uvalawai

Schedule

Week 1 (29 August 2025)

Pre-Course Survey

cs4501 students only: Submit this pre-course survey before 5pm on Thursday, 28 August:
cs4501: Pre-Course Survey (Google Form)

Readings: (to be read before class)

Frank H. Easterbrook, Cyberspace and the Law of the Horse, 1996 University of Chicago Legal Forum 207 (1996). [PDF]
Ted Chiang, ChatGPT is a Blurry JPEG of the Web, The New Yorker, 9 February 2023. [PDF] [Original Site]

Week 2

Readings: (to be read and thought about before classs on Friday 5 September)

Mark Riedl, The Intuition Behind How Large Language Models Work, Part I, Medium (Aug. 6, 2025).
Mark Riedl, The Intuition Behind How Large Language Models Work, Part II, Medium (Aug. 13, 2025)
William A. Ryan, et al., Practical Lessons from the Attorney AI Missteps in Mata v. Avianca, Association of Corporate Counsel (Aug. 8, 2023).
Introduction to Law and Legal Systems, Chapter 1 from Don Mayer et al., Introduction to the Law of Property, Estate Planning and Insurance (2012)

The Law students are also reading the first three readings, but not the Introduction to Law and Legal Systems chapter, which covers things they are expected to already know well from having at least a year of Law school. Please think about any questions you have from that and ask them in class (or email us before class) on Friday.

Homework

Submit the Homework 1: Using LLMs assignment in canvas by 9pm on Wednesday: https://canvas.its.virginia.edu/courses/147155/assignments/757555
If you joined the class late and missed the message about the pre-course survey, please make sure to submit this soon: https://forms.gle/ApXvZV5LorAX2SD46

Link to notebooks from class:

Note to run these yourself, you will need to get a token from https://huggingface.co/.

Week 3

Readings:

Solon Barocas, Moritz Hardt & Arvind Narayanan, Chapter 3: Classification from Fairness and Machine Learning (2023). Chapter link or PDF
Solon Barocas & Andrew D. Selbst, Big Data’s Disparate Impact, 104 California Law Review 671 (2016), https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2477899. Direct PDF link

Homework

Submit Homework 2: Document Bot in canvas before 9pm on Wednesday, 10 September. Note that this requires reading the Barocas & Selbst paper first.

Week 4

Project 1: Notebook Link

Readings:

Solon Barocas, Moritz Hardt & Arvind Narayanan, Chapter 5: Causality from Fairness and Machine Learning (2023). Chapter link or PDF
Nripsuta Saxena and Karen Huang and Evan DeFilippis and Goran Radanovic and David Parkes and Yang Liu. How Do Fairness Definitions Fare? Examining Public Attitudes Towards Algorithmic Definitions of Fairness. AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society (AIES), 2019. Conference Link: PDF.
Thomas B. Nachbar, Algorithmic Fairness, Algorithmic Discrimination. 48 Florida State University Law Review 509 (2021).

There is no assignment to submit this week, but we are expecting teams to get to the part of the Project 1 notebook marked as “Target for Week 1”. Your completed Project 1 notebook will be due on Wednesday, 24 September.

Week 5

Project 1: Project 1 is due on Wednesday (Sept 24) at 9pm. Each team should submit their Project 1 using the Group Project 1 assignment in Canvas. Only one team member submits your PDF for the full team.

Slides: The slides for today’s class (and all previous classes) are in the “Files/Class Slides” directory in Canvas.

Readings:

P. Jonathan Phillips, et al., Four Principles of Explainable Artificial Intelligence, NIST Interagency/Internal Report (NISTIR) 8312 (2021): https://doi.org/10.6028/NIST.IR.8312
Christoph Molnars, Interpretable Machine Learning: A Guide for Making Black Box Models Explainable, Chapter 17: Shapley Values. https://christophm.github.io/interpretable-ml-book/shapley.html (Law students can skip the “Shapley value theory” section, but we encourage CS students to read it)
Aidan Cooper, Explaining Machine Learning Models: A Non-Technical Guide to Interpreting SHAP Analyses: https://www.aidancooper.co.uk/a-non-technical-guide-to-interpreting-shap-analyses/

Week 6: Copyright

Project 2 Notebook Project 2 is due Wednesday, 9:00pm.

