Finding Common Ground in a Sea of Alternatives
We study the problem of selecting a statement that finds common ground across diverse population preferences. Generative AI is uniquely suited for this task because it can access a practically infinite set of statements, but AI systems like the Habermas machine leave the choice of generated statement to a voting rule. What it means for this rule to find common ground, however, is not well-defined. In this work, we propose a formal model for finding common ground in the infinite alternative setting based on the proportional veto core from social choice. To provide guarantees relative to these infinitely many alternatives and a large population, we wish to satisfy a notion of proportional v...
| Authors | Jay Chooi, Paul Gölz, Ariel D. Procaccia et al. |
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| Primary category | cs.GT |
| Published | 17 March 2026 |
| Last updated at source | 17 March 2026 |
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