Prof. Kobi Gal

A Citizens' Assembly (CA) is a democratic innovation tool where a randomly selected group of citizens deliberate a topic over multiple rounds to generate, and then vote upon, policy recommendations. Despite growing popularity, little work exists on understanding how CA inputs, such as the expert selection process and the mixing method used for discussion groups, affect results, and therefore on how to systematically set such parameters to optimize the process. In this work, we model CA deliberation and opinion change as a Multi-Agent Systems problem. We introduce and formalise a set of criteria for evaluating successful CAs using insight from previous CA trials and theoretical results. Although real-world trials meet these criteria, we show that finding a model that does so is nontrivial; through simulations and theoretical arguments, we show that established opinion change models fail at least one of these criteria. This is an extended abstract of a JAAMAS article [2].