Presenter: Grant Schoenebeck, University of Michigan Abstract: Advances in machine learning enable new forms of human-AI collaboration, but collaborative settings typically involve agents with divergent objectives and private information. This will become increasingly critical in the emerging world of agentic AI, where ML-powered agents act on behalf of individuals or institutions with conflicting goals. I use the […]