Artificial Intelligence: A Survey for Po

Updated course description: Artificial intelligence is not a purely technical field. Its roots lie in computer science, statistics, cognitive science, philosophy, linguistics, and other areas, and the policy questions are similarly varied. AI is at once a set of methods with a particular history and mathematical structure; a technology through which institutions make decisions about employment, finance, health, criminal justice, and more; and an international industry built on commercial incentives and physical infrastructure, including semiconductors, data centers, energy grids, and mineral supply chains. These dimensions are often treated separately, but many of the most consequential questions for policy arise where they meet.

This course examines AI from all these perspectives. It gives a basic foundation in computer science and machine learning, then uses concrete case studies to examine how technical choices interact with institutions, markets, law, and public policy. Topics may include government services, labor and workplace management, finance, healthcare, privacy, security, fairness, criminal justice, policing, immigration, facial recognition, and autonomous systems. The political economy of AI, including industrial concentration, compute, infrastructure, labor, trade, and the distribution of benefits and harms, serves as a throughline across the course.

The class is highly reading- and writing-intensive. One of its central goals is to train students to read contemporary research in artificial intelligence from a policy perspective, including work from computer science and adjacent technical fields. The instructor served as the first Director of AI for New York City and draws on that experience throughout. The course also includes guest speakers who work directly on significant AI and AI policy projects.