Guiding Questions

• How does the process of machine learning differ from traditional computer programming, and what unique legal challenges does this difference create?
• What fundamental tensions exist between rapid AI development and our current legal frameworks? Which seem most urgent to address?
• How should we balance the benefits of AI innovation against the need for oversight and regulation? What role should law play in this balance?

Required

• R2D3 (Stephanie Yee and Tony Chu), A Visual Introduction to Machine Learning

• David Lehr & Paul Ohm, Playing with the Data: What Legal Scholars Should Learn About Machine Learning, 51 U.C. DAVIS L. REV. 652 (2017) (Intro, Part II)

• Ryan Calo, Artificial Intelligence Policy: A Primer and Roadmap, 51 U.C. DAVIS L. REV. 399 (2017) (skim Part II)

• Bryan Casey, Amoral Machines, Or: How Roboticists Can Learn to Stop Worrying and Love the Law, 112 NW. U. L. REV. 1 (2017)

Optional

• Marc Andreessen, Why AI Will Save the World, ANDREESSEN HOROWITZ (June 6, 2023).

• Dario Amodei, Machines of Loving Grace: How AI Could Transform the World for the Better (Oct. 2024).

• Interview with Arvind Narayanan & Sayash Kapoor in Justin Hendrix, AI Snake Oil: Separating Hype from Reality, TECH POL'Y PRESS (Sept. 29, 2024).