Category: Culture

Thoughts on the No AI FRAUD Act

The acronym stands for No Artificial Intelligence Fake Replicas and Unauthorized Duplication. Introduced as a discussion draft by Rep. Maria Salazar et al., the No AI FRAUD Act would create a novel form of intellectual property in direct response to the use of AI to “clone” a likeness. With parallels to right of publicity (ROP) law, combined with a copyright-like, transferable ownership of rights, the No FRAUD bill is sweeping as currently proposed, citing a range of conduct, from deepfakes to create and distribute nonconsensual intimate material, to cloning an actor or singer’s voice for commercial exploitation.

In short, the law would prohibit replication of anyone’s likeness without permission, and then, the purpose of the unlicensed replication would determine the nature of the harm and available remedies. Although the intent of this bill is well-founded in addressing certain harms to individuals like performing artists, the bill’s current scope, combining permission and intent, and seeking to remedy a broad range of potential harms, raises some difficulties.

Permission vs. Intent

As discussed on this blog, Cyber Civil Rights Initiative (CCRI) leaders, Danielle Citron and Mary Anne Franks, have advocated a permission-based, rather than an intent-based cause of action for the nonconsensual distribution of intimate material, commonly referred to as “revenge porn.”[1] The CCRI has worked hard to demonstrate that merely distributing this material without permission is criminal, regardless of the intent to cause harm, and this makes sense in response to the nature of the conduct. But advancement in AI replication presents a unique challenge to the principle that permission is universally the signal event triggering liability.

No question that the guy who shares intimate material of an ex, a girl at school, a work colleague, etc. should be held accountable solely on the basis that he lacked permission, and this is valid whether the visual material is real (i.e., photographic) or synthetic (i.e., produced with an AI). First Amendment defenses for this type of conduct have reasonably failed when various parties challenged the constitutionality of several of the “revenge porn” laws, now in force in 48 states. The permission principle in harassment-based complaints should not be disturbed by the No FRAUD Act, and Congress should likely avoid any temptation to combine the intent of this bill with current or developing federal prohibitions for “revenge porn.”

But the use of AI to replicate a likeness cannot so broadly be proscribed for all purposes. As the Motion Picture Association notes in its response to the bill, “… any legislation must protect the ability of the MPA’s members and other creators to use digital replicas in contexts that are fully protected by the First Amendment.” Notwithstanding contractual conflicts that may arise in the future among performers and producers, the MPA is right to note that AI cloning for expressive purposes that constitute protected speech should not be swept into the scope of legislation like the No FRAUD Act.

The example I often use with friends and colleagues is the movie or TV series that casts a public figure (let’s call him Donald Trump) in a light he might not appreciate. Expressive portrayals—factual, dramatic, or sardonic—of public figures are paradigmatic forms of protected speech, and this principle should not be altered by vesting new IP rights in persons, premised solely on the use of AI models to achieve the same expressive results historically created with old-school “movie magic.” In other words, Trump should no more be empowered to enjoin the use of his AI likeness to comment upon his role in society than he would have been allowed to stop Saturday Night Live from producing the sketches featuring Alec Baldwin.

Vesting new “likeness IP” rights in all persons is a reasonable response to the potential harms—both financial and reputational—that may be caused to millions of creative professionals and ordinary citizens. But these goals must allow for expressive uses of AI replication, adhering to longstanding contours protecting the speech right and controlling limits like libel and defamation.

In another example, imagine a documentary about the events of January 6th that includes reenactments based on witness testimony describing the actions of the former president during the attack on the Capitol. The documentary producer’s legal responsibility to balance faithful reportage with reasonable expressive license should not be altered solely on the basis that the film may use generated AI likenesses of Trump, Meadows, Hutchinson, Ivanka, et al. rather than actors to produce the same scene.

With a documentary film, one can imagine a legal requirement to inform the viewer that what they are seeing is an AI-generated reenactment (rather than, say, someone’s cellphone recording), but no such requirement should apply to a non-documentary audiovisual work. In either case, misinformation is already thriving in a dangerously blurry space between fact and fiction and a decline in media literacy fostered by the ability of any individual to distribute any fragment of material without context on a public platform. In other words, the documentarian can do her job right, but she cannot stop every potential bad actor from taking a segment of that reenactment and publishing it in a manner that changes its context and feeds a false narrative. (Thank you to all those who celebrated “remix culture” as a rejection of copyright law.)

