A Bayesian analysis of debunking arguments in ethics

Shang Long Yeo*

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    Abstract

    Debunking arguments in ethics contend that our moral beliefs have dubious evolutionary, cultural, or psychological origins—hence concluding that we should doubt such beliefs. Debates about debunking are often couched in coarse-grained terms—about whether our moral beliefs are justified or not, for instance. In this paper, I propose a more detailed Bayesian analysis of debunking arguments, which proceeds in the fine-grained framework of rational confidence. Such analysis promises several payoffs: it highlights how debunking arguments don’t affect all agents, but rather only those agents who updated on their intuitions using a specific range of evidentiary weights; it underscores how the debunkers shouldn’t conclude that we should reduce confidence beyond some threshold, but rather only that we should reduce confidence by some amount; and it proposes a method of integrating different kinds of evidence—about the kinds of epistemic flaws at play, about the different possible origins of our moral beliefs, about the background normative assumptions we’re entitled to make—in order to arrive at a rational moral credence in light of debunking.

    Original languageEnglish
    Pages (from-to)1673-1692
    Number of pages20
    JournalPhilosophical Studies
    Volume179
    Issue number5
    DOIs
    Publication statusPublished - May 2022

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