Rational Polarization

The Philosophical Review (forthcoming)
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Abstract

Predictable polarization is everywhere: we can often predict how people’s opinions—including our own—will shift over time. Extant theories either neglect the fact that we can predict our own polarization, or explain it through irrational mechanisms. They needn’t. Empirical studies suggest that polarization is predictable when evidence is ambiguous, i.e. when the rational response is not obvious. I show how Bayesians should model such ambiguity, and then prove that—assuming rational updates are those which obey the value of evidence (Blackwell 1953; Good 1967)—ambiguity is necessary and sufficient for the rationality of predictable polarization. The main theoretical result is that there can be a series of such updates, each of which is individually expected to make you more accurate, but which together will predictably polarize you. Polarization results from asymmetric increases in accuracy. This mechanism is not only theoretically possible, but empirically plausible. I argue that cognitive search—searching a cognitively-accessible space for a particular item—often yields asymmetrically ambiguous evidence; I present an experiment supporting its polarizing effects; and I use simulations to show how it can help explain two of the core causes of polarization: confirmation bias and the group polarization effect.

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Kevin Dorst
Massachusetts Institute of Technology

Citations of this work

Evidence and Bias.Nick Hughes - forthcoming - In Clayton Littlejohn & Maria Lasonen Aarnio (eds.), Routledge Handbook of the Philosophy of Evidence.
Being Rational and Being Wrong.Kevin Dorst - 2023 - Philosophers' Imprint 23 (1).
Echo Chambers.M. Giulia Napolitano - forthcoming - In Kurt Sylvan, Matthias Steup, Ernest Sosa & Jonathan Dancy (eds.), The Blackwell Companion to Epistemology, Third Edition.
Political polarization: Radicalism and immune beliefs.Manuel Almagro - 2023 - Philosophy and Social Criticism 49 (3):309-331.
Bounded Reflectivism and Epistemic Identity.Nick Byrd - 2022 - Metaphilosophy 53 (1):53-69.

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References found in this work

Knowledge and its limits.Timothy Williamson - 2000 - New York: Oxford University Press.
Thinking, Fast and Slow.Daniel Kahneman - 2011 - New York: New York: Farrar, Straus and Giroux.
The Structure of Scientific Revolutions.Thomas S. Kuhn - 1962 - Chicago, IL: University of Chicago Press. Edited by Ian Hacking.
The Foundations of Statistics.Leonard J. Savage - 1954 - Wiley Publications in Statistics.

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