania drives him to take over the Oval Office, having naysayers locked up in detention camps (or just laser-visioning them in half) along the way.

For what it’s worth, I was hooked from the first season in 2019, while the Trumposaurus was finishing off his first term.

This vulgar world of corporate-branded superheroes isn’t just an ironic conceit; it’s a brilliant, subversive lampooning of our politically divided, social-media-addicted, celebrity-hypnotized society — and, in the words of the “Boys” showrunner Eric Kripke, of the “powerful and selfish people using social media to intentionally tear people apart for their own selfish interests.”

It may not be subtle. But neither is the era we live in. The Shakespearean scramble of “House of Cards” or “Succession” (both repeat Emmy winners for outstanding drama series) seems quaint by comparison with what we get on newsfeeds every day. [...]

You might wonder why a show that focuses on the superheroes isn’t called “The Supes,” but that’s really the point here. The characters putting the plot into action aren’t the supes, but “the boys,” the four men, and eventually two women, who commit themselves to destroying the company and the supes who are making their world a living hell. Even if some have superpowers, they don’t know what they’re doing. They take insane chances. They fail over and over and keep getting outsmarted by Vought — until they don’t. The show’s real heroes, working outside the official system, pursue their impossible task no matter how the deck is stacked against them. And that is how they win.

There’s more at the link.

What do you do when you retire?

Brian J. O’Connor, You’re About to Retire. What Are You Doing for the Next 20 or 30 Years? NYTimes, July 18, 2026.

“Most people have never been retired, so they can’t connect their present reality with their future unknown reality,” said Michael Crews, author of the retirement book “Saturday Everyday” and chief executive of North Texas Wealth Management in Allen, Texas.

“The biggest question that people miss is the goal-setting and lifestyle for retirement,” he said. “In retirement, you still have to figure out what’s really important to you. And people just aren’t having those conversations.”

Like Mr. Crews, an increasing number of financial planners now say the most important retirement question to answer isn’t your net worth, your marginal tax rate, your gift-tax exclusions or expected longevity. Instead, it’s this: How do you plan to spend your time?

Unretiring:

Other retirees stop working entirely for a while and then return part-time or as consultants, aiming to balance the social and mental stimulation with shorter hours and less stress than in a full-time job. An AARP study published early this year found that of the 7 percent of retirees returning to work, 15 percent cited boredom as the reason, with 14 percent saying they were motivated to help others. Still, nearly half said they needed the money.

“People unretire, I think, largely because it was part of their plan to do that all along,” said Geoffrey Sanzenbacher, a research fellow at the Center for Retirement Research at Boston College, who said that academic literature finds that nearly a quarter of retirees unretire at some point. “They’re stressed, they’re done, they retire, and at some point they’re recharged and they come back to work, especially the more educated group, where there’s not a physical component to the job.”

Three phases of a long retirement:

A retirement of 20 years or longer can cover three phases: An active, healthy phase right after leaving work, followed by a period of less activity, and a final period when retirees settle in to a lifestyle with little activity near the end of life.

Phase One: If they have the resources, this is when retirees should travel, before illnesses or ailments show up. Conventional wisdom once held that spending dropped after you left work, but later, research found that spending actually increased as retirees took up new hobbies, traveled, relocated and pursued other long-delayed plans.

Phase Two: After 10 to 15 active years, physical reality catches up with 75- or 80-year-old retirees. Those who were working part time have typically finished but still have time for family, friends and social activities. Spending tapers off.

Phase Three: After an additional five to 10 years, retirees typically stay closer to home with less activity and may develop more serious health issues that can lead to large medical bills. As of 2025, the median cost for nonmedical caregiver services at home was $80,000 a year (assuming 44 hours a week), assisted living was just over $74,000 and a private nursing home room cost about $130,000.

There's more at the link.

Democratic socialism, American style: Douthat interviews Bashar Sunkara

Ross Douthat, A Vision of a ‘Society Without Capitalism’, NYTimes, July 16, 2026

Democratic socialists are having a moment. But can they actually remake the Democratic Party — and the American economy — in their image? My guest today, Bhaskar Sunkara [founding editor of Jacobin], WLB, is a longtime democratic socialist, and he makes the case that socialism has a universal appeal that transcends our current politics and will ultimately triumph against capitalism.

Well into the interview, Bill of Rights socialism:

Douthat: So you’re saying that if there’s a socialist contract with America, it does not promise collectivization and a one-party state?

Sunkara: I think we believe in a Bill of Rights socialism.

Douthat: So what is it?

Sunkara: There’s an immediate set of demands that you could call us attempting to bring about doses of socialism within capitalism.

This comes in the realm of decommodification of certain goods, providing them as social rights instead of them being dependent on your ability to pay.

Health care in America is partially decommodified. If you’re elderly, if you’re very poor, if you’re a child, you’re going to have guaranteed access to health care. We want to see that extended.

Same thing with things like Social Security and certain other benefits, or an expansion of the welfare state — not unlike Norway.

