A Mathematical Model for Optimal Decisions in a Representative Democracy
Malik Magdon-Ismail, Lirong Xia

TL;DR
This paper develops a mathematical model to optimize decision-making in representative democracies, demonstrating conditions under which they outperform direct voting, and identifying optimal group sizes for representatives based on costs and benefits.
Contribution
It introduces a formal mathematical framework for analyzing and optimizing the structure of representative democracies, focusing on decision accuracy and group size parameters.
Findings
Representative democracy can effectively decide on multiple noisy issues.
Optimal group size for representatives is linear in the number of voters under fixed costs.
When costs and benefits are polynomial, the optimal group size remains close to linear.
Abstract
Direct democracy is a special case of an ensemble of classifiers, where every person (classifier) votes on every issue. This fails when the average voter competence (classifier accuracy) falls below 50%, which can happen in noisy settings where voters have only limited information, or when there are multiple topics and the average voter competence may not be high enough for some topics. Representative democracy, where voters choose representatives to vote, can be an elixir in both these situations. Representative democracy is a specific way to improve the ensemble of classifiers. We introduce a mathematical model for studying representative democracy, in particular understanding the parameters of a representative democracy that gives maximum decision making capability. Our main result states that under general and natural conditions, 1. Representative democracy can make the correct…
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Taxonomy
TopicsGame Theory and Voting Systems · Electoral Systems and Political Participation
