On Monday, the Ninth Circuit issued a decision in Hunley v. Instagram, a case about whether Instagram (and platforms like it) can be held liable for secondary infringement based on its embedding feature, whereby websites employ code to display an Instagram post on their sites within their own content. We are delighted to announce that the court ruled in favor of Instagram, reinforcing important copyright principles which allow authors and other creators to link to and embed third-party content, enriching their writing in the process. 

Our Brief

Authors Alliance signed on to an amicus brief in this case, arguing that Instagram should not be held liable for contributory infringement for its embedding feature. We explained that Instagram was not liable under a precedential legal test established in Perfect 10 v. Amazon, and moreover that a ruling to the contrary could place our ability to link to other online content (which is analogous to embedding in many ways) at risk for legal liability. 

Narrowing the Perfect 10 test—which establishes that a website does not infringe when it does not store a copy of the relevant work on its server—would have struck a blow to how we share and engage with online content. Linking to other information allows authors to easily cite to other information without disrupting the flow of their writing. By the same token, it allows internet users to verify information and learn more about topics of interest, all with the click of a button. We are pleased that the court ruled in favor of Instagram, declining to revisit the Perfect 10 test and holding that it foreclosed relief for the photographers that had filed the lawsuit. In so doing, the court has helped maintain a vibrant internet where all can share and engage with knowledge and creative expression.

The Decision

The case concerned a group of photographers whose instagram posts were embedded into content by several media outlets. The photographers then sued Instagram in the Northern District of California, on the theory that by offering the “embedding” feature, it was facilitating copyright infringement of others and therefore was liable. The district court found that Perfect 10 applied to the case, and therefore that Instagram was not liable for infringement for the outlets’ display of the posts. 

The Ninth Circuit agreed, and furthermore declined to revisit or narrow the Perfect 10 case for a number of reasons—it rejected the argument that the search engines at issue in the Perfect 10 case itself were somehow different from social media platforms, and affirmed that Perfect 10 was consistent with more recent Supreme Court case law. The court also cited with approval our argument that embedding and in-line linking have paved the way for innovation and creativity online, though did not adopt the justification, reasoning that it is not a court’s job to serve as a policymaker. In applying the Perfect 10 test, the court explained that Instagram did not infringe the photographers’ copyrights, and where there is no direct infringement, there cannot be related secondary infringement. Instagram displayed a copy of the relevant photographs on its platform, which users permit via a license they agree to by using the platform. But it did not facilitate the images’ display elsewhere, because the computer code used by the media platforms that embedded the instagram posts did not make a copy of the posts, but rather formatted and displayed them. 

On May 17, the Copyright Office held a listening session on the topic of copyright issues in AI-generated audiovisual works. You may remember that we’ve covered the other listening sessions convened by the Office on visual arts, musical works, and textual works (in which we also participated). In today’s post, we’ll summarize and discuss the audiovisual works listening session and offer some insights on the conversation.

Participants in the audiovisual works listening session included AI developers in the audiovisual space such as Roblox and Hidden Door; trade groups and professional organizations including the Motion Picture Association, Writers Guild of America West, and National Association of Broadcasters; and individual filmmakers and game developers. 

Generative AI Tools in Films and Video Games

As was the case in the music listening session, multiple participants indicated that generative AI is already being used in film production. The representative from the Motion Picture Association (MPA) explained that “innovative studios” are already using generative AI in both the production and post-production processes. As with other creative industries, generative AI tools can support filmmakers by increasing the efficiency of various tasks that are part of the filmmaking process. For example, routine tasks like color correction and blurring or sharpening particular frames are made much simpler and quicker through the use of AI tools. Other participants discussed the ways in which generative AI can help with ideation, overcoming “creativity blocks,” eliminating some of the drudgery of filmmaking, enhancing visual effects, and lowering barriers to entry for would-be filmmakers without the resources of more established players. These examples are analogous to the various ways that generative AI can support authors, which Authors Alliance and others have discussed, like brainstorming, developing characters, and generating ideas for new works.

The representative from the MPA also emphasized the potential for AI tools to “enhance the viewer experience” by making visual effects more dramatic, and in the longer term, possibly enable much deeper experiences like having conversations with fictional characters from films. The representative from Hidden Door—a company that builds “online social role-playing games for groups of people to come together and tell stories together”—similarly spoke of new ways for audiences to engage with creators, such as by creating a sort of fan fiction world with the use of generative AI tools, with contributions from the author, the user, and the generative AI system. And in fact, this can create “new economic opportunities” for authors, who can monetize their content in new and innovative ways. 

