Objective Bayesianism and the Abductivist Response to Scepticism

An important line of response to scepticism appeals to the best explanation. But anti-sceptics have not engaged much with work on explanation in the philosophy of science. I plan to investigate whether plausible assumptions about best explanations really do favour anti-scepticism. I will argue that there are ways of constructing sceptical hypotheses in which the assumptions do favour anti-scepticism, but the size of the support for anti-scepticism is small.

Objective Bayesianism and Knowledge-First Epistemology

This chapter distinguishes between subjective and objective versions of Bayesianism, arguing for the latter variety. The distinction is made in terms of constraints on ur-priors. Lewis’s “Principal Principle” is discussed as one such constraint. The Carnapian program of delineating a unique ur-prior in purely syntactical terms is presented, and rejected for familiar reasons. It is then argued that the failure of the Carnapian program does not entail the failure of Objective Bayesianism more generally. Ur-prior Conditionalization is introduced as a better alternative to Conditionalization. The chapter ends by presenting Factualism, the view that our evidence consists of what we know.

The Principal Principle and subjective Bayesianism

This paper poses a problem for Lewis’ Principal Principle in a subjective Bayesian framework: we show that, where chances inform degrees of belief, subjective Bayesianism fails to validate normal informal standards of what is reasonable. This problem points to a tension between the Principal Principle and the claim that conditional degrees of belief are conditional probabilities. However, one version of objective Bayesianism has a straightforward resolution to this problem, because it avoids this latter claim. The problem, then, offers some support to this version of objective Bayesianism.

Naturalness as a Constraint on Priors

Many epistemological problems can be solved by the objective Bayesian view that there are rationality constraints on priors, that is, inductive probabilities. But attempts to work out these constraints have run into such serious problems that many have rejected objective Bayesianism altogether. I argue that the epistemologist should borrow the metaphysician’s concept of naturalness and assign higher priors to more natural hypotheses.

Inference to the Best Explanation, Bayesianism, and Knowledge

How do we reconcile the claim of Bayesianism to be a correct normative theory of scientific reasoning with the explanationists’ claim that Inference to the Best Explanation (IBE) provides a correct description of our inferential practices? This chapter articulates and defends a version of the heuristic defence of IBE. Three challenges remain that focus on the idea that IBE can lead to knowledge. Answering those challenges requires renouncing standard Bayesianism’s commitment to personalism, while also going beyond objective Bayesianism regarding the constraints on good priors. The result is a non-standard, super-objective Bayesianism that identifies probabilities with evaluations of plausibility in the light of the evidence.