Tag: Featured

Before Generative AI, Big Tech Taught Artists to Abdicate Copyright Rights

One of the more challenging aspects of copyright advocacy is the fact that many artists and creators are conflicted about enforcing their own rights, and from observation, the disconnect is ideological. For the last 30 years, copyright skepticism has been woven into political narratives rooted in criticism of corporations and the excesses of capitalism—popular themes among the political left, which encompasses most artists. Now that generative AI developers are turning creative works into “pink slime,” and artists are suddenly more interested in their rights, it might help to recognize that the industry deploying AI is the same one that taught creators to advocate against copyright in the first place.

The year 2011 was an extraordinary time to jump into the fray. It was immediately apparent that allegations of “copyright maximalism” were deeply intertwined with a sincere and animated belief that the internet would foster a new and potent form of direct democracy to confront a litany of injustices. Copyright enforcement was characterized as a barrier to that promise, and so, the Stop SOPA campaign (to kill anti-piracy legislation) became part of a larger, frenetic collage that included OWS protests, European pirate parties, Anonymous, Wikileaks, etc., all feeding an atmosphere of revolution that corresponded with headlines and memes claiming that “Hollywood” wanted to use copyright to break the internet and stifle speech.

But Big Tech’s promise to democratize everything was a Trojan Horse from which the AI bots have now emerged to ransack the village. Not only did promoters of the “free flow of information” elide the fact that their platforms were as likely to produce the January 6th insurrection as the “Pussy Hat” March, but the allegation that copyright was a barrier to information flow had nothing to do with liberating our speech and everything to do with limiting their liability.

Every time members of the creative community echoed the anti-copyright messages pumped out by Fight for the Future, the EFF, Public Knowledge, or the platforms themselves, what was really being advocated was a lack of accountability for online service providers. I never fully understood how one of the most exploitative industries in history managed to turn anti-corporatist sentiment to its advantage, but I assumed it was the gestalt of the internet. The illusion that social platforms belong to the people was a charade that enabled Google, Facebook, et al. to camouflage their interests as our rights.

That theme has aged about as well as the tobacco industry’s efforts to sell freedom to get smokers to ignore cancer, but it’s been almost two years since Big Tech’s “Big Tobacco moment,” and little has changed. Neither in Congress nor the courts have online service providers been held accountable for much of anything—and that’s with laws on the books. When we consider that, for almost three decades, the major platforms have acted in bad faith with their end of the DMCA bargain, and the courts have interpreted Section 230 as an unlimited liability shield, it is hard to feel hopeful about a legal framework for accountability for harms resulting from AI.

In fact, certain AI tools (e.g., LLMs) may imply a wider “neutral” buffer between potentially harmed parties and potentially liable parties. “Knowledge” and “intent” are key factors in establishing liability, and we have watched Big Tech play shell game with the concept of what they can “know” or “intentionally” control about activity on their platforms. AI tools could take these shenanigans to the next level, enabling new forms of harm with an even weaker nexus linking the machines to the people who design and operate them.

In the copyright world, platform operators have consistently circumvented their obligations under the DMCA with shrugging statements like We can’t police the internet, alluding to staggering volume while conjuring an association with authoritarianism. Now, the circumstances are different. It is a near certainty that every creative work made has been, or will be, ingested into one or more AI training models, and unless the courts find this to be an act of mass piracy and order disgorgement of the datasets, creators may have to accept that their work is being turned into pink slime.

While it is encouraging to see artists take a more active interest in copyright rights as a response to AI, it is also a bittersweet transition in light of all that has happened so far. Whatever comes next, I hope the creative community will recognize that copyright rights are the closest thing to labor rights the independent artist has. And these rights should not be weakened or abandoned for the sake of more billionaires making false promises about democracy and free speech.

EFF to Honor Scientific Paper Pirate Sci-Hub

The Electronic Frontier Foundation (EFF) announced that among the 2023 recipients of the EFF Award (formerly the Pioneer Award), it will honor Sci-Hub founder Alexandra Asanova Elbakyan this September. The Russian-based Sci-Hub is an enterprise-scale pirate site specifically built to host scientific papers about which the EFF states:

Through Sci-Hub, Elbakyan has strived to shatter academic publishing’s monopoly-like mechanisms in which publishers charge high prices even though authors of articles in academic journals receive no payment. She has been targeted by many lawsuits and government actions, and Sci-Hub is blocked in some countries, yet she still stands tall for the idea that restricting access to information and knowledge violates human rights. 

