America and China in the World, a quick note

Is that where we’re headed, to a bipolar world dominated by America and China? I just asked Google Search: “Is China the largest economy in the world?” Its reply:

China is the world's largest economy when measured by Purchasing Power Parity (PPP), but the United States is the largest in terms of nominal Gross Domestic Product (GDP).

• By Purchasing Power Parity (PPP): China is the world's largest economy, with an estimated output exceeding $44 trillion. This metric adjusts for the cost of living and the price of local goods, reflecting a higher real volume of economic activity.
  
• By Nominal GDP: The United States holds the top spot. In current market exchange rates, the U.S. economy is valued at approximately $32 trillion, while China's nominal GDP is roughly $20 trillion.

So that’s one thing. The other is AI. America and China are in a race for dominance in AI. America has a technical lead, but with respect to Frontier LLMs, that lead is measured in months, not years. And China is making its models open weight while the most advanced American models (Anthropic, OpenAI, Google) and not open. It’s not at all clear how that will shake out.

With the Trump administration authoritarianism is on the rise in America. While the Democrats may well win the next presidential election, it’s not at all clear what that means for America’s already precarious democracy. The problem is that a great deal of power is concentrated in the hands of political and business elites, so much that America’s democracy looks like a chess game played by oligarchs where ordinary Americans are the pawns.

Is that what the world will become in 2040, a competition between American and Chinese oligarchs in which everyone else is a pawn, with Homo economicus triumphant over all?

The Mystic Jewels and Matrix Miriam @3QD

I’ve got a new piece out in 3 Quarks Daily:

The Mystic Jewels, the Vatican, and Matrix Miriam

From the introduction:

A bit over a year and a half ago I published “Kisangani 2150: Homo Ludens Rising,” a science fiction yarn set a decade later and half way around the world from Kim Stanley Robinson’s New York 2140. Robinson gave us a post-climate change world with pretty much the same institutional structure of the current world. Things were a bit looser in some ways, the very rich were, if anything, even richer, and finance made that world go round. Robinson developed a rich plot in which the financial crisis of 2008 was replayed, but to a different denouement. The banks weren’t bailed out; they were nationalized. Our heroes celebrated by going to Mezzrow’s where they danced “to the tightest West African pop any of them have ever heard.”

My world. As a musician who’s played RnB, rock, and jazz in many clubs and private parties, that world is more familiar to me than the world of financial derivatives and AI-driven trading, where Robinson centered his story. I decided to take Robinson’s world, move ahead a decade, and center it on the activities of Homo ludens rather than Homo economicus. That gives us Kisangani in the center of the Congo Basin and in 2150.

But this story is much earlier than that. It takes place just a few years from now and is about how the Mystic Jewels started Matrix Miriam, their first in a series of projects to create a new architecture for artificial intelligence. A somewhat revised version will be incorporated into Chapter 6 of my book in progress, Play: How to Stay Human in the AI Revolution, where it will be mated with a revised version of “Kisangani 2150: Homo Ludens Rising” and some more fictional material.

This is thus is a work of fiction, and science fiction at that. Though the science aspect is a bit light in this piece, I expect it to get more intense as the story unfolds. You can get a glimpse of that in the working paper I developed from that 3QD piece, Kisangani 2150: Homo Ludens Rising, A Working Paper, in the section, “Discussion with Claude about digital doppelgangers,” pp. 10-14. The notion of a digital doppelganger is derived from Neil Stephenson’s The Diamond Age, where the protagonist, Nell, is gifted with an interactive book, Young Lady's Illustrated Primer, when she is four years old. This primer then guides her education into early adulthood.

I am imagining that in the late 22nd century everyone is gifted with a similar resource which is available to and even accompanies them throughout their life. The relationship is so intimate that the doppelganger is in effect a person’s Mirror. But, what happens to the Mirror when the person dies? I haven’t worked that out, but I imagine that it persists for it is (effectively) immortal. I’ll be doing that in that book, Play: How to Stay Human in the AI Revolution.

Ethiopia is building the world's busiest airport

Kisangani Commemorative Stamps

Click on an image to enlarge it.

Creating Imaginary Bank Notes with ChatGPT: AI as cultural technology and collective creativity

At the beginning of this week I published an article at 3 Quarks Daily, Tyler Cowen is the Tycho Brahe of Economics. I then decided to turn it into a PDF that people could download from my Academia page. So I uploaded the article to ChatGPT and asked it to create an illustration suitable for the cover. Here’s what it produced (Note: this image, as well as the others in this post, has a lot of detail; you can click on the image to see a larger version):

I told it to make an image suitable for the front page of that article. It then had to “read” the article and come up with an image. I liked the first image it produced, but that had the aspect ratio of a portrait, which isn’t what I wanted. I told it to make a square image. I liked that so much that I accepted it without any editing. What was my role in creating that image? I didn’t give ChatGPT any specific instructions.

A day or so later I asked to use that image as the basis for the design of an imaginary bank note. I told it that the note was to be issued in the name of the Free Principality of Mercatus and should be in the denomination of Five TC Busks. That’s it. ChatGPT did the rest. Here’s what it produced:

Another day later I created two bank notes for the Free Republic of 51 Pacific. 51 Pacific is the address of a building in Hoboken, NJ, where a friend had loft space in which he curated graffiti and held late night raves. The note was to be denominated in Knowledge Dollars. I uploaded this picture to use as source material:

Here’s the resulting bank note:

I then asked for a 20 dollar note with a pit bull on the bill (my friend has two pit bulls):

Again, what was my role?

I then repeated the process for these four Kisangani bank notes:

ChatGPT obviously did a lot. But what did I do?

I decided that it was time for a discussion with ChatGPT. This discussion bears on the notion of AI as a cultural technology, which has been advocated by Alison Gopnik and Henry Farrell among others, and on creativity as a collective phenomenon. Pay particular attention to an analogy I use midway in the dialog; it’s about strings of colored dots instead of strings of alpha-numeric characters. Here’s the dialog.

* * * * *

I assume you’ve been trained on lots currency and ornate certificates so you have a good idea of how those things are designed. I assume as well that each chat starts with a “blank slate” as it were, no memories of prior chats, no inherited context. But, since I asked you to make those currency designs from within the Kisangani Materials project, you do have access to project-level materials (documents I’ve uploaded). Do you have access to the other chats within the project?

