Algorithms process data from the past while economic decisions are dynamic and forward-looking
By Marian L. Tupy and Peter Boettke. Excerpts:
"Prices enable people to engage in economic calculation, which forms the basis for the rational allocation of scarce resources among alternative ends. Prices also function as decentralized feedback loops. “A price is a signal wrapped up in an incentive,” note Tyler Cowen and Alex Tabarrok. This dual signal communicates information about relative scarcities and simultaneously encourages economic actors to adjust their plans accordingly. When lithium prices rise, producers and consumers conserve, recycle, innovate, and explore alternatives.
The belief that AI can achieve comparable results to free markets, let alone surpass them, reflects a misplaced confidence in computation and a misunderstanding of the price system. The problem for the would-be AI planners is that prices don’t exist like facts about the physical world for a computer to collect and process. They arise from competitive bidding over scarce resources and are inseparable from real market exchanges. Moreover, prices aren’t fixed inputs to be assumed in advance. They are continually being discovered and formed by entrepreneurs testing ideas about future consumer wants and resource constraints.
Economic models that treat prices as given overlook the entrepreneurial actions that create them in the first place. Ludwig von Mises made this point in 1920: Without real market exchange, central planners lack meaningful prices for capital goods. Consequently, they can’t calculate whether directing steel to railways rather than hospitals adds or destroys value.
AI can process vast amounts of data—but always from the past. Economic action, by contrast, is forward-looking. An algorithm may extrapolate trends, but it can’t anticipate innovation and changing tastes. It can’t discover what hasn’t been imagined."
"The very data planners rely on become unreliable as people adapt their behavior to avoid being captured by the system. Our research on post-socialist transitions shows that meaningful price signals only re-emerged after private exchange and budget discipline were restored. Computational power didn’t restore order—institutional reform did."
So it is interesting to see Robert Heilbroner in his essay Socialism that he says motivation was the problem:
"The effects of the “bureaucratization of economic life” are dramatically related in The Turning Point, a scathing attack on the realities of socialist economic planning by two Soviet economists, Nikolai Smelev and Vladimir Popov, that gives examples of the planning process in actual operation. In 1982, to stimulate the production of gloves from moleskins, the Soviet government raised the price it was willing to pay for moleskins from twenty to fifty kopecks per pelt. Smelev and Popov noted:
State purchases increased, and now all the distribution centers are filled with these pelts. Industry is unable to use them all, and they often rot in warehouses before they can be processed. The Ministry of Light Industry has already requested Goskomtsen [the State Committee on Prices] twice to lower prices, but “the question has not been decided” yet. This is not surprising. Its members are too busy to decide. They have no time: besides setting prices on these pelts, they have to keep track of another 24 million prices. And how can they possibly know how much to lower the price today, so they won’t have to raise it tomorrow?This story speaks volumes about the problem of a centrally planned system. The crucial missing element is not so much “information,” as Mises and Hayek argued, as it is the motivation to act on information. After all, the inventories of moleskins did tell the planners that their production was at first too low and then too high. What was missing was the willingness—better yet, the necessity—to respond to the signals of changing inventories. A capitalist firm responds to changing prices because failure to do so will cause it to lose money. A socialist ministry ignores changing inventories because bureaucrats learn that doing something is more likely to get them in trouble than doing nothing, unless doing nothing results in absolute disaster."
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