AI Generated Likeness and the Misinformation Problem

Regarding the documentary example, the preamble of the No FRAUD working draft cites the use of unauthorized likenesses for the purpose of disinforming the public about matters of a factual or newsworthy nature. And while this is indeed a problem that AI tools will be used to exacerbate, it is a challenge that should be addressed separately from the intent and sweep of the No FRAUD proposal. Congress must recognize that the capacity to cause widespread, societal harm through disinformation by means of AI likeness replication is too hazardous and too rampant to remedy on a case-by-case, civil-liability basis. And that’s even if the producer of the fake is operating within the reach of U.S. law rather than, say, China or Russia.

Further, there is a legal tension created by comparing and contrasting the entertainment satirist with the news provocateur who trades in misinformation, as we see in the claims of slander against Tucker Carlson of FOX News in 2020. Arguing that “no reasonable person” would truly believe everything Carlson says, Fox’s attorneys successfully defended the network against any cause of action, and while this may be a reasonable finding based on the facts presented, it is one of many examples in which the lines separating opinion, criticism, satire, and information have been blurred beyond relevance vis-à-vis public perception. Now add the ability to cheaply recreate anyone’s likeness with sophisticated AI, and how far can a “news” organization push the line under the same protections that apply to the satirical filmmaker or The Daily Show?

Of course, my references here to Trump and Carlson allude to a much bigger, underlying problem—namely that Congress is not going to effectively address the use of AI likeness for misinformation unless Members on both sides can agree to mutually define fact and fiction. Not to say that Dems never cling to narratives built on some rather shaky foundations, only that it’s hard to compete with the existential lies of whatever the hell the GOP has become in the thrall of Trumpism. That and no American political figure has ever proven to be so thin-skinned in response to criticism.

For the moment, my own view is that a bill like No FRAUD should be narrowly tailored to vest new “likeness IP” in persons to proscribe compelled speech and commercial exploitation that meets standards akin to unfair competition. Further, because such uses require a court to weigh the intent of likeness replication, this new right should not preempt or alter anti- “revenge porn” legislation, where lack of permission must remain the sole cause of action. While I see the potential of this bill to protect various artists and non-artists with novel rights against novel harms, difficulties like those addressed in this post must help define the contours of those new rights.

[1] “Revenge porn” is a problematic term because it implies intent to harm, which is anathema to the principle that lack of consent is the cause of action.

Image by: meyerandmeyer

“Fair Use” is Not a Great Business Plan

Lately, we’ve seen several headlines and comments from tech giants say that AI ventures simply cannot succeed if they are forced to contend with the copyrights in the billions of works they have scraped for the purpose of machine learning (ML). When these headlines are paired with the rampant assertions that ML is inherently fair use—a subject addressed in last Wednesday’s Senate Judiciary Committee (SJC) hearing on AI and journalism—one has to wonder about the business decisions being made before generative AI exploded last year.

In many posts on this blog, including at least a few written during “Fair Use Week,” I have repeated the caveat that “fair use” is not a magic phrase that makes infringement claims disappear. Usually, that advice is directed at small and independent users of works, suggesting they not listen to Big Tech and its network of academics and activists, who will not be on the hook for the small guy’s copyright infringement. I always assumed the big guys knew better, that they were merely chanting the “fair use” mantra as a rhetorical device in the blogosphere to promote the anti-copyright agenda. But maybe they don’t know better.

If I were an AI investor asking about potential liability, and the founders told me, “Don’t worry, what we’re doing is fair use,” my immediate response would be to ask whether there is sufficient funding for major litigation, to say nothing of predicting the outcome of that litigation. Because simply put, the party who conjures the term “fair use” has effectively assumed that a potential liability for copyright infringement exists. And if that assumption is a bad business decision, then that’s the founders’ problem, not a flaw in copyright law.

No matter what the critics say, or how hard certain academics try to alter its meaning, the courts are clear that fair use is an affirmative defense to a claim of copyright infringement, which means that building a business venture on an assumption of fair use is tantamount to assuming that lawsuits are coming. And if it’s a multi-billion-dollar venture that potentially infringes millions of works owned by major corporations, then the lawsuits are going to be big—perhaps even existential.

Do Not Expect Congress to Change Fair Use in Any Direction

Notably, as reported in Wired, Conde Nast CEO Roger Lynch stated at one point during questioning by the SJC last week, “If Congress could clarify that the use of our content, or other publisher content, for the training and output of AI models is not fair use, then the free market will take care of the rest,” to which Sen. Hawley replied that this seems reasonable. But I wonder about this exchange. While it is encouraging to find the senators more sympathetic with the news organizations than with the AI developers, I doubt (and would not even hope) that Congress is going to amend the law to explicitly state that ML is categorically never fair use.

