The A.I. Case for Socialism

Current debates about A.I. range from the challenges authors and readers face when confronted with a tsunami of “AI slop” to the location of data centers and the potential for mass unemployment resulting from AI job displacement. The latter raises issues such as granting everyone a universal basic income, funded by taxes on the profits companies make from AI efficiency. The reality is, tax cuts have been preferred to ‘government handouts’ to the unemployed. That smacks too much of socialism (or “communism” as the current US President calls it.)
But what if socialism is in fact the endgame of the AI revolution?
Writing in the Weekend Financial Times, commentator Martin Sandbu asks if A.I. could “revive the socialist dream”.
Historically, central planning and socialist direction of the means of production have not been a success. Absent a market economy, goods cannot be bought and sold freely. This stops the creation of natural prices. The complexity of an industrial society doomed central planning. Sandbu notes:
A central planner would need massive amounts of information from every little corner of the economy. … The knowledge needed to allocate resources well — of who needs what and who can provide what on what conditions — is so local and dispersed that no central planner could ever collect it.
Free market capitalism offered a superior solution. Rather than a bureaucrat in Moscow or Beijing, “the market price, in a single number, conveys just what is needed for local decisions that match the overall efficient market allocation.”
The champions of capitalism, such as ‘Austrian school’ economist Fredrick von Hayek, believed that, through the mechanism of adjustable prices, free markets efficiently allocate resources and set prices, what Adam Smith called the “invisible hand”. This anti-socialist viewpoint influenced the policies of Margaret Thatcher, among others. The problem is that the hand does not always work efficiently.
AI Agents unite! You have nothing to lose…
Sandbu suggests that the challenges faced by 20th-century central planners might be about the disappear, as AI agents overcome the advantages of free market capitalism, which had obvious failures:
Market prices get a lot of things wrong. People don’t always know enough to choose the best goods; they get addicted, defrauded or bankrupted. Consumption and production have spillover effects on third parties — “externalities” — that pricing decisions don’t capture; so we get pollution, resource depletion, climate damage. Price adjustments don’t stabilize the macroeconomy; so we get business cycles, bubbles and busts.
In Hayek’s time, information about local prices and quantities could only be collected by human workers armed with clipboards. Today, with so much commerce being done online, prices can be comprehensively “scraped” off the internet. AI can then mine unstructured economic data from social media and the internet of things and so “offers the promise of transcending price information altogether by predicting who wants, needs or can produce what at what cost, better than market prices could ever summarize.”
AI removes one of the 20th century’s strongest arguments against central planning. And to the extent that both public and private sectors adopt AI to guide decision-making — how much to invest, in what, and how best to tax for desired policy outcomes? — our economies will look increasingly planned and decreasingly market-shaped.
Sandbu recognizes that this raises significant political questions. He lists three:
- Would the current leaders of AI development — almost all hardcore libertarians — support allocating capital to AI-powered planners rather than free financial markets, given how much the latter favor them?
- Might the general public, whose AI skepticism is currently rising, be won over by more “rational” economic decision-making that delivers more for them than our existing form of capitalism?
- Would an economy where AI informs most decisions be able to overcome the conflicts of interest and co-ordination that have always held back productivity — the so-called tragedies of the commons and prisoner’s dilemmas? (Consider, for example, whether a super-AI empowered to allocate resources would tolerate our very slow rate of decarbonization.)
To these I’d add:
- Aren’t China, Russia, and other centrally planned economies in a much better place to implement AI efficiencies than capitalist societies? Does this mean they will enjoy an unbeatable advantage, even as China outsmarts American frontier AI companies with cheaper, faster AI’s, layered on an institutional infrastructure able to exploit this advantage?
- Will a future American administration resurrect DOGE — Elon Musk’s ‘Department of Government Efficiency’ — to implement *actual* AI efficiencies, not just take a chainsaw to institutions?
- Which constituencies will be threatened and which empowered by the conflicts of interest mentioned by Sadu? Consider:
- The challenge to insurers and for-profit hospital systems if an AI attempts to logically allocate medical resources to benefit patients, not maximize revenue.
- The response of NIMBY residents to an AI recommending an increase in the supply of houses to reduce rents and homelessness.
- Trade-offs in dozens of other areas where access to scarce resources is allocated by vested interests.
- Where does control of the AI system reside?
Which way the chips fall — into the pockets of the billionaires, or across all of society — remains to be seen.

































