The connection between law and artificial intelligence is becoming increasingly important as AI systems shape various aspects of our lives, including healthcare, finance, government, and online platforms.
These technologies raise key questions for the legal system, such as who is responsible for decisions made by machines? How do we protect privacy when massive amounts of people’s data are being processed? And how do we ensure that algorithms act in ways that are fair and transparent?

At the Center, Prof. Eldar Haber recently published the book “The Rise of the AI Author”, a book that explores how artificial intelligence is changing the idea of authorship and copyright, and also challenges longstanding assumptions about creativity and ownership.

An article that was published at the center was “Algorithms, AI and Mergers” by Prof. Michal S. Gal. The article shows how companies can use algorithms to coordinate business behavior, which challenges traditional antitrust rules and suggests ways that the current law should adapt.

Another article written in the center is “AI and the Future of Disputing: Naming, Blaming, Claiming, and Preventing,” by Prof. Orna Rabinovich-Einy, which examines how AI can not only help resolve conflicts online but even prevent them before they escalate.

Prof. Tal Zarsky, in his article, “Fair-Enough AI,” explains why current rules about fairness in AI are too vague and argues for clearer and more practical standards.

Finally, Prof. Daniel Benoliel and Dr. Dalit Ken-Dror Feldman propose in “Beyond Explainability: The Case for AI Validation” that we need to move on from explaining how AI works to validating its reliability, especially in high-risk uses.

Sources:

Haber, Eldar, The Rise of the AI Author. Independently published, 2025.

Gal, Michal S., and Rubinfeld, Daniel L., Algorithms, AI, and Mergers. 2023. Antitrust Law Journal, NYU Law and Economics Research Paper No. 23-36.

Katsh, Ethan; Schwartz-Maor, Talia; Rabinovich-Einy, Orna. “AI and the Future of Disputing: Naming, Blaming, Claiming, and Preventing”. In: Conflict Resolution Quarterly. 2025; Vol. 43, No. 1. pp. 79-89.

Yakowitz Bambauer, Jane R., and Zarsky, Tal, Fair-Enough AI. 2024. 27 Yale J.L. & Tech. 1-52, University of Florida Levin College of Law Research Paper No. 25-12.

Ken-Dror Feldman, Dalit & Benoliel, Daniel, Beyond Explainability: The Case for AI Validation. 2025.