I didn’t expect to have more uncomplimentary things to say about the unfortunate intellectual relationship between (a few) economists and (a few) Silicon Valley billionaires right away. But Noah Smith republished his review of Daron Acemoglu and Simon Johnson’s Power and Progress this morning as part of a feud with Acemoglu and Johnson over whether we ought be trying to “steer” the development of AI.

A “timely repost” he says. Not so much. When Noah first put up his review, I responded, pointing out some of the things it got very badly wrong about the book it purported to describe. Then, he and Brad DeLong did one of their very occasional podcasts. Noah did not so much respond to any of the particulars as double down on his (again: obviously wrong) claims about the book without actually responding to any of the things I had said. I responded to that too.

Now, Noah is republishing the original piece with the note:

So anyway, here’s that review for you to enjoy. Hopefully it gets a few people to think a little harder about the AI-related ideas that Acemoglu has been promoting throughout the econ world, and why it would be a big mistake to make those ideas the default position of the economics profession on the AI issue.

I don’t for a moment think that Noah is a wicked person, but if there are economists who “need to think a little harder about … AI-related ideas,” he absolutely ought to be first in the queue. When Noah wrote his original review back in February 2024, it was to ridicule the notion that we ought worry about the power of Silicon Valley billionaires. That was an obviously bad argument then, but it is now much worse, given everything that has happened since.

So here’s my own “timely repost”: an edited and very slightly updated remix of relevant bits from the two very long pieces that I wrote in response to his earlier review and the podcast he did with Brad doubling down on his position. The TLDR of a very long post is that Silicon Valley billionaires do, actually, have power to shape political debate and get people to fawn over them, that Acemoglu and Johnson’s book is very valuable on this very important topic, that economists actually should adopt some form of their view as a default position, and that Noah himself should not be digging himself deeper, but trying to dig himself out, by admitting how badly he got things wrong back then. I don’t hold out much hope that he will: the even shorter TLDR is the screenshot at the top of this newsletter. Perhaps I will be happily surprised.

I don’t much like having to do this - I genuinely like Noah as a person - but I am startled and dismayed to see him resurrect claims that he should never have made in the first place. He has a lot of readers, and his failure to think hard and honestly about what he got wrong does them a great disservice. Repost below the fold.

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Before letting rip, Noah says nice things about Acemoglu and Johnson, and I’ll do the same here for him. There are many on the left who detest Noah, but I know him to be a genuinely decent person. What I do think (and I’ve said more or less this to him in person - my views won’t come as news) is that Noah represents a style of economics that has an overly Panglossian view of power, economics and progress.

Many (but not all by any means!) economists just don’t like to think about power that does not involve visible coercion at gunpoint. They are especially resistant to the notion that power and ideas might be intertwined. Instead, being economists, they prefer to believe that ideas are intertwined with markets. Specifically:

By gesturing toward this imaginary intellectual marketplace, in which everyone definitionally competes on an equal footing, they can wave away all counterclaims. Neither impertinent criticisms from non-economists, nor heretical anti-market arguments from fellow initiates can even scratch the surface of their magnificent assurance. Such counterclaims effectively become invisible.

That might seem like a rather strong hypothesis. But it is the only plausible theory I can come up with as to why Noah apparently can’t see the words and sentences printed on the pages that he read. There is a dizzyingly vast gulf between what Noah believes Acemoglu and Johnson are saying about power and what they actually say.

Noah says that Acemoglu and Johnson’s

entire chapter on power and persuasion left me bewildered. I do not understand why we should put accidental success in a nonviolent marketplace of ideas in the same conceptual category as chattel slavery and feudalism. [all Noah’s italics]

He suggests that Acemoglu and Johnson’s argument is both impossibly capacious and intellectually incoherent:

it’s clearly true that technology can be used to benefit average people or to hurt them. But how does society choose how to use technologies? Acemoglu and Johnson’s answer is “power”, from which they get the title of their book. But what is power? Here, in Chapter 3, Acemoglu and Johnson deploy a definition that veers into the tautological: “Power is about the ability of an individual or group to achieve explicit or implicit objectives. If two people want the same loaf of bread, power determines who will get it.”

Using this definition, how could we ever conclude that power wasn’t the reason for an observed outcome? Two people want a loaf of bread, and one of them gets it; we know this was due to “power”, because “power” is defined by who gets a loaf of bread. This kind of definition is semantically valid, but empirically useless; if you define “power” such that it simply means “whatever caused an outcome to happen”, you haven’t isolated causality, you have simply given it a new name.

Acemoglu and Johnson have a reason for employing a definition this infinitely broad; it allows them to include persuasion and compulsion in a single category of “power”.

In practice, according to Noah, Acemoglu and Johnson base their entire theory of power on the eloquence of techbro poasting. Specifically:

Acemoglu and Johnson believe that entrepreneurs … select from a menu of technologies, … to replace people or … that complements people’s labor … often they’ll choose the wrong thing. And not only will they choose the wrong thing, but they will use their quote-unquote power … persuading people [by] writing articles and … PR, … [and] their mighty power of blog posts … tweeting to … convince the world to allow them to invent the human replacing thing

Such an understanding of power is “useless and even counterproductive” since it assumes that “people just hearing arguments and deciding that those arguments are right means power has been exercised.” Power becomes a “residual” explanation: “[t]he only way you get there is by just assuming that all outcomes are due to power and then … applying the label power to whatever you think produces the outcomes.”

It isn’t unreasonable for Noah to want to know how to identify power when he sees it. Nor is it unreasonable for him to note that social scientists find it hard to prove that power inequalities caused this or that outcome, when the power dynamic doesn’t come out of the barrel of a smoking gun.

However, the fact that causation is really hard to isolate for certain social phenomena does not, ipso facto, mean that they lack causal force.

What Acemoglu and Robinson are saying is something quite different than what Noah depicts them as saying. For sure, they acknowledge that persuasion has some stochasticity. But they stress that it is not a series of haphazard accidents. Instead, under their argument, there are some kinds of people who are systematically more likely to succeed in getting their views listened to than other kinds of people. This asymmetry can reasonably be considered to be an asymmetry of power.

Noah claims Acemoglu and Johnson respond to the question “why are the tech bros so persuasive?” with a simple answer: “luck.” He says that he has found the killer quote:

They admit that quite a bit of the process of persuasion is random and declare that you are enormously lucky if you get the right idea, just the right ring to it at just the right time. … I do not understand why we should put accidental success in a non violent marketplace of ideas in the same conceptual category as chattel slavery and feudalism.

Let’s look at what Acemoglu and Johnson actually say! They do indeed argue that “all else equal, an idea is more likely to spread if it is simple, is backed by a nice story, and has a ring of truth to it.” But the problem for Noah’s interpretation is that they spend the next fifteen pages or so explaining at great length why all else is not equal, beginning with the very next sentence after the one that Noah quotes.

Acemoglu and Johnson argue that the success of ideas has some stochasticity - it is not a simple product of brute power. That is the burden of the sentence that Noah singles out as their core claim, and of similar provisos scattered throughout. But they certainly do not think that “success” is merely “accidental.”

For starters, Acemoglu and Johnson claim that the success of ideas depends on the “social status” of their originators and transmitters. Ideas that come from “respected cheerleaders” are more likely to spread. Social status is associated with success - we are hardwired to admire and imitate those who seem to be successful. But “societies and their rules” also shape social status and charisma: women and minorities have had enormous difficulty in having their voices heard, even when they have great ideas! More generally:

A huge amount of creativity, charisma, and hard work is no guarantee that an academic or entrepreneur will come up with an impactful idea. Prevailing beliefs and the attitudes of powerful individuals and organizations determine which ideas will appear compelling, rather than wacky or so ahead of their time as to be safely ignored.

Social networks also create power imbalances. Some people are very well connected. Others, not so much. Acemoglu and Johnson say that:

when it came to the power of big banks, it was not only ideas and stories. Bank executives and board members belonged to social networks that had enormous economic power and propagated these ideas. The big-finance-is-good idea was being repeated by economists and lawmakers, who were eager to provide theories and supportive evidence.

Furthermore:

It is not just the self-confidence and the social networks that powerful people have for propagating their ideas. It is also whether your voice is amplified by existing organizations and institutions, and whether you have the authority to counter objections.

Specifically this allows for important forms of agenda control:

The rules of the political system determine who is fully represented and who has political power, and thus who will be at the table. If you are the king or the president, in many political systems you will have ample influence on the agenda—sometimes you can even directly dictate it. Likewise, economic institutions influence who has the resources and the economic networks to mobilize support and, when necessary, pay politicians and journalists.

In short: theirs is not a simple theory of tweeting eloquence and accidental success! Nor, for that matter, is it an argument that starts from a “marketplace of ideas.” As Acemoglu and Johnson explicitly note:

the marketplace for ideas is an imperfect frame for technology choices, which are at the heart of this book. To many people, the word market implies a level playing field in which different ideas try to outcompete each other primarily on their merits. This is not how it happens most of the time.

To summarize: Noah’s Theory of Acemoglu and Johnson is as follows.

• Techbros and entrepreneurs write blogposts and tweets in a free and thriving marketplace of ideas. Through luck and eloquence, the techbros persuade people that their arguments are right. This Is Somehow Power.

Acemoglu and Johnson’s Theory of Acemoglu and Johnson is just a little bit different.

• Success in ideas is in part stochastic. Luck does play a role. But so do systematic inequalities. Specifically:

  • People who are perceived as more successful have higher social status and are more likely to have influence.

  • People who do not belong to disempowered minorities have higher social status and are more likely to have influence.

  • People who have dense connections to powerful economic networks are more likely to have influence.

  • People who have the ears of politicians are more likely to have influence.

  • People whose voice is amplified by existing institutions and organizations are more likely to have influence.

  • People who have substantial financial resources to sway journalists and experts are more likely to have influence.

• This ain’t no level playing field market of ideas! Political, financial and social asymmetries have substantial consequences for who has influence and who has not.

Such inequalities of influence help explain something else that perplexes Noah: why Acemoglu and Johnson “explicitly try to rehabilitate the original Luddites,” and argue that these Luddites “were right to worry about knitting frames decimating their livelihoods.” From Power and Progress:

The Luddites themselves seem to have understood not just what the machines of the age meant for them but also that this was a choice about how to use technology and for whose benefit. In the words of a Glasgow weaver, “The theorists in political economy attach more importance to the aggregate accumulation of wealth and power than to the manner of its diffusion, or its effects on the interior of society.”

The Glasgow weaver still has a point, some two centuries later. Many “theorists in political economy” still attach importance to the collective accumulation of wealth and power, without inquiring closely how it is distributed, or what second order consequences it may have for society. Acemoglu and Johnson are, of course, themselves political economists, but they look to push back against some of the main tendencies in the field.

There are two parts to the Glasgow weaver’s complaint. One is a distributional concern: in their words, economists usually pay more attention to aggregate social benefits than how those benefits are diffused to particular groups in society. They all too readily leap from a broad utilitarian-philosophical claim - that we ought maximize on some notion of the general social benefit - to the empirical assumption that if we maximize aggregate benefits at time t1 we can expect that the distributional problems will sort themselves out in some proximate future period, t2. More crudely put: they assume that if you let ‘progress’ rip right now, the particulars of who gets what will sort themselves out in some broadly acceptable way in the future.

According to Noah (in the podcast), Acemoglu and Robinson’s argument is that “entrepreneurs … select from a menu of technologies, … to replace people or … that complements people’s labor … often they’ll choose the wrong thing.” Under this interpretation, Acemoglu and Johnson are wrong, because they believe that entrepreneurs have the foresight to envision what their technologies will do to labor in the future. Noah is then moved to launch into an extended fantasia on how “after combing through” the book, he has failed to find a “scrap of evidence” for the proposition that entrepreneurs and technologists can foresee the consequences for labor of the technologies that they invent, and how various tech folk and entrepreneurs are terrible at predicting the future.

Again (I regret that I have to keep saying this), this is not what Acemoglu and Johnson say. They do not claim that entrepreneurs make a single choice over technologies that they might get right or wrong, leading to the one path of development or to the other. They do not worry that tech people are prophetic geniuses, fiendishly choosing the worst possible human future so as to maximize their personal advantage. Instead, they fear that the bros’ unseeing ignorance leads to over-reach, but that their choices may nonetheless become self-reinforcing because of the mutually reinforcing intersection of influence, technological development and political power. Again, it is worth reading their actual written words:

Those enriched by new technologies, or whose prestige and voice are magnified, become more powerful. Technological choices are themselves defined by dominant visions and tend to reinforce the power and status of those whose vision is shaping technology’s trajectory. This self-reinforcing dynamic is a type of vicious circle. Students of history and political economy have highlighted such dynamics, documenting the pathways that make the rich politically more influential and how this additional political power enables them to become richer. The same is true of the new vision oligarchy that has come to dominate the future of modern technology.

In other words, economic inequality tends on average to compound into political inequality, and inequality of social influence, in a kind of feedback loop. And even the feedback has feedbacks! Just as social influence is magnified by economic clout, so too social influence can translate into economic and political benefits. Hence:

persuasion power generates strong self-reinforcing dynamics: the more people listen to you, the more status you gain and the more successful you become economically and politically. You are thus enabled to propagate your ideas more forcefully, amplifying your power to persuade and further boost your economic and political resources. This feedback is even more important when it comes to technology choices. The technological landscape not only determines who prospers and who languishes, but it also critically influences who holds social power. Those enriched by new technologies, or whose prestige and voice are magnified, become more powerful. Technological choices are themselves defined by dominant visions and tend to reinforce the power and status of those whose vision is shaping technology’s trajectory.

There are long standing battles about feedback processes within the profession of economics. Many economists - in particular right-leaning economists - Do Not Like increasing returns processes because they mess up a lot of the economic standard arguments for market efficiencies. But at this point, I think that most reasonable economists accept that feedback helps explain how some trajectories of technological progress get locked in, and why some get locked out. So Acemoglu and Johnson take that one step further, arguing that technological trajectories are shaped by political and social feedback in ways that will magnify the influence of elites, absent strong countervailing forces.

If (a) there are different technological trajectories, (b) these trajectories have long term distributional implications (they lock in economic patterns of who gets what), and (c) this in turn affects the distribution of political and social power, then you can’t assume that these problems will sort themselves out in some fair and equitable fashion in the long run. They will not: instead, whatever solutions are created in the future will reflect inequities that are being generated today.

The second part of the weaver’s complaint is a social concern - that maximizing on aggregate wealth and power may have adverse effects for society, and may hurt some groups particularly badly. This of course, fades into the distributional problem, but it has some broader consequences too. Again, there is an unfortunate tendency in the mainstream of economics towards a callous calculus of the ultimate good, in which the travails of those who suffer through economic adjustments are regarded as sad, in some abstract and generalized way, but a necessary cost of building a better world that will manifest itself at some hazy point in the future. At the extreme, this can turn into statements like Nassau Senior’s infamous quip that the Irish famine “would not kill more than a million people, and that would scarcely be enough to do much good.”

Acemoglu and Johnson are not responding to sentiments as vile as those of Nassau Senior. But I suspect that they are familiar with the attitude of much of their profession to workplace innovations that seem to improve ‘efficiency’ at the expense of making workers’ lives worse. For example, algorithms including machine learning algorithms, are having more immediate consequences within the U.S. workplace, as illustrated by this Bloomberg article on Amazon’s work practices. Rather than making the customer wait, Flex drivers ensure the packages are delivered the same day. They also handle a large number of same-day grocery deliveries from Amazon’s Whole Foods Market chain. Flex drivers helped keep Amazon humming during the pandemic and were only too happy to earn about $25 an hour shuttling packages after their Uber and Lyft gigs dried up.

But the efficiencies come at a stark human cost:

the moment they sign on, Flex drivers discover algorithms are monitoring their every move. Did they get to the delivery station when they said they would? Did they complete their route in the prescribed window? Did they leave a package in full view of porch pirates instead of hidden behind a planter as requested? Amazon algorithms scan the gusher of incoming data for performance patterns and decide which drivers get more routes and which are deactivated. Human feedback is rare.

… former Amazon managers … say the largely automated system is insufficiently attuned to the real-world challenges drivers face every day. Amazon knew delegating work to machines would lead to mistakes and damaging headlines, these former managers said, but decided it was cheaper to trust the algorithms than pay people to investigate mistaken firings so long as the drivers could be replaced easily. …

Inside Amazon, the Flex program is considered a great success, whose benefits far outweigh the collateral damage, said a former engineer who helped design the system. “Executives knew this was gonna shit the bed,” this person said. “That’s actually how they put it in meetings. The only question was how much poo we wanted there to be.”

