But I claim it is an inevitable consequence of your suggestion, since the same sort of arguments that might be made about which way of calculating the probability can be made about which utility problem to solve, if you’re doing the same math. Or put another way, you can take the decision-theory result and use it to calculate the rational probabilities, so any stance on using decision theory is a stance on probabilities (if the rewards are fixed).
I think the problem just looks so obvious to us when we use decision theory that we don’t connect it to the non-obvious-seeming dispute over probabilities.
Again, I didn’t suggest trying to reformulate a problem as a decision problem as a way of figuring out which probability to assign. Probability-assignment is not an interesting game. My point was that if you want to understand a problem, understand what’s going on in a given situation, consider some decision problems and try to solve them, instead of pointlessly debating which probabilities to assign (or which decision problems to solve).
Oh, so you don’t think that viewing it as a decision problem clarifies it? Then choosing a decision problem to help answer the question doesn’t seem any more helpful than “make your own decision on the probability problem,” since they’re the same math. This then veers toward the even-more-unhelpful “don’t ask the question.”
Then choosing a decision problem to help answer the question doesn’t seem any more helpful than “make your own decision on the probability problem,” since they’re the same math.
It’s not intended to help with answering the question, no more than dissolving any other definitional debate helps with determining which definition is the better. It’s intended to help with understanding of the thought experiment instead.
Changing the labels on the same math isn’t “dissolving” anything, as it would if probabilities were like the word “sound.” “Sound” goes away when dissolved because it’s subjective and dissolving switches to objective language. Probabilities are uniquely derivable from objective language. Additionally there is no “unaskable question,” at least in typical probability theory—you’d have to propose a fairly extreme revision to get a relevant decision theory answer to not bear on the question of probabilities.
But I claim it is an inevitable consequence of your suggestion, since the same sort of arguments that might be made about which way of calculating the probability can be made about which utility problem to solve, if you’re doing the same math. Or put another way, you can take the decision-theory result and use it to calculate the rational probabilities, so any stance on using decision theory is a stance on probabilities (if the rewards are fixed).
I think the problem just looks so obvious to us when we use decision theory that we don’t connect it to the non-obvious-seeming dispute over probabilities.
Again, I didn’t suggest trying to reformulate a problem as a decision problem as a way of figuring out which probability to assign. Probability-assignment is not an interesting game. My point was that if you want to understand a problem, understand what’s going on in a given situation, consider some decision problems and try to solve them, instead of pointlessly debating which probabilities to assign (or which decision problems to solve).
Oh, so you don’t think that viewing it as a decision problem clarifies it? Then choosing a decision problem to help answer the question doesn’t seem any more helpful than “make your own decision on the probability problem,” since they’re the same math. This then veers toward the even-more-unhelpful “don’t ask the question.”
It’s not intended to help with answering the question, no more than dissolving any other definitional debate helps with determining which definition is the better. It’s intended to help with understanding of the thought experiment instead.
Changing the labels on the same math isn’t “dissolving” anything, as it would if probabilities were like the word “sound.” “Sound” goes away when dissolved because it’s subjective and dissolving switches to objective language. Probabilities are uniquely derivable from objective language. Additionally there is no “unaskable question,” at least in typical probability theory—you’d have to propose a fairly extreme revision to get a relevant decision theory answer to not bear on the question of probabilities.