Category: Intellectual Property

The Courts Should Embrace the Novelty of Generative AI in Copyright Law

courts

Courts can’t stick their heads in the sand to an obvious way that a new technology might severely harm the incentive to create, just because the issue has not come up before. Indeed, it seems likely that market dilution will often cause plaintiffs to decisively win the fourth factor—and thus win the fair use question overall—in cases like this. – Judge Vincent Chhabria, Kadrey et al. v. Meta –

In several posts, I have argued that generative AI (GAI) invokes novel copyright considerations on the basis that the technology has the potential to harm authorship itself, even where it may not harm specific works of authorship under traditional fair use analysis. GAI is distinguishable from any technology with which copyright law has had to contend, and if the courts will continue to guide the law to preserve copyright’s foundational principle—the incentive to create—they should recognize and even embrace the invitation to plow some new legal ground.

In the Copyright Office’s third report on artificial intelligence, one section introduces the notion of market dilution, which cites several comments including my own. Naturally, the AI industry rejects the premise that market dilution of all works, or even a certain type of work, is a valid consideration under copyright law. This argument, albeit self-interested, has some merit under traditional fair use analysis. Fair use factor four, which considers whether a specific use potentially threatens the market value of the work(s) in suit may be narrowly construed to reject the kind of generalized market harm implied by GAI.

But as the quote above reveals, Judge Chhabria in Kadrey et al. v. Meta (not even one of the strongest cases against AI developers) recognizes the novelty of this technology to undermine the foundational purpose of copyright law.  He also states, “…by training generative AI models with copyrighted works, companies are creating something that often will dramatically undermine the market for those works, and thus dramatically undermine the incentive for human beings to create things the old-fashioned way.”[1] This recognition of far-reaching harm to the “incentive” foundation for copyright addresses an even broader question than the term “market dilution” implies.

A Broader Fourth Factor Analysis

In the Copyright Office’s report, the section called Market Dilution offers guidance for a reading of fair use factor four that is broad enough to address the fact that GAI outputs can harm the overall market for the same kind of works used in training. Here, I would endorse a view that broadens the fourth factor consideration, which traditionally only looks to potential harm to the copyright owner’s exclusive right to exploit the works in suit.

As argued in other posts, and in my comments to the USCO, the courts should place considerable weight in deciding whether the use at issue furthers the purpose of copyright. My submitted comment the Office chose to highlight states: “[G]enerative AI—if it does not produce market substitutes—primarily represents potential harm to authors and future authorship. . . .[T]he consideration in the context of ‘training’ should be expansive and doctrinal—namely that a potential threat to ‘authorship’ cannot, by definition, ‘promote the progress’ of ‘authorship.’”

I believe that dichotomy, novel to GAI, is precisely what the courts must resolve in order to prevent the technology from swallowing copyright law itself—perhaps especially where a given AI product does not output unlawful copies of works used in training.  The one consideration that rescues GAI products as promoting the purpose of copyright is where they are demonstrably “tools” for creators, but this goes to my overarching argument that the courts likely cannot obtain sufficient facts to discover whether the “tool” is constructive, destructive, or agnostic with regard to copyright’s purpose.

An AI tool used for ideation, for example, may further the purpose of copyright by helping the creator discover a new path from idea to protectable expression, but it is impossible for the court to assume this is the general purpose of the “tool.” The same product might just as easily be used in ways that are destructive to authorship.

For example, the vast majority of material produced and distributed will not be copyrightable due to the human authorship requirement for copyright rights to attach. Additionally, we are already seeing a large volume of AI “slop” distributed on platforms like Amazon and Spotify, and it is well established that driving traffic to garbage content is a profitable model for those willing to engage in the practice. Although a specific bucket of AI “slop,” when considered in a traditional fourth factor analysis, may not directly compete with any specific works of authorship, the courts should continue to give weight to the undeniable fact that a market flooded with “slop” does not in any sense promote copyright’s purpose and is most likely destructive to that purpose.

