Complementarity and Delegation in Multi-Agent Models

When multiple agents -- potentially consisting of a mixture of AI and human participants -- collaborate on a task, they often bring complementary abilities and information sources. This leads to a number of computational problems related to the optimal way to synthesize decisions, and for determining when and how one member of the group should delegate to others. We'll consider a set of related problems of this form, focusing on choices related to hand-off, delegation, and the role of distinct information sources. The talk is based on joint work with Solon Barocas, Kate Donahue, Nikhil Garg, Sophie Greenwood, Hoda Heidari, Karen Levy, Gali Noti, Sigal Oren, and Kenny Peng.