Video games are similarly already incorporating generative AI. In fact, generative AI’s antecedents, such as “procedural content generation” and “rule-based systems” have been used in video games since their inception. 

Centering Human Creators

Throughout the listening session, participants emphasized the role of human filmmakers and game developers in creating works involving AI-generated elements, stating or implying that creators who use generative AI should own copyrights in the works they produce using these tools. The representative from Roblox, an online gaming platform that allows users to program games and play other users’ games, emphasized that AI-generated content is effective and engaging because of the human creativity inherent in “select[ing] the best output” and making other creative decisions. A representative from Inworld AI, a developer platform for AI characters, echoed this idea, explaining that these tools do not exist in isolation, but are productive only when a human uses them and makes creative choices about their use, akin to the use of a simpler tool like a camera or paintbrush. 

A concern expressed by several participants—including the Writers Guild of America West, National Broadcasters Association, and Directors Guild—is that works created using generative AI tools could devalue works created by humans without such tools. The idea of markets being “oversaturated” with competing audiovisual works raises the possibility that individual creators could be crowded out. While this is far from certain, it reflects increasing concerns over threats to creators’ economic livelihoods when AI-generated works compete alongside theirs. 

Training Data and Fair Use

On the question of whether using copyrighted training materials to train generative AI systems is a fair use, there was disagreement among participants. The representative from the Presentation Guild likened the use of copyrighted training data without permission to “entire works . . . being stolen outright.” They further said that fair use does not allow this type of use due to the commercial nature of the generative AI companies, the creative nature of the works used to train the systems (though it is worth noting that factual works, and others entitled only “thin” copyright protection, are also use to train these tools), and because by “wrest[ing] from the creator ownership and control of their own work[,]” the market value for those works is harmed . This is not, in my view, an accurate statement of how the market effects factor in fair use works, because unauthorized uses that are also fair always wrest some control from the author—this is part of copyright’s balance between an author’s rights and permitting onward fair uses. 

The representative from the Writers Guild of America (“WGA”) West—which is currently on strike over, among other things, the role of generative AI in television writing—had some interesting things to say about the use of copyrighted works as training data for generative AI systems. In contract negotiations, WGA had proposed a contract which “would . . . prohibit companies from using material written under the Guild’s agreement to train AI programs for the purpose of creating other derivative and potentially infringing works.” The companies refused to acquiesce, arguing that “the technology is new and they’re not inclined to limit their ability to use this new technology in the future.” The companies’ positions are somewhat similar to those expressed by us and many others—that while generative AI remains in its nascency, it is sensible to allow it to continue to develop before instituting new laws and regulations. But it does show the tension between this idea and creators who feel that their livelihoods may be threatened by generative AI’s potential to create works with less input from human authors. 

Other participants, such as the representative from Storyblock, a stock video licensing company, emphasized their belief that creators of the works used to train generative AI tools should be required to consent, and should receive compensation and credit for the use of their works to train these models. The so-called “three C’s” idea has gained traction in recent months. In my view, the use of training data is a fair use, making these requirements unnecessary from a copyright perspective, but it represents an increasingly prevailing view among rightsholders and licensing groups (including the WGA, motivating its ongoing strike in some respects) when it comes to making the use of generative AI tools more ethical. 

Adequacy of Registration Guidance

Several participants expressed concerns about the Copyright Office’s recent registration guidance regarding works containing AI-generated materials, and specifically how to draw the line between human-authored and AI-generated works when generative AI tools are used as part of a human’s creative process. The MPA representative explained that the guidance does not account for the subtle ways in which generative AI tools are used as part of the filmmaking process, where it often works as a component of various editing and production tools. The MPA representative argued that using these kinds of tools shouldn’t make parts of films unprotected by copyright or trigger a need to disclose minor uses of such tools in copyright registration applications. The representative from Roblox echoed these concerns, noting that when a video game involves thousands of lines of code, it would be difficult for a developer to disclaim copyright in certain lines of code that were AI-generated. 

