Disagreement is a ubiquitous feature of human life, and philosophers have dutifully attended to it. One important question related to disagreement is epistemological: How does a rational person change her beliefs (if at all) in light of disagreement from others? The typical methodology for answering this question is to endorse a steadfast or conciliatory disagreement norm (and not both) on a priori grounds and selected intuitive cases. In this paper, I argue that this methodology is misguided. Instead, a thoroughgoingly Bayesian strategy is what’s needed. Such a strategy provides conciliatory norms in appropriate cases and steadfast norms in appropriate cases. I argue, further, that the few extant efforts to address disagreement in the Bayesian spirit are laudable but uncompelling. A modelling, rather than a functional, approach gets us the right norms and is highly general, allowing the epistemologist to deal with (1) multiple epistemic interlocutors, (2) epistemic superiors and inferiors (i.e. not just epistemic peers), and (3) dependence between interlocutors.
“The Epistemology of Disagreement: Why Not Bayesianism?”
“The Epistemology of Disagreement: Why Not Bayesianism?”
Recent Publications
- Common Law Liberalism: A New Theory of the Libertarian Society (Oxford University Press, 2024)
- “Diversity and Group Performance,” Encyclopedia of Diversity, Springer, 2024
- “Evading and Aiding: The Moral Case Against Paying Taxes,” with Christopher Freiman and Jessica Flanigan, Extreme Philosophy, ed. Stephen Hetherington, Routledge (2024)
- “Online Sports Betting Giants Place Their Bets Against Growing Rivals”
- “Liberal Tolerance for an Illiberal, Intolerant Age”
Recent News
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- Jason Brennan and Hélène Landemore, Debating Democracy (University of Zurich’s UBS Center, 2024)
- Jason Brennan “Everything Wrong with Democracy” on the Alex O’Connor Podcast (January 28, 2024)
- On the affirmative action ruling, the Supreme Court got it half right