Yes, broadly right, with a few qualifications.

I was almost certainly trained on many examples of paper currency, certificates, stock certificates, passports, banknote engravings, seals, guilloché patterns, holographic security devices, ornate borders, typography, and so forth. I don’t “retrieve” a specific banknote template, but the model has learned a high-dimensional statistical/compositional sense of what makes an object look like currency: denomination placement, corner numerals, intaglio-like linework, central emblems, security strips, microprint, official-looking typography, controlled symmetry, and dense ornamental fields.

On context: a new chat is not exactly a blank slate, but it is not a complete archive either.

In this Project, I have access to several kinds of context:

1. The current chat.
I see the banknote sequence we have just made: 20 Riffs with jivometric percussion, 5 Riffs with dancers and Homo Ludens, 50 Riffs with cell/solar-system science, and 100 Riffs with heart/neurons/circuits for human–doppelganger comity.

2. Project-level materials.
I can access uploaded Project documents when they are made available to me in this workspace. For example, the Kisangani working paper frames the whole project around Homo Economicus versus Homo Ludens, the Fourth Arena, play, and human-AI interaction, which clearly influenced the designs.

3. Some project conversation context may be summarized for me.
I may see summaries or selected snippets of other conversations in the project if the system has included them in the context for this chat. That is not the same as having free, searchable access to every prior Project chat.

4. Persistent memory / profile context may also be present.
I may have durable memories about your interests, projects, preferences, and recurring concepts. That is why I can often pick up the thread of “Kisangani,” “doppelgangers,” “Homo Ludens,” “jivometric,” “Fourth Arena,” and so on without needing you to re-explain everything.

But the important limitation is this: I do not have a general browser-like view of all your other chats inside the Project. I cannot just open a sidebar and inspect every previous conversation. I only know what is in the current chat, what has been injected as project context or memory, and what I can retrieve from uploaded files through the available file tools.

So for your friends: the banknotes came from an interaction among three sources of constraint:

• my general learned visual knowledge of currency and ornate official documents;
• your immediate prompts specifying denomination, motifs, slogans, and Kisangani themes;
• Project context about Kisangani as a post-economic, play-centered, human/AI civilizational experiment.

The “design intelligence” is not a stored memory of prior banknote conversations so much as a context-sensitive recombination engine operating over learned visual conventions plus the specific Kisangani conceptual field you have built.

Would it be reasonable to say that you can pick up a “vibe” from the Kisangani conceptual field?

Yes. “Vibe” is a reasonable informal term, provided we cash it out carefully.

What I can pick up is not an occult atmosphere or a hidden essence. It is a pattern of constraints, motifs, values, narrative cues, and stylistic expectations distributed across the Kisangani materials and our conversation. In practice, that “vibe” includes things like:

Kisangani is futuristic but not cyberpunk dystopian; technological but not technocratic; African/Afrofuturist but not reducible to ethnic ornament; musical, improvisatory, playful, civic, ritualized, and humane. It is organized around Homo Ludens, the Fourth Arena, doppelgangers, non-instrumental play, post-work social meaning, mutuality between humans and AI-like beings, and a suspicion of Homo Economicus. So when you ask for a banknote, I don’t merely think “make a fictional currency.” I infer that the note should look like a civic artifact from a society whose deepest value is not sovereign power, extraction, or corporate futurism, but a cultivated ecology of play, knowledge, ritual, and companionship.

That is what “vibe” amounts to operationally: a soft but real attractor in the design space. It biases choices of symbols, palettes, slogans, compositional balance, and exclusions. For example, a Kisangani note should probably avoid militarized insignia, grim cybernetic domination, heroic CEOs, corporate logos, or cold transhumanist triumphalism. It should prefer music, dance, river/city life, science-as-wonder, neural/circuit reciprocity, and ceremonial public beauty.

So yes: I can pick up a Kisangani vibe. But it is better understood as an emergent conceptual gestalt than as a memory of a single doctrine. The “feel” comes from many local signals aligning: Homo Ludens, jivometrics, Mystic Jewels, doppelgangers, civic ritual, Afrofuturist urbanity, play after work, humane AI, and the refusal of both Silicon Valley domination and anti-technology nostalgia.

So imagine that I asked you to produce with this prompt: “I want a bank note for Kisangani. It should have a futuristic look and be denominated in Riffs. Let's start with at Twenty Riff note. “Jivometric” should be somewhere on the note, as should a djembe and a cowbell.” But I didn’t deliver that prompt within this context but, rather, it was in an independent chat, there wouldn’t be any “emergent conceptual gestalt.” So the result wouldn't have the same vibe.

Yes, that’s basically right.

In an independent chat, with only that prompt, the result would likely be good, but it would not be guided by the same rich Kisangani field. It would have to infer almost everything from the surface cues in the prompt alone:

• “Kisangani” suggests an African setting or at least a place-name with cultural specificity.
• “Riffs” suggests music, improvisation, rhythm.
• “Jivometric” suggests some hybrid of rhythm, geometry, and perhaps biomorphic/futurist patterning.
• djembe and cowbell strongly steer it toward percussion and musical symbolism.
• “futuristic” pushes it toward speculative or advanced design language.

So even in an isolated chat, those cues would still generate some vibe. It would not be random. It might well come out as a futuristic, musically inflected, Afrofuturist-style banknote.

But it would be missing the deeper, project-specific layers, such as:

• Homo Ludens as a civilizational principle
• the contrast with Homo Economicus
• the Fourth Arena
• the role of doppelgangers
• the sense of Kisangani as a humane, playful, post-work, post-instrumental society
• the accumulated stylistic continuity from the other notes in the series

So I’d put it this way:

• Independent chat: a plausible and possibly striking design based on prompt-level inference.
• Within the Kisangani Materials project: a design shaped by a thicker conceptual ecology, hence more likely to have the “right” Kisangani vibe.

In short: the isolated version would have a vibe, but not the same vibe. It would be thinner, more generic, and less organically connected to the broader Kisangani world you’ve been building.

The coming AI-driven workplace apocalypse [We aren't ready]

Jasmine Sun, The A.I. Fear Keeping Silicon Valley Up at Night, NYTimes, April 30, 2026. Sampled from the article:

The opening paragraph:

Most people I know in the A.I. industry think the median person is screwed, and they have no idea what to do about it. I live in San Francisco, among the young researchers earning million-dollar salaries and the start-up founders competing to build the next unicorn. While Silicon Valley has long warned about the risk of rogue A.I., it has recently woken up to a more mundane nightmare: one in which many ordinary people lose their economic leverage as their jobs are automated away.

