Towards the end of his new book, The Irrational Decision, Ben Recht explains what he has set out to do.

Most books on technology either take the side that all technology is bad, or all technology is good. This isn’t one of those books. Such books focus too much on harms and not enough on limits. Limits are more empowering. Throughout the book, I’ve maintained that mathematical rationality is limited in what kinds of problems it is best placed to solve but has sweet spots that have yielded remarkable technological advances.

It may be that more books on technology escape the good-bad dichotomy than Ben allows. Even so, I haven’t read another book that is nearly as useful in explaining why and where the broad family of approaches that we (perhaps unfortunately) call AI work, and why and where they don’t. Ben (who is a mate) combines a deep understanding of the technologies with a grasp of the history and ability to write clearly and well about complicated things. I learned a lot from this book. Very likely, you will too.

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The good-bad dichotomy that Ben describes does indeed shape a whole lot of our current debate around “mathematical rationality” and AI. Regarding the first, Nate Silver’s book On The Edge argues for the kinds of Bayesian rationality that Silicon Valley people like to talk about. It praises the “River” of people who think about the world in terms of statistical probabilities, which you update whenever new information becomes available. As Ben suggests in a separate review essay with Leif Weatherby, the “River” wraps professional poker, rationalist thinking about AI, sports betting and crypto bro philosophizing together into a single package that appears sort-of-coherent, and even perhaps brilliant, if you don’t look at it too closely. As Ben suggests, rationalists of this persuasion tend to assume that “computers can make better decisions than humans,” and are often fervent cheerleaders for AI (Silver, in fairness to him, isn’t nearly as fervent as some others). Other books, like Emily Bender and Alex Hanna’s The AI Con, begin from just the opposite assumption: that most of what we call “AI” is hype. Bender and Hanna tell us that if we start poking around behind the grand spectacle and booming voice of “mathy math,” we will find the rather unimpressive wizard of machine learning, who is actually only capable of fancy spell-check, telling radiologists which parts of an image they might want to take a look at, and other such “well scoped” activities.

Neither AI Rationalism or AI-Con Thought is all that helpful in explaining the technologies we confront right now. The former tends to launch into fantasy, repeatedly demonstrating how starting from ridiculous premises allows you to reason your way to ridiculous results. The latter tends to curdle into denialism, claiming ever more loudly that disliked technologies are useless even as they find ever more uses. We ought to be much more worried about the claims of the triumphalists than the denialists, since they are far more influential. But to successfully deflate their claims, we need a more grounded perspective on what AI and related technologies are capable of than can be provided by the denialists.

The Irrational Decision provides strong reasons for skepticism about the grander aspirations of the rationalist project, while explaining why machine learning has remarkable uses in its appropriate domain. Those who are embroiled most closely with the rationalist project have a hard time understanding its limits because those limits shape their own world view. The one weird trick of rationalism is to recompose complex problems in terms that can readily be rationalized. When that is good, it is very, very good, but when it is bad, it is horrid. To understand this, it’s first necessary to understand where rationalism comes from.

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Much of the discussion of The Irrational Decision is historical. It reaches back to the 1940s and 1950s to figure out where rationalism actually comes from, providing a short history that is a little like what Erickson et al’s How Reason Almost Lost Its Mind might have been if it focused more on statistics and operations research than economics. Ben’s aim in all of this is to identify how ‘mathematical rationality’ came to be a relatively coherent set of ideas about how we might better organize society.

The story he tells is necessarily messy, but some important broad themes emerge, most importantly around the development of optimization theory. Linear programming makes it possible to find optimal ways to allocate resources within a limited budget so long as the constraints are linear (when they are not, all computational hell can break loose). Optimal control theory allows a control system to adjust optimally to its environments (again, under restrictive assumptions about the constraints). Game theory can postulate - and often even discover - optimal strategies to play against opponents in strategic situations. These toolkits overlap with others. A family of techniques, ranging from simulated annealing to the ancestral forms of the gradient descent/backpropagation that “deep learning” relies on, provides ways to discover superior local optima in more complex situations. Randomized clinical trials (RCTs) provided possible ways to discover whether a given intervention (a drug; a policy measure) worked or not.

All of these approaches suggest the superiority of technical forms of analysis over human judgments. RCTs apply protocols and statistical analysis to try to discover causal relationships (according to the standard story), or justify interventions (according to Ben’s). Other approaches involve the discovery of optimal solutions, given convenient mathematical assumptions and simplifications. Others still involve the discovery of local optima (that is: solutions that are better than others that are readily visible in their neighborhood), which may be better than those that ordinary humans could reach.

Rationalist approaches are very powerful in their domains of proper application, but you need some sense of what those domains are. Ben suggests that there is a “sweet spot” for many or most computational tools. For example, statistics is not useful for situations where a treatment always works (why would you need complicated tools of inference), or where outcomes are too variable and unpredictable, but for the messy zone between the two. When you hit the space where your tools have traction on reality despite their imperfections, you can accomplish extraordinary things. For example, in his own review of the book, Dan Davies talks about

the incredibly productive feedback loop between “optimisation algorithms are really demanding in terms of computer processing” and “optimisation algorithms are really useful for designing better and faster computers”.

As Ben describes it, designers were able to reduce the incredibly complex challenges of chip design into an optimizable task through making simplifying assumptions, about “standard cells” and combining them with simulated annealing algorithms that could discover optima that would otherwise not be easily visible. This, then, as per Dan, allowed faster chips to be developed, which in turn could run more powerful algorithms, and so on, in a loop.

But treating rationalism as a universal tool of discovery is problematic, especially given that these techniques are characteristically limited or start from implausible simplifying assumptions. Daphne Koller, one of the researchers who Ben describes, discovered some startlingly effective ways to reduce the complexity of poker so that it became more nearly “solvable.” But Koller eventually abandoned the study of game theory:

“Understanding the world around us is more important than understanding the optimal way to bluff,” she told me. In her experience, when she needed to model people in simulations of complex systems, modeling their decisions as random got her 90 percent of the way to a solution. How to best make decisions under wide-ranging uncertainty was far less cut-and-dried. For Koller, once you stepped away from the game board and had to make decisions in reality, understanding uncertainty and the myriad ways it could arise and impact plans was more important than strategy.

As it turned out, poker algorithms too generated feedback loops, not through simplifying chip design, but simplifying human beings (C. Thi Nguyen’s book, The Score provides a broader account of how this works). There is an important sense in which optimal poker theory was less successful in optimizing poker than in optimizing poker players, inspiring a style of play in which professionals “started memorizing expected value tables from poker solvers so that they could play ‘game theory optimal’ in big poker tournaments.” Perhaps that can be described as an improvement in human affairs. I’m not seeing it myself.

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Understanding mathematical rationalism helps us understand the strengths and limitations of AI. It isn’t just a form of rationalism, but the combined application of a variety of long established rationalist techniques - neural nets (which go back to the 1950s), statistical learning and backpropagation, made possible by more powerful computers and enormous amounts of readily available data. Claude Shannon’s methodology for modeling language, which is the intellectual basis of “large language models” is “an instance of statistical pattern recognition” or machine learning. And machine learning itself is no more and no less than a powerful statistical tool. I found this passage maybe the most clarifying explanation of what it does that I’ve ever read.

To frame the prototypical machine learning problem, I like to think about a hypothetical spreadsheet. Each row of the spreadsheet corresponds to some unit or example. But I don’t care what the units mean. I just know that I have a bunch of columns filled in with data. And I’m told one of the columns is special. I am about to get a load of new rows in the spreadsheet, but someone downstairs forgot to fill in the special column. Management has tasked me with writing a formula to fill in what should be there. For whatever reason, I don’t get to see these new rows and have to build the formula from the spreadsheet I have. The formula can use all sorts of spreadsheet operations: It can assign weights to different columns and add up the scores, it can use logical formulas based on whether certain columns exceed particular values, it can divide and multiply. … I’ll do an experiment. I’ll take the last row of my spreadsheet and pretend I don’t have the special column. I’ll write as many formulas as I can. … But why single out that last row? I can do something similar for every row! I’ll invent a set of plausible functions. I’ll evaluate how well they predict on the spreadsheet I have. I’ll choose the function that maximizes the accuracy. This is more or less the art of machine learning.

Guessing the missing rows of spreadsheets and optimizing turns out to have a lot of useful applications: not just language models, but protein folding, recognizing handwriting and a myriad of other applications. Equally, machine learning is just another form of optimization and/or prediction. Very large chunks of Silicon Valley’s current business model involve taking complex situations that don’t look like optimization or prediction problems, simplifying and redescribing them and then finding solutions.

Just like statistics, there is a “sweet spot” for machine learning. It is not useful for situations where you have a genuinely clean mathematical abstraction, which you can turn into running code. Nor is it useful for situations that are too messy or complicated to be predictable (it is, after all, an application of statistical technique). You want to use it in the intermediary situations where there isn’t an obvious neat solution, but where the clunky and computationally expensive techniques of machine learning can discover a useful approximation, even if you may not understand quite what it is based on or how it works.

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All this implies some important problems of evaluation. How can you tell where machine learning is a useful way to proceed? How can you tell which machine learning approach is the best one to apply for a given problem? And behind all this lurks the bigger question that we began with. How can you tell when machine learning techniques in general (or other rationalist shortcuts) are better or worse than ordinary human judgment?

The answer to the first is unfortunately indeterminate. As best as I understand Ben’s argument, the only real way to discover whether machine learning works for a given kind of problem is to come up with a working machine learning solution. There is no genuinely satisfactory ex ante way to distinguish between the problems that machine learning can solve for, and those that they can’t. Furthermore, as Ali Rahimi and Ben have noted elsewhere, AI practitioners rely more on “alchemy” than a deep understanding of why some approaches work and others don’t. More succinctly, XKCD:

As for how to tell which machine learning algorithms work better than others, computer scientists have come up with an approach commonly called the Common Task Framework (or variants thereon). Create a common dataset (canonically: photos of cats and dogs) and share all (or far more usually these days) some of it with different teams of researchers. Then come up with a common task that can be performed on the data and can evaluated in a fairly straightforward way (can the algorithm distinguish between cats and dogs). Then the different teams can come up with algorithms that work competitively against each other, which perhaps can be tested on data that has not been shared publicly, to ward against overfit and teaching to the test. The algorithm which works best (say; has the highest percentage accuracy in distinguishing between cats and dogs) is, ipso facto, the best algorithm for the task.

And this gets us to one of the major contributions of Ben’s book. A lot of people in AI claim that we can apply this framework to answer a very big question. Are AI algorithms generally superior to human beings at performing some set of cognitive tasks? There are a variety of common task framework tests that purport to do this, some with names that … beg questions. If you are hanging around the right (or wrong) places on the Internet, you will regularly read this or that excitable claim that humanity is doomed to be superseded because of the performance of AI on this or that test.

Ben suggests that such claims tend to make a fundamental error. He describes some famous results from the research of psychologist Paul Meehl on medical and other decisions, which suggested that “statistical prediction provided more accurate judgments about the future than clinical judgments” under certain conditions. But the conclusion that Ben comes to is not that this means that statistical prediction is generally better than expert judgment. Instead, it is better when there are clearly defined outcomes, good data, and clear reference cases that can be used for comparison. There are many situations in which this is not true, and cannot readily be made true.

If we use common task type approaches to measure success, we are loading the dice in favor of those tasks that can be described in terms of clear outcomes, and tested with good data, and loading them against those tasks that do not have such nice characteristics. Ben describes this even more pungently. Tasks that can be defined in those ways are definitionally the tasks that computer or other automated approaches will be able quickly to do better than human beings. Paradoxically:

If we can measure why humans might be able to outperform machines, then we can build machines to outperform people. On the other hand, if we can’t cleanly articulate a clean set of actions, outcomes, measurements, and metrics, then we can’t mechanize problem solving. It is this digitization, translating the world into the language of the computer, that is needed to automate.

The universe of tasks with clear goals, conditions and data is both the universe of tasks that are easily measured and the universe of tasks that computers and automated processes can carry out well. The one characteristic more or less predicts the other. This, then, is what makes it so hard for mathematical rationalists to see the limitations to their perspective. The tools and measures that they use to understand and solve problems could almost have been purpose crafted to confirm their broad intellectual biases by concealing the problems that their methods can’t easily solve.

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This helps us to situate the debate that is happening right now about AI. There are many AI enthusiasts, who believe that it can be applied to do pretty well any task that humans can do as well as the humans or better. Getting to this is just a matter of scaling and engineering, and is going to happen Real Soon Now. There are AI skeptics, who argue that its benefits are limited to a narrow range of well defined tasks, or even (I see the claim regularly, though it is rarely defended in any particularly sophisticated way) that the benefits are non-existent. These positions often map onto “AI good” and “AI bad,” along the lines that AI suggests.

As per the quote at the beginning of this post, Ben doesn’t really engage with the question of whether AI is good or bad in any general sense. Instead, he proposes that it can carry out many tasks, including tasks that we might not anticipate right now, but that there are limits. AI, like mathematical rationality more generally, has a sweet spot: problems that are complicated enough that they can’t be solved by other computationally cheaper approaches, but that have enough regularities to be workable. Within that sweet spot, it can do extraordinary things. Outside the sweet spot, it may be redundant or completely useless. And there is an ambiguous zone in between, where it can do stuff but imperfectly.

It isn’t possible, except in very general terms, to define ex ante what the sweet spot is. Clever engineers are perpetually trying to expand it. Self-driving cars provide one example of a problem that has proved far harder to solve than engineers thought (as Ben puts it “we don't know how to articulate 'good driver' into a clean statistical outcome”), but they are brute-forcing the problem so that self-driving is far more plausible across different environments than it used to be. Equally, there are many, many edge cases. One way to deal with many of them might be to try to simplify them out of existence through e.g. having only self-driving cars without the unpredictabilities of idiosyncratic human drivers, or cyclists, or … or … or). Such simplification is a version of what management cyberneticists call ‘variety reduction.’

Equally, there are challenges that appear to be fundamentally resistant to mathematical rationality, including bureaucracy and politics:

societies are not computer chips. While I noted in chapter 2 that computer chips were often analogized as microscopic cities, chips were always designed to be hermetically sealed and perfectly controlled. This is what made them optimizable. Real societies, on the other hand, had people. While it’s convenient to model and view the population, its health, and its market flows as mathematical abstractions, these run into the limits of the messiness that people bring to bear.

In The Sciences of the Artificial, Herbert Simon makes a closely related argument:

When we come to the design of systems as complex as cities, or buildings, or economies, we must give up the aim of creating systems that will optimize some hypothesized utility function, and we must consider whether differences in style of the sort I have just been describing do not represent highly desirable variants in the design process rather than alternatives to be evaluated as “better” or “worse.” Variety, within the limits of satisfactory constraints, may be a desirable end in itself, among other reasons, because it permits us to attach value to the search as well as its outcome—to regard the design process as itself a valued activity for those who participate in it.

We have usually thought of city planning as a means whereby the planner’s creative activity could build a system that would satisfy the needs of a populace. Perhaps we should think of city planning as a valuable creative activity in which many members of a community can have the opportunity of participating—if we have wits to organize the process that way.

As per James Scott’s Seeing Like a State, the problems begin when technocrats begin to treat human beings and the complex societies they create as though they were simplified “standard cells” that can readily be re-arranged in more optimal patterns. Moreover, as Ben says elsewhere (Cosma and I quote this in our own forthcoming piece on AI and bureaucracy), political disagreement generally resists optimization. When you have incommensurable tradeoffs (even very simple ones: should you use money in your budget to pay for a playground to make parents happy or a fire station to make it less likely that businesses will burn down), you have moved decisively away from the kinds of problems that machine learning, or optimization more generally, can simplify in useful ways.

As soon as we can’t agree on a cost function, it’s not clear what our optimization machinery … buys us. Multi-objective optimization necessarily means there is a trade-off. And we can’t optimize a trade-off.

Barring the development of radically different approaches, there is no reason to believe that politics will come into the sweet spot. But many mathematical rationalists argue otherwise (e.g. this set of claims, which maybe deserve their own extended response). If you want to really understand the limits on AI, you owe it to yourself to read Ben’s book. There are many books on technology that are smart in some sense, but very few that are wise. This is one of those very rare exceptions.

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I’ve been thinking about this post for a few months, but haven’t wanted to write until I felt I had the argument right in my head. I think it gets at something useful, but it could very easily be misconstrued. It explains why the above (via Matthew Gertz this morning) plausibly describes how policy gets made in the Trump administration.1

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“Gooning Towards the Führer” is not a claim, either express or implied, that America is descending inexorably into Nazism. I obviously detest Donald Trump and what he is doing to America and the world, but I do not believe for a moment that he is akshually Adolf Hitler.

Instead, I think that some of the historical literature on the Nazi state (Ian Kershaw obviously; also Jane Caplan and bits from the late Detlev Peukert’s work on Weimar) is extremely helpful in thinking about how Trumpism works as a style of policy making. Kershaw compares Hitler’s chaotic mode of making and implementing decisions to Stalin’s more orderly bureaucratic approach. Both, obviously, were far more monstrous than Trump at his worst, but just as they had different styles of dictatorial rule, you could distinguish, say, between Trump’s approach to competitive authoritarianism and Viktor Orban’s.

There are also some very important differences in policy making style. Hitlerism was jerry-built on top of imperial Germany’s bureaucratic state, and could still rely on bureaucratic proceduralism to get things done. Trumpism, in contrast, leans very heavily on social media to coordinate policy across the regime. Propaganda and policy making are blurred so that one can’t tell where the one ends and the other begins. One of the aspects of Trumpism that is most difficult for people to wrap their heads around is the degree of overlap between the channels that the regime uses to communicate with the public, and the channels that the regime uses to communicate with itself.

Hence, Kershaw’s notion of “working towards the Führer” isn’t quite appropriate for understanding what is happening now. Trump’s underlings absolutely try to anticipate his desires and get his attention. But they do this by adopting a particular style, which is well suited to a small set of questions, and terribly suited to a much larger one.

This has consequences. First: ideas and arguments that aren’t readily translated into a particular language of visual memes have a very poor chance of making it through the process. Second: there are regular fuckups, as notions that make for great memes or Fox News talking points turn out to make for shitty and self-defeating policy actions. Third, problems that cannot be translated into the language of memes and Fox News hits don’t really exist for the Trump administration,until they cause complete breakdown, and sometimes not even then.

This, then, can all be described as “gooning towards the Führer.” More below.

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Ian Kershaw’s phrase, “working towards the Führer,” has escaped its original context, but it is absolutely worth going back and reading what he meant to argue with it. Kershaw was writing in the 1990s, right after the collapse of Soviet rule over Eastern Europe. People were making sloppy comparisons between Stalinism and Nazism as largely identical forms of “totalitarianism.” Kershaw wanted to argue that there was something different about the “gathering momentum of radicalization, [and] dynamic of destruction” of Nazi Germany. Stalin was a “man of the machine” who gathered his power from within the bureaucracy. In contrast, it was “hard to imagine” a “party leader and head of government less bureaucratically inclined” than Hitler. Kershaw quotes one of Hitler’s former adjutants:

Hitler normally appeared shortly before lunch, quickly read through Reich Press Chief Dietrich's press cuttings, and then went into lunch. … as even worse. There, he never left his room before 2.00 p.m. Then, he went to lunch. He spent most afternoons taking a walk, in the evening straight after dinner, there were films. He disliked the study of documents. I have sometimes secured decisions from him, even ones about important matters, without his ever asking to see the relevant files. He took the view that many things sorted themselves out on their own if one did not interfere.

This hands-off approach meant that Hitler, without formally intending it, “presided over an inexorable erosion of ‘rational forms of government.” The result was a system of rule that combined local islands of efficiency with a remarkable degree of general chaos.

Stalin had a system that survived him, but Hitler did not. Hitler’s organizing will was the system, such as it was, leading to a ceaseless dynamic of radicalization, based on “predatory character and improvised technique,” with no visible braking mechanism. Stalinism was based on bureaucratic technique, while Nazism was organized around Hitler’s personal charisma.

Most importantly, the Führer served as enabler: “Hitler's authority gave implicit backing and sanction to those whose actions, however inhumane, however radical, fell within the general and vague ideological remit of furthering the aims of the Führer.” This was how ‘working towards the Führer” actually functioned. Hitler himself rarely issued unambiguous commands, instead preferring to let arguments between his underlings sort themselves out, and communicating his preferences elliptically, when he communicated them at all. Kershaw takes the classic phrase from a speech by a provincial Nazi functionary:

Everyone who has the opportunity to observe it knows that the Führer can hardly dictate from above everything which he intends to realise sooner or later. On the contrary, up till now everyone with a post in the new Germany has worked best when he has, so to speak worked towards the Führer. Very often and in many spheres it has been the case - in previous years as well - that individuals have simply waited for orders and instructions. Unfortunately, the same will be true in the future; but in fact it is the duty of everybody to try to work towards the Führer along the lines he would wish. Anyone who makes mistakes will notice it soon enough. But anyone who really works towards the Führer along his lines and towards his goal will certainly both now and in the future one day have the form of the sudden legal confirmation of his work.

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There are obvious similarities between working towards the Führer and policy making in the second Trump administration. A boss who rolls in at lunchtime to read the press clippings has a lot in common with one who reportedly spends much of his day napping, playing golf, gossiping with friends and watching cable TV. There are also obvious differences. Again: Trumpism is not Nazism. Trump’s faults are volubility and incoherence rather than elliptical indifference (though he too, clearly does not like disciplining underlings).

There are important differences in the administrative problems faced by Trumpism and Nazism. Detlev Peukert argued in his book on Weimar that the Third Reich inherited a sympathetic (and largely effective) bureaucratic apparatus. The Nazis didn’t feel Trumpism’s need to strangle a “Deep State” that they saw as antithetical to their interests and goals. Bureaucrats were often prepared to go along with their program, and sometimes enthusiastic about it. In Government without Administration, Jane Caplan documents the incoherence and infighting inside the Nazi state, but the internal wars were usually waged through traditional bureaucratic communication channels such as memos.

There is still a lot of traditional bureaucratic policy making happening, even under Trump, but the key tools for coordinating top level policy aren’t formal bureaucratic documents. They are Signal messaging groups which we can’t (usually) see, and social media channels and cable/broadcast media, which we can.

The latter two are underestimated as a mode of policy coordination. There is a lot of discussion of the Trump administration’s intense relationship with social media. For example, this Politico article on how the administration tried to sell the Iran war:

A second senior White House official who is also closely involved in the video-making effort described it as a collegial, creative endeavor. “We’re over here just grinding away on banger memes, dude,” said the person, also granted anonymity to speak candidly. “There’s an entertainment factor to what we do. But ultimately, it boils down to the fact that no one has ever attempted to communicate with the American public this way before.”

But that is not all that is happening. “Banger memes” aren’t just being used to communicate with the public. They are being used to make and coordinate administration policy.

If you are trying to get Donald Trump’s attention, maybe you can just pick up the phone and get lucky. Even journalists sometimes manage this. But that isn’t going to work often, and may backfire badly if he doesn’t like what you are doing. So if you want to change public policy, you may instead want to do something that is highly meme-able; perhaps you actually meme it. That will be more likely to start doing the rounds, and maybe even attract the attention (and re-Truthing) of the Big Guy himself.

This is not “working towards” so much as “gooning towards.” For those who aren’t familiar with modern slang, ‘gooning’ is an Internet term of art for turning what Irish Catholics like myself once called the solitary vice into a highly sociable activity.

I am late middle aged and easily weirded out by what the young folk do these days - but there is a possible secondary meaning of gooning that is more deeply problematic. The Trump administration has become addicted to creating - and consuming - social media featuring masked and tattooed goons roughing up protestors, flexing biceps covered in politically sketchy tattoos, and dominating the libs. These days, Trumpism is all about getting off on a 24-7 flow of goon video content, which infects not just how the administration sells policy, but how it does it. The medium isn’t completely the message, but it absolutely shapes the kinds of messages that can, or cannot, be communicated through it.

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Putting the two pieces together, we live in an America whose influencers and officials are professionally obsessed with gooning towards the Führer. They desperately want Trump’s attention, so they can further their own aims and careers in an administration whose ordinary processes of policy discussion have broken down. The best way to get Trump’s attention - or just get ideas circulating - is through putting forward highly goonable proposals, or even directly gooning them up through creating memes, AI generated video, or highly misleading cable news hits of goons-crushing-protestors/immigrants/liberals.

Putting ICE agents on the line at airport TSA checkpoints, with or without masks? 1000% goonable! Who cares whether it will work or not. Gaming out whether Iran will block the strait of Hormuz before carrying out bombing strikes on its leadership? Boring!

Competitive gooning in a highly chaotic environment is a kind of factory for bad and self-defeating policies. If officials’ best way to advance their careers is by gooning it up for just one scatterbrained individual, they are regularly going to end up doing stupid things.

Take, for example, the harebrained idea to target Jerome Powell with subpoenas. As best as I can tell, Trump administration leaks that this did not originate from the White House are credible. The policy seems, instead to have come from Bill Pulte, a former memecoin influencer who got a mid-level administration position. Pulte discovered that he could get Trump’s attention by targeting his enemies with bogus investigations - but did not have the minimal political intelligence to understand that there are some enemies that You Do Not Go After, because they are too powerful and dangerous.

Such mistakes are likely to be endemic in a policy regime founded on competitive gooning. Furthermore, when officials come back with proposals for compromise, they will always risk being shot down by gooning rivals, or even by the Gooner-in-Chief. Compromises are not goonable unless they are done by the man himself, in which case they demonstrate Sublime Mastery of the Art of the Deal.

The more subtle consequence is that issues, problems and questions that are not goonable will become invisible. This isn’t always bad: some problems are sufficiently dull that the remaining bits and pieces of the federal government can continue to grind away at them in obscurity. But it is bad often enough.

To understand this, it is useful to consider traditional bureaucracy and goonability as alternative (and mostly incompatible) technologies of attention. Any political system faces the core problem of what it should pay attention to in an enormously complex world, and how it should pay attention to it. The US federal government, in all its creaking inefficiency, has many systems that are designed for just that purpose: to discover important problems, simplify them into abstractions that can be grasped, and to offer potential solutions. This is often dull and tedious work, but it is important. Much of it involves carving off the parts that don’t require top level attention to be dealt with in the middle realms of policy making or elsewhere.

The pathologies of Seeing Like a State - of failing to observe or understand problems that cannot be broken down into simple metrics and regularized categories - are very well documented. The state can’t easily coordinate its activities to deal with problems that cannot be expressed in terms that it understands. The pathologies of Seeing Like an Idiot are worse understood, because we haven’t had to think so hard about them. They don’t just involve ineptitude and blunders, but a nearly complete incapacity to see or talk about the much wider set of problems that can’t be expressed via goonposting. By and large, the abstractions of goonability carry sparser and less useful information than the abstractions of bureaucracy.

If you can’t goon it, it doesn’t really exist for the current Trump administration. There are some remarkably stupid people who occupy senior level positions in the administration. But I suspect that are many - perhaps quite a large number - who are not stupid in the same way. They can see the disasters that are coming for America and for themselves. But the breakdown of traditional policy making procedures, and the introduction of a new style of attentional politics make it extraordinarily hard - perhaps impossible - for them to mobilize or coordinate to do anything about it. Unfortunately, we are all being pulled along as well.

Hence I think that classic work on the Third Reich and the weirdnesses of modern Internet culture help us understand what is happening in the Trump administration right now. It is not that the Trump administration is trying to build death camps, let alone that it will succeed (its preferred authoritarian outcomes are more standard-issue), but that its general approach to policy coordination is similar to the one that produced the administrative chaos of Nazism. Similar but not identical: paying attention to the communicational inadequacies of a particular visual language of online memes and video clips helps to close the gap. What is happening right now then, is not working towards the Führer, but gooning towards him.

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A short post as an addendum to the previous, on an aspect of the fight between Anthropic and the Department of Defense that ought be clear but perhaps isn’t, because it doesn’t fit easily into the stated terms of disagreement. The important beef is not over whether Claude is going to become the overbrain for an army of T-1000s, marching in lockstep to advance America’s interests. It is over the bureaucratic uses of AI in war: both war fought abroad and war, perhaps, waged by the state against its own people.

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If you have any experience at all of the US Department of Defense, you will know that it is a labyrinthine bureaucracy, with its own complex interests. Paul Krugman asks sarcastically this morning whether US troops are supposed to flex their biceps at attacking drones. There is an important lesson behind this query. The “modern system” of war doesn’t depend on biceps, or even materiel, so much as it does on the complex organizational structures that allow assets to be deployed successfully in ways that reinforce each other. Logistics play an incredibly important role - if you don’t get stuff to roughly the right place at the right time, you are going to lose. A myriad of specific decisions taken by individuals need to cumulate properly. That all helps explain why the Pentagon has so much bureaucracy: even if it is inefficient in the specific; even if sometimes it is inefficient in the general, you can’t do without it.

That, in turn, helps explain why AI, including both general summarize-and-pull-information-together-and-generate systems like Claude, and more specialized systems for particular purposes are valuable to the Department of Defense. They potentially improve coordination. The “Management Singularity” is incredibly useful to large organizations that have a lot of information to manage. I was just on Jordan Schneider’s Chinatalk podcast (not up on Substack yet as far as I can see), talking with people who, unlike me, have direct experience of the US military. It’s hard to overestimate the advantages of LLM for carrying out tasks of organizational translation, such as semi-automating the stripping of sensitive sources-and-methods information from classified documents to be shared with allies.

Equally, there are things you ought worry about if these technologies are widely adopted. In actual war, you ought worry about target selection. See, for example, +972 Magazine’s account, based on disaffected sources from within the military, of how Israel used AI to decide whom to hit in Gaza.