In addition to the EFF’s usual flare for the dramatic, the organization continues to flaunt its unwavering hostility toward all copyright rights as a foundational raison d’etre. Note the word shatter in that quote above. To the ideologues at EFF et al., Sci-Hub is not merely a response to subscription fees but should be revered for its assault on the very idea that journal publishers ought to exist in the first place. In fact, the timing of this award is telling in that it comes two years after a landmark, open access agreement was negotiated by the University of California (UC) with publishing giant Elsevier.

Although subscription cost has often been a point of contention for many in the academic community, even contributing authors, the UC has been negotiating open access agreements with academic publishers on behalf of colleagues at smaller institutions with more limited resources. “We refer to these agreements as transformative open access agreements because they convert subscription payments into payments for open access publishing (with reading provided for free). It is a new approach we helped develop with other leading institutions a few years ago, in large part through the OA2020 initiative,” says librarian and economics professor Jeffrey MacKie-Mason of UC Berkeley.

Settled in March of 2021, the Elsevier deal was the ninth open access agreement the UC negotiated with academic publishers, which suggests that many authors of scientific research papers do not view a pirate site like Sci-Hub as a viable “solution” to whatever criticisms they have of the commercial publishers. While I do not presume to have expertise about the complex world of scientific journal publishing, a 2018 article by industry consultant Kent Andersen lists “102 things journal publishers do,” and it’s a lot more than hosting PDFs on a website. Notably, even among some of the critical comments on that article, which appear to be written by academic authors, there is no mention of Sci-Hub in particular, or piracy in general, as obviating the role played by journal publishers in the industry.

Although it is true (as the EFF emphasizes) that the authors of these papers are not paid for their writing, the academic publisher is more like a venue operator than a trade book publisher—a venue operator that, at best, serves as a neutral party to control quality. These journals invest substantial resources to review millions of submissions, prepare documents, maintain databases, check for plagiarism, organize peer review, etc. And although these investments need to be recovered profitably for the publisher to exist, the UC deals indicate that there is room for negotiation, which leaves EFF’s panegyric to Sci-Hub sounding as hollow as it is untimely.

Speaking of timing, with academics, policymakers, journalists, artists, and just about everyone else wondering how badly generative AI might exacerbate the misinformation problem, could there be a worse moment to award a pirate of scientific journals? How is Sci-Hub not the natural place for a generative AI developer to harvest scientific writing to train an algorithm to, perhaps, “write” papers without scientists? Notably, in the class-action case Tremblay et al. v. OpenAI, the plaintiffs allege that the defendant obtained literary works for machine learning (ML) from “shadow libraries,” (i.e., pirate sites like Z-Library). So, by the same logic, Sci-Hub would seem to be a natural source where an AI developer can scrape scientific papers.

I am neither motivated nor qualified to critique the entire scientific publishing ecosystem, let alone to dispute complaints among some academics about cost, et al. I would grant Elbakyan the benefit of the doubt that her intent is at least distinguishable from the typical entertainment media pirate whose only motive is financial, and I recognize that scientists and academics in various regions have access Sci-Hub for what may be difficult to obtain information. Nevertheless, the worn out view that piracy is a solution to imperfections in a given system is, at best, narrowly focused on distribution while ignoring the means and motives for production.

Not unlike Peter Sunde’s mourning the lost Marxist idealism he saw in the The Pirate Bay, Elbakyan echoed this same naivete when she told the Washington Post in 2016, “On my website, any person can read as many papers as they want for free, and sending donations is their free will. Why Elsevier cannot work like this, I wonder?” Indeed. The alleged “white hat” pirate never seems to grasp that there is always a cost to production and that, whatever system covers that cost, it won’t be a damn tip jar, and it will rely on copyright in some form. As the court stated in 2015 when Elsevier successfully sued Sci-Hub for infringement, “Elbakyan’s solution to the problems she identifies, simply making copyrighted content available for free via a foreign website, disserves the public interest.”

