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This lecture discusses the concepts of fairness, representativeness, and transparency in the context of citizens' assemblies. It covers the goals of representativeness and fairness in panel selection, the status quo of panel selection algorithms, and the mathematical programming formulations used to achieve maximal fairness. The lecture also explores the practical impact of fair selection algorithms, the transparency of lottery processes, and future work in democratic innovation and fair machine learning.
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