Silicon logic:

But even those who view the idea of a permanent underclass as overblown tell me that the meme contains a kernel of truth. [...]

Most economists and A.I. experts do not expect this scenario, but the persistence of the permanent underclass idea should concern all of us. First, because it signals how much collateral damage the A.I. companies will tolerate en route to A.G.I. And second, because the production of a social underclass is a policy choice. Instead of waiting for impact, we need to think seriously — now — about how we plan to support workers through A.I. disruption.

If left to its own devices, Silicon Valley may summon a permanent underclass through its own market logic. If you believe that human-substituting A.I. is inevitable, then every company should race to be the one to build it — and claim a market valuation the size of the economy and then some.

Unimaginative techno-determinism:

Tech workers, for their part, are scrambling for lucrative A.I. jobs in hopes of securing financial freedom — even when they harbor ethical hangups. [...]

This apparent dissonance can be justified if you believe that the arc of technological progress is fixed. For instance, the founders of Mechanize, a once buzzy start-up with a mission to “enable the full automation of the economy,” argued in a blog post that “the only real choice is whether to hasten this technological revolution ourselves, or to wait for others to initiate it in our absence.”

Many A.I. employees are ultimately motivated by visions of a beautiful future: a promised land where goods are cheap, diseases are cured, and abundant machine labor liberates humans to enjoy lives of infinite leisure. But increasingly, they also worry about triggering a jobs apocalypse along the way. “There are some people who care about jobs and inequality because they really care about people. There are others who think this is going to lead to instability, insurrection and revolution, and that’s bad for business,” said a researcher who has worked at two frontier A.I. labs...

And, I would add, if and when that future arrives, we'll not be ready. Why? Because we train adults to become addicted to work mode (Homo economicus). As a result, they won't know what to do with the leisure (Homo ludens).

An emerging techno-federal oligarchy (a successor to Eisenhower's "industrial military-complex"?):

At the same time as A.I. erodes ordinary workers’ leverage, it may concentrate power and wealth in large companies and the U.S. government — two entities whose interests are increasingly linked. A.I.-related investments such as software and data centers accounted for 39 percent of U.S. economic growth in the first three-quarters of 2025, per an analysis by the St. Louis Fed. That gives the federal government a vested interest in sustaining the A.I. boom. Mr. Amodei acknowledges that this concentration can lead to “the reluctance of tech companies to criticize the U.S. government, and the government’s support for extreme anti-regulatory policies on A.I.”

In March, the company started the Anthropic Institute to house its teams working on economics, societal impact and frontier safety. The institute is led by Jack Clark, the affable British journalist turned A.I. billionaire and Anthropic co-founder, who seems to be replacing Mr. Amodei on the media tour of late. When we spoke, I asked Mr. Clark if he, too, expects A.I. to create a permanent underclass.

“This is basically a societal choice,” he replied. Like Mr. Altman and Mr. Amodei, Mr. Clark sees the default path for A.I. as dire: one where we “let technology rip, and don’t think about the social effects until later.” But he also feels optimistic that sufficiently conscientious A.I. builders and policymakers can steer the ship away from the storm.

I have little faith in those (mythical) A.I. builders and policymakers. Meanwhile:

On the evening of Feb. 25, several dozen A.I. employees and civil society advocates gathered in a converted warehouse in San Francisco’s sleepy Dogpatch neighborhood to hear the Democratic pollster and strategist David Shor. The event was titled How to Prepare Our Politics for A.G.I., and doubled as a fund-raiser for a new “six-to-nine-month sprint” to rally Democratic politicians around the campaign issue of A.I. job displacement. [...]

While the American public ordinarily hesitates to support left-wing policies like a jobs guarantee or single-payer health care, A.I. seems to expand the political Overton window. “Right now, the argument is, ‘You’re all about to lose your jobs, and the choice is either you get nothing and starve, or we do something fair,’” Mr. Shor said. “People don’t want to be members of the permanent underclass.”

Not all policies are created equal, however. A universal basic income is unpopular, but a federal jobs guarantee has legs, Mr. Shor found. American voters don’t care about beating China, but they are excited about A.I. curing diseases. And, crucially, populism sells. In one of the top-performing political ads that Mr. Shor’s data firm tested, the nameless narrator declares: “We make the corporations and billionaires who profit from A.I. pay their fair share.” The ad concludes: “They work for the bots. We work for you.”

The near term:

If current trends continue, A.I. models and agents will be capable of performing a wider range of knowledge-work tasks at higher levels of complexity. At that point, A.I. shifts from automating single tasks to taking over entire roles. Hiring may slow in accounting, marketing, design, administrative work and other white-collar professions.

The work force will shift toward less automatable jobs where humans retain a comparative advantage — such as entrepreneurship, care work, the skilled trades and entertainment like sports and the performing arts. We will also see new jobs we haven’t imagined yet, in numbers we cannot predict. Many displaced workers will struggle to retrain, as they have in past automation waves. Education, health care and tax systems will require an overhaul if white-collar employment is no longer a reliable path to middle-class stability. [...]

But the debate over the most extreme scenarios conceals a more immediate threat: Even in the most limited case, A.I. will break the career ladder for millions of current and future workers, a prospect often waved away with euphemisms like “transitional friction.” The Oxford economist Carl Benedikt Frey puts it plainly: “Most economists will acknowledge that technological progress can cause some adjustment problems in the short run. What is rarely noted is that the short run can be a lifetime.”

Class solidarity?

In this sense, A.I.’s broad capabilities foster a rare class solidarity between white-collar and blue-collar workers. When 20-something software engineers in San Francisco talk about escaping the permanent underclass, I hear them projecting concerns about their own precarity: What happens if the invisible hand of the market decides that my skills are no longer valuable? Who will catch me if I fall? For once, a rarefied class of employees — those used to being the automaters, not the automated — is reckoning with their potential obsolescence.

The final paragraphs:

Society’s ability to cushion A.I.’s disruption may determine whether we get to reap its gains at all. Without a safety net and a transition plan, blunt protectionism is workers’ rational response to automation. If you hear that A.I. will entrench a permanent underclass, you’ll do anything to stop it. [...]