From the perspective of management, algorithmic bedshitting is wonderfully efficient! It costs less, and is much less of a pain in the ass. And if drivers have to piss into bottles in their vans because they fear being punished by the algorithms, then so be it. This is a cost that they pay, not investors, nor managers, nor customers.

Whether Noah cares to acknowledge it or not, the perspective of people like Amazon Flex drivers is less influential on decision making than the perspective of certain other groups. As Acemoglu and Johnson mention in their bibliographical essay, there is some very solid empirical research - and by economists too! - explaining situations in which power-as-social-influence has been very consequential indeed! Specifically, Elliott Ash, Daniel Chen and Suresh Naidu FOIA-ed the hell out of George Mason University, and combined the results with other data. They wanted to discover what happened when right wing foundations paid for judges to attend seminars in nice resorts, with great food and drink, where they listened to Milton Friedman and his mates explaining The Virtues of Free Markets, the Evils of Government Regulators, the Benefits of Chicago School Antitrust Doctrine, and the Healthy Incentives Provided by Harsh Criminal Sentences.

The evidence shows, unsurprisingly, that the judges were influenced! Not only were there measurable long term consequences for the judges’ decisions after they were wined and dined but there were secondary consequences, via social influence osmosis, for other judges whom the first set of judges worked with.

Noah would like to believe that we live in a thriving “marketplace of ideas.” Ash et al. focus in contrast on ideas of the marketplace, how rich people have shaped them, and how in turn, they are reshaping U.S. society. Again: this ain’t no residual account. There’s actual econometrics! These findings were published by the National Bureau of Economic Research, an organization that Noah is possibly familiar with. Oh happy marketplace of ideas, where the Scaife Foundation and Amazon Flex workers alike can try their luck, and hope for accidental success in influencing federal judges!

So how do we create a situation in which other voices than those of accidentally eloquent billionaires like Elon Musk can have some influence on debates over tech policy? Succinctly, Acemoglu and Johnson want MOAR equality and MOAR democracy. The first borrows from J.K. Galbraith’s notion of countervailing power:

We need to reshape the future by creating countervailing forces, particularly by ensuring that there is a diverse set of voices, interests, and perspectives as a counterweight to the dominant vision.

The second derives from a more recent body of findings about problem solving and social cognition, which I and various co-authors have also drawn from.

There is also another reason for democratic success: cacophonous voices may be the greatest strength of democracy. When it is hard for a single viewpoint to dominate political and social choices, there are more likely to be opposing forces and perspectives that undercut selfish visions imposed on people, regardless of whether they want them or benefit from them.

and

The democratic advantage may not be just the aggregation of separate views, but rather the encouraging of diverse perspectives to engage with and counterbalance each other. The strength of democracy is thus in the deliberation among different viewpoints, as well as in the disagreements that this often generates. Hence … a major implication of our approach is that diversity is not a “nice to have” feature; its presence is necessary to counteract and contain the overconfident visions of elites. Such diversity is also the essence of democracy’s strength.

When Acemoglu and Johnson talk about “steering,” they are suggesting that it is better not to leave crucially important decisions to the techbros, but to have them decided democratically through processes that allow ordinary people to have some countervailing power against elites. The downside of democracy is that it is slow, conflictual, and a massive pain in the arse. The upside is that it allows people with different interests to defend their interests, and to collectively draw on diverse understandings of the world for a more complex mapping of plausible future developments. And when you are making decisions that may set patterns in stone for very long periods of time, you really want those who are affected by these decisions to have a say.

If Acemoglu and Johnson are right, our children and grandchildren may not be dealing with technology-produced problems in circumstances of their own making. Instead, the trajectories that determine who makes the choices, who, indeed, defines what is a problem and what is not a problem, are being shaped today and tomorrow and tomorrow. When increasing returns intersect with political and social influence, it is perfectly plausible that the decisions we make right now could dramatically constrain the ability of people in the future to make decisions at all.

Moving away from democracy towards a fuller embrace of market awesome may radically undermine the capacity to exercise democratic choice later. Plumping for the new vision oligarchs, and continuing to support them over time, potentially vitiates collective choice through democracy in order to encourage unbound marketism, with a side-order of unbridled authoritarianism should folks like Musk, Thiel and their ilk get their way. That is what is at stake in Noah’s fight against Acemoglu and Johnson. And that is why both his criticisms and the blinkered perspective that they emerge from get the situation we are in so badly wrong.

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Two pieces last week had sharply differing takes on the politics of Silicon Valley billionaires.

Tyler Cowen:

Andrew Hall is on a roll … Excerpt: “For most of the past decade, anti-billionaire language was a niche product. … In the weeks after an inauguration that seated tech CEOs in the front row and the dizzying drama of Elon Musk’s ill-fated DOGE experiment, billionaire mentions in Democratic emails quadrupled, peaking above 20 percent of all emails sent and holding around 15 percent ever since. Anti-billionaire fundraising tactics are now a mainstay of Democratic messaging.”

Yes, billionaire derangement syndrome is now a thing.

Tim O’Reilly:

Elon Musk … now envisions SpaceX becoming “worth more than the rest of Earth” if it accomplishes its long-term goals. … Before anyone claimed that markets were efficient, political thinkers claimed that the self-interest of merchants would be a gentler master than the passions of princes. Albert Hirschman reconstructed this forgotten case in “The Passions and the Interests”. Montesquieu held that commerce makes manners gentle, le doux commerce. James Steuart thought economic complexity would restrain a prince more reliably than any constitution, since a ruler who wrecked the delicate machinery of trade would beggar his own kingdom. John Maynard Keynes put it plainly 150 years later: better that a man should tyrannise over his bank balance than over his fellow citizens.

… The self-interest of merchants did not tame the passions. It became infused with them, and turned the greatest of merchants back into princes carrying all the undisciplined appetites of old. They built a new and stranger tyranny: not the old corporate machine obedient to shareholders, but a machine that uses shareholder capitalism’s legal forms while escaping its restraints. SpaceX’s astronaut-in-chief is not maximising shareholder value. He is using the instruments of shareholder capitalism to raise enormous amounts of capital while freeing himself from any restraints from those who provide it, so that he can spend the proceeds on Mars, humanoid robots, artificial intelligence or whatever next satisfies his ambition.

Unsurprisingly, I think that the second of these is vastly more insightful than the first. But rather than comparing the pieces I want to hybridize them. Tyler’s riff on “Trump Derangement Syndrome”1 insinuates that you likely have a screw loose if you oppose the political influence of billionaires. But what if you turned this phrase against itself, and instead asked why some tech billionaires seem to be deranged?

Then, I think that you could weld it together with Tim’s basic argument to reach some plausible conclusions about how this happened. Under the wrong conditions, undisciplined princely appetites can transform into madness.

To be clear: this hybrid would be notably different to Tim’s argument, and likely actively objectionable to Tyler. I alone am to blame. But there is inadvertent support for some of its key elements from Peter Thiel, who is a surprisingly valuable chronicler of the conditions that give rise to billionaire derangement, as well as a living example of it (the Antichrist is among us!).2 Here, I’m drawing both on lectures that Thiel gave at Stanford, as summarized by his amanuensis Blake Masters, and the resulting co-authored book, Zero To One. These sources have a lot to say about the connections between entrepreneurship, kingship, and personal eccentricity.

The conclusion I draw is that the forces that Tim identifies, combined with specific aspects of the political economy of Silicon Valley, help explain the derangement of certain Silicon Valley billionaires and their epigones. Old style princes were notorious for their tendencies to deranged behavior, which came not just from their inbreeding, but their power, and the unwillingness and inability of others to contradict or check them. So too, modern princes.

Not too long ago, many people, including Tyler, hoped that the advance of classical liberalism would go hand-in-hand with the growing power of tech billionaires, advancing both causes at once. Now, politically influential tech billionaires have visibly lost contact both with reality and with anything that could plausibly be described as classical liberal values. See the screen shotted quote above. Rather than making snide asides about billionaire derangement syndrome, it might be time for such people to confront what actual billionaire derangement means for the ideological straddle that they have relied on for so long. That is even more so, in a world where markets as well as market-makers are being devoured by the passions.

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To summarize the particulars of my theory: Thiel’s lectures and book provide good, if incomplete evidence that the princely passions described by Hirschman didn’t disappear, but went underground. Commerce and power were fused into a new ideology of entrepreneurial virtù that became highly influential among the founder community in Silicon Valley. This combined with Silicon Valley’s (and popular culture’s) tendency to connect genius with eccentricity, not simply selecting people who seemed strange, but compounding their strangeness through self-reinforcing feedback loops. Finally, this all happened in an intimate social environment of founders and funders. Billionaires know each other and measure themselves and their success against those they consider peers, in a dense entangled clique that commingles high degrees of mutual influence with rivalries and jealousies.

Of course, all of these factors have benign as well as malign aspects. Entrepreneurial risk taking can be awesome; weird people are often more likely to be original; densely linked communities have many advantages. Furthermore, I would guess that none of these factors was sufficient on its own to precipitate the madness of princes that we see today. It is perfectly possible that they would have worked together in much more benign ways under different external circumstances. But we are in the world we’re in: one where the boundless appetites and irrationalities of a small number of billionaires seem increasingly incompatible with the need to maintain a stable civil society.

The victory of doux commerce was never complete. Economists like Schumpeter and Hayek deplored the encroachments of bureaucracy and treated disruptive entrepreneurialism as a kind of heroism. Schumpeter specifically argued that monopoly rents were needed to spur technological innovation.

These ideas about entrepreneurialism resonated with well connected Silicon Valley thinkers like Peter Thiel and Marc Andreessen (who regularly mentions Schumpeter as a source of ideas). Even more interesting, given Tim’s piece, is that they often went hand-in-hand with ideas about kingliness. Thiel’s Stanford lectures reportedly stressed the similarities between founders and monarchs.

A startup is basically structured as a monarchy. We don’t call it that, of course. That would seem weirdly outdated, and anything that’s not democracy makes people uncomfortable. But look at the org chart:

… Once a startup becomes a mature company, it may gravitate toward being more of a constitutional republic. There is a board that theoretically votes on behalf of all the shareholders. But in practice, even in those cases it ends up somewhere between constitutional republic and monarchy. Early on, it’s straight monarchy. Importantly, it isn’t an absolute dictatorship. No founder or CEO has absolute power. It’s more like the archaic feudal structure. People vest the top person with all sorts of power and ability, and then blame them if and when things go wrong.

This notion of the monarch as someone vested with “all sorts of power and ability” who gets the blame “if and when things go wrong” reflect Thiel’s Girardian hotchpotch of notions from The Golden Bough combined with management theory. For Thiel, kingship is a quasi-religious institution that combines the right to rule and the prospect of being sacrificed by the multitudes when things go bad. In three successive sections of Zero To One, “Where Kings Come From,” “American Royalty,” and “Return of the King,” Thiel and Masters emphasize the need both to cultivate a kingly myth and not allow it to dominate you.

Thiel also believes that you need not just to thwart socialist bureaucracy but to break out of the stifling confines of market discipline to get things done. The good stuff comes from convention breakers.

The usual narrative is that society should be organized to cater to and reward the people who play by the rules. Things should be as easy as possible for them. But perhaps we should focus more on the people who don’t play by the rules. Maybe they are, in some key way, the most important. Maybe we should let them off the hook.

Monopoly profits are what enable rule-breakers to achieve greatness and technological innovation, allowing them to escape the war of all against all that is market competition and establish more secure forms of dominion. From Zero To One

Americans mythologize competition and credit it with saving us from socialist bread lines. Actually, capitalism and competition are opposites. Capitalism is premised on the accumulation of capital, but under perfect competition all profits get competed away. The lesson for entrepreneurs is clear: if you want to create and capture lasting value, don’t build an undifferentiated commodity business.

… Monopolists lie to protect themselves. They know that bragging about their great monopoly invites being audited, scrutinized, and attacked. Since they very much want their monopoly profits to continue unmolested, they tend to do whatever they can to conceal their monopoly—usually by exaggerating the power of their (nonexistent) competition.

… In business, money is either an important thing or it is everything. Monopolists can afford to think about things other than making money; non-monopolists can’t. In perfect competition, a business is so focused on today’s margins that it can’t possibly plan for a long-term future. Only one thing can allow a business to transcend the daily brute struggle for survival: monopoly profits.

In short then, Thiel sees tech entrepreneurialism and kingship as intimately bound together: acting outside the rules to build the future that no-one else has the long term vision to grasp. “There have to be CEOs and founders. Those people are expected to wear the crown.” Monopoly is what enables you to do things that no-one else can do. Thiel is also a strong proponent of fending off bureaucracy and accountability as long as possible, so that founders can do founder stuff.

Of course, such ideas are not unique to Thiel or Musk. The “Silicon Valley Canon” is substantially made up of texts celebrating the willingness of great men to do great things, bringing together politicians, traditional tycoons and tech founders into a linear history of awesome overachievement by men who dared to do what no-one else would do.

Furthermore, as Thiel acknowledges, founders tend to be extreme outliers who get more extreme over time.

Thinking about founders … the dynamic might work like this. People start out being different. They are nurtured to develop their already somewhat extreme traits. Those traits become more important, and they learn to exaggerate them. Others perceive that inflated importance and exaggerate in turn. The founders thus end up being even more different than they were before. And we cycle and repeat.

Finally, Silicon Valley is highly cliquish. Both Zero to One and Thiel’s lectures depict the tech industry as a place where everyone who counts knows everyone else. Venture capitalists are closely interconnected. Founders and CEO's look at each other with a mixture of respect and jealousy.

Thiel describes how you want to build your company around a ‘mafia,’ and Silicon Valley is organized in ways that are not entirely unlike its Sicilian predecessor in its golden era. There is no central organization, but there are central cliques. You need to be connected to get things done. Ostentatious declarations of friendship and mutual interest go hand-in-hand with indirect threats, and the ever-present risk of betrayal. While the histories of the ‘Paypal Mafia’ do not reveal garrotings, shootouts and dissolutions of the bodies of opponents in acid baths (all part of the history of the Sicilian mafia - I once had to do a lot of secondary research), they are drenched with the sense that the Valley is ‘Our Thing.’ Figures like Peter Thiel and Elon Musk may possibly despise other, but also clearly recognize what they have in common that others don’t.

This is an environment in which ideas and modes of comportment may spread rapidly, both among true insiders, and those who aren’t inside but would dearly like to be. It has been quite entertaining, for example, to see Thiel’s theories of Girardian conformity spread among those who want to signal how hard they conform. And so too for other modes of relating to the world.

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In short then, Thiel - both as reported by Masters and in collaboration with him - suggests that Silicon Valley is a place where being a founder is tantamount to being a king. You have a greater chance of succeeding if you are weird, and if you succeed, your weirdness will likely feed upon itself in feedback loops of positive reinforcement. Finally, it is a closely interconnected social system where the key people are conjoined in a dense tangible clique. They observe each other all the time, and are observed by others for cues of what you need to do to become a made man.

Thiel is, of course, not the only force in Silicon Valley, but he, and other Paypal Mafia members, including Elon Musk, have helped to shape an environment in which we might expect (a) the kinds of kingly notions that Tim talks about to be popular; (b) for personal eccentricities to compound upon themselves into active derangement, and (c) for both kingly ambitions and derangement to spread among a broader group of both principals and observers. And this is what we appear to be seeing.

SpaceX perhaps marks a culmination of the kingly ideal, a moment in which, as Tim puts it, someone like Musk can “raise enormous amounts of capital while freeing himself from any restraints from those who provide it, so that he can spend the proceeds on Mars, humanoid robots, artificial intelligence or whatever next satisfies his ambition.” But it is also the moment in which someone who is visibly profoundly disturbed has briefly become the world’s first trillionaire. And it is one in which others want to copy him.

Bringing together Tim’s ideas with deranged billionaire syndrome helps clarify how the stripping of restraints can combine with circumstances to produce a more generalized frenzy. As Hirschman said, it was the disorderly passions that the classical liberals wanted to escape from. Those passions regularly led to chaos and to madness. And now they are back.