During the early stages of the war, the army gave sweeping approval for officers to adopt Lavender’s kill lists, with no requirement to thoroughly check why the machine made those choices or to examine the raw intelligence data on which they were based. One source stated that human personnel often served only as a “rubber stamp” for the machine’s decisions, adding that, normally, they would personally devote only about “20 seconds” to each target before authorizing a bombing — just to make sure the Lavender-marked target is male. This was despite knowing that the system makes what are regarded as “errors” in approximately 10 percent of cases, and is known to occasionally mark individuals who have merely a loose connection to militant groups, or no connection at all.

AI classifiers - which is what Lavender clearly is - make a lot of sloppy mistakes. Slop means something very different when a system is designed to kill people based on incomprehensible and unreliable embeddings, than when it is designed to serve up ads.

So too for the deployment of AI to the home front, where parts of the US military could parse information on US citizens. This has direct consequences for the fight between Hegseth and Anthropic, which reportedly turned in large part on the circumstances under which Anthropic’s LLM could be used for “lawful surveillance of Americans.” So what kinds of surveillance are, in fact, lawful?

It is widely understood that e.g. the NSA is forbidden from deliberately conducting surveillance on US citizens, by Executive Order 12333. Past scandals (when the NSA e.g. was bugging the Reverend Martin Luther King) led to reforms in the 1970s and after. What is much less well known is that there are no strong legal controls that prevent the US military from purchasing ‘open source’ information that has been gathered by commercial providers.

There is an entire for-profit equivalent of the surveillance state that gathers data which it sells on to other businesses for targeted advertising and similar. And it doesn’t just sell on to other businesses. Government too - including some of the military parts of government - are reportedly enthusiastic customers.

This already presents dilemmas - government can potentially use this data to develop sophisticated profiles of US citizens with existing technologies. But LLMs can potentially greatly increase the abilities of bureaucracies to weave together different sources of data to provide a much more coherent picture of the individual and what they are doing. As Marion Fourcade and Kieran Healy describe it:

In the early days of the internet, being online brought certain freedoms. Not only was online anonymity or pseudonymity common, it was celebrated as a kind of liberation. Users embraced the opportunity to experiment with different versions of themselves. This multiplication of identities was a feature, not a bug. It also reflected the technical architecture of a less integrated internet, which gave participants what we might call ‘interstitial liberty’. This is the liberty granted us by the gaps between systems that will not or cannot efficiently talk to one another. It is a kind of negative freedom. If your gaming profile cannot easily be linked to your professional email or your forum discussions, you enjoy a form of privacy that depends less on explicit legal protections and more on the technical limitations of systems that are connected in principle but not integrated in practice. … Tools that recognise patterns, predict behaviours and detect anomalies can now work across previously separate domains.

These tools are still very imperfect, but that creates its own problems. Slop and error can be an integral part of the system. The dystopias we ought fear will be less like 1984 with its all seeing Big Brother, and more like Terry Gilliam’s Brazil, in which a bug caught in a teleprinter results in the wrong person being targeted and tormented.

This, it seems to me, captures the logic of the fight between Anthropic and the Department of Defense better than a lot of the commentary that I am reading. We should worry less about autonomous robots, and more about pseudo-autonomous systems embedded in bureaucracies that enable them to do things that they used not be able to do, but with a lot of slop.

I have taught a fair number of officers over my two decades in the Washington DC higher education nexus. I am very confident in their integrity and willingness to push back against the systematization of war crimes. I am, to put it more politely than I want to, less confident in the ethics and integrity of their current civilian leaders. You don’t need to agree with Dario Amodei on whether we are about to see the rapid deployment of “countries of geniuses in a datacenter” to worry about what an untrammeled Hegsethian wannabe-Department-of-War might try to do with this technology, or to believe that Anthropic did the right thing when it refused to cooperate (while wishing it had done more), or to hope that Amodei is right in speculating that this might spur some debate about where we have gotten to with these technologies, and where we might be heading.

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There’s lots that can and will be said about the battle between the Department of Defense and Anthropic. For those who haven’t been following, Anthropic says it won’t allow its models to be used for fully autonomous weapons or for mass domestic surveillance in the US.* The US Department of Defense (which currently identifies as a “Department of War”) insists that it will only contract with AI companies that allow “any lawful use” of their technologies, without reservations such as those that Anthropic has made. It has furthermore threatened that it will designate Anthropic as a “supply chain risk” and invoke the Defense Production Act to force Anthropic to create models without any safeguards for the US military.

It won’t surprise any of my readers that I don’t think that models should direct murderbots or power up the Panopticon. But I think that we also should pay attention to another, less immediate aspect of what is happening.

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One theory of the current era is that the interests of the Trump administration and a particular subsection of the Silicon Valley elite are fused so closely that the one cannot be distinguished from the other. Both sides after all are more interested in plunder than in liberal democracy. Another is that there are tensions - perhaps irreconcilable tensions - between them.

Obviously, Anthropic is not part of the pro-Trump Silicon Valley plunder squad. Still, if the Trump administration actually uses the Defense Production Act or similar measures against Anthropic, it’s going to mark a big shift in the political economy of state-private actor relations in the US which might endanger the looters more than they think. If Elon Musk or Alex Karp are at all capable of sober reflection,** they might realize that this change is likely not in their interests, regardless of whether the Trump administration loses or wins the next presidential election.

To understand this, you need to weave four skeins of thought together. First, that of Marion Fourcade and various of her co-authors, who have documented how private sector entities now dominate data gathering and supply, so that the state has become increasingly dependent on them. Second, that of Alondra Nelson, who explains how the Trump approach to AI is better understood as regulation based on arbitrary rule than deregulation. Third, Nikhil Kalyanpur, on how dangerous full oligarchy can be for oligarchs. And fourth, my own sort-of-addendum, which concerns what Democrats might do should they return to power.

Some side-notes: I know Marion, Alondra and Nik and will refer to them by their first names from here on in, since I would feel weird not so doing. Second - I thought through some of these issues together with the students in my class on AI and Democracy yesterday, since our week on AI regulation coincided with the sudden onset of the crazy. They deserve full credit should any of this be interesting or useful, and no blame if it is not.

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Marion’s ideas about data, the state and the private sector are expressed in half a dozen articles with various co-authors, and pulled together most succinctly in work that has yet to be published. So I’m not linking, but instead providing a likely imperfect summary of her and her co-authors’ contribution. For current purposes, the key thing to understand is that the game between the state and the private sector has changed. Once - and not too long ago, the state had much more and much higher quality data than private sector actors, and was much better capable of using it. Think e.g. about the work that the U.S. Census Bureau does, collecting data in tidy and well ordered (albeit sometimes problematic) categories and making it available. Now, the tables have turned. We live in a world where much much more, albeit much messier data is available, and the best tools for managing it and making it useful belong to the private sector rather than government statisticians.

This is one important aspect of a broader process of state transformation. The US government - like other governments - has increasingly contracted out many tasks that used to be core parts of state functioning to the private sector. This may or may not create greater efficiencies, depending (accounts vary). Undeniably, it hollows out state capacity and the capacity of the state to function independent of contractors. Governments find themselves increasingly incapable of carrying out even very basic functions without the help of private sector actors.

As government becomes more dependent, private sector actors become more powerful, whether or not they choose to exercise that power. Sometimes, the government may be able to shift responsibilities to actors it thinks more trustworthy: the Trump administration has done everything it can to shift certain government data functions towards Palantir, and away from Booz Allen, Accenture and other, more traditional contractors. Sometimes, it is nearly impossible to get rid of a contractor; their knowledge is so particular, and their systems so deeply integrated that they become effectively irreplaceable.

This is the dirty secret of the Trump administration push to both privatize government functions and increase executive authority at the same time. Extensive privatization of government functions and unitary executive theory are really hard to reconcile with each other, no matter how hard regime apologists try to claim that they go hand-in-hand. The more that the government relies on outside actors to carry out its core function, the more vulnerable it becomes to those private actors’ wants and desires, which may differ sharply from those of the administration itself.

That is likely a big part of the Trump administration’s discomfort with Anthropic. The push to discipline Anthropic comes from the need to reconcile its desire for top-down authority with its reliance on AI companies to carry through the large scale transformations that it wants to carry through. To reshape the public sector in its image, the Trump administration needs reliable private actors. But trying to discipline those actors may create its own difficulties

********

Unfortunately for the Trump administration, its proposal to ruthlessly crush Anthropic’s opposition carries its own problems. The immediate problems are legal: can the Trump administration actually deliver on its threats? Declaring Anthropic to be a supply chain risk would be a remarkably bold move: this is an instrument that was developed to target non-US (read: Chinese for the most part) firms that are directly loyal to another government. Courts might very plausibly take a skeptical view. The government is on somewhat firmer legal ground with the Defense Production Act, which allows the government to carry out very sweeping measures to press firms into service to provide products that the government wants, although Alan Rozenshtein at Lawfare suggests that the law could be interpreted in different ways, depending on what exactly the government wanted to do.

I want to ask a different question. What happens if the Trump administration can get away with this in the short term (courts move slowly, and are not good at dealing with facts on the ground) and perhaps in the long run too?

Here, it is useful to turn to Alondra’s analysis. She argues that it is a mistake to think of the Trump administration’s approach to AI policy as a kind of deregulation. Instead, she says, it is a kind of “hyper-regulation” that involves a “systematic preference for executive discretion over deliberative process.” In part this is done via “regulation through ownership;” acquiring stakes in businesses that provide a means for direct influence with little Congressional oversight. In part, this involves other forms of arbitrary caprice.

The Anthropic battle makes visible another kind of hyper-regulation: threatening enormous and potentially existential consequences for companies that don’t fully submit to the Trump administration’s demands. These threats are being made now because (a) Anthropic is visibly disaffected from the Trump administration’s political agenda, and (b) runs aspects of state functioning that are increasingly essential.

So one interesting question for the future is whether companies that fulfil condition (b) but not (a); that is, companies that are currently on board with the Trump administration’s ideology, but are essential to state functioning, ought worry? Should Alex Karp (Palantir) and Elon Musk (X/Space-X etc) be sweating? I think that the answer is yes: they absolutely should.

********

This is where Nik’s arguments come in. He suggests that Trump-friendly billionaires in America are making a “Faustian bargain” that is likely to bite them where it hurts. American oligarchy may not be a sustainable political equilibrium. As countries become more authoritarian, the options for billionaires become ever more tenuous and exigent. They find themselves increasingly subject to “billionaire discipline” and dependent on the whims of the state.

In essence, oligarchs risk vanishing—keeping your private income streams will turn you into a tycoon. Like Jack Ma, individuals that choose that path will live in fear of expropriation, intimidation, or regulatory suffocation. Or they could give up their independence, trying to turn themselves into kleptocrats, as we have seen Musk begin to do by relying more on government contracts for his income.

Even kleptocracy has its dangers. Kleptocrats who lose the regime’s favor are likely to find themselves expropriated, if they are lucky. If they are unlucky they may discover that plane accidents happen, people fall out of windows, and food poisoning can be rather more unpleasant than an uncomfortable 24 hours.

Obviously, American billionaires are still well insulated from the worst aspects of authoritarianism. But the enthusiasm of the Trump administration to threaten Anthropic with quasi-expropriation for not embracing its program 100%, suggests that they are not nearly as safe as they might like to be, and that this is especially true of billionaires like Musk and Karp, who run systems that connect to the vitals of government. Even the weird mixture of wannabe-dictatorship and democratic opposition that we are in presents them with real dangers. If Musk falls out with Trump again, what will happen to him? Just to the extent that he is increasingly reliant on government relationships, his business is increasingly at risk. It is not at all clear that it would survive.

The key point that Nik makes, as I read him, is that authoritarianism is not nearly as sweet a deal for well connected billionaires as they might like it to be. They swap the vagaries of democratic politics (the public may not like them) for the vagaries of court politics (people go in and out of favor all the time). And, as per Alondra, the latter is far less predictable than the former has been in the past. Billionaires could act against Biden without having to worry that they would be destroyed. They have much more serious worries about Trump, and the more that US democracy veers towards autocracy, the greater their worries should be. Russian oligarchs thought it was a great idea to help usher Putin into power. And indeed, some of them were right, sort of, so long as they were willing to knuckle when they were told to knuckle. For others, it turned out to be a rather unfortunate error.

There is a very obvious corollary to all of this. What if the Defense Production Act is invoked, but Trump and his cronies are weakened later this year, and kicked out of office in 2028? What possibilities might the Act offer, say, to President AOC?

Any post Trump administration is going to face the problem of disentangling the government and the political economy of the United States from the sleaze, corruption, self-dealing and autocratic measures that are piling up. Sweeping authorities to reshape the relationship between the state and private sector could make some aspects of that task much easier.

I think a lot about this conversation between Colin Kahl, then Biden’s Deputy Secretary for Defense, and Elon Musk, about Starlink access during the Ukraine war

The Pentagon would need to reach a contractual arrangement with SpaceX so that, at the very least, Musk “couldn’t wake up one morning and just decide, like, he didn’t want to do this anymore.” Kahl added, “It was kind of a way for us to lock in services across Ukraine. It could at least prevent Musk from turning off the switch altogether.”

Typically, such a negotiation would be handled by the Pentagon’s acquisitions department. But Musk had become more than just a vender like Boeing, Lockheed, or other defense-industry behemoths. On the phone with Musk from Paris, Kahl was deferential. According to unclassified talking points for the call, he thanked Musk for his efforts in Ukraine, acknowledged the steep costs he’d incurred, and pleaded for even a few weeks to devise a contract. “If you cut this off, it doesn’t end the war,” Kahl recalled telling Musk.

What would that conversation have looked like if the Defense Production Act had recently been deployed by a different administration to force a major tech provider to supply what the government wanted it to supply? What would negotiations between a Palantir that has become deeply embedded in the US government’s core systems and a putative Democratic administration in 2029 look like if the administration could just dictate terms? Perhaps Musk, Karp and their underlings have not thought through the implications, but they could be far-reaching.

To be absolutely clear: I do not want to imply that it would be a good thing to see the Defense Production Act invoked against Anthropic. I am deliberately focusing on just one set of relationships and possible implications under different scenarios, because I think they’re being overlooked in the debate right now. Even if you are in favor of empowering President AOC a few years down the line, you might want to think about the more immediate consequences. Nor do you need to believe in the case for strong or weak AGI to worry about how the Department of Defense might use these technologies. As Jack Shanahan suggests, you ought be more worried rather than less if you think these technologies are imperfect.

I am trying to weave Marion’s, Alondra’s and Nik’s work together towards the much more modest purpose of explaining why the tensions we are now seeing are not just about the specifics of the relationship between Anthropic and the Department of Defense. They highlight more general contradictions in the Trump coalition between executive-authority enthusiasts and Silicon Valley oligarch-wannabes. It may be possible to patch over these contradictions, but it will take some effort and skill, and the more that the Trump administration deploys arbitrary instruments of quasi-expropriation against tech companies, the more quickly the contradictions will widen. One path leads to Silicon Valley oligarchs becoming kleptocrats, increasingly vulnerable to the whims of the Commander in Thief. The other leaves them far more exposed to a future administration that can more forcefully chop away the roots of their power over government. Each would be its own kind of cage.

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* Anthropic seems to possibly be OK by implication with using its tech to facilitate US mass surveillance of other democracies? That raises some questions.

** I know, I know.

There is a reason I don’t accept paying subscribers for this newsletter (although I am grateful to those who offer to pay). I want to be free to use terrible headlines like the one I’ve used for this post, without feeling even slightly conflicted about it.

I spent three years as the editor of a political science blog that was hosted at the Washington Post. We spent a lot of time thinking about how to write catchy and seductive headlines that would get people to read posts about social science.* The common wisdom about how best to do this shifted, as different social media platforms grew or fell (we were pretty well out of the game by the time that social media stopped driving traffic entirely). Preferred headlines got shorter as the metrics started suggesting that they worked better: the newspaper imposed a character cap for headlines that we all tried to adhere to.

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One thing remained constant. You did not want to have any academic jargon whatsoever in your headline if you wanted to attract eyeballs. And you absolutely did not want to have a headline that juxtaposed two unfamiliar pieces of academic jargon, so that they could duke it out over which was better suited to drive punters away.

We knew how many readers each post got, and struggled to make the numbers as good as we could get them, while trying somehow to hold onto the truth that we weren’t, in the end of the day, primarily interested in the numbers game. It was what we had to do to justify our existence as a small ideas shop hitchhiking a ride on a much bigger publishing enterprise. Hence, when I started writing a newsletter, I decided from the beginning that it was going to be my newsletter. It would talk about the things I wanted to talk about in the ways I wanted to talk about them, without any profit model tugging me to juke the numbers by writing about the topic of the day or sanding away the weirdnesses of my writing style. I’m somewhat startled that so many people read it. My writing for it is deliberately idiosyncratic, discursive, even meandering.

Hence too, my unashamed love of C. Thi Nguyen’s new book, The Score. It is a book that is about metrics (like viewer numbers, though I don’t recall him citing those in particular) and how they define not simply our lives but our very selves, if we carelessly let them. It is a book about pizza. Also: weird yo-yo tricks and the zen-like states that accompany them. Also also: climbing, on which there is lots. Also also also: drunken cooking competitions. And that is just for starters. It is a book that absolutely ought not work, for the same structural reasons that bumblebees ought not be able to fly. The aerodynamics are all wrong. But good god, does it fly. The achieve of, the mastery of the thing! I would not have believed that a book about metrics could be a joyful and delightful book. The Score not only manages that extraordinarily difficult trick, but makes it look easy.

The Score, then, is about very many things, but it is not about electoral politics. This post explains why I think that its lessons travel to politics, in much the same way that Brian Eno’s ideas about music have nothing to do with democracy, except that they absolutely do.

In particular - and finally we begin to get to the meat of the post - electoral political strategy is increasingly driven by metrics and related simplifications. This has many advantages. It forces people to put their pet theories of what will work and what will not to the test, and makes it easier for everyone to coordinate around the same approach and message. But it has substantial drawbacks too, along the lines that Nguyen suggests. If everything gets reorganized around the metric, then all the important things that the metric hides are likely to rear their heads and devour you. Metrics are lossy abstractions of complex wholes. As Maxim Raginsky puts it, “abstraction hides a great deal of complexity from view, and this is both its main virtue and its primary peril.”

So first, I want to talk about a fight that is happening right now within the Democratic Party that conceals a more fundamental conflict about metrics and abstractions. Then, I’ll explain how the median voter theorem fits into this fight, and how it has become what Nguyen calls a “clarity trap.” Then, finally, I will talk about ways to maybe escape that trap and find something better.

*****

The electoral strategy of the US Democratic party mainstream is all about the main virtues of simple metrics. The perils that this ignores are the root cause of much unhappiness right now. Some of that spilled out into a forum in the Boston Review last week. Two prominent political scientists, Adam Bonica and Jake Grumbach, argued that the Democratic Party’s focus on milquetoast moderation was leading it astray. There were lively responses from those on the other side, including Matt Yglesias, who has argued that the Democrats need to moderate, and that left wing excesses explain Kamala Harris’s defeat.

This is one episode in an ongoing dispute with many rejoinders and counter-rejoinders about methodological particulars, “wins-above-replacement” metrics and the like. And it is not just an arid statistical squabble. Matt has written occasional spicy social media posts about how he is finally coming to understand the basic dishonesty of academic political science, while those on the other side, broadly considered, make their own mordant comments about the idiocy of pundits, and the economic incentives of pollsters who work regularly with the party.

While this fight seems superficially to be a back-and-forth over which are the best statistical instruments and abstractions to capture public opinion, it is bitterly fought because it maps onto a more directly political dispute over whether the Democratic party should turn to the left or to the center.

What I would like to see people paying real attention to is a third disagreement, which lurks beneath both the statistics and the politics. Should the Democratic party be sticking to tried-and-tested techniques (based on the standard metrics and assumptions) for attracting voters, or should it be trying new stuff out? At the moment, this fight very loosely maps onto the other two, because moderates are (a) the faction that would most visibly lose if the party starts experimenting with new ideas, and (b) are intellectually tied to a broader metric-driven approach that is shared across much of the business world, technology, and, perhaps weirdly depending on how you think about them, sports.** After Bezos gutted the Washington Post last week, he issued a statement defending the cuts that had been made on the theory that “the data tells us what is valuable and where to focus." That theory of what we ought pay attention to guides a lot of competitive activity these days.

But as Nguyen points out in the book, data often conceals as much as it tells us. As he describes the problem elsewhere, .

The basic methodology of data—as collected by real-world institutions obeying real-world forces of economy and scale—systematically leaves out certain kinds of information. Big datasets are not neutral and they are not all-encompassing. There are profound limitations on what large datasets can capture. … Data collection techniques must be repeatable across vast scales. They require standardized categories. Repeatability and standardization make data-based methods powerful, but that power has a price. It limits the kinds of information we can collect. … an overemphasis on data may mislead even the most well-intentioned of policymakers, who don’t realize that the demand to be “objective”—in this very specific and institutional sense—leads them to systematically ignore a crucial chunk of the world.

If you are already convinced that you understand how the world works based on a combination of the data and a few simplifying intuitions, you are going to be disinclined to experiment to find things out that you don’t already know. If you are the kind of cook who sticks mechanically to a particular recipe, you may produce good meals, but you are going to miss out on other, perhaps great meals that you could discover by messing around. If you live in a static world and don’t mess around, you are going to remain stuck at a possibly inferior local optimum, when there are much better possibilities out there that could be discovered by doing things that deviate from the ordinary (as Nguyen’s stories about the strange discoveries of drunken cooking illustrate; you can think about throwing ingredients together when you are half loaded as a kind of simulated annealing if you really have to).

And if you are in a rapidly changing environment, then things might be much, much worse. Your insistence on looking at the world through fixed metrics may make you incapable of seeing the transformations that are happening around you, but that get filtered out by the metrics that you think are important.

That, plausibly, is what is happening now with a largish chunk of the moderate wing of the Democratic party. I, myself, am a lefty, but from a broader political perspective, the problem with Democratic moderates right now is not that they are moderate. It is that they are defining their moderation in ways that depend on metrics and simplifying notions that (a) are increasingly out of sync with the environment, and (b) tend to preclude experimentation.

I think that the Democratic party would be in a significantly better place if the moderates became experimentalists. That is, it would be great if moderates moved decisively away from the position that the metrics tell us what we need to know, and treated them as valuable but limited tools of inquiry for grappling with a world that is vastly more complex than any metrics can plausibly capture, and started trying to explore those complexities in different ways. That is not least true because there are likely things that moderates can discover, if they are so inclined, that lefties (and conservatives) cannot.

I don’t think that the debates between the left and moderates would necessarily be any friendlier if they were disagreeing over the best ways to experiment to attract voters and create compelling policies, but I do think that they would be more likely to result in interesting and unexpected discoveries than what we have now: interminable disagreements over whether the statistically maybe-sort-of-measurable-if-you-squint-in-a-charitable-way rewards of moderation are a .5%, 1% or 2% greater share of the vote.

One way to get moderates moving in this direction might be to get them to move away from the “median voter theorem,” a particularly beautiful mathematical abstraction that has become what Nguyen calls a “clarity trap” for moderates: hence my incomprehensible seeming headline. But what is the median voter theorem, and why is it so weirdly politically important?

*****

The median voter theorem is, as the box says, a theorem. That is, it is a proof that if you start from certain mathematical assumptions, then certain conclusions follow. It is, furthermore, a really neat theorem. Its mathematical virtues do not explain why it has become politically important, but it is helpful to have at least a summarized version and simplified version of what the theorem actually says.

The median voter theorem starts in economics rather than politics, and its most broadly influential version is the one in Antony Downs’ book An Economic Theory of Democracy. It is in broad form a particular application of Harold Hotelling’s ideas about market convergence.

The bowdlerized version of Hotelling’s account goes as follows. Imagine two shopkeepers that want to maximize sales, but both have to locate their store on the same street. They know that customers are likely to frequent the shop that is closest to them. That means that the shop that is located just a little bit closer to the middle part of the street will get slightly more customers than the one that is further away. Like many influential economic models, this one has an equilibrium, a final state that rational economic actors will converge on. The rival shop owner will have an incentive to relocate their own store a little closer to the center, to grab back some customers. This then plausibly leads the first shop to move too. Eventually, the two shops will end up side by side, bang in the middle of the street. That is the equilibrium where there is no possible better move that an actor can make.

For the Median Voter Theorem, imagine a version of this model, where instead of shops you have political parties, instead of customers you have voters, and instead of a street, you have a single ideological dimension on which the parties and voters locate themselves. Again, you assume that voters vote for the party whose position on this one-dimensional continuum is closest to them. And much the same thing happens. Over time, parties too are likely to converge towards the central point, so that each is in its best possible position to maximize vote share. The Median Voter Theorem then makes a simple prediction. Rational parties, if they want to win elections, will necessarily pursue the median voter right at the center (according to one measure) of the political spectrum. Whoever attracts the median voter will win a majority. Hence, parties that want to win ought become centrists.

If you treat this as a mathematical theorem, you might want to think carefully about the many mathematical assumptions that lie behind this rather lovely result. Voters’ preferences need to be well behaved in certain ways (“single peaked”). More pertinently, it has to be possible to collapse the entire space of political issues into a single dimension of political contention. If there are two dimensions of political contention, things get a lot messier (although there are still some regularities). If there are three or more dimensions, then anything goes (social choice theory has various `chaos theorems’ that say that outcomes will be unpredictable). Finally, voters’ political preferences need to be fixed in advance. Parties cannot persuade voters under this model. They can only adapt themselves towards what the voters want. This is a static universe - the only dynamics are the ones that conduct voters and parties to the single predictable equilibrium.

If you forget the assumptions and treat the median voter theorem instead as a guide to party strategy, it is incredibly attractive to moderates. The median voter theorem entails that there is one weird trick to winning elections: always move towards the center. If you are a rational politician, you always need to asking yourself (and the polls), what the voter right at the center is looking for. If you give the median voter what they want, you will win. You don’t have to worry about voters on the left (if you are a Democrat) or the right (if you are a Republican). They will vote for you, because you are the party that is closest to them, even if they think that you are a centrist sellout. You should absolutely ignore what various identity groups are telling you about what to do - their advice is at best misleading and at worst treacherous and dangerous.

If you take this idea to its logical conclusion, you don’t even need a political party. All you need are accurate measures of public opinion, built on survey data that captures voters’ fixed preferences, and politicians who are willing to respond to it in the ways that their rational desire to win office dictates.

Of course, nobody - or nearly nobody - actually takes these ideas to their logical conclusion. But some moderates come a lot closer than you might imagine. I’ve seen one well-known Democratic ‘strategist’ (a term that covers a multitude of sins) describe the median voter theorem in terms that seem better suited to a recent, urgent personal religious revelation about the true nature of the world. They are young, so I am not naming them. And it is not hard to see why they feel so strongly. When you are inclined towards centrism, and find a simple, clarifying theory that tells you why your understanding of politics is not only right but inevitably right, it is difficult to resist. Add a panoply of surveys, and some other useful simplifications as auxiliary hypotheses and you are set up in business for life.

Furthermore, as per Raginsky’s dictum, the median voter theorem is a useful abstraction under many circumstances. It allows politicians to focus on strategic issues that are plausibly quite important. Pushing towards the center is indeed, quite often, an electorally useful strategy. The theorem, in its pop-culture form, furthermore serves as a valuable disciplining mechanism, to help prevent politicians from wishcasting the public that they would like to have into existence, instead of dealing with the public that they actually have. Finally, it helps build party discipline, getting a variety of disparate actors to concentrate on the same thing, rather than heading off in a million different and mutually contradictory directions.

Equally, as Raginsky suggests, these virtues can become perils. They can conceal a lot of dangerous complexity that you really ought be paying close attention to. Or as Nguyen might describe it, using a different but related vocabulary, they can make it far harder for you to see the world around you in all its glorious weirdness.

That is what Nguyen is getting at when he talks about “clarity traps.” When an idea - whether it be a weird conspiracy theory, a seductive social science result, or a beautiful graph - seems to simplify an altogether-too-complex world, it may give you the sensation of sudden understanding, of having the scales fall away from your eyes so that you suddenly arrive at the single true understanding of the world. That sense of epiphany (a word descending from the Greek word ‘to show’) is not always altogether a bad thing. Beautiful ideas are often beautiful because they do carve the world at its joints, or at least closer to the joints than we have hitherto been able to achieve. But this loveliness can betray you if you mistake the apparent clarity for the undoubtedly messier truth. As Nguyen puts it;

So here is a recipe for a seductive clarity trap:

First, build a belief system that offers a satisfyingly clear, coherent explanation of the world.

Second, make sure the belief system conceals any evidence of its own error.

The median voter theorem, and a set of closely associated ideas have become a clarity trap for Democratic moderates. They offer a simple, clear explanation of what the Democratic party always ought do. Moderate! Move to the center! Figure out what the median voter wants, and do just that! And they also offer a means of concealing errors. Whenever Democrats fail to win elections, it is definitionally due to their failure to observe this universally sound advice. Very obviously, they have been listening closely to the groups and failing to pay attention to rigorously conducted opinion surveys, which are the true and proper barometer of what the public wants.

There are other diagnoses that seem to me more plausible. Public opinion is not, actually fixed in the ways that the median voter theorem suggests, even if they are not nearly as protean as people on the left might want them to be. The more that political parties rely on metrics and other simplifications, the more they are likely to be blindsided by voters whose wants and ideas are not readily captured by simple measures.

Most radically (and this has implications for left-leaning political scientists too), we are living through times of upheaval in the underlying structures of democratic politics. In such times, all our instruments for identifying causal relationships will become less helpful, because some of the causal relationships we are most interested in are likely to be undergoing rapid ferment. Even the most accurate photographs of unpredictably moving targets may not be that useful for very long.

The deep problem of clarity traps such as the popularized version of the median voter theorem is a side effect of their attractiveness. Exactly because they are so attractive - they tell you that you are right goddamit, and there is objective proof of it - they are extremely difficult to escape.