A game developer and professor expressed her view that in the realm of video games, we are approaching a reality where generative AI is “so integrated into a lot of consumer-grade tools that people are going to find it impossible to be able to disclose AI usage.” If creators or users do not even realize they are using generative AI when they use various creative digital tools, the Office’s requirement that registrant’s disclose their use of generative AI in copyright registration applications will be difficult if not impossible to follow.

Today, the Supreme Court handed down a decision in Jack Daniel’s v. VIP Products, a trademark case about the right to parody popular brands, for which Authors Alliance submitted an amicus brief, supported by the Harvard Cyberlaw clinic. In a unanimous decision, the Court vacated and remanded the Ninth Circuit’s decision, overturning the decision asking the lower courts to re-hear the case with a new, albeit it very narrow, principle announced by the Court: special First Amendment review is not appropriate in cases where one brand’s trademark is used in another, even when used as a parody. In addition to the majority opinion delivered by Justice Kagan, there were two concurring opinions by Justice Sotomayor and Justice Gorsuch, each joined by other justices. 

Case Background

The case concerns a dog toy that parodies Jack Daniel’s famous Tennessee Whiskey bottle, using some of the familiar features from the bottle, and bearing the label “Bad Spaniels.” After discovering the dog toy, Jack Daniel’s requested that VIP cease selling the toys. VIP Products refused, then proceeded to file a trademark suit, asking for a declaratory judgment that its toy “neither infringed nor diluted Jack Daniel’s trademarks.” Jack Daniel’s then countersued to enforce its trademark, arguing that the Bad Spaniels toy infringed its trademark and diluted its brand. We became interested in the case because of its implications for creators of all sorts (beyond companies making humorous parody products). 

As we explain in our amicus brief, authors rely on their ability to use popular brands in their works. For example, fiction authors might send their characters to real-life colleges and universities, set scenes where characters dine at real-life restaurant chains, and use other cultural touchstones to enrich their works and ultimately, to express themselves. While the case is about trademark, the First Amendment looms large in the background. A creator’s right to parody brands, stories, and other cultural objects is an important part of our First Amendment rights, and is particularly important for authors. 

Trademark law is about protecting consumers from being confused as to the source of the goods and services they purchase. But it is important that trademark law be enforced consistent with the First Amendment and its guarantees of free expression. And importantly, trademark litigation is hugely expensive, often involving costly consumer surveys and multiple rounds of hearings and appeals. We are concerned that even the threat of litigation could create a chilling effect on authors, who might sensibly decide not to use popular brands in their works based on the possibility of being sued. 

In our brief, we suggested that the Court implement a framework like the one established by the Second Circuit in Rogers v. Grimaldi, “a threshold test . . . designed to protect First Amendment interests in the trademark context.” Under Rogers, in cases of creative expressive works, trademark infringement should only come into play “where the public interest in avoiding consumer confusion outweighs the public interest in free expression.” It establishes that trademark law should only be applied where the use “has no artistic relevance to the underlying work whatsoever, or, if it has some artistic relevance, unless the [second work] explicitly misleads as to the source or the content of the work.”

The Supreme Court’s Decision

In today’s decision, the Court held that “[w]hen an alleged infringer uses a trademark as a designation of source for the infringer’s own goods, the Rogers test does not apply.” Without directly taking a position on the viability of the Rogers test, the Court found that, in this circumstance, where it believed that VIP Products used Jack Daniel’s trademarks for “source identifiers,” the test was inapplicable. It held that the Rogers test is not appropriate when the accused infringer has used a trademark to designate the source of its own goods—in other words, has used a trademark as a trademark.” The fact that the dog toy had “expressive content” did not disturb this conclusion. 

Describing Rogers as a noncommercial exclusion, the Court said that VIP’s use was commercial, as it was on a dog toy available for sale (i.e. a commercial product). Further supporting this conclusion, the Court pointed to the fact that VIP Products had registered a trademark in “Bad Spaniels.” It found that the Ninth Circuit’s interpretation of the “noncommercial use exception” was overly broad, noting that the Rogers case itself concerned a film, an expressive work entitled to the highest First Amendment protection, and vacating the lower court’s decision. 