I’ll finish by noting that this is just one aspect of a greater change. Deranged billionaires like Musk and Thiel are both partly responsible for this transformation, and notable symptoms of it. Still, they are not the whole of it. The reason that the SpaceX IPO temporarily succeeded, even though the numbers make no sense whatsoever, is that investment markets too are ruled by vibes. Tyler’s co-blogger, Alex Tabarrok, devoted years of his life to making the case for prediction markets, arguing that they would distill market wisdom into a more general source of knowledge on a multitude of topics. Now they are here, but all too often it’s spirits, not wisdom, that they seem to be distilling. Even more so for crypto. Matt Levine makes a joke about “Bleebzorx Tokens” to explain the worthlessness of memecoins, and someone else invents Bleebzorx Tokens to make a tidy profit.

We live not just amidst the madness of princes, but the madness of crowds. It might be nice for classical liberals to start thinking - and talking - more systematically about what this means for their understanding of the world.

If I wanted to write a cute post today, it would be about the Balogun red card reversal as a synecdoche for Trump’s corrupting influence. And there is a way in which it provides a useful metaphor for something broader. But I’m going to be perverse and contrary, and leave that until the end. After all, the purpose of this newsletter is not to woo readers with up-to-the-minute takes. If we want to really understand corrupting influences, we can’t just look at Trump. We want to pay attention to the current Supreme Court majority too.

You can make the argument that the Roberts Court is a corrupt institution if you want to. Instead, I want to put the motivations of the individual justices, Roberts included, aside, and make the importantly different claim that it is a corrupting institution. Specifically, the last two decades of Supreme Court jurisprudence have tended systematically to corrupt American democracy across a variety of related issues: campaign finance (including last week’s decision), presidential immunity, and, of course, the prosecution of bread-and-butter political corruption.

To understand this, you need to think more systematically about the relationship between democracy and corruption. The best way of understanding this relationship that I know of is laid out in an academic article that was published the year before John Roberts was named Chief Justice, Mark Warren’s “What Does Corruption Mean in a Democracy?" Here goes.

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Mark taught me political theory when I was doing my Ph.D. (I still remember, and regularly quote, his off-the-cuff dictum that Weber’s essay, “Politics as a Vocation,” concealed “diamonds of Nietzschean brilliance in a great bowl of sociological porridge”). His article on corruption starts from the insight that our current understanding of corruption is both too expansive and too limited.

To understand corruption properly, we shouldn’t think of it as an individual level phenomenon. Classical thinkers, like Machiavelli, understood corruption as a condition that could afflict governments and indeed societies. But if we value democracy as the best way to order our affairs, we should understand corruption as not a moral phenomenon but a political one, which involves the corruption of democratic processes.

Specifically, we should understand corruption as involving what Mark calls “duplicitous exclusion.” The most fundamental norm of democracy is “empowered inclusion of those affected in collective decisions and actions,” so that “every individual potentially affected by a decision should have an equal opportunity to influence the decision.” This implies equal power: people should be provided with “individual participation in collective decisions, such as the right to vote.” People should also have equal voice: “equal chances to influence public judgment, actualized in rights and effective opportunities to speak and to be heard in those deliberative processes that define the agendas, choices, and public framing of issues.”

What that suggests is that “the norm violated by corruption is that of inclusion in collective decisions and actions of all affected.” Corruption is not just exclusion, but duplicitous exclusion.

Corruption does not imply normative disagreement fought out in public, but rather a corrosion of public norms by those who profess them. Corruption involves hypocrisy. For an elite (or group or individual) to be corrupt in the democratic sense, it must both profess and violate the democratic norm of inclusion. Thus, corrupt exclusion is distinguished by duplicity, a characteristic that implies not just the possibility of condemnation, but also the possibility of immanent critique: the corrupt can be called to account by their own standards.

It furthermore involves some benefit that is shared by insiders at the expense of some or many outsiders. Such duplicitous exclusion directly corrupts democracy, even when it is facially harmless.

it is the fact of exclusion and the duplicity of justification that corrupts democracy, whether or not specific harms can be identified. What suffers [from] corruption are the political processes and institutions that would, ideally, expose and limit potential harms by including those affected in making collective decisions and organizing collective actions. Importantly, because a democratic conception of corruption focuses on processes, it also highlights institutionalized corruption. Duplicitous corruption can become routine within institutions, usually in the form of dual cultures, one of which pays lip service to the norms of democratic inclusion, and the other which facilitates and justifies corrupt exchanges.

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Mark’s article describes how courts and judges can become democratically corrupt. Again, I want to put that to one side.1 Instead, I think it is useful to ask whether the Supreme Court, as its majority is currently constituted, is democratically corrupting. The answer, under Mark’s definition, is an unqualified yes. And what is useful about Mark’s approach is that it shows how apparently quite different lines of Supreme Court jurisprudence are mutually reinforcing. Across various dimensions, they systematically corrupt the democratic process.

Consider, for example, the line of jurisprudence that has culminated in last week’s decision to overturn limits on the amounts that political parties can spend in direct coordination with candidates. The practical consequence of this is to undermine limits on campaign contributions. In his opinion for the majority, Kavanaugh claims that:

under the Supreme Court’s current campaign finance cases, the only rationale for campaign-finance restrictions is to prevent “quid pro quo” corruption – that is, “contributions in exchange for official action.” … there are other measures in place to prevent such circumvention that do not restrict speech in the same way that the coordinated-expenditure limits do, Kavanaugh emphasized: the base limits on contributions, federal laws that treat “earmarked” contributions as contributions to a candidate, and federal disclosure laws. … most states do not impose these kinds of coordinated-expenditure limits in their elections, but “‘no evidence of corruption’ via circumvention ‘has materialized.’ … Kagan argued in her dissenting opinion that the court’s ruling “ushers in the same opportunities for quid pro quo corruption that the contribution limits were meant to check.”

Properly understanding the relationship between democracy and corruption means that we should not just be worried about direct “quid pro quo” corruption. Allowing those who can afford it to make very large contributions undermines people’s equal opportunity to participate in collective decision making as well as their collective voice. It means that very rich people and organizations will have much greater say in politics than poor, middle class, or even moderately rich ones. Already, 300 billionaires and their close family members were responsible for nearly 20% of campaign contributions in 2024.

Consider too, the 2024 decision that US presidents enjoy “absolute immunity for actions that relate to “core” or “exclusive” presidential powers, [and] at least presumptive immunity for all other “official acts.” This decision has clearly empowered the current president to enrich himself in a staggeringly corrupt fashion, without any plausible means of judicial redress. But that enabling of individual corruption directly contributes to the corruption of democracy too. As Mark describes it:

Consistent with the modern conception, corruption consists in activities by public officials that depart from the norms, laws, and expectations of their offices, from which they realize gains. Government as the trustee and executor of collective purposes is corrupted. Democracy is directly harmed when people lack a collective agent they can trust to execute collective decisions because they are effectively disempowered. Indirect harms to democracy also result: corruption not only leads to inefficient and ineffective government but also produces an atmosphere that is arbitrary, permeated by differential treatment. Under these circumstances, individuals lack the securities necessary for association, pressure, voice, and other modes of citizen participation that underwrite democracy. An atmosphere in which even everyday acts of democratic participation require heroism can induce or reinforce passivity and distrust among citizens. [my italics]

In other words, the presidential immunity decision does not just make it easier for Trump to enrich himself and his cronies. It enables him to remake government into a means for exercising arbitrary power, punishing individuals, non-profit entities and corporations who oppose him, or who simply have things that he wants and refuse to hand them over. That in turn undermines the conditions for democratic association and voice.

The Roberts Court’s long term campaign to defang traditional legal protections against day-to-day corruption enables democratic corruption too. Take, for example, the landmark decision in McDonnell v. United States:

In 2014, Robert McDonnell was found guilty of eleven counts of public corruption for accepting gifts and loans from Jonnie Williams, a Virginia businessman and CEO of Star Scientific. McDonnell and his wife, owing over $80,000 in credit card debt, needed help to alleviate this debt and turned to Williams. Williams promised to alleviate this debt and in return, McDonnell helped Williams get FDA approval for his dietary supplement, Anatabloc, by attempting to persuade Virginia universities to do the necessary research so that Williams’s company would not have to pay for it. As a result of this arrangement, McDonnell and his wife received over $175,000 in loans and gifts from Williams, while McDonnell facilitated meetings between Williams and state agency officials.

The federal bribery statute makes it a crime “for a public official to receive or accept anything of value in exchange for being influenced in the performance of any official act … The Supreme Court rejected the prosecution’s argument that McDonnell’s actions constituted bribery under the federal bribery statute, concluding that McDonnell’s actions did not meet the definition of “official acts.” … Justice Roberts wrote that only formal government actions, such as filing a lawsuit or making an administrative determination, could be considered “official acts.” He went on to say that political courtesies such as “arranging meetings or urging underlings to consider a matter” generally do not constitute official acts, even if the public official receives gifts or money in exchange. The Court conceded that, although McDonnell’s conduct is “distasteful,” the Court characterized this behavior as a type of “condoned politicking,”

Again, this decision very clearly fosters democratic corruption. It actively encourages the kinds of corrupt exchange that Mark describes, in which democratic equality counts for far less than willingness to pay off politicians’ credit card debts. By relentlessly narrowing the scope for prosecution of corrupt acts, the Supreme Court is increasing the perception and the actuality of democratic corruption in American politics today.

Finally, Court decisions that nominally have nothing to do with individual corruption can be democratically corrupting. This applies to the Court’s gutting of voting provisions aimed at ensuring racial equality, which have culminated in a system where the Court is prepared to bless gerrymandering more or less explicitly, so long as it is done for partisan reasons, rather than to provide racial minorities with voice. This has, predictably, led to a gerrymandering arms race, which undermines basic political equality, by devaluing the votes of Democrats in red states and Republicans in blue ones. This, indeed, may be the most democratically corrupting line of jurisprudence that the Roberts Court has been responsible for.

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I don’t believe that Chief Justice John Roberts, or most of his colleagues are personally corrupt, in the sense that they are willing to take bribes [if you disagree, that’s fine, but I’ll ask you not to make a thing of it in comments, since that would miss the actual argument of this post]. However, it seems to me to be indisputable that their jurisprudence has and is doing a great deal to corrupt American democracy.

Mark Warren’s account of democratic corruption is valuable because it explains why various aspects of this jurisprudence have had this joint consequence. Across an apparently unrelated range of issues - campaign finance, executive immunity, political corruption and gerrymandering - the Roberts Court’s decisions have persistently corrupted the workings of democracy, so as to undermine equality in decision making and voice in favor of processes that are both duplicitous and exclusive. Whether this is deliberate, or the consequence of induced myopia, or some combination, is secondary. To adapt the rhyme: One cannot hope to bribe or twist/ (thank God!) the U.S. chief jurist. But seeing what the man will do/ unbribed there’s no occasion to.

There are bits of Mark’s approach that could be updated. Two decades later, it turns out that democratic corruption can be blatant rather than hypocritical. But again, its great value is in bringing the whole together.

And this, at last, brings us to Trump’s efforts to reverse Balogun’s red card. Trump himself has drawn the comparison to democracy in his characteristically perverse way.

President Trump said the U.S. team’s match against Belgium at the World Cup on Monday night will be more fair after his intervention because both teams will have a full slate of players available, and invoked his baseless claims that the 2020 election was stolen. “And we’re going to have a full team, and Belgium is going to have a full team,” he said. “And you know what? If they beat us, then they can be really proud. The other way, if they beat us, we’ll say it was — I’d say— it was rigged, just like the election was rigged in 2020.

Just as the harm of democratic corruption is not individual self-enrichment but the hurt to democracy as a whole, the damage that the corruption of the red card rules will do is to soccer as a whole, weakening confidence in the sport, and corrupting enjoyment of it, regardless of who wins. So too, we should pay less attention to the specific consequences of corruption, instead focusing on the general systemic harms that it does to democracy, undermining a system that should be based on equality with one where clandestine connections and political influence don’t just matter at the edges, but corrode the basic processes that are supposed to provide some minimal guarantee of fairness.

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Paul Krugman gives my and Abe Newman’s book, Underground Empire, a shoutout in today’s newsletter. That reminds me that I’ve been meaning to provide an update on what’s happening to US dollar power in the light of recent events.

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The short version. The Trump administration seems to be abandoning its long-existing weaponization of the dollar against Iran. It is also enthusiastically embracing cryptocurrencies that were already allowing adversaries like Iran to make and receive payments. But it continues to weaponize dollars against allies such as Europe. This is not resulting in direct pushback, but it is leading Europe to embrace alternative payment architectures that will make it less vulnerable to U.S. pressure in the future. The dollar is not being challenged head-on, but dollar based payment systems are becoming ever less attractive to allies, who worry both about dollar based coercion and the instability and crime risks of dollar-based crypto. That will not undermine the dollar on its own, but might open up possibilities if Other Stuff Begins To Happen.

A decades-long policy direction has been overturned

Last week, I briefly explained how Stuart Levey had radically increased pressure on foreign banks to comply with U.S. sanctions. As Abe and I say in our book, Levey’s main target was Iran. Previously, U.S. banks were already prevented from facilitating direct transactions involving Iran. As we describe it:

Countries that bought Iranian oil needed to pay for it. … Previous U.S. sanctions against Iran specifically allowed Iranian companies to conduct so-called U-turn transactions, transferring their money from one non-U.S. bank to another via the dollar clearing system. This exception acknowledged the central role of the U.S. dollar in global financial transactions, and the U.S. worry that other countries might stop using dollar clearing if it became politicized.

Levey, who was the US Treasury Undersecretary for Terrorism and Financial Intelligence began to reverse that, blocking Bank Saderat from using the U-turn in 2006, and gradually extending the ban so that all Iranian banks were blocked from using the U-turn by 2008. This was a very big part of what prompted Iran to come to the bargaining table on its nuclear program. Financial sanctions made it extraordinarily hard for Iran to get paid for oil. As one former US official described it, Iran was “forced to barter oil directly for ‘wheat and tea from India, rice from Uruguay, and zippers and bricks from China.’”

This is changing. The Department of Treasury has issued a general license, allowing the unblocking of “all transactions prohibited by the above-listed authorities that are ordinarily incident and necessary to the production, sale, delivery, or offloading of crude oil, petrochemical products, or petroleum products of Iranian origin” until August 21. In plain language, if you want to buy or sell Iranian oil using U.S. dollars, you are now welcome to do it. If you want to import Iranian oil into the United States, you now have the blessing of the U.S. Treasury. This goes far beyond reversing the U-turn ban, into normalizing Iranian oil transactions on global markets.

The license is a temporary measure - but it is an extraordinarily important one. It’s notable that the U.S. has not revoked it, even while it and Iran exchange physical attacks. If the license does get revoked, it will send a much stronger signal that the deal is dead than desultory exchanges of fire. If it does not, it signals an extraordinary climb-down by the U.S, and there may be more to come.

The U.S.-Iran memorandum reportedly talks about lifting all U.S. sanctions in the context of a full deal. That would require more than unilateral administration promises - some of the sanctions are written into law. But it is hard to see how the U.S. regains full financial authority, even if the Trump administration decides to do another U-turn on its U-turn on the U-turn. After all, there are now other ways in which Iran can get paid for its oil.

The dollar is being weakened by crypto

Iran has already been able to use cryptocurrency to circumvent the US dollar. A few days ago, the Wall Street Journal published a piece explaining how Iran’s Central Bank has been funneling large sums of money through a complex system of crypto transactions involving the crypto exchange, CoinEx.

Since 2019, wallets with an identifiable link to Iran have moved more than $3.84 billion through CoinEx, according to blockchain intelligence firm TRM Labs. Among its dealings, wallets hosted by the exchange have received hacked crypto acquired by Iran’s Central Bank and transacted directly with accounts that U.S. officials have since attributed to the country’s Revolutionary Guard, that analysis shows. Haipo Yang, a former Tencent engineer who runs one of the world’s largest bitcoin mining pools, launched CoinEx from Hong Kong in 2017. In text messages with The Wall Street Journal, Yang acknowledged that the exchange had been widely used by Iranians, but said it doesn’t have a relationship with the Iranian government.

Iran’s complex system for laundering money also relied on two stablecoins, Tether and DAI, the Binance crypto exchange, and a smart contract on the Ethereum blockchain that swapped Tether for a variety of crypto currencies.

