When Democracy Meets the Algorithm: Auditing Representation in the Age of LLMs
Opening — Why this matters now The rise of AI in civic life has been faster than most democracies can legislate. Governments and NGOs are experimenting with large language models (LLMs) to summarize public opinions, generate consensus statements, and even draft expert questions in citizen assemblies. The promise? Efficiency and inclusiveness. The risk? Representation by proxy—where the algorithm decides whose questions matter. The new paper Question the Questions: Auditing Representation in Online Deliberative Processes (De et al., 2025) offers a rigorous framework for examining that risk. It turns the abstract ideals of fairness and inclusivity into something measurable, using the mathematics of justified representation (JR) from social choice theory. In doing so, it shows how to audit whether AI-generated “summary questions” in online deliberations truly reflect the people’s diverse concerns—or just the most statistically coherent subset. ...