University of Chicago
Monday, November 6, 2023
154 Hurley Hall
3:30 pm - 4:30 pm
Title: The Economics of Machine Learning
Abstract: This talk will introduce our recent works on the economics of machine learning, with two complementary themes: machine learning for economics and, conversely, economics for machine learning. The first theme focuses on designing and analyzing ML algorithms for economic problems, ranging from foundational game-theoretic models to real-world applications such as recommender systems and national security. The second theme employs economic principles to study machine learning itself, such as the pricing of data, information and ML models, and designing incentive mechanisms to improve large-scale ML research peer review. While the research focuses primarily on developing methodologies, we will also highlight some real-world impacts of these works, including ongoing large-scale live experiments and potential deployments in real applications.