CONCEPT
Algorithmic Central Planning
The condition in which AI systems deployed at scale recreate, in mathematical form, the epistemic failures of the centralized economic planning that Hayek and Friedman spent their careers diagnosing—gathering knowledge into a single model, eliminating the distributed error-correction of competitive markets, and optimizing an objective chosen by whoever owns the system rather than revealed by the dispersed preferences of the people it serves.
In the 1920s and 1930s, a group of socialist economists argued that central planning could match the market: gather the data, write down the equations of supply and demand, solve the system, and you would arrive at the same prices the market gropes toward, but faster and without the waste. The reply from the liberal tradition—Mises first, then Hayek, then Friedman—was not that the equations were too hard to solve. It was that the data to put into them does not exist in gatherable form, because the relevant knowledge is generated by the market process itself and has no existence prior to it. The price is not a measurement of a pre-existing fact; it is the outcome of a discovery that has not happened until the trading happens. The socialist calculators of
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