*****

One way to conclude this essay might be to claim that moderates are wrong and that people to their left have the right of it. And there is a particular and temporary way in which this is true. In their essay, Bonica and Grumbach not only wallop the Median Voter Theorem, but say the below:

The reality is that electoral politics has entered an era of profound volatility, one when yesterday’s certainties become today’s mistakes. We are not making a general case for running to the left instead of to the center but for dispensing with outdated conventional wisdom. Instead, we favor experimentation and exploration. Embracing these requires expanding our sense of possibility and the range of our explorations, partly by paying close attention to what has worked in other countries that have faced democratic backsliding.

That seems to me to be absolutely on the money. But the lesson I personally take from it is not that moderates should abandon their values and priors. Those priors are likely to very often be quite useful. Many members of the public are likely more comfortable with moderate views than lefty ones. Some parts of the country are likely much more moderate than others. Perhaps (and on some issues probably) there are much easier national majorities to find based on moderate appeals than immoderate ones.

Instead, I think that moderates should put far less trust in their preferred simplifications and metrics. The median voter theorem is politically attractive to them because it reflects their political priors so perfectly, making it very hard to give up. Again: this also explains why it is liable to be a particularly vicious clarity trap. Who would not prefer to have the world clarified in ways that suggest that everyone who does not converge on their own preferred political philosophy is stupid, wicked or dishonest? It is in the nature of clarity traps that they continue to seem compelling even as they draw you ever closer to the brink of the abyss. It is really hard to escape this kind of trap, especially if you have built your identity around it. But it can be done, and doing it opens up new possibilities.

I think that there is a lot of room for moderates to start engaging in experimentation with different political approaches that are less reliant on opinion polls and median voter assumptions. Here, I particularly like a recent Daniel Schlozman essay that argues (as I read it - maybe wrongly) that it is the left that ought to start paying more attention to the kinds of institutionalization and partisan hardball that normie Democrats built up before, and ought start trying to build again under different conditions. A program to build up a normie Democratic party that was actually a real political party, connecting politicians to voters, would be a great start.

A second approach might be to look to the lessons of the evangelical movement. Ezra Klein got a lot of grief from people on the left for saying that there was something right about what Charlie Kirk was doing. My interpretation (again maybe wrong) of Ezra’s core intuition is that the Democrats too need to start evangelizing as Kirk did, by getting out and talking to people who they don’t agree with and don’t usually talk to. Again, there are a lot of ways in which some moderates are better positioned to experiment with doing that than people to the left (although left economics also maybe provides some useful starting points).

A third is that moderates should be stealing in quite different ways from the left than the ways that they are doing now. This gets back, in a weird, backhanded and not necessarily very intellectually coherent way, to something that my brief account of Nguyen’s book mostly misses out on. The Score a genuinely joyful book, about the delights and surprises of everyday life. It is striking that few people would deploy “joyful” as an adjective to describe the Democratic party’s way of thinking and communication. That of course reflects the real grief, anguish, anger and frustration of the world around us. But it also reflects bad habits of carping, begrudgery and misdirected spleen that plague all of us.

It would be great to try to break these habits, and I think that it is still, occasionally possible to find weird and surprising joy amidst it all. The most valuable transferrable lesson of Zohran Mamdani’s victory and early governing style may not be the talking points about “affordability.” Instead, it’s the capacity to discover delight in being outstaged by kids at press conferences, to admit fallibility, to experiment while admitting that things don’t always work, to build connections and to try to draw new constituencies in. I don’t see any fundamental reason why moderates shouldn’t be able to work with some version of that style of discovery and communication just as well as lefties, and I suspect that it would get them much further, and to more interesting and unexpected places, than doubling down on technocratic measures.

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* Or at least, start reading them. If you ever want to get depressed about the reading public, ask a newspaper executive how many people actually finish reading an article after clicking it.

** There is a great essay to be written about how Nguyen’s ideas about games intersect with “Moneyball.” This is not that essay.

[David Byrne playing “Life During Wartime” live, Washington DC, September 28, 2025. Author’s photo]

I did the Ezra Klein show last Friday, and it went up on the NYT website this morning. A whole lot has happened in the meantime. The way I think is through talking with other people, and a lot of thinking happened in the conversation. It wove together what happened in the world last week with what is happening in Minneapolis, in ways that I am still trying to work out. So here is a short interim report, written less as a polished essay than an attempt to pull these thoughts together.

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What became clearer to me, as Ezra and I talked, is the connection between the limits to US power in the world, and the limits to the Trump administration’s power inside the borders of America. We briefly mentioned a long-ago fight that I had with the late David Graeber, who advanced a theory of world politics in his book, Debt, that described the global economy as a tribute system, and emphasized the awesome power of the United States to terrify the rest of the world into submission. Back then, I disagreed with Graeber’s claims and Graeber took strong exception to my disagreement, provoking a very long response from me. The upshot of my argument was that the United States is incapable of pulling what I called the “Delian League Switcheroo.” Thucydides describes how 5th century BCE Athens transformed its alliance against the Persians, the Delian League, into a protection racket to squeeze allies and turn them into vassals. I argued back then that the US would find it very hard to do this at scale:

The US ability to intervene abroad is limited both by financial costs, and by difficulties in maintaining domestic political support. This suggests that the US power to intervene militarily abroad is far more qualified than Graeber thinks it is. The current world order can very reasonably be described as an empire. But it is not an empire of crude coercion where the US can call all the shots, based on its military capacity, or where other countries can expect military intervention if they e.g. stop denominating important stuff in dollars, or fail to pay their debts.

In fairness to Graeber, the Trump administration’s consistent policy over the last year appears to be to make his nightmare vision come true. The administration clearly does want to turn allies into vassals. But as we saw last week, it doesn’t have the power to do this. When it wants to intervene in one part of the world, it has to forego opportunities to intervene in others.

Ezra and I also discussed Thucydides’ Melian Dialogue - ‘the strong do what they will, while the weak suffer what they must’ - which Mark Carney quoted at the beginning of his speech. Trump-sycophants, catchfarts and sneaking regarders like Niall Ferguson like to cite this speech as evidence of the eternal verities of international power politics. But as Seva Gunitsky says here, Thucydides used it instead to illustrate Athenian folly. Athens’ hubris was clobbered by nemesis, when its expedition to Sicily failed, resulting in the destruction of hundreds of ships and the slaughter or enslavement of thousands of hoplites.

Domestic politics too was corrupted across the entire Greek city state system, as everyone took sides in a struggle between soi-disant democrats and soi-disant fans of oligarchy that fused warfare between city states with domestic factionalism :

Words had to change their ordinary meaning and to take that which was now given them. Reckless audacity came to be considered the courage of a loyal supporter; prudent hesitation, specious cowardice; moderation was held to be a cloak for unmanliness; ability to see all sides of a question incapacity to act on any. Frantic violence became the attribute of manliness; cautious plotting a justifiable means of self-defense. The advocate of extreme measures was always trustworthy; his opponent a man to be suspected. … even blood became a weaker tie than party, from the superior readiness of those united by the latter to dare everything without reserve; for such associations sought not the blessings derivable from established institutions but were formed by ambition to overthrow them; and the confidence of their members in each other rested less on any religious sanction than upon complicity in crime.

From Athens to America: does any of that sound at all familiar? Mothers and nurses become “domestic terrorists” when they are gunned down in the street. Hesitation to crush the “organized illegal insurgency” is a sign of weakness. Hatred of moderation, exaggerated manliness, extreme measures, destruction of institutions. I could keep going on, and on, and on, but I suspect that most readers know it already. The parallels are clear enough.

The Trump administration’s domestic hubris seems to be running aground, after the killing of Alex Pretti (which happened after the show was recorded). I don’t believe that the Trump administration is going to back down any more than it absolutely has to. Still, the limits to its power to escalate are becoming clearer. When confronted with large scale peaceful resistance, the administration finds that it is not nearly strong enough to overwhelm. The weak do not need to suffer so long as there are enough of them and they can get organized.

To summarize the joint claim of this week’s and last week’s posts, the Trump administration faces the same problems with its opponents at home as its soi-disant allies abroad. Its advantage is that it is much more powerful than any of them individually. Its disadvantage is that it is much too weak to crush them all at once. The administration’s powers of intervention are limited. When it tries to bully Europe into giving up Greenland, it discovers that it has to back down when it faces united opposition. ICE and CBP are perfectly capable of disrupting the life of a mid-sized American city. They are not capable of controlling it if the population pushes back.

That does not mean that the victory of the allies, or of protesters in Minnesota and around the country is assured. Collective action - whether among countries or people - is always hard, given differences of interest and belief. There is a lot that the administration can do, and will try to do, to pick off defectors. And both at home and abroad, there is a vacuum of leadership. If counteraction does not become institutionalized, it eventually becomes exhausted. Even so, there are possibilities to work with.

Finally, as Ezra emphasized in the conversation, visible moral degradation is a turn off for many people. I responded by drawing on the political science:

Susanne Lohmann, a political scientist, wrote this classic article on this. She argues that the Leipzig protesters seemed like normal people — good, decent people you would like to have as neighbors. The East German propaganda is that these are evil, weird freaks, that these are dissidents, they’re scruffy, they’re whatever. And it’s the fact that these look like normal, ordinary people that actually make this powerful.

So I think what we’re seeing in Minnesota is we’re seeing ordinary people. It’s very clear that the people who are organizing, the people who are pushing back are neighbors. They are people who seem like very straightforward, very ordinary Midwestern people, people who are part of the community. I think that the killing of Renee Good … She is not a domestic terrorist under any reasonable definition … this becomes more and more of a weakness.

Bringing the political science is in part a personal protection mechanism: I find it very hard to be impassive or coolly analytical about what is happening, and talking about the scholarship rather than the beatings and killings helps me get through. But there is an analytic point nonetheless, which has been made even more clearly by the events of the last few days. Cruelty can sometimes turn out to be a weakness rather than a strength.

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Corrected to fix a naming error and two errors about Greek history. Thanks to Brad DeLong and Neville Morley for spotting and pointing out.

This post tries to combine a conversation I had yesterday (more on that soon) with a piece from Adam Tooze this morning (behind paywall) and two other pieces from Adam and Paul Krugman over the last couple of days. We’re all trying to figure out what exactly happened at Davos, and I think that there is a very useful book that might help explain it. The book is Michael Chwe’s Rational Ritual: Culture, Coordination and Common Knowledge. It’s a game theoretic account of why ritual is important.*

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First, Adam and Paul. In his newest piece, Adam talks about the two alternative theories he had of what would happen at Davos this year. One guessed that it would be irrelevant; the other saw it as the place where capital might come together to coordinate against Trumpism.

These two particular theories map onto broader accounts about how Davos (a yearly meeting of very rich and very powerful people, with various hangers on and the odd academic or expert here or there for ornamentation) works. The ‘it doesn’t matter’ argument is closely compatible with the many journalistic and critical accounts of Davos that see it as an empty ceremony, in which people come together to boom out the shared collective wisdom at volume. The ‘capital might coordinate against Trump’ argument maps onto a different, but not entirely incompatible account of Davos as a place where the people with the money exercise their clout over politicians.

But as Adam says, neither is a good explanation of what happened this week.

The weight of Larry Fink and BlackRock added to the attraction of the WEF itself. It secured a truly remarkable turnout of capital of all kinds - asset managers, banks, hedge funds, PE, tech, industry from all over the world. … What was no less striking, however, was the collective public silence of this array in the face of the performance of the MAGA delegation. … The most plausible interpretation is not that this silence implies tacit approval, but rather fear of retaliation and victimization by the administration.

In his earlier post, Adam uses visceral language to describe what that feels like.

I remember the evening before, the stony-faced CEO warning me: “Be clear. Don’t be surprised. When he comes through the door … They will beat up on you. You will squeal. Then they will beat up on you again. You will hurt some more. They don’t mean to kill you. In the end you will settle on a spectrum of terms that they dictate. This is how it works. Time you understood it.”

Yet as he says, something unexpected happened. Adam explains this in terms of convening, staging and acting. You bring a lot of rich and powerful people together, you use media to build a stage that the outside world can see and is likely to pay attention to, and you call on politicians to be actors on that stage. That all creates an opportunity for politicians to go off script, as they did.

As Paul said separately:

Donald Trump and his team clearly went to Davos determined to demean and insult their hosts. It was, one might say, a novel approach to diplomacy: “You’re pathetic, your societies and economies are falling apart, now give us Greenland.” And it worked about as well as you’d expect. Trump may have imagined that the Europeans would cower in the face of his wrath. Instead, they humiliated him. He dropped his latest tariff threats in return for a “framework” that gave the United States essentially nothing it didn’t already have — and left behind a Europe that is finally united in resistance to his bullying.

You could see this shift happening in real time in the public statements of Trump administration officials. So what exactly happened, and how important is it?

This is where I find Chwe’s arguments to be extremely useful. I take two lessons from his book. First, that Davos fits very clearly into his definition of `ritual.’ Second, that rituals are important because they create common knowledge.

What we have seen at Davos over the last few days was an effort by the Trump administration to create new common knowledge in the world, an agreement that Trump was in charge, and that politics revolved around him. That effort has failed because of pushback from politicians, both Europeans who were furious at Trump, and Canada’s prime minister, Mark Carney who gave a quite extraordinary speech. However, the result is most certainly not a decisive victory for Europe, Canada, and the other forces allied with them. Instead, it is one significant moment in a longer story of struggle and contention.

Chwe argues that rituals are about creating coordinated expectations, and that this is why they are often an exercise in power. He quotes Clifford Geertz on ‘royal progresses’ - journeys undertaken by monarchs and their entourages through their countries and hinterlands, which are in large part about creating a shared understanding of who is in charge.

Royal progresses . . . locate the society’s center and affirm its connection with transcendent things by stamping a territory with ritual signs of dominance. . . . When kings journey around the countryside . . . they mark it, like some wolf or tiger spreading his scent through his territory, as almost physically part of them.

But Chwe qualifies Geertz’s evocative metaphor. He suggests that the exercise of power is less about the the royal progress awing the peasants, than the peasants realizing that other peasants are seeing the same thing, and being publicly awed by it. It is not the tiger’s musk, so much as the knowledge that everyone is smelling the musk at the same time that is important.

Our interpretation focuses exactly on publicity, the common knowledge that ceremonies create, with each onlooker seeing that everyone else is looking too. Progresses are mainly a technical means of increasing the total audience, because only so many people can stand in one place; common knowledge is extended because each onlooker knows that others in the path of the progress have seen or will see the same thing. That the monarch moves is hence not crucial; mass pilgrimages or receiving lines, in which the audience moves instead, form common knowledge also. Under our interpretation, widespread ritual signs of dominance do not by their omnipresence evoke transcendence but are rather more like saturation advertising: when I see the extent of a vast advertising campaign, I know that other people must see the advertisements too. This is quite different from the wolf analogy, if taken seriously: a lone animal knows to stay away from another’s area by smelling the scent at a given place; no one perceives or infers the entire scent trail (for that matter, scents keep away rivals, whereas progresses are for “domestic” consumption).

Rituals often take place in consecrated places. British kings are crowned in Westminster Abbey. They also often take place at a particular time of the year (see churches and organized religion, passim). So it is not at all a stretch to see the Davos meeting as a ritual that is held in the same overcrowded place at much the same time every year. Like many rituals, its boredom and its ceremony go hand in hand. For many years, Davos’s most obvious social purpose was to reinforce the consensus about globalization, in predictable ceremonial language. Its very dullness and lack of surprise was a side effect of its power.

That was then; this is now. I don’t think that it is at all implausible to see Trump’s planned descent on Davos this year as a version of a royal progress (see Stacie Goddard and Abe Newman on “neo-royalism”). Swooping into Davos, and making the world’s business and political elite bend their knees, would have created collective knowledge that there was a new political order, with Trump reigning above it all.

Business elites would be broken and cowed into submission, through the methods that Adam describes. The Europeans would be forced to recognize their place, having contempt heaped on them, while being obliged to show their gratitude for whatever scraps the monarch deigned to throw onto the floor beneath the table. The “Board of Peace” - an alarmingly vaguely defined organization whose main purpose seems to be to exact fealty and tribute to Trump - would emerge as a replacement for the multilateral arrangements that Trump wants to sweep away. And all this would be broadcast to the world. Adam’s combination of stage, convening and acting would provide a means to shape the collective understanding of a global audience that Trump was now in charge.

That, of course, is not what happened. First, the Europeans were finally pushed to the point where they pushed back. As Belgium’s prime minister put it, “Living as a happy vassal is one thing, existing as a miserable slave is another.”** It was clear that the Europeans were finally becoming willing to retaliate against Trump. That in turn had consequences for business.

As Adam suggests, businesses are unwilling to visibly step up to oppose Trump one on one. But businesses are not only individual participants in the ceremony. They are also members of a vast and depersonalized audience, via the anonymizing mechanism of the market, and, as Chwe suggests, it is the collective understanding of the audience that is most important. Just as the ouija board allows individuals to express their desires without being held accountable to them (thanks to the ‘ideomotor effect’) so too, the invisible hand of the market moves the planchette of stock prices in ways that no particular business can be held accountable for. When stock markets fall, even at the prospect of trade conflict between Europe and the United States, politicians pay attention. “Market fundamentals” (a loaded and problematic term) provided a very different understanding of the shared consensus than the one Trump sought to impose.

Second, Carney’s speech laid out an entirely different understanding of what was happening, and what had gone before. In his words:

Let me be direct: We are in the midst of a rupture, not a transition. Over the past two decades, a series of crises in finance, health, energy and geopolitics have laid bare the risks of extreme global integration. But more recently, great powers have begun using economic integration as weapons. Tariffs as leverage. Financial infrastructure as coercion. Supply chains as vulnerabilities to be exploited.

A family member joked with me that “it sounded like he was reading straight from Underground Empire,” Abe’s and my book (please go buy ! ) on how the integrated global world economy was weaponized. And that’s true, sort-of! Also, it is a rhetorically beautiful and well executed speech, in a way that politicians’ speeches rarely are (ask James Fallows, who knows political speech crafting from the inside). Its bluntness is the product of hard work and artifice.

But from Chwe’s more immediate perspective, what is more important than the vision of the past and future is where Carney said it and how he framed it. If you are planning a grand coronation ceremony, which is supposed to create collective knowledge that you are in charge, what happens when someone stands up to express their dissent in forceful terms?

The answer is that collective knowledge turns into disagreement. By giving the speech at Davos, Carney disrupted the performance of ritual, turning the Trumpian exercise in building common knowledge into a moment of conflict over whose narrative ought prevail. Chwe again, this time clarifying where he agrees and disagrees with James Scott.

A public declaration creates “political electricity” … But Scott’s main explanation is the same as ours, that public declarations create common knowledge: “It is only when this hidden transcript is openly declared that subordinates can fully recognize the full extent to which their claims, their dreams, their anger is shared by other subordinates.” When Ricardo Lagos accused General Pinochet of torture and assassination on live national television, he said “more or less what thousands of Chilean citizens had been thinking and saying in safer circumstances for fifteen years”; the openness and publicity, not the content, of his speech, made it a “political shock wave.” “In a curious way something that everyone knows at some level has only a shadowy existence until that moment when it steps boldly onto the stage”

This is why Carney’s speech was so remarkably efficacious. He wasn’t telling people anything that they didn’t know as individuals. He was, instead, turning that private knowledge into a putative collective understanding that countered the alternative collective understanding that Trump wanted to impose upon the world.

This is very much the way that dissidents think about politics, as Scott’s description of Lagos’s action suggests. And Carney very explicitly quotes Václav Havel to highlight the urgency and importance of disrupting the ritual.

In 1978, the Czech dissident Václav Havel, later president, wrote an essay called The Power of the Powerless. And in it, he asked a simple question: How did the communist system sustain itself?

And his answer began with a greengrocer. Every morning, this shopkeeper places a sign in his window: “Workers of the world, unite!” He doesn’t believe it. No one does. But he places the sign anyway to avoid trouble, to signal compliance, to get along. And because every shopkeeper on every street does the same, the system persists.

Not through violence alone, but through the participation of ordinary people in rituals they privately know to be false.

Havel called this “living within a lie.” The system’s power comes not from its truth but from everyone’s willingness to perform as if it were true. And its fragility comes from the same source: when even one person stops performing — when the greengrocer removes his sign — the illusion begins to crack.

So this, I think, provides a good integrated explanation of what happened at Davos; at least, it is the best that I can come up with. We should think about Davos as a site and moment of ceremony, in the terms that Chwe lays out, which cements common knowledge about who is in charge, and what the principles of rule are. That, in turn provided Trump with a possible opportunity to anoint himself as the central figure in a new vision of the West, in which, in Stacie and Abe’s terms,

a small clique [maintains] dominance in both material and symbolic goods. It thus rejects notions of sovereign equality and noninterference, and rests instead on the idea that a royalist clique is dominant, and will only recognize rival “great cliques” as peers; all others are unequal, and not due recognition.

The ceremony was disrupted by European threats of retaliation, which in turn led the market audience to express its unhappiness, and by Carney’s quite deliberate and self-conscious effort to crack the illusion of inevitability.

That does not mean that the Trump political project has been defeated. It is going to be very hard for Europe and Carney to build a viable counter-consensus. Already, Trump is looking to discipline Canada and seize back control of the narrative. What we have seen was a battle, not a war. But to appreciate the weapons that the battle was fought with, and understand the prize that was contended for, it is really helpful to emphasize the relationship between ritual and collective expectations. Chwe’s book is the clearest account of this relationship that I know of.

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* Non-rational choice sociologists may reasonably complain that they’ve been discussing this question for well over a century,. This is completely fair, but it is quite difficult for those who have not been initiated into the mysteries to read this work and understand why it is so important.

** “Happy vassal” has become a term of art in this debate.

My quick read on the incredible events of the last 24 hours is as follows. We don’t know what went into the apparent (and still ambiguous) pullback on the threat of invading Greenland. One plausible story is that the Trump administration did not realize that the Europeans were willing to come together and push back, and had to revise their expectations rapidly over the last couple of days.

I present: Bessent and Lutnick: a Farce in Four Acts.

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Act One: Europe Can’t Do Nothing to Stop Us!.

“Scott Bessent suggested the 27-strong group of nations’ slow decision-making would hamper its ability to put together a potent reaction or quickly wield the so-called anti-coercion instrument, its strongest trade measure. “I imagine they will form the dreaded European working group first, which seems to be their most forceful weapon,” Bessent told a small group of reporters in Davos, Switzerland, where he is attending the World Economic Forum.”

Act Two: Actually, Europe, We Don’t Want You to Escalate!

“What I’m urging everyone here to do is sit back, take a deep breath, and let things play out. As I said on April 2, the worst thing countries can do is escalate against the United States.” But he specified that “what President Trump is threatening on Greenland is very different than the other trade deals.” “So I would urge all countries to stick with their trade deals we have agreed on them,” Bessent added.

and

“Everyone, take a deep breath. Do not escalate, do not escalate. And President Trump has a strategy here.”

Act Three: Europe is Escalating But It Will All Work Out for America

Howard Lutnick, the US Commerce Secretary, projected calm, saying during a panel discussion that, “If we’re going to have a kerfuffle, so be it. But we know where it’s going to end. It’s going to end in a reasonable manner.”

Act Four: Exit, Stage Right, Pursued by Bears.

US commerce secretary Howard Lutnick was heckled at a World Economic Forum dinner in Davos, with European Central Bank president Christine Lagarde walking out during his speech. The gathering on Tuesday night descended into uproar after combative remarks from Lutnick, according to several people present, with widespread jeering amid appeals for calm from BlackRock’s Larry Fink, the host of the event and interim co-chair of the WEF. Lagarde was among the attendees who walked out during the speech, according to people familiar with the matter. This year’s gathering in the Alps has the theme: “A spirit of dialogue.”

But I also have a more structural read on Europe’s underlying strengths - and weaknesses - when escalation dynamics hit in the New York Times this morning. It focuses on the other side of Trump’s threats - economic coercion.

The fundamental message is that Europe needs to start thinking about political economy in a different way, drawing not on theories of market integration, but crisis bargaining from the nuclear era, if it wants to be able to push back against Trump (and China). I argue that:

The only way to maintain European independence is to escalate back. To do this well, Europe needs to incorporate ideas into its economic thinking that seem alien to a continent that prefers soft power to hard security strategies — deterrence, credible threats and escalation dominance.

Repeated submission has gotten Europe into a mess. To get out, Europe needs to commit to not back down.

Credible commitments and tripwires are the strategic concepts of Thomas Schelling, the Nobel-winning economist and national security thinker who died in 2016. Mr. Schelling’s ideas shaped America’s nuclear strategy in the Cold War. He saw proxy wars and threats of missile strikes as the brutal language in which the Soviet Union and the United States bargained with each other, each seeking political advantage while avoiding mutual nuclear annihilation.

The argument emphasizes how the anti-coercion instrument (see also Paul Krugman this morning) could be used to build leverage. It’s also worth reading a number of other people, starting from similar premises* to reach a variety of different conclusions.

There are two points that I wasn’t quite able to shoehorn into a NYT article that has word limits and is aimed at people who have almost certainly never heard of the anti-coercion instrument and may reasonably still not be sure why they ought care.

First, I suggest that the instrument can be thought of as a highly imperfect commitment mechanism but don’t explain why in any detail. The reasons have to do with the complications of EU decision making. How the instrument works is as follows (greatly simplified).

(1) The European Commission proposes an investigation into some other country that is apparently coercing the US. It can do this on the basis of a suggestion from the EU’s member states, or on its own initiative, but the politics suggest that it is unlikely to succeed unless it has substantial member state backing.

(2) It proposes a set of measures, which the member states can then vote up or down. To succeed, the measures need to get a ‘qualified majority’ (a weighted majority by number and population) of member states to agree to go forward. Member states can also come together to modify the proposals if they really don’t like them.

(3) The Commission then implements the measures until the coercing state gives in, or agrees to binding arbitration, or other less likely/relevant things happen.

The point is, then, that the process has some binding power over the member states once it begins. Individual member states cannot stop the measures from going through - they have to create a sufficiently large blocking minority (a minimum of four member states with sufficient population). That also means that an aggressive coercive power (say: the United States or China) can’t stymie action by getting a single member state (say: Hungary, which is close to Trump and also has a massive amount of Chinese inward investment) to refuse consent. Other instruments, such as economic sanctions, do require unanimous consent to go forward and are accordingly more difficult to deploy.

That is why I suggest that the anti-coercion mechanism is plausibly the best option to increase EU credibility if it wants to promise broad-scale retaliation against threats like Trump’s tariffs. Equally, it would be much more credible if it had greater binding force.

One of the most fundamental and useful points that Schelling makes is that there is often a stark trade-off between flexibility and control on the one hand, and ability to make credible commitments on the other. Making a credible commitment or credible threat (from a game theoretic perspective, they are much the same thing) involves binding yourself to do something in the future that might be painful or unpleasant, because it allows you to change other actors’ expectations about you today. I sign a contract to deliver a good, which stipulates that horrible things will happen if I fail to deliver, because this enables my customer to trust me enough to pay in advance. I station troops in West Berlin (Schelling’s example, which I use in the NYT piece) because they will die if the Soviets pour in, and this will oblige me to escalate and retaliate, perhaps to the point of precipitating war. The Soviets consider my credible threat, and decline to invade.

The implication, then, is that the European Union might be much more credible with the Bessents of the world if they could more readily bind themselves to take painful or difficult steps to counter aggression. However, the European Union’s member states often look at the problem differently. They are worried about delegating security power to the European Commission, for fear it will do something that hurts their economic interests or other national interests. The Schelling argument is that this increases their flexibility, but weakens their ability to demonstrate resolve against outside threats.

Other possible systems would lower flexibility but increase the Commission’s bargaining strength. If, for example, the member states had to reach a qualified majority to block the Commission from acting, it would greatly increase the risk that the Commission could ignore, say, the specific desires of Germany and its friends. But it would also correspondingly increase the credibility of the EU’s threat to retaliate against other countries that hurt it.

That suggests that the European Union might want to reconsider its priorities. The anti-coercion instrument is much less credible than it might be, because the member states worry that it will be used in ways that hurt their interests. If they want to increase their credibility ex ante in discouraging attacks, they are going to have to weaken their degree of ex post control, so that they are less tempted to back down when the going gets rough. That, in turn, lowers the chance that the going will get rough, because potential aggressors will see that the Europeans have bound themselves, and desist from attacking. This is one of Schelling’s most important arguments, and while it may seem counter-intuitive at first, it makes a lot of sense when you think about it.

This framework may be extremely dangerous if applied in stupid ways- one of the reasons that the US made such a disaster out of the Vietnam war is that it feared damaging its credibility if it withdrew. Still, the EU is some very considerable distance from even notionally being able to make such grievous mistakes.

The second point is that if we think about this in terms of escalation dominance, Europe has more options than it might initially seem to have. And this morning’s more conciliatory speech suggests that that Trump knows it.

Here, Paul Krugman has arguments from the economic side; I have ones from the strategic perspective. The first, which is mentioned in the NYT piece, is that the Greenland gambit is wildly unpopular among US citizens, and perhaps not enormously popular among Republican politicians either.

The most difficult point, which will likely arise again in other disputes, is that the ultimate doomsday weapon stems from America’s national security role as guarantor. The immediate risk is not that the US invades Europe, but that it withdraws support from Ukraine. That would be a disaster for Europe if it happened. Equally, it would be a disaster for the US on two mutually reinforcing fronts. It would precipitate a major crisis in transatlantic relations, causing likely economic crisis, as the stock market wobbles suggest. And it would mean that the US would suddenly lose its major hold over Europe, making Europe much more likely to start pulling out of the US technology stack, arming up even more quickly, and start using the actual economic leverage it has to hurt the US back.