Tether and Binance are prominent members of the rogue’s gallery of crypto: Zeke Faux’s great book, Number Go Up, memorably describes Tether as having a business model that is “practically quilted out of red flags,” while Binance had to pay $4.3 billion in penalties under the Biden Administration, and its CEO was convicted of money laundering and served time. Underground Empire quotes DAI’s founder, Rune Christensen, as arguing that DAO had been designed so that “it could never possibly become a tool of financial surveillance and control,” and explains how the notorious Tornado Cash smart contract was built to facilitate the mixing and obfuscation of crypto currencies.

Past U.S. administrations worried that crypto might undermine the U.S. dollar. The second Trump administration has instead embraced crypto. A few months ago, Dan Davies and I wrote a report for the British Council, describing how even before the Iran debacle, Trump administration policy was weakening the dollar. As we said:

The administration has partly abandoned efforts to extend its enforcement capacities to crypto. An internal memo sent by Deputy Attorney General Todd Blanche … instructed staff at the Department of Justice that it ‘will no longer target virtual currency exchanges, mixing and tumbling services, and offline wallets for the acts of their end users or unwitting violations of regulations’ …. Of course, targeting intermediaries for the acts of their end users is how money launderers are prosecuted; on its face, this appears to give these entities carte blanche.

While the Trump administration has sanctioned particular entities for facilitating Iranian transactions, its unwillingness to take general actions against crypto has encouraged the growth of a system that is resistant to traditional financial controls. Notably, the Trump administration pardoned Binance’s CEO, and Trump appears to view crypto as a handy means to enrich himself, his family, and people close to them.

The U.S. is still willing to use sanctions

Of course, the U.S. is still willing to weaponize the U.S. dollar - just not against Iran. Soon after the Trump administration came to power, a former U.S. sanctions official remarked to me that U.S. financial power was now more likely to be used against allies than adversaries. The U.S. has notoriously pursued financial sanctions against judges and International Criminal Court officials for their impertinence in prosecuting Israeli officials and authorizing investigations of CIA “secret sites” in which detainees were tortured. It also reportedly considered sanctioning the French judge who banned French politician Marine Le Pen from politics for five years for misuse of EU funds. Judges and officials who are sanctioned find themselves cut off from businesses that rely on U.S. financial infrastructure. For example, they can’t get Gmail accounts, use Microsoft Office, or use standard credit cards

European officials have so far been unwilling to push back directly, for fear of escalating the fight. As Lindsay Graham charmingly put it, “So to any ally, Canada, Britain, Germany, France, if you try to help the ICC, we're going to sanction you.” But they have become notably more enthusiastic about building alternative infrastructure that would help to insulate Europe against American financial coercion. This plays into international debates over payment systems, including crypto but not limited to it.

From the Trump administration’s perspective, stablecoins that are linked to the U.S. dollar make illicit transactions much easier, but also extend dollar dominance. From Europe’s perspective, stablecoin’s combination of dollar-domineering, criming and possible financial instability is increasingly unattractive in ways that bleed over into more conventional dollar based payment systems.

The European Union’s “digital euro” initiative recently got a go-ahead from the European Parliament, and is explicitly intended to provide an alternative payment system within Europe that wold push back against dollar-linked stablecoins like Tether. Dan and I quote Philip Lane, the European Central Bank’s chief economist, as explaining how stablecoin:

exposes Europe to risks of economic pressure and coercion and has implications for our strategic autonomy, limiting our ability to control critical aspects of our financial infrastructure. When we rely on international cards, apps or stablecoins, we effectively outsource our payment infrastructure.

As Lane suggests, the EU also increasingly views more traditional US linked payment systems, such as Visa and Mastercard as threats as well. And at least one ECB board member foresees the digital euro being attractive outside Europe:

While the digital euro would primarily be used in the euro area, it is worth considering its possible international use. The current draft legislation foresees an approach that respects the sovereignty of third countries, mitigates potential risks for them and offers them new opportunities. ... Moreover, the digital euro’s design includes multi-currency enabling features similar to those of [the ECB’s existing international interbank payments system]. In practice, this means that non-euro area countries could use the digital euro infrastructure to offer their own digital currencies, thus facilitating transactions across these currencies.

The dollar is not in huge trouble … yet

None of this means that the dollar is in great danger of immediate collapse. As Mark Blyth argues in a recent interview, there is a great deal of ruin in a dominant currency. It is hard for others to move away from dollar payments. It will be even harder for other powers to replace the dollar without radical shifts to their own internal economy. The power of the dollar rests not just on dollar based coercion, but also on its central role in transactions, and the need of countries to maintain dollar reserves.

Still, we are in for some interesting times. During the first Trump administration, Abe and I spoke to former officials who had previously worried that sanctions overreach might destabilize the international role of the dollar. They were revising their opinions, now that other countries had not fled the dollar, and more likely to think that there was little risk of blowback from US financal sanctions. It’s notable that the Biden administration was unable to come up with a coherent policy for limits on financial coercion. In the administration’s “2021 Sanctions Review’ ..., the 40-page draft … dwindled to eight pages and contained the earlier document’s most toothless recommendations.”

Now, in Trump’s second go-around, the coercive power of the dollar is being put to a much more extreme stress test. The result is that US allies are increasingly looking to build alternative payment rails, just as adversaries have done in the past. Almost certainly, this is not enough on its own to precipitate a crisis, but it is likely to leach away at dollar power at its edges, and might combine with other crises and U.S. actions (e.g. would the Trump administration extend unlimited swap lines to other countries in the event of a new financial crisis?) to precipitate a more rapid unraveling.

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Below, a post on the Trump-Anthropic fight over Fable, focusing on the generalities (which are more important than you might think) rather than the particulars, which I don’t know any better than anyone who has been following events. If you haven’t been following events, skip down to the first footnote for a brief outline of the facts that don’t seem to be in dispute.1

I’m less interested in the fight itself than the politics behind it. One group of commenters sees the blocking of Fable as an arbitrary exercise of power by an administration that is using export controls to punish Anthropic rather than cracking down on exports of AI chips to China. Another blames Anthropic, saying that the company pressed for regulation of what it itself has described as a dangerous technology, and is hypocritically complaining now that it has gotten what it was looking for.

These two perspectives loosely map onto two broader approaches to AI regulation which are currently struggling for dominance. The first is associated with the past Biden administration and Anthropic itself, and argues that geopolitics and US-China relations make it urgently necessary to regulate the diffusion of AI to make sure that America stays in control. The other is connected to the informal alliance between the Trump administration and the pro-AI, anti-DEI coalition in Silicon Valley, and argues that impeding the development of a transformative technology will carry massive geopolitical and human costs. Both assume that AI will likely have world-changing consequences, but disagree on what to do next.

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There is a third approach that better gets at the underlying problems. It is best articulated in a piece that Alondra Nelson wrote a few months back for Science. Alondra argued that it was a big mistake to think that the Trump administration wanted to deregulate AI. As she put it:

What distinguishes the current [Trump administration] approach is … its character: a greater reliance on executive discretion than on deliberative, public processes. … what it has advanced is not the absence of AI regulation but its rearrangement, often by caprice: intensive state intervention operating through industrial policy, trade restrictions, immigration controls, equity stakes in private firms (selected by the state), the redirection of research funding, and the strategic preemption of state authority.

Perhaps then, instead of shoehorning debate into stylized pro- and anti- regulation positions, we should ask what particular forms of regulation actually involve, and what degree of discretion is associated with them.

Specifically, given what has happened with Fable (and in earlier Trump administration moves against Anthropic), we should pay attention to the tools of national security policy as a mode of regulation. Export controls and related national security tools provide the administration with great discretion in regulating tech. This was true before Trump’s second term: the Biden administration proposed a vast system that would control who had access to AI across the entire planet, which would not be founded on treaties, or even unilateral legislation, but on export controls and executive agreements. It is even more true now.

In the past, this discretion has been deployed in pursuit of a vision of global American technological hegemony. Now, it is being used for very different purposes. What the Trump administration is doing to Anthropic is bad, in the same way that other Trumpian exercises of arbitrary regulatory authority to punish enemies have been bad. Equally, it is the past vision of national security via American power, which Anthropic openly embraces, that makes the Trump administration’s sweeping claims of authority over technology possible. Anthropic is trapped by the assumptions it shares with the administration. It cannot readily push back against arbitrary exercises of export control powers, without recognizing how this arbitrariness is built into the broader framework of national security.

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Alondra’s article highlights the ambiguities of the word ‘regulation.’ People often think about regulation as narrowly involving governing through the predictable application of specific rules. As Alondra suggests, there are many means through which government regulates private sector behavior. My own personal list would also include informal connections, antitrust and other such legal interventions, spending decisions and a variety of other threats and inducements, whether public or private; perhaps that goes too far.

Under any broader understanding of regulation, the Trump administration is not opposed to regulating AI or other private sector activities. It is emphatically interested in controlling what private actors do and say. It just wants to move away from regulatory approaches that emphasize predictability and public or democratic accountability and towards approaches that maximize its flexibility and discretion. Such a shift (a) reflects a notional theory of the unitary executive, under which the president uniquely represents the interests of the American people, (b) allows the administration to undermine and punish actors whose politics they dislike, and (c) allows people in the administration or their friends to pursue private benefit at the public expense while minimizing the opportunity for outside pushback.

That differs in very important ways from how other modern administrations have viewed their role. But - and this is a big but - there are genuine continuities with existing institutional frameworks. Some policy areas are much more open to executive discretion than others. In particular, the zone where national security, economics and technological knowledge intersect has always allowed a great deal of governmental discretion, because such discretion was seen as necessary to the untrammeled pursuit of the national interest.

That applies, for example, to financial sanctions. Abe’s and my book, Underground Empire (obligatory plug: do go buy ) explains how the US employed strategic ambiguity to scare foreign banks and businesses into advance compliance with administration wishes. As Stuart Levey, who used to run the relevant bits of Treasury, described banks’ incentives:

Keeping a few customers that we have identified as terrorists or proliferators is not worth the risk of . . . a regulatory action that may impact on [sic] their ability to do business with the United States or the responsible international financial community.

A major US law firm said that US sanctions rules “at times seem almost purposefully confusing” so that “the strongest impact of these sanctions may be their mere existence rather than their exercise, as highly-regulated and risk-averse financial institutions steer well clear of the line.” The result, as economic sociologists Gregoire Mallard and Jin Sun have described it, is that banks have developed extraordinarily cumbersome systems of internal controls to satisfy U.S. demands for compliance.

Export controls have similarly become a cornerstone of US power. Kevin Wolf, who ran the export controls bureau at the US Department of Commerce, told us how the first Trump administration built up the so-called Foreign Direct Product Rule (FDPR), which would apply U.S. export controls to a much broader range of products made across the world, like financial sanctions. As he put it, “trillions of dollars of transactions, trillions with a ‘T’ ” were affected by a technical rule “that was buried in 9 point font in a footnote at the bottom of a 320 page Entity List.” Weirdly for Abe and me, our ideas were used by a senior official in the first Trump administration to justify this rule change.

Export controls are often specified in much greater technical detail than sanctions, sometimes allowing them to be gamed. Equally, crafting and applying them involves difficult judgment calls. As Mario Daniels and John Krige note in their recent history, Knowledge Regulation and National Security in Postwar America, “to assess how dangerous a technology, if exported, could be, is incredibly challenging.” The result is an incredibly detailed and complex body of regulation, which is based on tricky judgments both of how the technology might be used against the interests of the United States, and of the actors most likely to use it in these ways.

Daniels and Krige emphasize that export controls stem from America’s sweeping vision of national security, which posits that:

the control of intangible knowledge and know-how was the most important function of export controls. They target objects as carriers of “embodied” knowledge that can, for example, be extracted by means of reverse engineering or actively transferred in face-to-face interactions between an American donor and a foreign receiver. Moreover, these targets are assessed not in isolation, but in relation to the technological system in which they are, or will be incorporated. The overriding question is: “would this export help the foreign country to close a gap it cannot fill with its own knowledge?”

In a response, Karen Alter argues that it’s more complicated than this: some US officials recognize that it can be counterproductive to try too hard to control the spread of knowledge between the United States and other countries. But all these authors agree that export controls have the purpose of ensuring continued US technological leadership. Furthermore, Karen notes some agreement with Daniels and Krige:

The far reaches the US government asserts via the deemed export category alarmed the authors, and it will also surprise most readers because the rules apply to all US citizens and firms, regardless of where the sharing occurs. Sharing knowledge with graduate students or foreign colleagues in a US university or academic meeting; international research collaboration with foreign labs or a company subsidiary; working with new foreign owners to help them understand what a US company does; setting up a joint production or licensing arrangement in the US or abroad; even the non-commercial sharing of the ideas and expertise that budding entrepreneurs or researchers generate and own within their very person may be controlled, disallowed, and even criminalized.

To be clear: there are limits. Such controls over conversation are generally understood to be restricted to engineering and technical knowledge: mere social scientific knowledge and ordinary conversation aren’t covered. Daniels and Krige describe how the first Trump administration’s National Security Strategy:

continue[d] to stress the need for deregulation to stimulate exports. But it combines the use of export controls to deny sensitive technology to rivals with a raft of new measures to erect a protective wall around sharing emerging critical technologies and related knowledge with China, in particular.

When the Biden administration came into office, it built upon this approach, creating what then-National Security Advisor Jake Sullivan described in a speech as a “Small Yard, High Fence” strategy, under which China would be denied access to the high-end semiconductors needed to train powerful AI, and other “foundational technologies” as needed. The fence that was supposed to deny China access was mostly made out of export controls.

As Trump was preparing to come into power, the Biden administration proposed an extraordinary plan to use export controls on semiconductors and AI model ‘weights’ to control the development and use of AI across the planet. The entire world would be divided into three different zones - close friends and allies, which would have more or less unrestricted access to AI, competitors and enemies who would have none, and a large intermediary zone of countries with initially limited access, who could negotiate with the US for better arrangements.

Like many other exercises of US technological power, this plan depended on a complex mixture of detailed technocracy and high discretion. Biden administration officials hoped that extraterritorial export controls would allow the US to leverage the US head-start in AI, building an enduring system of global control over future development of technology, while providing officials with substantial discretion to cut specific deals with other countries, such as the Gulf States, which wanted more access to AI.

The Trump administration, however, declined to take up this detailed technocratic plan to impose a system on the rest of the world, in favor of its own vaguer but equally sweeping ambitions for AI “dominance.” It has no principled objection to sanctions and other tools of economic coercion, although officials express their contempt for the moralism that has inspired their use in past administrations. Instead, the current administration cares more about short-term deal-making and breaking, and raw exercises of power. It seems at least as interested in subduing its domestic enemies as in coercing adversaries abroad. Both are means towards the end of remaking a world so that the administration and its friends are in control, and others either have to supplicate them or suffer the consequences.

Hence, the administration is less interested in further cutting off China from AI, especially after China has demonstrated its ability to cut off the supply of rare earths that US manufacturers care about, than in figuring out deals. The Biden administration wanted to use AI to bind the Gulf States closer to the US, and further from China. The Trump administration has looked to cut them into the bargain, in return for general and particular concessions. Externally, AI is another means of leverage to exploit as the administration tries to make one-sided bargains. Internally, it would like to adopt AI to replace bureaucracy with all its human inconveniences. It worries about the AI labs as an alternative power base, and is especially concerned about Anthropic because of its connection to the past administration and loosely liberal politics.

*****

Thus, the Fable fight is part of a bigger struggle. Both of the two dominant approaches to regulating AI believe in continued American technological hegemony. Both tend to be bullish about the potential of AI to radically transform society. They disagree on whether it is better to build global power through painstaking technocracy or through deals based on self interest, and on what should happen on the home front.

As already mentioned, the Biden administration enthusiastically embraced the first Trump administration’s expansion of export controls to cover actors outside the US, and deployed it systematically to stifle China’s AI ambitions, through restrictions on high end semiconductors. As Graham Webster describes it, officials feared that authoritarian governments might use AI as a tool of widespread control. In part, they worried that whoever got first to ‘recursive self-improvement’ (AI that could make itself better in a feedback loop of self-reinforcing awesome), would be able to shape the destiny of the world.

The stakes were especially high, some believed, because a powerful AI system might be used to develop even more capable AI systems, compounding a country’s lead and leaving competitors not just incrementally behind, but wallowing in a bygone paradigm. If some of these fears sound vague or far out, that’s because they are. Policymakers, however, are forced to take action in the face of uncertainty, and here, the uncertainty itself was cause for alarm.