I also would go further and say that even within capitalism in the here and now, there are sectors of the economy that I would like to see greater state control of. In the old language of the left, we would call it the commanding heights of the economy, but even things like rail — there are benefits to selective nationalization, particularly of natural monopolies.

That vision right there of socialism within capitalism, could be true of a lot of social democrats.

So beyond that, the question is: Why would you go about calling yourself a democratic socialist? For me, I call myself a democratic socialist because I actually believe in a socialism beyond capitalism.

I actually do believe in an economy built on the idea that workers should control their workplaces and on this more radical vision of a society without capitalism, even if it still has a motor needed for investment and for efficiency gains and growth and so on.

Housing:

Douthat: OK. But those people in Queens who you mentioned, they’re concerned about housing, right? Is the leftward view of what housing policy should be for the Democrats, going forward?

Sunkara: I think everyone can see, across the political spectrum, that there’s a huge problem with housing construction in the U.S.

So Zohran’s policy, for example, in New York, is very heavily built around upzoning and making it easier for developers to build, and I think people agree with that.

But beyond that, I think on the left, we point to successful examples around the world of public housing being done right. We think at least part of the construction needs to be public housing. We also need to maintain and expand existing units.

I think that’s the room for the state to step up and do more things. But I think these solutions are largely, first and foremost, on the supply side. Then beyond that, we do believe in certain stabilizations and other things.

Douthat: Rent stabilization, meaning rent control or —

Sunkara: Rent control, which can be designed well. It could also be designed poorly.

But you could imagine, for example, telling landlords: “We’re going to clear the way. We’re going to allow you to create this big housing development. We’re going to fight against the interests of local homeowners, and you build your big piece of housing. But after 30 years, after you have a reasonable return on investment, that unit is going to have some degree of rent stabilization,” for instance.

That, to me, is a perfectly common sense, economically coherent vision for housing. I know there’s lots of talk on the left and in the Democratic Party about the debate over abundance, but fundamentally, any form of social democracy is grow-give.

There needs to be a motor for economic investment. There needs to be profitability in order to have something to redistribute. The added component that I would say is an important part of a socialist agenda is making sure that there are strong unions in workplaces that can advocate for higher wages even before the state gets involved with redistribution.

A.I.:

Douthat: What about A.I.? Bernie has taken some pretty strong stances, I would say. He has sort of staked out a position as the Democratic politician most open to both doomer narratives about A.I., but also most enthused about the prospect of strong government intervention.

What is the socialist position on the A.I. industry right now?

Sunkara: I think there’s a host of different socialist positions. I lean more on the side of just seeing it as any other technology. Companies are going to invest in new technologies. The economy is going to change. We’re going to need to adapt and figure out how to regulate it.

Obviously, any changes that we do, any regulation we need to do, need to make sense in an international context too.

It doesn’t make sense to tank certain U.S. companies if there’s going to be other companies creating the same disruption that are coming from other parts of the world.

But I think this gets to the level of policy where there’s legitimate debates. I think the idea which has been touted by figures as varied as Bernie Sanders and Steve Bannon is of the U.S. government owning a stake in major A.I. companies.

It makes perfect sense, too. But, fundamentally, we have to respond to a dynamic economy in which there’s always going to be new technologies, there’s always going to be new wants and needs, and new goods and services, and we need regulation that’s able to be flexible and adapt with changes. [...]

There needs to be a motor for economic investment. There needs to be profitability in order to have something to redistribute. The added component that I would say is an important part of a socialist agenda is making sure that there are strong unions in workplaces that can advocate for higher wages even before the state gets involved with redistribution.

What of capitalism?

Douthat: But just pulling back, I feel like we’ve danced around this a little bit, so let me just ask it directly: Is democratic socialism compatible with capitalism?

Sunkara: In the long term, no. We’re anticapitalist. We want a world beyond capitalism. But in the short term, while we’re within a capitalist economy, of course, we need firms that are profitable, that are providing employment, that are providing taxation. So I think to govern in the short term as social democrats, we need profitable firms.

But in the long term, you know, I don’t hide my desire that I think the economy should be socialized, even if I think in the socialized economy, there needs to be a role for markets and also a role for worker-controlled firms to be able to meet people’s needs and provide new goods and services.

Douthat: What’s the distinction you make between capitalism and markets then?

Sunkara: Well, I think markets existed before capitalism. Capitalism is a regime of property ownership that says that as an individual capitalist or as a corporation, we own this private property and we use this private property to employ people and to produce goods and services.

And in my vision of a just society, of a socialist society, that private property would be controlled by ordinary workers who would get their financing from public banks, who would still operate with hard budgets. They would still need to meet goods and services and meet their payroll obligations and things like that.

But you don’t have a class of people who, as individuals, control investment decisions.

There's much more at the link.

Feelings for Sale in China

There's a video at the link (NYTimes). Here's a transcript of the voice over:

Visitors to a theme park in central China are lining up for selfies with this cosplayer. While this hiker is paid to guide and carry visitors up one of the country’s most popular mountains. It’s all part of a growing trend among young people here who are increasingly anxious about the future because of declining wages and high youth unemployment.

