Abstract

I examine Hume's account of chance and his account of probabilistic judgment for the light they throw on his theory of causal necessity. A chance event, in Hume's analysis, is the reciprocal inverse image of a caused event. And an ordinary, full-confidence judgment of causal necessitation is, for Hume, a kind of limit case of probabilistic judgment—a case where our distribution of confidence across the various possible outcomes coalesces into one unique expectation. I argue that both Hume's treatment of chance and his treatment of probability help to cement the case for the expressivist interpretation of his theory of causal necessity.