This has implications for escalation dominance, which you ought think of in game theoretic terms. You look to the end-stage of the game, and see who wins and loses, then you reason backwards to see how this affects the ways in which actors ought behave (if they figure that they are going to ultimately lose if they play a belligerent strategy of always escalating, they will just not play that strategy at all).

If you are Europe, and you think of the end-stage as ‘the day that the US pulls out of Ukraine,’ then you may have strong incentives not to challenge the US, since it is going to be less hurt in the end than you are. If you are Europe, and you instead think of the end-stage as ‘the day after the day that the US pulls out of Ukraine, when Europe erupts and the US economy goes to hell,’ you may very plausibly revise your calculations, and be more willing to escalate.

It is clear from Trump’s speech that he backed down in part because of how markets were reacting to the Greenland dispute (even if he confused “Iceland” for “Greenland” when he was talking). Europeans should take note of this, and update their understanding of escalation dominance accordingly. Equally, if they want to be able to act strategically in a world that is much less friendly to them, they may need to sacrifice flexibility and member state control so as to enhance their credibility against outside threats. Other news today suggests the EU isn’t nearly there yet. It needs to get there, and soon.

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* It is a bit startling to see everyday commentary homing in on “escalation dominance” as a key concept.

Here are three things that are connected.

First, my sometime co-author James Evans dropped a banger a few days ago. James, Alison Gopnik, Cosma Shalizi and I were chatting via email about a lovely piece that Walter Frick wrote for Bloomberg a few days ago, which starts from our shared ideas about AI as a social and cultural technology. James mentioned in passing, as you do, that he and other co-authors had a forthcoming research article in Nature about how AI was changing science. The takeaway argument is that using AI (which they define as involving a variety of machine learning techniques) is great for scientists’ careers, but not so great for the broader scientific enterprise. That piece is now out.

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Second, by coincidence, there’s been a lot of conversation among political scientists about “academic slop” this week. Andy Hall, a political scientist at Stanford Business School, suggested that Claude Code would enable a single academic to write “thousands of empirical papers (especially survey experiments or LLM experiments) per year.” The very next day, he put his money where his mouth was, publishing an entire Claude Code replication of an earlier paper that he’d written, plus the prompts and other stuff, to Github. The result is a lot of nervous chatter about what the industrialization of social science might mean for academic publication and careers.

The third may seem at first to be the one of these things that is not like the others. It’s a piece I wrote myself a few weeks ago, which is mostly a repackaging of Cosma’s and Alison’s ideas, riffing on how sung Yugoslavian folk-tales from the 1930s do and don’t resemble the outputs of Large Language Models.* The upshot is that if you want to think of LLMs as a generative cultural technology, they are far from being the first such technologies that humans have come up with.

What I want to argue is that the third phenomenon is plausibly the glue that connects the second with the first. James and his co-authors suggest that older versions of AI are connected to collective pathologies in science. The Andy Hall Experiment is a specific micro-level instance of the way in which newer and different forms of generative AI present similar, and possibly much worse problems. But it is the Yugoslav folktales that join micro-level opportunities with macro-level pathologies. LLMs threaten to genre-fy the practice of science.

[Update: Kevin Munger has further arguments on the social sciences that start from a similar perspective to my own]

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James and his co-authors are interested in the natural sciences: physics, chemistry, medicine and the like, and how they work at scale. There is already a lot of worry among natural scientists about what is happening to their fields. In the news section of Nature I counted no less than three news pieces on the topic: “AI is saving time and money in research — but at what cost?,” “More than half of researchers now use AI for peer review — often against guidance,” and “‘I rarely get outside’: scientists ditch fieldwork in the age of AI.” The new piece is research rather than news, but it too suggests that there are reasons to be worried.

The article uses an early and customizable large language model called BERT to categorize over 40 million papers, identifying the ones that appear to have used AI/machine learning techniques (which have a wide variety of legitimate applications to data).

First, AI use seems to be really good for the careers of individual scientists. Scientists who use it are able to write a lot more papers, with less help from other human researchers. Those papers are more likely to be cited by others. Their authors are on average promoted more quickly. All these relationships are associational rather than causal, but they are both visible and important at scale.

The problem is that what is good for scientists may not be good for science as a whole. Papers that use AI are more likely to succeed, but apparently less likely to stretch boundaries. Evans and his co-authors deploy another bespoke AI model to measure how AI-aided papers shape knowledge production. They find that AI-enabled research tends to shrink scientific inquiry to a smaller set of more topical questions. Furthermore, the linkages between papers suggest that there is less vibrant horizontal exchange associated with AI. The authors conclude that:

These findings suggest that AI in science has become more concentrated around popular research topics that become “lonely crowds” with reduced interaction among papers, linking to more overlapping research and a contraction in knowledge extent and diversity across science.

So is this likely to become more of a problem as scholars use AI not just to interrogate data, but actually to carry out research, review other scientists’ papers and so on? To understand this it’s useful to step back a bit, and think about what science is supposed to be doing in the world.

The entire enterprise of scientific research is intended to produce and evaluate useful discoveries. Usefulness, of course, is subjective, and disputed, but few apart from the late Ted Kaczynski would condemn the entire enterprise wholesale. Unfortunately, while the delights and benefits of disinterested discovery are genuine, they are insufficient to keep the scientific enterprise going at scale. To do that, you need some set of social institutions that imperfectly reconciles individual self-centered incentives (I, a scientist want not just to find out about the world, but to have a great job and career, and the admiration of my colleagues) with the production of general scientific knowledge.

The gap between individual goals and collective benefits explains much of the workings of science. Publication pressures, peer review, competitive funding are all highly imperfect means to incentivize individuals to participate in the scientific enterprise, and to increase the chances that good work rises to the top.

So what happens when we add LLMs to the equation? To be clear, as best as I understand James and his colleagues’ research, it is not aimed at detecting LLM use but figuring out when researchers explicitly use AI tools e.g. for data analysis.

What LLMs plausibly do is to exacerbate already existing contradictions between individual incentives and collectively beneficial outcomes of interesting and creative research. This is where the Andy Hall Experiment provides a useful example. It provides a best-case scenario for the use of LLMs to enhance science: obviously, it is about the social sciences rather than the natural sciences, but I am pretty sure that the basics of datasets, packages and prompts carry over pretty well to a wide variety of fields.

The experiment is noteworthy in that there are collective as well as individual benefits to this kind of work. As Seva Gunitsky says, replication of existing results is (a) important, (b) unprestigious, and (c) a massive pain in the arse. Having Claude Code doing it instead usefully fills in some gaps in the existing scientific enterprise. Equally, the creation of an automated system that can churn out thousands of scientific papers sounds ominous. So too, the use of LLMs for peer review and a myriad other potential uses. But why should it be ominous? These, after all, are the kinds of industrialization and automation that have served us well in a myriad of other economic sectors. Are academics the equivalents of 19th century craftsmen, deploring the factories that are capable of turning out product at scale for putting them out of jobs?

I think academics’ worries are justified, but LLMS are probably not so much creating fundamentally new problems as exacerbating old ones. In particular, I suspect that LLMs are hastening the genre-fication of scientific research.

To understand this, it is useful to highlight three words in the Hall comments, which possibly gave rise to an instinctive shudder in some, though certainly not all of the political scientists reading this essay: “especially,” “survey” and “experiments.” My comments on survey experiments below are not only political science insider-baseball, but highly tendentious insider-baseball. All I can say in their defense is that they come from a place of genuine pain.

Survey experiments are opinion surveys in which you randomly assign respondents to different treatments (e.g. different question wordings, or different initial scenarios that may prime respondents to think about some topic in particular ways) to see if there are meaningful differences in their responses. They have become semi-ubiquitous in political science. There are a lot of publications that use this approach, but my sense is that much fewer of them are good, in the sense that they contribute in a genuinely significant way to collective knowledge of politics. They do, however, plausibly contribute to their authors’ chances of tenure and promotion.

Indeed, they are reasonable responses to the institutional incentives of the field of political science. Academics who want to land and keep good jobs want to get their work published in respectable journals. Editors and reviewers for such journals are often more inclined to reject than encourage submissions, because they get so many of them. Scholars, especially younger scholars, are desperate to figure out sure-fire ways of navigating the obstacles of a review process that seems purpose-designed to frustrate them.

Articles that employ survey experiments have a better chance of getting through this process than many other approaches. Political science is often a heavily lagging indicator of trends in economics, and economists have become much more interested in causal identification in the last couple of decades - isolating causal relationships to figure out what is actually causing what. Political scientists have followed suit, making it much harder for articles without a good story about causation to get published. The problem is that establishing causation is difficult, expensive and murky in the real world. Survey experiments do not tell you very much about the real world unless they are carefully done (some are!), but they do make it very easy to tell a story about causation (they are, after all, built around a treatment which may cause one response or another). The result is that low quality survey experiment articles have become the political science version of kudzu - an infestation of most-mediocre-output-that-is-potentially-publishable that threatens to take over the entire ecosystem.

So what does this have to do with AI? The way in which I would adapt Hall’s comment (this may or may not bear any resemblance to his own ideas) is that survey experiment articles have become a genre, for much the same reason that pop music generates genres. There too, myriads of desperate young people are trying to succeed in producing outputs that will prove acceptable to a fickle and inscrutable public. There too, when someone miraculously succeeds, everyone else will rush in to copy them. There too, successful methods tend to turn into replicable packages: specific beats, lengths, themes and vocals in the one; forms of presentation, methodologies, kinds of data and means of arguing for significance in the other.

And if there is one thing we know about LLMs, it is that they are machines for detecting and reproducing genres. Here, then, is where the Yugoslav folk singers described in Albert Lord’s The Singer of Tales get their due. LLMs are very much like the generative cultural systems that created these folk tales with their minor variations, processing textual material so that it hits the right linguistic beats, harks to the right tropes at the right times and so on.

There is a lot of speculation that LLMs are returning us to something like oral culture. There is rather less that engages in any very intelligent way with the particulars of how oral culture works. Oral culture, like LLMs, involves lossy abstractions that also serve as generative systems. It too produces myriads of variations on common themes, adapting them to particular prompts and circumstances. It too is indifferently geared for verbatim transmission of the work on which it has been trained. When Varshney describes Lord’s formulas as “heuristic solutions to constrained optimization problems that must be solved in real-time,” he is using language that Lord might perhaps have found peculiar (though also perhaps not; Jakobson was on his dissertation committee), but that Wolfe would readily have recognized.

Many academic articles too are “variations on common themes” that are adopted to particular prompts and circumstances. Is it any wonder that sophisticated LLMs like Claude Code are capable of replicating them en masse?

As I said back then:

many aspects of human work and culture involve broadly similar combination of templates and stereotypes to those employed by the singers of tales. I suspect that this helps explain the facility of LLMs in carrying out many programming tasks, since programming too involves figuring out how to apply a common formula to a particular problem. The poiesis of the programmer is closer to the heroic poiesis of the bard than we think. … And perhaps also for much of the practice of social science? Dani Rodrik has written that a great deal of the art of the economist consists in accumulating a large mental library of mathematical models, and building an intuitive grasp of which model one ought to use when.

I didn’t at all expect that this throwaway suggestion would become relevant so quickly!

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This, then, suggests a possible theory of what is happening. This is nowhere near a complete theory - there are plausibly lots and lots of specific micro-mechanisms jostling with each other to connect cause to effect. But I like it, perhaps only because it is my own.

Science is two things - a process of open-ended discovery and verification of those discoveries and an institutional system for employing the energies of scientists towards that process and compensating them. The two ought point in the same direction, and do, to some substantial degree. There is an awful lot of waste in the system, but it is impossible to eliminate some (the open-endedness is part of the point; apparently useless discoveries may cumulate into great things), and extremely difficult to eliminate others (many proposed cures are more damaging than the disease). There are always tensions, and there are disciplines and sub-disciplines (metascience; chunks of social epistemology) devoted to studying and perhaps partly remedying these tensions.

One way in which those tensions manifest is genre-fication. Interesting discovery is hard, unpredictable and often requires a lot of resources. Scientists across the hard, soft and social sciences would often prefer, as all humans would, to have a more predictable world in which they can land jobs. This gives rise, in turn, to tendencies towards genre-fication. When someone discovers a path through the kill-zone of peer-review, others will want to copy it, in they hope that they too will succeed in winning kudos and career success. This results in the creation of scientific genres - packets of techniques, methodological approaches and rhetorical claims that scientists adopt in the hope that they will prosper. And that opens up the way for technologies that are good at picking up on genre cues and replicating them.

People will reasonably disagree about the merits of specific scientific genres. As should be clear, I am skeptical about the merits of survey experiments in political science, but many of my colleagues may very reasonably disagree. And genre has value! Some coordination is necessary for science to work. But the overall effects of genre-fication are to winnow out some of the variety among scientists that produces unexpected discovery. That LLMs may create their very own new genre of social science articles that treat LLMs as a proxy for public opinion, generating outputs that become inputs? This only adds icing to the cake.

LLMs then, as they are currently employed by scientists, are likely to reduce diversity. Claude Code is plausibly still at the stage where it is good at doing replications, but not so great at assembling the package in ways that produce somewhat novel-seeming research. I suspect, as Hall does, that it is not far away from it. This will, however, rapidly accelerate the genre-fication of science.

LLMs are excellent at assembling outputs that match the requirements of particular templates - producing genre outputs. They are also very good at match-and-mixing genres. In contrast, they are remarkably poor at generating usefully novel outputs or recognizing novelty in the data they are trained on. Accordingly, the more that LLMs are employed in the ways that they are currently being employed, the more concentrated science will be on studying already-popular questions in already-popular ways, and the less well suited it will be to discovering the novel and unexpected. James and his colleagues’ findings identify an existing problem that may likely become much worse with the newer forms of generative AI that are rapidly reshaping science.

To be clear, this is not an inevitable consequence of the technology. To steal another analogy from pop music, Autotune has likely, on average, made pop music more bland, but it has also been used in weird and interesting ways to expand the range of things that you can do. The Nature article employs a basic LLM to make the scientific enterprise visible at scale in ways that would have been inconceivable fifteen years ago. But it is going to be hard to get to a place where the technology is better suited to serve the interests of science, rather than those interests of scientists that point away from discovery.

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* I do take credit - or blame - for the excursion into the Proustian science fiction of Gene Wolfe.

As I said when last I wrote a roundup post, in January 2025, this is a self-consciously idiosyncratic newsletter. I’m enormously grateful to the surprisingly large group of readers who have committed to pay for it, but don’t intend to take them up on their offer. As a matter of policy, I politely decline to engage in the kinds of reciprocity with other newsletters that can help build friendly relations, and I try to pay no systematic attention to eyeball counts. The reasons for these behaviors are largely self-centered. I want to write about what genuinely interests me, and to have a relationship with readers and other writers based on free exchange rather than implied obligation.

Hence, this too is a self-centered post! Rather than highlighting the pieces that got high readership or lots of feedback, I want to present the posts that from 2025 that I personally found useful to write. They build on the ideas of other people, but point towards a broader set of concerns that I am still trying to articulate in a semi-coherent way. So rather than dwelling on the bits that I liked about them, I will talk about how they contribute to what this newsletter is trying to do, how they fit into existing conversations, and where those conversations might go next.

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In order of publication date:

#1 - We’re Getting the Social Media Crisis Wrong

This was my first substantial post of 2025. It makes a simple claim, but one that I’m still trying to work out properly.

We tend to think about the informational crisis of democracy in individual terms, and to focus on individual solutions: training people e.g. to identify disinformation and misinformation. But this crisis is better thought of collectively. Rather than focusing on the frailties of individual citizens, we should be looking at the problems of democratic publics. Our publics are malformed in part because they build on and perpetuate incorrect understandings of what other citizens believe.

The implication is that we need to pay more systematic attention to the relationship between what might be called technologies of representation and publics. Publics do not magically manifest themselves in transparent ways - they are mediated through social and actual technologies such as voting, opinion polls, social media feeds, and, increasingly, soi-disant AI.

Here, I am riffing on the ideas of Hanna Pitkin (mediated through conversations with Nate Matias), Andy Perrin and Katherine McFarland and Kieran Healy and Marion Fourcade. Hahrie Han and I have written a piece on AI and Democratic Publics that begins to lay out a broader version of this argument. As Cosma Shalizi pointed out to me later, the newsletter does overemphasize the importance of individuals who are designing the algorithms that shape new publics: malformed publics are perfectly capable of building themselves without Elon Musk putting his thumb on the scale.

Actually doing something about all of this will require a much better understanding of how technologies of representation intersect with the ways that humans think. The post also builds on work that Hugo Mercier, Melissa Schwartzberg and I have done to sketch out an initial agenda for how to do this. Samuel Bagg has recently written an incredibly helpful overview of academic research and thinking about these questions that points in a broadly similar direction; see also his recent conversation with Dave Roberts.

#2 - Absolute Power Can Be a Terrible Weakness

I wrote this post on the train from DC to Baltimore, but was only able to do so quickly because I’d been thinking about it for years. It builds on the ideas of Russell Hardin, who was one of the great theorists of collective action, and also a scholar of David Hume (I strongly recommend his book on Hume).

Hardin has a valuable short essay on the relationship between power and social coordination. This, in turn, suggests a theory of the respective strengths and weaknesses of would-be tyrants and civil society in situations of democratic breakdown.

Hume proposes that tyrants too, depend on social power and influence. They want to create an impression of inevitability, in which everyone accepts that the tyrant is going to win, and have self-interested reasons to jump in on the side of the winning coalition. Civil society can coordinate against the tyrant, but coordination is really hard! The best way for civil society to coordinate is not to generate an expectation of inevitability, but a shared understanding that politics is in play, and that they can succeed in pressing back against incipient tyranny if they get out and do things together to push back.

I think that this was a useful essay in getting Hardin’s and Hume’s ideas out into the world. It also generated (with great editing and restructuring) a New York Times opinion piece that people have told me was helpful in generating a common understanding, although I think that would have come anyway, as people actually began to get out on the ground.

I’m not the right person to turn these loose notions into serious models, but I’m grateful to Filipe Campante for pointing to “global games” as the technique that might most plausibly allow you to do this. It might also be interesting and useful to turn this into an actual boardgame, perhaps like Root, which Thi Nguyen describes as a “completely asymmetric game” about political power struggle, “where each different position has totally different goals and totally different mechanisms.” That might help people understand the dynamics in a practical and concrete way, though again I’m not the right person to to do this.

What I can do, and hope to do more of, is to write about how Hume and other people who are usually treated as classical liberals, provide valuable lessons for the left, centrist liberals, and the actually-democratic right. I’m reading Laura K. Field’s book on intellectuals and Trump at the moment. One of the lessons I take from it is that the right’s unmooring from the ideas of people like Hume has had terrible and pernicious consequences. This has been especially visible in Silicon Valley, but has been important elsewhere. Loosely similar notions to Field’s led me to write this post on Ernest Gellner; further pieces on Gellner’s sometime-friend, sometime-antagonist Karl Popper, and on Gerald Gaus’s fascinating posthumous book on the open society and its complexities will be coming sooner or later.

#3- Brian Eno’s Theory of Democracy

This post comes at the problems of democracy from a different but complementary angle from the first two. It asks how we might think coherently about democracy as an adaptive system, and suggests that an essay by Brian Eno provides a very useful starting point, even if it doesn’t mention the word ‘democracy’ once.

The problem is as follows: that the kinds of democracy we have don’t seem to be working, either in representing people in satisfactory ways, or in responding to a world that is far more complex and threatening than existing institutions are geared to handle. Eno offers a set of design principles for music, which apply remarkably well to other forms of social organization too, including democracy. When you are in a complex environment, you want institutions that are capable of generating new experimental ways of doing things, and building on the variations that seem to work.

This is, as Eno explicitly says in the essay, a cybernetic understanding of design, along the lines proposed by Stafford Beer. Unsurprisingly, it fits well with Dan Davies’ ideas about why large scale organizations and modes of economic policy making are increasingly dysfunctional, which revive Beer Thought for the early-to-mid 21st century.

Dan describes how Allende, when asked what was the ultimate cybernetic control system for society, pointed back to ‘the people.’ Equally, as the social media crisis post suggests, Allende’s dictum begs the question of how ‘the people’ articulates its own views and perspectives. And so back to democratic publics. One way is to build entirely new approaches to democracy. Another is to take existing institutions - such as political parties - and ask how they can be made more adaptable and responsive in a changed attention economy. Something like this intuition pops up in this Ezra Klein and Chris Hayes conversation about Zohran Mamdani. Can you bring together an experimentalist approach to policy with a new kind of attention politics?

I’ll be writing more on this this year, both in academic form with Margaret Levi (we want to ask how democratic experimentalism and social science notions about the experimental method fit together), and in this newsletter. I think the fights between left and moderates in the Democratic Party obscure a more fundamental set of arguments about experimentalism, which I’d like to bring to the fore.

The fundamental motivation for writing about this is that people who talk about democracy are often not strong at understanding the problems of institutional design in a unpredictable world. That is not the body of ideas that they are trained to draw from or to contribute to. People who are actually trying to do stuff in the world are somewhat better, because they have to be, but not nearly as good as they might be if there was a more organized conversation. It would be great if we had a more explicit body of work, ideas and examples that people could draw on, and Eno’s pithy, lovely essay is one way to get people thinking in different ways than they usually do.

#4 - Understanding AI as a Social Technology

This is another effort to build coherent debate where it is lacking, riffing on the ideas of others (in particular, Alison Gopnik, James Evans and Cosma Shalizi). Earlier this year, we wrote an article arguing that we needed to think about AI (emphasizing LLMs, diffusion models and their cousins) as social and cultural technologies rather than agentic intelligence in the making. We felt that a lot of very important questions about social and cultural consequences were being left to one side, because they did not fit into arguments about When AGI Is Coming And What It Means.

This post provides a downpayment on what it might mean to think of AI as a social technology in particular. It suggests that AI is another social shock in the long series of shocks that are the Long Industrial Revolution. When we look at the Industrial Revolution, we tend to overemphasize the technologies themselves, and underestimate the social, economic, political and organizational changes that went along with them. That is likely a mistake.

The post is rather stronger on exhortatory statements about What We Must Do, Comrades, If We Are To Be Real Social Scientists than concrete proposals for how we ought do the things that ought be done. There will be a paper with Cosma Shalizi, sooner rather than later all going well, which is intended to provide a more concrete starting point for bridging the social sciences and computer science so that each can better understand the social consequences (and, indeed, nature) of AI. The paper will likely build on some version of the ideas of Herbert Simon, who managed somehow to make seminal contributions to AI, economics, administrative science and cognitive science, all at the one time. So more on this soon.

#5 - Large Language Models As The Tales That Are Sung

I happened upon the perfect illustration for this piece by accident. It’s a papercut by Hans-Christian Andersen, in which the themes of fairytales repeat and exfoliate, with tiny variations caused by the material and cutting. That aptly illustrates an argument about why LLMs more closely resemble cultural systems of production like fairytales than most technologists suppose. Albert Lord’s The Singer of Tales is the classic account of how such cultural systems of production work.

This certainly isn’t the article that brought in most readers, but it is the piece that I am happiest about having written last year. It helped me articulate things that I had wanted to say but couldn’t figure out how to. As with pretty well everything else I have written, it borrowed heavily from other people. The core intuitions about structure came from Cosma Shalizi and Leif Weatherby, filtered through the broader arguments about AI as a cultural technology that I’ve already mentioned. Others than Cosma and I have noticed the strong similarities between LLMs and the kinds of structures of story telling that Lord describes.

But there is also something deeper and more personal in there too. Gene Wolfe’s books have shaped me in ways I find difficult to describe; especially his Book of the New Sun. For years, I have been trying to articulate how his understanding of story (which is attentive to the problems of structure and predictability that LLMs raise) could help us think about new technologies. I’ve tried before and failed. This time, I feel that I’ve succeeded better, by putting Wolfe (a Catholic humanist who was also an engineer) in conversation with a kind of structuralism that doesn’t dismiss the importance of human intention.

I’d like more people to read Wolfe, and not just because I find current humanist debates about AI frustrating. He was one of the greats. I’d also like to see more AI enthusiasts pay attention to culture as generative structure, to broaden their theoretical vocabulary for understanding technologies like AI. I’ll try to write soon about this conversation between Tyler Cowen and Alison Gopnik, where Tyler, who is more interested in culture than most economists, nonetheless seems to me to radically underestimate its scope and importance, and hence to mistake what is Alison is saying about AI as a cultural technology.

These are the posts from 2025 that I found most useful for my own self-centered purposes. I write this newsletter to build a kind of nexus of conversation that draws together a small number of themes, ideas and people that I think are complementary and important. I’ve tried to explain how some of what I’ve written speaks to these themes, ideas and people, to pull them together and suggest ways in which the conversation might go from here. Thanks to all, and best wishes for 2026!

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Today’s post is brought to you by Donald Trump’s Truth Social comment on Rob Reiner. But first, a quick obligatory plug for my and Abraham Newman’s book, Underground Empire (a fantastic last minute gift for your loved one who wants to understand what in the name of god is happening to the world), and musings on Irish politicians, fairy forts and tattoos that will seem at first to be completely irrelevant. I think that they add up into a backhanded theory of why no-one ever describes Trump as classy,* and why this is both a strength and a weakness for him.

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First, the Irish politician and the fairy-fort. From way back in 2017.

Independent TD (HF - a TD is a member of the Irish ‘Dail’ or national parliament) Danny Healy-Rae has insisted a dip in a Kerry road which had been repaired before mysteriously reappearing is due to the presence of fairy forts.“There are numerous fairy forts in that area,” he said yesterday. “I know that they are linked. Anyone that tampered with them back over the years paid a high price and had bad luck.” Asked if he believed in fairies, the TD said the local belief – which he shared – was that “there was something in these places you shouldn’t touch”. These were “sacred places” and fairies were believed to inhabit them, he said. “I have a machine standing in the yard right now. And if someone told me to go out and knock a fairy fort or touch it, I would starve first,” said Mr Healy-Rae, who owns a plant hire company.

At first glance, this appears to be an absolutely mad thing for an astute politician to say in a modern country. And Ireland is a modern country. We save stories about fairies for casual experiments to discover what gullible American journalists will swallow, and occasional excursions into ‘Celtic mysticism.’ Danny Healy-Rae is a canny politician, as anyone who has spent time in Kerry will know. He spends a lot of time getting to know his constituents: he called in to my parents during the last election, even though he knew perfectly well that there were no votes to be had in that household. So why would Danny Healy-Rae want to say something that will surely lead a lot of people to laugh at him?

Second, tattoos. As the great sociologist, Diego Gambetta has observed, criminals in many Western societies have a striking enthusiasm for visible and offensive tattoos. He describes one prisoner who had “spit on my grave” tattooed on his forehead, and “I hate you Mum” on his left cheek. Why would criminals want to have tattoos that would prevent them from ever getting a regular job or being treated ordinarily by ordinary people?

Gambetta’s explanation is that such tattoos are examples of a particular style of strategic communication, which aims to win by dividing. As I will explain, the same is plausibly true both of Irish politicians warning about the dangers of fairy forts and Donald Trump’s entire political style. The problem is that politics isn’t just about communication, but about governing and making decisions that affect people’s lives.

As Gambetta argues, criminal tattoos can be understood in game theoretic terms as a costly signal. As I’ve written before, building on Gambetta’s arguments, trustworthiness is a big problem for criminals. As one wannabe criminal described the problem, in a delightfully vexed plea that I came across on the dark web when I was doing research on such matters:

I have been scammed more than twice now by assholes who say they’re legit when I say I want to purchase stolen credit cards. I want to do tons of business but I DO NOT want to be scammed. I wish there were people who were honest crooks. If anyone could help me out that would be awesome! I just want to buy one at first so I know the seller is legit and honest.

So how do you find honest crooks? Your strategy will vary, depending on which kind of honesty and reliability you are looking for. The scammer who will cheat you on credit cards may be different from the person who will turn you in to the cops.

As a very first step, if you want to find a genuine criminal to crime with, you might reasonably want to start with people who have offensive and visible tattoos. Precisely because they have taken a costly step that makes it unlikely they will reintegrate with ordinary society, they are going to be more reliable along some dimensions of trustworthiness (while possibly being wildly unreliable along others). That is Gambetta’s argument.

A whole class of signals aims to inform the truster that defection would be not so much unprofitable as impossible. This logic stresses the presence of constraints rather than benefits. If there are no ready-made constraints to display, there is still the option of designing some, of binding oneself in some way, of burning one’s bridges or tying one’s hands so that one’s partners know that one could not defect even if one wanted to. In terms of the basic trust game it amounts to persuading one’s partners that the option “cheat” just is not there, or is so infinitely costly thatit is not worth worrying about it.

Here, the logic is that of what game theorists call a ‘signaling game.’ Imagine (this is stylized) that you are trying to find the right people to do a criminal transaction with, and you know that there are two ‘types’ who you might encounter: narks who will turn you in, or ordinary decent criminals (ODCs) who will do business with you.

You might not be able to distinguish narks from ODCs on the basis of what they say - both types will swear blind that they are proper criminals. If you can’t distinguish the one from the other (which leads to what game theorists call a ‘pooling equilibrium’), you may decide that the transaction is just too risky. However, if it is much less expensive for ODCs (who are committed to the criminal life) to signal their type by irreversibly tattooing themselves than it is for narks, then the result may be a ‘separating equilibrium,’ in which you can easily distinguish ODCs from narks by their tats, and profitably do business with them.

Importantly, as per Gambetta’s argument, tattooing is an effective signal because it cuts off future options. After you get your tattoo, you are committed to staying as a denizen of the underworld, because you have cut off the option of reintegrating into the civilian economy.

This logic applies to politics too! Danny Healy-Rae’s publicly proclaimed belief in fairy forts can be understood as a costly signal to Kerry voters. Kerry is a rural and remote part of Ireland, which is often looked down upon by other Irish people. English people used to tell Irish jokes; Irish people used to tell much the same jokes as Kerry jokes.

