The US Copyright Act has never been praised for its clarity or its intuitive simplicity—at a whopping 460 pages long, it is filled with hotly debated ambiguities and overly complex provisions. The copyright laws of most other jurisdictions aren’t much better.
Because of this complexity of copyright law, the implications of changes to copyright law and policy are not always clear to most authors. As we’ve said in the past, many of these issues seem arcane, and largely escape public attention. Yet entities with a vested interest in maximalist copyright—often at odds with the public interest—are certainly paying attention, and often claim to speak for all authors when they in fact represent only a small subset. As part of our efforts to advocate for a future where copyright law offers ample clarity, certainty, and real focus on values such as the advancement of knowledge and free expression, we would like to share with you two recent projects we undertook:
The 1202 Issue Brief and Amicus Brief in Doe v. Github
Authors Alliance has been closely monitoring the impact of Digital Millennium Copyright Act (DMCA) Section 1202. As we have explained in a previous post, Section 1202(b) creates liability for those who remove or alter copyright management information (CMI) or distribute works with removed CMI. This provision, originally intended to prevent wide-spread piracy, has been increasingly invoked in AI copyright lawsuits, raising significant concerns for lawful use of copyrighted materials beyond training AI. While on its face, penalties for removing CMI might seem somewhat reasonable, the scope of CMI (including a wide variety of information such as website terms of service, affiliate links, and other information) combined with the challenge of including it with all downstream distribution of incomplete copies (imagine if you had to replicate and distribute something like the Amazon Kindle terms of service every time you quoted text from an ebook) could be potentially very disruptive for many users.
In order to address the confusion regarding the (somewhat inaptly named) “identicality requirement” by the courts in the 9th Circuit, we have released an issue brief, as well undertaken to file an amicus brief in the Doe v. Github case now pending in the 9th Circuit.
Here are the key reasons why we care—and why you should care—about this seemingly obscure issue:
- The Precedential Nature of Doe v. Github: The upcoming 9th Circuit case, Doe v. GitHub, will address whether Section 1202(b) should only apply when copies made or distributed are identical (or nearly identical) to the original. Lower courts have upheld this identicality requirement to prevent overbroad applications of the law, and the appellate ruling may set a crucial precedent for AI and fair use.
- Potential Impact on Otherwise Legal Uses: It is not entirely certain if fair use is a defense to 1202(b) claims. If the identicality requirement is removed, Section 1202(b) could create liability for transformative fair uses, snippet reuse, text and data mining, and other lawful applications. This would introduce uncertainty for authors, researchers, and educators who rely on copyrighted materials in limited, legal ways. We advocate for maintaining the identicality requirement and clarifying that fair use applies as a defense to Section 1202 claims.
- Possibility of Frivolous Litigation: Section 1202(b) claims have surged in recent years, particularly in AI-related lawsuits. The statute’s vague language and broad applicability have raised fears that opportunistic litigants could use it to chill innovation, scholarship, and creative expression.
To find out more about what’s at stake, please take a look at our 1202(b) Issue Brief. You are also invited to share your stories with us, on how you have navigated this strange statute.
Reply to the UK Open Consultation on Copyright and AI
We have members in the UK, and many of our US-based members publish in the UK. We have been watching the development in UK copyright law closely, and have recently filed a comment to the UK Open Consultation on Copyright and AI. In our comment, we emphasized the importance of ensuring that copyright policy serves the public interest. Our response’s key points include:
- Competition Concerns: We alerted the policy-makers that their top objective must include preventing monopolies forming in the AI space. If licensing for AI training becomes the norm, we foresee power consolidating in a handful of tech companies and their unbridled monopoly permeating all aspects of our lives within a few decades—if not sooner.
- Fair Use as a Guiding Principle: We strongly believe that the use of works in the training and development of AI models constitutes fair use under US law. While this issue is currently being tested in courts, case law suggests that fair use will prevail, ensuring that AI training on copyrighted works remains permissible. The UK does not have an identical fair use statute, but has recognized that some of its functions—such as flexibility to permit new technological uses—are valuable. We argue that the wise approach is for the UK to update its laws to ensure its creative and tech sectors can meaningfully participate in the global arena. Our comment called for a broad AI and TDM exception allowing temporary copies of copyrighted works for AI training. We emphasized that when AI models extract uncopyrightable elements, such as facts and ideas, this should remain lawful and protected.
- Noncommercial Research Should Be Protected: We strongly advocated for the protection of noncommercial AI research, arguing that academic institutions and their researchers should not face legal barriers when using copyrighted works to train AI models for research purposes. Imposing additional licensing requirements would place undue burdens on academic institutions, which already pay significant fees to access research materials.