The Court instead directed the lower court to consider a different inquiry, whether consumers will be confused as to whether Bad Spaniels is associated with Jack Daniel’s, rather than focusing on the expressive elements of the Bad Spaniels toy. But the Court also explained that “a trademark’s expressive message—particularly a parodic one, as VIP asserts—may properly figure in assessing the likelihood of confusion.” In other words, the fact that the Bad Spaniels toy is (at least in our view) a clear parody of Jack Daniel’s may make it more likely that consumers are not confused into thinking that Jack Daniel’s is associated with the toy. In her concurrence, Justice Sotomayor underscored this point by cautioning lower courts against relying too heavily on survey evidence when deciding whether consumers are confused “in the context of parodies and potentially other uses implicating First Amendment concerns.” In so doing, Justice Sotomayor emphasized the importance of parody as a form of First Amendment expression. 

The Court’s decision is quite narrow. It does not disapprove of the Rogers test in other contexts, such as when a trademark is used in an expressive work, and as such, it is unlikely to have a large impact on authors using brands and marks in their books and other creative expression. Lower courts across the country that do use the Rogers test may continue to do so under VIP Products.However, Justice Gorsuch’s concurrence does express some skepticism about the Rogers test and its applications, cautioning lower courts to handle the test with care. However, as a concurrence, this opinion has much less precedential effect than the majority’s. 

Remaining Questions

All of this being said, the Court does not explain why First Amendment scrutiny should not apply in this case, but merely reiterates that Rogers as a doctrine is and has always been “cabined,” with  “the Rogers test [applying] only to cases involving ‘non-trademark uses[.]’” The Court relies on that history and precedent rather than explaining the reasoning. Nor does the Court discuss the relevance of the commercial/noncommercial use distinction when it comes to the role of the First Amendment in trademark law. In our view, the Bad Spaniels toy did contain some highly expressive elements and functioned as a parody, so this omission is significant. And it may create some confusion for closer cases—at one point, Justice Kagan explains that “the likelihood-of-confusion inquiry does enough work to account for the interest in free expression,” “except, potentially, in rare situations.” We are left to wonder what those are. She further notes that the Court’s narrow decision “does not decide how far the ‘noncommercial use exclusion’ goes.” This may leave lower courts without sufficient guidance as to the reach of the noncommercial use exclusion from trademark liability and what “rare situations” merit application of the Rogers test to commercial or quasi-commercial uses.

Earlier this week, the Copyright Office convened a listening session on the topic of copyright issues in AI-generated music and sound recordings, the fourth in its listening session series on copyright issues in different types of AI-generated creative works. Authors Alliance participated in the first listening session on AI-generated textual works, and we wrote about the second listening session on AI-generated images here. The AI-generated music listening session participants included music industry trade organizations like the Recording Industry Association of America, Songwriters of North America, and the National Music Publishers’ Association; generative AI music companies like Boomy, Tuney, and Infinite Album; music labels like the Universal Music Group and Wixen; and individual musicians, artists, and songwriters. Streaming service Spotify and collective-licensing group SoundExchange also participated. 

Generative AI Tools in the Music Industry

Many listening session participants discussed the fact that some musical artists, such as Radiohead and Brian Eno, have been using generative AI tools as part of their work for decades. For those creators, generative AI music is nothing new, but rather an expansion of existing tools and techniques. What is new is the ease with which ordinary internet users without musical training can assemble songs using AI tools—programs like Boomy enable users to generate melodies and musical compositions, with options to overlay voices or add other sounds. Some participants sought to distinguish generative tools from so-called “assistive tools,” with the latter being more established for professional and amateur musicians. 

Where some established artists themselves have long relied on assistive AI tools to create their works, AI-generated music has lowered barriers to entry for music creation significantly. Some take the view that this is a good thing, enabling more creation by more people who could not otherwise produce music. Others protest that those with musical talent and training are being harmed by the influx of new participants in music creation, as these types of songs flood the market. In my view, it’s important to remember that the purpose of copyright, furthering the progress of science and the useful arts, is served when more people can generate creative works, including music. Yet AI-generated music may already be at or past the point where it can be indistinguishable from works created by human artists without the use of these tools, at least to some listeners. It may be the case that, as at least one participant suggested, audio generated works are somehow different from AI-generated textual works such that they may require different forms of regulation. 