This view does not ignore or dismiss the creative and cultural potential of GAI as a means of expression. Many popular videos online are made with (presumably) human-authored scripts combined with AI generated AV material. That the expressions in these works will generally be unprotectable is a valid basis on which to find that the purpose of the AI product does not promote copyright’s purpose. But further, the fact that many of the creators of these works are not incentivized by copyright rights—they are motivated by the opportunity to share ad revenue with the platforms—means that these works, regardless of their qualitative value, live outside the copyright system. As such, works incentivized and enabled by a model other than copyright cannot reasonably be held to further the purpose of copyright.

In my view, these considerations look beyond the typical factor four analysis, and even beyond the ordinary concept of market dilution, to ask a fundamental question:  Can a technology built by mass copyright infringement properly make fair use of works when the product’s ultimate purpose is either destructive or irrelevant to the purpose of copyright law? I don’t think so.

Is Denial of Licensing for AI Training a Market Harm?

A recent post by Copyright Alliance CEO Keith Kupferschmid states that both Judge Alsup in Bartz and Judge Chhabria in Kadrey erred by too hastily concluding that authors are not entitled to license fees for the use of their works in AI training. On that assumption, both judges held that under factor four, the claimants could not show market harm due to the defendants’ failure to license. Kupferschmid writes:

Both judges are incorrect because they ignore the important realities that a robust emerging market for licensing of AI training material already exists. Licensing markets under the fourth factor may only be circular and non-cognizable when the market being considered is a potential licensing market and the judge is trying to determine whether that potential market is too speculative. But when there is an actual market that already exists, the circularity argument has no place and both judges were incorrect to summarily claim the argument is circular. 

Notably, Judge Chhabria, in rejecting the existence of a licensing market for AI training, cites Tresona Multimedia v. Burbank High School, but in addition to Kupferschmid’s point that a licensing market already exists for AI training, I am not sure the court’s reference to Tresona even applies. Judge Chhabria quotes from the opinion thus: “In every fair use case, the ‘plaintiff suffers a loss of a potential market if that potential [market] is defined as the theoretical market for licensing’ the use at issue in the case.” However, the next part of the opinion reads as follows:

…a copyright holder cannot prevent others from entering fair use markets merely ‘by developing or licensing a market for parody, news reporting, educational, or other transformative uses of its own creative work.’ (citation omitted)

This appears to tie the question of whether a licensing market is merely “theoretical” to a finding of whether the purpose of the use is indeed transformative. And although both the Kadrey and Bartz courts found those uses to be transformative, I believe those holdings are so tautological (i.e., lacking proper analysis) as to be ripe for significant challenge. Notably, at issue in Tresona was an educational use of small amounts of musical works—a paradigmatic fair use consideration, and one that may be as far from the implications of generative AI as we might imagine. “Further, the Warhol decision calls into question whether fair use cases like Tresona are still good law,” Kupferschmidt said to me by email.

The interplay between factors one and four, while inherent to the fair use analysis, reveals a vexing circularity in the context of GAI where the court is persuaded to find that the remarkable nature of the technology is transformative solely because the use appears to serve a “different purpose” than the works used. In addition to not fully aligning with Warhol, Judge Chhabria’s well-founded instincts about authored works “competing” with voluminous GAI works under factor four cannot be comfortably harmonized with the finding that the AI product serves a different purpose under factor one.  Clearly, if the purpose of the input material is to entertain and inform and the purpose of the “competing” output material is to entertain and inform, these are not different purposes.

The important difference, then, is that the input works are human authored, about which copyright law speaks volumes, while the output works are machine made, about which copyright law says almost nothing. In general, GAI no more adds to the productivity of copyright than the sea steadily eroding stone into an aesthetically pleasing “natural sculpture.” The courts need not attempt to foresee whether GAI will be socially beneficial or harmful but only find that in context to copyright law there are far more reasons to disfavor fair use than to favor it.

[1] I would have preferred that Judge Chhabria had not used “old fashioned,” which may be improperly read to mean “outdated” in contrast to AI generated works.

