Publications

Publications of Matthew Sag, Jonas Robitscher Professor of Law in Artificial Intelligence, Machine Learning, and Data Science at Emory University School of Law. Google Scholar counts 3,295 citations to this work (H-index 27, as of May 2026), and these papers have been downloaded from SSRN more than 48,000 times. For the intellectual story connecting them, see the Research Agenda; a complete CV is here.

Books and casebooks

  • Copyright Law in the Age of AI (2025, revised 2026). A complete, free casebook on United States copyright law — 28 chapters, 177 extracted decisions, current to August 2026 — with AI integrated throughout rather than quarantined to a single chapter.
  • Extended Readings on Copyright (2019; updated annually through 2024). A 1,000-page open-access casebook distributed under a Creative Commons license and used in copyright courses in the United States and overseas; the predecessor to Copyright Law in the Age of AI.
  • Building Legal Literacies for Text Data Mining (Pressbooks 2021) (with Scott Althaus, David Bamman, Sara Benson, Brandon Butler, Beth Cate, Kyle K. Courtney, Sean Flynn, Maria Gould, Cody Hennesy, Eleanor Dickson Koehl, Thomas Padilla, Stacy Reardon, Rachael Samberg, Brianna L. Schofield, Megan Senseney, Timothy Vollmer, and Glen Worthey). The open handbook of the NEH-funded Building Legal Literacies for Text Data Mining Institute.

Articles and essays

2024–2026: Generative AI and copyright’s frontier

  1. Copyright’s Jagged Frontier, 76 Duke Law Journal (forthcoming 2026). (SSRN)
  2. The Illusory Normativity of Rights-Based AI Regulation, 21(2) Indian Journal of Law and Technology (2025) (with Yiyang Mei). (SSRN) (journal)
  3. The False Hope of Content Licensing at Internet Scale, ProMarket (Nov. 19, 2025). (ProMarket)
  4. The Paradox of Intellectual Property at the U.S. Supreme Court, 41 Berkeley Technology Law Journal 135 (2025) (with Tonja Jacobi). (SSRN)
  5. The Globalization of Copyright Exceptions for AI Training, 74 Emory Law Journal 1163 (2025) (with Peter K. Yu). A comparative account of how jurisdictions worldwide are building copyright exceptions for AI training. (SSRN)
  6. We are the AI Problem, 74 Emory Law Journal Online 1 (2024). (SSRN)
  7. Forward Looking Academic Impact Rankings for U.S. Law Schools, 51 Florida State University Law Review 762 (2024). (SSRN)
  8. Fairness and Fair Use in Generative AI, 92 Fordham Law Review 1887 (2024). A framework for assessing the fair use claims of generative AI developers. (Fordham) (SSRN)

2019–2023: Machine learning, the Supreme Court, and empirical copyright

  1. Copyright Safety for Generative AI, 61 Houston Law Review 295 (2023). One of the first frameworks for how model developers can reduce the risk of infringing outputs; introduced the “Snoopy problem.” (Houston L. Rev.) (SSRN)
  2. Supreme Court Interruptions and Interventions: The Changing Role of the Chief Justice, 103 Boston University Law Review 1741 (2023) (with Tonja Jacobi). (SSRN)
  3. SCOTUS in the Time of COVID: The Evolution of Justice Dynamics during Oral Arguments, Law & Policy 1 (2023) (with Eve M. Ringsmuth, Timothy R. Johnson & Tonja Jacobi). (journal)
  4. Discovering eBay’s Impact on Copyright Injunctions Through Empirical Evidence, 64 William & Mary Law Review 1447 (2023) (with Pamela Samuelson). (SSRN)
  5. Sean M. Flynn, Matthew Sag, et al. & Jorge L. Contreras, Legal Reform to Enhance Global Text and Data Mining Research, 378 Science 951 (2022). A call in one of the world’s leading scientific journals for legal reform to enable text and data mining research globally. (Science)
  6. Oral Argument in the Time of COVID: The Chief Plays Calvinball, 30 Southern California Interdisciplinary Law Journal 399 (2021) (with Tonja Jacobi, Timothy R. Johnson & Eve Ringsmuth). (SSRN)
  7. Implementing User Rights for Research in the Field of Artificial Intelligence: A Call for International Action, European Intellectual Property Review (2020) (with Sean Flynn, Christophe Geiger, João Quintais, Thomas Margoni, Lucie Guibault & Michael W. Carroll). (SSRN)
  8. 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 United States law for text data mining and machine learning after HathiTrust and Google Books. (SSRN)
  9. Taking Laughter Seriously at the Supreme Court, 72 Vanderbilt Law Review 1423 (2019) (with Tonja Jacobi). (SSRN)
  10. The New Oral Argument: Justices as Advocates, 94 Notre Dame Law Review 1161 (2019) (with Tonja Jacobi). (SSRN)
  11. Empirical Studies of Copyright Litigation, in Research Handbook on the Economics of Intellectual Property Law (Vol. II — Analytical Methods) (Edward Elgar 2019).

