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> In the case of poker, it appears that adaptability is not as good as pure mathematical optimization. Humans can adapt their strategy, but it’s basically just worse regardless because this thing has cracked the code.

Adaptability is beaten by perfect strategic play in games with clear victory conditions.

My familiarity with optimal control theory is nil but Kydland (1977) applied it to monetary policy to show that the right rules dominate discretion. What the right rules are for monetary policy is still an open question though, because while the victory conditions in economic policy are clearly defined the surrounding environment is very far from static so you deal with out of training set data regularly. Once AI can deal with these kind of out of context problems it seems plausible GAI is a matter of time.


> Rules Rather than Discretion: The Inconsistency of Optimal Plans

> Even if there is an agreed-upon, fixed social objective function and policymakers know the timing and magnitude of the effects of their actions, discretionary policy, namely, the selection of that decision which is best, given the current situation and a correct evaluation of the end- of-period position, does not result in the social objective function being maximized. The reason for this apparent paradox is that economic planning is not a game against nature but, rather, a game against rational economic agents. We conclude that there is no way control theory can be made applicable to economic planning when expectations are rational.

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