This post is by Maria Crusey, a third-year law student at Washington University in St. Louis. Maria has been working with Authors Alliance this semester on a project exploring legal claims in the now 30+ pending copyright AI lawsuits. 

In the recent spate of copyright infringement lawsuits against AI developers, many plaintiffs allege violations of 17 U.S.C. § 1202(b) in their use of copyrighted works for training and development of AI systems.  

Section 1202(b) prohibits the “removal or alteration of copyright management information.” Compared to related provisions in 17 U.S.C. § 1201, which protects against circumvention of copyright protection systems, §1202(b) has seldom been litigated at the appellate level, and there’s a growing divide among district courts about whether §1202(b) should apply to derivative works, particularly those created using AI technology.

At first glance, §1202(b) appears to be a straightforward provision. However, the uptick in §1202(b) claims raises some challenging questions, namely: How does §1202(b) apply to the use of a copyrighted work as part of a dataset that must be cleaned, restructured, and processed in ways that separate copyright management information from the content itself? And how should 1202(b) apply to AI systems that may reproduce small portions of content contained in training data?  Answers to this question may have serious implications in the AI suits because violations of 1202(b) can come with hefty statutory damage awards – between $2,500 and $25,000 for each violation. Spread across millions of works, the damages could be staggering. How the courts resolve this issue could also impact many other reuses of copyrighted works–from analogous uses such as text data mining research to much more routine re-distribution of copyrighted works in other contexts. 

One of these AI cases has requested that the Ninth Circuit Court of Appeals accept an interlocutory appeal on just this issue, and we are waiting to see whether the court will accept it.

For an introduction to §1202(b) and observations on this question, among others, read on:

What is § 1202(b) and what is it intended to do?

Broadly, 17 U.S.C. § 1202 is a provision of the Digital Millennium Copyright Act (DMCA) that protects the integrity of copyright management information (“CMI”). Per §1202(c), CMI comprises certain information identifying a copyrighted work, often including the title, the name of the author, and terms and conditions for the use of a work.

Section 1202(b) forbids the alteration or removal of copyright management information. The section provides that:

“[n]o person shall, without the authority of the copyright owner or the law – 

(1) intentionally remove or alter any CMI,

(2) distribute or import for distribution CMI knowing that the CMI has been removed or altered without authority of the copyright owner or the law, or 

(3) distribute, import for distribution, or publicly perform works, copies of works or phonorecords, knowing that copyright management information has been removed or altered without authority of the copyright owner or the law, knowing, or with respect to civil remedies under section 1203, having reasonable grounds to know that it will induce, enable, facilitate, or conceal an infringement of any right under this title.”

17 U.S.C. § 1202(b).

Congress primarily aimed to limit the assistance and enablement of copyright infringement in its enactment of §1202(b). This purpose is evident in the legislative history of the provision. In an address to a congressional subcommittee prior to the adoption of the DMCA, the then–Register of Copyrights, Marybeth Peters, discussed the aims of §1202(b). First, Peters noted that the requirements of §1202(b) would make CMI more reliable and thus aid in the administrability of copyright law. Second, Peters stated that §1202(b) would help prevent instances of copyright infringement that could come from the removal of CMI. The idea is if a copyrighted work lacks CMI, there is a greater likelihood of infringement since others may use the work under the pretense that they are the author or copyright holder. In creating a statutory violation for a party’s removal of CMI, regardless of later infringing activity, §1202(b) functions as damage control against potential copyright infringement.

What are the essential elements of a § 1202(b) claim?

To have a claim under §1202(b), a plaintiff must allege particularized facts about the existence and alteration or removal of CMI. Additionally, some courts require a plaintiff to demonstrate that the defendant had knowledge that the CMI was being altered or removed and that the alteration or removal would enable copyright infringement. Finally, some courts have required plaintiffs to show that the work with the altered or removed CMI is an exact copy of the original work–what has become known as the “identicality” requirement. This last “identicality” requirement is one of the main issues in the AI lawsuits raising §1202(b) and is detailed further below.

→ The “Identicality” Requirement

Courts that have imposed “identicality” have required that plaintiffs demonstrate that the work with the removed CMI is an exact copy of the original work and thus is “identical,” except for the missing or altered CMI. 