Right of Publicity and Name, Image, and Likeness

Although the topic of the listening session was federal copyright law, several participants discussed artists’ rights in both their identities and voices—aspects of the “right of publicity” or the related name, image, and likeness (“NIL”) doctrine. These rights are creatures of state law, rather than federal law, and allow individuals, particularly celebrities, to control what uses various aspects of their identities may be put to. In one well-known right of publicity case, Ford used a Bette Midler “sound alike” for a car commercial, which was found to violate her right of publicity. That case and others like it have popularized the idea that the right of publicity can cover voice. This is a particularly salient issue within the context of AI-generated music due to the rise of “soundalikes” or “voice cloning” songs that have garnered substantial popularity and controversy, such as the recent Drake soundalike, “Heart on My Sleeve.” Some worry that listeners could believe they are listening to the named musical artist when in fact they are listening to an imitation, potentially harming the market for that artist’s work. 

The representative from the Music Artists Coalition argued that the hodge podge of state laws governing the right of publicity could be one reason why soundalikes have proliferated: different states have different levels of protection, and the lack of unified guidance on how these types of songs are governed under the law can create uncertainty as to how they will be regulated. And the representative from Controlla argued that copyright protection should be expanded to cover voice or identity rights. In my view, expanding the scope of copyright in this way is neither reasonable nor necessary as a matter of policy (and furthermore, would be a matter for Congress, and not the Copyright Office, to address), but it does show the breadth of the soundalike problem for the music industry. 

Copyrightability of AI-Generated Songs

Several listening session participants argued for intellectual property rights in AI-generated songs, and others argued that the law should continue to center human creators. The Copyright Office’s recent guidance regarding copyright in AI-generated works suggests that the Office does not believe that there is any copyright in the AI-generated materials due to the lack of human authorship, but human selection, editing, and compilation can be protected. The representatives from companies with AI-generating tools expressed a need for some form of copyright protection for the songs these programs produce, explaining that they cannot be effectively commercialized if they are not protected. In my view, this can be accomplished through protection for the songs as compilations of uncopyrightable materials or as original works, owing to human input and editing. Yet, as many listening session participants across these sessions have argued, the Copyright Office registration guidance does not make clear precisely how much human input or editing is needed to render an AI-generated work a protectable original work of authorship. 

Licensing or Fair Use of AI Training Data

In contrast to the view taken by many during the AI-generated text listening session, none of the participants in this listening session argued outright that training generative AI programs on in-copyright musical works was fair use. Instead, much of the discussion focused on the need for a licensing scheme for audio materials used to train generative AI audio programs. Unlike the situations with many text and image-based generative AI programs, the representatives from generative AI music programs expressed an interest and willingness to enter into licensing agreements with music labels or artists. In fact, there is some evidence that licensing conversations are already taking place. 

The lack of fair use arguments during this listening session may be due to the particular participants, industry norms, or the “safety” of expressing this view in the context of the music industry. But regardless, it provides an interesting contrast to views around training data text-generating programs like ChatGPT, which many (including Authors Alliance) have argued are fair uses. This is particularly remarkable since at least some of these programs, in our view, use the audio data they are trained on for a highly transformative purpose. Infinite Album, for example, allows users to generate “infinite music” to accompany video games. The music reacts to events in the video game—becoming more joyful and upbeat for victories, or sad for defeats—and can even work interactively for those streaming their games, where those watching the stream can temporarily influence the music. This seems like precisely the sort of “new and different purpose” that fair use contemplates, and similarly like a service that is unlikely to compete directly with individual songs and records. 

Generative AI and Warhol Foundation v. Goldsmith

Many listening session participants discussed the interactions between how AI-generated music should be regulated under copyright law and the recent Supreme Court fair use decision in Warhol Foundation v. Goldsmith (you can read our coverage of that decision here), which also considered whether a particular use which could have been licensed was fair use. And some participants argued that the decision in Goldsmith makes it clear that training generative AI models (i.e., the input stage) is not a fair use under the law. It is not clear precisely how the decision will impact the fair use doctrine going forward, particularly as it applies to generative AI, and I think it is a stretch to call it a death knell for the argument that training generative AI models is a fair use. However, the Court did put a striking emphasis on the commerciality of the use in that case, deemphasizing the transformativeness inquiry somewhat. This could impact the fair use inquiry in the context of generative AI programs, as these programs tend overwhelmingly to be commercial, and the outputs they create can and are being used for commercial purposes. 

Yesterday, the Supreme Court released two important decisions in Warhol Foundation v. Goldsmith and Gonzalez v. Google—cases that Authors Alliance has been deeply invested in, submitting amicus briefs to the Court in both cases. 

