3.0

Average Course Rating

This advanced course explores state-of-the-art AI methods for social science research, focusing on LLM-based approaches including synthetic participants, AI-augmented surveys, and computational simulations of human behavior, including historical participants. Students will critically evaluate recent work (2023-2026) through paper discussions and an original research project. Projects will involve empirical work with publication potential, such as replication studies comparing synthetic to human data, meta-analyses of field practices, or development of validation frameworks for the emerging field of AI-augmented social science. Required Course Background: At least one graduate-level computer science course in Artificial Intelligence or Machine Learning (including CSS, NLP, Computer Vision, etc.), two preferred, or permission of the instructor. Students must be comfortable with reading recent research papers and discussing key concepts and ideas.