AI, Central Planning, and Hayek's Knowledge Problem: Why "The Use of Knowledge in Society" Survives the Age of Artificial Intelligence

This paper reassesses F. A.Hayek's "The Use of Knowledge in Society" in light of the rise of artificial intelligence. AI substantially strengthens the case for certain forms of planning by expanding data collection, prediction, codification, monitoring, logistics optimization, and hierarchical coordination. Recent arguments by Acemoglu and by Brynjolfsson and Hitzig suggest that AI may reduce the informational advantage of local actors, enlarge the effcient scale of firms, and revive some forms of algorithmic or AI-assisted planning. The paper argues, however, that AI does not fundamentally invalidate Hayek's knowledge problem. Hayek's central claim was not merely that planners lack computing power, but that economically relevant knowledge is dispersed, tacit, contextual, incentive-laden, forward-looking, and often generated only through decentralized action. AI can process data, but data are not identical to knowledge; AI can predict, but prediction is not discovery; AI can simulate prices, but simulated prices are not market prices generated by property, exchange, competition, profit, and loss The paper further argues that comprehensive AI planning raises serious problems of truthful revelation, metric gaming, surveillance, political power, and objective-function selection. AI may improve planning within firms, platforms, and governments, but such planning works best when embedded in a competitive, price-guided, polycentric market order. The conclusion is not anti-AI but anti-monopoly over social knowledge: AI should augment decentralized discovery rather than replace it with centralized control.