Nathaniel Baron-Schmitt

This paper gives a new account of the actuality entailments of ability claims. We observe that, in the environments which give rise to the actuality entailment, ability claims carry a presupposition of trying. We show that, given this presupposition, the actuality entailment is straightforwardly predicted by a conditional theory of ability. We give a theory of why this presupposition arises, showing how to derive it from a presupposition of strong settledness. We then show how to predict contextual variation in the precise content of our presupposition; how to extend our account to apparent deontic and teleological actuality entailments; and how to adapt our account to more sophisticated conditional accounts of ability.

Accuracy-first epistemology says that the rational update rule is the rule that maximizes expected accuracy. Externalism says, roughly, that we do not always know what our total evidence is. It’s been argued in recent years that the externalist faces a dilemma: Either deny that Bayesian Conditionalization is the rational update rule, thereby rejecting traditional Bayesian epistemology, or else deny that the rational update rule is the rule that maximizes expected accuracy, thereby rejecting the accuracy-first program. Call this the Bayesian Dilemma. Here is roughly how the argument goes. Schoenfield (2017) has shown that following Metaconditionalization maximizes expected accuracy. But if externalism is true, Metaconditionalization is not Bayesian Conditionalization. Therefore, the externalist must choose between the rule that maximizes expected accuracy (Metaconditionalization) and Bayesian Conditionalization. I am not convinced by this argument; once we make the premises fully explicit, we see that it relies on assumptions that the externalist has every reason to reject. Still, I think that the Bayesian Dilemma is a genuine dilemma. I give a new argument—I call it the continuity argument—that doesn’t make any assumptions the externalist rejects. Roughly, I show that if you're sufficiently confident that you will correctly identify your evidence, then you'll expect adopting a rule that I call Accurate Metaconditionalization to be more accurate than adopting Bayesian Conditionalization.