Some of you may recall that Authors Alliance published our long-awaited guide, Writing About Real People, earlier this year. One of the major topics in the guide is the right of publicity—a right to control use of one’s own identity, particularly in the context of commercial advertising. These issues have been in the news a lot lately as generative AI poses new questions about the scope and application of the right of publicity. 

Sound-alikes and the Right of Publicity

One important right of publicity question in the genAI era concerns the increasing prevalence of “sound-alikes” created using generative AI systems. The issue of AI-generated voices that mimicked real people came to the public’s attention with the apparently convincing “Heart on My Sleeve” song, imitating Drake and the Weeknd, and tools that facilitate creating songs imitating popular singers have increased in number and availability. 

AI-generated soundalikes are a particularly interesting use of this technology when it comes to the right of publicity because one of the seminal right of publicity cases, taught in law schools and mentioned in primers on the topic, concerns a sound-alike from the analog world. In 1986, the Ford Motor Company hired an advertising agency to create a TV commercial. The agency obtained permission to use “Do You Wanna Dance,” a song Bette Midler had famously covered, in its commercial. But when the ad agency approached Midler about actually singing the song for the commercial, she refused. The agency then hired a former backup singer of Midler’s to record the song, apparently asking the singer to imitate Midler’s voice in the recording. A federal court found that this violated Midler’s right of publicity under California law, even though her voice was not actually used. Extending this holding to AI-generated voices seems logical and straightforward—it is not about the precise technology used to create or record the voice, but about the end result the technology is used to achieve. 

Right of Publicity Legislation

The right of publicity is a matter of state law. In some states, like California and New York, the right of publicity is established via statute, and in others, it’s a matter of common law (or judge-made law). In recent months, state legislatures have proposed new laws that would codify or expand the right of publicity. Similarly, many have called for the establishment of a federal right of publicity, specifically in the context of harms caused by the rise of generative AI. One driving force behind calls for the establishment of a federal right of publicity is the patchwork nature of state right of publicity laws: in some states, the right of publicity extends only to someone’s name, image, likeness, voice, and signature, but in others, it’s much broader. While AI-generated content and the ways in which it is being used certainly pose new challenges for courts considering right of publicity violations, we are skeptical that new legislation is the best solution. 

In late January, the No Artificial Intelligence Fake Replicas and Unauthorized Duplications Act of 2024 (or “No AI FRAUD Act”) was introduced in the House of Representatives. The No AI FRAUD Act would create a property-like right in one’s voice and likeness, which is transferable to other parties. It targets voice “cloning services” and mentions the “Heart on My Sleeve” controversy specifically. But civil societies and advocates for free expression have raised alarm about the ways in which the bill would make it easier for creators to actually lose control over their own personality rights while also impinging on others’ First Amendment rights due to its overbreadth and the property-like nature of the right it creates. While the No AI FRAUD Act contains language stating that the First Amendment is a defense to liability, it’s unclear how effective this would be in practice (and as we explain in the Writing About Real People Guide, the First Amendment is always a limitation on laws affecting freedom of expression). 

The Right of Publicity and AI-Generated Content

In the past, the right of publicity has been described as “name, image, and likeness” rights. What is interesting about AI-generated content and the right of publicity is that a person’s likeness can be used in a more complete way than ever before. In some cases, both their appearance and voice are imitated, associated with their name, and combined in a way that makes the imitation more convincing. 

What is different about this iteration of right of publicity questions is the actors behind the production of the soundalikes and imitations, and, to a lesser extent, the harms that might flow from these uses. A recent use of a different celebrity’s likeness in connection with an advertisement is instructive on this point. Earlier this year, advertisements emerged on various platforms featuring an AI-generated Taylor Swift participating in a Le Creuset cookware giveaway. These ads contained two separate layers of deceptiveness: most obviously, that Swift was AI-generated and did not personally appear in the ad, but more bafflingly, that they were not Le Creuset ads at all. The ads were part of a scam whereby users might pay for cookware they would never receive, or enter credit card details which could then be stolen or otherwise used for improper purposes. Compared to more traditional conceptions of advertising, the unfair advantages and harms caused by the use of Swift’s voice and likeness are much more difficult to trace. Taylor Swift’s likeness and voice were appropriated by scammers to trick the public into thinking they were interacting with Le Creuset advertising. 

It may be that the right of publicity as we know it (and as we discuss it in the Writing About Real People Guide) is not well-equipped to deal with these kinds of situations. But it seems to us that codifying the right of publicity in federal law is not the best approach. Just as Bette Midler had a viable claim under California’s right of publicity statute back in 1992, Taylor Swift would likely have a viable claim against Le Creuset if her likeness had been used by that company in connection with commercial advertising. The problem is not the “patchwork of state laws,” but that this kind of doubly-deceptive advertising is not commercial advertising at all. On a practical level, it’s unclear what party could even be sued by this kind of use. Certainly not Le Creuset. And it seems to us unfair to say that the creator of the AI technology sued should be left holding the bag, just because someone used it for fraudulent purposes. The real fraudsters—anonymous but likely not impossible to track down—are the ones who can and should be pursued under existing fraud laws. 