So many are buying feel-good experiences and products that provide “qíng xù jià zhí” — which means emotional value in Chinese. The phrase is everywhere. Companies use it in ads to sell everything from A.I. pets that provide companionship to blind boxes that bring surprise. Even some local governments are using the term in their annual economic reports.

The trend has fueled a nearly $400 billion market that’s estimated to grow 70 percent by 2029. We found two young Chinese workers who are cashing in on the craze. Their social media posts and videos they shared with us give a glimpse inside the emotional value phenomenon.

College student, Lu Zhaoyu, is part of a group that helps people hike Mount Tai in eastern China. The 20-year-old markets his services with photos of himself, promising “maximum emotional value” all the way up to the summit. He said his clients are usually women in their 20s and 30s who prefer to spend money on their feelings rather than practical things.

A Lang bounced between different jobs before becoming a cosplayer at an amusement park. The park advertises that its good-looking actors and actresses provide a “full emotional experience” for $15 per visitor. The 30-year-old usually spends an hour transforming himself into a warrior from a video game. He said some visitors in the crowd are fans who have seen his videos on social media. A Lang said his goal is to create a moment of joy for each person.

What sets Lu apart from a typical hiking guide are the services he offers his clients such as fresh fruit at a rest stop or champagne to celebrate the hike. Clients pay about $100 for a six-hour trek. Many get exhausted along the way and ask to be carried. Sometimes Lu said he feels like a therapist. Both Lu and A Lang said the job can be emotionally and physically draining. But emotional value can also be a two-way street. “Getting exhausted during the hike is inevitable. But providing emotional value or carrying their bags is the basics of the job.” “When I am tired, I will turn on the livestream and sing to release my emotions.”

What Gibbon has to teach us: Learn to change your mind

Charles King, What the Definitive Book on Empires Says About America Today, NYTimes, July 13, 2026

Charles King has a lot to say about Edward Gibbon's The History of the Decline and Fall of the Roman Empire, the current situation in America, and the application of the former to the latter. For example, setting the stage:

Anyone living in the 18th century could see the contemporary relevance of Gibbon’s Rome — just as we can see it today, during the year of America’s semiquincentennial. “Substitute the word America for the word Rome,” Henry Adams wrote after reading “Decline and Fall” in 1860, “and the question became personal.” Adams could sense the work’s significance for the United States, which was then mired in sectional conflict and preparing for civil war. In the century and a half since, Gibbon has been reliably cited as the perennial prophet of what happens when a good country goes bad.

Here's the heart of the matter:

Because Gibbon has become a universal sage, it is easy to miss this principal fact about him and his great work. He was an honest historian who, in an age of political division, fading empires and revolutionary upheavals, scribbled a long book with a large and surprising message at its core. Gibbon’s singular insight was that the whole point of reading a history book — or writing one — is not to come away with one big truth. The stealthy purpose of studying history is to get you comfortable with changing your mind.

That resonates with me, not so much for its applicability to the current state of American politics and society. Rather, I believe it's what I'm up to with my book on AI, Play: How to Stay Human in the AI Revolution. That's why I'm putting two chapters of (science) fiction in an eight chapter book where the other chapters are non-fiction.

Later:

At its most basic, making the chaotic events of the past into a coherent thing we call history is an act of intentional, purposeful understanding. History forces us to confront things we don’t comprehend, decisions we can’t fathom, and ways of being and believing that seem utterly bizarre. It makes us look for evidence in unlikely places. It requires that we think like grown-ups, drawing conclusions that we know will change when the available evidence does.

Facing up to AI has similar requirements.

All the things we consider normal, dear and true will one day pass away, as they did for the thousands of emperors, queens, citizens, soldiers, philosophers, priests and parents who populated “Decline and Fall.” Yet the possibility of happiness, meaning and a legacy that matters lies not in a disembodied hope for a better future. It lies in the hard evidence — here, let me show you, Gibbon tells us across the centuries — that the dead managed these things, too.

I can't say that (science) fiction counts as evidence. It does not. But it may made you open to different evidentiary requirements, different modes of construal.

There's more at the link.

Perhaps we need First Amendment rights for software

Paul Ford, What the Government’s Fight With Anthropic Reveals About Free Speech in America, NYTimes, July 12, 2026.

Ford begins by reviewing the history of Anthropic's relationship with the federal government concerning Mythos and then Fable 5, concluding:

Whether you take Anthropic’s side here or the White House’s, the events of the last several weeks are clearly a poor, disorganized way to approach governance of these models. I think they point to a troubling future. And that brings me back to the idea of free speech and code.

Moving on:

It’s easy to see large language models and chatbots as exhibiting pseudo-consciousness. [...]

But these things are not conscious. They gathered vast troves of public and private information — sometimes without permission — and organized it into huge blobs of interconnected numbers.