Major Film Studios File Copyright Suit Against Midjourney

midjourney

“Midjourney is the quintessential copyright free-rider and a bottomless pit of plagiarism.”

Well, there it is. If you had been wondering whether and when the major studios would file a copyright infringement suit against a developer of generative AI (GAI), it finally happened on June 11. Disney and its subsidiaries, along with Universal Studios, filed a complaint against developer Midjourney alleging copyright infringement of many of the studios’ most famous and valuable intellectual properties. In the broader AI saga, the lawsuit is a big deal, though what it means for creators in general is hard to say. The studios imply that their complaint is a slam dunk, and it probably is. As the brief states:

This case is not a “close call” under well-settled copyright law. Midjourney set up a lucrative commercial service by making countless, unauthorized copies of Plaintiffs’ copyrighted works, and now sells subscriptions to consumers so that they can view and download copies and derivatives of Plaintiffs’ valuable copyrighted characters. That is textbook copyright infringement.

The 110-page complaint hardly expounds upon legal arguments and, instead, presents substantial evidence that Midjourney willfully violates the reproduction, derivative works, public display, and public distribution rights of the plaintiffs. Both as a matter of input (model training) and output of prompted materials, the studios compellingly show that their highly valuable works went into the system and that those same works come out of the system with simple prompting by users. Outputs also include expressive details like lighting and production design copied from the motion picture environments associated with famous characters.

For example, the user doesn’t just produce Darth Vader but can obtain a rendering of Vader on a Star Wars ship with lighting and production values that result in a highly detailed unlicensed derivative. The studios also allege that Midjourney itself publicly displays these outputs as a means of promoting its product’s capabilities. And finally, the studios anticipate that Midjourney will claim not to be the direct infringer and, therefore, allege that the developer is liable for secondary copyright infringement by facilitating mass infringement among its customers.

Aaron Moss, on his blog Copyright Lately, contends this case stands out among the roughly 40 active lawsuits against AI developers because the studios present so much compelling visual evidence of mass copying of protected works. While other GAI cases like Suno, Udio, and NY Times also present substantial evidence of infringing outputs, I think Moss is right that in the visual arts cases, plaintiffs rely more on the assumed infringement by means of model training more than they show obviously infringing outputs. In Disney et al., any ordinary observer can see that the characters and worlds produced are precise copies of iconic IP belonging to the studios.

Personally, I don’t see how Midjourney defends itself and, therefore, assume this case will be settled rather than fully litigated. Whatever comes of that settlement, motion picture studios generally have an interest in the development of GAI, which raises questions about independent creators and workers in the industry, as well as the future of filmmaking itself.

GAI and the Future of Filmmaking

Historically, the independent creator and the “line worker” in the industry both benefit from copyright enforcement actions of the institutional creator. For instance, when the studios go after pirate sites, the indie filmmaker benefits from a legal action she cannot afford to take, and the many crew professionals have their livelihoods protected. But with GAI, not only are the studios not seeking to shut down the developers, but they are presumably interested in the prospect of using the technology to produce motion pictures with fewer workers. This longstanding ambition of various film executives may not be attainable, but many professionals are certain that it will be attempted.

In conversations with friends in the industry, opinions vary, including those who find that GAI tools present intriguing opportunities for independent creators to produce new kinds of work at lower cost and greater speed. But at the same time, anxieties are high that GAI will mean job loss in every department of a typical production, including writers, directors, and actors.

There is no question that many motion picture jobs are threatened by GAI, but concerns that the future of filmmaking will be reduced to a few executives overseeing a roomful of programmers may be unwarranted. While GAI motion visuals are impressive and improving rapidly, it is also a shiny new toy that forecasts various cultural, financial, legal, and technological questions yet to be answered. And that’s just for film production.

My long-held view is that it was Star Wars (1977) that short-circuited the era known as the American New Wave in cinema because suddenly the prospect of the mega-franchise was much bigger than the movie itself. The end of the studio contract system resulted in greater creative independence, and a group of young directors, including George Lucas, produced what many consider a brief golden age of American motion pictures that were simultaneously box office hits, critical successes, and award winners.