Authors Alliance has said elsewhere that reforms to copyright law cannot be the solution to any and all harms caused by generative AI. The same goes for the intellectual property-like right of publicity. Sensible regulation of platforms, stronger consumer protection laws, and better means of detecting and exposing AI-generated content are possible solutions to the problems that the use of AI-generated celebrity likenesses have brought about. To instead expand intellectual property rights under a federal right of publicity statute risks infringing on our First Amendment freedoms of speech and expression.

Last month, Authors Alliance submitted detailed comments in response to the Copyright Office’s Notice of Proposed Rulemaking in support of our petition to expand the existing Digital Millennium Copyright Act (DMCA) exemptions that enable text and data mining (TDM) as part of this year’s §1201 rulemaking cycle. 

To recap: our expansion petitions ask the Copyright Office to modify the existing TDM exemption so that researchers who assemble corpora of ebooks or films on which to conduct text and data mining are able to share that corpus with other academic researchers, where this second group of researchers qualifies under the exemption. Under the current exemption, academic researchers are only able to share their corpora with other qualified researchers for purposes of “collaboration and verification.” This simple change would eliminate the need for duplicative efforts to remove digital locks from ebooks and films, a time and resource-intensive process, broadening the group of academic researchers who are able to use the exemption. 

Our comment argues that the existing TDM exemption has begun to enable valuable digital humanities research and teaching, but that the proposed expansion would go much further towards enabling this research and helping TDM researchers reach their goals. The comment is accompanied by 13 letters of support from researchers, educators, and funding organizations, highlighting the research that has been done in reliance on the exemption, and explaining why this expansion is necessary. Our thanks go out to our stellar clinical team at UC Berkeley’s Samuelson Law, Technology & Public Policy Clinic—law students Mathew Cha and Zhudi Huang, and clinical supervisor Jennifer Urban—for writing and submitting this comment on our behalf. We are also grateful to our co-petitioners, the Library Copyright Alliance and American Association of University Professors, for their support on this comment. 

Ambiguity in “Collaboration”

One reason the expansion is necessary is the uncertainty over what constitutes “collaboration” under the existing exemption. Researchers have open questions about what level of individual contribution to a project would make researchers “collaborators” under the exemption. As our comment explains, collaboration can come in a number of different forms, from “formal collaborations under the auspice of a grant, [to] ad hoc collaborations that result from two teams discovering that they are working on similar material to the same ends, or even discussions at conferences between members of a loose network of scholars working on the same broad set of interests.” But it is not clear which of these activities is “collaboration” for the purposes of the exemption. And this uncertainty has had a chilling effect on the socially valuable research made possible by the exemption. 

Costly Corpora Creation 

Our comment also highlights the vast costs that go into creating a usable corpus for TDM research. Institutions whose researchers are conducting TDM research pursuant to the exemption must lawfully own the works in question, or license them through a license that is not time-limited. But these costs pale in comparison to the required computing resources—a cost which is compounded by the exemption’s strict security requirements—and human labor involved in bypassing technical protection measures and assembling a corpus. Moreover, it’s important to recognize that there is simply not a tremendous amount of grant funding or even institutional support available to TDM researchers. 

Because corpora are so costly to assemble and create, we believe it to be reasonable to permit researchers to share their corpora with researchers at other institutions who want to conduct independent TDM research on these corpora. As the exemption currently stands, researchers interested in pre-existing corpora must duplicate the efforts of the previous researchers, incurring massive costs along the way. We’ve already seen indications that these costs can lead researchers to avoid certain research questions and areas of study altogether. As our comment explains, this “duplicative circumvention” can be avoided by changing the language of the exemption to permit corpora sharing between qualified researchers at separate institutions. 

Equity Issues

Worse still, not all institutions are able to bear these expenses. Our comment explains how the current exemption’s prohibition on sharing beyond collaboration and verification—and consequent duplication of prior labor—-”create[s] barriers that can prevent smaller and less-well-resourced institutions from conducting TDM research at all.” This creates inequity in what type of institutions can support TDM projects, and what types of researchers can conduct them. The unfortunate result has been that large institutions that have “the resources to compensate and maintain technical staff and infrastructure” are able to support TDM research under the exemption, while smaller institutions are not. 

Values of Corpora Sharing

Our comment explains how allowing limited sharing of corpora under the exemption would go a long way towards lowering barriers to entry for TDM research and ameliorating the equity issues described above. Since digital humanities is already an under-resourced field, the effects of enabling researchers to share their corpora with other academic researchers could be quite profound. 

