Literature Review

Keeping up with the academic literature on copyright, law & AI, or the intersection of copyright and AI can be hard. Each page offers a short guide to one article: what it argues, why it matters, and suggestions for further reading. The guides cover my own papers; the “further reading” on each page points to work by other scholars. Within each area the guides are listed newest first.

Copyright and AI

• Matthew Sag, Copyright’s Jagged Frontier, 76 Duke Law Journal (forthcoming 2026)
  Why the boundary between lawful and infringing generative-AI outputs is likely to be jagged, and how “copyright safety” filtering points toward a licensing market.
• Matthew Sag & Peter K. Yu, The Globalization of Copyright Exceptions for AI Training, 74 Emory Law Journal 1163 (2025)
  How copyright systems worldwide are converging toward permitting text and data mining and AI training.
• Matthew Sag, The False Hope of Content Licensing at Internet Scale, ProMarket (2025)
  Why licensing training data at internet scale cannot work as a general fix, and what that means for the market.
• Matthew Sag & Yiyang Mei, The Illusory Normativity of Rights-Based AI Regulation, 21(2) Indian Journal of Law and Technology (2025)
  A critique of rights-based approaches to AI regulation and the assumptions they conceal.
• Matthew Sag, Fairness and Fair Use in Generative AI, 92 Fordham Law Review 1887 (2024)
  A principled framework for when generative-AI training is fair use, grounded in copyright’s architecture rather than policy balancing.
• Tonja Jacobi & Matthew Sag, We are the AI Problem, 74 Emory Law Journal Online 1 (2024)
  Why the jarring outputs of AI image generators are a mirror of societal inequalities rather than mere technical failures.
• Matthew Sag, Copyright Safety for Generative AI, 61 Houston Law Review 295 (2023)
  One of the first frameworks for how AI developers can reduce infringing outputs, introducing the “Snoopy problem.”

Text and data mining, mass digitization, and the internet

• Matthew Sag, The New Legal Landscape for Text Mining and Machine Learning, 66 Journal of the Copyright Society of the U.S.A. 291 (2019)
  The doctrinal map of U.S. law for text mining and machine learning after HathiTrust and Google Books.
• Matthew Sag, Internet Safe Harbors and the Transformation of Copyright Law, 93 Notre Dame Law Review 499 (2017)
  How the DMCA safe harbors quietly transformed the substance of copyright law.
• Matthew L. Jockers, Matthew Sag & Jason Schultz, Digital Archives: Don’t Let Copyright Block Data Mining, 490 Nature 29 (2012)
  The case for data-mining rights, made in Nature while the HathiTrust and Google Books cases were pending.
• Matthew Sag, Orphan Works as Grist for the Data Mill, 27 Berkeley Technology Law Journal 1503 (2012)
  Why mass digitization for non-expressive analysis need not raise an orphan-works problem.
• Matthew Sag, The Google Book Settlement and the Fair Use Counterfactual, 55 New York Law School Law Review 19 (2010)
  Measuring the proposed Google Books settlement against what fair use litigation would likely have produced.
• Matthew Sag, Copyright and Copy-Reliant Technology, 103 Northwestern University Law Review 1607 (2009)
  The article that originated the concept of non-expressive use.

Fair use

• Matthew Sag, Predicting Fair Use, 73 Ohio State Law Journal 47 (2012)
  Empirical evidence that fair use is more predictable than its critics claim, with transformative use at the center.
• Matthew Sag, The Pre-History of Fair Use, 76 Brooklyn Law Review 1371 (2011)
  Fair use traced to eighteenth-century English abridgment cases, long before Folsom v. Marsh.
• Matthew Sag, God in the Machine: A New Structural Analysis of the Fair Use Doctrine in Copyright Law, 11 Michigan Telecommunications & Technology Law Review 381 (2005)
  A structural account of the fair use doctrine and the work it does within copyright.

Empirical studies of copyright and copyright policy

• Matthew Sag & Pamela Samuelson, Discovering eBay’s Impact on Copyright Injunctions Through Empirical Evidence, 64 William & Mary Law Review 1447 (2023)
  Empirical evidence of how eBay v. MercExchange changed the availability of copyright injunctions.
• Peter DiCola & Matthew Sag, An Information-Gathering Approach to Copyright Policy, 34 Cardozo Law Review 173 (2012)
  Choosing copyright institutions by their ability to gather information about the impact of new technology.

The Supreme Court

• Tonja Jacobi & Matthew Sag, The Paradox of Intellectual Property at the U.S. Supreme Court, 41 Berkeley Technology Law Journal 135 (2025)
  How intellectual property became depoliticized at the Supreme Court.
• Tonja Jacobi & Matthew Sag, The New Oral Argument: Justices as Advocates, 94 Notre Dame Law Review 1161 (2019)
  Evidence that the Justices increasingly use oral argument to advocate to one another rather than to question counsel.
• Tonja Jacobi & Matthew Sag, Taking Laughter Seriously at the Supreme Court, 72 Vanderbilt Law Review 1423 (2019)
  What decades of courtroom laughter reveal about power and advocacy at oral argument.
• Matthew Sag, Tonja Jacobi & Maxim Sytch, Ideology and Exceptionalism in Intellectual Property, 97 California Law Review 801 (2009)
  Empirical evidence that judicial ideology predicts IP outcomes at the Supreme Court, though less strongly than in hot-button cases.

And one about sports stadiums

• David Haddock, Tonja Jacobi & Matthew Sag, League Structure & Stadium Rent Seeking — the Antitrust Role Reconsidered, 65 Florida Law Review 1 (2013)
  Why the structure of American sports leagues enables the stadium rent-seeking that English clubs cannot manage.