Large language models, to me, are simply artifacts: objects made from the language expressed by tens of millions of people. And Anthropic, to me, is a software publisher. I do not see Claude as a living thing; I see it as a reference work prone to glitching, a surreal encyclopedia with wild side effects. I pay for the privilege of using it to generate new things — code mostly, and industry research reports.

Notice, BTW, how these statements are consistent with the view that LLMs and their encompassing chatbots are cultural technology, collective entities comparable to markets, libraries, and corporations. See also my article at 3QD, Of Grammar and Truth: Language Models and Norms, Truth and the World. Now back to Ford, in progress: 

But, critically, the things it generates are then mine, and I use them as I see fit. And, also critically, if I share them with the world, I bear responsibility for them. You see this with lawyers who submit A.I.-generated briefs — judges have no empathy for “the bot wrote it” arguments.

Prudence and slow-rolling releases might benefit the public in the same way that crash-testing cars is of benefit. Standards are good. But if the government can yank access at its whim, we’re starting down a slippery slope — the same slope we go down when we monitor library patrons and track what they read.

Now there are rumblings of ID-verification programs for A.I. users, to assure nationality. Do I need to be permitted to be an A.I. user, like I need to be to drive a car or own a gun? Do we want a future where Officer Claude pulls you over on the information superhighway and demands your license and registration?

Further along:

It is, I admit, appealing to imagine the government — well, maybe not this government — hitting the brakes on A.I. We could all use a rest. But ask yourself: Are you willing to compromise your free speech rights in order to keep people from finding bugs in your word processor? That’s what’s increasingly being asked of us when the government restricts the use of these models by certain groups, with little transparency and poorly articulated reasoning.

If A.I. is the new interface for creating code, and code is a form of communication and expression, then it’s incumbent to ensure only the most critical restrictions are applied to these models. And this is a new kind of technology, an industrial-strength symbol generator that often works in unpredictable ways. The balance is incredibly hard to strike, and it requires enlightened governance. Then again, there are established exceptions to free speech in America. We are capable of discernment.

There's more at the link.

We need a more balanced approach to developing and deploying AI

Eric Schmidt and Selina Xu, We Must Address the Growing Rage Against the A.I. Machine, NYTimes, July 11, 2026.

On the whole US AI developers want to move as fast as possible while the public is increasingly skeptical and opposed. The Chinese are more cautious and want to develop AI while preserving social stability thus the Chinese public are more optimistic about AI than Americans.

Dismissing A.I. entirely would be a mistake. The technology can help diagnose diseases, predict protein folding, improve farming, forecast disasters better, design new materials, accelerate scientific and drug discovery and power robots in dangerous environments to improve human safety (such as in space, firefighting and minefields).

Yet how technology spreads is never inevitable. If A.I. is viewed as benefiting the few at the expense of the majority, then the public will rage against the machine. And A.I. won’t be able to make our lives better in the long run if it cannot survive in the short term. The real challenge, then, isn’t whether the United States or China will build an overwhelming, insurmountable advantage over the other. It’s whether either can figure out how to realize the benefits of A.I. without ripping apart its social fabric. Neither has found the answer yet.

Silicon Valley tech executives and policymakers across the country are waking up to that fact. States have introduced dozens of bills this year to put safety and privacy guardrails around A.I. The Trump administration issued a new executive order that seeks to give the government more oversight over new models before they’re released to the public. [...]

To get to the other end of the tightrope, we need radical and incremental solutions alike. Here’s one to start: a populist A.I. agenda that treats the technology as a public project. Just as NASA made space a national mission rather than a private one, the government should now do the same for A.I. to ensure that its benefits reach the public, not just the companies building it. Here are some concrete ways to do that:

One, treat some A.I. profits as a shared resource and distribute them directly to citizens. This can be in the form of a sovereign wealth fund, seeded by contributions from A.I. companies in the form of stock or cash. [...]

Two, support public-interest A.I. models that the private sector might not be incentivized to build. Examples include models to help citizens navigate government services and benefits, to help them gain legal aid or to help educate their children. We strongly believe in the importance of open-source A.I., which anyone can freely use and modify. [...]

Three, regulate one area that attracts bipartisan agreement: the way children and teens interact with A.I.

There's more at the link.

NYTimes Opinion: Don't Stress about AI; Don't Bring Back the Tests; A New Generation of Creatives

Three from The New York Times, June 22, 2026.

Robert J. Shiller, We Have to Stop Freaking Out About A.I.

Like many others, I believe A.I. could lower employment. But unlike most, I don’t necessarily blame the technology itself. Instead, I worry about the potency of the fear it is generating.

Our brains are wired to respond to stories. Narratives floating in a population can affect individuals’ economic decisions about whether to buy a big house, or whether to send their kids to an expensive private school or even whether to have kids at all. When millions of people make millions and millions of decisions based upon negative expectations, there is a risk that fear can actually help birth the reality.

