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REPRESENTATION IN MODELS OF EPISTEMIC DEMOCRACY

Published online by Cambridge University Press:  21 December 2018

Patrick Grim ,
Aaron Bramson ,
Daniel J. Singer ,
William J. Berger ,
Jiin Jung  and
Scott E. Page
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Abstract

Epistemic justifications for democracy have been offered in terms of two different forms of information aggregation and decision-making. The Condorcet Jury Theorem is appealed to as a justification in terms of votes, and the Hong–Page ‘diversity trumps ability’ result is appealed to as a justification in terms of deliberation in the form of collaborative search. Both results, however, are models of full and direct participation across a population. In this paper, we contrast how these results hold up within the familiar structure of a representative hierarchy. We first consider extant analytic work that shows that representation inevitably weakens the voting results of the Condorcet Jury Theorem. We then go on to show that collaborative search, as modeled by Hong and Page, holds its own within hierarchical representation. In a variation on the dynamics of group search, representation even shows a slight edge over direct participation. This contrast illustrates how models of information aggregation vary when put into a representative structure. While some of the epistemic merits of democracy are lost when voting is done hierarchically, modeling results show that representation can preserve and even slightly amplify the epistemic virtues of collaborative search.

Type
Articles
Information
Episteme , Volume 17 , Issue 4 , December 2020 , pp. 498 - 518
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Copyright
Copyright © Cambridge University Press 2018

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Footnotes

This work was produced by the computational social philosophy lab (cspl), an interdisciplinary and multi-institutional group of researchers that investigates questions of social epistemology, philosophy of science, and political philosophy using traditional philosophical methods and agent-based computer models with an eye toward empirical results.

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