Equity and Governance for Artificial Intelligence

Catalog description

This course invites students to argue about the consensus-building processes that shape the development and governance of AI systems. This course requires writing op-eds, policy memos, and research papers, in which students will critically engage AI policy documents while debating norms of fairness, accountability, and transparency. Students will also get hands-on practice evaluating generative AI models with interactive red-teaming and automated test suites (requires a small amount of coding in a group project). Students will engage real-world legislative proposals and case studies topics including human rights, artwork, the environment, and geopolitics. This course fulfills both the ethics and Writing in the Major WiM requirements, and is designed to prepare Stanford juniors, seniors, and graduate students to participate in AI public policy design at the national and global levels. Prerequisites: PWR1, PWR2, CS106A and CS106B. While this course requires no other prerequisites, it is designed for students who are comfortable engaging in an active learning environment that will include interactive workshops, student debates, and collaborative group projects. Students will be expected to speak frequently in sections and navigate the social dynamics of multi-stakeholder negotiations. Comfort with writing short python programs and working on a Unix/Linux command-line interface will be helpful for the AI model evaluation group project.