Readings:

A. Feder Cooper, Aaron Gokaslan, Ahmed Ahmed, Amy B. Cyphert, Christopher De Sa, Mark A. Lemley, Daniel E. Ho, Percy Liang. Extracting memorized pieces of (copyrighted) books from open-weight language models. https://arxiv.org/abs/2505.12546 (Don’t be scared by the 171 pages! The part to read is only the first 17 pages, the rest are appendices.)
Regina Sam Penti, Matthew J. Rizzolo & Yam Schaal. Anthropic’s Landmark Copyright Settlement: Implications for AI Developers and Enterprise Users, Ropes & Gray (Sept. 8, 2025). https://www.ropesgray.com/en/insights/alerts/2025/09/anthropics-landmark-copyright-settlement-implications-for-ai-developers-and-enterprise-users
U.S. Copyright Office. Copyright and Artificial Intelligence Part 3: Generative AI Training (prepublication version May 2025). https://www.copyright.gov/ai/Copyright-and-Artificial-Intelligence-Part-3-Generative-AI-Training-Report-Pre-Publication-Version.pdf You are only expected to read pages 1-31, on the basic technology (which will be a refresher) and on infringement. We will talk about fair use, but we will be focusing on the infringement inquiry.
John M. Griem, Jr. and Judith Wallace. Managing the Risk of Using AI-Generated Content in a World of Copyright Uncertainty: Are AI Content Generators and AI Generated Expressions “Derivatives” of Copyrighted Works?. Carter Ledyard (Aug, 28, 2023). https://www.clm.com/managing-the-risk-of-using-ai-generated-content-in-a-world-of-copyright-uncertainly-are-ai-content-generators-and-ai-generated-expressions-derivatives-of-copyrighted-works/

Week 7: Anti-Trust

Project 3 is due Wednesday, October 15 at 9:00pm (not this week, but next week includes “Fall Break”). The notebook for Project 3 is here: https://uvalawai.github.io/project3 (you should be working in your own team’s copy).

In class 7, we will discuss the relationship between antitrust and AI and ML.

The readings (all located in the Files portion of the Canvas site) are:

Renato Nazzini & James Henderson, Overcoming the Current Knowledge Gap of Algorithmic “Collusion” and the Role of Computational Antitrust, Stanford Computational Antitrust, 2024. [PDF]
Amended Complaint, U.S. et al. v. RealPage [PDF]. (Just review the Complaint to get a sense of the case - we will go over what you need to know in class. Be sure to take a good look at the Introduction and the first four Claims in Section VIII.)
Proposed Final Judgment, U.S. et al. v. RealPage [PDF]. (Again, just get an overall sense of what is happening with the settlement. Make sure to look at Sections IV, VII, and VIII.)

(The original sources and other materials from the case against RealPage are available at https://www.justice.gov/atr/case/us-and-plaintiff-states-v-realpage-inc.)

Week 8: Regulation

Project 3 is due Wednesday, October 15 at 9:00pm. The starting notebook for Project 3 is here: https://uvalawai.github.io/project3.

Final Project Topic Discussion: Contribute to the Final Project Topic Discussion before Thursday, October 16 at 8:00 PM.

Readings:

Artificial Intelligence Legislation Tracker, Brennan Center (Dec. 30, 2024): https://www.brennancenter.org/our-work/research-reports/artificial-intelligence-legislation-tracker (skim)

EU Made Simple, The EU’s AI Act Explained, Youtube Video (Sept. 21, 2024): https://www.youtube.com/watch?v=s_rxOnCt3HQ

Sarah Schechner and Stacy Meichtry, Vance Warns U.S. allies to Keep AI Regulation Light, Wall Street Journal, 11 February 2025. (available on course Canvas site) https://www.wsj.com/tech/ai/vance-warns-u-s-allies-to-keep-ai-regulation-light-aa33c008?st=YXwaw7&reflink=desktopwebshare_permalink
California Transparency in Frontier Artificial Intelligence Act (TFAIA), SB 53: https://leginfo.legislature.ca.gov/faces/billTextClient.xhtml?bill_id=202520260SB53

Week 9: Privacy

Joel Reardon, Serge Egelman, Kenneth A. Bamberger, and Larel E. McGrane. Anonymity, Consent, and Other Noble Lies: An Empirical Study of the Data Economy. To appear in Yale Journal of Law & Technology, 2025. [Canvas Link]

Serge Egelman will be our visitor in class on October 24.