That led them to embrace export controls as a tool of global management, hoping that they could keep China behind for just long enough to make the necessary difference.

the US government found the FDPR irresistible. It would … eventually wield it to constrain high-powered computing in China. “Obviously we started using it like candy,” says Estevez. “Certainly threatening to use it if not actually using it.”

The Biden administration’s belated sweeping plan to remake the world, using export controls to subordinate other countries to America’s technological hegemony, was a culmination of this approach.

Now, the Trump administration is more interested in deals with side-payments than in constructing a global empire of technocracy. It wants instead to use national security tools to subordinate American companies. First, the US Department of Defense designated Anthropic as a supply chain risk - a tool that has hitherto been deployed against non-US companies - because it refused to revise a contract that prevented its models from being used for autonomous weapons or for domestic mass surveillance in the US. As Dean Ball (who was the White House AI advisor for the first part of this administration) described what happened:

Anthropic was the company most enthusiastic about these national security uses, and they came to an agreement with the Biden administration … the Trump administration agreed to those restrictions, as well. Then in the fall of 2025 … Emil Michael as under secretary of war for research and engineering…. comes to the conclusion that no, we cannot be bound by these usage restrictions. The objection is not so much to the substance of the restrictions but to the idea of usage restrictions in general. So that conflict actually began several months ago.

That is how and why the US government has gone after Fable. Supply chain risk designation and export controls authorities most certainly cover technologies like AI - indeed it is hard to imagine a technology that is more precisely a “carrier of embodied knowledge” than a frontier model - but they are not supposed to be used for domestic control. However, because national security authorities are quite open-ended, they provide the executive branch with a lot of discretion to go after domestic actors whom it doesn’t like. The result is that export controls and related measures are being used to shape domestic politics in Trump-friendly ways.

People clustered around the Biden administration-Anthropic axis argue that something has gone wrong when the Trump administration goes after Anthropic, while apparently slow-walking many of the Biden era’s measures against China. Under their understanding, the US is misusing these tools, neglecting actual national security threats in favor of notional ones.

Others such as Dean - who has just moved to a political/strategic position at OpenAI - do not fully embrace the administration’s approach but say that it is understandable, since they believe that AI is a fundamentally world changing technology.

Everything the U.S. government was communicating, in policy and in rhetoric, seemed to suggest “go ahead, release your model!” And yet common sense would dictate otherwise. Anthropic is still in the midst of a heated dispute with the Department of War about that agency’s decision to label Anthropic a supply-chain risk. Bitter disputes about policy and politics between the Administration and Anthropic remain unresolved, among them export controls, federal preemption, and the general reality that Anthropic supports Democratic candidates for office while Republicans occupy the seat of power.

Of course they needed to tread carefully. What the law says does not matter. What Administration officials argue on one day does not matter. Anthropic is a political enemy of this Administration, in part because they have explicitly chosen to make themselves one. …

The stark reality is that making superintelligence is a profoundly political act even in the healthiest of societies, to say nothing of the filthily political world we Americans currently inhabit. A model like Mythos goes beyond being a mere political act and implicates the sovereignty of the state itself. No company gets to shake the foundation of state sovereignty while staying blithely above the raw reality of politics.

It is unusual for a sincere classical liberal to defend an administration exploiting regulatory ambiguity to go after its “political enemy” on the grounds that “[w]hat the law says does not matter. “ The presumable justification is that AI is in that small class of technologies (e.g. nuclear weapons) that are so powerful that private companies, especially one that “supports Democratic candidates,” cannot be allowed control.

That seems a questionable way of thinking about the politics of AI, but it is startling that so many of the underlying premises are shared with the arguments of a blogpost that Amodei put up shortly before the launch of Fable. AI is set to transform national security.

Mythos Preview scrambled the global cybersecurity landscape. But its broader significance is that it proves beyond doubt that AI models are now tools of global and national strategic consequence.

And it needs to be regulated.

I believe the best analogy, at least at the current stage of the exponential, is to cars, airplanes, or drugs—powerful technologies essential to the modern economy, but capable of killing large numbers of people if designed or operated poorly. I therefore believe we should model AI regulation on agencies like the Federal Aviation Administration (FAA). Frontier AI models, like airplanes, should be required to go through technical testing and auditing, and their release should be blocked or reversed as a threat to public safety if they do not meet high standards of safety [emphasis in original]. I am grateful to see the Trump administration’s Executive Order move incrementally towards a greater role for government in AI, though Anthropic’s proposal recommends even further action.

To be clear: it would be completely unfair to claim that Amodei was begging to be export controlled - he was calling for the careful construction of ordinary bureaucratic institutions rather than for sweeping seat-of-the-pants national security decisions by the executive. But when Amodei writes that:

US export controls on frontier chips and SME to China have been a major contributor to the US’s overall lead in AI, and these policies need to be expanded, tightened, and coordinated with other likeminded states.

he seems to be suggesting that export controls and other national security authorities are absolutely fine for China. It’s when they are applied to Anthropic (or, more generously: American and likely allied companies that are not looking to cooperate with the adversary) that something has gone wrong.

And this gets to what I see as the heart of the matter. National security tools like export controls and supply chain risk designations are relatively unbounded. That makes them very attractive to the current administration which, as Alondra says, wants to regulate in ways that maximize its discretion. And these tools are likely to become more attractive soon. If the Republicans lose one or both houses of Congress in November, as seems likely, the administration will find some of the means that it is using harder to employ. The president’s foreign policy powers as commander-in-chief - and willingness of courts to defer to them - have always been substantial, and have grown over the last couple of decades. That suggests that we are likely to see the Trump administration using national security powers more, and possibly much more, after November, to pursue domestic goals and punish domestic enemies.

Such overreach can be fought - possibly successfully - in the courts. On the one hand, courts tend to defer to the president on many national security issues. On the other, of the Achilles’ heels of the whole economic security apparatus is that large parts of it are built upon authorities that have been stretched, and stretched, and stretched some more. The foreign actors who have been the typical targets have often not wanted to appeal, because they haven’t fancied their chances in US courts. That might change with plaintiffs like Anthropic (and in so doing, reshape what the US government can and can’t do). But courts tend to work slowly, especially on sensitive matters. Victories won through the legal system may come too late to make a real difference.

The use of such powers puts both sides of the existing debate in an awkward position. I believe that Dean (who I know slightly) is sincere in his arguments, but they depend both on his enthusiasm for unitary executive theory, and his belief that current AI is, or is about to become, so powerful that it’s going to sweep traditional forms of government away. I think that Dean is straightforwardly wrong on both - but even if he is not, does he really believe that the Trump administration will confine its use of these tools to Anthropic and other AI companies? The logic of his position that perceived enemies of the administration, including companies that support “Democratic candidates for office,” can place no faith in the law, goes in obviously problematic directions for classical liberalism, which has typically been understood to imply the need to defend a genuinely plural society against the incursions of the state.

The implications for the other side are more subtle, but quite as damaging. The standard approach - as Amodei’s own writings repeatedly make clear - is that you can have two great things at once. You can build up a thriving democracy at home, regulating AI carefully to avoid existential risk and support democratic institutions, and you can use your awesome national security powers abroad to stunt the technological development of authoritarian adversaries.

I think that this formulation was already in trouble, in a world where China is clearly capable of building up a large array of technological advantages regardless of US coercion. But it is now being undermined from inside too, as the second Trump administration is beginning to turn the national security state against domestic enemies.

What is now becoming obvious is that the Amodei and Biden administration position that you could have your cake and eat it too, depended on a semi-explicit consensus on what US national security was, and how sweeping powers with ambiguous constraints could or could not be used to pursue it. That consensus has now shattered, and it isn’t plausibly going to be rebuilt. Strengthening powers such as export controls without very careful design (and I am not sure that they can be so designed) will strengthen the present and future abilities of illiberal and antidemocratic officials to deploy these powers against domestic as well as foreign adversaries.

These and other related tradeoffs are likely to get sharper over time. The United States has a set of national security institutions that are purpose-built for a dominant power, but the United States itself is now clearly in relative decline. Its ability to use these institutions against foreign adversaries will dwindle. Its ability to deploy them against perceived domestic enemies will not shrink to nearly the same extent. We need to think more seriously about the problems that this will create, and indeed is already creating. I’m not seeing much of that thinking yet.2

Addendum: This, from Ganesh Sitaraman and Tim Meyer is extremely useful:

To date, AI companies have wanted an unregulated federal regime – and they have even pushed for a ban on any state regulation of AI. But the demand for regulation is like water: it has to go somewhere. Frontier technologies like advanced AI models raise too many policy considerations–to say nothing of the economic competition between technology firms both within and outside the United States–for policymakers to simply turn a blind eye.

In practice, the failure to regulate economically and politically significant developments means that we will get presidential regulation, an idiosyncratic and non-transparent or procedurally irregular system of regulation that will oscillate based on who is president, which company is at issue, and the particular issue. To the average American, it will seem much more like rule by fiat than the rule of law.

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The SpaceX IPO is today: here’s a paragraph from the rather remarkable SEC filing.

we have formed the most ambitious, vertically integrated innovation engine on (and off) Earth with unmatched capabilities to rapidly manufacture and launch space-based communications that connect the world, to harness the Sun to power a truth-seeking artificial intelligence that advances scientific discovery, and ultimately to build a base on the Moon and cities on other planets.

A co-author and myself will soon have more to say about the science fictional aspects, which most certainly don’t end with “cities on other planets.” This is almost certainly the first major IPO prospectus that requires a definition in its glossary for Kardashev II Civilization.

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But the document also serves as a prime example of what Quinn Slobodian and Ben Tarnoff call “Muskism” in their new book, Muskism: A Guide for the Perplexed. They suggest that just as we thought of classic mid-twentieth century producer capitalism as Fordism, we should think of the new approach to economic organization that Musk and others are trying to put together as Muskism, and start figuring out how it works.

Slobodian and Tarnoff explain how Muskism involves both a particular approach to organizing physical production, and exoticized human-machine feedback loops. The former is briefly identified in the chunk of SEC filing above, by the four words describing Musk’s actual engineering approach: “vertically integrated innovation engine.” The rest of the text exemplifies a particular example of the latter: propagating a mythology of the future that is in fact a promissory note that you can turn into financial and political capital today.

Both are important. The vertical integration is as much a geopolitical as an engineering strategy, and shapes the specific ideas that get propagated. Equally, if you focus just on the engineering, you’ll miss out on the crucial role of cybernetic feedback circuits in shaping both the political and the economic project. Gigafactories are infrastructure, but as Slobodian and Tarnoff provocatively say, “trolling is infrastructure” too.

So below is a piece that is not a real review, but my own response to the book and where the project might go next. The two sides of Slobodian and Tarnoff’s argument address topics that I have been fascinated with for years, but have never been able to join together: geopolitics and political economy on the one hand, and the consequences of technology for democratic politics on the other.

Hence, I focus on the bits of the book that are close to my own obsessions, disregarding all sorts of interesting pieces of information that don’t fit. The purpose is to pull out ideas about the broader political economy that we might be able to build by thinking more clearly about the incoherence of Muskism, rather than the aspects that seem to fit together. As Slobodian and Tarnoff discuss throughout, Muskism also involves the increasing integration of infrastructure businesses with the state. How do ideology, production and state hybridization fit together? What is most valuable about the book - for my selfish purposes - is that it pushes us to start asking these questions. Equally, just as you had to move beyond Henry Ford to think about Fordism, mapping out all of this will require us to ask what Muskism would look like without Musk.

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Much of the first half of Muskism is about Musk’s approach to physical production. Some of the story has been told before - lessons from Silicon Valley; fail, iterate, fail better, eventually succeed; the move away from waterfall approaches (plan everything from above) to agile development (keep on revising the relationship between goals and means). What is new and extremely interesting to me is the relationship that Slobodian and Tarnoff identify between Musk’s approach to vertical integration and geopolitics.

The standard story we tell about high tech manufacturing in the early 2000s is all about outsourcing. Abe and I use semiconductor manufacturing as our example in Underground Empire - the modern semiconductor industry starts from the belief that it makes sense to separate design from manufacture, which has led to a complex production network involving myriads of separate firms. Much the same is true for the manufacture of laptops, iPhones or many other complex products. All of these involve contractors and subcontractors, engaged in an intricate dance of production.

Musk’s companies have tried, as much as possible, to take just the opposite approach. As Slobodian and Tarnoff describe it:

Musk’s drive to reduce his reliance on external suppliers and to concentrate production as much as possible within the walls of the firm cut against the globalizing currents of the 2000s, which positioned the factory as a node within an international production network woven together through supply chains. Muskism, by contrast, envisions the factory as an enclave.

For example, Tesla’s “Gigafactories” were intended to liberate Tesla from reliance on external battery manufacturers. Musk’s insistence on control meant that his companies were better insulated from geopolitics than many competitors. Equally, it sometimes forced him to make awkward choices. Tesla built Gigafactories in Texas, Shanghai, and then Berlin, giving him footholds in each of the major power blocs.

But if from one perspective, Muskism is a series of islands of production in different geopolitical zones, from another it’s an enclave that was built inside the confines of the American state. SpaceX had its origins in an effort to break away from the existing, heavily regulated approach that NASA took to spaceflight, and to the domination of the ‘primes’ - the big defense companies that understood the byzantine contracting procedures of the US national security state, and could navigate them. Vigorous legal activism and friends in high places allowed SpaceX to get contracts, and work actively to reduce costs by remaking the production process. As Slobodian and Tarnoff accept, this did result in real efficiency gains, while increasing the power of the private sector.

Admittedly, the company conquered the market in large part by achieving a dramatic reduction in launch costs. … But this cheapness came with a cost: the state would eventually cede its sovereignty to such a degree that it was forced to buy it back in increments from a corporation.

SpaceX’s launch model led to the Starlink satellite network. That in turn became “indispensable” to modern militaries, obliging then Undersecretary of Defense Colin Kahl to beseech Musk personally to allow Starlink to be used by Ukraine.

But Muskism is more than the relentless pursuit of efficiency. As the SpaceX SEC filing suggests, it has a strong ideological element too. Slobodian and Tarnoff say that Musk has long “spun persuasive science fictions to win the confidence of his investors.”

“Like the Soviet state dangling the promise of a radiant future in front of its tired citizens,” the critic Phil Jones observed, “Musk’s success is sustained by predictions of a technological sublime that’s only ever another decade away.”

They describe how Musk was eaten by the attention economy even as he was trying to devour it. I’ve paid attention to Musk’s relationship with the attention economy over the last few years, but I still learned quite a lot from Slobodian and Tarnoff’s telling of it.

Dogecoin provided a kind of entry drug - a joke cryptocurrency whose only value was what people attributed to it. Musk’s half-mocking enthusiasm helped pump up its price. Memes became ever more central to Musk’s self-image - as did half-baked cybernetic theories of how the circulation of beliefs and information might provide a collective countermeasure against evil AI. And then Musk began worrying about cybernetic contagion (he was latching onto a much older idea1 ), theorizing that anything that upset his preferred hierarchies was an example of the “woke mind virus,” which threatened to destroy humanity.

When Musk bought Twitter and turned it into X, he had his engineers goose the algorithms to ensure that people were relentlessly exposed to the prophylactic of his own received truths. Next, there were various amateurish efforts to re-engineer the Grok model so that it would deviate from its purportedly woke training data.

The general consequence has been to create ever more deranged feedback loops between Musk and the information structures that he has created, as illustrated by this New York Times article from last year. I’ve recently been re-reading a lot of Philip K. Dick for reasons, and this bit from The Transmigration of Timothy Archer sticks out:

he simply recycles his own nutty thoughts forever, enjoying them even though, like transmitted information, they degenerate. They become, finally, noise. And the signal that is intellect fades out.

Just so, except that Musk doesn’t give the impression that he is particularly enjoying his recycled thoughts. His own form of degeneration is darker and its consequences more vicious, despite the rhetoric about humanity’s destiny amidst the stars.

These two quite different tendencies - engineering for optimality and social media-driven promises of a radiant future - came together in DOGE, which both purported to remake American government on the basis of private sector efficiencies, and was named after a meme. The first is described by Sam Hammond of the Foundation for American Innovation in his encomium to “DOGEmaxing”

I concluded that, if we were ever going to transition to a more libertarian form of government, it would be essential to first use information technology to improve and streamline core government services in a way that creates space for crowding-in privatized forms of governance. … just as Marc Andreessen said “software is eating the world,” perhaps software will eventually eat the state. And nearly a decade later, it seems like this strategy for disrupting bureaucracy is finally coming to fruition in the form of Elon Musk’s Department of Government Efficiency.

