Preference Aggregation

Preference aggregation focuses on combining individual preferences to reach a collective decision, aiming to find methods that are both fair and efficient. Current research explores diverse approaches, including algorithms that leverage partial preferences to reduce data collection costs, the use of large language models to augment and predict aggregate preferences, and the development of robust aggregation methods that account for heterogeneous preferences and potential strategic behavior. These advancements have implications for various fields, from improving online services through personalized recommendations to designing more representative and responsive democratic systems.