Abstract

The standard principle of expert deference says that conditional on the expert’s credence in a proposition _A_ being _x_, your credence in _A_ ought to be _x_. The so-called Adams conditionalization is an attractive update rule in situations when learning experience prompts a shift in your conditional credences. In this paper, I show that, except in some trivial situations, when your prior conditional credence in _A_ obeys the standard principle of expert deference and then is revised by Adams conditionalization in response to a shift in your conditional credence for a proposition _B_ given _A_, your posterior conditional credence in _A_ cannot continue to obey that principle, on pain of inconsistency. I explain why this tension between Adams conditionalization and the standard principle of expert deference is puzzling and why the option of rejecting the update rule appears problematic. Finally, I suggest that in order to avoid this inconsistency, we should abandon the standard principle of expert deference and think of an expert’s probabilistic opinion as a constraint on your posterior credence distribution rather than your prior one.