The second is what we actually ended up with - a chaotic process of lopping off core aspects of government functioning that often seemed to be driven by whichever pustule of idiocy and malevolence had most recently appeared on Musk’s social media feed. Slobodian and Tarnoff conclude the last substantial chapter by saying that you can read the brief, sordid history of DOGE either as a story of overreach, in which Musk’s celebrity was incapable of transforming the state, or as a symptom of a deeper structural story, in which Palantir and Musk are nonetheless succeeding in reshaping the state in their image.

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Slobodian and Tarnoff’s final chapter provides four stylized accounts of where Muskism might go, each based on an exaggerated form of some particular element in their account. Another approach might be to ask how different elements, such as production, ideology and state fusion interact with each other. My best guess is that Muskism is more fragile than it might seem, and that the most likely place to discover fragilities is the crude joins between these different aspects.

Musk’s vertically integrated production model has insulated his companies from some geopolitical risks, so that they have adapted more quickly to a world of mutually suspicious sovereigns than many of his competitors. Equally, it carries its own risks and contradictions. Having factories in China and the EU as well as the US gives Musk greater clout, but also exposes him to a variety of governments, each with its own interests, each jealous to some greater or lesser degree of the others.

This has not been as much of a problem as it might have been thanks to Musk’s fraught but continuing alliance with Trump. Other countries that might otherwise want to press Musk, or even exclude him from their markets have to worry that they will find themselves on Trump’s shitlist.

The current situation of the world - enough geopolitical risk that complex supply chains are not the miracle of efficiency that they once seemed to be, but not so much as to actively endanger Musk’s companies in other parts of the world - seems well calibrated to Musk’s interests. He wants enough risk to drive people to rely on his island fortresses, but not so much that he can’t build or maintain them. But this temporary balance probably isn’t politically stable. As geopolitical tension accelerates, it becomes harder for Musk to straddle horses, forcing him to double down on American imperial hegemony.

That creates its own risks. Obviously, other countries may view Musk’s infrastructures as dangerous, fearing that they may be used against them. They have few alternatives to Starlink right now, or to SpaceX’s industrialized launch capabilities. But they are trying to build them, and may be able to substitute for other aspects of Musk’s empire, including the AI that is the purported source of SpaceX’s profit model. No-one - not even in Trump’s government - wants to use Grok if they have an alternative.

So too perhaps at home. Governments - including the US government - are increasingly open to the idea of nationalizing essential parts of economic infrastructure. Manufacturing, space launch and, as J.S. Tan and Kathy Thelen have argued, modern AI all involve big, physically immovable investments that can rapidly become captive assets if government becomes unfriendly. There is a lot of talk about moving data centers to space. One of the informal arguments I’ve heard bruited is that space based platforms might be less vulnerable to terrestrial government aggression, building on a somewhat different set of science fiction mythologies (Robert A. Heinlein and others on LIBERTARIANS IN SPAACCE!) than the cosmic destiny tropes.

All this is held together by an ideology that seems to be at its peak right now. The SpaceX IPO marks the massive expansionary inflation of an entirely imaginary universe. As far as I can tell, no-one actually believes that SpaceX is going to capture its roughly-$23 trillion “total addressable market,” which as Matt Levine points out is “perhaps 20% of the world’s economic output and perhaps 40% of the revenue of the world’s corporations.” But there are lots of people who are willing to go along for the ride for the moment, as long as other people are willing as well. How long can that last? What will happen to SpaceX and Musk when it begins to fall apart? The Musk bet seems to be that he can make himself an essential enough part of the world’s global economic infrastructure by the time that the crash happens that it won’t matter. A lot of things will have to go right for this to be true.

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This then suggests a broader agenda for figuring out what is happening in the world right now. What is most valuable in the long term about Slobodian and Tarnoff’s perspective is what they really don’t have the space to discuss properly in a short book that is aimed at a broader audience. They are emphatic in arguing that Muskism is a phenomenon that is broader than Musk himself, but they don’t have much room to talk about the non-Musk aspects. Fordism too was about much more than the vagaries of Henry Ford, who, like Elon Musk, was a deeply weird and unpleasant dude, with vicious conspiratorial beliefs. Some aspects of Ford’s approach failed (his desire to control every last aspect of the private lives of his employees). Some spread and became generalized (as aspects of mass production). Some led to compromises such as the grudging accommodation with unions that Ford himself would have absolutely hated.

It’s hard to even begin to articulate this question on a day where on the one hand Musk is enjoying his stock market apotheosis, and on the other is doing everything he can to stir up race riots. But what would Muskism look like without Musk? I take Slobodian and Tarnoff’s ultimate lesson as being that we need to move beyond Musk’s personality, and start thinking about Muskism or Muskismus (I like the German word, which is why this post has the German translation’s cover) as a mode of organizing production, as a generic ideology, as a set of political bargains, as a form of state-business fusion, or some weird amalgam of all four. If Muskism is going to change the world as its backers hope, it is highly unlikely to be because SpaceX manages to corner the entire global economy. If it fails, as I personally suspect it will, it is going to be because of the underlying contradictions that are getting papered over.

To figure this out, we might begin with the other businesses that seem to exemplify Muskism. Obviously, this would include Palantir, and a bunch of the defense-tech businesses funded by Musk’s adversary Peter Thiel. Thielismus starts from many of the same premises as Muskism, but with a different clatter of tacked-on lunacies (less cosmism; more prophecies of the Antichrist). Are there businesses that adopt some of the aspects of Muskism that Slobodian and Tarnoff acknowledge as useful (SpaceX has transformed the launch business) without all of the negatives? It would be useful to know: the waterfall approach to project management has not been good e.g. for Europe’s defense sector.

We might also want to ask whether Muskism is inextricably intertwined with US hegemonic power. What happens to the Muskist project if US hegemony fails? What happens to US hegemony if Muskism fails? How does Muskism compare to e.g. the explosion of Chinese domestic manufacturing, which applies sometimes similar ideas in a very different political context? Is small-d democratic Muskism a contradiction in terms? If not, what would it look like? If so, what are the democratic alternatives that might press back against Muskism, and what opportunities and tradeoffs do they represent?

And so on. We are in a world where an enormous amount is up for grabs. Muskism, across its various dimensions, is a project for grabbing as much as possible before anyone else figures out how to push back. Slobodian and Tarnoff’s book is valuable both in identifying the contours of the problem, and setting out an agenda for a broader political economy of the world that is taking shape today, right around us, that might provide maps for action.

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No new post this week - I’ve got an unexpected short term writing deadline. In lieu of that, I’m republishing (with tiny updates/edits) one of the best short pieces of criticism that I think I’ve ever written, on William Gibson’s novel, The Peripheral.

I’ve been thinking of putting this up for a while, but was pushed into doing it now by Andrew Brown’s complaints about Gibson’s greatly inferior sequel, Agency. In retrospect, Agency is a book of the short period when many people believed that you could return to a timeline in which everyone could see that Hilary Clinton ought to have won, if it hadn’t been for social media manipulation. This watered down the bleak realism of The Peripheral, which better describes the future we have found ourselves in. Warning for those who haven’t read the book: there are plenty of spoilers.

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William Gibson’s The Peripheral time is the best novel of his late period, and in my view, the best novel that he’s ever written. It doesn’t have the shock value of Neuromancer (which blew my mind when I read it at the age of fifteen, in a small provincial town in Ireland). However, it’s a much better novel. The Sprawl books are all opaque and dazzling mirrorshades – the surfaces of high-gloss people reflecting the surfaces of high-gloss objects that reflect the surfaces of high-gloss people. The not-quite-science-fiction novels he was writing for a decade or two take the givens of the Sprawl books as a problem, engaging in a kind of archeology of objects and brand names, and how they reflect both the vast systems around us and our individual desires. I like them (they combine the intelligence of Don DeLillo with much of the warmth of Philip K. Dick), but I like his short book of essays, Distrust That Particular Flavor even better (it’s a book full of insights, which, like Borges’ version of Kafka, generates its own predecessors). The Peripheral returns to science fiction – but a science fiction that very clearly reflects present day concerns.

Gibson presents two timelines – one sort-of-nearish future, one several decades out again. They’re connected in some science fictional way that is never explained. The people in the further future are somehow able to access the past timeline (maybe the past timeline is a simulation so good that it’s effectively real; maybe it’s a parallel universe; nobody knows or seems to care particularly1). Physical contact between the two universes is impossible, but quite sophisticated forms of information can go back and forth, allowing people from the further future timeline to intervene in what used to be their past (as soon as they start intervening, the past starts to develop along a different path than the one that they know, becoming partly unpredictable).

What’s interesting is not the technology (which isn’t even a macguffin), but the uses that it’s put to. Gibson acknowledges the influence of Bruce Sterling and Lewis Shiner’s short story, “Mozart in Mirrorshades,” which depicts a future that uses alternative past timelines as a resource. I would guess that Paul McAuley’s criminally under-appreciated Cowboy Angels (in which an America on one timeline effectively colonizes and exploits other versions of itself in other timelines; our timeline is called the “Nixon sheaf”) is another significant influence. McAuley is thanked as an advance reader in Gibson’s acknowledgments. But Gibson doesn’t want to pursue the general questions of cultural appropriation that Sterling and Shiner’s story talks about, or the Cold War politics of McAuley’s book. He wants, I think, to talk about the relationship between the 99% and the 1%, using science fiction to turn the social relationships that Piketty and Saez talk about into a kind of ontology.

The farther future is one in which the 1% has won and become a global ruling class. A set of events called the “Jackpot” (a combination of environmental, technological and social failures) has led to most of humanity dying off. The results of the jackpot were rigged by the usual structural inequalities; those who were already rich and well connected were likely to survive; while those who weren’t so privileged mostly disappeared. This future is dominated by “klepts” (kleptocratic clans), the guilds of the City of London and the like, with the remnants of the state serving not as a restraint on the powerful but as an artifice for balancing between them (the politics is out of Engels via Poulantzas, with perhaps a touch of Wallerstein embedded in the pun in the book’s title). There may be ordinary people in this future, but we don’t see much of them; those we do see are the powerful and their higher servants (who have privileges, but only on the sufferance of those greater than they).

The nearer future timeline is set in a rural America where the real economy has collapsed, leaving people to survive making illicit drugs and working dead end jobs for homeland security (America’s comparative advantage turns out to be in meth, not music, coding and pizza-delivery). In this timeline, we don’t see the 1%, although they’re there in the background. Instead we see the kind of people who are about to be left behind and perish in the Jackpot.

Hence, the science fictional trick of The Peripheral, which is to turn the separation between the 1% and the 99% into a metaphor of physics (or, perhaps, information). The two literally live in different universes. They can perceive each other; they can act on each other to some degree (through proxies enabled by the exchange of information); they cannot physically touch each other. The rural America timeline is a curiosity owned by a minor member of a kleptocratic clan. A few people in it become significant by accident – one of them is operating a remote security drone in the further future timeline, and witnesses an important murder. A group of people who were peripheral, who were, indeed, toys, become important for a short period of time.

The result is a dark comedy, played with a very straight face. Two different factions start manipulating the entire world economy of the past timeline in order either to kill or to protect a tiny group of individuals in a small and depressed corner of rural America. One of these factions certainly seems nicer than the other (although that’s in doubt at some points in the narrative), but it’s not at all clear that its interventions will work out well in the longer run. At the very best, it’s acting like a Western aid organization in Somalia, trying to improve things a little, profoundly disrupting local economic and power relations simply by virtue of being there, and hoping that the goodies it brings will be used for socially beneficial purposes and not to enable ‘technicals’.

The novel finishes with something that plausibly resembles a happy ending for the individuals involved – complete disaster is averted, friendships are maintained across the barriers between the twin universes, and a few sympathetic poor people become rich and powerful. There are relationships, and one pregnancy. But the larger story is one in which nothing really changes. Perhaps the Jackpot (which is a lovely metaphor for the arbitrary-but-not-random rigged game through which people become or don’t become members of the elite) won’t be quite as painful, thanks to the intervention of benign overlords from the future. Even so, the one universe is still a toy of someone in the other. With less benign owners, things would be very different. The world depicted in The Peripheral is one where the best we can hope for is that our masters will be motivated by paternalism or benign neglect. That’s not an especially hopeful vision.

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Above is a video-format coda to the AI as Social Technology paper that Cosma and I wrote, drawing on work with other collaborators too. I spent last week at Oxford’s Blavatnik School, where I gave the Astor lecture on AI as Social Technologies. I didn’t realize that they were recording it, but it’s now up on YouTube. If you’ve read Cosma’s and my paper, you’ll have a good idea of what it says - it does include some very brief discussion of how our argument applies not simply bureaucracy but to democracy and markets too. When we wrote our original paper, we were planning to do all three, but then discovered that just doing bureaucracy on its own took more than 10,000 words, and since we had not been commissioned to write a short book …

Anyway, enjoy and of course feel free to share.

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Here’s another data point about the relationship between AI and organization. While rightwing politicians in other countries are fantasizing about DOGE-ing their civil service and replacing large swathes with AI, businesses are boasting about what they have already done.

Last Saturday, Matthew Prince, the CEO of Cloudflare wrote a self-congratulatory op-ed in the Wall Street Journal, suggesting his company was the only one in recorded business history to grow by 30% while laying off more than 20% of its employees. His message was that everyone needed to follow his example, by using AI to implement the True Wisdom of Revered Management Guru Peter Drucker.

It’s worth quoting Prince’s arguments at some length:

what we did is likely going to become the norm over the next year. This is a story about artificial intelligence, but executives and commentators are misunderstanding how it will disrupt business and who will be affected. To understand the issue, I went back to a book published in 1954, 20 years before I was born: Peter Drucker’s “The Practice of Management.” Drucker explores the different roles inside every business, which I would categorize as builders, sellers and measurers. Builders create products. Sellers sell those products. Measurers do everything else: internal audit, revenue recognition, finance, legal, compliance, middle management, operations and on and on. … builders aren’t going anywhere. … Sellers, too, are safe from extinction. … Measurers are also critical to a business, but different from the other two. …

Drucker argues that measuring business is important, but customers are earned through building and selling. The best businesses would maximize investment in those two functions. AI isn’t coming for builders or sellers, but it is coming for measurers. … AI won’t kill all jobs. But it will change every business. Ultimately, it will prove Drucker right. AI will allow us to better measure our organizations so the humans on our teams can focus on where they create and capture value: building and selling.

Matthew Prince is right about one big thing. You should absolutely read Peter Drucker’s The Practice of Management if you can. But while I presume that Prince is telling the truth about reading and re-reading Drucker, he doesn’t seem to have really understood what Drucker actually wrote.

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Prince’s Peter Drucker wrote a book about how building and selling are crucial, and new technologies such as AI can be used to get rid of great swathes of middle management that don’t do more than measure what everyone else is doing, all for the benefit of the boss. Drucker’s Peter Drucker wrote a book about how all management involves measurement and planning and action on the basis of those measurements. Those measurements aren’t supposed to help the boss decide who to promote and fire, but to enable the managers themselves to do better. Drucker’s Peter Drucker is much less interested in keeping the accountants happy, or, for that matter, maximizing profits, than in increasing the capacity for managers to exercise human judgment, something that can’t be automated.

As I see it, Prince has badly misread an author whose understanding of business (at least in the book he cites; I haven’t read everything by Drucker) provides a radically different alternative to the standard Silicon Valley CEO narrative. If you take Drucker seriously, instead of whittling him into a peg to hang your boasts on, you will discover that he offers a different, and potentially useful understanding of how AI ought be applied within the firm, and equally importantly, how it ought not.

*******

Peter Drucker was an engaging and interesting general purpose intellectual, even if he is rarely considered as such. He was more a theorist than an ordinary guru - a Harvard Business Review poll of business writers identified Drucker, James March and Herbert Simon as their favorite thinkers. That seems the right crowd to situate him in: all three were worldly philosophers in the broad sense, and their ideas about organization have a surprising amount in common.

Drucker was visibly influenced by Schumpeter, without Schumpeter’s arrant elitism, occasional sneaking regard for Fascism, or extraordinarily lively prose style; Drucker has some very good lines but is careful rather than exuberant. Schumpeter and Drucker also had quite different attitudes to the workings of the post-World War II economy. While Schumpeter deplored the strangulation of the hero-entrepreneur by management and bureaucracy, Drucker was prepared to make peace with the new dispensation, and celebrated managers as innovators. He used the term “manager” capaciously, not just to celebrate CEOs and their immediate underlings, nor even middle-managers, but workplace foremen, who necessarily exercised managerial capacities and judgment as part of their responsibilities. If Druckerism is in part Schumpeterianism-lite, it is Schumpeterianism-lite nearly all the way down, focusing on cultivating initiative and self-actualization all the way through the rank-and-file of the firm.

