Billionaire solipsism, dictator solipsism, AI, and the fascist paradigm
AGI works best in a K-hole.
With great power comes great solipsism: the more power you wield over other people, the less real they become to you. To rule is to see people as aggregates, statistical artifacts, as a means to an end. It’s how people seem when you’re at the bottom of a k-hole.
Per Granny Weatherwax, this is the root of all evil: “Sin is when you treat people like things”:
https://brer-powerofbabel.blogspot.com/2009/02/granny-weatherwax-on-sin-favorite.html
The problem (for powerful people) is that other people aren’t things; they’re people, with stubborn attachments to their own priorities and needs. This is a huge problem for social media bosses, since the force that keeps you stuck to their platforms is your love of your friends, which sucks (for social media bosses), because your friends refuse to organize their interactions with you to “maximize engagement.” There is a group of platform users who are dedicated to maximizing your engagement: performers (which is why legacy social media platforms have reduced the quantum of your feed given over to your friends to a bare minimum and swapped in the amateur dramatics of theater kids). But even “influencers” demand treatment as people, not things (which is why legacy social media is squeezing out performers in favor of slop):
https://pluralistic.net/2026/04/17/for-youze/#forever
Running a social media service is especially solipsism-inducing, since the back-end of a social media service always reduces people to statistical artifacts to be steered, thwarted, or rewarded based on the degree to which they are “maximizing engagement.” No wonder zuckermuskian social media bosses mythologize themselves as dopamine-hacking wizards who’ve built a mind-control ray. Skinnerism and solipsism fit together very neatly, seducing you into the belief that everyone else is a stimulus-responding automaton, programmed to think they have free will:
https://pluralistic.net/2025/05/07/rah-rah-rasputin/#credulous-dolts
(Of course, the AI boss version of this is the belief that everyone else is a “stochastic parrot”:)
https://xcancel.com/sama/status/1599471830255177728
But in truth, any corporate boss is prone to solipsism. To maximize corporate profits, you must view other people — employees, suppliers and customers — as inconvenient problems to be solved, not true people with feelings and needs that are co-equal with your own.
This is why AI is so attractive to the ruling class. For corporate leaders, the fantasy of your own worth is always dangerously close to collapsing, due to the haunting knowledge that if you don’t show up for work, everything continues as per normal; while if your workers don’t show up for work, the shop closes down and stays closed. Bosses really want to be in the driver’s seat, but ultimately they know that they’re strapped into the back seat, playing with a Fisher Price steering wheel. AI is a way to wire that toy steering wheel directly into the drive-train: it’s the fantasy that a boss can have an idea and the corporation will execute it, without any messy human needs or demands getting in the way:
https://pluralistic.net/2026/01/05/fisher-price-steering-wheel/#billionaire-solipsism
Solipsism is why bosses fetishize IP and ignore process knowledge. IP is the part of the job that the worker can explain (and that you can train an AI model on). Process knowledge is the part of the job that can’t be abstracted, alienated or commodified. The very existence of process knowledge is the major impediment to de-skilling workers so they can be interchanged with other, more desperate, more timid workers (or with sycophantic AI):
https://pluralistic.net/2025/09/08/process-knowledge/#dance-monkey-dance
Of course, there’s a whole group of powerful people outside of the political world who are gripped by solipsistic AI fantasies: politicians. Like social media bosses, politicians deal with people as statistical artifacts who respond to policy inputs with semi-predictable outputs:
https://en.wikipedia.org/wiki/Seeing_Like_a_State
And of course, politicians have their own detested class of workers whom they fantasize about replacing with chatbots: bureaucracies. When Trump et al bemoan the “deep state,” they are engaged in the politicians’ version of the corporate boss’s solipsism: “I make policies, but to enact them, I have to convince civil servants to turn my agenda into action. This sucks. Can’t we just have an all-powerful executive who decides on things and then those things just happen?”
Writing for Columbia’s Knight First Amendment Institute, political scientist Henry Farrell and statistician Cosma Rohilla Shalizi have produced the definitive account of how AI psychosis has infected our political classes:
https://knightcolumbia.org/content/ai-as-social-technology
Farrell and Shalizi use this political AI psychosis to explain DOGE, framing DOGE as a project where politicians and their loyal vassals cut such a deep wound in the administrative state on the basis that general AI was about to emerge. With godlike AI around the corner, these bureaucrats — who insist on having opinions based on long experience and ethical sensibilities — could be replaced with sycophantic chatbots who’d turn the will of the unitary executive into policy without any filtration through unreliable, squishy humans.
This is a political version of my maxim that “the fact that an AI can’t do your job doesn’t stop an AI salesman from convincing your boss to fire you and replace you with an AI that can’t do your job.” Private sector bosses are easy marks for AI salesmen, and not just because they want to reduce their wage bills, but also because it will fulfill the solipsist’s fantasy of a corporation that turns the singular genius of the boss into a product without any messy demands from workers (and, if you’re Zuckerberg and convinced that you’ve created a mind-control ray, your product can be rolled out without any messy demands from your customers, either, since you’ve hypnotized them into doing as they’re told).
The public sector version of this is the fantasy that you can eliminate the civil service and use an army of chatbots to do the job — not merely as a way of slashing the federal budget, but also as a way of purifying the transfer of the leader’s will to the people without any intervening loss of fidelity resulting from the need to have your policies interpreted (and willfuly misinterpreted) by bureaucrats.