When Healy-Rae professes the fairy faith in public, he knows that he is likely to be treated with scorn (as he was) by sophisticated Dublin commentators. But that is what he wants! He is making a costly signal, losing the respect of some so as to win the loyalty of others. He actively welcomes the contempt of the commentariat because this will secure his reputation in the eyes of rural voters; it is what makes his signal costly and effective. Healy-Rae’s constituents can trust that he will not go native in Dublin and come to look down on them, as other representatives might.

From this somewhat functionalist perspective, the fairy faith and tattoos are much the same thing. In both cases, the particulars of the signal are irrelevant. Nobody cares whether Danny Healy-Rae really believes in fairies, any more than they were interested in whether Gambetta’s tattooed prisoner had a profound and lasting hatred for his mum. Commitment, not content, is what matters.

So this gets us, in a very roundabout way (I’m Irish, and a commitment to lengthy and genial narrative indirection is my costly signaling device) to Donald Trump and Rob Reiner. I don’t think that I need to belabor the many ways in which Trump’s style of communication is the Danny Healy-Rae Fairy Fort Strategy played on a much grander scale. So much of Trump - his contempt for niceties; his love of burgers and delight in gaudy decorations; even his verbal incontinence - is a commitment to all the things that college educated elites and wannabes absolutely hate. And this contempt, as others have commented, generates a kind of self-perpetuating feedback loop that game theorists might characterize as type separation. The more that decadent elites like myself sneer, say, at Trump’s penchant for putting marble everywhere, the more straightforward it is for Trump to signal that he is on the side of all the people who don’t like decadent elites. Like a bizarro-world FDR, he welcomes our hatred.

Equally, there are serious drawbacks to Trump’s approach. Trump is visibly not a strategic thinker in the game theoretic sense of the word. He is incapable of modulating his signaling as circumstances suggest.

This likely marks an important difference between him and the likes of Danny Healy-Rae. Another of Healy-Rae’s communicative antics was to propose the introduction of a “drinking license.”

The Kerry TD said the closure of pubs in rural areas had “left the social fabric in smithereens” and the community trapped and isolated. He told Tánaiste [HF - deputy prime minister] Simon Coveney in the Dáil: “I’m asking you to provide a permit for the people who are only travelling on local rural class three roads so they can have their two pints and drive home on those roads. “If they stray beyond those roads then nail them, but give them a chance to live and give them a chance to try it. All work and no play makes Jack a dull boy.” But dismissing his call, the Tánaiste said Mr Healy-Rae seemed to be making the case that the way to keep pubs open is to allow people to drink and drive.

However, Healy-Rae almost certainly did not mean this as a serious policy proposal. It was total guff, purpose-designed to get a rise out of the likes of Simon Coveney. In the unlikely event that Healy-Rae ever became a member of the Irish government, he would not, actually, press for people in rural areas to be allowed to drink and drive home, because this would likely alienate many of his voters (drunk driving licenses would very quickly come to have visible downsides).

As president, Donald Trump would and has pressed for policies that are even more strategically short-sighted than drunk driving licenses. Unlike the canny Healy-Rae, there is no discernible difference between what Trump signals and who he is. There is a famous Mario Cuomo dictum that a politician should campaign in poetry and govern in prose. Donald Trump both campaigns and governs in the language of shitposts. His great tragedy is that this is all that he is capable of doing.

Trump is mostly uninterested in the content of policy; the signal and the dismay of his adversaries are what he cares about. That is great for sticking it to the man; not so great for moments where policy actually matters. And for many, and likely most people, policy does count when politicians are in government.

This finally gets us to Trump’s attack on the late Rob Reiner. It was mean-spirited, shitty, and almost certainly politically counterproductive. It didn’t obviously win Trump friends, and likely stirred up opposition, making it that little bit cheaper for unhappy members of his coalition to come out against him.

But such attacks are very much who Donald Trump is. He is the kind of person who will, almost inevitably, say things like that, even when it cuts against self-interest. He is incapable of being classy in public - of showing generosity to those who oppose him or who he feels have injured him. That can be a great advantage in winning over voters who feel screwed over by the prevailing compromises of politics, and don’t want someone who will make nice with the powers that be. Trump is absolutely committed to the bit. He is the type of politician who won’t deviate, because he simply can’t deviate.

Hence, Trump is reliably trustworthy to his constituents, in a very particular sense that is impossible for ordinarily strategic politicians to emulate. He will never suck up to the traditional power elite. As long as that is what you mostly care about, Trump has the advantage.

Equally, when he actually comes to power, this strength is liable to turn into weakness. You can be absolutely sure that Donald Trump will never become a narc for the traditional power elite - both native disposition and the larger system of social resentments that shape his understanding of America rule that out.

Still, you wouldn’t want ever to trust him to deal with you fairly if his interests pointed in the other direction, any more than you would any other heavily tattooed criminal. When his decisions shape your day-to-day life, that becomes a problem for you, and perhaps, increasingly for him, as it becomes more salient to voters.

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* To a Substacker’s first approximation. I’m not going to spend hours in Google searches trawling for disconfirming evidence, only to be trumped by some obsessive who finds the one shining example buried deep in an archived Truth Social posting.

I’ve spent the last couple of days in Italy at the Grand Continent Summit, a geopolitics meeting which takes the word summit seriously. It culminated in a trip to the Matterhorn glacier, 4,000 meters or so above sea level (I should be clear that this isn’t the kind of event that I usually get invited to). There was a lot of discussion, much of it skeptical, about the U.S.-Europe relationship, but no-one I talked to on the closing day had any idea of how wild the Trump Administration’s National Security Strategy would get.

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Back when I taught “Intro to International Relations," I always did a week on “grand strategy." Half the lecture talked about international relations theorists who dreamed of becoming the new George Kennan, drafting some sweeping and comprehensive approach to world order that would remake US foreign policy making for decades. The other half described the more mundane and important activity of crafting America’s National Security Strategy, a document that does its best to spell out a broad strategic vision, but inevitably gets pulled into the awkward realities of complicated issues, different factions in US politics, ally politics etc.

The Trump administration’s new strategy for the world is a kind of Groyper Grand Strategy Cosplay, which simultaneously purports to be a guide to specific policy.* It is set to fail, even by its own ludicrous and wildly offensive standards. As I used to tell my students, a National Security Strategy speaks to three audiences: the U.S. government itself; allies and friends, and adversaries. The new strategy can’t be coherently implemented by the first, will alienate the second still further, and will open up opportunities to the third.

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As mentioned, a National Security Strategy (NSS from here on in), sets the government’s national security priorities. New administrations have new goals and approaches to the world - each at some point comes up with its own NSS.

The NSS doesn’t have any binding force, but it is meant to serve an important practical use. The United States policy making apparatus is enormously complex, with many different institutions, agencies and departments which have some greater or lesser role in national security, but regularly get in each other’s way. That poses enormous challenges of coordination.

The NSS helps to mitigate these challenges by laying out the administration’s broad objectives, tradeoffs and preferred approaches, so that everyone has a rough sense of how policies are supposed to fit together. However, broad objectives and approaches don’t magically coordinate the government on their own. That is why the US has a National Security Council (NSC), which is primarily responsible for connecting the priorities of the president to the different parts of the government, building understanding across institutions and agencies, and banging heads together when heads need to be banged. Then, those institutions and agencies are supposed to do all the things that need to be done given these priorities, coming back and providing further information as needed. This is a gross simplification of an enormously complex cybernetic mess, but it gives the broad picture as I understand it.

The brand new NSS purports to be vastly clearer and more effective than its predecessors (which it describes as mere “laundry lists” of “vague platitudes”). Finally, after many false starts, America’s true national security interests have been discovered, heralding a new age of decisive national security policy making!

Or, perhaps, not. Laying out grand plans is not much help if the government is incapable of delivering on them. Who is going to make sure that these priorities get implemented? The NSC has been gutted in a series of ideological purges, egged on by those who interpret expertise and experience as codewords for Deep State sympathies. It is less than half its previous size, and even less able than that might suggest to connect priorities to process. Matters are even worse in the State Department, and the strategic decision making bits of major national security institutions aren’t doing great either. People are still fleeing and being fired. So too for the bits of government that are actually supposed to implement the detail of policy. All this is compounded by the president, who most likely hasn’t read the document, and will continue to do whatever the hell he feels like doing in the moment.

That all has big consequences, if you think through the implications. People blame the Trump administration’s foreign policy failures on bad ideas, self-dealing and inexperience. These indeed are important problems. But, as someone recently remarked to me, there is another, even more fundamental challenge. Even if the stupidity and cupidity magically evaporated, the Trump administration lacks the institutional bandwidth to execute the sweeping changes that it proposes. It has hollowed out the coordinating apparatus that the US government uses to set priorities and coordinate across the whole bureaucracy. Stuff still happens, but haphazardly. When underlings turn priorities into policy, they are likely to do so in different ways that may be contradictory or even mutually undermining. Sometimes this will be the product of sincere mistakes, and sometimes of deliberate misinterpretation, as different factions vie for advantage. There isn’t any effective NSC to manage clashes or ride herd.

The problems aren’t just within the US government. The NSS also gives allies and other friendly countries some sense of what to expect from America. That isn’t its direct purpose, but it is absolutely something that its drafters need to think about when they’re writing it. They know that the document will be read by other countries that want to figure out what US national security priorities are, and what their consequences might be.

What signals does Trump’s new NSS send to allies and potential allies? There is lots that could be said e.g. about the revival of the “Monroe Doctrine” (under which the US considers the western hemisphere its exclusive sphere of influence), and the “Trump corollary” of “enlisting” and “expanding,” whatever that is supposed to mean in practice (please don’t call these ‘vague platitudes’ - it would be rude). However, others are better suited to explain these questions than I am.

What I can talk about is Europe, having just sat through a couple of days of conversations among Europeans, and having listened to many similar conversations over the last several months. It has been clear for some while that the Trump administration has a … novel … understanding of America’s relationship with Europe. But it has not always been as clear as it ought be to European officials. These officials have often vacillated in response to previously unthinkable demands, sometimes making concessions, sometimes looking to preserve a little autonomy. Brief shocks (such as J.D. Vance’s speech at Munich) have not been sufficient to galvanize long term coherence.

I can’t say for sure that the NSS will do the galvanizing, but I think that it will push Europe a fair distance further along the road to resistance. The document soft-pedals America’s rivalry with China (the central theme of the first Trump administration’s NSS) while spitting malice and venom at America’s most established supposed allies. Its clear message is that Europe - as it is currently constituted - is a threat to U.S. wellbeing.

The National Security Strategy declares that Europe is not just in economic decline, but faced with the prospect of “civilizational erasure.” The “European Union and other transnational bodies” are undermining “political liberty and sovereignty.” Europe is riddled with “censorship of free speech and suppression of political opposition.” It is led by “unstable minority governments, many of which trample on basic principles of democracy to suppress opposition.” Most fundamentally, Europe is being turned into a zone of “strife” by migration policies, so that it will be “unrecognizable” in two decades. Certain NATO members will become “majority non-European”and no longer reliable allies. It doesn’t take much sophistication to decipher what terms like “majority non-European” are intended to mean.

However, the NSS says, America “cannot afford to write Europe off.” Instead, it will work to foster what it calls “genuine democracy, freedom of expression and unapologetic celebrations of European nations’ individual nations’ character and history.” America “encourages its political allies in Europe to promote this revival of spirit, and the growing influence of patriotic European parties indeed gives cause for great optimism.” To help all this along, the NSS says that America will undertake actions which include “[c]ultivating resistance to Europe’s current trajectory within European nations” and “[b]uilding up the healthy nations of Central, Eastern, and Southern Europe through commercial ties, weapons sales, political collaboration, and cultural and educational exchanges.”

This is, quite straightforwardly, a program for regime change in Europe, aimed at turning it into an illiberal polity. Accomplishing this transformation would involve undermining existing liberal governments in cahoots with Europe’s own far right, and turning Eastern Europe into an ideological wedge against its Western neighbors.

That all sounds horrifying: might it work? Theodore Roosevelt famously recommended that the U.S. should speak softly while carrying a big stick. Big talk and soft stick are likely less effective.

Again: the Trump administration’s capacity to turn rhetoric into concerted action is undermined by its self-created lack of bandwidth and capacity to coordinate policy. Nor does the Trump administration have the solid domestic support in the United States that it needs to make its threats and promises stick over time. It is electorally weak and looks, at least on current trends, to be growing weaker.

It probably isn’t a good idea to telegraph threats like a James Bond villain. Vacillating European liberal leaders are now less likely to be hesitant than in the past. The Trump administration has declared, in its defining national security document, that the EU and they themselves are a security threat to the United States. I suspect that this is more likely to build solidarity and resistance than to break it down.

We’ll likely see very soon whether this guess is right. The NSS depicts the EU as a threat to liberty, casting its restrictions on social media as censorship and oppression. The same morning that the NSS was published, the EU issued a preliminary finding that Twitter/X had breached EU law proposing to fine it 120 million euro. More findings and more fines are likely in the future.

Even before the finding was announced, JD Vance had condemned it. Elon Musk has asked that the US not only punish the EU, but the individual officials who were responsible for the decision. Will the US retaliate against the EU, and if so, how? If it does retaliate, will the EU back down, or will it stick to its guns? The NSS has likely lowered the odds of capitulation and increased the odds of resistance. So too has Trump’s decision to mostly back down from similar threats that he made against Brazil.

None of this implies that Europe is not in serious political and economic trouble. But the NSS likely undermines rather than bolsters the US ability to reshape Europe, which it would anyway find hard. Perhaps the US can help European far right parties a little. Alternatively, its efforts to help them might turn out to be counterproductive. Europe’s more serious political challenges are internal; if the US accomplishes anything it will likely be opportunistic, on the margin, and happen half by accident.

Finally, America’s rivals and adversaries will take lessons from the NSS too. The decision to target close US allies, rather than China or Russia, says a whole lot about America’s priorities right now. They are inward focused - the guff about civilizational collapse in Europe reflects the administration’s anxieties about the continued strength of liberalism within its own political system.

All this suggests that America isn’t going to pay much serious attention to the rest of the world for the next few years, except when it pays off for Trump and his cronies in very direct ways. The US government’s lack of available bandwidth may worsen as it gets mired down in some of the mistakes that it makes. When America does pay attention to the world, it will likely make bad choices, which may create sometimes create greater uncertainty and risk for America’s adversaries, but may also open up greater opportunities. Finally, America is now saying that key allies are in fact its greatest enemy. That gives those allies strong incentives to reduce their dependence on American power and technological and economic platforms, building closer connections among themselves and perhaps with others. All this is likely to the benefit of those who’d like to see America taken down a peg or three.

The Trump administration’s vision of American greatness is making the country poorer, weaker, and meaner. The new strategy document will do its own little bit to accelerate that process.

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* In fairness, George Kennan was not nearly as far from the groypers on race and democracy as his aristocratic mien might suggest.

[“A Fully Cut Fairy Tale”. Paper cutout by Hans Christian Andersen. From the collection at the Met, and remarkably apt for the post below]

When I wrote some months back about various ways of thinking about AI as a cultural technology, I left one approach out: humanism. This is a loose family of understandings that oppose Large Language Models on the grounds that they replace human culture with something that is machinic and alien. I couldn’t see a good way to reconcile this approach with the others that I discussed, which think about culture in different ways. Leif Weatherby, for example, is sharply critical of what he describes as ‘remainder humanism,’ which he sees as ignoring the large systems, most notably including human language, that actually produce culture.

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I’m intellectually sympathetic to Weatherby’s arguments; but I’m also sympathetic to certain flavors of humanism, and have been thinking about how to put the two in conversation with each other. Writing a piece that tries to do this has taken a while. These are not the kinds of argument I specialize in as a scholar. The weird intellectual path I’ve chosen leads through the science fiction of Gene Wolfe and the folklore studies of Albert B. Lord. I also take liberties with the ideas of friends and others, who bear no responsibility for any intellectual abominations that I commit. Caveat lector.

Both Wolfe and Lord died before LLMs became a thing. Nonetheless, both thought about the relationship between the immensities of language and human culture and the more particular desires of human beings to tell their own stories. I read their ideas as as implying that LLMs have much in common with the long existing traditions that storytellers draw upon. It is not simply that the compressions that LLMs derive from enormous corpora of text resemble, and arguably incorporate, the characters, stock phrases, tropes, situations and narrative structures that storytellers weave together. It is that LLMs and storytelling traditions are similar structures - large scale bodies of generic cultural knowledge that are drawn upon in somewhat predictable ways to create specific cultural instances.

These are not original claims on my part. Their proximate beginnings lie in an emailed side-remark by Cosma Shalizi about LLMs and The Singer of Tales, and his extended discussion of LLMs here. Kush R. Varshney independently struck upon the same comparison in this paper, which investigates the relationship between LLMs and Lord’s ideas from an engineering perspective. [Update: also Bill Benzon, David Smith, and, I suspect, others too]. I’m also influenced in ways it would be hard to set out by the work of my grand-aunt, Maire MacNeill. She was a folklorist who died too early for me to know well, but her writing and translations shaped my childhood; The Festival of Lughnasa, fairy tales collected from the oral tradition in West Donegal; the book of the storyteller, Sean O’Conaill, who lived on the same peninsula that John McCarthy’s people came from. More even than most children, I grew up amidst the cultural structures of folklore, without ever really thinking about what they involved.

LLMs resemble folklore in structure, but differ in their relationship to intentionality and performance. In one sense, stories are assemblages of tropes about third sons, enchanted rings, animal helpers and the like. In another, which is equally important, stories don’t exist until they are spoken and are products of the circumstances of their speaking. Their meaning doesn’t just reflect a shared tradition, but the particular circumstances under which they are told: an individual human speaking to other humans, snipping or stretching out the cloth of the tale as it is woven, to suit the desires, expectations and responses of his or her audience. In this, stories differ from LLMs, which instantiate the tradition itself, in its indifferent and inhuman nakedness. LLMs are not the singer, despite their apparent responsiveness, but the structural relations of the tales that are sung. Still, we can now listen to and even interrogate those structures without immediate human intermediation. That is new.

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Gene Wolfe is one of the great science fiction writers, though he is little known outside the genre. Ted Chiang cites him as an important influence. Ursula Le Guin compares him to Melville, who, like Wolfe, freighted adventure stories with theological and metaphysical speculation. Kim Stanley Robinson likens him to Proust, whose prose style and sense of time as a lucid dream was put by Wolfe to his own purposes. Wolfe has had little influence on debates over AI, unlike some of his lesser peers. Perhaps that should change.

Wolfe was an engineer, but his great love was for stories. As Severian, the imagined narrator of his great work, the five “New Sun” books, remarks after a story-telling competition:

it often seems to me that of all the good things in the world, the only ones humanity can claim for itself are stories and music; the rest, mercy, beauty, sleep, clean water and hot food (as the Ascian would have said) are all the work of the Increate. Thus, stories are small things indeed in the scheme of the universe, but it is hard not to love best what is our own—hard for me, at least.

From this story, though it was the shortest and the most simple too of all those I have recorded in this book, I feel that I learned several things of some importance. First of all, how much of our speech, which we think freshly minted in our own mouths, consists of set locutions. The Ascian seemed to speak only in sentences he had learned by rote, though until he used each for the first time we had never heard them. Foila seemed to speak as women commonly do, and if I had been asked whether she employed such tags, I would have said that she did not—but how often one might have predicted the ends of her sentences from their beginnings.

I’ll return to “this story” (told by an Ascian prisoner) below. For the moment, just note the tension that Wolfe identifies. Severian (presumably speaking for Wolfe) describes stories as something that is uniquely “ours,” uniquely human. Yet he also notes that they are composed of language that is predictable, a commingling of stock parts or “set locutions,” as is our ordinary language itself. Those locutions are joined together into sentences that are highly redundant.

As for language, so too for the tales we tell with it. They too are regularly built from stock parts, as Propp and others have argued. In an earlier book in the New Sun series, a child asks Severian to “find a story with a boy in it who has a big friend and a twin. There should be wolfs in it.” Boys, animal friends and twins appear regularly in folk tales, together with many other stock elements. One consequence of this is that folk tales can be recombined more readily than other narrative forms such as novels or written poems; they are mishmash from the beginning. The story that Severian tells the boy commingles The Jungle Book with the rescue of infant Moses, the rivalry of Romulus and Remus (who, like Mowgli, were suckled by wolves), and the founding of colonial America. In Severian’s far future earth, our stories and our history have commingled to become part of the common stock of collective human wisdom.

Misprision becomes a source of new variations. Another story recounted by Severian confounds the hero Theseus with a graduate student’s thesis, while the Minotaur and the steamship Monitor are merged into a fearsome giant with a “naviscaput,” roaming a maze of silted channels purpose-built to exhaust his prey. Wolfe resembles Joyce as well as Proust and Melville in his delight in wordplay and sometimes terrible puns.*

Yet this play is not completely open-ended. It builds on and from a system. Wolfe’s remark that “how often one might have predicted the ends of [Foila’s] sentences from their beginnings” is strongly reminiscent of the ideas of Claude Shannon. Such predictability is the core insight of Shannon’s predictive account of language, which in turn was the intellectual starting point for the development of Large Language Models. A “statistical model of language,” which makes the open-endedness of language (its particular version of the ‘curse of dimensionality’) tractable, combined with the particular affordances of the transformer architecture, powers the next-token prediction of LLMs.

Wolfe had great love for stories, but he was also an engineer. I suspect that the resemblance between Severian’s critique and Shannon’s ideas is the product of deliberate artifice. There’s no explicit evidence I’m aware of that Wolfe read Shannon (perhaps such can be found somewhere in his technical essays for Plant Engineering, which have never been collected), but elsewhere in the books Severian presents a theory of the knowledge of magicians that is based on signaling theory and lossy transmission.

Yet Severian does not love stories because they are a statistical extrapolation of underlying structures in language and culture. He loves them because they are human. So how do human stories emerge from vast systems, without being reducible to them?

*******

That question is explored in another extraordinary book, Albert B. Lord’s The Singer of Tales (available for free online). Lord built on the work of Milman Parry, who he had helped to record Yugoslavian singers of tales in the mid-1930s. From this experience and archive, Lord constructed a broader account of the oral tradition, which he believed encompassed Homer and other singers of epic histories. By extension, his argument also covers other forms of the oral tradition, such as the Irish fairy tales that my grand-aunt and others translated, compiled and sought to understand.

Parry and Lord listened to singers, whose tales described great heroes, villains and battles of the past (unsurprisingly, given the asperities of Yugoslav history, Christian and Muslim singers disagreed about who were the heroes and who the villains, though Christian singers could calibrate their stories for Muslim audiences and vice versa). The anthropologists recorded these songs on crude discs. These songs were the last whispers of a tradition passed down by illiterate singers and story tellers (although when Parry and Lord heard them, their singers were already beginning to be influenced by written culture). Some of the songs were very long, but accomplished singers could sing very many of them. How, given the faults and frailties of human memory, did they manage this?

The answer, according to Lord, lay not in rote memorization, but the nature of the oral tradition that they drew upon. While the singers themselves insisted that they could reproduce the songs perfectly and without error, their sense of perfection differed from ours. Neither the epic songs, nor the broader tradition they drew upon were unchanging texts. Instead, the specific epics they sang, and the epic form itself was better understood as a kind of “dynamic structure” that could generate new cultural instances.

This structure was a kind of ‘grammar,’ a set of rules that determined not simply the meter, but how the story flowed, which themes were emphasized and which suppressed, and so on.

In studying the patterns and systems of oral narrative verse we are in reality observing the “grammar” of the poetry, a grammar superimposed, as it were, on the grammar of the language concerned. Or, to alter the image, we find a special grammar within the grammar of the language, necessitated by the versification.

Singers constructed their tales around set “themes” or situations, such as the “council meeting” in which the possibility of battle is discussed. To describe these themes, they drew on a “common stock” of formulas they then deployed to reconcile characters, the style of the story, the expectations of the audience, and the meter of the song. Different singers had slightly different repertories of formulas, which might be greater or smaller, depending.

The singer never stops in the process of accumulating, recombining, and remodeling formulas and themes, thus perfecting his singing and enriching his art.

Singers might come up with their own variations, which could in turn be copied by others. All this perpetuated a tradition that was continually recreated in its own performance. In the oral tradition, epics are not fixed texts, but generative systems of songs, endlessly articulated, re-articulated and adapted in varying forms, according to the particularities of the singer and the circumstances they sing in. As Lord puts it: “we cannot correctly speak of a “variant,” since there is no original to be varied.”

As Cosma has pointed out, there is a remarkable resemblance between LLMs and Lord’s depiction of the oral tradition. That is because LLMs, like Lord’s singers, have mastered the tropes from which tales are made, but on the level of written culture itself rather than any narrative form or genre therein.

A huge amount of cultural and especially intellectual tradition consists of formulas, templates, conventions, and indeed tropes and stereotypes. To some extent this is to reduce the cognitive burden on creators: this has been extensively studied for oral culture, such as oral epics. …

The formulas make things easier to create and to comprehend once you have learned the formulas. The ordinary way of doing so is to immerse yourself in artifacts of the tradition until the formulas begin to seep in, and to try your hand at making such artifacts yourself, ideally under the supervision of someone who already has grasped the tradition. (The point of those efforts was not really to have the artifacts, but to internalize the forms.) Many of the formulas are not articulated consciously, even by those who are deeply immersed in the tradition.

Large models have learned nearly all of the formulas, templates, tropes and stereotypes. (They’re probability models of text sequences, after all.) To use Barzun’s distinction, they will not put creative intelligence on tap, but rather stored and accumulated intellect. If they succeed in making people smarter, it will be by giving them access to the external forms of a myriad traditions.

There is a lot of speculation that LLMs are returning us to something like oral culture. There is rather less that engages in any very intelligent way with the particulars of how oral culture works. Oral culture, like LLMs, involves lossy abstractions that also serve as generative systems. It too produces myriads of variations on common themes, adapting them to particular prompts and circumstances. It too is indifferently geared for verbatim transmission of the work on which it has been trained. When Varshney describes Lord’s formulas as “heuristic solutions to constrained optimization problems that must be solved in real-time,” he is using language that Lord might perhaps have found peculiar (though also perhaps not; Jakobson was on his dissertation committee), but that Wolfe would readily have recognized.

Again, it is a mistake to treat either oral epics or LLMs as fixed texts. From an analytic perspective, they are systems for producing particular cultural forms, which adhere to particular rules, stereotypes and expectations. They can be expected to be lossy in loosely similar ways. Lord notes that singers employ the “principle of thrift.” Once they have discovered a good technique for solving a particular class of textual problem (e.g. reconciling a particular kind of description with the expected meter), they will deploy it again and again. LLMs have their own principle of thrift, so that their compressions emphasize commonly encountered cultural patterns to the detriment of those encountered rarely in their training data.

As it turns out, LLMs are not very good at the rhyme and meter of language (perhaps since they are trained on written text rather than its heard performance).** But many aspects of human work and culture involve broadly similar combination of templates and stereotypes to those employed by the singers of tales. I suspect that this helps explain the facility of LLMs in carrying out many programming tasks, since programming too involves figuring out how to apply a common formula to a particular problem. The poiesis of the programmer is closer to the heroic poiesis of the bard than we think. As one of my old XKCD t-shirts puts it: stand back - I know regular expressions! So too for performance in math olympiads.

And perhaps also for much of the practice of social science? Dani Rodrik has written that a great deal of the art of the economist consists in accumulating a large mental library of mathematical models, and building an intuitive grasp of which model one ought to use when. Equally, there is reason to suspect that there are sharp limits to the capacities of LLMs to apply their compressions and transformations to unexpected challenges, and to aspects of the physical or social environment that don’t translate easily into spreadsheet form.

The fundamental point, then, is that a lot of human culture and endeavor does not just depend on lossy compressions, but involves dynamic systems that combine and apply these compressions in useful ways. These combinations may be surprising (involving unexpected juxtapositions), although they will likely have limited originality. Equally, originality may be unnecessary for many tasks, and even over-rated: Lord hints that our desire for artistic originality may be related to the anxieties of print and the other technologies of accurate production that have overtaken oral culture:

Expression is [the business of the singer], not originality, which, indeed, is a concept quite foreign to him and one that he would avoid, if he understood it. … There are periods and styles in which originality is not at a premium

Perhaps we might expect that in the near future we will return to some form of those norms of expression, to the extent that LLMs become culturally dominant. Perhaps instead, we ought anticipate a cultural reaction against them, doubling down on originality.

Whatever happens, Lord suggests that human culture does not have to be original to be human in the ways that writers such as Wolfe care about. Structural systems such as epics can produce possibilities for human meaning. As he says, “the style is not really so mechanical as its systematization seems to imply.” The tales would not work if they were mere jumbles of expected cliches.

Most importantly, stories are performed in settings that emphasize the relationship between the singer and the audience. When the singer sings, “the song produced in performance is his own. The audience knows it as his because he is before them.” Lord describes how the singer (apparently always male in 1930s Yugoslavia, though of course women are storytellers too) adapts his performance of the story to the audience and what they seem to want. If the audience appears to be growing restive, the tale may be changed, or truncated. While the tale draws on structure, it is performed in the moment, and in the context of human intentions and human relationships shared by singer and listener.

That, then, is an important - and from some perspectives crucial - difference between traditional generative cultural systems such as the oral epic tradition in Yugoslavia and its Homeric ancestor and cousin, and algorithmically generative cultural systems such as LLMs. The former are inseparable from their performance in human contexts: the system can be abstracted from their performances, but does not have any substantial being independent of them. The tradition’s existence is manifested through the stories that humans tell each other. LLMs, in contrast, are a condensation and actualization of the tradition itself and all the other traditions that have been folded and compressed into its statistical weights, stripped of the specifics of human relationships and reapplied to them as an algorithmic process. LLMs speak only when prompted, but their continuations of those prompts are not expressed through two-way human relationships (though the words used by the prompter, training via RLHF and fine tuning etc obviously affect the outputs). The person who prompts the LLM is interrogating a lossy representation of the tradition itself. Of course, LLMs may then shape human understandings, and fool people into treating them as human, but they are not. Their tangible abstraction is something that is novel and different in its application than the previously intangible cultural knowledge that they summarize.