Researchers who wrote letters in support of the petition described a multitude of exciting projects, and have built “a rich set of corpora to study, such as a collection of fiction written by African American writers, a collection of books banned in the United States, and a curated corpus of movies and television with an ‘emphasis on racial, ethnic, sexual, and gender diversity.’” Many of those who wrote letters in support of our petition recounted requests they’ve gotten from other researchers to use their corpora, and who were frustrated that the exemption’s prohibition on non-collaborative sharing and their limited capacity for collaboration prevented them from sharing these corpora. 

Allowing new researchers with new research questions to study these corpora could reveal new insights about these bodies of work. As we explain, “in the same way a single literary work or motion picture can evince multiple meanings based on the lens of analysis used, when different researchers study one corpus, they are able to pose different research questions and apply different methodologies, ultimately revealing new and original findings . . . . Enabling broader sharing and thus, increasing the number of researchers that can study a corpus, will allow a body of works to be better understood beyond the initial ‘limited set of research questions.’”

Fair Use

The 1201 rulemaking process for exemptions to DMCA § 1201’s prohibition on breaking digital locks requires that the proposed activity be a fair use. In the 2021 proceedings, the Office recognized TDM for research and teaching purposes as a fair use. Because the expansion we’re seeking is relatively minor, our comment explains that the types of uses we are asking the Office to permit researchers to make is also fair use. Our comment explains that each of the four fair use factors favor fair use in the context of the proposed expansion. We further explain why the enhanced sharing the expansion would provide does not harm the market for the original works under factor four: because institutions must lawfully own (or license under a non-time-limited license) the works that their researchers wish to conduct TDM on, it makes no difference from a market standpoint whether researchers bypass technical protection measures themselves, or share another institution’s corpus. Copyright holders are not harmed when researchers at one institution share a corpus created by researchers at another institution, since both institutions must purchase the works in order to be eligible under the exemption. 

What’s Next?

If there are parties that oppose our proposed expansion, they have until February 20th to submit opposition comments to the Copyright Office. Then, on March 19th, our reply comments to any opposition comments will be due. We will keep our readers and members apprised as the process continues to move forward.

We are delighted to announce the publication of our brand new guide, the Authors Alliance Guide to Writing About Real People, a legal guide for authors writing nonfiction works about real people. The guide was written by students in two clinical teams at the UC Berkeley Samuelson Law and Public Policy Clinic—Lily Baggott, Jameson Davis, Tommy Ferdon, Alex Harvey, Emma Lee, and Daniel Todd—as well as clinical supervisors Jennifer Urban and Gabrielle Daley, along with Authors Alliance’s Senior Staff Attorney, Rachel Brooke. The guide was edited by Executive Director Dave Hansen and former Executive Director, Brianna Schofield. This long list of names is a testament to the fact that it took a village to create this guide, and we are so excited to finally share it with our members, allies, and any and all authors who need it. You can read and download our guide here. 

On Thursday, we are hosting a webinar about our guide, where Authors Alliance staff will share more about what went into producing it, those who partnered with us or supported the guide, and the particulars of the guide’s contents. Sign up here!

The Writing About Real People guide covers several different legal issues that can arise for authors writing about real people in nonfiction books like memoirs, biographies, and other narrative nonfiction projects. The issues it addresses are “causes of action” (or legal theories someone might sue under) based on state law. The requirements and considerations involved vary from state to state, so the guide highlights trends and commonalities among states. Throughout the guide, we emphasize that even though these causes of action might sound scary, the First Amendment to the U.S. Constitution in most cases empowers authors to write freely about topics of their choosing. The causes of action in this guide are exceptions to that rule, and each of them is limited in their reach and scope by the First Amendment’s guarantees. 

False Statements and Portrayals

The first section in the Writing About Real People guide concerns false statements and portrayals. This encompasses two different causes of action: defamation and false light. 

You have probably heard of defamation: it’s one of the most common causes of action related to writing about a real person. Defamation occurs when someone makes a false statement about another person that injures that person’s reputation, when the statement is made with some degree of “fault.” The level of fault required turns on what kind of person the statement is made about. For public people—people with some renown or governmental authority—the speaker must exercise “actual malice,” or reckless disregard as to whether the statement is true. But for private people, a speaker must be negligent as to whether the statement was true, meaning that the speaker failed to take an ordinary amount of care in verifying the veracity of the statement. An author might expose themselves to defamation liability if they write something untrue about another person in their published work that is held up as factual, that statement injures a person’s reputation, and the author failed to take the requisite level of care to ensure that the statement was factual. 

False light is similar to defamation, and many states do not recognize false light since these causes of action are so similar. Where defamation concerns false statements represented as factual, false light concerns false portrayals. It can occur when a speaker creates a misleading impression about a subject, through implication or omission, by example. Like defamation, false light requires fault on the part of the speaker, and the public person/private person standards are the same as for defamation. 

Invasions of Privacy

The second section in the Writing About Real People guide concerns invasions of privacy, or violations of a person’s rights to privacy. This covers two related causes of action: intrusion on seclusion and public disclosure of private facts. 

