CS283: Governing Artificial Intelligence: Law, Policy, and Institutions

LAW4052/CS283/COMM252A/POLISCI245B/445B

Lectures: Monday & Wednesday, 2:15–3:45pm
Sections: Thursday or Friday, 2:30–3:20pm (optional), Room 14, basement of Crown
Location: Crown Building, Stanford Law School, Room 290
Website: cs283.stanford.edu

Syllabus details, including reading lists, are subject to change and may be updated up until two weeks before the start of a lecture.

Course description

Artificial intelligence (AI) is rapidly reshaping industries, institutions, and societies — and its governance is one of the most urgent and complex policy challenges of our time. This course explores how societies are responding to AI through technical interventions, law, regulation, ethics, professional standards, and institutional and organizational design. Taught by a cross-disciplinary faculty team, students will engage with historical analogues, present-day legal and policy debates, technical problems, and emerging governance models across democratic, authoritarian, and multilateral contexts. The course combines philosophical, social-scientific, legal, and technical readings with real-world case studies, inviting students to explore the limits and possibilities of governing AI.

There are no prerequisites.

Students should direct any questions to the course staff via Ed. You can also reach the Head CA at zappia@stanford.edu.

Learning objectives

By the end of the course, students will be able to:

Explain the technological foundations of modern AI systems, including how they are trained, evaluated, and deployed, and describe their broader societal implications.
Engage with technical governance problems, such as meaningful evaluation design, system access considerations, and privacy-preserving analysis of use and misuse of AI systems.
Critically evaluate the technical, organizational, and normative dimensions of AI oversight.
Analyze the historical patterns of governance responses to frontier technologies.
Identify and assess key legal, technical, and institutional approaches to AI governance across national and global contexts.
Anticipate and reason through future challenges in AI governance, including the role of closed vs. open models, (multi-)agents, low-resource models, disinformation, and global coordination.
Synthesize interdisciplinary perspectives to formulate and evaluate actionable governance proposals.

Attendance policy

Except in cases of an OAE accommodation or another valid reason that is brought to the course managers or a student’s course assistant’s attention before lecture, attendance at lectures is mandatory. If a student has a prolonged illness or a personal situation that might lead to more than one lecture absence, the student should contact a member of the course staff before missing a lecture. Attendance will be taken at the beginning of each class. Any student coming in late shall be marked as absent.