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A Mathematical Model for Optimal Decisions in a Representative Democracy

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  • Malik Magdon-Ismail
  • Lirong Xia

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 decisions simultaneously for multiple noisy issues. 2. When the cost of voting is fixed, the optimal representative democracy requires that representatives are elected from constant sized groups: the number of representatives should be linear in the number of voters. 3. When the cost and benefit of voting are both polynomial, the optimal group size is close to linear in the number of voters. This work sets the mathematical foundation for studying the quality-quantity tradeoff in a representative democracy-type ensemble (fewer highly qualified representatives versus more less qualified representatives).

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  • Malik Magdon-Ismail & Lirong Xia, 2018. "A Mathematical Model for Optimal Decisions in a Representative Democracy," Papers 1807.06157, arXiv.org.
    • Handle: RePEc:arx:papers:1807.06157
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    References listed on IDEAS

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    Cited by:

    1. Ben Abramowitz & Nicholas Mattei, 2022. "Towards Group Learning: Distributed Weighting of Experts," Papers 2206.02566, arXiv.org.
    2. Ben Abramowitz & Omer Lev & Nicholas Mattei, 2022. "Who Reviews The Reviewers? A Multi-Level Jury Problem," Papers 2211.08494, arXiv.org, revised Dec 2023.

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