Warhol Foundation v. Goldsmith and Transformativeness

First, the Court issued its long-awaited opinion in Warhol Foundation v. Goldsmith, a case Authors Alliance has been following for years, and for which we submitted an amicus brief last summer. The case concerned a series of screen prints of the late musical artist Prince created by Andy Warhol, and asked whether the creation and licensing of one of the images, an orange screen print inspired by Goldsmith’s black and white photograph (which the Court calls “Orange Prince”), constituted fair use. After the Southern District of New York found for the Warhol Foundation on fair use grounds, the Second Circuit overturned the ruling, finding that the Warhol Foundation’s use constituted infringement. The sole question before the Supreme Court was whether the first factor in fair use analysis, the purpose and character of the use, favored a finding of fair use. 

To our disappointment, the Supreme Court’s majority agreed with the holding of the district court, finding that the purpose and character of Warhol’s use favored Goldsmith, such that it did not support a finding of fair use. This being said, the decision focused narrowly on the Warhol Foundation’s “commercial licensing of Orange Prince to Condé Nast,” expressing “no opinion as to the creation, display, or sale of any of the original Prince Series works.” Because the Court cabins its opinion, focusing specifically on the licensing of Orange Prince to Condé Nast rather than the creation of the entire Prince series, the decision is less likely to have a deleterious effect on the fair use doctrine generally than a broader decision would have. 

Writing for the majority, Justice Sotomayor argued that Goldsmith’s photograph and the Prince screen print in question shared the same purpose, “portraits of Prince used to depict Prince in magazine stories about Prince.” Moreover, the Court found the use to be commercial, given that the screen print was licensed to Condé Nast. Justice Sotomayor explained that “if an original work and secondary use share the same or highly similar purposes, and the secondary use is commercial, the first fair use factor is likely to weigh against fair use, absent some other justification for copying.” Justice Sotomayor found that the two works shared the same commercial purpose, and therefore concluded that factor one favored Goldsmith. 

Justice Kagan, joined by Chief Justice Roberts, issued a strongly worded dissenting opinion. The dissent admonished the majority for its departure from Campbell’s “new meaning or message test,” an inquiry that Authors Alliance advocated for in our amicus brief. Justice Kagan further criticized the majority’s shifting focus towards commerciality, arguing that the fact that the use was a licensing transaction should not be given so much importance in the analysis. While Authors Alliance agrees with these points, we are less sure that the majority’s decision goes so far as to “constrain creative expression” or “threaten[] the creative process. And while it’s uncertain what effect this case will have on the fair use doctrine more generally, one important takeaway is that the question of whether the use in question is commercial in nature—a consideration under the first factor—has been elevated to one of greater importance. 

While we thought this case offered a good opportunity for the Court to affirm a more nuanced approach to transformative use, we much prefer the Supreme Court’s approach to the Second Circuit’s decision, and applaud the Court on confining its ruling to the narrow question at issue. The holding does not, in our view, radically alter the doctrine of fair use or disrupt a bulk of established case law. Moreover, some aspects of arguments we made in our brief—such as the notion that transformativeness is a matter of degree, not a binary—are present in the Court’s decision. This is a good thing, in our view, as it will allow for more nuanced consideration of a use’s character and purpose, and stands in contrast to the Second Circuit’s all or nothing view of transformativeness. 

Gonzalez v. Google and the Missing Section 230

Also yesterday, the Court released its opinion in Gonzalez v. Google, a case that generated much attention because of its potential threat to Section 230, and another case in which Authors Alliance submitted an amicus brief. The case asked whether Google could be held liable under an anti-terrorism statute for harm caused by ISIS recruitment videos that YouTube’s algorithm recommended. In its per curiam decision (a unanimous one without a named Justice as author), the Court stated that Gonzalez’s complaint had failed to state a viable claim under the relevant anti-terrorism statute. Therefore, it did not reach the question of the applicability of Section 230 to the recommendations at issue. In other words, a case that generated tremendous concern about the Court disturbing Section 230 and harming internet creators, communities, and services that relied on it ended up saying nothing at all about the statute. 