This is a very important framing, and it explains why fascists like Trump and dead-eyed technocrats like Canadian Prime Minister Mark Carney are hell-bent on gutting their countries’ civil service and replacing it with chatbots:
https://policyoptions.irpp.org/2026/04/carney-ai-government-risks/
This is how Muskism and DOGE connect to Trumpism and AI: Musk doesn’t believe other people are real. He calls them “NPCs” (non-player characters). He wants to put a microchip in your head so he can “replace your bad programming”:
https://pluralistic.net/2026/04/21/torment-nexusism/#marching-to-pretoria
It’s the fascist paradigm: the idea that people are incapable of self-rule, save for a very small number of singular geniuses who should be put in a position of absolute authority over all of us, to keep us safe from our own foolish impulses:
https://pluralistic.net/2026/05/12/donella-meadows/#paradigmatic
The Technocrats — a protofascist Italian movement that once captured the imagination of Musk’s great-grandfather, and now are frequently quoted and alluded to by the likes of Mark Andreessen — were addicted to the quantitative fallacy that infects economics and other disciplines. That’s the idea that every social process can be expressed as a mathematical model, which can then be optimized.
The problem, of course, is that much of the real world is qualitative, and the act of quantizing those qualia is a very lossy process. To quantize a qualitative question is to incinerate all the qualitative aspects and then do mathematics on the dubious quantitative ash that is left behind:
https://locusmag.com/feature/cory-doctorow-qualia/
In their paper, Farrell and Shalizi cite Ben Recht’s maxim that “you can’t optimize a trade-off”:
https://www.argmin.net/p/are-there-always-trade-offs
But of course, we optimize trade-offs all the time. That’s what being a boss means, and it’s also at the very core of self-determination: the right to decide what trade-offs you want to make. What Recht means is “you can’t optimize a trade-off for everyone else.” Those stubborn not-quite-people — customers, workers, bureaucrats — insist that they want different trade-offs.
In translating the will of a supreme leader to policy without any intervening need for buy-in by humans, fascist projects like DOGE seek to optimize trade-offs according to the preferences of the supreme leader. AI in government is grounded in the idea that a sufficiently deserving leader can be trusted to vibe-code the entire apparatus of state, checked only by his own sense of rightness:
https://thehill.com/policy/international/5680714-trump-morality-international-law/
Farrell and Shalizi forcefully make the point that statecraft is not a set of discrete problems with provably correct answers that must be solved. Government is a matter of making choices between mutually exclusive policies that have benefits and costs, and those costs and benefits befall different groups differently.
The idea that you can simply feed every fact about a society into a chatbot and order it to “solve” the nation reveals a profound ignorance about the nature of political contests. There’s no empirical way of deciding whose priorities deserve to be realized and who must be disappointed. There isn’t even an empirical way to compare the benefits that one group receives to the costs another group pays.
What’s more, any system that uses LLMs to make high-stakes tradeoffs between different societal priorities will be relentlessly targeted by the groups that stand to win or lose based on those decisions, and by bureaucrats whose careers depend on making the number go up. They will poison the LLMs’ training data, figure out how to trick it into deceiving their bosses about the situation on the ground.
Back in 2018, Yuval Harari predicted that LLMs would supercharge dictatorships by overcoming “authoritarian blindness” — when the suppression of political opinion is so effective that the first sign that a dictator has of his waning support is a mob that burns the presidential palace down. This prediction failed, because people who live under dictators have switched all the energy they used to use to put on a good show for the secret police into putting a good show on for the chatbots:
https://pluralistic.net/2023/07/26/dictators-dilemma/#garbage-in-garbage-out-garbage-back-in
Meanwhile, the “variability” introduced by bureaucrats who adapt political policies is a feature, not a bug. When a long-tenured public official receives a directive from on-high that they know will be a disaster if implemented unchanged, they can tweak the policy so that it is at least partially successful.
Fire that bureaucrat and hand the policy to a rigidly loyal LLM that will not deviate from its strict instructions and you will end up with nothing (rather than a perfect policy implementation). Indeed, you may end up with less than nothing, as resentful local populations sabotage your agenda.
Both Hayek and Marx agreed that people at the very periphery of the system have insights into local conditions that no boss/central planner can know (though they disagreed about what that fact implied). An LLM is the ultimate micro-manager, and government by Computer Says No would only work if the person writing the system prompt knew everything about everyone everywhere.
As Farrell and Shalizi write,
The frustrations of actually existing bureaucracy do not merely arise from inept or technically-inadequate solutions to the principal-agent problem. They emerge too from the collision of multiple incommensurable demands, each with its own problems and benefits, so that there are no optimal design solutions. Those who build or reform bureaucracies, like those who build other artifacts, need to satisfice across multiple intersecting needs and pathologies. Designs that neatly address one kind of problem may radically worsen others. Actually-existing AI has its own imperfections, some of which are endemic. Grafting AI systems onto existing bureaucracies will solve some problems but will worsen others and make altogether new ones. It will not eliminate the political difficulties of mediating across different, often non-commensurable, goals. Imagining replacing bureaucracy wholesale with AI is only plausible if one waves away the actual difficulties associated with real social technologies.
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