Sortition is the practice of delegating public decision-making to randomly selected panels. Recently, it has gained momentum worldwide through its use in citizens' assemblies, sparking growing interest within the computer science community. One key appeal of sortition is that random panels tend to be more representative of the population than elected committees or parliaments. Our main conceptual contribution is a novel definition of representative panels, based on the Wasserstein distance from statistical learning theory. Using this definition, we develop a framework for analyzing the panel complexity problem -- determining the required panel size to ensure desirable properties. We focus on three key desiderata: (1) that efficiency at the panel level extends to the whole population, measured by social welfare; (2) that fairness guarantees for the panel translate to fairness for the population, captured by the core; and (3) that the probability of an outlier panel, for which the decision significantly deviates from the optimal one, remains low. We establish near-tight panel complexity guarantees for these desiderata across two fundamental social choice settings: participatory budgeting and facility location.
View on arXiv@article{brustle2025_2504.20508,
title={ The Panel Complexity of Sortition: Is 12 Angry Men Enough? },
author={ Johannes Brustle and Simone Fioravanti and Tomasz Ponitka and Jeremy Vollen },
journal={arXiv preprint arXiv:2504.20508},
year={ 2025 }
}