Yesterday, I represented Authors Alliance in a Copyright Office listening session on copyright issues in AI-generated literary works, in the first of two of such sessions that the Office convened yesterday afternoon. I was pleased to be invited to share our views with the Office and participate in a rousing discussion among nine other stakeholders, representing a diverse group of industries and positions. Generative AI raises challenging legal questions, particularly for its skeptics, but it also presents some incredible opportunities for authors and other creators.

During the listening session, I emphasized the potential for generative AI programs (like OpenAI’s Chat GPT, Microsoft’s Bing AI, Jasper, and others) to support authorship in a number of different ways. For instance, generative AI programs support authors by increasing the efficiency of some of the practical aspects of being a working author aside from their writings. But more importantly, generative AI programs can actually help authors express themselves and create new works of authorship. 

In the first category, generative AI programs can support authors by, for example, helping them create text for pitch letters to send to agents and editors, produce copy for their professional websites, and develop marketing strategies for their books. Making these activities more efficient frees up time for authors to focus on their writing, particularly for authors whose writing time is limited by other commitments. 

In the second category, generative AI has tremendous potential to help authors come up with new ideas for stories, develop characters, summarize their writings, and perform early stage edits of manuscripts. Moreover, and particularly for academic authors, generative AI can be an effective research tool for authors seeking to learn from a large corpus of texts. Generative AI programs can help authors research by providing short and simple summaries of complex issues, surveys of the landscape of various fields, or even guidance on what human works to turn to in their research. Authors Alliance is committed to protecting authors’ right to conduct research, and we see generative AI tools as a new, innovative, and efficient form of conducting this research. Making research easier helps authors save time, and has a particular benefit for authors with disabilities that make it difficult to travel to multiple libraries or otherwise rely on analog forms of research. 

These programs undoubtedly have the potential to serve as powerful creative tools that support authorship in these ways and more, but, when discussing the copyright implications of the programs and the works they produce, it’s important to remember just how new these technologies are. Because generative AI remains in its infancy, and the costs and benefits for different segments of the creative industry have yet to be seen, it seems to me to be sensible to preserve the development of these tools before crafting legal solutions to problems they might pose in the future. And in fact, in our view, U.S. copyright law already has the tools to deal with many of the legal challenges that these programs might post. When generative AI outputs look too much like the copyrighted inputs they are trained on, the substantial similarity test can be used to assess claims of copyright infringement to vindicate an authors’ exclusive rights in their works when those outputs do infringe. 

In any case, in order for generative AI programs to be effective creative tools, it’s necessary that they are trained on large corpora. Narrowing the corpus of works the programs are trained on—through compulsory licensing or other mechanisms—can have disastrous effects. For example, research has shown that narrow data sets are more likely to produce racial and gender bias in AI outputs. In our view, the “input” step, where the programs are trained on a large corpus of works, is a fair use of these texts. And the holdings in Google Books and HathiTrust indicate that it is consistent with fair use to build large corpora of works, including works that remain protected by copyright, for applications such as computational research and information discovery. Additionally, the Copyright Office has recognized this principle in the context of research and scholarship, as demonstrated by its approval of Authors Alliance’s petition for an exemption from DMCA restrictions for text and data mining. 

The question of the copyright status of AI-generated works is an important one. Most if not all of the stakeholders participating in this discussion agreed with the Copyright Office’s recent guidance regarding registration in AI-generated works: under ordinary copyright principles, the lack of human authorship means these texts are not protected by copyright. This being said, we also recognize that there may be challenges in reconciling existing copyright principles with these new types of works and the questions about authorship, creativity, and market competition that they might pose. 

But importantly, while this technology is still in its early stages, it serves the core purposes of copyright—furthering the progress of science and the useful arts by incentivizing new creation—to allow these systems to develop and confront new legal challenges as they emerge. Copyright is not only about protecting the exclusive rights of copyright holders (a concern that underlies many arguments against generative AI as a fair use), but incentivizing creativity for the public benefit. The new forms of creation made possible through generative AI can incentivize people who would not otherwise create expressive works to do so, bringing more people into creative industries and adding new creative expression to the world to the benefit of the public.

The listening sessions were recorded, and will be available on the Copyright Office website in the coming weeks. And these listening sessions are only the beginning of the Office’s investigation of copyright in AI generated works. Other listening sessions on visual works, music, and audiovisual works will be held in the coming weeks, and the Office has indicated that there will be an opportunity for written public comments in order for stakeholders to weigh in further. We are committed to remaining involved in these cutting edge issues, through written comments and otherwise, and we will keep our readers informed as policy around generative AI continues to evolve. 