LLMs, then, can reasonably be understood as a summarized composite of the tales that are sung. In their particular applications, they are even a version of the singing of the tales. But they are not, and cannot be, the singers. Our relationship to them, and our interpretation of what they tell us is necessarily different from our relationship with and interpretation of what we tell each other.

*******

To understand this, it’s helpful to return to Wolfe’s Severian. As I’ve already noted, Severian makes his remarks about stories in the context of a story telling competition. He has fallen ill, and is stuck in a lazaret with soldiers recovering from their wounds, where there are few other ways to distract from current circumstances than to talk. Two of the other inmates are vying for the hand of a third, Foila, who has said that she will marry whoever can tell the best story. This framing story itself partakes of the logic of the folk tale, but it is also a space for the play of agency. Foila changes the rules of the competition twice to suit herself; once to allow a third inmate, an Ascian prisoner, to join the contest; then to enter into the competition on her own behalf by telling her own story. For after all:

Even a man who courts a maid thinking he has no rivals has one, and that one is herself. She may give herself to him, but she may also choose to keep herself for herself. He has to convince her that she will be happier with him than by herself, and though men convince maids of that often, it isn’t often true.

Severian wonders whether the Ascian prisoner too has picked his story to convey a hidden message, and why Foila had allowed him to participate at all. None of this is obvious - the competition is a maze of ambiguous intentions.

I had not learned those things I had most wished to learn as I listened to the Ascian and to Foila. What had been her motive in agreeing to allow the Ascian to compete? Mere mischief? From her laughing eyes I could easily believe it. Was she perhaps in truth attracted to him? I found that more difficult to credit, but it was surely not impossible. Who has not seen women attracted to men lacking every attractive quality? … And what of him? Melito and Hallvard had accused each other of telling tales with an ulterior purpose. Had he done so as well? If he had, it had surely been to tell Foila—and the rest of us too—that he would never give up.

Stories can convey messages, but those messages are likely (except in the most debased and simple tales) to be partly obscured, and sometimes more obscure even than that.

The Ascian’s story is constructed as a most difficult case for individual meaning. He comes from a future North America that seeks deliberately to stamp out individuality in favor of imposed culture. In Ascia, people apart from children can only speak by reciting rote phrases, taken from a small set of approved texts that they have memorized. Hence, the story that the prisoner tells is a sequence of a couple of dozen of these phrases, from which the careful and informed listener can construct a story.

On its face, this seems a fantastical version of Orwell’s Newspeak, a victory for the imposition of the unchanging printed phrase, and the antithesis of the dynamic oral traditions from which new usages and conjunctions may appear. Yet even in this deliberately cramped and pinched linguistic system, ambiguity of intention can seep from the cracks, interstices and implied spaces of imposed tradition. The tale cannot fully be confined within the artificial prison house of language.

I learned once again what a many-sided thing is the telling of any tale. None, surely, could be plainer than the Ascian’s, yet what did it mean? Was it intended to praise the Group of Seventeen? The mere terror of their name had routed the evildoers. Was it intended to condemn them? They had heard the complaints of the just man, and yet they had done nothing for him beyond giving him their verbal support. There had been no indication they would ever do more.

Severian does not grasp the intention of the tale, nor the Ascian’s intention in its telling. Yet his belief that there is some intentionality to both the tale and teller, however murky or unclear - perhaps unclear even to the Ascian himself - is what makes the story human. Telling a story is a human speech act, through which one human looks deliberately to communicate with others. The selection of certain rote phrases rather than others combines with the circumstances of their utterance to convey meaning and ambiguity, both so entangled as to be impossible to separate. As Wolfe says elsewhere, the speaking of any word is futile unless there are other words, words that are not spoken. The meaning behind the choice of some words or stock phrases, certain tropes rather than others is hard to grasp, yet we struggle to understand this meaning, because there has been some choice that matters to us. We are more than the bearers of structure and ideology.

It is this that distinguishes human stories from the productions of LLMs. On some dimensions, LLMs are much more open-ended than the little red books of the Group of Seventeen. Indeed, as Varshney points out, LLMs are not in fact well captured by the common stock phrase “stochastic parrots,” since they can come up with novel combinations. Even back in 2023, they could do weird and unexpected things, such as inventing cod-Latin phrases, as I discovered when I prompted one to rewrite the plot of Hamlet in the style of a chemistry textbook.

However, they’re definitionally incapable of the kind of ambiguity that the Ascian prisoner can achieve through the mere combination of rote catchphrases. There is no valid room for wondering about LLMs’ motives for saying things, since they don’t have any motives to wonder about. As Weatherby argues, LLMs have “heat-maps” of summarized correlations between themes, tropes and words instead of intentions.

As I noted at the beginning, Weatherby dismisses “remainder humanism,” ideological efforts to distinguish human culture from the systems that perpetuate it. However, he still acknowledges the distinction between poetry - a system of conventions and usages, and the individual sonnet that “unites poetry with an intention.” Even if LLMs are made out of poetry, they are incapable of producing poems. Or in Wolfe’s language, both the epic form and LLMs are story, but are incapable of telling stories. That requires the marriage of structure and intention that human mediation provides. LLMs are a kind of composite of the singing of tales, but are not singers, even if we sometimes misconstrue them as such.

*******

Thinking about stories - and perhaps art more generally - in this way does not lead to any very emphatic conclusions about the relationship between humanistic values and vast impersonal structures. At most, I think, it provides a common space where people concerned with the one can more easily talk to the other, and where the spaces of agreement and disagreement become more visible. And perhaps not even that: I’m venturing well outside my own areas of expertise, and may have blundered. Even if so, I still believe that humanism is not incompatible with the acknowledgement of large structure, nor structuralism with acknowledging the importance of human intentions.

This leaves open the question of whether LLMs and their cousins (e.g. diffusion models) can produce art. Does art necessarily involve human intention? Perhaps not necessarily. I suspect that as artists begin to use these tools, many of the effects they produce will rely on what Mark Fisher calls the “eerie” - the sense that agency is missing where it ought to be, and that something strange has crept in to fill the void. Others may dispute whether such productions are, in fact art, or something different. Others still may argue that even if AI is at a remove from human intentions, it is still human made. And there will be all sorts of hybrid productions.

I’m not the right person to mediate such disagreements, let alone resolve them, but I would like to see them better and more sharply articulated. Technologies such as LLMs are neither going to transcend humanity as the holdouts on one side still hope, nor disappear, as other holdouts might like. We’re going to have to figure out ways to talk about them better and more clearly.

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* One joke that I have not seen picked up anywhere involves the “Cumaean,” who, in Wolfe’s version is a serpentine alien, covered in scales that resemble human faces. Naturally, Wolfe never uses the word “pythoness” in connection to the Cumaean or otherwise, leaving the discovery of the pun as an exercise for the reader.

** Casual experimentation suggests that the most recent version of Claude Opus has gotten quite good at reproducing iambic pentameter (a meter that I’ve chosen for the semi-arbitrary reason that a few of Wolfe’s aliens speak exclusively in it). Ironically, Claude Sonnet cannot. Nor can the most recent version of GPT.

[Image from the Met]

Here’s a trick for reading Ezra Klein’s article in the New York Times yesterday. First of all, read Ross Douthat’s piece offering advice to the Democrats on what they ought do. Then, as you are reading Ezra’s piece, ask yourself: are there important differences between what the two are saying?

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Some people seem to read them as minor variations on the same theme. I think that is badly mistaken. The difference between the argument that “the Democratic party should become a moderate party” and the argument that “the Democratic party should be more welcoming to moderates and other people who don’t agree with all their positions” may appear subtle at first glance, but has substantial practical consequences.

The one hectors Democrats, saying that it is “obvious” that they need to move closer towards Republicans’ positions and converge on the center, because voters converge there too. The other argues that Democrats need to deal with the fact that they are a plural party, with many internal disagreements, but that this is not necessarily a bad thing. It reflects the messiness both of practical liberalism and of politics; voters are plural, and public opinion is complicated.

Douthat says that fixing the Democrats’ problems is easy in principle - just look to the median voter and make him happy! Klein’s framework suggests that politics is … political .., a perpetual messy and argumentative process of balancing tensions, dealing with the wants of squabbling factions, attracting and retaining voters who don’t agree on everything at all, and somehow still moving forward. Grace and generosity are crucial to maintaining any viable political coalition. And this is true, whether you begin, as Ezra does, from a position that is closer to the center, or from one that is further to the left. Both face the same practical challenges of forging and maintaining coalitions.

******

Douthat’s advice for the Democrats explicitly channels the “popularist” analysis associated with a particular centrist faction in the Democratic party. Popularism argues that the problem with the Democratic party, very straightforwardly, is the undue influence of its left wing. Douthat’s op-ed is based on a recent report, with lots of public opinion polling, that makes this case at length, and it is remarkably useful because it lays out the basic claims of popularism in a single piece that is short, and easy to access (if you have a NYT subscription or can get someone to share a link).

According to Douthat, Democrats’ problems are “completely obvious” (italics in original): the party “overcommitted to a range of unpopular left-wing positions.” This is “plain to anyone with eyes,” as is the decisive case for moving the party en masse to the right. Those who want to tell other “stories” about what is happening, or to criticize the pollsters are engaging in purposeful “evasion” of uncomfortable truths. Worries about how media changes are reshaping politics, or the electoral system are so many versions of denial. The way to win elections, as always, is to move closer to the preferences of the “median voter.” The only thing that prevents Douthat from claiming the Full Popularism Jackpot, perhaps to his credit, is that he doesn’t cast aspersions on the honesty of the many quantitative political scientists who disagree with this understanding of polls and elections.

I’ll be getting back to my own problems with this simplified understanding of politics below. What is important is that Ezra starts from a different understanding of the Democrats’ problems. And quite explicitly so:

an increasingly bitter debate has taken hold over what the party needs to become to beat back Trumpism. Does it need to be more populist? More moderate? More socialist? Embrace the abundance agenda? Produce more vertical video? The answer is yes, yes to all of it — but to none of it in particular. The Democratic Party does not need to choose to be one thing. It needs to choose to be more things.[my italics]

The problems, on this diagnosis, are less about the issues than the social relationships that can bring together a party with a multitude of views, and make it more attractive to those who have left or haven’t yet committed.

Sometimes people tell me about issues where the Democratic Party departed from them. But they first describe a more fundamental feeling of alienation: The Democratic Party, they came to believe, does not like them. … The structure of American life changed in a way that has made the genuine relationships of politics much harder. Instead of representing many different kinds of people in many different kinds of places, the parties now tilt toward the place in which the elite of both sides spend most of their time and get most of their information. The first party that finds its way out of this trap will be the one able to build a majority in this era.

The professional political classes spend their time online, and their understanding of politics is increasingly shaped by that environment.

The conversations pulsing across these platforms are shaped not by civic values but by whatever proves to keep people scrolling: Nuanced opinions are compressed into viral slogans; attention collects around the loudest and most controversial voices; algorithms love conflict, inspiration, outrage and anger. Everything is always turned up to 11.

Social media has thrown everyone involved at every level of politics in every place into the same algorithmic Thunderdome. It has collapsed distance and profession and time because no matter where we are, we can always be online together. We always know what our most online peers are thinking. They come to set the culture of their respective political classes. And there is nothing that most of us fear as much as being out of step with our peers.

The result is that the Democratic party has become a much more unwelcoming place for people who are out of step with an online consensus that favors a particular kind of online purity. What we want instead is liberality:

It flowered into religious tolerance when that idea was truly radical — when mainstream thought held that the violent persecution of heretics was an act of charity because it would keep others in the church. Liberality proposed a different way of relating across disagreement and division. It built toward liberalism’s great insight, what Edmund Fawcett, in his book “Liberalism: The Life of an Idea,” calls liberalism’s first guiding idea: “Conflict of interests and beliefs was, to the liberal mind, inescapable. If tamed and turned to competition in a stable political order, conflict could nevertheless bear fruit as argument, experiment, and exchange.”

Today, political tolerance is harder for many of us than religious tolerance. Finding ways to turn our disagreements into exchange, into something fruitful rather than something destructive, seems almost fanciful. But there is real political opportunity — dare I say, a real political majority — for the coalition that can do it.

This seems to me to be to be recognizably right, even to many people who are on the left. There is a reason why many people who spend a lot of time on Bluesky and bristle at criticism from outsiders, sometimes joke about how Bluesky can be unbearable. Its problem is not the mob politics of Twitter, but the stifling consensus of the village, where those who don’t adhere to the local consensus are made to feel unwelcome and unworthy.

The fundamental message of Ezra’s piece is not that the Democratic party needs to become a moderate party. It is that it needs to become a party that is welcoming to moderates, as to others who don’t completely share its beliefs, if it is to succeed. Figuring out ways to manage - and even welcome - differences inside the party is not only crucial in itself, but may help it to build stronger and more enduring coalitions among citizens too. They too are more likely to be attracted by a party that is more interested in bringing people in, than in telling them what they ought to do or who they need to be.

The lesson of this is not that managing pluralism is easy. Pretty well by definition, it is anything but. Instead, it’s that building tolerance, and figuring out how to work through the inevitable messiness and conflict, can not only create common purpose internally, but attract others to your cause. The small-l liberal bet is that plurality is not simply an inescapable problem, but an enormous source of political strength. It is realizing that strength involves bridging differences rather than seeking to eradicate them.

*******

There are two obvious risks in this kind of liberal appeal to pluralism. First, such appeals may be prettier seeming in the abstract than they are in reality. They may underestimate the practical political difficulties involved. Second, they may be unconsciously or deliberately loaded with their own ideology: calls for moderation cloaked in the language of pluralism.

It helps, then, that there is a leftwing version of this case, rooted in the pragmatic challenges of movement organizing. If anyone wants to accuse the people of Hammer and Hope of being moderate sellouts, good luck to them! Some while ago, this publication (it’s lively and excellent if you haven’t read it) published a very useful interview of Doran Schrantz by Hahrie Han, on the problem of building practical bridges across groups with different ideologies. Schrantz was a key organizer of the effort to build a multiracial coalition in Minnesota, bringing together different social and religious groups. She describes the challenges of holding this coalition together after the repeal of Roe v. Wade.

For example, in the middle of our election work in 2022, Roe v. Wade was overturned. … How in the hell are we going to hold our base together through this? We have a significant suburban base of primarily white women who are normie to progressive Christians — they are going to want to motivate themselves and others around this issue. But I knew that the Muslim coalition, parts of the rural organizing project, and the Black barbershops and Black congregations would not have the same reaction. So I had to step up as a political leader. I called key people across the organization and built a path to unpack it together.

So … we negotiated. Can we actually have mutual interest in this moment? The group decided that ISAIAH would not make any statement on the fall of Roe v. Wade as an organization. However, we agreed that staff and leaders of Faith in Minnesota, our C4 expression, could organize in their own communities grounded in their own interest. The Faith in Minnesota coalition were essential actors in flipping the Minnesota State Senate to DFL control, which staunchly supports reproductive freedom. The DFL majority enshrined reproductive freedom in Minnesota in a statute. If we had torn the organization apart at that moment because we were not able or willing to do our own internal politics grounded in our shared power, would that have been the best way to achieve our values in the world?

Very possibly, Doran Schrantz and Ezra Klein would have lively disagreements on the particulars if they ever talked together. But as far as I can see, they are as one on the fundamental question of how to build power in a world of real, grounded clashes among your constituents. It involves creating strong relationships of mutual respect between groups that often have sharp differences. Where those divisions are sufficiently deep that they might tear the coalition apart, it is often better to recognize and to allow this disagreement than to demand that everyone follow the party line. That can help facilitate progress - even on divisive issues such as abortion.

******

One final point. All this - and to be clear this whole section is me talking, not Ezra - doesn’t just imply that there is something awry with the left wing of the Democratic elite. It points to problems with the centrist wing too. Each has been captured by its own ideological simplifications. The popularist obsession with the median voter that Douthat says is quite as ideologically stifling in its own way as left-leaning villagism.

If you truly believe that the voter bang at the middle of a one dimensional single-peaked distribution of opinion is the pivot point of politics, you are a centrist by force of axiom. You are less likely to worry about whether voters think there is something fundamentally wrong with politics as a whole. Nor will you be particularly concerned with flaws in the media structures through which voters perceive parties and policies. Most fundamentally, your view of politics will tend towards the apolitical - politics is less about the slow boring of hard boards, than it is about the technocratic adjustments of policies and messages to what the median voter wants, as measured through a plethora of opinion polls and other measures.

Obviously, this is a caricature - few popularists are nearly as technocratic as that* - but it’s a caricature with the same force as the cartoon image of the lefty who cares more about ideological purism than winning elections. It usefully identifies loose intellectual tendencies, and the kinds of justifications that are deployed unconsciously or consciously to support them. If the left tends to overplay the importance of internal unity at the expense of the compromises required by actual electoral and movement politics, centrists tend to big up the awesome moderating power of thermostatic public opinion, and to dismiss the problem of bringing different factions along as mere pandering to the “groups.”

Both tend towards nostalgia for simpler times at the expense of trying to figure out the more complex age that we are in, and how to address it. My biggest objection to Douthat’s article is not that he overestimates the benefits of centrist messaging, though he surely does. It’s that his simplistic - and, quite literally, one dimensional - framework filters out all the other important environmental changes that are happening. Instead, he presents a cartoonish vision of politics as a pendulum which inexorably swings back and forth along one narrow ideological axis as politicians repeatedly mistake the nature of the problem.

But as Lee Drutman - one of the political scientists whom Douthat snipes at - implies, that mistakes the disease for the cure. We live instead in a world of what complexity scientists would describe as high dimensionality, where lots of complex phenomena interact in highly unpredictable ways. One of these high dimensional problems is public opinion itself - which is in part entangled with these bigger difficulties, and in part its own complex space. To do better, parties need to better explore the space of possible solutions. But that is ever more impossible as our available list of political solutions becomes increasingly confined to those that are compatible with a single dimension of partisan contention.

Lee’s solution to this is to open up the space of party competition. Jenna Bednar proposes remaking federalism. There are other proposed paths to opening up diversity, so that we are not stuck desperately trying to apply low dimensional solutions to very high dimensional problems.

This provides another possible experimentalist justification for the kind of liberalism that Ezra proposes. Exactly contra Douthat, the ways out of our predicament are not obvious, and going all-in on rhetoric and simplistic solutions based on opinion polls are likely to make things worse (look at the Labour government in the UK right now to see how the pathologies might play out). Actually existing centrism dampens down some sources of useful variety in discovering ways out. Actually existing left-purism dampens down others.

What I think most is valuable about Ezra’s argument is that it opens up debate rather than closing it. Don’t opt for just one approach. Choose to be more things. Figure out how to build a party that can manage those tensions. This is valuable in itself, and also likely attractive in bringing other people in. Try to figure out which things work and which do not. That is valuable in other ways (which Ezra might or might not be hinting at in his argument, though it flow from Fawcett’s mention of experimentation, but which I am here arguing for explicitly).

Succinctly: some of the great value of liberalism, including its classical, centrist and social democratic variants, is that it acknowledges the need to manage diversity and pluralism internally. Some is that - unlike its major adversary right now - it emphasizes the value of diversity and pluralism in society as well. Some is that - if done right - it respects the worth and value that other people who are currently outside the coalition have, and looks to bring them in. And some is that it can employ this useful variety to experiment, discovering better ways to live together and to figure out how best to mitigate or solve the enormous problems we all face.

* Although this Comrades: True Centrism Has Never Failed, It Has Only Been Failed exhortation perhaps comes close.

[various small edits have been made throughout since first publication - I do this for all my posts, but there were higher numbers than usual of grammatical glitches, slight misphrasings etc]

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There are many possible stories about why American political conservatism is such an intellectual trainwreck. Here’s one. Conservatives used at least nominally to argue that it was important to protect civil society from the depredations of government, and many genuinely believed it. Some still do, but now, the dominant figures in political conservatism want to use government to weaponize and suborn civil society.

Like all simplified fables, this gets a fair amount wrong, both in its understanding of what happened and in what it leaves out. Still, it isn’t a bad way to start understanding some of what is taking place. Yet it begs an important question. What is civil society?

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When I wrote about how civil society could beat Trumpism a couple of weeks ago, I felt a mild sensation of intellectual guilt - I knew I was invoking a complicated set of ideas without properly explaining them. So here’s my attempt to make up for that, and to explain why we ought want to protect civil society too, leaning on the account in Ernest Gellner’s book, Conditions of Liberty.

I suspect that few people younger than 50 have read this book - it’s been out of print for thirty years or so. Gellner wrote it back in the 1990s, when civil society seemed to promise a path forward for the newly freed democracies of Eastern Europe. Now people are rediscovering the idea, not because of future hopes, but because they want to explain what is going wrong as the state escapes its restraints and threatens to crush the people’s liberties.

Gellner’s understanding of civil society is both relevant and a possible bridge between certain parts of the left and right. While he identified loosely with the left, Gellner was profoundly influenced by the kinds of classical liberalism articulated by Adam Ferguson and David Hume. They, in turn, wrote in the aftermath of the English Civil War and Glorious Revolution of the previous century, when Scottish and English society had been torn apart by vicious religious controversies.

Gellner’s account of civil society, like those of his intellectual forebears, begins from the fact of profound disagreement and asks how best to manage it. From Gellner’s perspective, civil society is a marvelous accident, an unanticipated by-product of the seventeenth century stalemate between Calvinist enthusiasts (here and below, the term ‘enthusiast’ refers to Protestants who believe that God lives inside them, and are accordingly uncomfortable with certain kinds of hierarchy) and the English state. Yet this accident has shaped the world that we live in, creating a realm of autonomy in which people are free to live their lives in many different ways, within broad structures that support a reasonable degree of peace and shared order.

The dominant strain in American political conservatism has abandoned any commitments that it once had to this vision of pluralism. Some conservatives favor a shared notion of the common good, which ought be imposed as necessary on society. Others are more straightforwardly interested in domination and plunder. Neither faction has any interest in preserving the autonomy of civil society. Instead of a pluralistic realm to be protected or left alone, they see a “cathedral” of left ideology and argue that universities, non-profits, even multinational corporations are redoubts of the enemy that must be taken by storm. This is dingbat Gramscianism, strained through the turd-encrusted sieve of Curtis Yarvin Thought.

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Debates about civil society are confusing, because they often use the term to refer to very different things. Crudely speaking, the most important distinction is between a Marxist approach civil society, which mostly comes from Gramsci, and a liberal tradition, which can be identified with Ferguson, Hume and others. There is relatively little overlap between them (even if the great liberal thinker Norberto Bobbio, was in many respects sympathetic to Gramsci).

I’ll summarize the first approach briefly; it’s not what I want to focus on here, but, as already mentioned, it’s indirectly relevant to the ideological changes in conservatism. Marx treated ‘civil society’ as synonymous with the deep ‘base’ of economic relations that drove history. Gramsci argued instead that civil society was the superstructural realm of private organizations, educational and cultural institutions and the like. But, unlike other Marxists who dismissed superstructure, he saw it as enormously politically important. This realm of apparently independent and semi-independent institutions was a system of hegemony, providing the ideological underpinning of the prevailing order, while state coercion provided more directly brutal means of keeping existing power hierarchies entrenched.

From this perspective, both civil society and state may reinforce an existing economic and social order (albeit in a more subtle and complex relationship than in cruder Marxist formulations, such as Althusser’s Ideological State Apparatus and Repressive State Apparatus framework). However, civil society also provides openings for change. In Gramsci’s understanding, Marxists could move towards power by first gaining hegemony, forming what Bobbio summarizes as “a collective will, capable of creating a new state apparatus and of transforming society, [as well as] elaborating and propagating a new conception of the world.” Reshaping civil society, though it would almost certainly require many years of trench warfare, was a crucial step towards remaking politics along better lines. From this perspective, then, civil society was a battlefield, which the dominant forces sought to hold in their struggle to retain ideological hegemony, while challengers looked to seize it away.

The second, classical liberal account of civil society provides a very different understanding. It depicts civil society less as battlements or battlefield than as a means of sublimating the ideological energies and divisions that might otherwise lead to civil war. This helps explain why classical liberals became interested in the concept. Again, Hume and Ferguson were born in living memory of a sequence of war and revolution that had torn their country apart, as Presbyterians, Dissenters and churchmen fought bitterly over who was to hold power, and under what conditions. Doctrinal disagreements over whether altars should be located in the center of the church helped precipitate brutal battles, in which thousands died. Jonathan Swift’s Lilliputians, who warred with each other for a century over which end of the egg ought be broken before eating, were a scathing parody of these religious vexations. But there were practical questions at stake in these fights too; most obviously, how much power should the Crown possess?

Ferguson and Hume wanted, then, to understand the conditions under which people who disagree ferociously can live in peace. How did the sectarian conditions that spurred civil war lead to a peace that became a kind of foundation-stone for liberty? That is the question that Gellner then takes up, asking as well how civil society can constrain the state.

As Jonathan Healey warns in his excellent history of the English Civil War and Glorious Revolution, The Blazing World, we shouldn’t make over-easy extrapolations from a very different period of history. Still, Gellner suggests that the current conditions of liberty are descended from those conditions that pre-occupied the classical liberals.

His biggest question is why these conditions should have come into being at all. For most of human history, we have either dwelled beneath despots who exercise conventional kinds of tyranny, or subsisted within the “tyranny of cousins”; societies in which one’s identity is cloyingly defined by clan based relations. Both profoundly constrain the freedoms that Western small-l liberals have come to take for granted. Now, instead, we live in a world where we can define our lives, within certain broad contours, as we like. How on earth did this come about?

Gellner’s explanation builds on Hume’s dictum that “superstition is an enemy to civil liberty, and enthusiasm a friend to it.” Hume and Gellner want to know why the wild-eyed extremist Protestants who fought a civil war to establish the rule of the Saints on earth eventually became advocates of religious toleration and freedom.

Hume emphasizes the internal logic of Protestantism; Gellner partly agrees but suggests that the politics count too. It is likely important that the enthusiasts were defeated, but not crushed. They had incentive to help build a civil peace within which they could pursue their own religious goals. In Gellner’s description:

the coming of Civil Society, a society liberal in the modern sense rather than the ancient non-liberal cousinly and ritualized plural and balanced society, presupposed a political stalemate between practitioners of superstition and the zealots of enthusiasm, such as in fact did occur in seventeenth-century England, leading to a compromise.

This was, as Adam Ferguson recognized soon after it began to shape itself, in many ways an unnatural development. It hadn’t ever happened before. But once this limited form of pluralism established itself it became, to some extent and for some period of time, self-perpetuating and self expanding. An initially limited form of civil society, which tolerated (some) different forms of religious practice, self-ramified to broaden religious freedoms and then foster civic freedoms too. This, in turn, helped support continual and indeed exponential economic growth. States which had a strong civil society seemed to do better economically than those states that “throttled” liberty, providing them with advantages in inter-state competition.

The result was not just that religious and doctrinal disagreements became matters of private conscience and peaceful social activity. It was the creation of a new kind of society in which coercive force was centralized in the state, but was counterbalanced by economic and social pluralism. State power only went so far. People could, within reasonably broad parameters, choose who they wanted to be, and what they wanted to do.

The distinguishing feature of civil society (as opposed to more traditional forms of social organization) was its modularity:

How is Civil Society possible at all? … The question may be spelled out more fully: how is it possible to have atomization, individualism, without a political emasculation of the atomized man (as in the world of Ibn Khaldun), and to have politically countervailing associations without these being stifling (as in the world of Fustel de Coulanges)?

Miraculously, Civil Society does achieve both these aims. It is defined by such an achievement. Modularity of man is an illuminating way of referring to this condition. … Modular man is capable of combining into effective associations and institutions, without these being total, many-stranded, underwritten by ritual and made stable through being linked to a whole inside set of relationships, all of these being tied in with each other and so immobilized. He can combine into specific-purpose, ad hoc, limited association, without binding himself by some blood ritual. He can leave an association when he comes to disagree with its policy, without being open to an accusation of treason. A market society operates not only with changing prices, but also with changing alignments and opinions: there is neither a just price nor a righteous categorization of men,, everything can and should change, without in any way violating the moral order. …

It is this which makes Civil Society: the forging of links which are effective even though they are flexible, specific, instrumental.

Stripped of the gender language (Gellner was, very definitely, One Of Those Guys)*, this is a very useful explanation of the foundations of civil society and its value. Civil society is that situation in which we are free to form our own associations, independent of the power of state and clan. As he goes on to argue:

Civil Society is a cluster of institutions and associations strong enough to prevent tyranny, but which are, none the less, entered and left freely, rather than imposed by birth or sustained by awesome ritual. You can join (say) the Labour Party without slaughtering a sheep, in fact you would hardly be allowed to do such a thing, and you can leave it without incurring the death penalty for apostasy.

From this perspective, civil society is a crucial underpinning of the kinds of social order that welds together democracy and markets. According to classical liberal influenced political economists such as the late Doug North, John Joseph Wallis and Barry Weingast, it is the most important distinguishing characteristic between the “closed orders” of ancient and modern authoritarian states, and the “open access orders” that preserve liberalism. According to more left-of-center political economists such as Daron Acemoglu and James Robinson, a strong civil society is a crucial protection against tyranny. Both of these strains of thought lay heavy emphasis on the essential role that democracy plays in supporting to free societies. Open civil society and democratic institutions are inseparable from each other, although Gellner liked to insist that democracy emerged from civil society rather than vice versa.