As for the EFF Award, it’s worth asking what Sci Hub’s agenda is in 2023, if indeed traditional publishers are adopting open access agreements and academics are still willing to work with those publishers? Is it truly Elbakyan’s mission to “shatter” the entire scientific publishing ecosystem and, with it, essential processes like peer review? Or is that just the EFF’s hyperbole? Presumably, it’s both. And by honoring Sci-Hub, the EFF proves once again that it will promote any anti-copyright agenda—legal or otherwise—with the zeal of a conspiracy theorist watching “chemtrails” fill the sky.

AI Machine Learning:  Remedies Other Than Copyright Law?

In my last post, I discussed some of the allegations that “machine learning” (ML) with the use of copyrighted works constitutes mass infringement. Citing the class action lawsuits Andersen and Tremblay, I predicted that if the courts do not find that ML unavoidably violates the reproduction right (§106(1)), copyright law may not offer much relief to the creators of the works used for AI development. As of last week, it remains to be seen whether we’ll get to that question after Judge Orrick of the Northern District of California stated that he is tentatively prepared to dismiss the suit with leave to amend the complaint. The judge did indicate that a claim of direct infringement could survive, but we’ll have to see what comes of an amended complaint.

As mentioned in the last post, if the court does not find a valid claim of copyright infringement, the other allegations will likely fail as a result. Nevertheless, though the state allegations may be moot in the class cases filed thus far, I had intended in this post to look at whether any non-copyright remedies present much hope for creators. For instance, the Andersen complaint alleges violations of statutory and common law rights of publicity and violations of statutory unfair practice prohibitions in the State of California.

Right of Publicity and Works “in the style of…”

One of the most concerning aspects of generative AI is that it allows a user to prompt the system to make a work “in the style of [named artist].” Karla Ortiz, in her testimony to the Senate Judiciary Committee on July 12, stated, “[Artist] Greg Rutkowski, had his name used as a prompt between Midjourney, Stability AI and the porn generator Unstable Diffusion, about 400,000 times as of December 2022. (And these are on the lower side of estimates).” This is a deeply personal assault on the identity, work, and potential livelihood of an artist who has spent years mastering his craft and developing that distinctive style which can now be mimicked by a computer. But as a matter of doctrine, copyright does not protect style. So, can state laws like the right of publicity (ROP) offer any relief?

Only half the states in the U.S. have statutory rights of publicity, though most states recognize a common law ROP, which may prove more expansive in a litigation. The California statute, considered one of the strongest, prohibits the use, without consent, of a person’s likeness, name, voice, or signature for commercial purposes. In particular, advertising a product, service, or viewpoint so that a representation of the individual implies that person’s endorsement, is a paradigmatic violation of ROP and may infringe the speech right of the individual. But does prompting a generative AI to create an image “in the style of [artist]” implicate the artist’s ROP? Maybe and sometimes.

Because a user can prompt the production of a visual work “in the style of Greg Rutkowski,” one obvious implication is that there will be hundreds or thousands of “Rutkowskis” in the world which the artist did not create. If any of those AI-generated works are substantially similar to an existing work he did create, then he may have claims of copyright infringement—and potentially too many to contemplate addressing. But what about the works that do not look substantially similar to anything in the artist’s portfolio but to the observer, do look like “new Rutkowskis”?

In the fine-art trade, the duty to validate provenance and authenticity (i.e., not commit forgery) should offer some protection for those artists who sell their work in galleries etc. But in the commercial market, if a new vodka brand wants images in the style of, say, Molly Crabapple for its ad campaign but doesn’t want to hire Molly for the job, they could use generative AI to make something in her style. No question this implies that artists will lose gigs, but whether ROP offers a remedy to Crabapple herself in this hypothetical is questionable.

To begin, artwork in the style of the artist is not a “likeness.” Thus, Crabapple would have to prove that observers seeing the ads would perceive the images as her work and that the images, therefore, result in an unlicensed endorsement in violation of ROP. That can be a high bar to reach, let alone repeat in what could amount to multiple complaints by just one artist—and potentially in multiple states! Although a violation of ROP can stand alone without an underlying violation of some other law, it is a fact-intensive, case-by-case consideration and, therefore, hard to imagine how it can support allegations of harm to a plaintiff class as alleged in Andersen.