Yesterday, Authors Alliance submitted a comment to the U.S. Copyright Office in response to a notice of proposed rulemaking asking for feedback from the public on new rules to govern ex parte communications. “Ex parte communications” refer to communications outside the normal, permitted channels of communication—in this case, to communications between organizations or members of the public and Copyright Office staff outside of hearings or other formal proceedings. Ex parte communications with the Copyright Office are important, because they allow stakeholders and the office to work out open questions in rulemakings or other proceedings outside of the formal channels. Authors Alliance relied on our ability to make ex parte communications during the last Section1201 rulemaking cycle (where we obtained our text data mining exemption) in order to clarify certain issues. Now, the Office is proposing establishing formal rules for how these communications can be made, as well as establishing transparency around them. We support this proposal, and shared our thoughts in a comment. You can read our full comment here.

On Friday, Southern District of New York Judge John Koeltl issued a much-anticipated decision in Hachette Books v. Internet Archive. Unfortunately, as many of our members and allies are aware, the judge ruled against the Internet Archive, finding that its CDL program was not protected by the doctrine of fair use and granting the publishers’ motion for summary judgment. You can read the 47-page decision for yourself here. 

In his fair use analysis, Judge Koeltl found that each of the four fair use factors weighed in favor of the publishers, emphasizing above all else his view that IA’s controlled digital lending program was not transformative, an important consideration under the first fair use factor, which considers the purpose and character of the use. This inquiry also involves asking whether the use in question was commercial. To the surprise of many, the decision stated that IA’s use of the publishers’ works was commercial, because the Open Library is part of the IA’s website, which it uses “to attract new members, solicit donations, and bolster its standing in the library community.” The judge found this to be the case in spite of the fact that IA “does not make a monetary profit” from CDL. In other words, the judge held that the indirect, attenuated benefits the Internet Archive (which is, after all, a nonprofit) reaps from operating the Open Library makes its CDL program commercial. 

Judge Koeltl gave less attention to the fourth factor in the fair use analysis, “the effect of the use on the potential market for the work,” which is often held up to be of significant importance. One consideration under this factor is whether the use creates a competing substitute with the original work. Unfortunately, on this point too, the court—in our view—missed the mark. This is because the decision does not draw a distinction between CDL scans and ebooks, going so far as to call CDL scans “ebooks” throughout. As we explained in our summary of the proceedings last week, many features of both CDL and ebooks make them both functionally and aesthetically distinct from one another. By glossing over these differences, the judge reached the conclusion that CDL scans are direct substitutes for licensed ebooks.

Authors Alliance is deeply concerned about the ramifications of this decision, which was exceedingly broad in scope, striking a tremendous blow to the CDL model, rather than only IA’s implementation of it. Local libraries across the country practice CDL, and library patrons and authors alike depend on it to read, research, and participate in academic discourse. 

As it stands, this decision only applies to Internet Archive and is only about the 127 books on which the publishers based their lawsuit. It does not set a binding precedent for any other library, but if left in place (or worse, if affirmed on appeal), it could cause libraries to avoid digitizing and lending books under a CDL model, which in our view would not serve the interests of many authors. This decision makes it harder for those authors to reach wide audiences: CDL enables many authors to reach more readers than they could otherwise, and authors like our members who write to be read would not be served if fewer readers could access their books. 

The decision also hampers efforts to preserve books—aside from IA’s scanning program, there are few if any centralized efforts to preserve books in digital format once their commercial life is over. Without CDL, those books could quite literally disappear, and the knowledge they advance could be lost. IA’s scanning operations do preserve such books, which is one reason we have strongly supported them in this lawsuit. By the same token, if this decision stands, it will also limit authors’ ability to conduct efficient research online. The CDL survey we launched last year revealed that CDL is an effective research tool for authors who need to consult other books as part of their writing process, and in many cases it enables them to access far more works than they could at their local library alone. Authors who rely on CDL in this way would be harmed by this decision, as they could well be forced to undergo a more time-consuming research process, detracting from time that could be spent writing. 

The Internet Archive has already indicated that it will be appealing Judge Koeltl’s ruling, and we look forward to supporting those efforts. We will continue to keep our readers and members apprised of updates as this case moves forward.