The idea that something like artificial intelligence will replace many human jobs goes back thousands of years. Aristotle envisioned a powered loom and a self-playing lyre someday replacing human servants. In the 19th century, groups of textile workers (the Luddites) destroyed the new machines they believed were replacing them. In the 1920s, the play “R.U.R.” — the letters stand for “Rossum’s Universal Robots” — depicted a war of the robots against humans. [...]

...the British mathematician I.J. Good wrote an essay that imagined a new technology that could continue improving itself until its abilities would surpass those of humans. The idea, which came to be known as the “singularity,” would quietly circulate until 2005. That’s when the futurist Ray Kurzweil wrote “The Singularity Is Near,” a book arguing that human-level A.I. would arrive by 2029. Either we would merge with machines and transcend our biological limits, or the machine would grow so powerful it could end all of humanity.

The theory captured the imaginations of tech titans, and even the top A.I. researchers and executives, who warned of a range of alarming scenarios, from job losses to widening inequality or even the eradication of humanity itself. While the job market has slowed for a host of reasons, there are reports that fear of an A.I. apocalypse is worsening the freeze and contributing to record lows in consumer sentiment.

There’s only so much Washington can do about these narratives. And, suffice to say, Donald Trump is no Franklin Roosevelt.

As such, perhaps the best we can do is to appeal directly to the leaders of Silicon Valley who have been promoting these negative narratives with such vigor. Surely the resulting media attention highlighting how dangerously powerful your A.I. model is may help you sell more wares, but it may be far harder to do so in a period of recession. Try not to forget the critical lessons taught by our past.

Ross Wiener, I Thought ‘No Child Left Behind’ Would Fix Public Schools. I Was Wrong.

The new data is emboldening calls to restore something like the No Child Left Behind Act, the stringent, test-based accountability policy that defined American education from 2002 to 2015 and imposed penalties on schools whose students did not meet proficiency requirements on state standardized tests. The Atlantic captured that impulse in a 2025 podcast episode titled “Bring Back High-Stakes School Testing.” In it, Margaret Spellings, a secretary of education under President George W. Bush and now president of the Bipartisan Policy Center, argues we need to restore “the muscle of accountability, the muscle of assessment.” Rahm Emanuel, exploring a 2028 presidential run, said in April that Democrats have abandoned standards and accountability and must return to them.

It was a mistake in the past to treat test scores as the purpose of public schools rather than as partial proxies for what a good education actually delivers. Reading and math are profoundly important and improving instruction must be part of any serious agenda. But test-based accountability policies were not sufficient decades ago. They are even less adequate now. [...]

Over time, I became convinced that, with the best of intentions, I and many others in the education reform community had transferred our moral commitment to children over to the standardized tests. We had done this earnestly, not cynically, but we still did damage.

In 2023, 40 percent of high school students reported persistent feelings of sadness or hopelessness. One in five had seriously considered suicide; nearly one in 10 had attempted it. Research from the SNF Agora Institute at Johns Hopkins found that 40 percent of Gen Z believes political violence can be justified, compared with 11 percent of baby boomers. Too many students experience school as an obligation with few opportunities for agency or meaning; recent survey data indicates that large shares of students find school boring and irrelevant and are struggling with engagement in the classroom. The academic crisis and the human crisis are not entirely separate phenomena. [...]

Taking their priorities seriously would mean broadening what we expect from the classroom. Schools should put what students can do on equal footing with what they know, embedding real skills in academic learning rather than leaving them to chance or sequencing them to later in life. Schools should reconnect with the communities they serve, so young people learn through and about the places where they live. And they should reanimate the character-forming, developmental mission a pluralistic democracy requires.

Tom Rothman, Hollywood Needs Regular Jolts of Creativity. It Just Got One.

In the last month, “Backrooms,” a horror movie directed by Kane Parsons, a YouTube creator who just turned 21, opened to an astounding $81.5 million in America. A second horror film, “Iron Lung,” made and self-distributed by Mark Fischbach, another online creator, has grossed over $50 million worldwide. Perhaps most significant of all, “Obsession,” a horror film directed by Curry Barker, a 26-year-old YouTube creator, crossed $200 million at the box office this weekend and surpassed the latest “Star Wars” film.

“Backrooms,” “Iron Lung” and “Obsession” each has its own unique origin story. But what they have in common is that they’re all fueled by an avid young audience — exactly the demographic that gloomy industry pundits have repeatedly declared will never return to movie theaters.

Wrong.

Is this YouTube-fueled youthquake simply a coincidental confluence of events? Or does it portend an upending of the Hollywood status quo? Actually, it’s a bit of both. Indeed, for any fear of YouTube barbarians at the gates, this is instead a great opportunity for traditional Hollywood. [...]

Rothman then goes on the list changes in taste following Altman's M*A*S*H in 1970 and Soderberg's Sex, Lies, and Videotape in 1989.

This kind of moment is happening again. Mr. Barker, with a background in short films and YouTube sketch comedy, tells a story in “Obsession” that is so powerfully relatable to Gen Z audiences that the word of mouth has caused the box office to defy gravity.

