That analogy is helpful, thanks. I think I still feel like there’s a gap between developing a good theory of decision-making and putting that theory into immediate practice. For instance, immediately after developing expected utility theory, I could imagine there’s a processing gap among someone who isn’t used to using it to make everyday decisions; I feel a meaningful amount of doubt that von Neumann was much less likely to read books while driving after internalizing expected utility theory (obviously, maybe his preference for doing this was just that strong, but let’s suppose it was in fact irrational of him!). I’d guess this would especially be true with high-pressure decision-making.
I don’t have a good picture of what solving agent foundations would look like, but I could also imagine a lot of theoretical problems being solved in ways that are not immediately translatable into decision-making. Expected utility theory has the advantage of feeling “simple,” in some way, to translate into a real-world decision. Do you think it would be comparably easy to intuit this kind of solution? (Genuinely unfamiliar here, and am open to believing that it would be!)
I’m persuaded, however, that if solving agent foundations would lead to a theory that powerful, it would cause better decision-making. I’m still intuitively skeptical that it would be better enough; I’d guess I would have to try to visualize object-level solutions better to get some intuition for why.
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