Suppose, for example, a photographer owns the copyright to a photograph they took. The photographer adds CMI to the photograph and takes care to protect the integrity of the work as it is dispersed online. A third party captures the photograph posted on a website by taking a screenshot and removes the CMI from the copied image while keeping all other aspects of the original photograph the same. The screenshot with the removed CMI is an “exact copy” of the original photograph because the only difference between the copyrighted photograph and the screenshot is the removal of the CMI.

Federal courts are divided in imposing the identicality requirement for §1202(b) claims, though the circuit courts have not yet addressed the issue. Notably, district courts of the Ninth Circuit Court of Appeals have varied in their treatments of the identicality requirement. For example, the court for the District of Nevada in Oracle v. Rimini Street declined to impose the identicality requirement because the requirement may weaken the intended protections for copyright holders under §1202(b). Conversely, in Kirk Kara Corp. v. W. Stone & Metal Corp., a court in the Central District of California applied the identicality requirement, though it provided little explanation for why it adopted it. Application of the identicality requirement is also unsettled in district courts beyond the Ninth Circuit (see, for example, this Southern District of Texas case discussing at length the identicality requirement and rejecting it). 

What are the §1202(b) claims at issue in the present suits?

The claims in Doe 1 v. Github exemplify the §1202(b) issues common among the present suits, and it is the Github suit that is presently before the Ninth Circuit Court of Appeals to take, if it wishes, on appeal.  

In Github, owners of copyrights in software code brought a suit against GitHub, a software developer platform. The plaintiffs alleged that Microsoft Copilot, an AI product developed in part by GitHub, illegally removed CMI from their works. The plaintiffs stored their software in GitHub’s publicly accessible software repositories under open-source license agreements. The plaintiffs claimed that GitHub removed CMI from their code and trained the Copilot AI model on the code in violation of the license agreements. Moreover, the plaintiffs claimed that, when prompted to generate software code, Copilot includes unique aspects of the plaintiffs’ code in its outputs. In their complaint, the plaintiffs alleged that all requirements for a valid § 1202(b) claim were met in the present suit. The plaintiffs stressed that, in removing CMI, the defendants failed to prevent users of products from making non-infringing use of the product. Consequently, they claim, the defendants removed the CMI, knowing that it would “induce, enable, facilitate, and/or conceal infringement” of copyrights in violation of the DMCA.

Regarding the §1202(b) claims, the parties contest the application of the identicality requirement. The plaintiffs first argue that § 1202 contains no such requirement: “The plain language of DMCA § 1202 makes it a violation to remove or alter CMI. It does not require that the output work be original or identical to obtain relief. . . By a plain reading of the statute, there is no need for a copy to be identical—there only needs to be copying, which Plaintiffs have amply alleged.” 

As a backstop, the plaintiffs further argue that Copilot does produce “near-identical reproduction[s]” of their copyrighted code and allege this is sufficient to fulfill the identicality requirement under §1202(b). Specifically, plaintiffs claimed that Copilot generates parts of plaintiffs’ code in extra lines of output code that are not relevant to input prompts. Plaintiffs also claimed Copilot generates their code in output code that produces errors due to a mismatch between the directly copied code and the code that would actually fit the prompt. To make this assertion work, plaintiffs distinguish their version of “identicality” –semantically equivalent lines of code–from a reproduction of the whole work. They argue that the defendant’s position, that “the reproduction of short passages that may be part of [a] larger work, rather than the reproduction of an entire work, is insufficient to violate Section 1202,” would lead to absurd results. “By OpenAI’s logic, a party could copy and distribute a fragment of a copyrighted work—say, a chapter of a book, a stanza of a poem, or a scene from a movie—and face no repercussions for infringement.” 

 In their reply, the defendants countered that §1202, which defines CMI as relating to a “copy of a work,” requires a complete and identical copy, not just snippets. Defendants noted that the plaintiffs have conceded that Copilot reproduces only snippets of code rather than complete versions of the code. Therefore, the defendants argue, Copilot does not create “identical copies” of the plaintiffs’ complete copyrighted works. The argument is based on both the text of the statute (they note that the statute only provides for liability when distributing copies that CMI has been stripped from, not derivatives, abridgments, or other adaptations), and they bolster those arguments by suggesting that allowing 1202 claims for incomplete copies would create chaos for ordinary uses of copyrighted works: “On Plaintiffs’ reading of § 1202, if someone opened an anthology of poetry and typed up a modified version of a single “stanza of a poem,” . . . without including the anthology’s copyright page, a § 1202(b) claim would lie. Plaintiffs’ reading effectively concedes that they are attempting to turn every garden-variety claim of copyright infringement into a DMCA claim, only without the usual limitations and defenses applicable under copyright law. Congress intended no such thing.” 