Drucker believed that good management required giving a remarkable degree of leeway to managers. Instead of distinguishing between builders, sellers and measurers, he identified “measurement” as one of the five essential activities that all managers need to engage in, together with setting objectives, organizing, motivating and communicating, and developing people. The manager:

establishes measuring yardsticks, and there are few factors as important to the performance of the organization and of every man in it. He sees to it that each man in the organization has measurements available to him which are focused on the performance of the whole organization and which at the same time focus on the work of the individual and help him do it. He analyzes performance, appraises it and interprets it.

The problem of measurement is one of setting goals for oneself and keeping track of whether you are reaching them, and of communication. Everyone in the business needs to have some sense of what the business as a whole needs, and how his or her own activities meet those needs. Equally, everyone needs to exercise their own “judgment” (a term that Drucker employs repeatedly) as to how they carry out their particular role. Measurements are primarily supposed to orient the manager rather than judge and condemn him (or her, if we are writing in the 2020s rather than 1950s) from outside.

reports and procedures should be the tool of the man who fills them out. They must never themselves become the measure of his performance.

Measurement should absolutely not be used as a means of top down control:

I have not talked of ‘control’ at all; I have talked of measurement. This was intentional. For ‘control’ is an ambiguous word. It means the ability to direct oneself and one’s work. It can also mean domination of one person by another. Objectives are the basis of ‘control’ in the first sense; but they must never become the basis of ‘control’ in the second, for this would defeat their purpose.

Where measurement becomes an instrument of control, it can have disastrous consequences.

In [an unnamed] company a control section audits every one of the managerial units … The results of the audits do not go, however, to the managers audited. They go only to the president, who then calls in the managers to confront them with the audits of their operations. … the nickname the company’s managers have given the control section: ‘the president’s Gestapo.’ Indeed more and more managers are now running their units not to obtain the best performance but to obtain the best showing on the control section audits.

The quote about the Gestapo illustrates a more general point. Drucker believes that the pathological versions of top-down control-by-company-president-or-CEO have much in common with political dictatorship. Management, properly understood, is a mode of human autonomy, a liberal activity in the strong sense of the word. Squashing it into mere implementation is accordingly tyrannical.

Fundamental to Henry Ford’s misrule was a systematic, deliberate and conscious attempt to run the billion dollar business without managers. [italics in original] … Henry Ford’s concept was not even unique in industry. It was widely held in the early years of the century. He shared it, for instance, with one of his most distinguished contemporaries: Lenin.” … Above all, it seemed to make possible industrialization without management, in which the ‘owner,’ represented by the political dictatorship, would control all business decisions while business itself would employ only technicians.

Drucker was suspicious, on similar grounds, of Taylorist efforts to automate business activities so as to separate out planning from doing.

Planning and doing are separate parts of the same job; they are not separate jobs

By suggesting otherwise, Taylorism verges on authoritarianism:

the divorce of planning and doing was also part of the elite philosophy that swept the Western world in the generation between Nietzsche and World War I - the philosophy that has produced such monster offspring in our time. Taylor belongs with Sorel, Lenin and Pareto. … power must be grounded in moral responsibility; anything else is tyranny and usurpation

The role of the manager is not to plan what others do, or merely to implement the plans of others, but to exercise human judgment within a moral setting to integrate social activity:

The manager has the task of creating a true whole that is larger than the sum of its parts … One analogy is the conductor of a symphony orchestra, through whose effort, vision and leadership individual instrumental parts that are so much noise by themselves become the living whole of music. But the conductor has the composer’s score; he is only interpreter. The manager is both composer and conductor. … The task of creating a genuine whole also requires that the manager in every one of his acts consider simultaneously the performance and results of the enterprise as a whole and the diverse activities needed to achieve synchronized performance

Again, Drucker emphasizes repeatedly that this vision of managerial capacities does not apply to the top of the hierarchy but to everyone whose work is not completely technical.

It is no exaggeration to say that Drucker views management as a specific mode of realizing human potential. This is sweeping, romantic and occasionally a little corny. It also makes Drucker an enormously attractive writer and thinker in ways that many of his epigones are not. He views action and responsibility as going together, stressing both that business has a broader social role (profit is no more than a necessary condition to stay in operation, and business must pay attention to the common good), and that the task of the manager is to achieve a human synthesis of individual autonomous decision making with some reasonable understanding of the wellbeing of the firm and society.

*******

Matthew Prince’s goals seem notably different. Quoting the Wall Street Journal op-ed again:

Tireless, independent, efficient and available, AI systems can now measure an organization with a level of objective detail and precision that was previously impossible even for the best employees. … as CEO, I’ve never had better tools to measure exactly how the business is performing, including identifying our rising stars. The vast majority of those we laid off last week were measurers. We cut middle managers across the organization because AI allows us to have more direct reports per manager while still measuring and mentoring our teams effectively. … With fewer people needed for measuring, we can now invest more in people in the areas that drive growth

If you squinted with great vigor, you could perhaps just about interpret this as liberating managers from the tyranny of bureaucratic minutiae and establishing the conditions of autonomy that Drucker emphasizes. It does, after all, mention “mentoring” in passing. But those who are less charitable, such as myself, might emphasize the rather more explicit “as CEO, I’ve never had better tools to measure exactly how the business is performing, including identifying our rising stars.” That might in turn lead them to turn to a different analogy.

Deceased Business Intellectual: In my book I described Henry Ford’s Corporation Without Managers as a cautionary tale. Tech Company CEO: At long last, we are creating the Corporation Without Managers from classic business text Don't Create The Corporation Without Managers.

Matthew, Prince of Cloudflare, is deploying AI to better descry his realm as a whole, and to create a more efficient hierarchy. AI will allow him to reward those who the indicators say are valuable, while firing those whom he believes to be superfluous.

Do note a trick that appears and disappears very quickly in the text. Prince literally classifies everyone in his company who is not either building or selling as “measuring.” While he acknowledges that really good human measurers can be valuable, and presumably isn’t firing all of them, he claims that AI can do most human measurers’ jobs more tirelessly, independently and efficiently. AI, then, doesn’t simply automate the carrying out of technical functions. It replaces managers who aren’t visibly building or selling stuff, doing their jobs better than human beings ever could.

None of this is in Drucker’s book, unless I’m missing something. Indeed, as far as I can see, Drucker believes the contrary. He insists that measurement fails its purpose if it is used as a top-down tool of assessment. He argues that the people who do not contribute visibly to the bottom line regularly play a crucial role, even if they sometimes can be mismanaged.

what the accountant lumps together as ‘overhead’ - the very term reeks of moral disapproval - contains the most productive resource, the managers, planners, designers, innovators. It may also, however, contain purely parasitical, if not destructive elements in the form of high-priced personnel needed only because of malorganization, poor spirit or confused objectives, that is, because of mismanagement.

And all of this stems from the notion that measurement is a chancy undertaking, and is especially chancy when it is separated from human judgment. Anticipating both Herbert Simon and a lot of the modern discussion of metrics, Drucker emphasizes that the “measurement used determines what one pays attention to. It makes things visible and tangible. The things included in the measurement become relevant; the things omitted are out of sight and out of mind.” While measurements are essential, they are highly imperfect. They can support managerial judgment but they cannot substitute for it.

to manage a business is to balance a variety of needs and goals. This requires judgment. … the attempt to replace judgment by formula is always irrational; all that can be done is to make judgment possible by narrowing its range and the available alternatives, giving it clear focus, a sound foundation in facts and reliable measurement of the effects and validities of actions and decisions. And this, by the very nature of business enterprise, requires multiple objectives

Such business judgment simply cannot be substituted by actually-existing AI. As Cosma and I have argued about other forms of organization (building on Ben Recht).

[optimization] simply does not provide any objective means of weighing the kinds of choices across non-commensurables that are essential to the bureaucratic process. Simon, Smithburg and Thompson (1958, 74) … note … “internal conflicts and contradictions among the ultimate objectives…” Such vexing choices regularly emerge in bureaucratic implementation and articulation, as well as in goal-setting at the top, making them fundamentally political problems, and this is just what optimization does not solve. As Recht (2023) bluntly says, “you can’t optimize a trade-off.” There is no consensus over how to optimize over multiple independent objectives in even moderately complex situations. Machine learning, with or without neural nets, does not offer magical solutions to this.

The obvious risk of identifying large groups of managers as mere “measurers,” and replacing them with AI, is that you later discover that they were doing a whole lot of irreplaceable tasks of judgment too, balancing across the different and complicated choices that Drucker, like Simon and his colleagues, identifies as crucial to managing. AI will certainly supplement measurement, and might usefully substitute for many aspects of it, if carefully implemented. However, it cannot reliably substitute for managerial judgment as Drucker describes it.

Perhaps Matthew Prince has just written a very sloppy op-ed; he and his immediate reports may possibly have correctly identified the tradeoffs in their hiring and firing decisions and calibrated them accordingly. Or perhaps not, in which case, he and his readers should consider Drucker’s pithy dictum that “It takes years to build a management team; but it can be destroyed in a short period of misrule.”

*******

Drucker’s actual philosophy of management provides an interesting alternative starting point for thinking about how AI ought be deployed in business. When Drucker wrote his book in the 1950s, both automation and “operations research” (optimization techniques which were an important ancestor of modern AI) were big deals. Drucker wanted managers to use information science to do their job better, but vehemently opposed claims that human judgment and human relationships could be magically automated away.

The Practice of Management expressed deep skepticism about “lurid ‘science fiction’ … about Automation,” invoking “visions of the “technocrat’s paradise, in which no human decision, no human responsibility, no human management is needed, and in which the push button run by its own ‘electronic brain’ produces and distributes abundant wealth.’ However valuable operations research was, it could not substitute for human management: “these are tools of information, and of information-processing, not of decision-making.” Failing to understand this would lead the manager, like “the Sorcerer’s Apprentice, [to] become the victim of his own bag of tricks.”

Back then too, there were grandiose claims about how This New Technology Will Fix Everything And Is Completely Inevitable, So Lie Back and Enjoy.

I have learned to be extremely sceptical of any prediction of imminent revolution or of sweeping changes in technology or business organization

and:

Now that we in the free world no longer accept the planners’ remedies as good for us, an attempt is being made to make us swallow the same nostrums under the pretext that they are inevitable.

Obviously, AI isn’t identical to early operations research or the Taylorist program to turn workers into optimizable machines. There are many things that modern AI can do more efficiently and reliably than past technologies, and indeed human beings. Equally, the differences between AI and past forms of automation are not nearly as marked as much of the current rhetoric might suggest.

Drucker suggests that

Procedures can work only where judgment is no longer required, that is, in the repetitive situation for whose handling the judgment has been already supplied and tested. Our civilization suffers from a superstitious belief in the magical effect of printed forms. And the superstition is most dangerous when it leads us into trying to handle the exceptional, non-routine situation by procedure.

Modern AI too is surrounded by superstitious beliefs about magical effects, and tends to fail when it encounters exceptional situations.

When street-level algorithms encounter a novel or marginal case, they execute their pre-trained classification boundary, potentially with erroneously high confidence.

The best bits of The Practice of Management lay out a moral vision that subordinates technology to a particular understanding of human wellbeing. When Drucker argues that automation ought replace repetitive drudge work, he suggests that this will lead to more management rather than less.

the new technology will not render managers superfluous or replace them by mere technicians. On the contrary, it will demand many more managers. It will greatly extend the management area; many people now considered rank-and-file will have to become capable of doing management work. The great majority of technicians will have to be able to understand what management is and to see and think managerially.

The bigger point is that management is a moral, as well as an economic activity. It involves people developing and exercising their independent capacities of judgment towards the broader goals of the organization and the society that they live in. Drucker’s perspective thus has more in common with Pope Leo’s new encyclical than with Matthew Prince’s effusions. The similarities are unsurprising: Drucker was both a Christian (his book talks in passing about “Our Lord’s Parable of the Talents”) and a Christian Democrat.

A plausible reading of Drucker’s argument is the following: Businesses should pursue automation up to the point, and only up to the point that it supports the capacities of both traditional managers and rank-and-file to exercise individual human judgment in their work. That is not only in the best interests of the business, properly considered, but of the living community of individuals who constitute it. “Extending the management area” is not just an expected outcome of automation done right. It is also an appropriate moral goal, allowing work to move away from drudgery and toward the development and use of human capacities. Where automation change business organization so that it departs from this goal it hurts both the people and the organization itself.

This is not the only possible reading of Drucker’s book in the age of AI, but it seems to me to be highly congruent with his thought. It also has obvious implications for how we think about AI in the workplace. My version of Drucker might say the following. The current Silicon Valley approach to AI is profoundly problematic. It reinforces hierarchy and subordination to the vision of the CEO, rather than enabling individual judgment. It grossly simplifies many of the complex and multifaceted activities of management into “measurement” processes that AI can purportedly replace. It subordinates the moral and developmental aspects of business activity to abstract measurements of efficiency. If someone were actually to write an op-ed that applied Drucker’s ideas to AI, and its associated business model, they would say very different things than Matthew Prince.

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Over the last few months, Cosma and I have been writing a new paper, “AI as Social Technology.” It’s now out, in the Knight First Amendment Institute’s series. I’m obviously terribly biased, but I think it’s a banger. Go read it.

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The piece has three main aims. First together with other things we have written, it pushes back against a generic strain of Singularity thinking, which deploys feral thought experiments to prophesy the near future. Instead, it argues that you ought draw on actual social science and history. They will tell you that things are more complicated and interesting than stylized accounts would have you believe, but that is because the future is likely to be a mess, in ways that both resemble and are dissimilar to the mess we have today.

Second, it aims to provide sa better way of thinking about the mess. In particular, it combines recent work on “coarse graining” with the ideas of Herbert Simon and Charles Lindblom, suggesting that these build common ground between computer science, the traditional social sciences and science and technology studies.

Finally, and most directly, it argues that one particular variety of dubious AI thinking helped fueled the rise of DOGE.

AGI-centric accounts depict bureaucracy as centralized coordination, the key problem being how lower layers fail to implement the priorities of the top … Speculative arguments about AGI helped inspire Elon Musk’s DOGE project, which sought to hack away great swathes of America’s administrative machinery. Much of DOGE’s work and aspirations involved the application of LLMs and AI ‘agents’ to accomplish a variety of open-ended tasks, often very badly. … We certainly can’t blame AGI speculation alone for DOGEmaxing and the Trump administration’s evisceration of the federal bureaucracy; there are many overlapping causes. However, if you believe that the duty of a bureaucracy is to implement the leader’s program, and AGI is nigh, it is not hard to conclude that the latter offers a providential way to accomplish the former.

There’s lots more in the paper, including plenty more detail on the intersection between AGI-speculation and DOGE thought, and argument how the consequences of AI for bureaucracy are going to be much messier than any of these stylized interpretations. But there are also things that we didn’t have time to talk about. Two are worth mentioning.

First, “effective accelerationism” is an important part of the intellectual mix that helped produce the AI-DOGE chimera. In particular, the neo-reactionary arguments of Nick Land have had real, and pernicious consequences. “DOGEMaxing” and similar notions owe an intellectual debt to Land’s ideas (the term “machinic” pops up a lot in argument), even if the people who make these arguments don’t necessarily agree with everything he says. Claims about how our world will be radically remade in the image of machine logic are nearly ubiquitous, whether the authors view the machine-god state as something to be feared, celebrated or both at once. Equally, as as we suggest in the quoted excerpt above, AI speculation is only one justification for the Trump administration’s efforts to disembowel the administrative state. I’d be startled to discover that e.g. Russell Vought has been reading technology-fueled neo-reactionary online manifestoes.

Second - and this is something I figured out belatedly when writing, is that there is a fundamental difference between the disastrous DOGE project and the apparently similar push by both center-right and left leaning people to create a more effective and responsive government bureaucracy. That has in fact been the source of considerable confusion. The two approaches differ crucially on the question of who should the government be responsive to?