Intrusion on seclusion occurs when someone intentionally intrudes on another’s private place or affairs in a way that is highly offensive—judged by the perspective of an ordinary, reasonable person. For authors, intrusion on seclusion can arise when an author uses research or information-gathering methods that are invasive. This could include things like entering someone’s home without permission or digging through personal information like health or banking records without permission. Intrusion on seclusion might be an issue for authors during the research and writing stages of their processes, not when the work is actually published, as is the case with other causes of action in this guide.

Public disclosure of private facts occurs when someone makes private facts about a person public, when that disclosure is highly offensive and made with some degree of fault, and when the information disclosed doesn’t relate to a matter of public concern. Essentially, public disclosure of private facts liability exists to address situations where a speaker shares highly private information about a person that the public has no interest in knowing about, and the subject suffers as a result. Like defamation and false light, the level of fault required for a speaker to be liable depends on whether the subject is a public or private person, and these levels are the same as for defamation (actual malice for public people, and negligence for private people). This means that authors have much more leeway to share private information about public people than private people. And the “public concern” piece provides even more protection for speech about public people. 

Right of Publicity and Identity Rights

The third section in the Writing About Real People Guide concerns the right of publicity and unauthorized use of identity. Violations of the right of publicity, or unauthorized uses of identity, can occur when someone uses another person’s identity in a way that is “exploitative” and derives a benefit from that use. Importantly for authors, this excludes merely writing about someone in a book, article, or other piece of writing. The right of publicity is mostly concerned with commercial uses, like using someone’s name or likeness to sell a product without permission, but it can also apply to non-commercial uses that are exploitative, like using someone’s identity to generate attention for a work. In most cases, the right of publicity involves uses of someone’s image or likeness rather than just evoking their identity in text, but this is not necessarily the case. This section might be informative for authors who want to use someone’s image on their book cover or evoke an identity in advertising, but most authors merely writing nonfiction text about a real person do not have to worry too much about the right of publicity. 

Practical Guidance

A final section in our guide covers practical guidance for authors on how to avoid legal liability for the causes of action discussed in the guide in ways that are simple to understand and implement. Using reliable research methods and sources, obtaining consent from subjects where that is practicable, and carefully documenting your research and sources can go a long way towards helping you avoid legal liability while still empowering you to write freely.

We are pleased to announce that we have submitted a comment to the Copyright Office in response to their recent notice of inquiry regarding how copyright law interacts with generative AI. In our comment, we shared our views on copyright and generative AI (which you can read about here) and the stories we heard from authors about how they are using generative AI to support their creative labors, research, and the mundane but important tasks being involved with being a working author. The Office received over 10,000 comments in response to its NOI, showing the high level of interest in how copyright regulates AI-generated works and training data for generative AI. We hope the Office will appreciate our perspective as it considers policy interventions to address copyright issues involved in the use of generative AI by creators. You can read our full comment here, or at the bottom of this post. 

You can hear more about our comment, and about contributions from other commenters, at the Berkeley Center for Law and Technology virtual roundtable on Monday, November 13th, where Authors Alliance senior staff attorney Rachel Brooke will be a panelist. The event is free and open to the public, and you can sign up here. 

Background

Since the Copyright Office issued an opinion letter on copyright in a graphic novel containing AI-generated images back in February, the debate about copyright and generative AI has grown to a near fever pitch. Authors Alliance has been engaged in these issues since the decision letter was released: we exist to support authors who want to leverage the tools available in the digital age to see their creations reach broad audiences and create innovative new works, and we see generative AI systems as one such tool that can support authors and authorship. We participated in the Copyright Office’s listening session on copyright issues in AI-generated textual works this spring, and were eager to further weigh in as the Copyright Office wades through the thorny issues involved. 

In late August, the Copyright Office issued a notice of inquiry, asking stakeholders to weigh in on a series of questions about copyright policy and generative AI. These were broken down into general questions, questions about training AI models, questions about transparency and recordkeeping, and various issues related to AI outputs—copyrightability, infringement, and labeling and identification. 

Our Comment

Our comment was devoted in large part to sharing the ways that authors are using generative AI systems and tools to support their creative labors and research. We heard from authors that used generative AI systems for ideation, late stage editing, and generating text. We also learned that authors are using generative AI systems in ways we wouldn’t have anticipated—like creating books of prompts for other authors to use as inputs for generative AI systems. Generative AI has helped authors who don’t publish with conventional publishers create marketing copy and even generate book covers (despite the common adage, these are pretty important for attracting readers). We also heard from researchers using generative AI for literature reviews as well as to make their writing process more efficient so they can focus on doing the work of researching and innovating. Generative AI also has the potential to lower barriers to entry for scientific researchers who are not native English speakers, but want to make contributions to scientific fields in which literature tends to be written in English. 