The GitHub court has addressed the issue now several times: it initially dismissed the plaintiffs’ §1202(b)(1) and (b)(3) claims, subsequently denied the plaintiffs’ motion for reconsideration of the claims, allowed the plaintiffs to amend their complaint and try again with more specificity, then dismissed the claims again. The reasoning of the court has been consistent, and largely focused on insufficient allegations of identicality. The court agreed with Defendants that the identicality requirement should apply and that the snippets do not satisfy the requirement. Following the dismissal, the plaintiffs sought and received permission from the district court to file an interlocutory appeal (an appeal on a specific issue before the case is fully resolved– something not usually allowed) to the Court of Appeals for the Ninth Circuit to determine whether § 202(b)(1) and (b)(3) impose an identicality requirement. The Ninth Circuit is presently considering whether to hear the appeal.

What would the Ninth Circuit assess in the appeal, and what are the implications of the appeal for future lawsuits?

If the appeal is accepted, the Ninth Circuit will determine whether §1202(b)(1) and (b)(3) actually impose an identicality requirement. Moreover, with regard to the facts of the Github case, the court will decide whether the identicality requirement requires exact copying of a complete copyrighted work, or perhaps something less. The Ninth Circuit’s hearing of this appeal would be notable for a number of reasons.

First, as mentioned above, §1202(b) is largely unaddressed by the circuit courts, and explicit appellate guidance has only been provided for the knowledge requirement referenced above. Consequently, determinations of §1202(b) claims are largely informed by varying district court decisions that are binding only on the parties to the suits and provide inconsistent interpretations of the requirements for a claim under the provision. An appellate ruling that accepts or rejects the identicality requirement would create additional binding authority to further clarify courts’ interpretations of §1202(b).

Second, a ruling on the identicality requirement from the Ninth Circuit specifically would be notable because it would be binding on the large number of §1202(b) claims presently being litigated in the Ninth Circuit’s lower courts. And, given the centrality of AI developers operating in California and elsewhere in the Ninth Circuit, the outcome of the appeal would significantly impact future lawsuits that involve §1202(b) claims.

It is hard to predict how the Ninth Circuit might rule, but we can work through some of the implications of the choices the court would have before it: 

If the Ninth Circuit interprets the identicality requirement as requiring a complete and exact copy, it would impose a high standard for the requirement and plaintiffs would likely be constrained in their ability to bring §1202(b) claims. If the court did this, the Github plaintiffs’ claims would likely fail as the alleged copied snippets of code generated by Copilot are not exact copies and do not comprise the complete copyrighted works. This hypothetical standard would be advantageous for individuals who remove CMI from copyrighted works in the course of processing them using AI as well as those who deploy AI systems that produce small portions of content similar (but not exactly so) to inputs.  So long as the works being processed or distributed are not complete exact copies, individuals would be free to alter the CMI of the works for ease in analyzing the copyrighted information. 

Alternatively, the Ninth Circuit could adopt a loose interpretation of identicality in which incomplete and inexact copying would be sufficient. One approach would be to require identicality but not copying of the entire work (something the plaintiffs in the Github suit advocate for). How the parties or the Ninth Circuit would formulate what standard would apply to this “less than entire” but still “near identical” standard is hard to say, but presumably, plaintiffs would have an easier time alleging facts sufficient for a §1202(b) claim. Applied to Github, it still seems unclear that the copied snippets of the plaintiffs’ code in the Copilot outputs could pass muster (this is likely a factual question to be determined at later stages of the litigation). But it could allow claims to at least survive an early motion to dismiss. As such, the adoption of this standard could limit how AI developers engage with works but also potentially affect others, such as researchers using similar techniques to process, clean, and distribute small portions of copyrighted works as part of a dataset.

