Citizens’ assemblies, randomly selected panels contributing to policy questions, necessitate selection algorithms balancing representativeness and equal selection probabilities. Existing algorithms prioritize representativeness, neglecting equal opportunity. This paper introduces algorithms achieving maximal fairness by selecting representative panels while making individual selection probabilities as close to equal as possible. An implemented algorithm, already used globally for over 40 assemblies, demonstrates substantially fairer selection probabilities than previous methods.
Publisher
Nature
Published On
Aug 26, 2021
Authors
Bailey Flanigan, Paul Gölz, Anupam Gupta, Brett Hennig, Ariel D. Procaccia
Tags
citizens' assemblies
selection algorithms
representativeness
fairness
policy questions
equal selection probabilities
randomly selected panels
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