DOGE/AI Thought starts from the premise that bureaucracy should be primarily (perhaps even exclusively) responsive to the people at the top. From this perspective, the problem that AI solves is a mixture of regular institutional inertia and specific “deep state” resistance. There are implied tradeoffs for some people who buy into this argument (others; the true idolators, may simply not care that much). Using AI to build the machinic Moloch means both empowering the Trump administration in its quest to build up American Greatness, and empowering the Chinese Communist Party in its quest to stamp out human individuality and freedom. What makes it easier for Trump to get rid of mid-level official saboteurs by buying in private sector AI and expertise, also makes it easier for Chinese Communist Party leaders to construct machine learning apparatchiks that perfectly implement its program. Under this analysis, perhaps you can hold China back by e.g. not exporting the fastest chips for AI training; perhaps not.

The effective government bureaucracy people, in contrast, are not in the business of making sure that Dear Leader’s commands get implemented as they ought. Instead, they are primarily interested in freeing bureaucrats to do things that are obviously the right things to do, rather than burying them beneath the concrete of top down mandates. The impulse, then, is to trust bureaucrats more, and give them the means and autonomy to respond to obvious needs. This involves creating better feedback loops between top and bottom, so that measures, tools and perhaps even goals are redefined as the problem becomes better understood. But it also means creating interfaces through which bureaucrats can engage more with the public, and respond better and more quickly to public demands, as well as helping them work sideways with others in the bureaucracy who have necessary skills and knowledge, without getting smothered in red tape. The general bet is not on better subjugating bureaucrats, but on making them more autonomous. This is more or less the opposite of DOGE, and its vision of AI is murkier.

Obviously, some reforms or technologies that might help the one vision might plausibly help the other. But one of the implications of Cosma’s and my arguments is that they have radically different understandings of what the state should be doing, and for whose purposes. I suspect - though this would require a lot more work to establish - that the differences between DOGEMaxing and the effective bureaucracy approach map quite well onto the differences between Soviet cybernetics with its programmatic ambitions to Plan Everything, and the management cybernetics of Stafford Beer and his colleagues. Like those, they are very different approaches that are lumped together because of some commonalities of terminology.

Anyway - these are side notes to a larger argument. If you are interested, do read the piece itself!

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[Battista Angelo del Moro, “The Corrupt Judge.” Courtesy of the Met]

Obviously this post is occasioned by the terrible Supreme Court decision earlier this week. It is also motivated by the string of other terrible decisions over the last few years, and by a long established amateur interest in the topic of the conservative legal movement. What follows are better described as notes toward an argument than a fully developed set of ideas, but that’s all I’ve got right now.

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The Conservative Legal Movement is Not Purely Political

There’s been a lot of scorn expressed on Bluesky and elsewhere at John Roberts’ apparent claim that Supreme Court justices are not “political actors.” If you read the original article, Roberts doesn’t quite say that, despite the AP’s spiced-up headline and somewhat misleading first line. What he actually says is:

“I think, at a very basic level, people think we’re making policy decisions, we’re saying we think this is how things should be, as opposed to what the law provides …I think they view us as purely political actors [my emphasis], which I don’t think is an accurate understanding of what we do.”

I haven’t been able to find a transcript of the original speech, and I imagine that Roberts didn’t elaborate further. I suspect that if he had so elaborated, he would have said very different things than what I am about to say below. Nonetheless, it is both true and important that the Supreme Court justices, and conservative legal scholars and movement activists are not purely political actors. They would be much less effective if they were. They have an ideology, originalism, which is clearly quite closely related to a set of policy priorities, but it doesn’t ineluctably lead on every possible occasion to the preferred policy outcomes.

If conservative legal thought were simple intellectual hackwork, it would be less legitimate, and hence much less suited to coalition building and getting results. Equally, treating it as a set of ideas floating far above politics in some empyrean of purely intellectual discourse would be even more wildly misleading [see further below]. The implication is that we can’t just treat the ideas as by-products of the politics. We have to understand how the ideas and the politics interact. And that leads us to the Federalist Society.

The Federalist Society is a Political Movement

If you want to understand how the conservative legal movement hangs together, you need to pay very close attention to the Federalist Society, a club of conservative lawyers. The Federalist Society is about ideas, as suggested by the title of Amanda Hollis-Brusky’s book on the organization, Ideas Have Consequences (a sardonic gloss on the title of a famous conservative book). It is also about distributing the spoils of patronage.

Hollis-Brusky - who has done the interviews - explains how the Federalist Society plays a central role in the promulgation of originalism, the doctrine that conservative justices have used to remake constitutional interpretation and jurisprudence in ways that are congenial to their ideology.

For example, as Federalist Society member Daniel Troy explained in our interview, “what the Federalist Society offers is an opportunity to interact with people who at least share your point of view about constitutional interpretation. . . people who have shared views about Originalism.” Similarly, Federalist Society member John Yoo emphasized in our interview that if he had to identify the single most important thing that the Federalist Society stood for, it would be “a commitment to Originalism.”

The Federalist Society does not simply develop originalist ideas and arguments . It also enforces the party line tacit combination of cheering section and ideological firing squad. Hollis-Brusky again:

Several conservative commentators when discussing Republican nominees John Paul Stevens, Harry Blackmun, Potter Stewart, David Souter, and even Anthony Kennedy in part attribute the leftward drift of these Justices to their desire for approval from the Washington, D.C., elite circles.

In helping to build a conservative and libertarian counter-elite around a shared belief in Originalism as the only valid mode of constitutional interpretation, the Federalist Society acts as a bulwark … holding members accountable for staying true to their principles. In the course of my interviews with key Federalist Society members, it became clear that they engage in this kind of feedback-loop with the Justices frequently—at Federalist Society conferences, at barbeques, through personal correspondence, and through scholarly publications.

As Federalist Society cofounder Steven Calabresi said in our interview, the growth of a conservative and libertarian counter-elite through the Federalist Society has “absolutely” helped keep Justices such as Scalia, Thomas, Roberts, and Alito in check: “I think it absolutely helps keep them in check. When one tries to think about what kinds of checks exist on officials as powerful as Supreme Court Justices I think the check of criticism by law schools, journalists, and conservative think tanks like the Federalist Society, criticism from those quarters is something that they notice. They may or may not be persuaded by it but I think they know it’s out there and I think it is something of a check on them.”

Hence, ideas are really important but they are ideas with a purpose, and an organizational structure behind them.

Still, if the Federalist Society were just about debating originalist ideas, it would be much less politically effective. The other, very important thing that the Federalist Society does is to distribute patronage. If you are a young aspiring lawyer and you want a political appointment in a Republican administration, or even more pertinently, a clerkship for a conservative judge, and all of the career benefits that flow from that, you really, really want to participate actively in the Federalist Society.

Thus, patronage politics (judges have great personal discretion in who they choose as clerks) plays a very important role in keeping the Federalist Society thriving and healthy. FedSoc’s liberal equivalent, the American Constitution Society, is relatively anemic, because it doesn’t have a similar stranglehold on who gets clerkships and who does not. It illustrates what FedSoc might look like if it were just about debate and nothing more.

In one sense then, you might think of the Federalist Society as a watered down version of what Tammany Hall might have looked like if it had taken all of the culturally offensive ceremonial nonsense about Grand Sachems and wigwams in deadly earnest. There is notably less riotous drinking, and far less overt corruption than in its nineteenth century equivalent, but FedSoc is in substantial part a machine for dispensing patronage to the right people. Just like nineteenth century Irish immigrants to New York, conservatives in law schools were denied access to the trough and had to organize themselves. They similarly came to dominate a system that once seemed to be rigged against them.

In another sense, the Federalist Society is indeed about ideas, but in a very different way to, say, an ordinary university department. Again, the Society’s mission is to ensure that ideas have consequences by shaping jurisprudence in specific ways. Debate happens only to the extent that it is compatible with this broader objective.

In conclusion then, you have to understand both aspects of the Federalist Society, and how they fit together, to see how it cements the conservative legal movement together. If it didn’t weld patronage politics to ideas, it would be much less attractive to young lawyers. If it didn’t weld ideas to patronage politics, it would be incapable of reshaping judicial discourse and constitutional politics around its conservative objectives.

The Conservative Legal Movement is Decadent

When it began, the conservative legal movement could see itself as an ideological vanguard. It was taking on a corrupt and complacent liberal legal academy that it saw, with some justification, as more interested in self-perpetuation than new ideas. Those days are long gone. Now, the conservative legal movement is the establishment, or at least a central element within it. Lawyers like Marty Lederman increasingly have to search for originalist justifications to achieve liberal ends [update: for qualifications see “Jon W” in comments].

Holding power - and seeking to maintain and extend it - have had predictably dismal consequences for ideas. Purportedly textualist Supreme Court justices come up with bizarre justifications that lack historical support, for decisions that they want to take. Historical constitutional interpretation becomes an exercise in cherry picking to justify new doctrines, rather than the sober moderating of judicial overreach that originalists purported to provide. Zealots of constraint, once they get into power, are keener to limit their opponents’ excesses than their own.

It is a problem when the concealing patina of ideas wears down. It is also a problem when patronage politics become so gross as to explode through the covering layer. The Roberts Court is not only presiding over the most spectacularly corrupt government in the history of US politics (itself a remarkable achievement). It is actively enabling it, both through its past jurisprudence and current decisions.

People rightly highlight decisions such as this week’s, as well as the grant of near complete immunity to presidents in the course of their official duties, the manipulation of the shadow docket to frustrate efforts to restrain the administration, and the efforts of DC circuit court justices to frustrate contempt proceedings against visibly contemptuous Trump officials. Other, less flashy lines of jurisprudence, such as the slow gutting of meaningful anti-corruption measures are likely to have equally pernicious consequences if control of the legislative and executive branches change hands.

I suspect that Roberts and his cronies do not like to think that they are associated with the more uncouth aspects of the political conservative movement. They are not only associated with it, but an active and vital element of the machine. It is increasingly difficult to maintain the pretense of separation. Once, like Burke in his early days, conservatives railed against official corruption. Now they are apologists for a regime whose decadent excesses resemble the more startling aspects of Marie Antoinette’s court.

Decadence opens up vulnerabilities.

To say that a system of pelf and ideology-laundering is in decay is not to say that it is in imminent danger of collapse. There is a great deal of ruin in a movement that has successfully seized power. Yet there are contradictions, weaknesses and fissures. Originalism is the theory that the Federalist Society knows what it wants, and deserves to get it good and hard. It’s now getting it good and hard, and some legal conservatives are reportedly unhappy.

Still, so long as the movement maintains its chokehold on patronage, it will be difficult to detach more than a few individuals. I’ve sometimes wondered what would happen to the Federalist Society if future reforms eliminated the power of individual judges to choose their own clerks, in favor of some form of panels or open competition. This would obviously discomfit many liberal and left leaning lawyers; they too have their own networks of benefit disbursal. But it is likely not nearly as essential a part of their organizing machinery.

It could be that the Federalist Society is sufficiently well established that it will continue to operate more or less as it does, or that it may integrate further into a conservative movement that is ever more closely organized around the division of spoils. It’s also possible - even likely - that it would lose a lot of the power that it has to attract and organize lawyers, unraveling the threads that weave patronage, cheerleading and disciplining lawyers into a single interconnected system of power. Perhaps in a few years we’ll have the opportunity to find out.

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I haven’t been writing as much here over the last several weeks, because of multiple other writing commitments. Some of these are about to start bearing fruit. Substack posts will get easier now that the semester is coming to a close, but in the meantime, here’s a short piece to tide you over, and an opportunity for those as wants to take it up.

One of the pieces that is forthcoming (co-authored with Cosma Shalizi) relates indirectly to the theme of this Elias Isquith post. Elias draws a comparison between how AI figures like Altman talk about the future, and the bizarre homespun philosophy of Anton Chigurh, the killer in the movie, No Country for Old Men.1

in both cases, we have men positing that they have a unique grasp of the nature of the universe and the direction of human history. And at the risk of stating the obvious: This is not a small claim!

In another era, in another culture, this hubristic assertion of having discerned the golden path to the inevitable future would be grounds for charges of heresy or blasphemy. The egomania here is astounding, no less so than that of a character who fancies himself Fate (and/or Death) incarnate.

And in both cases, we are confronted with false prophets who are telling us, albeit in different registers, that human superfluousness is either already true (Chigurh) or inevitable (Altman). In the face of such monstrous certainty, despair would be understandable.

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I think that it is worth drawing out a difference between Chigurh and Altman that is hinted at in Elias’s indirect Dune reference. Chigurh’s philosophy is a cockeyed version of determinism, suggesting that we don’t have real choices going forward. Altman is drawing on a much stranger set of notions, which suggests that our present is not determined by our past, or by chance, but by a radically constrained version of the future. A lot of AI discourse reverses the arrow of time, so that instead of a fixed past and an indefinite future, we face a definite future, which directly or indirectly shapes its own past.

This follows from standard arguments about the Singularity. People who subscribe to middling-to-stronger versions of Singularity thinking believe that we are about to hit a massive phase-change in human history, which will have a dichotomous outcome. Once strong AI hits, either the machines master us, or we master the machines. The result is to render present concerns largely irrelevant, except insofar as our collective decisions make us more likely to follow the one path or the other. The AI 2027 paper provides a fine example of the genre.

And it is a genre; a concatenation of LessWrong posts, academic and sort-of-academic articles, think-tank thought pieces, Substack posts and the like, which not only build on a similar set of tropes, but also (and here is the point I want to emphasize) adopt a narrative structure that interprets the present only in terms of some posited near term future of radical transformation. It’s notable how significant elements of the mythology of the Singularity - things that people in this space don’t usually fully believe, but that often indirectly affect their thinking - describes direct intervention by some future that rearranges the past so as to ensure that it comes into being. Here, most obviously, Roko’s Basilisk (more generally; when one considers the collective fate of humanity as an exercise in applied game theory, backward induction may lead you to some very strange conclusions).

This famous quote from Nick Land is even more on point:

what appears to humanity as the history of capitalism is an invasion from the future by an artificial intelligent space that must assemble itself entirely from its enemy’s resources.

The obvious rebuttal is no: we actually can’t see the future of AI. We can’t even engage in the limited kinds of hedged predictions that we can make when we model reasonably well understood phenomena. The question, “How technology will develop in the future?” is an open ended one.. If innovation were predictable in its consequences, like the tech tree in Civilization, we’d be in a very different kind of history altogether than the history we are in.

What we can see are the outcomes of thought experiments. Thought experiments can be very useful as a means of thinking more systematically about unknowns. However, one shouldn’t overestimate what you can do with them. In the end, thought experiments are nothing other than moderately disciplined guesswork. When we mistake them for reliable predictions of what lies ahead, and reshape our world around what they say, we’re liable to end up in a mess, unless we are improbably brilliant, lucky, or both.

But we are in a world where many people - including very important policy makers - see a particular strain of thought experiments as being determinative. I don’t think that these people are stupid or wicked, but I am frustrated with how their arguments are driving out other ways of thinking (that may finally be changing now that concerns about economic disruption are coming to the fore, but it is changing much more slowly than I would like). That makes it much harder to see the enormous variety of futures that might be possible, depending on the choices we make and their consequences, both predictable and stochastic. Those possible futures are being devoured by thought experiments which have gone feral, and have spread like an invasive species from their proper environment into the realm of general discourse. That stunts democratic debate and understanding of the choices we do and don’t have.

Some version of this complaint informs the opening parts of a jointly written paper with Cosma Shalizi that should be out soon. You can plausibly read this classic post of his as yet another version of this complaint, which was aimed at an earlier version of this discourse. If we see the Singularity as having happened in the past, we can better understand the ways in which it is contingent, rather than extrapolating the eschaton from growth charts.

Enough griping: here’s the positive opportunity. The Protopian Prize competition for short fiction that imagines a democratic future is going to open up tomorrow. There will be a $5,000 prize for the winning entry, and I’m going to be one of the judges. While I wasn’t even slightly involved in setting up the prize, and the bit that I am concerned with is not about AI, the competition will surely generate a variety of different possible futures, all of which will start from an understanding of how or whether we can collectively steer towards one direction or another. That kind of steering, is, after all, what democracy involves. I don’t have any further particulars beyond what is on the website, and absolutely don’t want to suggest that people should write in one or another vein (the variety of possibilities seems to be the point) but do encourage you to enter. As per Elias’s post, I would like fewer thought experiments about how we have no or very few choices to make, and more thinking about how our future is not constrained to one or the other narrowly defined path.

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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 Ben 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

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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.

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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.