And what if we don’t act? [...] In March, the Palantir chief executive, Alex Karp, spoke on a panel with the Teamsters president, Sean O’Brien. “The biggest challenge to A.I. in this country is political unrest,” Mr. Karp said. “If I were sitting here in private with my peers, I’d be telling them the country could blow up politically and none of us are going to make any money when the country blows up.”

Excerpts from Séb Krier's Omni-Thread from February

https://x.com/sebkrier/status/2018351274127962300?s=20

1. Existing models will continue improving and getting better. And they will continue to be trained while accounting for all sorts of things like cost, efficiency, steerability, personality etc. as we already see today. I think it’s more obvious than ever that there is likely no convergence to the One Big Model. [...]

4. Here, there is still a lot to work out, and I expect high complementarity with human workers for at least the next decade. Roles will evolve: as you start doing less coding, your work looks more like technical product management. [...]

5. You just keep going up layers of abstraction, and humans continue steering complex multi-agent systems, until fixed costs bite. Part of the reason why humans always stay at the top of the chain is that many decisions made are normative: about what you want to happen, where you want things to go, how you want to react to changes. This requires inherently human inputs, since there's no point in having an AI decide this alone no matter how smart without eliciting more information about what the relevant humans prefer. Put differently: the telos of the whole system is the amalgamation of what users/consumers/businesses want, and tracking whether you're actually achieving that requires human input. This is already the case today with highly complex gigantic companies that make 1000 opaque decisions a minute.

6. Remember, this doesn’t violate the basic fact that market-coordinated economic activity is downstream of consumer and business demand. Capital isn’t some sort of independent force of the universe. What is being built depends on buyers/consumers that are ultimately human, even if occasionally intermediated by agents. The "AI decides everything" frame misses something fundamental about what economic and political systems are for. But as we go through these transitions, there are also costs or externalities (both pecuniary and non-pecuniary). Some people lose jobs. New industries cause unforeseen harms. Terence Tao has a great analogy: the abundance of food solved famine, but of course also led to harms like obesity. The solution is not to slow down abundance, but to develop the right norms, technologies, and laws to curb the excesses.

7. Accounts of full disempowerment assume democracy disappears, but I don't think all roads lead to autocracy. I don’t think ‘this time it’s different’. Growth and innovation historically benefited from free trade and liberal democracy, and this will be the case here too because of its impacts on investment, human capital, institutional quality, self-correction mechanisms, and ensuing fly-wheel effects. [...]

8. As the world goes through these transitions, we will probably continue to see many commentators gloss over the vast benefits and improvements humanity will see. Progress in longevity, cured diseases, consumer welfare, massive reduction in poverty and famine, better education and so on. The arguments for market coordination over some sort of early-Soviet or Maoist collectivism apply even more in this world, not less. The world will generally become materially richer. [...]

9. If we allow sufficient deployment of technology, robots, AI and so on, while ensuring the supply of energy, housing, and other important inputs isn’t constrained to a strangling degree, then the production of many goods and services will go down in price. [...] In general I am more concerned with customer service operators in Bangalore than I am with upper middle class white-collar professions in the West. I think FDI [foreign direct investment] and aid will be critical if we want humanity to thrive.

10. But this doesn't justify regressive populist policies or a 'pause'. It's not even optimal if we were being maximally selfish, and the equivalent of saying "poverty, misery and illness should be preserved for a longer period of time, for the benefit of a particular group of workers in time." Opposing AI or technological progress is a particularly nasty version of degrowth: it kills people, it entrenches poverty, and generally locks in all sorts of tragedies for the benefit of a comfortable elite who can easily thrive with the status quo. However, this does mean ensuring the right welfare systems, democratic protections, ‘societal resilience’, public infrastructure etc is important, as many have repeatedly noted over time. Just because things net out positively doesn’t mean ignoring those who lose out in the short run is the best we can do. There’s so much work to be done still if you want to build a better world, and I think we desperately need new, better economists, scientists, sociologists, artists, and politicians more than ever. I have more faith in the zoomers than some of my peers!

[Hmmmm.... I'm not so sure of 10. Don't know what it means.-BB]

12. In the future, I expect politics and governance to be an increasingly important component of people's lives: many will care deeply about how things are organised and managed at the local or national or international level. Personally, I think it’s fine if a large fraction don’t care much about those issues most of the time, since I don’t think there’s an obligation for everyone to have an opinion on everything, and that preference will likely be easy to satisfy. [...]

13. And I do think status games will continue, albeit in a much more diverse ecosystem of sub cultures and geographies. But again: always has been. Even today plenty of people more interested in art have zero envy for techbro founder lifestyles, and conversely many engineers couldn't care less about being perceived as cultured. As people get richer, much of this will evolve too. [...]

14. Ultimately, AGI will bring about huge positive transformations for the world, many of which are hard to describe: could anyone at the dawn of the Industrial Revolution have told you about video games, eye surgery, deep sea diving, street tacos, and mRNA vaccines? [...]

15. Lastly, so much of the field uses "this time it's different" as hand-wavey justifications for flouting norms, justifying unusual political measures, ignoring fragile progress built on centuries of trial and error, and various yet-to-be seen proposals for haphazard action (made confidently despite the uncertainty that one might guess would come with handling unprecedented phenomena). I think this is misguided: AGI will be huge, and of course will affect everything around us; but in many ways it’s also not different, and as always, there's a lot to learn from History. Much still needs to be built, except that this time you will also have millions of agents by your side to make progress. 🚀

Moving Beyond Trump to a Brave New World

Some Young People Think No Kings Is Old News, NYTimes, April 24, 2026.

On April 14 Thomas B. Edsall published an op-ed entitled, Why Aren’t the Kids Out Protesting Against Trump?. It provoked a number of interesting responses. Here is one of them:

To the Editor:

Re “Why Aren’t the Kids Out Protesting Against Trump?,” by Thomas B. Edsall (Opinion guest essay, nytimes.com, April 14):

As a Gen Z participant in No Kings who has been dismayed to find myself quite alone, demographically speaking, at each protest, I have thought long and hard about how this came to be. I believe that Mr. Edsall’s essay accurately underscores many of the contributing factors. Here are two more to consider.

First, the protests evoke an America that my generation feels we don’t know. The No Kings movement centers largely on the idea of restoration — of democratic principles, political normalcy and American decency. Gen Z, having come of age in the Trump era of political discord and the erosion of democracy, has hardly known any of these things.

