On Richard Pettigrew's latest accuracy-first argument for Probabilism

(Epistemology, English)

ayesianism aims to give a general normative account of reasoning by giving rationality constraints for credences, i.e. for how strong we believe in propositions. Its fundamental tenet is a coherence norm called Probabilism. This norm says that, in order to be epistemically rational, our credences need to be probabilistic, i.e. they need to satisfy the Kolmogorov axioms for probability.

One recent promising strategy to argue for Probabilism is given in accuracy-first arguments. The core claim is that truth is the only epistemic goal. A mathematic characterization of distance from truth is given. It is then shown via a theorem that probabilistic credences are systematically closer to the truth than non-probabilistic credences.

Richard Pettigrew, in his wonderfully perspicuous and comprehensive 2016 book ''Accuracy and the Laws of Credence'', surveys all previous accuracy-first arguments for Probabilism and argues persuasively that each of them fails. He then presents his own proposal. I will argue that it fails as well. Moreover, the reason why it fails constitutes a challenge for future accuracy-first arguments.

Pettigrew's theorem rests almost exclusively on Decomposition, the claim that distance from truth decomposes linearly into two parts. First, distance from being well-calibrated, where a credence function is well-calibrated if 80 percent of the propositions believed to degree 0.8 are true, and so forth. Second, distance between being well calibrated and truth.

I show that Pettigrew's justification for Decomposition ultimately rests on an alleged intuition that in certain ceteris paribus situations, closeness to being well calibrated correlates with closeness to truth. I argue that there is no such intuition. In fact, I consider a specific kind of example for these ceteris paribus situations in which there is an intuition against such a correlation. Basically, this intuition is that moving a credence away from the truth should not be punished harder in terms of accuracy than moving towards it is rewarded. Moreover, I show that this intuition conflicts with the so-called Brier score, a popular measure for distance from truth. I argue that this constitutes a challenge for future accuracy-first arguments.

Chair:

Time: 14:40-15:10, 18 September 2019 (Wednesday)

Location: HS E.002

Richard C. Lohse

(University of Konstanz, Germany)

Richard Lohse received a bachelor's degree in physics in 2015 and a master's degree in philosophy in 2018, both at the University of Konstanz. He is interested in all subdisciplines of analytic philosophy, but focuses on epistemology.

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