When Mr. Parsons expanded his YouTube short films into the feature-length “Backrooms,” the aesthetic he’d honed as a teenager on the internet captured an underlying anxiety in his audience, with whom he’d already developed a direct relationship online. These filmmakers are very young, but what matters is not chronological age so much as an iconoclastic spirit, an instinct for what the audience is wanting but not getting and, of course, talent. [...]

“Backrooms” and “Obsession” are also the beneficiaries of expensive and savvy studio marketing campaigns. Reminiscent of how the New Hollywood directors made a lot of money for the old studios in the ’70s — think Francis Ford Coppola and “The Godfather” — and how the indie darlings of the ’90s did the same, these YouTube-born phenomena have ultimately prospered handsomely inside the system.

For perfect symmetry, note that the No. 1 film at the box office when it debuted two weekends ago, one spot ahead of “Obsession,” was “Disclosure Day,” made by Steven Spielberg, the greatest artistic and commercial director in history. “Disclosure Day” is his 37th film. His first was the ’70s New Hollywood anti-authoritarian film “The Sugarland Express,” which he made when he was not much older than Mr. Barker and Mr. Parsons.

The integration of independent creativity with industry influence is a good thing all around. It offers exposure for, and help to, new voices, giving them more visibility and opportunity, and it promotes the kind of originality that Hollywood desperately needs.

Needless to say, there's more at the links.

Keeping AI slop out of the kitchen

Katie Robertson, Visuals by Bob Miller, The Giant Test Kitchen Where Cooks Battle A.I. Slop, NYTimes, June 20, 2026.

As the smell of sizzling bacon wafted through the air, dozens of recipe developers, food stylists and photographers bustled about, misting bottles of wine with Evian to portray the perfect drops of condensation and dusting chocolate shavings over a fluffy peanut butter pie.

This is what Neil Vogel likes to think of as his “secret weapon” in the new era of artificial intelligence: a 40,000-square-foot test kitchen just outside Birmingham, Ala.

Mr. Vogel, the chief executive of People Inc., one of the country’s biggest digital and print publishers and the home of brands like Food & Wine, People, Entertainment Weekly, Allrecipes and Southern Living, has already seen chatbots upend search traffic and A.I.-generated slop flood the internet. And he is betting that readers would rather make a recipe created by someone who knows how to handle a chef’s knife than one generated by a robot.

People's has a kitchen hub with 28 kitchens where real humans test and develop recipes.

Honoring that spirit of name-changing, People Inc.’s parent company, IAC, announced in April that it would now be known as “People Incorporated” to reflect a focus on its publishing business. That decision was deliberate in the age of A.I., said Barry Diller, the chairman of People Incorporated.

“Until we get to the final simulation, people are the only really valid, honorable and positive endeavor that People Inc. can take,” he said in an interview.

The Birmingham facility develops some 1,800 new recipes a year and tests an additional 5,300. Downstairs is a prop storage room, bursting with a rainbow of crockery, glassware and table linens in every fabric imaginable. The facility also has a “lab” that has evaluated more than 3,000 products to date, mostly kitchen appliances.

Web traffic dropped:

Traffic to People Inc. websites from Google has plummeted to 25 percent of visits, from 75 percent, over the last four years because of the search platform’s use of A.I. summaries. So the company quickly pushed to build new audiences on platforms like Instagram, Apple News and YouTube and to find other ways to make money, through events, sponsorships and licensing deals.

A feel for the phenomena:

“A.I. can’t smell what something smells like,” said Sid Evans, the editor in chief of Southern Living. “It can’t taste. It doesn’t understand nostalgia. And I think we are able to communicate all of that, and the expertise that we have.”

Mr. Vogel is quick to acknowledge he is not an A.I. denialist. People Inc. has a licensing agreement with OpenAI, and uses it both for research and to make operations more efficient by monitoring social media or pricing out ingredients. A.I. is not used for writing, editing, visuals or other creative work at any of the brands, he said.

There's more at the link.

Big AI vs. Big Government in the 21st Century

Ross Douthat, The Battle With Anthropic Is the Start of a New Kind of Conflict, NYTimes, June 16, 2026.

The nature of the Anthropic conflict can be swiftly summarized even if the details are in dispute. Two months ago the company declined to publicly release its latest model, Mythos, citing various safety concerns (and hyping the model’s revolutionary power). After previewing Mythos to the U.S. government and certain corporate actors, Anthropic then released Fable, a version of the model with various safety guardrails. Amazon, an Anthropic investor and client, discovered a way to bypass some of those guardrails. This was reported to the White House, Anthropic’s response was deemed unsatisfactory, and the administration used its export-control power to forbid the use of Fable by any foreign national inside the United States and anybody at all outside it — a rule that Anthropic treated as a requirement to shut the new A.I. model down.

That’s where we are now, with the company and the administration negotiating over how to bring back Fable while ongoing leaks to the press paint one or the other side as unreasonable or reckless or ideological and clueless about tech.