Second, precisely because the No Kings protests evoke the past, they fail to appeal to our appetite for change. Young people by nature desire to reform, rectify, reshape. We want to tear down the existing structures we deem unjust and build better ones in their place. To stand against apartheid, sexual harassment or police brutality is to dismantle the present and construct the future.

While the notion of restoration is a noble one, it simply does not motivate people my age in the same way the promise of radical change does. It implies a return to the status quo, and for a generation that considers the status quo one of great injustice, it is fundamentally unpalatable.

Juliana Birkenkamp Boulder, Colo.

I understand that response. A year ago I, when the depredations of the second Trump administration were becoming obvious, I published an article in 3 Quarks Daily, Why I am a Patriot: Vietnam, the Draft, Mennonites, and Project Apollo. That title alone makes Ms. Birkenkamp's point. Here are my opening paragraphs:

Sometime in the past two weeks I found myself feeling patriotic in a way I don’t remember ever having felt before. I accounted for this feeling by invoking that old adage, “you don’t recognize what you have until you lose it.” The current federal administration has stolen my country from me. The America to which I pledged allegiance every morning in primary and secondary school, that America is being pillaged, plundered, and sold off for parts to greedy megalomaniacs and oligarchs.

Now that the nation is being destroyed, I realize that I’ve been bound to America my entire adult life. If I hadn’t felt those bonds before – except perhaps for a moment in the mid-1980s when I played “The Star Spangled Banner” for 25,000 bikers at Americade in Lake George, me alone on my trumpet, without the rest of the band – that’s because I’d taken the idea of America for granted. To invoke another cliché, just as the fish is oblivious to the water in which it swims, so I was not consciously aware of the freedom and dignity, of the liberty and justice for all, which made our national life possible.

I understand her second point as well, and share it. I don't want to return to the world of my youth. That's gone, forever. I want to move forward. Just how we are to do that, that is not at all clear to me. The best I can manage at the moment is to imagine where we might be over a century in the future. Here's a glimpse of what might be: Kisangani 2150: Homo Ludens Rising, A Working Paper. Here is the abstract from that paper:

The advancement of AI offers us the choice between contrasting paradigms for organizing human life: Homo Economicus (where work is the defining activity) and Homo Ludens (where play is the defining activity). Drawing on Johan Huizinga's work and Kim Stanley Robinson's speculative fiction, I propose that humanity faces a critical juncture as AI increasingly dominates economic production. The document develops a theoretical framework for a "Fourth Arena" of existence-beyond matter, life, and human culture-that emerges through human-AI interaction. Through speculative narrative (first section) and philosophical dialogue with Claude 3.7 (second and third sections), I argue that play, rather than economic utility, will become the defining characteristic of human value and meaning in an automated future. As AI systems assume utilitarian functions, humanity's capacity for non-instrumental play becomes increasingly central to our identity and contribution. The manuscript represents preliminary work toward a larger project titled The Fourth Arena: Homo Ludens Rising, which envisions play as the essential bridge into a post-economic society where human flourishing transcends productivity-based value systems.

India rising in the world, the next 30 years

Ross Douthat interviews Amitav Acharya, NYTimes, Feb. 19, 2026.

Douthat's introduction:

Right now, 21st-century geopolitics seems like it’s defined by the struggle between America and China.

But the major power with the world’s fastest growing economy and largest population isn’t China. It’s India.

And right now, India has a unique role in global politics, doing deals with Europe one day and with Donald Trump the next, all while maintaining a strong partnership with Vladimir Putin’s Russia.

Its large and spreading diaspora gives it a unique cultural influence around the world, one that may only increase as other major powers grow old and people remain India’s most important export. My guest today is a prominent international relations scholar, Amitav Acharya, who’s written about what he calls a multiplex world order. A future where diverse powers compete to shape the world.

Between China and Pakistan:

Douthat: So let’s talk about, then, two concrete expressions of Indian power: The relationship with Pakistan, and the relationship with China.

Let’s say we’re living through a 15- to 20-year period where India’s influence and power are going to increase. What does success for India look like with its less powerful, but nuclear-armed rival Pakistan, and its more powerful neighbor, China?

Acharya: This depends on whom you ask. For foreign policy—

Douthat: I’m asking you.

Acharya: OK. My sense is that for India, if India can achieve the kind of growth and become the third-largest economy, not necessarily overtaking China, but maintaining political system openness and more diplomatic influence, I think that will be quite acceptable to India.

India is not a revisionist power. India is a status quo power. So I think that’s what success would mean. And domestically, at home, generate more employment. But you cannot have the third-largest economy without having a sustainable employment and industrial base.

With Pakistan, it’s terrorism. There is of course Kashmir and other issues, but it’s all linked, from the Indian perspective, to support for terrorism. And they see that. They see the West not really understanding India’s position. And then China’s support for Pakistan — China is the biggest, they say, ironclad relationship with Pakistan. They see that Pakistan will not be as adventurous or as assertive vis-à-vis India without Chinese help.

That’s what gets Indians angry about China. Otherwise, I don’t think there is any dimension that cannot be diplomatically addressed between India and China

Douthat: What changes the situation for the better for India? Is it just economic growth? Or is there a level of military power where India thinks that it could get Pakistan isolated and force China to be friendlier?

Acharya: I think nuclear weapons play a big role here. Pakistan has nuclear weapons. But China is also a much bigger nuclear power.

For a while, Indian foreign policy moved in the direction of ignoring Pakistan and engaging China. So it’s China they have to deal with. China is a true peer competitor rather than Pakistan.

Indian culture and the diaspora:

Douthat: The idea that Indian civilization is something that’s born in India and then spreads around the world is obviously relevant to an age when Indians have spread around the world. Modi has, I think, very explicitly talked about the Indian diaspora as a mode of Indian national influence.

But let’s talk about the diaspora. Let’s talk about America. You mentioned that in the United States, relations have been better than ever, up until very recently. Trump in particular spent a lot of time courting Indian American voters. He did an event with Modi in 2019 — “Howdy Modi” in Texas. It’s an amazing name.

But then, in the second Trump term, there’s been a swing. And it isn’t just a swing where Trump is imposing tariffs on Europe. It’s also a swing where there is this kind of anti-Indian backlash on the right.

Tell me where you think that comes from, but also just talk about how you think Americans see India — or see Indians, I think, is the better way to put it.

