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Decision theory and dynamic inconsistency — LessWrong

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In this post I’ll discuss the last bullet in more detail since I think it’s a bit unusual, it’s not something I’ve written about before, and it’s one fo the main ways my view of decision theory has changed in the last few years. (Note: I think this topic is interesting, and could end up being relevant to the world in some weird-yet-possible situations, but I view it as unrelated to my day job on aligning AI with human interests.) In the transparent version of Newcomb’s problem, you are faced with two transparent boxes (one small and one big). The small box always contains $1,000. The big box contains either $10,000 or $0. You may choose to take the contents of one or both boxes. There is a very accurate predictor, who has placed $10,000 in the big box if and only if they predict that you wouldn’t take the small box regardless of what you see in the big one. Intuitively, once you see the contents of the big box, you really have no reason not to take the small box. For example, if you se

x Decision theory and dynamic inconsistency — LessWrong Decision theory AI Rationality Frontpage 85 Decision theory and dynamic inconsistency by paulfchristiano 3rd Jul 2022 Sideways View 11 min read 35 85 Here is my current take on decision theory: When making a decision after observing X, we should condition (or causally intervene) on statements like “My decision algorithm outputs Y after observing X.” Updating seems like a description of something you do when making good decisions in this way, not part of defining what a good decision is. ( More .) Causal reasoning likewise seems like a des

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