We also spent some time explaining our views on why the use of copyrighted materials in training datasets for AI models constitutes fair use and how fair use analysis applies when copyrighted materials are included in training datasets. The use of creative works in training datasets is a transformative one with a different purpose than the works themselves—regardless of whether the institutions that develop and deploy them are commercial or nonprofit. And it’s highly unlikely that a generative AI system could harm the markets for the works in the training sets for the underlying models: a generative AI system is not a substitute for a book a reader is interested in reading, for example. We also explained that the market harm consideration (factor four in fair use analysis) should consider the effect of the use (using training data on AI models) on the market for the specific work in question (i.e., in an infringement action, the work that is alleged to have been infringed), and not the market for that author’s other works, similar works, or anything else.

Our comment also argued that new copyright legislation on AI—either to codify copyright’s human authorship requirement and explain how it applies to AI-generated content or to address other issues related to copyright and generative AI—is not warranted. AI systems, AI models, and the ways creators use them are still evolving. Copyright law is already highly flexible, having adapted to new technologies that weren’t anticipated when the copyright legislation itself was enacted. And legislating around nascent technologies can result in laws that are eventually ill-suited to deal with unexpected challenges that new technologies bring about (recall that the DMCA, which has faced a lot of criticism as a statute intended to regulate copyright online, was passed in 1998). We instead suggest that the Office stick with a “wait and see” approach as generative AI and how we use it continue to develop rather than recommending legislation to Congress. 

Next, we explained why a licensing system for AI works in training data is neither desirable nor practicable. Because we consider the use of copyrighted works in training data to be a fair use, licenses are not necessary in the first place. We also explained the host of problems that either a compulsory licensing regime or a collective licensing scheme would bring about. The large size of datasets for training AI models make it difficult to envision systematically seeking licenses for each and every copyrighted work in the training dataset, and the “orphan works problem” means that a majority of rightsholders might not be able to be found. It’s also not clear who would administer licensing under a licensing regime, and we could not think of any appropriate party that exists or is likely to emerge. The Office’s past failed investigations into possible collective rights management organizations (or CMOs) only underscore this point. 

Finally, we echoed our support for the substantial similarity test as a way to handle generative AI outputs that look very similar to existing copyrighted works. The substantial similarity test has been around for decades and has been applied across the country in a variety of contexts. It seems to us to be a good way to approach the rare cases in which generative AI outputs are strikingly similar to copyrighted works (so-called “memorization”) such that a rightsholder might sue for infringement. 

What’s Next?

The same day we submitted our comment, the Biden Administration released an executive order on “Safe, Secure, and Trustworthy Artificial Intelligence,” directing federal agencies to take a variety of measures to ensure that the use of generative AI is not harmful to innovation, privacy, labor, and more. Then on Wednesday, representatives from a coalition of countries (including the U.S.) signed “The Bletchley Declaration” following an AI Safety Summit in the U.K., warning of the dangers of generative AI and pledging to work together to find solutions. All of this is to say that how public policy should regulate generative AI, and whether and how the law needs to change to accommodate it, is a live issue that continues to evolve every day. Dozens of lawsuits are pending about the interaction between copyright and the use of generative AI systems, and as these cases move through the courts, judges will have their opportunity to weigh in. As ever, we will keep our readers and members appraised in any new legal developments around copyright and generative AI. 

Authors Alliance is delighted to announce that the Copyright Office has recommended that the Librarian of Congress renew both of the exemptions to DMCA liability for text and data mining in its Notice of Proposed Rulemaking for this year’s DMCA exemptions, released today. While the Librarian of Congress could technically disagree with the recommendation to renew, this rarely if ever happens in practice. 

Renewal Petitions and Recommendations

Authors Alliance petitioned the Office to renew the exemptions in July, along with our co-petitioners the American Association of University Professors and the Library Copyright Alliance. Then, the Office entertained comments from stakeholders and the public at large who wished to make statements in support of or in opposition to renewal of the existing exemptions, before drawing conclusions about renewal in today’s notice. 

The Office did not receive any comments arguing against renewal of the TDM exemption for literary works distributed electronically; our petition was unopposed. The Office agreed with Authors Alliance and our co-petitioners, ARL and AAUP, observing that “researchers are actively relying on the current exemption” and citing to an example of such research that we highlighted in our petition. Apparently agreeing with our statement that there have not been “material changes in facts, law, technology, or other circumstances” since the 1201 rulemaking cycle when the exemption was originally obtained, the Office stated it intended to recommend that the exemption be renewed. 

Our renewal petition for the text and data mining exemption for motion pictures, which is identical to the literary works exemption in all aspects but the type of works involved, did receive one opposition comment, but the Copyright Office found that it did not meet the standard for meaningful opposition, and recommended renewal. DVD CCA (the DVD Copyright Control Association) and AACS LA (the Advanced Access Content System Licensing Administrator) submitted a joint comment arguing that a statement in our petition indicated that there had been a change in the facts surrounding the exemption. More specifically, they argued that our statement that “[c]ommercially licensed text and data mining products continue to be made available to research institutions” constituted an admission that new licensed databases motion pictures had emerged since the previous rulemaking. DVD CCA and AACS LA did not actually offer any evidence of the emergence of new licensed databases for motion pictures. We believed this opposition comment was without merit—while licensed databases for text and data mining of audiovisual works are not as prevalent as licensed databases for text and data mining of text-based works, some were available during the 2021 rulemaking, and continue to be available today. We are pleased that the Office agreed, citing to the previous rulemaking record as supporting evidence.

