SPI 352/COS 352: Artificial Intelligence Law

Princeton Polaris Lab Princeton Polaris Lab
PRINCETON UNIVERSITY, FALL 2025
Location: Robertson Hall 016
Time: Thursdays 1:30pm-4:20pm
Instructor

Prof. Peter Henderson, J.D., Ph.D.

Assistant Professor in CS/SPIA

Teaching Assistant

Nimra Nadeem

MSE Candidate

Course Description

This course examines the implications of artificial intelligence (AI), particularly foundation models, for law and public policy. We will cover how AI affects and reshapes legal doctrine and policy, including: intellectual property law, administrative law, anti-discrimination law, and more. Also covered will be emerging regulatory policies and legislative efforts around AI, as well as the limits of proposed approaches. Emphasis will be placed juxtaposing the legal and policy considerations with technical design decisions, in an interdisciplinary and accessible way. This course is suitable for students of all backgrounds; no technical knowledge is assumed.

Course Expectations & Grading

Components

  • 📝 Reading Responses (25%): Due 5pm ET the day before class on Canvas. 1-2 pages, Times New Roman, 12 pt font, single-spaced. We’re mainly looking for your reflections: what you found interesting or confusing in the readings, points you disagree with, research ideas the readings sparked, etc. Consider readings two weeks ahead of a lecture to be locked in. Because this is a fast-moving field, I reserve the right to change readings >2 weeks ahead as new events materialize. Note: Some of the readings are lengthy in page count. It is okay to skip footnotes and skim portions that are repetitive. Important: You can skip two reading responses without penalty, and you can replace 2 additional reading responses with scribing - just let us know if you want to pick that option.
  • 👥 Participation (20%): 20% of the grade will come from participation. That means attending lectures and being engaged during classtime, especially during breakout discussions. Starting week 2, we will have a panel system (like the Socratic method used in law schools!). If you're on the panel for the day, I may call on you directly with questions like: “Can you walk us through what happened in Bartz v. Anthropic?”, "What arguments can be made for or against this position?", "What’s your take on the court’s reasoning here?". You don't need to do extra work beyond the assigned reading, but you should be prepared to discuss the readings more actively. If you don't want to be called on, you can opt out of the panel participation system by doing the scribing option below! Note: This course is not being taught at a law school, but I’m going to treat it like a law school class (almost). I will make a best effort to provide necessary background as needed, but I might miss things at times. Please feel free to ask questions on the canvas discussion board on anything that you may be unfamiliar with. If you’re unfamiliar with it, chances are that others are as well. Don't be shy about asking questions or expressing uncertainty!
  • ✍️ Scribing Option: In lieu of participation, you can choose to "scribe" class lectures, taking notes during the lecture and converting the notes into well-written prose in the style of a text-book chapter in LaTeX. This option is first-come, first serve based on a signup sheet starting week 2. (But if there are LLM hallucinations in the notes, this is null and void.) Scribe notes are due by Friday at 5:00 p.m. of the week following the class you signed up for.
  • đź“„ Final Paper/Project (55%):
    • Literature Review & Project Proposal - October 18th (10%)
    • First Draft - November 18th (15%)
    • Final Draft - Dean's Day (30%)

Course Schedule

Things are moving fast in this field. We're restructuring the latter parts of the syllabus to accommodate new topics. Please do not go more than 2 weeks ahead in readings as things may change.

DATE TOPIC LECTURE AGENDA
9/4 Preliminaries: What is AI?

What kinds of AI do you immediately think of when you think "AI regulation?" Do a search on the web, what is your preferred definition of AI, and why? Do you think we even need to define AI in regulatory efforts at all, why or why not? Getting a sense for class interests.

Required Readings:

No required reading for first day of class.