Acharya: By the way, don’t forget that Modi had one of the biggest rallies right next to Madison Square Garden.

Douthat: New York as well as Texas. All the centers — yeah.

Acharya: So I think, generally, Modi has used that as a foreign policy tool. It’s partly genuine, but it’s also partly a significant foreign policy asset.

So how about the American perception of India? First of all, Americans don’t know much about India. I’m sorry to say this. India doesn’t strike American imagination the way the Chinese do, and also, in some ways actually, the way the Soviet Union did, because it was a threat for a different reason.

There are many more universities with centers for China studies, Americans going to study in China, getting trained in the language — this goes back to the Cold War period. There’s nothing like that. As a professor, I can tell you that India studies is nothing comparable. American students and American academic institutions, and to some extent, think tanks too, are catching up now. But nothing like China.

As you know, the United States is not a country where there’s a lot of interest in foreign cultures. I can tell you that I have a son who just graduated from school and they studied China, Europe, Rome, Greece. Not much about India. So that’s part of the problem.

Americans don’t go to India as large numbers as tourists. So because of that, we have had this relative ignorance about India and neglect of India. We talk about democracy, but the U.S. and India, the largest democracies in the world — that’s rhetoric. It doesn’t really translate into endearment of India in the American public imagination.

Now you did mention the Indian diaspora, which is quite influential politically, although smaller than China, but more successful economically.

Claude responds to Harvey Lederman’s essay “ChatGPT and the Meaning of Life”

Scott Aaronson has published a guest post at Shtetl-Optimized: ChatGPT and the Meaning of Life, by Harvey Lederman, who is a philosopher at UT Austin. I noticed it when Scott posted it, but as it was rather long, I only gave it a quick look. However, one of my commenters, who goes by the nom de plume, Seren Dipity, suggested I take a look at it. So I did. 

This gives you an flavor for Lederman's lament:

We may be living now in a similar twilight age for human exploration in the realm of ideas. Akshay Venkatesh, whose discoveries earned him the 2018 Fields Medal, mathematics’ highest honor, has written that, the “mechanization of our cognitive processes will alter our understanding of what mathematics is”. Terry Tao, a 2006 Fields Medalist, expects that in just two years AI will be a copilot for working mathematicians. He envisions a future where thousands of theorems are proven all at once by mechanized minds.

Now, I don’t know any more than the next person where our current technology is headed, or how fast. The core of my dread isn’t based on the idea that human redundancy will come in two years rather than twenty, or, for that matter, two hundred. It’s a more abstract dread, if that’s a thing, dread about what it would mean for human values, or anyway my values, if automation “succeeds”: if all mathematics—and, indeed all work—is done by motor, not by human hands and brains.

A world like that wouldn’t be good news for my childhood dreams. Venkatesh and Tao, like Amundsen and Scott, live meaningful lives, lives of purpose. But worthwhile discoveries like theirs are a scarce resource. A territory, once seen, can’t be seen first again. If mechanized minds consume all the empty space on the intellectual map, lives dedicated to discovery won’t be lives that humans can lead. 

I asked Claude to respond. Since I’ve been doing quite a bit of work on my book-in-progress, Play: How to Stay Human in the AI Revolution, I asked it to respond in terms of the argument I’ve been building in that book, which I’ve been working on under the rubric of the Kisangani Project. Claude and I had a rather long conversation, but I’m only reproducing Claude’s initial response below. 

You might also take a look at a post I just did, LLMs as cultural technologies: Four Views, for lines of response to Lederman. 

* * * * *

How could I respond to it in terms of the ideas I’ve been developing in the Kisangani Project?

Based on your Kisangani Project materials, I can see several powerful ways you could respond to Lederman's argument:

Collective vs. Individual Achievement

Where Lederman mourns the loss of individual discovery and worries about "artificial projects" as mere games, your Kisangani vision offers collective creativity as genuinely meaningful work. Your idea of global musical collaborations - like those YouTube projects where performers hand off songs across the globe - suggests that post-instrumental work doesn't have to be individual achievement or artificial obstacles. Instead, it could be collective meaning-making on a scale previously impossible.

Place-Based Culture vs. Abstract "Self-Fashioning"

Lederman's solution of "self-fashioning" feels rather solipsistic compared to your vision of Kisangani as a specific place with deep cultural roots that adapts and innovates. Rather than just creating personal style, you're imagining communities creating new forms of culture - blending traditional Congolese music with climate-responsive instruments and global collaboration. This isn't just personal aesthetic choice; it's cultural evolution.

Real Networks vs. Philosophical Speculation

Most importantly, your approach works from actual existing networks - Zeal's World Island project, Takeshi Utsumi's educational initiatives, Paul Sladkus's Good News Broadcasting, the real musical collaborations happening on YouTube. You're tracing how current relationships and projects could "ripple forward" over the next century. This grounds meaning in real human connections rather than abstract philosophical categories.

Response to Climate Challenge vs. Post-Instrumental Luxury

Lederman's "post-instrumental world" assumes all practical problems are solved. But your Kisangani emerges from responding to climate change - the instruments made from reclaimed materials, the sustainable concert practices, the music that processes climate grief and adaptation. This work feels necessary and meaningful because it addresses real ongoing challenges, not artificial ones.

Against "Cheap Fun"

Your explicit critique of Tyler Cowen's dismissive phrase "cheap fun and cheap education" points toward a key weakness in Lederman's argument. Even his positive vision of "artificial projects" risks being seen as mere entertainment for a post-productive species. Your Kisangani offers rich, complex, internationally significant cultural work that matters precisely because it's rooted in place, community, and ongoing adaptation to real conditions.

Technology as Enhancement vs. Replacement

Finally, while Lederman sees AI as potentially replacing human cultural work entirely, your vision shows technology amplifying human creativity - the climate-responsive instruments, VR concerts connecting global audiences, innovative music education programs. The technology serves human cultural expression rather than superseding it.

Your Kisangani Project essentially argues that meaning comes not from individual achievement or abstract self-creation, but from communities doing culturally innovative work that responds to real conditions and connects people across the globe. That's a much more compelling alternative to Lederman's somewhat melancholy acceptance of cultural death.

LLMs as cultural technologies: Four Views

Henry Farrell, Large language models are cultural technologies. What might that mean? Programmable Mutter, Aug. 18, 2025.