Two facets of the conflict:

But beyond the specifics of why, say, the libertarian tech people in the Trump administration distrust the effective-altruist tech people running Anthropic, the kind of conflict we’re seeing here is overdetermined by the trajectory of the A.I. models: There is too much potential power here not to have ongoing, escalating struggles over who actually gets to rule.

The war over Fable previews the two broad forms that this conflict will take. First there is a private-public struggle, where governments grope for a regulatory sweet spot that allows them to maintain a meaningful veto over the A.I. behemoths without killing off their innovative power, while the A.I. companies try to maintain control over their own models and influence over how governments use their innovations.

There is a path here that leads to nationalization in all but name and a path that leads to a kind of de facto corporate takeover of the government, or at least a too-big-to-fail symbiosis. And along the way there may be not just conflicts between presidents and A.I. executives but also increasingly ruthless corporation-on-corporation action, out of fear that the A.I. landscape is winner-take-all to an extent we’ve never seen in capitalism before. [...]

Then alongside the struggle to control A.I. power within American borders, there is the geopolitical struggle to maximize global power (where the only real players are probably the United States and China) and maintain sovereignty (where everyone else is likely to be scrambling to maintain some independence). The use of export controls to shut down Fable presumably reflected U.S. fears of Chinese access to a jailbroken version of the model, but it was also a warning to every other country in the world: If we end up with economy-permeating A.I. models that are made and regulated in America, the American government will control the on-off switch.

There's more at the link.

In brains of Spanish-English bilinguals grammar is embodied in shared tissue

Xuanyi Jessica Chen and Esti Blanco-Elorrieta, A Shared Neural Mechanism for Abstract Grammatical Computations Across Languages in Bilinguals, The Journal of Neuroscience, June 15, 2026.

Abstract: A central question in cognitive neuroscience is how the brain implements abstract computations that must generalize across superficially different inputs. Language provides a strong test case: the same grammatical operation, such as pluralization, can be realized through distinct rules and forms across languages. Whether such transformations rely on language-specific neural systems or on abstract mechanisms that generalize across linguistic contexts remains unresolved. Crucially, these transformations must be computed online and integrated into speech planning within a tightly constrained time window. Using magnetoencephalography (MEG), we tracked the millisecond dynamics of grammatical word-form transformations during semi-naturalistic phrase completion in humans of both sexes. Highly proficient Spanish–English bilinguals produced singular and plural noun forms in both languages in a design that fully orthogonalized semantic number, phonological changes, grammatical inflection and produced language. Adjusting words to fit their grammatical context engaged a left-lateralized fronto-temporal network beginning ∼100 ms after cue onset. Multivariate decoding revealed that the neural patterns supporting this computation generalized across languages, across different surface plural forms, and to pseudowords, demonstrating that abstractly equivalent operations are instantiated in the same neural substrates despite differences in linguistic form. Together, these findings provide time-resolved neural evidence for a language-general computational mechanism, showing that the brain implements grammatical transformations as abstract, generative operations. More broadly, they show how bilingualism can be used to probe general principles of neural organization, revealing how abstract computations may be shared and reused across representational systems.

Significance Statement: Human language relies on the ability to modify words to convey information like number and tense, but languages vary widely in how these transformations are implemented. This variation raises a fundamental question in cognitive neuroscience: do such transformations depend on language-specific neural systems, or are they processed by abstract neural mechanisms that generalize across languages? We demonstrate that Spanish–English bilinguals engage a shared left frontal–temporal network when producing grammatically appropriate forms in both languages. This common neural signature emerges early during speech planning and even generalizes to novel words. These findings indicate that the brain builds abstract, reusable neural mechanisms, consistent with models where language is organized by computational principles rather than by language-specific systems.

Here's an article in the NYTimes about these results: K. R. Callaway, How Does One Brain Speak Two Languages?, NYTimes, June 15, 2026.

When deciding how to make a word singular or plural, for instance, bilingual people exhibit strikingly similar brain activity regardless of whether they are speaking in their first or second language.

“It wasn’t obvious that it was going to be so shared,” said Esti Blanco-Elorrieta, a psychologist and neuroscientist at New York University and an author of the study, which was published on Monday in the journal JNeurosci. “I think this is arguably one of the first very fine-grained findings of how truly integrated two languages in the brain are.”

Early research viewed bilingualism as an “add on” or “disruption” to the processing of one’s native language, said Judith Kroll, a psycholinguist at the University of California, Irvine who was not involved in the new study.

Subsequent studies have found that bilingual brains tend to display physical differences, such as more efficient white matter and changes to the gray matter, and to perform better on memory and concentration tasks.

Now scientists are probing further, to understand whether core aspects of the brain’s neural network does double or triple duty to process multiple languages.

A single grammatical engine:

The finding is in line with other initial results in this area, said Mirjana Bozic, a cognitive neuroscientist at the University of Cambridge who was not involved in the study. For instance, the new study provided additional evidence that the front left side of the brain was typically involved in processing the grammatical structure of sentences across different languages. On the whole, Dr. Blanco-Elorrieta said in a news release, a single “grammatical engine” in the brain appeared capable of powering multiple languages at once.