Finally, the Ninth Circuit may decide to do away with the identicality requirement altogether. While this may seem like a potential boon to plaintiffs, who could allege that removal of CMI and distribution of some copied material, no matter how small, plaintiffs would still face substantial challenges.  Elimination of the identicality requirement would likely lead to greater weight being placed on the knowledge requirement in courts’ assessments of §1202(b) claims, which requires that defendants know or have reasonable grounds to know that their actions will “induce, enable, facilitate, or conceal an infringement.” In the context of the Github case, even without an identicality requirement, plaintiffs §1202(b) claims contain scant factual allegations about the defendants’ CMI removal and knowledge in the court filings to date. For other developers and users of AI, the effects of not having an identicality requirement would likely vary on a case-by-case basis. 

Conclusion

Recent copyright infringement suits and the pending appeal to the Ninth Circuit in Doe 1 v. Github demonstrate that §1202(b) is having its day in the sun. Although the provision has been overlooked and infrequently litigated in the past, the scope of protections granted by §1202(b) is important for understanding whether and how AI developers can remove CMI when using copyrighted works to process, restructure, and analyze copyrighted works for AI development. Thus, as lawsuits against AI developers and users continue to progress, the requirements to have a valid §1202(b) claim are sure to become even more contentious.

Sara Silverman is the author of The Bedwetter, a comedy memoir.  Richard Kadrey wrote Sandman Slim, a fantasy novel series. Christopher Golden, a supernatural thriller titled Ararat. 

These authors might not seem to have much in common with an academic author who writes in history, physics, or chemistry. Or a journalist. Or a poet. Or, for that matter, me, writing this blog post.  And yet, these authors may end up representing us all in court. 

A large number of the recent AI copyright lawsuits are class action lawsuits. This means that these lawsuits are brought by a small number of plaintiffs who (subject to judicial approval) are granted the right to represent a much larger class. In many of the AI copyright lawsuits,  the proposed classes are extraordinarily broad, including many creators who might be surprised that they are being represented. If you live in the US and wrote something that was published online, there is a good chance that you are included in multiple of these classes. 

A very brief background on class action lawsuits

Class actions can be an efficient way of resolving disputes that involve lots of people, allowing for a single resolution that binds many parties when there are common interests and facts. As you can imagine, the class action mechanism can also attract misuse, for example, by plaintiffs (and their attorneys) who may seek large settlements on behalf of a large number of people. Those settlements may benefit the named plaintiffs and their attorneys but they aren’t really aligned with the interests of most class members. 

There are rules in place to prevent that kind of abuse.  In federal courts (where all copyright lawsuits must be brought), Rule 23 of the Federal Rule of Civil Procedure governs. It provides that:

“One or more members of a class may sue or be sued as representative parties on behalf of all members only if: 
(1) the class is so numerous that joinder of all members is impracticable; [“numerosity”]
(2) there are questions of law or fact common to the class; [“commonality”]
(3) the claims or defenses of the representative parties are typical of the claims or defenses of the class; [“typicality”] and
(4) the representative parties will fairly and adequately protect the interests of the class. [“adequacy”]”

The rest of Rule 23 contains a number of other safeguards to protect both class members and defendants. Among them are requirements that the court must certify that the class complies with rule 23,  that any proposed settlements be approved by the court,  and that class members receive notice of any proposed settlement and an opportunity to object. Additionally, there are a number of rules to ensure that the law firm bringing the suit can fairly and competently represent the class members. 

Class definition and class representatives in the copyright AI lawsuits

We believe it’s important for creators to pay attention to these suits because if a class is certified and that class includes those creators, the class representatives will have meaningful legal authority to speak on their behalf.  

Rule 23  provides that “at an early practicable time after a person sues,” the court must decide whether to certify the proposed class. Though we are now well over a year into some of the earliest suits filed, this has yet to happen. In the meantime what we have are proposed class definitions offered by plaintiffs. How broadly or narrowly a class is defined by the plaintiffs will be one of the most important factors in whether the class can be certified since it will directly affect the commonality of facts among the class, the typicality of claims, and whether the representatives can fairly and adequately represent the interests of the class. Plaintiffs have the burden of proving that they have satisfied Rule 23. 

