ACL2025
Can Language Models Reason about Individualistic Human Values and Preferences?
Liwei Jiang, Taylor Sorensen, Sydney Levine, Yejin Choi
Abstract
Recent calls for pluralistic alignment emphasize that AI systems should address the diverse needs of all people. Yet, existing methods and evaluations often require sorting people into fixed buckets of pre-specified diversity-defining dimensions (e.g., demographics, personalities, communication styles), oversimplifying the rich spectrum of individualistic variations. To achieve an authentic representation of