2015–2018: Copyright trolling and the transformation of enforcement

  1. Defense Against the Dark Arts of Copyright Trolling, 103 Iowa Law Review 571 (2018) (with Jake Haskell). A practical and doctrinal playbook for defendants in mass copyright litigation, cited by federal courts.
  2. Internet Safe Harbors and the Transformation of Copyright Law, 93 Notre Dame Law Review 499 (2017).
  3. IP Litigation in US District Courts: 1994 to 2014, 101 Iowa Law Review 1065 (2016).
  4. Promoting Innovation, 100 Iowa Law Review 2223 (2015) (with Spencer Weber Waller).
  5. Copyright Trolling, An Empirical Study, 100 Iowa Law Review 1105 (2015). The empirical study that documented the rise of mass “John Doe” copyright litigation; its findings and framing have been cited by federal courts confronting copyright trolls.

2011–2014: Mass digitization and the empirical turn

  1. League Structure & Stadium Rent Seeking — the Antitrust Role Reconsidered, 65 Florida Law Review 1 (2013) (with David Haddock and Tonja Jacobi).
  2. Digital Archives: Don’t Let Copyright Block Data Mining, 490 Nature 29 (2012) (with Matthew Jockers and Jason Schultz). The argument for data mining rights, made in Nature while the HathiTrust and Google Books cases were pending.
  3. Orphan Works as Grist for the Data Mill, 27 Berkeley Technology Law Journal 1503 (2012).
  4. An Information-Gathering Approach to Copyright Policy, 34 Cardozo Law Review 173 (2012) (with Peter DiCola).
  5. Predicting Fair Use, 73 Ohio State Law Journal 47 (2012). An empirical study of what actually predicts fair use outcomes in litigation.
  6. The Pre-History of Fair Use, 76 Brooklyn Law Review 1371 (2011).

2002–2010: Foundations

  1. The Google Book Settlement and the Fair Use Counterfactual, 55 New York Law School Law Review 19 (2010).
  2. Copyright and Copy-Reliant Technology, 103 Northwestern University Law Review 1607 (2009). The article that introduced the concept of non-expressive use — the framework now at the center of the copyright disputes over AI training.
  3. Taking the Measure of Ideology: Empirically Measuring Supreme Court Cases, 98 Georgetown Law Journal 1 (2009) (with Tonja Jacobi).
  4. Ideology and Exceptionalism in Intellectual Property — An Empirical Study, 97 California Law Review 801 (2009) (with Tonja Jacobi & Maxim Sytch).
  5. Patent Reform and Differential Impact, 8 Minnesota Journal of Law, Science & Technology 1 (2007) (with Kurt Rohde).
  6. Beyond Abstraction: The Law and Economics of Copyright Scope and Doctrinal Efficiency, 81 Tulane Law Review 187 (2006).
  7. Twelve Year-Olds, Grandmothers, and Other Good Targets for File Sharing Litigation, 4 Northwestern Journal of Technology & Intellectual Property 133 (2006).
  8. God in the Machine: A New Structural Analysis of the Fair Use Doctrine in Copyright Law, 11 Michigan Telecommunications & Technology Law Review 381 (2005).
  9. Source Code Versus Object Code: Patent Implications for the Open Source Community, 18 Santa Clara Computer & High Tech Law Journal 235 (2002) (with Daniel Lin).

Working papers and works in progress

  • Recodifying Fair Use, 73 Journal of the Copyright Society (forthcoming 2027).
  • What If? Hypotheticals and Doctrinal Exploration at Supreme Court Oral Argument, 78 Florida Law Review (forthcoming 2026) (with Tonja Jacobi).
  • A Student’s Guide to the Law and Policy of AI (2025), with companion papers on Fair Use and Generative AI and the Interests and Concerns Motivating AI Regulation. (SSRN)
  • AI Policies for Law Schools (2025). (SSRN)

Testimony, government submissions, and amicus briefs

  • Testimony before the U.S. Senate Judiciary Subcommittee on Intellectual Property, hearing on Artificial Intelligence and Copyright (July 12, 2023).
  • Brief of Copyright Law Professors as Amici Curiae in Thomson Reuters v. Ross Intelligence Inc., No. 25-2153 (3d Cir. 2025).
  • Copyright and the AI Action Plan, submission to the Office of Science and Technology Policy (March 2025). (read it here)
  • Comments and Reply Comments in response to the U.S. Copyright Office’s Notice of Inquiry on Artificial Intelligence and Copyright (2023) (with Pamela Samuelson and Christopher Jon Sprigman). (comments)
  • Briefs of Digital Humanities and Law Scholars in Authors Guild v. Google and Authors Guild v. HathiTrust (S.D.N.Y. and 2d Cir., 2012–2014) — the amicus briefs that put the non-expressive use framework before the courts in the mass digitization cases.
  • The Fair Use Doctrine in the United States — A Response to the Kernochan Report, submission to the Australian Law Reform Commission (2013) (with Gwen Hinze & Peter A. Jaszi).

This page lists scholarly publications. For blog posts and commentary, see the front page; for datasets, see data sets; for talks and media, see the CV.