5 papers
Internal Pluralism and the Limits of Pairwise Comparisons
Bailey Flanigan, Michelle Si
Local pairwise comparisons are a standard tool for learning how people want decision rules to work, e.g., in participatory design or alignment. However, their use builds in two str…
The End Justifies the Mean: A Linear Ranking Rule for Proportional Sequential Decisions
Carmel Baharav, Niclas Boehmer, Bailey Flanigan +1
AI alignment and participatory design motivate a new democratic design problem: how to collectively choose a decision rule to use repeatedly. We study this problem for linear ranki…
Strategic Candidacy in Generative AI Arenas
Chris Hays, Rachel Li, Bailey Flanigan +1
AI arenas, which rank generative models from pairwise preferences of users, are a popular method for measuring the relative performance of models in the course of their organic use…
Near-Optimal Dropout-Robust Sortition
Maya Pal Gambhir, Bailey Flanigan, Aaron Roth
Citizens' assemblies - small panels of citizens that convene to deliberate on policy issues - often face the issue of panelists dropping out at the last-minute. Without interventio…
Alternates, Assemble! Selecting Optimal Alternates for Citizens' Assemblies
Angelos Assos, Carmel Baharav, Bailey Flanigan +1
Citizens' assemblies are an increasingly influential form of deliberative democracy, where randomly selected people discuss policy questions. The legitimacy of these assemblies hin…