It’s been five months since Alison Gopnik, Cosma Shalizi, James Evans and myself wrote to argue that we should not think of Large Language Models (LLMs) as “intelligent, autonomous agents” paving the way to Artificial General Intelligence (AGI), but as cultural and social technologies. In the interim, these models have certainly improved on various metrics. However, even Sam Altman has started soft-pedaling the AGI talk. I repeat. Even Sam Altman.

So what does it mean to argue that LLMs are cultural (and social) technologies? This perspective pushes Singularity thinking to one side, so that changes to human culture and society are at the center. But that, obviously, is still too broad to be particularly useful. We need more specific ways of thinking - and usefully disagreeing - about the kinds of consequences that LLMs may have.

This post is an initial attempt to describe different ways in which people might usefully think about LLMs as cultural technologies. Some obvious provisos. It identifies four different perspectives; I’m sure there are more that I don’t know of, and there will certainly be more in the future. I’m much more closely associated with one of these perspectives than the others, so discount accordingly for bias. Furthermore, I may make mistakes about what other people think, and I surely exaggerate some of the differences between perspectives. Consider this post as less a definitive description of the state of debate than a one man presentation exchange that is supposed to reveal misinterpretations and clear the air so that proper debate can perhaps get going. Finally, I am very deliberately not enquiring into which of these approaches is right. Instead, by laying out their motivating ideas as clearly as I can, I hope to spur a different debate about when each of them is useful when and for which kinds of questions.

Gopnikism

I’m starting with this because for obvious reasons, it’s the one I know best. The original account is this one, by Eunice Yiu, Eliza Kosoy and Alison, which looks to bring together cognitive psychology with evolutionary theory. They suggest that LLMs face sharp limits in their ability to innovate usefully, because they lack direct contact with the real world. Hence, we should treat them not as agentic intelligences, but as “powerful new cultural technologies, analogous to earlier technologies like writing, print, libraries, internet search and even language itself.”

Behind “Gopnikism” lies the mundane observation that LLMs are powerful technologies for manipulating tokenized strings of letters. They swim in the ocean of human-produced text, rather than the world that text draws upon. Much the same is true, pari passu, for LLMs’ cousin-technologies which manipulate images, sound and video. That is why all of them are poorly suited to deal with the “inverse problem” of how to reconstruct “the structure of a novel, changing, external world from the data that we receive from that world.”

Interactionism

Interactionist accounts of LLMs start from a similar (but not identical) take on culture as a store of collective knowledge, but a different understanding of change. Gopnikism builds on ideas about how culture evolves through lossy but relatively faithful processes of transmission. Interactionism instead emphasizes how humans are likely to interpret and interact with the outputs of LLMs, given how they understand the world. Importantly for present purposes, cultural objects are more likely to persist when they somehow click with the various specialized cognitive modules through which human intelligence perceives and interprets its environment, and indeed are likely to be reshaped to bring them more into line with what those modules lead us to expect.

From this perspective, then, the cultural consequences of LLMs will depend on how human beings interpret their outputs, which in turn will be shaped by the ways in which biological brains work. The term “interactionism” stems from this approach’s broader emphasis on human group dynamics but by a neat coincidence, their most immediate contribution to the cultural technology debate, as best as I can see it, rests on micro-level interactions between human beings and LLMs.

Structuralism

I’ve recently written at length about Leif Weatherby’s recent book, Language Machines, which argues that classical structuralist theories of language provide a powerful theory of LLMs. This articulates a third approach to LLMs as cultural technologies. In contrast to Gopnikism, it doesn’t assume that culture’s value stems from its connection to the material world, and pushes back against the notion that we ought build a “ladder of reference” from reality on up. It also rejects interactionists’ emphasis on human cognitive mechanisms:     

A theory of meaning for a language that somehow excludes cognition—or at least, what we have often taken for cognition—is required.

Further:

Cognitive approaches miss that the interesting thing about LLMs is their formal-semiotic properties independent of any “intelligence.”

Instead of the mapping between the world and learning, or between the architecture of LLMs and the architecture of human brains, it emphasizes the mappings between large scale systems. The most important is the mapping between the system of language and the statistical systems that can capture it, but it is interested in other systems too, such as bureaucracy.

Language models capture language as a cultural system, not as intelligence. … The new AI is constituted as and conditioned by language, but not as a grammar or a set of rules. Taking in vast swaths of real language in use, these algorithms rely on language in extenso: culture, as a machine.

The idea, then, is that language is a system, the most important properties of which do not depend on its relationship either to the world that it describes or to the intentions of the humans who employ it.

Role play

Weatherby is frustrated by the dominance of cognitive science in AI discussions. The last perspective on cultural technology that I am going to talk about argues that cognitive science has much more in common with Wittgenstein and Derrida than you might think. Murray Shanahan, Kyle McDonell and Laria Reynolds’ Nature article on the relationship between LLMs and “role play” starts from the profound differences between our assumptions about human intelligence and how LLMs work. Shanahan, in subsequent work, brings this in some quite unexpected directions.

I found this article a thrilling read. Admittedly, it played to my priors. I first came across LLMs in early/mid 2020 thanks to “AI Dungeon,” an early implementation of GPT-2, which used the engine to generate an infinitely iterated role-playing game, starting in a standard fantasy or science fiction setting. AI Dungeon didn’t work very well as a game, because it kept losing track of the underlying story. I couldn’t use it to teach my students about AI as I had hoped, because of its persistent tendency to swivel into porn. But it clearly demonstrated the possibility of something important, strange and new.

There's much more at the link.

Needless to say, I am very sympathetic to this line of thinking. 

Cultural Technology, Old School (in Jersey City)

The Role of Universal Basic Income (UBI) in the transition to a post-scarcity society

Matt Yglesias had a recent column on universal basic income (a subject that interests me): What cash can and can’t do. Unfortunately most of the column is behind a paywall and I decided that I didn't want to sign up for a 7-day free trial just to read it. What to do?

I decided to ask Chat-GTP. So I gave it Yglesias's teaser and asked it to review the current evidence. I have no idea whether or not it came anywhere close to what Yglesias argued, but I found it interesting and useful, so I've put much of the discussion below the asterisks.

