Letters And Testimony


Generative AI and Copyright

letters and testimony

Generative AI and Copyright

September 11, 2023

Today, I signed a coalition letter submitted to members of the U.S. House of Representatives and U.S. Senate, expressing concern about calls for new copyright legislation that would jeopardize the benefits of AI and upend the core governing principles of our nation’s intellectual property regime. Click here to download a pdf of the letter.

Dear Members of the U.S. House of Representatives and U.S. Senate,

We are a broad coalition of public interest organizations, creators, academics, and others who share a common interest in ensuring that artificial intelligence meets its potential to enrich the American economy, empower creatives, accelerate the progress of science and useful arts, and expand humanity’s overall welfare. We write to express our concern about calls for new copyright legislation that would jeopardize these benefits and upend the core governing principles of our nation’s intellectual property regime. Our message is simple: existing copyright doctrine has evolved and adapted to accommodate many revolutionary technologies, and is well equipped to address the legitimate concerns of creators. Our courts are the proper forum to apply those doctrines to the myriad fact patterns that AI will present over the coming years and decades.

To be sure, like any transformative technology, AI will bring new risks and disruptions. But it is also important not to lose sight of AI’s tremendous benefits. Scientists have used AI to solve previously intractable mathematical and scientific problems. Doctors use AI for early cancer detection and improved patient care. Creators, like many of the undersigned, are already utilizing AI models to develop new works of fiction, new video games, and new software. And this is just the beginning. We believe AI has broad and enormous potential to advance the longstanding and fundamental purpose of our IP law: to encourage human ingenuity and creativity.

Unfortunately, the recent emergence of generative AI into the popular consciousness has brought with it calls for onerous new copyright restrictions. For instance, some are advocating for new laws that would require developers of AI systems to get permission from and negotiate with countless rightsholders to get access to the material they need to teach their models how to be useful in the modern world. These proposals would both significantly expand the scope of the traditional copyright monopoly and create overwhelming practical impediments to effective AI development, thus undermining the foundational purpose of our copyright law, which is, ultimately, to “promote the progress of Science and useful Arts.” U.S. Const. Art. 1, § 8, cl. 8. They would also undermine competition in the AI marketplace, by imposing significant financial and logistical burdens that new entrants may not be able to bear.

Existing copyright law achieves its purpose by giving creators important—but specific— rights to assure them that, if they write a new book or compose a new song, the law will protect their ability to earn money by selling copies of that work—incentivizing creators to produce more. But that bundle of rights has never included a monopoly over the basic building blocks of creativity: ideas, concepts, style, artistic technique, language, or grammar. Indeed, all creators stand on the shoulders of giants—new writers learn their craft by studying the works of earlier writers, new musicians study and iterate on the music of earlier musicians, and so on. A system that required follow-on creators to negotiate with and pay those they learned from would inhibit, rather than promote, the very artistic progress our IP laws seek to encourage.

That analysis should not vary merely because a computer is involved. AI models work by deriving abstract patterns and relationships from billions of pieces of training data, and using those abstract correlations to create wholly new content. This process of “machine learning” is similar in effect to human learning. AI systems learn how to use language. They learn facts about the world, ideas, and visual concepts. They are not designed to reproduce protected material from the data on which they are trained—and on the rare occasions that they do, copyright law provides the tools necessary for courts to enforce rightsholders’ legitimate protections.

Concerns about the impact of new technology on human creators and calls to impose IP-based restrictions on emerging technology are not new. Artists objected to the invention of photography, arguing that it would render the paintbrush obsolete. Orchestra conductors objected to the advent of recorded music, arguing that it would diminish the demand for live performances. Film studios objected to the development of home video technology on the grounds that it challenged their existing business model. But each of these technologies added much more than they displaced. Photography unleashed a new wave of artistic creation. Recorded music and home video unlocked a massive new source of revenue for musicians and filmmakers, and paved the way for today’s streaming economy.

We owe these value-driving innovations to the broad and flexible framework that Congress wisely created when fashioning our copyright regime. In essence, that framework ensures a fair reward to creators while also enabling technological innovation and follow-on creativity. That dynamic structure is the reason that the United States is not only the most successful creative economy in history, but is also the primary source of the technological innovation that has driven the global economy for over half a century. It is the reason why today’s AI leaders have chosen to build their innovative products in the United States, rather than elsewhere. Upsetting that balance through legislation that expands the scope of intellectual property protection would jeopardize our role as the global leader of AI development and hamper our ability to compete on the international stage. It would cede our current technological advantage to other nations, some of whom are not our friends.

To be clear, we do not discount the concerns raised by content owners and other stakeholders. But there are many ways to address them outside copyright law. For instance, existing right of publicity and trademark law can address the use of AI to create deepfakes or political disinformation, or to unfairly misappropriate artists’ voices or likenesses.

As Congress, the courts, creators, developers, and other stakeholders continue to discuss the impact of AI technology on our economy and our society, we look forward to continuing to work with you to understand this nascent technology and develop legislative solutions that protect both this nation’s thriving creative economy and its global leadership in this exciting and potentially transformative new area of science.


American Library Association

Association of Research Libraries Authors Alliance

Chamber of Progress

Creative Commons

Electronic Frontier Foundation Internet Archive

Public Knowledge

R Street Institute TechFreedom


Zach Graves (Executive Director, Foundation for American Innovation)

Jerome Hardaway (Executive Director, Vets Who Code; Chief Technology Officer, MyRuck AI)

Professor Jeremy Howard (Co-founder,; Digital Fellow, Stanford Digital Economy Lab; Hon. Professor, School of Information Technology and Electrical Engineering, University of Queensland)

John Luttig (Principal, Founders Fund)

Spence Purnell (Director of Technology Policy, Reason Foundation)

Professor Chris Callison-Burch (Associate Professor of Computer and Information Science, University of Pennsylvania)

Professor Michael Carroll (Professor of Law & Faculty Director, Program on Information Justice and Intellectual Property, American University Washington College of Law)

Professor Zachary L. Catanzaro (Assistant Professor of Law, St. Thomas University College of Law)

Professor Eric Goldman (Professor of Law, Co-Director, High Tech Law Institute, Santa Clara University School of Law)

Professor Mark Lemley (William H. Neukom Professor of Law, Director, Program in Law, Science & Technology, Stanford Law School)

Professor Matthew Sag (Professor of Law, Artificial Intelligence, Machine Learning, and Data Science, Emory University School of Law)

Professor Jason Schultz (Professor of Clinical Law, Director, NYU Technology Law & Policy Clinic, Co- Director, Engelberg Center on Innovation Law & Policy, NYU School of Law)

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