Collective Decision

Collective decision-making research focuses on understanding how individual preferences are aggregated into group choices, aiming to develop efficient and fair decision-making mechanisms. Current research explores diverse approaches, including machine learning models like neural networks and tailored embeddings to learn optimal voting rules, and applying social choice theory to guide AI alignment and improve the reliability of predictions from human feedback. This field is crucial for advancing AI safety, optimizing predictive maintenance, and improving the design of various systems relying on aggregated human input, impacting fields from computer science and engineering to social sciences and political science.