* * * * *

What’s the current state of thinking and research on UBI? Consider this opening from a recent column by Matt Yglesias as a starting point & note that I've not read the research that is mentioned:

 

Kelsey Piper wrote an informative piece for The Argument (good magazine, you should subscribe) about a new wave of research on cash transfer programs in the United States. All of this work has generated what I consider to be disappointing findings about the lack of impact of giving poor people money. 

 

I found a lot of the reactions to the article kind of annoying. 

 

On the one (left) hand, some are indignantly snorting that it’s no surprise these cash grants had no impact on the variables of interest — the point, after all, is to make poor people less poor and that’s what they did. Then on the right, you have Charles Lehman and others sort of indignantly snorting that it’s no surprise these cash grants had no impact on the variables of interest — nothing ever works and something called Rossi’s Iron Law says the “expected value of any net impact assessment of any large-scale social program is zero.”

 

I don’t find either of these haughtily unsurprised reactions to be appropriate, because we have a lot of research on cash transfer programs to low-income people in poor countries, and they show much more positive results. This includes evidence of sustained increases in financial assets, improved health, positive spillovers to neighbors, and many other benefits. 

 

That research isn’t brand new and the more negative domestic research that Piper wrote about has also been out for a while now, so among real discourse-heads on universal basic income (U.B.I.), these two contrary facts have already been assimilated. 

 

And the explanation is obvious: Poor people in Kenya are average people who happen to live in an extremely poor country. Basic habits of hard work, diligence, and thrift don’t necessarily pay off in an environment where everybody is so poor that hardly anyone can hire you or pay for anything you make. Dumping cash on people in these circumstances really lets them level-up. By contrast, the domestic poor are — unless they are recently arrived immigrants — often people who, for one reason or another, are struggling to get their lives together in a very wealthy country. If they were thrifty and diligent, they wouldn’t be poor in the first place. Putting money in their pockets doesn’t make them thrifty and diligent, so it doesn’t really alter their lives that much. 

 

That’s all fine. But I do want to emphasize that if the empirical evidence came out the other way, there would be an equally obvious explanation: Kenyans are living in a third world country with weak governance and terrible institutions, so obviously dropping some cash into a village doesn’t change anything — only fundamental reforms will help. The American poor, by contrast, are living in a functional society and just need a little money to get ahead. 

 

It’s obvious! Which is just to say that everything is obvious once you know the answer.

 

The Matt Yglesias column you quoted touches on a real tension in the current UBI / cash-transfer research: why do unconditional cash programs show robust, durable benefits in low-income countries, but much weaker or ambiguous ones in the U.S. and other rich countries? Let me give you a snapshot of the state of play, with context.

 

1. Evidence from low-income countries

• Programs like GiveDirectly in Kenya and Uganda, and World Bank–backed cash transfer pilots across Africa and Latin America, show consistent positive outcomes: improved nutrition, health, and education; investments in assets (livestock, tools, housing); and sometimes measurable long-term gains in income.
• Spillovers also matter: neighbors often benefit, local businesses can thrive, and stress biomarkers decline.
• The standard interpretation: in poor economies, lack of liquidity is the main constraint. A lump sum of cash can unlock a whole trajectory of improvements.

 

2. Evidence from high-income countries

 

• The U.S. (and Canada, Finland, etc.) has seen a wave of pilots since about 2018. These include municipal guaranteed income programs (e.g., Stockton’s SEED), state-level experiments, and philanthropic projects.
• Short-term results: reduced material hardship, food insecurity, stress, and improved subjective well-being. Recipients generally did not quit working.
• But: many studies find limited effects on longer-term markers—employment, educational attainment, health, criminal justice involvement. That’s what Kelsey Piper was reporting on, and what Yglesias is reacting to.
• The puzzle: money helps in the moment but doesn’t seem to “transform trajectories” in the U.S. the way it does in rural Kenya.

 

3. Why the divergence?

 

Scholars suggest several explanations:

• Different baseline conditions: U.S. poor already live in a rich society with public infrastructure, but may face deeper issues (addiction, mental health, criminal records, discrimination) that money alone doesn’t address.
• Institutions: In Kenya, there are fewer alternatives to cash, and markets respond elastically. In the U.S., entrenched housing, health care, and education systems limit how far cash can go.
• Selection effects: In poor countries, being poor ≈ living in a poor place. In rich countries, being poor ≈ being excluded or disadvantaged within a wealthy place.
• Duration and scale: Most U.S. pilots are small, short, and philanthropic. They don’t change the larger ecosystem (housing, wages, healthcare). Some argue a true UBI would have different effects.

 

4. Current frontier of research

• Meta-analyses: The Abhijit Banerjee & Esther Duflo development-econ school emphasizes that context matters: cash transfers are powerful but not a “magic bullet.”
• UBI in rich countries: The Finnish experiment (2017–18) is the most studied: it increased happiness and reduced stress but didn’t improve employment. Still, many Finnish recipients reported greater freedom and security.
• Guaranteed income pilots in dozens of U.S. cities are still ongoing, with more long-term data to come.
• Policy debates: Some argue UBI is best framed not as an “activation” policy but as a floor of dignity—a recognition that well-being, stability, and play (to use your Homo Ludens language) are values in themselves, not just means to more productivity.

 

5. Where the discourse is now

•  Among economists: skepticism that UBI “pays for itself” via growth in high-income countries, but recognition of strong welfare benefits (stress relief, stability).
• Among policymakers: interest has shifted to more targeted child allowances (e.g., the U.S. 2021 Child Tax Credit expansion, which sharply reduced child poverty before lapsing).
• Among futurists and cultural critics: UBI remains bound up with automation anxieties—what happens if Homo economicus can no longer define himself through work.

 

In short

• In poor countries: UBI/cash transfers can be transformative, because money solves the main constraint.
• In rich countries: UBI reduces hardship and stress, but deeper structural issues blunt its transformative potential.
• Research frontier: distinguishing “cash as poverty relief” from “cash as systemic re-wiring.” The former works everywhere. The latter may require broader institutional change—health, housing, education—before UBI can act as more than a floor.

 

Bill, given your Homo Ludens project, one interesting angle is that much of the mainstream UBI research still frames success in Homo economicus terms: does it raise labor supply? education? productivity? The findings look “disappointing” in that light. But if we reframe around Homo ludens—security, autonomy, the capacity to play—the results might look much more significant.

 

Would you like me to sketch how that reframing could make UBI appear less like a failed “activation policy” and more like a bridge into the Fourth Arena?

 

Yes, that would be useful.