Equally, Gellner argues that civil society is not a natural equilibrium. It came about through chance conditions - very possibly the conditions that Hume and Ferguson identified, perhaps others. It is in perpetual tension with nationalism, Gellner’s other great preoccupation (and the one he is most famous for writing on: his books on nationalism are still in print). A moderate nationalism can stabilize civil society; a radical nationalism will corrode it or attack it directly. Back in the early 1990s, Gellner was preoccupied with the conditions under which Central and Eastern Europe might rebuild civil society after Communism (he spent his last years teaching at the Central European University in Hungary). He feared that nationalism might again devour its sibling in the womb. As he remarked of the last days of the Hapsburg Empire:

the nationalists were hostile not merely to rival cultures, but also, and perhaps with special venom, to bloodless cosmopolitanism, probably in part because they perceived in it an ally of political centralism, and felt it to be a support for the old trans-national empires against neo-ethnic irridentism. They felt special loathing for those they considered to be the principal carriers of such cosmopolitanism. (They were right in the end, the liberals committed to an open market in goods, in a sense men and ideas, were the last supporters of centralism, remaining faithful to it even when the old baroque absolutist partisans of the ancien regime had themselves given up the struggle).

Gellner worried about how this drama would end, and he was right to worry. Most prominently, Viktor Orban, whose early career was fostered by the Open Society Foundation, turned on it, and civic liberalism more generally, condemning pluralism, embracing an extreme nationalism and doing everything he could to strangle civil society in Hungary. Media was tamed or lamed. Universities were transformed into ideological forcing houses, controlled by foundation structures that were stacked with Orban’s allies, and non-profit organizations were regularly hounded or driven out of existence. The Central European University where Gellner once worked, was forced to leave Budapest and Hungary, after having left Prague before.

Orban is now in real political trouble, but only after many years where he sought to reshape civil society in his own image. If the opposition is elected without sufficient seats and support to change the constitution, it may have a very hard time reversing these changes.

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From Gellner’s perspective, civil society is an essential underpinning of our current way of life. The worry is that it is not universally essential. Other ways of organizing society, many of which would strike us as wicked or miserable, are can be maintained without it. Indeed, maintaining civil society may be a continual challenge. Civil society requires the management of nationalism (some sense of national identity is good, to mitigate more immediate sources of partiality, but not too much). So too for the market system: “a liberation of the market from political control would be catastrophic.” Civil society may be burdensome to the individual: in many respects, living in a modular world is far more demanding than living in a society where you know exactly what role you are supposed to play. Yet its benefits, in the eyes of those who have adopted its norms at least, are enormous.

It is striking that the main tendency of American conservatives, who often used favor the independence of civil society from government, have moved decisively away from it. This is in part thanks to the influence of integralist political theorists, who view civil society’s pluralism with disgust and aversion. Imposing the common good means telling commoners what is good for them rather than letting them figure this out for themselves. But the more politically important faction is composed of those who’ve embraced a kind of trans-reversed Gramscianism in pursuit of straightforward political domination.

There’s always been a right wing fascination with Gramscianism, which included the late Rush Limbaugh, or at least his regular ghost-writer. Reactionary ideologist Curtis Yarvin has explicitly disclaimed Gramsci, but his notion of the “Cathedral” - a decentered but extraordinarily powerful consensus of academia, journalism and political elites - is a crude and debased version of Gramsci’s arguments about hegemony. Yarvin’s influence on the Silicon Valley right has been immense. More superficially presentable conservatives such as Chris Rufo disagree with his arguments about the Cathedral, but only to the extent that they think Yarvin is too pessimistic. According to Rufo, Florida’s Orban, Rick DeSantis, was successfully storming academia by taking over New College, and using it as a spearhead for a broader transformation of the academy.

Perhaps not so much,** but the Trump administration is now trying out this strategy at scale. It’s not just attacking universities, but non profit organizations (including the Open Society Foundation - that a foundation founded to defend Karl Popper’s principles is constantly attacked by conservatives says quite a lot about where we are), law firms and broadcasters. The administration wants either to destroy them or to force them to cave to its preferred ideology, replacing a plural system which is open to many different voices with a closed one, in which nominally independent organizations are required to repeat the government line.

The standard justification is that that the Trump administration is merely correcting for the excesses of the left wing. That obviously isn’t true: the demands for control are far more sweeping in effect and intent than would be necessary to address the problems they purport to solve. In its crudest form, these are efforts to impose control. Gellner again:

What distinguishes Civil Society (using the term to describe the entire society), or a society containing Civil Society (in the narrower sense), from others is that it is not clear who is Boss. Civil Society can check and oppose the state. It is not supine before it.

That is exactly why conservatives who are committed to the One Boss principle find Civil Society unbearable. And this has implications for all those who buy into the idea of civil society, whether they are left-leaning, right-leaning or centrist. Entirely apart from the Trump administration’s true intentions, you absolutely do not want a political system in which the government is able to remake civil society in its likeness. The value of civil society stems precisely from its capacity to (a) restrain government from tyrannical behavior, and (b) create a realm of free engagement, where people can live their lives, and freely create and dissolve bonds among each other.

There is plenty that is missing from the classical liberal account of civil society that Gellner lays out. It doesn’t capture many of the power dynamics that actually existing civil society entails. Civil society’s actual degree of pluralism varies, and is the subject both of legitimate debate and actual political struggle (something that both intelligent left- and right-Gramscian approaches capture better than classical liberal accounts).

Still, it does an excellent job in explaining why it is a problem when the government tries to capture civil society. If we lived in a world where the winning faction of conservatives recognized the value of civil society, we would be a lot better off than we are. There is also excellent reason to think that the left should be more appreciative of civil society too, and less prone to fantasies that everyone would change their politics if only this or that intellectual institution was controlled by the right people with the right way of thinking.

Liberal accounts of civil society push us to recognize the benefits of genuine pluralism, however painful and messy it may be, and however difficult to maintain in practice. Gellner’s particular version also has the particular benefit of emphasizing how contingent the development of civil society was, and how chancy its survival may be without relentless hard work.

Other societies may develop the economic benefits that helped civil society take off.

Whether we like it or not, the deadly angel who spells death to economic inefficiency is not always at the service of liberty. He had once rendered liberty some service, but does not seem permanently at her command. This may sadden those of us who are liberals and were pleased at being given such a potent ally - but facts had better be faced.

There will always be tensions in the relationship between nationalism and liberalism, which endanger the pluralism of civil society. Strong forms of national identity and strongman government based on fostering us-them divisions go hand-in-hand with each other. If economic growth stutters or fails, then social mobility is likely to become more problematic, and abusive hierarchy - the default condition of human society - may return.

That, then, is what civil society is (under one useful definition) and why we ought care about it.

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* There are multiple other possible objections. Gellner is very definitely parti pris. His account of Marxism is ungenerous, of Muslim society controversial, and of those whom he did not like or agree with unkind, if sometimes very funny. Shaky opinions are stated emphatically, and even as obvious and unchallengeable truths. I don’t recommend that people gulp down his arguments hook and line. But there is a great deal in his writing that is sharp, and a quite considerable amount that I believe be profound. Furthermore, Gellner is one of the few social scientists who knew how to write, providing the reader with a flow of examples of how to explain abstruse ideas and phenomena with lucidity and wit.

** In practical terms, the Florban Strategy has turned out to be a disaster.

I’m quoted this morning in a great New York Times piece by Ana Swanson and Meaghan Tobin, which explains how China is using rare earths to do to other countries what the US has been doing for years.

“The U.S. now has to face up to the fact it has an adversary which can threaten substantial parts of the U.S. economy,” said Henry Farrell, a political scientist at the Johns Hopkins School of Advanced International Studies. The United States and China are now very clearly “in a much more delicate stage of mutual interdependence,” he added.

“China has really begun to figure out how to take a leaf from the U.S. playbook and in a certain sense play that game better than the U.S. is currently playing it,” Mr. Farrell said.

But read the whole thing. It’s the best detailed account of what is happening between China and the US on semiconductors right now that I’ve seen to date, and draws on the knowledge of lots of people beside myself. What follows is not narrative journalism, but an explainer of the background to the story, as I at least interpret it, in the form of six broad theses.

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First, and most simply: China seems to be moving from one mode of exercising its power to another. China has exercised effective control over rare earths and other critical minerals for years, but when it has used or threaten to use it, it has done so implicitly and indirectly. Specifically, it has used informal restrictions: mysterious blockages, strange frictions and other means to hamper other countries’ access to China’s internal markets, and Japan’s access to rare earths in 2010. This led some observers even to doubt that China had introduced systematic restrictions on exports.

Now, there isn’t any doubt at all: China is explicitly asserting power over the entire semiconductor supply chain on the basis that semiconductors use China-processed rare earths. It has created an entire regulatory infrastructure to underpin this claim, and has effectively banned the export of rare earth processing equipment abroad, to try to maintain its chokepoint as long as possible.

Second, in doing this, China is very deliberately copying the US. The US Trade Representative, Jamieson Greer, is shocked, shocked, that any country could engage in this kind of “global supply-chain power grab”:

He said: “While China has taken a number of retaliatory trade actions against the United States, Europe, Canada, Australia and others in recent years, this move is not proportional retaliation. It is an exercise in economic coercion.

But China is in fact closely copying what the U.S. has been doing for years. See, for example, this super-useful chart by Gerard DiPippo.

As Abe Newman and I explain in our book, Underground Empire (if you want to support this free Substack, please go buy), officials in the first Trump administration used traditional export controls and a supercharged version of an obscure regulation, the “Foreign Direct Product Rule,” to assert jurisdiction over chips that had been manufactured outside the US. Chris Miller’s book, Chip War has a quote from a senior official suggesting that Abe’s and my ideas about “weaponized independence” played some role in the Trump administration’s thinking. The Foreign Direct Product Rule was first used to attack the Chinese telecommunications manufacturer, Huawei, and then deployed on a much wider scale by the Biden administration against Russia, and then China’s access to advanced AI chips.

The U.S. doesn’t like to publicly acknowledge that America too does economic coercion (one official even become indignant in private conversation with Abe and myself when we made this point), but it is clear that China is applying its own version of the Foreign Direct Product Rule. The consequences may be sweeping. As Swanson and Tobin explain:

The rules, which would go into effect later this year, shocked foreign governments and businesses, who would theoretically need to seek licenses from Beijing to trade in products ranging from cars to computer chips, even outside of Chinese borders. The system would also deny shipments to any U.S. and European defense or weapons manufacturers, who are still highly dependent on Chinese minerals.

Third, the bureaucracy to do this isn’t going away. U.S. Treasury Secretary Scott Bessent publicly blames a rogue Chinese official for going beyond his mandate.

Shifting from trade policy to the personal, Bessent on Wednesday described China’s chief trade negotiator Li Chenggang as “slightly unhinged” and “disrespectful”, alleging that he had threatened to “unleash chaos on the global system” if the U.S. went ahead with the port fees increases, and that he had invited himself to Washington for talks in August. … “Perhaps the vice minister who showed up here with very incendiary language on August 28 has gone rogue,” Bessent said.

I’m guessing (maybe wrongly) that this is a crude effort to provide Xi with a path towards de-escalation, by blaming an underling. But it appears to me to be unlikely that China’s rules will be withdrawn, and even if they are withdrawn, the bureaucratic structures that make them possible them will remain. Equally, China’s efforts to suggest that this is a purely technocratic exercise in protecting the environment etc are transparently mendacious. It is an explicit power play, backed up by the deliberate accretion of new bureaucratic authorities over the last few years.

Fourth (and this is where my comments to Swanson and Tobin came from), China appears to be better placed than the U.S. to use its powers of economic coercion intelligently in pursuit of its own long term interests. The Trump administration has junked the systems that allow the U.S. government to calibrate economic coercion and to anticipate possible downsides. The National Security Council - which had come to play a crucial role in coordinating and setting policy under the Biden administration - has lost more than half of its personnel, on the theory that it is the ultimate representative of the “Deep State.” Its key China people have been Loomered. Careful bureaucratic process has been replaced by the whimsical decision making of Trump himself, as in his infamous meeting with Jensen Huang. Bessent’s criticisms of officials “gone rogue” might better have been aimed at his own boss.

All this means that the US is likely to be highly unpredictable in its responses to China’s assertion of power. It might seek to double down on ferocious threats, or fold, depending on Trump’s mood, and the person he last spoke to. Who knows? China, in contrast, is much better placed than the US right now to think through the long term consequences of its actions.

Fifth - this doesn’t mean that China will necessarily get things right! Even when the US had proper bureaucratic structures, it regularly made big mistakes, and often didn’t have the information or capacities to think through the second and third order consequences of its actions. The same will be true of China, which is only beginning to figure out what it can or can’t do, and which moreover faces a much more complex set of problems than the U.S. did initially. When the U.S began to develop its muscles of economic coercion, no-one else was really capable of challenging it. China, in contrast, is challenging a relatively well entrenched competitor that already has built deep connections to, and considerable knowledge of, technology supply chains, and has many possible means of retaliation against Chinese actions.

That helps explain both why China is demanding information in return for licensing rare earth exports, and why companies and countries are resisting. Swanson and Tobin:

Companies and governments in the United States, Europe, Japan, India, South Korea and elsewhere are also concerned about the extensive corporate information that the Chinese government is requesting in the licensing process. Foreseeing “a lot of resistance” to providing that information, [Chris] Miller said it could accelerate efforts to build non-Chinese supply chains for rare earths. The argument is similar to one that critics of U.S. technology controls have long made, that they could push the world to adopt non-U.S. chip technology.

Again, this replicates what the US has done in the past. From Abe’s and my book:

On March 15, 2021, the Department of Commerce’s Bureau of Industry and Security (BIS) invited comments from the semiconductor industry. …Then, the Biden administration announced that it was asking businesses like TSMC to “voluntarily share information about inventories, demand, and delivery dynamics” to help the administration “understand and quantify where bottlenecks may exist.”

There was a big stick behind the soft-spoken request. As Biden’s commerce secretary, Gina Raimondo, explained, “What I told [semiconductor firms] is, ‘I don’t want to have to do anything compulsory but if they don’t comply, then they’ll leave me no choice.” If firms like TSMC didn’t provide the data, the Biden administration would invoke its powers under the Defense Production Act. Nor was the administration just demanding that TSMC provide information on its own activities. The data it wanted would allow it to peer into the intimate details of TSMC’s customers’ business.

But there is now a much higher likelihood of international conflict over whether companies should provide this kind of information. Semiconductor manufacturers and other customers for rare earths are likely to find themselves in an extremely difficult position, caught between warring demands.

And this carries to the sixth point. We are in the world that U.S. economic coercion has helped build, but it is not one that is good for the long term interests of the United States. As Abe and I said in 2019, in the conclusion to the article that apparently inspired at least one Trump official:

The world has entered into a new stage of network politics, in which other states have begun to respond to [U.S.] efforts. When interdependence is used by privileged states for strategic ends, other states are likely to start considering economic networks in strategic terms too. Targeted states—or states that fear they will be targeted—may attempt to isolate themselves from networks, look to turn network effects back on their more powerful adversaries, and even, under some circumstances, reshape networks so as to minimize their vulnerabilities or increase the vulnerabilities of others. Hence, the more that privileged states look to take advantage of their privilege, the more that other states and nonstate actors will take action that might potentially weaken or even undermine the interdependent features of the preexisting system.

Miller’s official either didn’t read this, or didn’t think it was very important (though Miller himself clearly got the implications of our claim).

We’re now living in a future where that prediction at least has come true. China has indeed reshaped networks so as to maximize the vulnerabilities of the US, creating a much more dangerous and unpredictable set of dynamics. The U.S. is currently very poorly positioned to manage these complex problems. The Trump administration is more concerned with attacking perceived internal enemies than the outside world, and has stripped the bureaucracies that would allow it to begin to think straight about the problem. China has better capacities to think in the long term, at least in principle - but it is also coming into the game very late, with little experience, and subject to its own misunderstandings. The risks of unanticipated and mutually compounding fuck-ups are very, very high.

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[Baptism by William B. Chappel, courtesy of the Met]

A few days ago, the MacArthur Foundation announced this year’s list of fellows. My colleague and friend, Hahrie Han, was among the winners. This is wonderful news for many reasons, one of which is that it should draw more attention to her ideas. Specifically, people should read her most recent book, Undivided: The Quest for Racial Solidarity in an American Church.

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Undivided begins with a puzzle. Cincinnati, Ohio passed a ballot initiative with a supermajority in 2016, raising taxes to provide universal pre-school education with particular benefits targeted at Black communities. How could something like this happen in a racially divided city in the throes of Trumpism? The answers that Hahrie finds are contingent and messy, but also valuable for the left right now. In particular, she implicitly suggests that there is a lot that the left can learn from the evangelical movement, as well as currents within it that it ought directly engage with. Hahrie’s intellectual background leads her to answer different questions than most people who think about religion. She looks at the evangelical movement not just as religion, or way of living, but a way of organizing. There is a lot that non-evangelicals can learn from how the evangelical movement brings these together.

NB, that the below doesn’t even try to capture the broader narrative of Hahrie’s book, which is narrative non-fiction, not applied social science. It’s my own extrapolation, drawing on one particular aspect of her argument. To really get what Hahrie is saying, you should buy the book.

******

Hahrie’s scholarship is all about civic action. Her first book, Moved to Action: Motivation, Participation, and Inequality in American Politics, looked at the circumstances under which people with very few resources, those who many political scientists would predict have no real opportunity to mobilize, can sometimes come together to pursue their collective interests. What she found was that people, even in the grimmest circumstances, could build from their understanding of their common circumstances to take action. As Elena, a farmworker whom she interviewed for the book, said, her activism came from “perceived injustice in her life and the life of people around her.” But it certainly helped when there some organizational frame (a farmer’s cooperative, a political party) that people like Helena could build around.

This led Hahrie to further work on why some organizations can change the world around them, while others are less successful. Her second book, How Organizations Develop Activists: Civic Associations and Leadership in the 21st Century stressed the difference between "transactional mobilizing,” and “transformational organizing.” Lots of organizations focus on lowering the transaction costs of doing things - pressing a button to send an email expressing outrage to a politician. However, it is the ones that get people involved in deeper ways and build relationships that can forge enduring communities. Organizations do this less often than they might, because building such relationships is messy, difficult and hard.

Her third book (co-authored with Elizabeth McKenna) on the role of volunteers in Obama’s 2012 campaign, not only shaped Democratic organizing, but received the notable backhanded compliment of being assigned as required reading for Republican National Committee organizers in 2016 and 2020. Republican organizers reportedly not only had to read it, but to take an exam on what it said.

All this means that Hahrie picks up on different aspects of evangelicism than most outside observers. While Undivided is woven together by the stories of the individuals who she met and talked to, it’s also a story about how organizations win people over and provide them with opportunities to do things.

For example, Hahrie discusses how evangelicals have changed the ways in which they look to convert people to their churches. Once, Protestant missionaries sought to woo individuals away from non-Christian communities by providing them not only with a religious message, but health care, education and other services. Then they started looking at the data:

In 1955, … Donald McGavran challenged the iconic mission stations in a book called The Bridges of God. McGavran was a third-generation missionary who brought a data-based approach to asking why some missions were so much better than others at gaining adherents. After analyzing data on many missions, McGavran concluded that the traditional mission station approach was the wrong way to promote evangelicalism. Instead of isolating potential converts from their communities, McGavran argued, missions should integrate into the communities they sought to convert, drawing on preexisting social networks.

Evangelicals in the US began to use sophisticated marketing techniques at more or less the same time, converting drive-by movie theaters and strip malls and other places in the middle of people’s shopping and lives into churches, and combining religious services with lessons learned from the entertainment industry. They wanted to bring in “seekers” - people who wanted meaning in their life but were not already committed to God. Their techniques to do this sometimes seemed cheesy but they often worked, fostering enormous new churches that could take advantage of economies of scale, just as businesses did. A lot of the initial energy of Crossroads, the church that Hahrie looks at, seems to have come from business people at Procter and Gamble.

Outsiders tend to overemphasize the consumer-focused cheesiness while paying less attention to the intricate honeycomb structures through which big churches build and maintain community, most notably small groups organized around particular interests.

These groups were the building blocks of evangelical megachurches, creating venues within giant congregations for people to get to know one another and pursue a common agenda. ... In 2020, the median megachurch reported that 45 percent of its members were involved in some kind of small group. In a church like Crossroads, which boasted about 35,000 members in 2020, that would be about 15,750 people organized into small groups if each person belonged to only one. They generally ranged from six to ten people, meaning that Crossroads could have had anywhere from 1,575 to 2,625 small groups meeting regularly. Small groups created honeycombs of intimacy, connection, and loyalty in those churches. As French philosopher Alexis de Tocqueville wrote, “In democratic countries knowledge of how to combine is the mother of all other forms of knowledge.” Because people do not naturally possess the skills and inclinations for working with one another, they need venues for learning. Small groups taught people through concrete experience how to act together.

Small groups provide a kind of social glue then, allowing people with different interests or problems to come together, and perhaps support each other. They explain why evangelicism has been so attractive to the conservative movement, as a kind of social substrate to provide it with energy and volunteers. But they also help explain why people are attracted to these churches in the first place. Megachurches provide a community where different people with different interests and problems can find others like them, provided those interests are compatible with the overall mission of the church. That broader mission isn’t set in stone, and is sometimes contested. Arguments over what the mission of Crossroads and the evangelical movement are what drive the main story of Undivided. Should the evangelical mission include a commitment to racial justice? And if so, how deep should that commitment go?

******

That’s the background to the puzzle that Hahrie’s book begins with. Volunteers from Crossroads contributed enormously to winning the ballot initiative. A grouping within the church had begun to engage with questions of racial justice, transforming many church members’ understanding of what their faith entailed. Church leaders created a curriculum that members could work through in small multiracial groups.

This was unusual within evangelicism. As Hahrie notes, polling suggests that White Christians are more likely than any other demographic group to hold racist views, and evangelical churches have regularly struggled with racial integration. Even churches that nominally opposed racism were regularly unwilling to tackle the deeper issues of systemic injustice associated with it. But even if the story of Undivided was unusual, it was not completely unprecedented. There is a long, messy history of argument over race within evangelicism, especially as previously nearly completely White denominations looked to attract Black members. Some churches, such as Crossroads, provided opportunities for pastors and church members to push back against racism.

The multiweek racial justice curriculum that Hahrie describes was more demanding than most such programs. It didn’t ask participants to run through a list of DEI shibboleths (the book is scathing on the efficacy of corporate DEI trainings, because the social science says they are more or less useless), but to actively engage with each other on potentially divisive racial questions. The stories that Hahrie recounts suggest that this was difficult, painful and highly imperfect. People didn’t understand each other at the beginning, and many came away unhappy and dissatisfied. It’s very hard to talk about awkward questions face to face. But talking face to face also makes it harder to be brutal or cruel to those who say embarrassing or difficult things (here, Hahrie draws a semi-explicit contrast with social media’s tendencies to abstracted cruelty and pile-ons). And doing so week after week with the same small group of people made it easier for people to take risks, to build connections, and to figure out how to forgive each other.

There is a clear parallel between this process and the experience of the civil society organizations that Hahrie studied earlier in her career. Again, building deep connections is messy, difficult and hard, but it allows people to accomplish things together. The program provided many of its participants with a “sense of community and … tools to speak out about injustice in their own lives.” That, in turn, inspired hundreds of church members to volunteer to pass a tax levy that was aimed at addressing structural racial injustices in education.

Inspiration isn’t the end of the game, and it isn’t magical. Hahrie’s story is not a tale of people finding common cause, and converting a megachurch into a vehicle for social justice, so that everyone lives happily ever after. As this campaign was coming together, Black people were being killed by police, in Ohio and elsewhere. The push to address racial injustice created tensions within the church. Not everyone was happy to go along at all. A police officer involved in one of the more notorious incidents quietly attended services at Crossroads. The people who carry the weight of Hahrie’s story had to deal with difficulties, and personal conflicts with families and loved ones that sometimes ended in bitter ways. The end result of all their efforts was an ambiguous victory at best; perhaps not a victory at all. One of the implied lessons is that we often do not know what was victory and what was defeat until decades after.

Undivided most emphatically does not present a simple linear progress towards justice. Instead, like all good non fiction, it tries to capture the complexities of its subject matter, rather than to smooth them away.

******

Still, I took away some lessons from it (these are my own notions after having read the book; they may or may not reflect Hahrie’s guiding intuitions). The first and simplest lesson is that evangelicism - even in White dominated churches - is not a monolith. Like all human institutions, it contains variety and disagreement, and evangelicism perhaps even more so than most, since it emphasizes the personal relationship to God, and accommodates new churches being founded around particular interpretations of that relationship. One of the most surprising aspects of evangelicism to me - as someone who grew up Catholic - was how individuals moved backwards or forwards across different churches to find one that fit their personal approach and values.

Given all of this, it is not as surprising as it might initially seem that a big evangelical church could commit for a while to a campaign centered on racial justice. Hahrie quotes a sociologist who estimates that roughly a third of evangelicals are “other” evangelicals who accept the theological tenets of evangelicism but implicitly or explicitly reject the particular brand of right wing politics that often go along with them.

But there are more subtle lessons too. One of the reasons that evangelical churches have succeeded on their own terms is that they don’t simply welcome converts, but build their organizational structures and practice around identifying seekers and bringing them into the fold. That can become a political style too. The late Charlie Kirk created a political organization that was notable for ruthlessly targeting perceived enemies. He was not interested in debate in the ways that liberals, who are open to changing their own minds, at least in principle, are. However, Kirk used debate not simply to demolish opponents, but to try to win converts to the cause, exploring what swayable people believed and wanted, and trying to blaze a path that might lead them towards his own political faith. That last is something that the left could learn from: treating people who don’t agree as seekers, and trying to figure out how to bring them on board.

So too, people on the left should note how evangelical churches provide a honeycomb of variegated spaces for people to find community with others. The breakdown of other forms of organized social life have created a vacuum of meaning in American society. There are many seekers, who are not just looking for God, but for community connections. A large, rather loose structure intended to provide general coherence, form and identity, combined with a multitude of opportunities to construct smaller cross-cutting groups can be a singularly attractive proposition.

Furthermore, as should already be clear, evangelical churches like Crossroads are more apt to transformational organizing than the transactional mobilizing that more traditional political organizations prioritize on both the left and right. People who get deeply involved in church life are transformed by their relationships. They are also likely to be able to apply the organizational lessons they have acquired in other contexts too. Again, large swathes of American liberalism and the left are structurally bad at offering those kinds of opportunities, because they have doubled down on shallower transactional forms of organizing.

But the most fundamental lesson that I took from Hahrie’s book is that creating justice is extraordinarily hard and demanding. It requires hard work, courage and grace. We live in a technocratic society, which often substitutes ritual for difficult labor. We put up signs in our yards as signals of welcome, and sometimes imagine that this is sufficient on its own. We work in organizations that require diversity training, through online videos and multiple choice questions that substitute legalistic box checking for sustained thought and practice. We yell about how bad things are on social media, but don’t always do much to try to make things better.

The reason is not that we are bad people, but that it is really hard to try to change things, rather than going through the motions of saying they ought be changed. There aren’t clear and obvious paths. Even when people of good will agree that something ought be done, they may ferociously disagree over how to do it. We don’t know how to succeed, or if we will succeed. And getting politically involved seems frightening and contentious.

Making it less hard and frightening involves forgiveness and acceptance. Hard work, courage and grace: of these three, grace is often the hardest. It’s what Francis Spufford, an Anglican, is talking about when he describes acknowledging the Human Propensity to Fuck Things Up as a starting point for living a Christian life. We are all wretches, undeserving of what we have, but from that can come both the hope that we can do better, and forgiveness of those who, like us ourselves, are entangled in their faults.

Again, this is something worth learning. Hahrie’s book describes how the notion of grace can be weaponized to excuse the gross abuse of power. But she also explains how it may be the beginning point too of our struggles against injustice, as imperfect human beings, trying to make things a little better.

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[University by Thomas Rowland, courtesy of the Met]

I’ve a piece in the New York Times today that connects the Trump administration’s proposed University Compact, which tries to leverage federal funding to get universities to comply with ideological oversight with my previous writing on collective action. Putting the two together suggests that we ought to see the compact as a sign of weakness rather than strength. If you want to see the most straightforward version of the argument, with proper editing and all, read the piece itself. Here, I’m just going to explain the underlying assumptions and complications.

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The underlying idea of the piece is that we ought to understand the Trump administration’s push towards a kind of electoral authoritarianism in which elections happen but Republicans somehow always win, as as a massive collective action game If the key actors in civil society see themselves as trapped in a "prisoner’s dilemma,”* the Trump administration will probably win. If, instead, they see themselves as playing a “coordination game,” the Trump administration will probably lose. Like all very simple frameworks, this leaves out a whole lot of valuable detail, but I think it still captures some pretty important dynamics.

The organizing idea (adapted from Russell Hardin, David Hume, Margaret Levi and others) is this. Authoritarian rule depends on shared expectations that the ruler is too strong for anyone to challenge. Even the most terrifying dictator relies on others - army and police - to do the enforcement (and dictators have to worry about what might happen to them if their security services become unhappy). Even the most efficient security state is far too small to prevail if all the citizens rise up against it. Hence, authoritarians want to ensure that everyone believes that Resistance is Useless. Even criticism of the rulers may be tolerated, as long as it reinforces the sense that they are going to prevail. An old Alasdair Gray short story explains this logic by conveying the sardonic enthusiasm of an imperial censor for a polemic against his boss.

Consider the weight this poem gives to our immortal emperor! He is not described or analysed, he is presented as a final, competent, all-embracing force, as unarguable as the weather, as inevitable as death. This is how all governments should appear to people who are not in them.