Lecture Notes: Optional Materials:
  • Matt O'Shaughnessy, One of the Biggest Problems in Regulating AI Is Agreeing on a Definition, Carnegie Endowment For Int'l Peace (Oct. 6, 2022) [link]
  • Andrej Karpathy, [1hr Talk] Intro to Large Language Models, YouTube (May 2023) [video]
  • Orin S. Kerr, How to Read a Legal Opinion: A Guide for New Law Students, 11 Green Bag 2d 51 (2007) [pdf]
9/11 Copyright

Should model training be a fair use? What if the model outputs exact pieces of the training data? How much verbatim regurgitation by models should be acceptable? Do you think the courts should resolve this or should Congress step in, why or why not? Should humans have authorship rights in AI-generated content purely from prompting?

Required Readings:
  • 17 U.S.C. § 107 (Fair Use) — statutory text [link]
  • Congressional Research Service, Generative Artificial Intelligence and Copyright Law (June 16, 2025) — skim all [pdf]
  • Kadrey v. Meta Platforms, Inc., Order Denying Plaintiffs' Motion for Partial Summary Judgment and Granting Meta's Cross-Motion, No. 3:23-cv-03417 (N.D. Cal. June 25, 2025) (Chhabria, J.) — Skim all; focus on pp. 25-39 (Factor Four market effects) [pdf]
  • Bartz v. Anthropic PBC, Order on Fair Use, No. 3:24-cv-05417 (N.D. Cal. June 23, 2025) (Alsup, J.) — Skim all, focus on the court’s fair use analysis [pdf]
  • A. Feder Cooper et al., Extracting memorized pieces of (copyrighted) books from open-weight language models (arXiv, July 10, 2025) — read Abstract + the “Harry Potter” case-study section [pdf]
  • Xiyin Tang, Intellectual Property Law as Labor Policy, 100 N.Y.U. L. Rev. 62 (2025) — Skim introduction only [pdf]
Lecture Notes: Optional Readings:
  • Benjamin L.W. Sobel, Artificial Intelligence's Fair Use Crisis, 41 Colum. J.L. & Arts 45 (2017)
  • Peter Henderson et al., Foundation Models and Fair Use, 24 J. Machine Learning Rsch. 1 (2023)
  • U.S. Copyright Off., Copyright Registration Guidance: Works Containing Material Generated by Artificial Intelligence, 88 Fed. Reg. 16190 (Mar. 16, 2023)
  • Katherine Lee et al., Talkin' 'Bout AI Generation: Copyright and the Generative-AI Supply Chain (The Short Version), in Proc. of the Symp. on Comput. Sci. & L. 48 (2024) [pdf]
  • Complaint, N.Y. Times Co. v. Microsoft Corp., No. 1:23-cv-11195 (S.D.N.Y. filed Dec. 27, 2023) [pdf] (skim)
  • Complaint, Concord Music Grp., Inc. v. Anthropic PBC, No. 3:23-cv-01092 (M.D. Tenn. filed Oct. 18, 2023) [pdf] (skim)
  • Carys J. Craig, The AI-Copyright Trap, 100 Chi.-Kent L. Rev. (forthcoming 2025) [link] (skim only pages 18-26)
9/18 Right of Publicity and Privacy

How do you think we should regulate use of likeness? What does it mean for a voice clone or character to be too close in likeness to a real person? What if multiple people have similar voices? Should restrictions on use of likeness expire ever? What about elected officials, should we be more or less restrictive about use of their likeness?

Required Readings:
  • Right of Publicity, Legal Info. Inst. [link]
  • Midler v. Ford Motor Co., 849 F.2d 460 (9th Cir. 1988) [link]
  • Colin Stutz, The Fake Drake AI Song Earned Millions of Streams – But Will Anyone Get Paid?, Billboard (May 25, 2023) [link]
  • Complaint, Vacker v. Eleven Labs, Inc., No. 1:24-cv-00987-UNA (D. Del. filed Aug. 29, 2024) [pdf]
  • Bobby Allyn, Scarlett Johansson says she is 'shocked, angered' over new ChatGPT voice, NPR (May 20, 2024) [link]
  • Biometric Information Privacy Act, 740 Ill. Comp. Stat. 14/1 et seq. [link]
Optional Readings:
  • Assemb. 1488, 221st Leg., 2024-2025 Sess. (N.J. 2024), [link]
  • Assemb. 1836 (CA 2024), [link]
  • S. 4569, 118th Cong. (2024) (TAKE IT DOWN Act), [link]
  • Jennifer King & Caroline Meinhardt, Rethinking Privacy in the AI Era: Policy Provocations for a Data-Centric World 1 (2024), [link]
  • MarĂ­a P. Angel and Ryan Calo, Distinguishing Privacy Law: A Critique of Privacy as Social Taxonomy, 124 Colum. L. Rev. 507 (2024), [link]
  • Alicia Solow-Niederman, Information Privacy and the Inference Economy, 117 NW. U. L. Rev. 357, 382–84 (2022) [link]
9/25 Tort Liability & Section 230