Dr. Bozic said that the find, although not surprising, was “highly informative, providing elegant and convincing evidence that bilingual speakers rely on shared neural mechanisms. She added, “One question that remains is how far these findings generalize across language pairs that differ more substantially.”

Ezra Klein contra (extreme) Homo economicus [Don't torture pigs]

Ezra Klein, What the Cult of Efficiency Costs Us, NYTimes, June 14, 2026.

The opening:

Chris Murphy, the Democratic senator from Connecticut, offered the graduates of Wesleyan University wise counsel in his commencement speech a few weeks back. “You are about to step out into a world that prizes efficiency and the annihilation of drift and friction above all else,” he said. “Our entire economy is built on rewarding companies that are efficient at making a profit, not based upon how they treat their workers, the social value of their product or the impact they have on the community.”

“You didn’t design this world,” he continued. “You didn’t choose it. But you will live with the consequences of this cult of efficiency. And you will have to choose which side you are on.”

Efficiency inflicted on pigs:

In 2016 and 2018, voters in Massachusetts and California passed ballot initiatives banning, among other things, the sale of pork from pigs confined in gestation crates. These crates confine breeding sows — large animals, often 400 to 500 pounds — in two-by-seven-foot cages in which they cannot so much as turn around, much less root or socialize. Because sows are often reimpregnated about a month after their piglets are born, they can spend years of their lives in these crates.

I watched, in the interest of fairness, a video from an arm of the National Pork Board on why gestation crates are good for pigs. It features row upon row of sows penned between bars so narrow they cannot turn around. It is no way for any animal to live, particularly not one as smart and as social as a pig.

There are studies I can cite on the psychic and physical violence these crates inflict on pigs — the elevated cortisol levels, the sores, the obsessive biting of metal bars — but I think the way Kristof puts it is simpler and more honest: “Think of your dog enduring what pigs face, and you realize that the moral cost is incalculable.” The difference between dogs and pigs is neither their intelligence nor their sentience. It is our willingness to admit their intelligence and their sentience. It is our decision to extend them our compassion and concern.

Homo economicus:

In traditional economics, prices are the informational lifeblood of an economy: They reveal the cost of materials and labor, the balance of supply and demand. But much can be hidden in prices. Perhaps it is artificially low because waste is being dumped into the rivers or workers are being robbed of their wages or the burden is borne by animals that will spend years of their lives without the comfort of their herd or the ability to feel grass beneath their hooves or turning around when curious about a sound. When that happens, we have sacrificed compassion for cost.

Most of us know by now that the lives animals lead in factory farms are often hideous. A 2019 survey by the Johns Hopkins Center for a Livable Future found that a majority of Americans wanted stronger oversight of confined animal feeding operations and a plurality wanted a ban on new ones. Those numbers were even higher when the same pollsters asked Iowans and North Carolinians, where majorities favored a ban on new concentrated animal feeding operations, in part because these operations often impose terrible costs on the human beings who live near them.

There's much more at the link.

Burton “Random Walk” Malkiel on SpaceX’s IPO and the poor upside potential for the stock

Burton Malkiel, best known for his 1973 book, A Random Walk Down Wall Street, has some interesting remarks in the NYTimes for those who are wary of being stuck with a stake on SpaceX (and perhaps OpenAI and Anthropic as well) as a consequence of having index funds in their 401(k).

Given that so many millions of Americans are suddenly having SpaceX shares foisted upon them, I understand why some financial experts are criticizing the practice of index investing itself. Right now, just a handful of A.I.-related stocks represent almost half the value of the total stock market index. If A.I. stocks collapse, so will the worth of your index fund.

This is the paragraph I find particularly interesting:

Unlike prior initial public offerings, SpaceX shares are already so expensive there isn’t a lot of upside potential left. When Facebook, now Meta, went public in 2012 with a valuation of $100 billion, shareholders were able to benefit financially from its growth to a $1.5 trillion giant. Amazon went public with a generous (for 1997) valuation of $440 million, and shareholders profited as it grew into a $2.5 trillion behemoth. Not so SpaceX. Because it was owned by private investors for so long, much of the gain will immediately be handed off to its venture and private equity backers rather than preserved for new investors.

He goes on to point this as well:

Moreover, unlike other public companies, SpaceX is employing a dual class share structure that gives Elon Musk essentially complete control with no independent oversight. Public shareholders will, comparatively, have no voice in corporate decisions. Mr. Musk controls multiple related corporate enterprises, raising the possibility of conflicted transactions within the Musk ecosystem. Many investors will be uncomfortable giving him so much power and holding an index fund in which he has so large a share.

He then says:

These are all legitimate reasons to worry. But in my view, it would be a mistake to abandon an indexing strategy. Timing the market is impossible. Yes, the stock market is unusually concentrated today, and it is likely to get even more so over the next period with Anthropic and OpenAI looking to go public soon.

You can read the rest of the article, if you wish. But it's that paragraph about upside potential that caught my attention.