In these AI lawsuits, we see some themes in terms of class representative and proposed classes, with many offering very broad class definitions. For example, in the now-consolidated In re OpenAI ChatGPT Litigation, the class representatives are 11 fiction writers of books such as The Cabin at the End of the World, The Brief Wondrous Life of Oscar Wao, What the Dead Know and others. 

They propose to represent a class defined as follows:  

“All persons or entities domiciled in the United States that own a United States copyright in any work that was used as training data for the OpenAI Language Models during the Class Period [defined as June 28, 2020 to the present].” 

This kind of broad “anyone with a copyright in a work used for training” approach to class definition is repeated in a few other suits. For example, the consolidated Kadrey v. Meta lawsuit has a similar (and overlapping) grouping of fiction author class representatives and an almost identical proposed class definition. Dubus v. NVIDIA is another suit that takes essentially the same approach. 

Other AI lawsuits have more variation in class representatives. Huckabee v. Bloomberg, for example, is another suit with a similar class definition (basically, all copyrighted works owned by someone in the US and used for training Bloomberg’s LLM) but with class representatives that are a bit different: mostly authors of religious books and of course, Mike Huckabee, a politician. 

There is at least one class action that is more precise both in terms of proposed class representatives and their relation to the proposed class definition. The now-consolidated Authors Guild v. OpenAI suit has some 28 proposed class representatives, most of whom are authors of best-selling fiction and non-fiction trade books, 14 of whom are members of the Authors Guild. In this suit, the plaintiffs propose two classes: one for fiction authors and one for non-fiction authors. It also places some restrictions around them: class members for fiction works must be “natural persons” who are “sole authors of, and legal or beneficial owners of Eligible Copyrights in” fictional works that were registered with the U.S. Copyright Office and used for training the defendants’ LLMs (and this includes persons who are beneficiaries of works held by literary estates). For nonfiction authors, class members are “[a]ll natural persons, literary trusts, and literary estates in the United States who are legal or beneficial owners of Eligible Nonfiction Copyrights’ which the complaint defines as works used to train defendants’ LLMs and that have an ISBN with the exception of any books classified as reference works (BISAC code REF). 

Some challenges and dangers
When you consider the scale and scope of materials used to train the AI models in question, you can immediately see some of the challenges that are likely to arise with relatively small groups of authors attempting to represent practically all individual U.S. copyright owners. 

While the exact training materials used for the models at issue remain opaque, it’s definitely true that they were not just trained on modern fiction. There is widespread acknowledgment that these models are trained on a large amount of content scraped from across the internet using data sources such as Common Crawl. This, in effect, means that these suits implicate the rights of millions of rights holders, with interests as diverse as those of YouTube content creators, computer programmers, novelists, academics, and more. 

How can these representatives fairly and adequately represent such a broad and diverse group–especially when many may disagree with the underlying motivations for the suit to begin with–is a tough question. Even the Authors Guild consolidated case, which is much more careful in terms of class definition, includes classes that are breathtakingly broad when one considers the diversity of authorship within them. The fiction author class, for example, could include everyone from NY Times bestselling authors to fan fiction writers. The nonfiction class, which is at least limited to nonfiction book authors of works assigned an ISBN, could similarly include everyone from authors of popular self-help books distributed by the millions to scholarly books with print runs in the low hundreds and distributed online on open-access terms. The interests, financial and otherwise, of those authors can vary significantly. 

Beyond the adequacy of representatives (along with questions about whether their experiences are really typical of others in the proposed class), there are other challenges unique to copyright law, for example, the opaque nature of ownership (there is no official public record of who owns what), making ascertaining who actually falls within the class an initial challenge. Compounding that, there are a dizzying variety of unique terms under which works are distributed online, some of which may afford AI developers a viable defense for many works. A fair use defense also requires some level of assessment of the nature of the works used, a fact-intensive inquiry that will vary from one work to another. This just scratches the surface of some of the issues that likely mean there really aren’t common questions of law or fact among the class. 

Conclusion
There are good reasons to think that the classes as currently defined in these lawsuits are too broad. For some of the reasons mentioned above, I think it will be difficult for courts to certify them as is. But this doesn’t mean authors and other rightsholders should sit back and assume that their interests won’t be co-opted by others in these suits who seek to represent them. We don’t know when the courts will actually address these class certification issues in these suits. When they do, it will be important for authors to speak up.