Should large language models be immune from liability under Section 230? What about recommendation systems? Where should we draw the line? What is considered reasonable care under a negligence standard in tort law?

📋 🚨 Warning: Readings in flux, but will be finalized 2 weeks before this class. Required Readings:
  • Ketan Ramakrishnan et al., U.S. Tort Liability for Large-Scale Artificial Intelligence Damages: A Primer for Developers and Policymakers, RAND Corp. (Aug. 21, 2024) [link]
  • Peter Henderson et al., Where's the Liability in Harmful AI Speech?, 3 J. Free Speech L. 589 (2023) [pdf] (only pages 620-626 after skimming 602-620)
  • Winter v. G.P. Putnam's Sons, 938 F.2d 1033 (9th Cir. 1991) [link]
  • Anderson v. TikTok, Inc., 2024 WL 3948248 (3d Cir. Aug. 27, 2024)
  • Eric Goldman, Bonkers Opinion Repeals Section 230 In the Third Circuit–Anderson v. TikTok, Tech. & Mktg. L. Blog (Aug. 29, 2024) [link]
10/2 Free Speech and First Amendment

As the conflicting readings suggest, there is significant grey area around the applicability of the First Amendment, what do you think the right position is? What makes you think this is the right position and how do you assess the "correctness" of your position? What are the consequences of taking one position of the other?

📋 🚨 Warning: Readings in flux, but will be finalized 2 weeks before this class. Required Readings:
  • NetChoice, LLC v. Bonta, No. 23-2969 (9th Cir. Aug. 16, 2024)
  • Eugene Volokh et al., Freedom of Speech and AI Output, 3 J. Free Speech L. 651 (2023)
  • Peter Salib, AI Outputs Are Not Protected Speech, 100 Wash. U. L. Rev. (forthcoming 2024) (skim)
Optional Readings:
  • Patrick Zurth, The German NetzDG as Role Model or Cautionary Tale? Implications for the Debate on Social Media Liability, 31 Fordham Intell. Prop. Media & Ent. L.J. 1084 (2020)
  • Toni M. Massaro & Helen Norton, Siri-ously? Free Speech Rights and Artificial Intelligence, 110 Nw. U. L. Rev. 1169 (2016) (skim)
10/9 National Security Threats & Uses, Export Controls, & The Executive's Power

What are the pros and cons of a distributed state-level approach to AI regulation versus an approach relying on executive powers? What about comparing a pre-clearance regime to a post-deployment monitoring regime? How should we balance expanding national security powers around AI against containing the risks of AI? How does the first amendment interact with executive powers?

📋 🚨 Warning: Readings in flux, but will be finalized 2 weeks before this class. Required Readings:
  • Exec. Order No. 14,110, Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence (2023) [link]
  • Exec. Order No. 14,117, Preventing Access to Americans' Bulk Sensitive Data and United States Government-Related Data by Countries of Concern [link]
  • Faiza Patel & Patrick C. Toomey, National Security Carve-Outs Undermine AI Regulations, Just Security (Dec. 21, 2023) [link]
  • Kat Duffy & Kyle Fendorf, In the Age of AI, Personal Data Security Is National Security, Council on Foreign Relations (Apr. 1, 2024) [link]
Optional Readings:
  • Christopher A. Mouton et al., The Operational Risks of AI in Large-Scale Biological Attacks Results of a Red-Team Study, RAND (Jan. 25, 2024) (skim) [link]
  • National Security Commission on Artificial Intelligence Report [link]
10/16 Fall Break
10/23 Antidiscrimination Law

What is your assessment of the complications of determining whether Facebook / Meta violated the Fair Housing Act? Do you agree with the resolution of the case? Do you think WorkDay should be liable for discrimination or should it be a problem only for direct employers? What if we go further upstream to OpenAI and other foundation model providers if they power WorkDay's service?

