(Note that throughout this post, when we refer to an agent “revising” their prior in light of awareness growth, we are not talking about Bayesian conditionalization. We are talking about specifying a new prior over their new awareness state, which contains propositions that they had not previously conceived of.)
Nice. One reason this is important is that if you were just doing the bayesian conditionalization thing, you’d be giving up on some of the benefits of being updateless, and in particular making it easy for others to exploit you. I’ll be interested to read and think about whether doing this other thing avoids that problem.
What do you mean by “the Bayesian Conditionalization thing” in this context? (Just epistemically speaking, standard Conditionalization is inadequate for dealing with cases of awareness growth. Suppose, for example, that one was aware of propositions {X, Y}, and that this set later expands to {X, Y, Z}. Before this expansion, one had a credence P(X ∨ Y) = 1, meaning Conditionalization recommends remaining certain in X ∨ Y; i.e., one is only permitted to place a credence P(Z) = 0. Maybe you are referring to something like Reverse Bayesianism?)
I just meant standard conditionalization, which I agree is inadequate for cases of awareness growth. I wasn’t making a particularly new point, just commenting aloud as I read along.
Nice. One reason this is important is that if you were just doing the bayesian conditionalization thing, you’d be giving up on some of the benefits of being updateless, and in particular making it easy for others to exploit you. I’ll be interested to read and think about whether doing this other thing avoids that problem.
What do you mean by “the Bayesian Conditionalization thing” in this context? (Just epistemically speaking, standard Conditionalization is inadequate for dealing with cases of awareness growth. Suppose, for example, that one was aware of propositions {X, Y}, and that this set later expands to {X, Y, Z}. Before this expansion, one had a credence P(X ∨ Y) = 1, meaning Conditionalization recommends remaining certain in X ∨ Y; i.e., one is only permitted to place a credence P(Z) = 0. Maybe you are referring to something like Reverse Bayesianism?)
I just meant standard conditionalization, which I agree is inadequate for cases of awareness growth. I wasn’t making a particularly new point, just commenting aloud as I read along.