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Explore the intersection of artificial intelligence and democratic decision-making in this seminar examining computational frameworks designed to identify common ground among collective preferences. Delve into the evolution from traditional polling methods to emerging technologies like the Habermas Machine, understanding how AI-assisted preference elicitation builds upon the historical foundation of opinion polling while recognizing that preferences are dynamic products of their decision-making contexts. Analyze when and how AI-based democratic innovations can serve as discovery tools to help societies navigate disagreement, surface shared reasoning, and pursue informed consensus. Examine both the promising potential of these systems to enhance democratic processes and their concerning risks, including enabling unreflective binding decisions, normalizing gradual disempowerment, and post-rationalizing political outcomes. Consider fundamental questions about what these systems should be designed to reveal and what aspects of democratic participation they must never replace, grounding the discussion in mathematical models, computational approaches, and political theory to understand collective agency in our increasingly networked, AI-mediated world.