When Star Wars demonstrated the potential of the film as franchise, the concurrent influx of MBA types into Hollywood amplified a new tension between film as art and film as product—i.e., the tension between filmmaker and film executive. Within that tug-o-war, it is only natural for the “suits” to want to produce as much product as they can with as little labor as possible—let alone expensive labor with opinions! Now, GAI theoretically presents that opportunity, though maybe not to the extent that many seem to either pessimistically or optimistically assume.

Usually, when the “suits” overreach with their analytics and try to predict what the market wants, the results are unimpressive. A theme I have repeated on this blog many times is that audiences want works that surprise them, not works that have been analyzed to death—and to produce fresh work takes artists, not algorithms. This rule, if it is a rule, implies a boundary that rejects the most stark predictions that major motion pictures will soon be made by three guys and a computer.

Potential Limits of GAI in Motion Pictures

Clearly, GAI output will continue to improve, and subtle renderings of naturalism will be attainable, which does imply that a whole motion picture with “human” characters can be produced without a camera or actor being involved. That this describes the future of all cinema seems unlikely, though it is notable that among the evidence presented in Disney et al., only one image is a depiction of a natural person (Mark Hamill as Skywalker), while every other infringing image is either a masked character or was originally made with pen and ink or computer illustration. Thus, the GAI’s ability to render these particular derivative works implies precisely the franchise material that could be produced without anyone building a set or rigging lights or pointing a camera at an actor. Still, there are limits.

For instance, the current Marvel franchise was primed with the first Iron Man (2008), the success of which owes a LOT to the performance by Robert Downey, Jr. This implies a caveat that films made without human artists can become what we might soon call the slop-flops of this dawning GAI era. Still, without a crystal ball or room to explore all the implications of eliminating one type of creative professional or another, a limiting factor for overuse of GAI may be copyright itself.

Because the human authorship requirement is, and will likely remain, a bedrock principle of copyright protection, GAI enables the production of a very large volume of unprotectable expression. Additionally, if two creators are using the same product, the likelihood of substantially similar, but independently created,[1] works may increase as well. In this light, creators, large and small, might want to be wary of overreliance on producing GAI material that may lack copyright protection. This concern would apply with greater force to newer characters, interpretations, and/or imagined worlds, if authorship in these works could be challenged on the basis that the expressions are the result of machine interpretation of the idea rather than human artists expressing the idea.

Personally, I would love to see the GAI genie stuffed back into its bottle because I believe that on balance the technology produces more social harms than benefits—and because the Techbros have zero credibility when it comes to ethical development or application of any of their products. But knowing that genie’s bottle has been shattered, I recognize how the technology can be used as a tool for new creative expression and am hopeful that lawsuits like this one at least push the application of GAI in that direction.

[1] Works that are independently created are, by definition, non-infringing even if they are substantial similar to other works.

Finding Fair Use for GAI Training is Highly Problematic

fair use

Although I have expressed aspects of these views in several posts over the past couple of years, I will try to consolidate my opinion as to why GAI training with protected creative works is a more problematic fair use consideration than many, even the courts, seem to believe. I acknowledge that even fellow copyright advocates will disagree with some of this analysis, but here it goes:

For the sake of narrowing the focus to the question of whether training generative AI (GAI) with protected works favors a fair use exception, the following assumes that the training requires unlicensed copying of protected expression. Further, even if the GAI maker limits the product’s capacity to output infringing copies, this does not alter the fact that considering fair use for this purpose is, at best, troubling and, at worst, so disturbing to case law that the AI developers are begging the courts to articulate doctrine out of whole cloth.

A GAI’s Purpose is Not Analogous to Past Fair Use Factor One Findings

The courts have largely rejected the overbroad opinion that making “something new” is a sufficient justification for unlicensed use of protected works. Thus, it is difficult to see where any court finds an authority to support the argument that making a “creator robot,” however revolutionary its developers proclaim it to be, is a transformative purpose under a factor one analysis.

