Social Choice

Social choice theory studies methods for aggregating individual preferences into collective decisions, aiming to design fair and efficient voting systems and preference aggregation mechanisms. Current research focuses on developing and analyzing novel voting rules, often leveraging machine learning techniques like neural networks to learn optimal aggregation functions from data, and applying these methods to diverse applications such as recommender systems and AI alignment. This field is crucial for addressing challenges in fair resource allocation, democratic decision-making, and the ethical development of AI systems, offering both theoretical frameworks and practical algorithms for improving collective choices.