Moreover, some states only recognize celebrity ROP and not average citizen ROP. So, in the case of the visual artist, what is the threshold where he or she is famous enough to be considered a celebrity? Crabapple, Rutkowski, et al. are very well known in the art world, but they’re not movie-star well known to the general public. So, what constitutes “celebrity” in this context? We don’t know. The specific problems caused by generative AI are brand new.

New Federal ROP Law?

In testimony before the SJC along with Karla Ortiz, General Counsel for Universal Music Group Jeffrey Harleston broached the subject of adopting a federal right of publicity, and the idea was at least entertained by some of the senators. A federal ROP could theoretically address some of the new harms to artists caused by generative AI. Not only would a federal statute provide a uniform, national framework, but the new law would be written with an understanding of AI and its potential harms as a foundation of legislative intent. Further, it was raised in committee that ROP should apply to everybody and not just celebrities.

The Motion Picture Association (MPA) filed comments in response to this discussion, and these were focused largely on the fact that, historically, ROP has applied to commercial/promotional uses, but not to expressive ones. The MPA is right to point to some tricky considerations that would need to shape a new federal ROP in order to strike a balance between disenfranchising creators or performers through AI-generated replicas while allowing use of the technology to create expressions that are protected by the First Amendment.

In fact, in my book, I allude to a hypothetical future biopic about Carrie Fisher that (with the family’s permission, of course) might dramatize scenes using AI replicas. Whether this use of the technology would be an engaging choice in lieu of casting an actress play young Carrie is a question of aesthetics and culture, but not a question that can or should be addressed as a matter of law. Suffice to say, the contours of a prospective new federal ROP are complex enough to be subject of future posts.

Unfair Competition

Unlike an ROP complaint, unfair competition does not stand alone as an allegation. In general, these laws bar businesses from gaining unfair advantage by engaging in some form of prohibited conduct. In the Andersen et al. class action suits, the underlying conduct is alleged to be copyright infringement, which allegedly makes the AI developers unfair competitors with the plaintiff class of artists. This state allegation would seem to have merit if the court finds the developers liable for violation of §106(1) of the Copyright Act, and unlike ROP, I can see it surviving as a complaint for a whole class—i.e., as unfair competition against all artists. That would be encouraging. But if, for instance, the court finds that not all the named plaintiffs have standing (i.e., do not have registered works in suit), it’s hard to say what this does to the unfair competition complaint as argued.

What About Trademark?

It is tempting to wonder whether certain creators can find protection in trademark law. In addition to the cost of registering and maintaining a trademark, only certain artists would be able to make effective use of this form of intellectual property. In this instance, trademark only protects use of the artist’s name in commerce, and since it is already illegal to trade in forgeries, registering one’s name as a trademark may be redundant and little protection against the use of AI to produce “in the style of” works.

Relatedly, the Federal Trade Commission (FTC) may have a role to play to protect consumers against fraud stemming from the uses of generative AI. As to the FTC stepping in, presumably they could respond to or seek prophylactically to protect consumers from forgery at scale. Not unlike the rampant proliferation of counterfeit products sold via eCommerce sites, generative AI certainly presents the opportunity for some party to start generating mass forgeries of popular artists and selling those in the millions. As such, measures to restrict the use of artists’ names in generative AI may belong in the FTC’s wheelhouse.

In both this post and the last, my intent is not to advocate on behalf of the AI developers. Far from it. Instead, I am trying to kick the tires of existing law to ask whether the law is sufficient to the task of protecting authors of creative works. Because, overall, I’m not sure it is, though it is also essential to note that every type of work has different implications (i.e., voice actors’ rights are more likely to sound in ROP than visual artists’ rights).

One thing is certain. Generative AI is not comparable to the printing press, camera, phonograph, or any more recent changes to production and distribution enabled by digital technology. Debate about AI must be sequestered from discussions about technologies of the past because few, if any, of those revolutions are instructive to the moment. There is no doubt that AI implies new regulation in medicine, finance, IT, security, and just about everywhere else it will invade; and there is no reason why Congress cannot adopt the same posture in order to protect America’s creative culture and economy.

Image source by: idaakerblom