Expansions and Next Steps

In addition to requesting that the Office renew the current exemptions, we (along with AAUP and LCA) also requested that the Office consider expanding these exemptions to enhance a researcher’s ability to share their corpus with other researchers that are not their direct collaborators. The two processes run in parallel, and today’s announcement means that even if we do not ultimately obtain expanded exemptions, the existing exemptions are very likely to be renewed. 

In its NPRM, the Office also announced deadlines for the various submissions that petitions for expansions and new exemptions will require. The first round of comments in support of  our proposed expansion—including documentary evidence from researchers who are being adversely affected by the limited sharing permitted under the existing exemptions—will be due December 22nd. Opposition comments are due February 20, 2024. Reply comments to these opposition comments are then due March 24, 2024. Then, later in the spring, there will be a hearing with the Copyright Office regarding our proposed expansion. We will—as always—keep our readers apprised as the process moves forward. 

Authors Alliance is currently at work on a submission to the Copyright Office regarding our views on generative AI (which you can read about here). If you’re an author who has used generative AI in your research or writing, we’d love to hear from you! Please reach out to Rachel Brooke, Authors Alliance Senior Staff Attorney, at rachel@authorsalliance.org.

Last week, the Court of Appeals for the D.C. Circuit released its opinion in the American Society for Testing and Medical Materials v. Public.Resource.org (“ASTM v. PRO”), an important fair use case that has been percolating in the D.C. Circuit for the past few years. Authors Alliance filed an amicus brief in the case in support of Public Resource, along with the Library Futures Institute, the EveryLibrary Institute, and Public Knowledge. The case is about public access to the law and the role of fair use in safeguarding that access, but it also has big implications for the ever-evolving doctrine of fair use. In general, we applaud the decision, which found for Public Resource, affirming the importance of access to the law and the important role that the fair use doctrine plays within copyright law. In today’s post, we summarize the case and offer our thoughts about what it might mean for fair use going forward, particularly regarding cases that impact our members and their interests.

Background

The case concerns standard-developing organizations and public access to the standards they produce. These organizations set standards and best practices for “particular industries, products, or problems,” including fire prevention and medical testing, among others. These standards are often incorporated into laws and regulations that govern these industries by various federal, state, and local lawmaking bodies. Government agencies incorporate these standards into law “by reference” when they refer to them in a given regulation, without reproducing the standards verbatim. For example, a federal regulation governing shipyard operators requires them to “select, maintain, and test portable fire extinguishers” in accordance with a particular National Fire Protection Association standard, but that regulation does not reproduce the standard itself. 

Public.Resource.org, a nonprofit organization that disseminates legal materials by posting them publicly online, posted on its website “hundreds of incorporated standards—including standards produced and copyrighted by the plaintiffs.” Then, in 2013, the standard-developing organizations sued for copyright infringement. Public Resource defended its posting of the standards as a fair use, but the lower court disagreed, requiring Public Resource to take the posted standards at issue down. After appeals, further fact development and multiple hearings at both the district court and appellate court level, the district court ultimately found Public Resource’s posting of the standards which were incorporated into law to be fair use. The standard-developing organizations appealed to the appeals court, which released its decision on September 12th.

Our Amicus Brief

In our amicus brief, we argued that “when a law-making body incorporates a standard by reference into legally-binding rule or regulation, the contents of the whole of that publication must be freely and fully accessible by the public.” Public access to the law is crucial for an informed citizenry and well-functioning democracy, which is why more conventional legal materials—like statutes, regulations, court cases, and agency rulemakings—have long been freely available to the public, online or otherwise. This principle ought to extend to legal standards that are incorporated by reference into law, despite the fact that private organizations create these standards, because incorporation by reference essentially gives them the force of law. We emphasized the potential harm to researchers and librarians were public access to standards incorporated by reference into law restricted. 

In fact, our brief argues that these standards should not be afforded copyright protection at all. Allowing private organizations to claim copyright in what is effectively the law does not serve the core purpose of copyright—to incentivize new creation for the benefit of the public. Materials authored by the federal government are automatically a part of the public domain, which also supports the important principle that no one can own the law—an idea which is enshrined in our Constitution and court cases dating to the 19th century. Due process—a Constitutional principle requiring the legal rights of all persons to be respected—mandates this kind of access, and it is often painted as one that is “beyond question.” While the standard-setting organizations have online “reading rooms” where the public can access the standards in question, this requires users to register, provide personal information, and agree to lengthy terms of service. As we explain in our brief, this is not sufficient for the free public access that the law requires.