Typically, a GAI’s purpose neither expresses “critical bearing” on the works used (AWF v. Warhol) nor provides information about the works to human readers (Authors Guild v. Google) nor fosters interoperability in computer devices (Google v. Oracle). Instead, a GAI’s most widely applied and widely promoted purpose is artificial “authorship” without authors—a purpose which forecasts myriad negative effects that may prove to dramatically overwhelm any benefits promised by the developers.

Naturally, certain GAIs (e.g., ChatGPT) can be used for various purposes, about which more below, but if the courts are distracted by the sheer novelty, scope, and hype around the “importance” of GAI and, therefore, presume transformativeness, they may be persuaded to articulate a rationale that would be tantamount to a blanket exception for GAI training. If the court adopts this carve-out in the context of fair use factor one, the result would be a reversal of its own reluctance to favor the broad “something new” argument for transformativeness so recently rejected in Warhol.

Notably, it is not unprecedented for the court to articulate rationales beyond the four-factor analysis. In the Google Books case, the court found that the search tool provides a “social benefit,” and a similar sentiment was articulated in Google v. Oracle regarding consumer benefit in advancing mobile products. Or looking back at the Betamax VCR case, the concept of “time shifting” the viewing schedule served the public interest by expanding flexibility in the consumption of copyrighted material that was lawfully obtained.

But if the courts look for a rationale beyond the case law (e.g., a clear social benefit of GAI), not only will they be making a wild guess, but any conclusion in favor of the developers will probably be wrong—perhaps dangerously so. While it is understandable that the courts may be reluctant to hobble technological development in principle, the available facts militate against disturbing fair use jurisprudence for the sake of nurturing GAI in general.

Put differently, if the courts are going to take a wait-and-see approach, there is ample evidence that GAIs already cause harm to individuals—from CSAM and defamation to cheating and psychological issues—to say nothing of the well-founded anxieties—social, political, economic, and environmental—associated with this multi-trillion-dollar gamble being played by the same people who unrepentantly accrued wealth and power from the darkest results of Web 2.0.

GAI as a Tool for Creators

To the extent that a given GAI product may be considered a tool for producing creative works, a fair use holding should at least find that the tool “promotes the progress” of authorship with respect to copyright’s purpose. But this is difficult because the same GAI in the hands of one skilled creator offers little insight about its ultimate purpose in the hands of 100-million unskilled users.

At the positive end of considering GAI’s purpose, my friend David Bolinsky, a medical illustrator and animator, recently made a series of 8 dozen topically and stylistically distinct ten second animations, introducing speakers and segment topics for a scientific conference, a daunting assignment. GAI collapsed well over a year of work (if using his standard 3D animation tools) into a matter of weeks. He was surprised at the breadth and depth of creative latitude GAI enabled. Further, he explained that although these presentations allowed more creativity than his typical discrete medical and scientific educational animations, an amateur lacking his experience still could not have used the same GAI tools to achieve the same results. Consequently, Bolinsky sees GAI as an opportunity to do more and different kinds of work and not as a threat to his creativity or livelihood.

In this example, the technology is socially beneficial and arguably “promoting the progress” of authorship, which may favor a finding that the tool is transformative. That said, due to the human authorship requirement, we are years away from guidance as to the degree of copyright protection on those animations; and if GAI tools are used to produce millions of works that have no “authors” as a matter of law, it is contrary to find that this “promotes progress” in regard to copyright’s purpose.

Further, the difficulty for the court in considering fair use is that Bolinsky and his colleagues who specialize in medical work are unique among professional creators, to say nothing of the many millions of non-creator customers that GAI developers need—because they are leveraged into the stratosphere—to make their products profitable. This scale implies an analysis reminiscent of Sony—i.e., a question of whether the purpose of the GAI is substantially beneficial or substantially harmful. But knowing that requires time travel.