📋 🚨 Warning: Readings in flux, but will be finalized 2 weeks before this class. Required Readings:
  • Solon Barocas & Andrew D. Selbst, Big Data's Disparate Impact, 104 Calif. L. Rev. 671 (2016)
  • Complaint, United States v. Meta Platforms, Inc., No. 1:22-cv-05187 (S.D.N.Y. 2022) [pdf]
  • Settlement Agreement, United States v. Meta Platforms, Inc., No. 1:22-cv-05187 (S.D.N.Y. 2022) [pdf]
  • Mobley v. Workday, Inc., No. 3:23-cv-00770-RFL (N.D. Cal. July 12, 2024) [pdf]
  • U.S. Department of Justice Civil Rights Division, Algorithms, Artificial Intelligence, and Disability Discrimination in Hiring (2022) [link]
10/30 Labor

What tools can we leverage to constrain concentration of power under increased automation? What role should different areas of law play in this? Should we battle concentration of power at all? Do you think labor organizing will be effective for this? What about antitrust law?

📋 🚨 Warning: Readings in flux, but will be finalized 2 weeks before this class. Required Readings:
  • Cynthia Estlund, What Should We Do After Work? Automation and Employment Law, 128 Yale L.J. 254 (2018)
  • Lina M. Khan, Amazon's Antitrust Paradox, 126 Yale L.J. 710 (2016)
  • SAG-AFTRA and Replica Studios Introduce Groundbreaking AI Voice Agreement at CES [link]
11/6 Challenges for Regulators in the Administrative State

Do you think the administrative state remains a viable option after recent supreme court jurisprudence? Is regulation better off in the hands of the states, or the executive?

📋 🚨 Warning: Readings in flux, but will be finalized 2 weeks before this class. Required Readings:
  • Amy Howe, Supreme Court strikes down Chevron, curtailing power of federal agencies [link]
  • US Supreme Court's October 2023 Term: Administrative Law Trilogy – Holdings, Analyses, and Implications of Jarkesy, Loper Bright, and Corner Post, Cooley LLP (July 26, 2024) [link]
  • Meta Platforms v. Federal Trade Commission [pdf]
  • Kate Andrias, Amazon, SpaceX and Other Companies Are Arguing the Government Agency That Has Protected Labor Rights Since 1935 Is Actually Unconstitutional [link]
11/13 The Government Using AI: Good and Bad

Does it matter if a human is in the loop? If so, when and how can we make sure that humans are actually doing their job when they're in the loop? If not, why not? Are there government uses of AI that you're more or less comfortable with?

📋 🚨 Warning: Readings in flux, but will be finalized 2 weeks before this class. Required Readings:
  • Cary Coglianese & David Lehr, Regulating by Robot: Administrative Decision Making in the Machine-Learning Era, 105 Geo. L.J. 1147 (2017)
  • Ryan Calo & Danielle Keats Citron, The Automated Administrative State: A Crisis of Legitimacy, 70 Emory L.J. 797 (2021)
  • Shirin Sinnar, Courts Have Been Hiding Behind National Security for Too Long, Brennan Center For Justice (Aug. 11, 2021) [link]
  • Government by Algorithm Report, Admin. Conf. of the U.S. [pdf]
Optional Readings:
  • Peter Henderson & Mark Krass, Algorithmic Rulemaking vs. Algorithmic Guidance, 37 Harv. J.L. & Tech. 1 (2023).
  • Danielle Keats Citron, Technological Due Process, 85 Wash. U. L. Rev. 1249, 1251-58, 1305-1313 (2008).
11/20 The Legal System after AI: Statutory Interpreation and More

TBD

11/27 Thanksgiving Recess
12/4 Floating Topic (Based on Class Preferences)

TBD