The Decision

In its decision, the court determined that Public Resource’s posting of the standards that were incorporated by reference into law was a fair use, holding that three out of the four fair use factors favored a finding of fair use. While the court did not hold that the standards incorporated by reference into law were free from copyright protection, it did affirm the legal and policy justifications for free public access to the law. 

The first fair use factor, the purpose and character of the use, weighed in favor of Public Resource. On this point, the court emphasized that “Public Resource’s use is for nonprofit, educational purposes.” The question of whether a use is commercial can impact the way a court views this factor, as can the degree to which a court finds the use to be “transformative.” The court similarly found that Public Resource’s use was transformative, in that it was new and different from the purpose of the works themselves. Unlike the purposes of the original standards developed by the organizations—to promulgate best practices for industries and problems in the interest of industries and consumers—Public Resource’s purpose was to share with the public “only what the law is, not what industry groups may regard as current best practices.” The court summarized: “Public Resource’s message (‘this is the law’) is very different from the plaintiffs’ message (‘these are current best practices for the engineering of buildings and products’).” 

The second fair use factor directs courts to consider the nature of the copyrighted work—in this case, the standards that were incorporated by reference into law. The court found that this factor strongly favored a finding of fair use. The further a work from the “core of intended copyright protection,” i.e., the more creative it is, the more this factor favors fair use. In other words, because the standards at issue were highly factual in nature, rather than creative (like fiction writing), the second factor weighed in favor of fair use. 

The third fair use factor considers the amount and substantiality of the portion of the original work that was used, asking whether the portion of the work that was used is reasonable in light of the purpose of the secondary user’s use. The court found that this factor also weighed in favor of fair use. The various standards promulgated by the standard-setting organizations tended to be much longer in their entirety than the portions that were incorporated by reference into law. Public Resource only posted the portions of these standards that were incorporated into law, which was of course reasonably in light of its purpose of educating the public about what the law is. 

The fourth fair use factor considers the effect of the use on the market for the copyrighted works, and the court found that this factor was, on balance, neutral, and “[did] not significantly tip the balance one way or the other.” The standard setting organizations argued that their customers—industry members that needed to understand best practices—would fail to pay for the standards if they could obtain them for free from Public Resource. The court pointed out that only the standards incorporated into law were at issue, and the most up-to-date standards relied on by these industries were not necessarily incorporated into law. Moreover, the standard-setting organizations could not actually produce any evidence of market harm, despite the fact that Public Resource had been posting them online for approximately 15 years. The court also indicated that the public benefit of sharing this information with the public had to be balanced against any potential market harm. But because there was a possibility that Public Resource’s online posting could have lowered demand for the standards, the court found that this factor was neutral.

Impact on the Fair Use Doctrine

It remains to be seen how this case will impact the fair use doctrine and fair use decisions going forward, but it seems quite likely that this new judicial precedent might make a difference in future fair use decisions.

First, the contours of factor one—the purpose and character of the use—are very much a live issue following the recent decision in Warhol Foundation v. Goldsmith. In that case (in which we also submitted an amicus brief, supporting the Warhol Foundation’s fair use argument), the Supreme Court emphasized the fact that Warhol’s use was commercial in finding the use not to be fair. It seemed to emphasize commerciality over “transformativeness,” a longstanding aspect of factor one analysis (though that court found the use to not be transformative). The court in ASTM v. PRO certainly discussed commerciality as part of factor one, emphasizing Public Resource’s nonprofit status. But regarding the question of transformativeness, the court also gave a lengthy and eloquent summary of the different purposes of the two uses, indicating that transformativeness is still an important inquiry, and is not necessarily secondary to commerciality.

The weight of commerciality in factor one analysis can make a big difference in the outcome of cases, and it is an issue many have been watching with the dearth of copyright lawsuits concerning the use of copyrighted works to train generative AI models. This is because while there is a strong argument that the use of training data for these models is highly transformative, it is also true that the companies behind many of the models—like OpenAI, Midjourney, and Stability AI—are commercial in nature, and monetize their programs in different ways. The recent ASTM v. PRO decision could affect how courts weigh the commerciality of these companies’ uses of copyrighted training data against the extent to which the uses are transformative, potentially tipping the scale towards fair use in the upcoming copyright lawsuits about generative AI and training data. 

Second, the question of market harm in factor four can be a complicated one, and this case may provide some guidance for courts going forward. This issue was animated in the recent decision in Hachette Books v. Internet Archive—the case about whether controlled digital lending is a fair use, which we have been covering and involved in for years now, notably as an amicus in support of the Internet Archive. In the Hachette decision, the judge found that factor four weighed in favor of the publishers without direct evidence of financial harm, based on the idea that CDL scans could be substitutes for licensed ebooks. But in ASTM v. PRO, the court was skeptical that an allegation of potential market harm, without actual evidence, was sufficiently convincing. Since Hachette has been appealed and will soon be before the Second Circuit, we are hopeful that ASTM v. PRO will be a useful precedent for those judges. Extending the logic of ASTM v. PRO, it may be that the publishers will need to demonstrate market harm with tangible evidence (such as concrete evidence of lost sales) in that case in order to prevail on factor four.

