I recently had a very insightful conversation with a group of professors who teach AI law or related tech law topics. Below, I’ll provide some resources related to our conversation. First, here’s our discussion:
A few quotes (edited slightly):
Margaret Hu: “What I tried to do was map out the field in five parts. The first part is very theoretical and conceptual. Part two is actual examples of regulatory frameworks and statutory frameworks. Part three is constitutional law and public law. Part four is private law. And part five is the future trajectory of AI law and policy.”
Margot Kaminski: “We tried to break the case book up into parts that would have these arcs where we’d have cases, we would have statutes, and all of that would be not necessarily AI specific but AI related and the end of the arc would turn to some AI specific regulatory frameworks or statutory frameworks either from the US or the EU or comparative (we have some sources from other countries as well in there). . . . The first part is on automated decision-making technology—so the use of automated systems or AI systems in consequential decisions in certain sectors. The second arc is on physical harms—about cyber physical systems including self-driving cars and medical devices. The third arc is on generative AI, and there we get into copyright first amendment synthetic content. The fourth is on data privacy. And the last one involves how we think overall about this project of regulating AI, which also gives us a perspective on regulating new technologies in general. Throughout all of this, we made sure we had tech primers so that at each section students could understand the technology we are discussing.”
Alicia Solow-Niederman: “I’m now teaching my third rendition of this course. I started teaching when I was working just from the table of contents that Paul had put together online. So I’ve gone through multiple renditions of me curating my own materials and then being a beta adopter last year of the Kaminski/Ohm/Selbst casebook and adapting it. It’s so fascinating because there’s just no one way to teach this topic, even when you’re ostensibly using the same materials. . . . My goal is to have what I think of as a three-legged stool. One leg of the stool is the technology—providing students with a basic technical primer. I think of the other two legs as what is the law currently and then what could the law be and what should the law be.”
Ryan Calo: “I’m really focused on technology as the relevant discursive unit. And what I would say is even if we don’t have a law of the horse, that doesn’t mean we don’t want animal law. So I just don’t know whether or not AI is one of the things that raises novel different questions than other technologies.”
Daniel Solove: “The technologies have been around for decades and decades now. They’ve evolved in certain ways as we’ve seen the explosion of data and vast increase in computing power. They’re old and new, and we we have to pay attention to both these qualities to it. It is new in that it changes scale, it changes power, it remixes some existing problems in ways that are creating new issues and new challenges for old laws. But we should understand that some of these things were around for a very long time and these issues were discussed with different terminology.”
Ryan Calo: “Some of the laws that exist are purposely open-ended. The Federal Trade Commission just today announced a big investigation of Anthropic and Open AI. And what does the FTC police? It polices against unfair and deceptive practices. And you hear that heavily moral, value-laden language. With consumer protection law at the turn of the century, people thought it was just immoral that big companies were getting away with stuff and that there ought to be a way to rein them in. Public interest and morality were at the center. That’s why the FTC Act uses words like unfair or deceptive.”
CASEBOOKS
MARGOT E. KAMINSKI, PAUL OHM, AND ANDREW D. SELBST, ARTIFICIAL INTELLIGENCE LAW (West Academic, 1st ed. 2027)
Their book manuscript has been in use for several years, but it will finally be out in print for next year. There’s no cover image yet, but I used AI to generate one in the West Academic style. Then I created my own based on the actual style. I think that the human wins!
MARGARET HU, AI LAW AND POLICY (Aspen 1st ed. 2026)
MARGARET HU, INTRODUCTION TO AI LAW AND POLICY: PRIMARY LEGAL AND POLICY SOURCES ON AI GOVERNANCE (Aspen 1st ed. 2026)
MARGARET HU, AI LAW AND POLICY: SELECTED STATUTES, REGULATIONS, AND OTHER MATERIALS (Aspen, 2026)
BOOKS AND ARTICLES
RYAN CALO, LAW AND TECHNOLOGY: A METHODOLOGICAL APPROACH (2025)
Daniel J. Solove, Artificial Intelligence and Privacy, 77 Fla. L. Rev. 1 (2025)
Alicia Solow-Niederman, AI and Doctrinal Collapse, 78 Stan. L. Rev. 955 (2026)
Alicia Solow-Niederman, Clickwrap Accountability, Fordham L. Rev. (forthcoming 2026)
OTHER RESOURCES
Luiza Jarovsky’s List of Recommended AI Books
A superb list of about 40 books about AI. I’m delighted that my book, ON PRIVACY AND TECHNOLOGY (2025) is included.
Nita Farahany’s AI Law and Policy Course on Substack
Follow along with Professor Nita Farahany’s AI law and policy course as she sums up each class in a Substack post. Every post is insightful!
Daniel J. Solove, EU AI Act Whiteboard
A visual summary of EU AI Act in one page; a free download for personal use.
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Daniel J. Solove is the Bernard Professor of Intellectual Property and Technology Law at the George Washington University Law School. He is the founder of TeachPrivacy, a company that provides workforce privacy, cybersecurity security, and AI training to companies and organizations around the world. He is the author of 10+ books and 100+ articles.
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