But aspiring rulers who merely want to be as unarguable as the weather face a big problem, especially if they are trying to consolidate authority in a democratic system. How do they reshape everyone’s expectations, so that everyone complies because they expect everyone else to comply too? Most people probably aren’t going to want that, and the rulers have yet to establish the facts on the ground that they want.

Stated a little more abstractly, what incipient authoritarians want to do is to turn a coordination game where everyone refuses to comply with the regime because everyone else refuses to comply, into a prisoner’s dilemma, where everyone expects everyone else to defect and side with the regime.

A coordination game is one where everyone is likely to choose a particular cooperative strategy because they know that everyone else is choosing the same approach: the classic example is coordinating on driving on the left or the right side of the road. If everyone knows that everyone else will protest the regime, they are likely to protest too. There is a lot of safety in numbers, because the regime is not going to be able to punish everyone. A prisoner’s dilemma is where everyone decides to defect because defecting is the ‘dominant’ strategy - no matter what other people do, I am better off behaving selfishly and not displaying solidarity. If people see their situation as one where coordinating against the regime is cheap and safe, they will be likely to hold out. If they see themselves as trapped in a prisoner’s dilemma, they will be more likely do what they need to do to protect their selfish interests. One way that authoritarian wannabes can shift the logic from coordination to prisoner’s dilemma is by breaking civil society: the sphere of independent activity in which citizens, organizations and businesses can freely engage with each other without direct government control.

There’s a lot of complications lurking behind the term ‘civil society’ - I’ll get into some of them in my next post. For now, it’s useful to think of civil society as the political, economic and social space in which citizens and private actors interact. It is murkier in practice than in theory, and its various sectors and organizations have their own internal politics and power dynamics. The CEOs and boards of news corporations, trustees of universities etc will have politics and interests that differ from those, say, of reporters and students, and the extent of that difference will vary from organization to organization.

Even despite these differences, civil society is key. It provides crucial channels through which a broader public’s interests can be articulated and expressed. That means that if the ruler can break the will of independent actors such as media (which shapes how people think other people are thinking) law firms (which can help citizens challenge government assertions of sweeping authority), non-profits (which can help citizens organize) and universities (which shape collective ideas), it will have made great progress towards reshaping citizens’ beliefs in the ways it wants.

Breaking the will of civil society again is about turning coordination games into prisoner’s dilemmas. If all the major law firms refuse to comply with outrageous and legally dubious demands, then the administration will have a hard time breaking them. If, however, it succeeds in getting some law firms to comply, then there is a chance that the others will rush to comply too, for fear that they will lose out on any benefits of compliance, and be brutally punished for their intransigence. The more law firms that have already complied, the stronger the pressure will be on the holdouts, possibly creating a self-reinforcing dynamic.

The regime will find it easier to attack sectors of civil society that (a) are concentrated so that you only have to subdue a few key entities, (b) have important internal constituencies that are willing to go along with the regime, perhaps even welcoming its intervention, and (c) are vulnerable to government action. It will have a tougher job when (a) there are many entities, (b) those entities are relatively unified in opposition, and and (c) are less vulnerable to government action, or at least cross-pressured, so that they have to worry about other people with different priorities than the regime’s.

That gets us to the administration’s strategy for universities. The Trump administration wants to force US universities to accept a general system of ideological oversight. Academic institutions would be expected to get rid of departments with the wrong ideology and squash politically inconvenient forms of student voice.

The administration has succeeded in crushing Columbia University. It has gotten real financial concessions from Brown and from Penn. But it has not succeeded in creating the sauve qui peut dynamic of prisoner’s dilemma expectations that it wants to achieve. Most universities have not made deals. Some are negotiating - most prominently Harvard - but not so far conceding. And even if Harvard does concede without completely caving, it is not clear that others will necessarily rush after.

This is why the Trump administration is shifting strategy. As Joseph Fishkin argues (we came to the same conclusions independently), it has moved from targeting universities one by one, in an effort to get them to agree to bespoke conditions, to targeting a group of universities that it suspects to be more internally divided, and perhaps more willing to give in. It is now pushing for a broad framework for a standardized deal that can be extended to other universities too. Fishkin is able to go into much more detail than I could in a short op-ed. In his description:

To gain the leverage it wants, the administration desperately needs multiple universities to say yes. It would be a disaster for May Mailman and her team if no one joined this thing, the way no news organization took the Pentagon up on its similar “offer” of continued access to the Pentagon if and only if reporters would agree to say only what the Pentagon approves. To roll up the sector, the administration needs the agreeing universities to be ones that other universities would feel comfortable joining. It’s no good if you get, say, Liberty University to join. That would actually help those in academia who hope to persuade their schools to refuse to sign this or any similar “compact” by arguing that if you do, you are Liberty University.

Similarly, if small, defenseless institutions such as community colleges joined, that would not be an especially persuasive starting point for rolling up the whole sector. You can see this calculation in the set of schools the Trump administration in fact chose to approach this week—Arizona, Brown, Dartmouth, MIT, Penn, USC, Texas, Vanderbilt, and UVA. These clearly represent an effort to find the intersection on the Venn diagram between schools with a good amount of prestige and schools that might be softer targets, sometimes because their strong leaders have already been deposed as a result of right-wing activism and replaced with figures who are weaker, more beholden to conservative donors or politicians, or both. Or so the government hopes.

The administration clearly hopes that this group of universities is sufficiently divided that they will accept its offer, or something close to it. Weak leaders will be pressed by boards of trustees and others into compliance. Then, perhaps other universities will feel pressure to sign on (or be left out) and other ones will follow those again, perhaps creating a self reinforcing dynamic as described above. In a prisoner’s dilemma, where people believe that the academic compact is a done deal that everyone will accept, no university will want to hold out.

However, the crucial point is that this hope is partly belied by what the administration is doing. If the Trump administration had been in a strong bargaining position, it would not have adopted this strategy. Instead, it would have looked to roll these universities up in private negotiations and then made a big public announcement that several major universities had signed onto a compact.

That could possibly have caused panic in other universities, although it would still have been a gamble, given the enormous diversity of interests and pressure points across third level education. The fact that they didn’t do this, or something like it, strongly suggests that they couldn’t. They are negotiating from weakness rather than strength, and they are taking an enormous risk. They are providing other public constituencies, who do not want to see universities knuckle under, with an opportunity to organize against them, creating the possibility of another Jimmy Kimmel moment. As I put it in the NYT piece, any wavering provides:

a big opportunity for the opposing coalition and encourages the public to get involved on the other side. Alumni will get organized, pressing university leaders not to sign a compact that could well permanently ruin their reputations. Students demonstrating against the imposition of ideological controls will likely win broad support and sympathy, even from those who have opposed recent campus protests. Some academics are condemning the compact and threatening boycotts, while Dartmouth College’s president has responded by saying she will always defend her university’s “fierce independence.” California’s governor, Gavin Newsom, has threatened to pull state funding from any institution that signs. U.T. Austin’s academic superstars might well have begun to get emails from other institutions, asking if they are interested in moving.

External and internal pressure along these lines will plausibly help ensure that the coordination game remains a coordination game, in which the dominant strategy remains protecting the institution’s independence and refusing to give in.

This has lessons for other fights. Obviously, the battle will be harder in more concentrated sectors than the academy, where institutions are less cross-conflicted, and more vulnerable to government attack, or enthusiastic to share the spoils. But wins can be self-reinforcing: showing that winning is possible, and beneficial makes everyone less likely to give in. More generally, the way to keep winning is through building broad coalitions, with mutual support, and focusing on the successes. When Ezra Levin of Indivisible says:

A defining feature of an emerging authoritarian regime is that it makes the opposition feel like shit on a daily basis. Every day, there is some new atrocity committed; some new institution attacked; some new democratic norm demolished. Some of it -- much of it -- we have little ability to stop in the moment.

But that’s not how to measure the health of an anti-authoritarian movement. Instead, we should measure it this way:

• Are we more unified than we were before?

• Are we bigger than we were before?

• Are our tactics proliferating?

• Is the regime’s popularity falling?

Every single month since the election last November, I’ve answered yes to each of those measures of movement health. Let’s keep it up with this week’s action items.

he is identifying the importance of collective expectations in ensuring that the movement wins, not the regime. There are other ways to think usefully about the battle that we are in, but the dynamics of collective action are very, very important.

* Update: a colleague emails to say that Prisoner’s Dilemma may not be the right game theoretic analogy, and I think they’re right. So focus on the informal reasoning rather than the handwaving towards game theory in the above.

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Back when the kids were small, my family went to a diner that was well known locally for its shtick. As soon as you came in the door, the host/owner would say something rude to you.

When we arrived, it was clear that the host had been at it for decades, and was long past caring. He glanced at us, muttered some predictable and non-specific insult, and we passed in. The whole restaurant had the same vibe. The food wasn’t terrible, but towards the end of the meal, a surprisingly large cockroach squirmed out of a crack near our table, considered its prospects and scuttled back into its darkness. When we told the waitress, she shrugged it off. It wasn’t her problem.

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That’s how the “Blueskyism” debate looks to me. Every one to two weeks, some centrist pundit writes a standardized and moderately insulting complaint about the pathologies of Bluesky, Every one to two weeks, the Plain People of Bluesky say rude things back. For both, it’s a highly ritualized performance.

Rather than going through the various examples in detail (they’re repetitive and uninteresting), I want to build on a essay by Ben Recht and Leif Weatherby, reviewing a recent book by Nate Silver (who coined the term “Blueskyism”). Adapting Ben and Leif’s ideas, the fight over Bluesky is a fight between a particular version of the center and a particular version of the liberal left over the nature of intellectual authority right now.

More specifically: much of the variation among centrist and left pundits can be predicted by the answer to a simple question. Does this or that pundit defer more to the intellectual authority of traditional expertise or the intellectual authority of the Silicon Valley model? This disagreement is increasingly being wrapped around a narrower dispute over whether pundits should be punditizing at Bluesky or at X. The political economies of both sites - the differences between the implicit incentives of the two sites’ algorithms - exacerbate this dispute and make it nastier.

The fight between traditional structures of authority and the intellectual model of Silicon Valley is the main theme of Silver’s book, which has just come out in paperback. Silver doesn’t make any secret of which side he is on. He depicts an America that is split between the “Village” - “Harvard and the New York Times; academia, media and government” and his own folks, the “River” of “Silicon Valley, Wall Street, sportsbetting, crypto, even effective altruism” all of which are dominated by “people who are very analytical but also highly competitive.” The River analogy is a reference to the last card in Texas Hold ‘Em poker. Riverians, like professional poker players, understand the odds and play them. Silver is himself a poker player, and suggests you should in general bet on the people who know how to bet.

The problem is that betting on the general usefulness of political and intellectual philosophies (which is what Silver is doing) is compromised by myside bias. Results from cognitive psychology tell us that we are absolutely terrible at seeing the flaws in our own views of the world, but quite good at detecting the flaws in others. Accordingly, while Silver’s book lands some very solid blows against the “Village,” his view of the River is ridiculously self-flattering.

As someone with different priors myself, I would suggest that the more useful and accurate dichotomy is between the Village and the Sewer. That would not differentiate hide-bound traditional elites from calm, calculating ratiocinators, but hide-bound traditional elites from frenzied degenerate gamblers. It would distinguish the censorious curtain-twitchers of Bluesky from the depraved mob-outrage enthusiasts of Twitter/X. On the one side, the blinkered self-satisfaction of the organized professions, as magnified by crowd sourced pressures towards conformism. On the other, the dynamics through which “first principles” and “do your own research” are digested by the intestinal apparatus of algorithms and crowd identification, producing an undifferentiated slurry that is re-devoured in an ecstatic collective communion so that the cycle can begin anew.

These metaphors likely indicate my own particular biases. I’ve thrown my lot in with the blinkered curtain-twitchers. If Blueskyism has problems, and I absolutely believe that it does, the problems of Sewerism seem to me to be much worse. But instead of entering the lists on behalf of one side or other side and being pulled into the shtick, I’d like us to start figuring out how the two work together. Why is it that we (for those of us who live in the US, and some other countries) are trapped in a system where the self-images of both the professions and tech innovation are increasingly organized around their worst rather than their best aspects? It would be nice to know! NB, however, that all the below is at best social science inflected opinion journalism. I’m pulling together a grab bag of personal observations and anecdotes, and trying to weave them together with a few generalizations into a cohesive story. Treat all this as a set of pointers towards a possibly better argument rather than the product of serious investigation,

Blueskyism and Sewerism

As already noted, there’s good evidence that human cognitive psychology is skewed in some quite particular ways. We are extremely bad at detecting the flaws of our own arguments. We are very good, in contrast, at spotting the holes in the arguments of people who we vehemently disagree with. The obvious corollary is that we ought to take criticism extremely seriously. On average, it is much more likely to be right than our own priors.

Hence, I’ll start by acknowledging that there is a lot that is right about the criticisms of Blueskyism! Bluesky indeed often feels like academia and traditional authority on holiday. The platform sometimes has the worst features of a small community in the throes of a Tidy Towns competition gone feral, ensuring that disruptive outsiders don’t get a look in. There is a tangible Village Consensus, which is deeply respectful of traditional expertise and professional knowledge, and acutely sensitive to criticisms thereof. Moral panics are frequent and pervasive, especially around topics (such as AI) that threaten the professional classes. Back in the early days of the platform (I was there from pretty early on), it was silly and giddy and fun. Now it’s End of the World, 24/7.

Equally, prominent critics of Blueskyism, who mostly are primarily attached to Twitter/X, are disinclined to note the problems of the Sewer that they inhabit. If Blueskyism worsens the inherent defects of academia and the professions, Sewerism does the same for the nastiest aspects of Silicon Valley, so that crypto scams, AI boosterism and unembarrassed power worship run together through the gutters of a social media service that does for the town square model of public debate what Nero did for the Olympic Games.

As Recht and Weatherby describe the main current of Silver’s argument:

The ideology is gambling, but the thinking is all reactionary hive mind. The main characters of the later chapters are all from the San Francisco Bay Area, but they spend a disproportionate part of their lives online. These are people like Bankman-Fried and the crypto bros, pseudonymous accounts like roon and Aella, self-made prophets of computational religion like Eliezer Yudkowsky. On the Edge is a celebration of the community that uses their phones to gamble on everything: to place sports bets, to bet on risky stock options, to bet on cryptocurrencies, to bet on elections.

This isn’t an icy-clear River but the Sewer in full spate. Recht and Weatherby compare the logic to a casino, where the house always wins in the end. For my own purposes, I’d compare it instead to meme stocks, an unstable world in which everyone is desperate to be on the winning side of the grift, but regularly half believe the stories that they’re telling themselves and others. Bayes’ Theorem becomes the spawning-point for a myriad of cults. Silicon Valley funders and founders get high on their own supply. And DOGE and other madnesses are released upon the world, and then quickly forgotten, because awkward and embarrassing.

The political economy of bad thinking

Such problems are reinforced by the ways in which the platforms work. And Bluesky and Twitter/X have their own particular tendencies. Critics of social media sometimes lump them together, suggesting that they are slight variants of the same bundle of pathologies. There’s something to this, but there are also very specific pathologies to each. To understand why, you have to have some kind of map of their differing political economies.

It’s easier to start with Twitter/X, where the structural problems are more commonly discussed and better understood. As I see it, the three most important aspects of the system are this. First, and most infamously, the underlying algorithm prioritizes not just posts that are likely to get attention, but posts by Elon Musk and his political allies. Second, it favors posts by people who pay to have their accounts “verified.” Third, it discriminates against posts that link to outside sources.

This has a number of plausible consequences. First, it creates a particular variant of what Paul Krugman calls a Sierra Madre economy, where many, many people try to attract the attention of Elon Musk or one of his close confederates, but very few succeed. The way to strike gold is to say something that appeals to the political priors of these very strange men. This creates a feedback loop where the crazy feeds upon itself and grows ever stronger. Second, the people who want to get verified are very often people who are trying to sell a bill of goods - selling a shitty product, or pumping up some meme coin or meme stock. This means that Twitter/X has a remarkably high ratio of scam to useful content, especially when you account for the pervasive (and often very low-quality), advertising. This combines with the third feature to create an economy of attention that is highly plugged into the fantasy world of crypto and pump-and-dump, and relatively insulated from the more sober world of ordinary reportage. Notably, there is a lot of really wild AI speculation, where ludicrous claims are regularly reinforced rather than corrected. There’s great cultural/economic sociology to be done by someone analyzing the consequences of Twitter/X for the current AI boom and its sustenance.

Bluesky, in contrast, doesn’t rely on a core attention-grabbing algorithm in the same way. You can pick and choose from a multitude of algorithms. While I know of no research on this, my working theory is that most, and likely nearly all, people opt for the default algorithm, which just presents posts from the people you have decided to follow in reverse chronological order. Bluesky doesn’t have any visible means to make money (yet). It does not penalize posts with links to online sources, and some online publications have suggested that it is becoming a valuable source of incoming traffic.

These create an internal political economy of attention that is notably less deranged (again, in my biased opinion) than that of Twitter/X. Still, it most certainly has its demented aspects, which are less a result of arbitrary algorithmic choices than the group dynamics that are transmitted through and underpinned by the algorithm.

Bluesky’s base algorithm means that you are still much more likely to see posts from some people than from others. Those who have lots of followers are obviously more likely to get read. Their posts in turn may get boosted by their readers, so that their readers’ readers are exposed to them, and, if they like them, boost them in turn. This generates preferential attachment dynamics. Even without algorithmic juking, those who are already well known are likely to increase their dominance over time, leading to a highly skewed distribution in which a small number of people get the lion’s share of the attention. In Bluesky’s case, those privileged people and organizations tend overwhelmingly (a) to have external cultural cachet and (b) to have anti-Trump politics. The relative political homogeneity (there are vicious internal arguments of course) is likely a product of Bluesky’s effective origin story as a refuge for those fleeing Twitter after Elon Musk took over. So too, the relatively strong connections to people with academia and expert knowledge (albeit outnumbered by celebrities and politicians in the top reaches).*

All this too has consequences for the internal political economy of attention (as I experience it personally at least: there is surprisingly little real research that I’m aware of). Really awful stuff is rarer than on Twitter/X. Nearly every poster who has lots of followers is not just a denizen of Bluesky. Typically, posters have some significant external reputation that might be dented or badly damaged if they went full catturd2. Equally, unsurprisingly, arguments or statements that align with the site’s politics tend to do well, especially when they are taken up by people with lots of followers. Those that do not so align, do not.

This leads to a close intertwining between Bluesky, mainstream media sources, and the Democratic party, even though Bluesky is significantly more partisan/left than MSM and the Dems and caters to a much more specific demographic. On the one hand, this results in a lot of traffic to places like the New York Times. On the other, there is also regular and bitter contention about how publications, politicians and pundits are too centrist.

There is strong antipathy to Silicon Valley, not just Musk, Andreessen-Horowitz and the rest, but to liberal-tinged and centrist tech types too, and to technologies such as AI that threatens academia, journalism and the established professions. People who use AI generated images get pushback, telling them firmly that this goes against the culture (although this hostility seems to me to be tapering off some). Bluesky’s own people apart, the only tech aligned poaster in the top 100 is Mark Cuban (who is also one of the most frequently blocked people on Bluesky).

The results are high cultural homogeneity, and a strong tendency to criticize and isolate people who don’t share the village’s values. Crusty jugglers watch out! Bluesky is also much more hierarchical than most of its users acknowledge. Bluesky leadership emphasizes the benefits of openness and decentralization, and the extent to which Bluesky provides users with free choices. These are indeed good things on the whole, but they certainly have their own associated pathologies.

The big lesson of preferential attachment is that power disparities can emerge from completely decentralized processes. Those at the top of the distribution of Bluesky play a powerful collective role in shaping what everyone, including they themselves, see, and tend to filter out perspectives that don’t fit their preconceptions. Equally, the structure isn’t centered on one individual, and there isn’t any equivalent of the Twitter/X Hunger Games, where people compete to get Elon Musk’s attention with ludicrous and horrible claims, creating a conveyor belt of crazy from the fringes to the chokepoints of attention.

Sometimes Bluesky hierarchy can have good consequences. After Charlie Kirk’s murder, Bluesky critics like Thomas Chatterton Williams claimed that Bluesky was chock full of people celebrating. Prominent Bluesky users retorted that there was little to no evidence of that in the feed. My anecdotal sense is that there were people celebrating his death on Bluesky, who you could find if you looked for them - but they were not being amplified or shared by the accounts at the center of the social graph. The consensus of the Village, shared by its leaders and enforced by the tacit hierarchies created by skew distribution functions, was that this was not something that Ought Be Celebrated. Those who did celebrate were consigned to the margins.

Mutually reinforcing caricatures

As argued (I), Blueskyism and Sewerism both have their own particular pathologies. As argued (II), these pathologies are reinforced and accentuated by the social media platforms that they are increasingly associated with, at least in the public eye (I have no idea how you would even begin to measure how many of the cultural features of Blueskyism or Sewerism as I have described them are associated with stuff that happens outside their platforms). The most speculative part of my argument is (III). New pathologies are springing up from a self-reinforcing polarization of debate between Bluesky villagers excoriating a tech-intellectual industrial complex that they hate (often with good reason) and Sewer denizens denouncing (often with good reason) a village that seems willfully ignorant of its own parochial interests, blind spots, and genteel corruption.

This third phenomenon is a meta-layer of emergent over-confident generalizations that emerge from the more particular lower-level pathologies of the two forms of expertise and their associated platforms. Again, Nate Silver provides an illustration (in conversation with Tyler Cowen), which touches on things adjacent to what I do meself.

COWEN: What was the last interesting thing you learned from the academic political science literature?

SILVER: Oh boy, this is going to seem like an insult. [laughs]

COWEN: No, no, we’re all for insults here.

SILVER: Look, I read a lot of Substacks and things like that. Oh, my gosh. I don’t know.

COWEN: I think that might be the right answer, to be clear.

[laughter]

SILVER: I think in some ways, what has come out of academic circles has been interesting. I think effective altruism has been interesting, for example. Certainly, critical theory or whatever, the origins of wokeness have had a lot of influence on the discourse more broadly. But I don’t really read a lot of journal articles anymore. Also, a lot of it’s gone on Bluesky, I think, and I can’t tolerate Bluesky, really. It’s too much of a circle jerk.

I think academics have maybe lost influence in that respect. Even though I have great experiences talking to academics, and I’ll do events at universities a couple of times a year.

They also fall into this trap where it’s so reflexively anti-Trump, a lot of it. I’m anti-Trump, in most senses of that term, but something about it has melted the brains a little bit of the nuance and the subtlety. And the slow-cooking method of academia, where you’re supposed to take more time with things, is not always a good match — you being one of the major exceptions — for rapid-fire reaction to the news cycle.

… I think that 90 percent of academic papers would work perfectly fine as blog posts. Including the tone of like, “Okay, I ran some regressions” instead of having Greek symbols and things like that, and the pretense of all of it.

Obviously, I’m not even slightly unbiased. I’m an academic political scientist! Also, maybe it’s worth disclosing here that I had lunch with Silver years ago, back when he was talking more to political scientists, and seemed to think, as did many political scientists, that we were all engaged in a collective endeavor to bring quantitative reasoning to the masses.**

But dismissing academic peer review (which is flawed, and a massive pain in the arse, but which has value) as “the pretense of all of it” is a notably self-flattering choice if you have opted instead for Substack newslettering as your livelihood. It also enables you to dismiss a whole lot of potentially valuable disagreement without ever having to consider it. Conflating academic papers with Bluesky circle-jerks with Greek Symbols and Book-Larning into one indifferent mass of badness allows one to invisibly circumnavigate how “rapid-fire reaction to the news cycle” can melt people’s brains too. As it happens, flash-frying is a whole lot quicker than slow cooking, and without naming names, there are a fair number of Substack quasi-academics, whose brains are sizzling in the heat of a business model that requires them to post confident seeming claims three or four times weekly.

I could find similarly tendentious stuff on Bluesky of course - while I’m biased to be annoyed by the kinds of arguments that reliably annoy me, readers should consider these vexations as a stand-in for a proper “plague on both your houses” argument. The actual point being that if you, as a Blueskyist, want to analyze the defects of Sewerism, go for it, and so too for Sewerists going after Blueskyists. But lack of self-awareness about the defects of your own position, and how the whole insult-swapping model is its own self-perpetuating clusterfuck, is liable to hurt rather than help your case. Making silly and tendentious claims encourages silly and tendentious responses. Ritual insults beget ritual responses as the cockroaches keep on scuttling out.

The current model of debate is an accidental and emergent phenomenon, but one that might as well have been purpose designed to get stupid fights going that distract from the actual problems rather than pointing towards them. There are a lot of problems with the Village model of intellectual authority; so too with the Sewer that threatens to swamp it with fetid semi-solids. But my very strong intuition is that the pathologies of the two are increasingly connected so that they feed off each other. That is not only missed when the one deplores the other without looking to itself or the wider system. It is reinforced.

The self-satisfied ignorance of the Village helps perpetuate the morass of scam and thwarted opportunities that many, perhaps most Americans are trapped in. Ritual denunciations of the Sewer do more to fence all this off from sight than make it better. Many of the Sewer’s most celebrated denizens are more interested (and this is where we get back to Ben and Leif’s casino) in profiting from this misery than addressing it. When crypto interests attack traditional notions of regulation, it’s not from disinterested love of freedom that they’re doing it. The more that the Village gets stuck on denouncing the Sewer (without looking at its own outflows of effluent) and the Sewer gets stuck on denouncing the Village (without recognizing how much it depends on a perpetual supply of suckers), the worse off we all are.

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* I note in passing that this has benefited me - while not a big poster, I have more followers on Bluesky than I ever did on Twitter.

** I’m guessing, maybe incorrectly, that some of the specific hostility to political science is connected to an increasingly nasty fight between non-academic pollsters such as David Shor and academic political scientists like Jake Grumbach over the lessons of the last election for future Democratic strategies. But that’s a speculation and a side-note.

[Photo by Jason Scott https://www.flickr.com/photos/textfiles/6301463398/]

The events of the last several days have made me think about the political processes through which people are made martyrs, and how the more interesting and complicated aspects of their humanity get rubbed away in the process. That in turn has spurred me to write about Aaron Swartz, not in implied comparison to anyone else, but in his own right. I wrote about Aaron a few years after his death. He was not a close friend but he was a good one. I didn’t know about his prosecution before he announced it, but in its aftermath he made it clear that he felt he could trust me to stick with him. I’m not able to to talk about him from the perspective of genuine intimacy, but I knew him well enough to talk about how he engaged with the world. And there was something valuable in that which is worth emulating.

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In 2019, I did one of those Conversations with Tyler Cowen, where I flubbed the standard question. He asks most guests what their “production function” is: how they decide what is useful to do and then do it. I didn’t really prepare, and didn’t have anything interesting to say on the topic. What I should have said is that I try - usually not very successfully - to do what Aaron did, but that what he did best is not what most people know about. Aaron’s public persona and personal charisma overshadows the fact that much of his contribution was invisible to the world. He devoted a startling amount of energy and attention to easing the way for other people whom he found interesting or thought might be useful.

For example: before Rick Perlstein became a well known historian, or even had a website, Aaron had discovered him. Aaron offered to build a website for him (Rick didn’t know who he was, and found it all a bit startling). So too, for Crooked Timber, a blog that I used to help run: when we ran into some technical issues, Aaron came out of nowhere to offer to host us. So too again for the amazing, intellectually and politically diverse group of people, with whom Aaron corresponded, many of whom I only discovered after his death.

Aaron had made enough money (or so it seemed) after the launch of Reddit to spend his time doing interesting stuff in the world, so long as he did not hog out on luxuries. And for him, interesting stuff typically involved figuring out practical ways to help others, and to build connections. Someone with apparently similar inclinations recently remarked to me that the problem with anarchism is that no-one ever wants to do the dishes. Aaron did the dishes without making a fuss about it.

He spent most of his time trying to build stuff for and with other people but he was not a saint. He had a considerable ego, although he was perfectly happy to be teased about it. He was not patient. If something wasn’t working out in his opinion, he would be quite ruthless in cutting it off and switching to another project that seemed more promising. I had conversations with people who were left behind after one or another of these about-turns. They felt aggrieved and unhappy; likely he could have treated them better.

Even so, it was striking how much came out of his willingness both to do the grind and to figure out how to help people with different views and perspectives than his own to do what they had in them. He was set on making the world into a more interesting place, with richer collective goods and better conversation. Whatever got in the way of that, he pushed to one side.

What I take from Aaron is that the best way to be truly productive on the margin, is to try to build for other people and connect them together. You don’t pretend to be indifferent to your own sense of what a better world would look like, and you need some degree of ruthlessness to work towards it. You have limited time, energy and attention, and at some point, you are likely to have many more people asking for these scarce resources than you can possibly help or satisfy.

Inevitably, your own ego is going to be implicated. Acts that you yourself perceive as relatively selfless will persistently curve back into your own self-interest, because that is the way that human cognition works. But exactly because this is true for everyone, small shifts on the margin towards collective good provision can have outsized consequences. If scenius is indeed much more productive and creative than individual genius, then you ought spend more of your time cultivating it - finding interesting people who might fit together in unexpected ways and figuring out how to connect them and build spaces where they can do their own stuff. And doing the dishes while you’re at it.

The most lovely and powerful lines that I’ve ever read are at the end of Middlemarch. George Eliot says of Dorothea:

Her full nature, like that river of which Cyrus broke the strength, spent itself in channels which had no great name on the earth. But the effect of her being on those around her was incalculably diffusive: for the growing good of the world is partly dependent on unhistoric acts; and that things are not so ill with you and me as they might have been, is half owing to the number who lived faithfully a hidden life, and rest in unvisited tombs.

The greatest parts of Aaron’s life are those that are hidden behind his myth. My strong belief is that his unhistoric acts were incalculably diffusive in just the ways that Eliot describes. He is missed.

[update: Rick Perlstein anecdote corrected by Rick: thanks]

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