Authors Alliance is pleased to announce that in recent weeks, we have submitted petitions to the Copyright Office requesting that it recommend renewing expanding the existing text data mining exemptions to DMCA liability to make the current legal carve-out that enables text and data mining more flexible, so that researchers can share their corpora of works with other researchers who want to conduct their own text data mining research. On each of these petitions, we were joined by two co-petitioners, the American Association of University Professors and the Library Copyright Alliance. These were short filings—requesting changes and providing brief explanations—and will be the first of many in our efforts to obtain a renewal and expansion of the existing TDM exemptions. 

Background

The Digital Millennium Copyright Act (DMCA) includes a provision that forbids people from bypassing technical protection measures on copyrighted works. But it also implements a triennial rulemaking process whereby organizations and individuals can petition for temporary exemptions to this rule. The Office recommends an exemption when its proponents show that they, or those they represent, are “adversely affected in their ability to make noninfringing [fair] uses due to the prohibition on circumventing access controls.” Every three years, petitioners must ask the Office to renew existing exemptions in order for them to continue to apply. Petitioners can also ask the Office to recommend expanding an existing exemption, which requires the same filings and procedure as petitioning for a new exemption. 

Back in 2020, during the eighth of these triennial rulemakings, Authors Alliance—along with the Library Copyright Alliance and the American Association of University Professors—petitioned the Copyright Office to create an exemption to DMCA liability that would enable researchers to conduct text and data mining. Text and data mining is a fair use, and the DMCA prohibitions on bypassing DRM and similar technical protection measures made it difficult or even impossible for researchers to conduct text and data mining on in-copyright e-books and films. After a long process which included filing a comment in support of the exemption and an ex parte meeting with the Copyright Office, the Office ultimately recommended that the Librarian of Congress grant our proposed exemption (which she did). The Office also recommended that the exemption be split into two parts, with one exemption addressing literary works distributed electronically, and the other addressing films. 

While the ninth triennial rulemaking does not technically happen until 2024, petitions for renewals, expansions, and new exemptions have already been filed. 

Our Petitions

Back in early July, we made our first filings with the Copyright Office in the form of renewal petitions for both exemptions. For this step, proponents of current exemptions simply ask the Copyright Office to renew them for another three year cycle, accompanied by a short explanation of whether and how the exemption is being used and a statement that neither law nor technology has changed such that the exemption is no longer warranted. Other parties are then given an opportunity to respond to or oppose renewal petitions. The Office recommends that exemption proponents who want to expand a current exemption also petition for its renewal—which is just what we did. In our renewal petitions, we explained how researchers are using the exemptions and how neither recent case law nor the continued availability of licensed TDM databases represent changes in the law or technology, making renewal of the TDM exemptions proper and justified. The renewal petitions follow a streamlined process, where they are generally simply granted unless the Office finds there to be “meaningful opposition” to a renewal petition, articulating a change in the law or facts. You can find our renewal petition for the literary works TDM exemption here, and our renewal petition for the film TDM exemption here.

But we also sought to expand the current exemptions, in two petitions submitted a few weeks back. In our expansion petitions, we proposed a simple change that we would like to see made to the current DMCA exemptions for text data mining. In the exemption’s current form, academic researchers can bypass technical protection measures to assemble a corpus on which to conduct TDM research, but they can only share it with other researchers for purposes of “collaboration and verification.” We asked the Office to permit these researchers to share their corpora with other researchers who want to use the corpus to conduct TDM research, but are not direct collaborators. However, this second group of researchers would still have to comply with the various requirements of the exemption, such as complying with security measures. Essentially, we seek to expand the sharing provision of the current exemption while leaving the other provisions intact. This is largely based on feedback we have received from those using the exemption and our understanding of how the regulation can be improved so that their desired noninfringing uses are no longer adversely affected by this limitation. You can find our expansion petition for the literary works TDM exemption here, and our expansion petition for the film TDM exemption here.

What’s Next?

The next step in the triennial rulemaking process is the Copyright Office issuing a notice of proposed rulemaking, where it will lay out its plan of action. While we do not have a set timeline for the notice of proposed rulemaking, during the last rulemaking cycle, it happened in mid-October—meaning it is reasonable to expect the Office to issue this notice in the next two months or so. Then, there will be several rounds of comments in support of or in opposition to the proposals. Finally, the Office will issue a final recommendation, and the Librarian of Congress will issue a final rule. While the Librarian of Congress is not legally obligated to adopt the Copyright Office’s recommendations, they traditionally do. Based on last year’s cycle, we can expect a final rule to be issued around October 2024. So we are in for a long wait and a lot of work! We will keep our readers updated as the rulemaking moves forward.