For those of you who like to “live by the syllabus,” here’s the full class laid out, with the hyperlinks to each class (Throughout the semester I’ll be updating the links as we go).
AI Law and Policy Fall 2025 Syllabus
Class #1 (August 25): AI Fundamentals (What is AI)
Class #2 (August 27): AI Fundamentals (How Actually Works)
Class #3 (Sept. 3): Open Source Debate (Open v. Closed Models: What Happens When the World Runs on Chinese Code)
Class #4 (Sept. 8): Open Source Debate (The AI Control Paradox, Open Source Models)
Class #5 (Sept. 10): AI Model Training, Outputs, and Copyright (The $1.5 Billion Question: How AI Learns from the World’s Words)
Class #6 (Sept. 15): AI Model Training, Outputs, and Copyright (Training Data, Discovery Wars, and Who Gets Paid: When Courts Meet Code)
Class #7 (Sept. 17): Compute Power in AI (Why China Quit US Chips: When Controlling Compute failed to control AI)
Class #8 (September 22): Compute Power and Governance (Your Electricity Bill Is About to Become an AI Policy Issue: The Compute Governance Paradox)
Class #9 (September 24): Bias and Fairness (When AI Discrimination Happens 1.1 Billion Times: The Scale of Algorithmic Bias)
Class #10 (September 29): Transparency (The Glass Box Paradox, When AI Can’t Explain Itself: When Seeing Isn’t Understanding)
Class #11 (October 1): Accountability and Liability (When AI Fails, Who Pays?: The Bromide Poisoning and the Liability Puzzle)
Class #12 (October 6): AI Safety, Robustness, and Adversarial Attacks (Red-Teaming AI When AI Red-Teams You: “I think you’re testing me,” says Claude)
Class #13 (October 8): AI Safety, Robustness, and Adversarial Attacks (Red-Teaming Governance: From Practice to Law: When the NYT Became a “Hacker”)
Class #14 (October 20): Content Authentications, Deepfakes, Misinformation (When Anyone Can Fake Anything: Deepfake Technology and the Post-Truth World)
Class #15 (October 22): Content Authentications, Deepfakes, Misinformation (Why Governing AI Synthetic Media is So Hard—And Why Everyone’s Trying To Anyway)
Class #16 (October 27): Manipulation and Deception in AI Models
Class #17 (October 29): Manipulation and Deception in AI Models
Class #18 (Nov. 3): Data privacy
Class #19 (Nov. 5): Equity, Civil Rights, Human Rights
Class #20 (Nov. 10): Risk and AI Governance (EU Approach)
Class #21 (Nov. 12): Risk and AI Governance (EU Approach)
Class #22 (Nov. 17): US Approach (Geopolitical and National Security Issues)
Class #23 (Nov. 19): US Approach (Geopolitical and National Security Issues)
Class #24 (Nov. 24): China and AI Regulation
Class #25 (Dec. 1): China and AI Regulation
Class #26 (Dec. 3): AI Agents, and Looking Ahead
See you next week!
Nita, this syllabus captures how law is finally beginning to mirror the structure of the technology it seeks to regulate. The sequencing, from model training to accountability, reflects the lifecycle of AI itself.
I recently published a paper titled “Linguistic Homogenization in AI-Generated Content: Cultural Impacts and Implications for AI Safety and Control,” exploring how repetitive rhetorical patterns in LLM outputs influence public reasoning and discourse diversity. It seems increasingly relevant to the “bias and fairness” and “manipulation and deception” topics in your course. The legal frameworks you’re teaching could one day determine how we classify and mitigate these subtle linguistic risks, where persuasion becomes a form of governance itself.