If a court could see a few years into the future and find, for instance, that the GAI at issue will be used substantially for nonconsensual pornography, disinformation, and scams, it would presumably decline to find these purposes are social benefits that favor an expansive transformativeness finding. Instead, at the moment, the courts simply have no idea what the true “purposes” are of various GAIs, which is unprecedented in fair use jurisprudence. The VTR, Google Books, Android phones, et al. did not serve materially different purposes years after they were presented to the courts in their respective cases. By contrast, GAIs present an incomplete and dynamic set of facts; and in my view, this alone should militate against finding that factor one favors any of these products.

The Threat to Authorship Itself

As stated in other posts and in comments to the Copyright Office, one unique challenge of GAI is that it poses a potential threat to authorship (i.e., that it will shrink the number of creative workers), which is clearly destructive to the progress clause and copyright law. Although my own view is that a party who poses an existential threat to copyright’s purpose should not be allowed to invoke one of copyright law’s affirmative defenses, I recognize the difficulty in that opinion.

Under U.S. law, copyright protects authors indirectly by protecting certain exclusive rights to use their works. Consequently, there is little foundation for arguing generalized harm to authorship itself, despite the overwhelming recognition that diversity in authorship has benefitted the United States both culturally and economically for almost two centuries. In this context, GAI provokes the question as to whether U.S. policy might shift toward a “moral rights” approach akin to Europe, but that’s a discussion for a different post.

Instead, the general threat to authorship is considered, to an extent, under fair use factor four, which weighs the potential threat to the market value of the works used. The key difficulty, however, is that if the GAI does not output the song “Ordinary” but instead outputs music in the style of Alex Warren, then the output is not, strictly speaking, a threat to the market value of “Ordinary” itself. While proposals like the NO FAKES Act would prohibit unauthorized replication of Warren’s voice, copyright law does not clearly prevent a GAI that makes Warren-like music that could theoretically obviate the need for Warren himself.[1]

For now, several plaintiffs in the roughly 40 active lawsuits GAI developers have presented evidence of outputs that are substantially similar to the works used in training, and this should disfavor fair use for the GAI developers under factor four. More broadly, plaintiffs in these cases argue that licensing works for the purpose of AI training is itself a market opportunity exclusive to the copyright owner, and therefore, the failure to license constitutes market harm under factor four.

Some courts may be reluctant to agree with the lost licensing opportunity claim, but that reluctance is unfounded—even if a developer successfully prevents its product from outputting copies of works used in training. So long as one of the exclusive copyright rights is implicated (and here, it would be the reproduction right), then a requirement to license exists. Consequently, failure to license, especially at such an extraordinary scale for unprecedented commercial venture, is unquestionably market harm to the copyright owner.

Even where there may be a close call on factor four, because the GAI developer should lose on factor one, and because factors two and three decidedly favor creator plaintiffs, factor four should not reasonably control in many of these cases. Moreover, the courts should pay scant attention to the claim by developers that the cost of licensing is existentially prohibitive to the development of GAI. In addition to the fact that this plea is barely tolerable from parties wildly spending billions on high-risk ventures, any claim that a license is “too costly” for any venture is no defense under copyright law. The copyright owner sets the terms for the use of her work, and the prospective user can accept those terms or not before using the work. If that rule applies to the bootstrapping indie filmmaker, surely it applies to Microsoft, Meta, Google, et al.

Conclusion

Fair use is a mixed question of fact and law, and I maintain that what should be most fatal to the developers’ fair use defense is that, like the public, the courts have insufficient facts about the ultimate purpose of GAI products. Just as with Web 2.0 in the late 1990s, we are witnessing unfounded political sentiment to once again let Big Tech do what it wants, preaching to the public that this time, the technology really will “solve the world’s problems.”

Of course, there is no rational basis for that belief beyond the self-interest of the developers and the investors losing billions every year. If past is prologue, Congress would live to regret the folly of allowing AI to run amok, just as Members of both parties now rue the unconditioned immunity of Section 230. In the meantime, while licensing copyrighted works for GAI training will not address all, or most, of the potential hazards of artificial intelligence, the courts should decline to adopt strained fair use rationales in the name of assumed progress that may turn out to be a complete disaster.

[1] I believe there are cultural reasons that militate against this result, but those predictions do not influence the fair use consideration.