Fair use comprises a history of judge-made law that was codified into statute as Section 107 of the 1976 revision of the U.S. Copyright Act. But the statute does not draw bright lines stating that X is always fair use and Y is never fair use, and for good reason. Because justice for all parties is best served by a court weighing the specific facts of a specific use of a specific work, or body of works. Hence, an attorney will tell you that fair use is a “fact intensive” consideration.

If Congress were to explicitly declare, for instance, that ML can never be fair use, this would be a significant departure from doctrine, and one that is preemptively unjust to the potential AI developer with a fact pattern that would favor a finding of fair use. As much as I find the major generative AI companies to be some combination of arrogant and/or useless, and as much as I scorn their generalizations to-date about fair use, it would be wrong to endorse legislative revision of the fair use doctrine as a sound response.

In fact, if the court were to find fair use for ML in New York Times v. Open AI (and I doubt it will), and Congress sought to remedy that outcome, it would still not make sense to amend Section 107. If anything, news organizations and other copyright owners would likely seek a new section of the Copyright Act tailored to the nature of the new form of harm, which Big Tech would then blindly oppose with every available resource. For instance, it is possible that the Times would not currently be suing Open AI if the tech industry had not opposed the Journalism Competition and Preservation Act (JCPA), which would have temporarily exempted news organizations from antitrust barriers to collective bargaining for licensing their content.

Regardless, no party should be asking Congress to “clarify fair use” in response to AI. If the AI founders and investors made a bad bet on an ultimate finding of fair use, that’s tough noogies for them. But neither should content creators want Congress to open that particular can of worms and disturb the fair use case law. Of course, where Congress should intervene is to address harms caused by AI where no law currently applies. On that subject, the next post discusses the recently proposed No AI FRAUD Act.

Phot source by areporter.

Things We Don’t Need: Generative AI

When I was planning to start The Illusion of More, I contemplated a category of posts under the heading We Don’t Need This. Although abandoned, I thought it might be an editorial framework for articles about innovations that really aren’t innovative, and the low-tech invention that originally inspired the idea was the kiddie-car/shopping-cart hybrid. In case you haven’t had the pleasure, this vehicle enables a small child to “drive” a plastic car attached to the basket one pushes through the supermarket. As the parent of a small child (at the time IOM was launched), I found this innovation was a terrible idea—one that demanded use the moment the child laid eyes upon it, but which mostly offered poor maneuverability through the aisles and unnecessary geometric struggle at check-out.

There is, of course, nothing connecting the kiddie-car/shopping-cart to generative AI except, in my view, the fact that we don’t need either one. Or at least, we don’t need most of what generative AI appears to be doing, and this is perhaps the most maddening aspect of the most prominent generative AI tools making the headlines—that they serve no purpose and, if we’re getting all IP about it, promote no progress. I’ve said it, and I’ll keep saying it:  we do not need computers to make artistic works.

This month, the Federal Trade Commission (FTC) issued a report describing its early findings about AI’s potential harms which may be addressable under the agency’s purview. Charged with enforcing prohibitions against unfair, non-competitive business practices and protecting consumers, the FTC hosted a roundtable discussion with members of the creative community to hear their concerns about both the development and public deployment of generative AIs. As the report states:

Various competition and consumer protection concerns may arise when AI is deployed in the creative professions. Conduct–such as training an AI tool on protected expression without the creator’s consent or selling output generated from such an AI tool, including by mimicking the creator’s writing style, vocal or instrumental performance, or likeness—may constitute an unfair method of competition or an unfair or deceptive practice.

In response to the report—specifically to the passage quoted above—three well-known copyright critics, Pamela Samuelson, Matthew Sag, and Christopher Sprigman (SS&S) criticized the FTC “both for its opacity and for the ways in which it may be interpreted (or misinterpreted) to chill innovation and restrict competition in the markets for AI technologies.” Before responding to that allegation, I must indulge in a little gallows humor and mention that the economic and global-security leader of the free world is in danger of shredding its Constitution, going full-tilt authoritarian, and spiraling into a deathroll of ignorance and cruelty. And yet, we’re going to talk about “chilling innovation” in generative AI as if it’s a matter of urgency. The world is in crisis, and billions have been invested to see who can do the best job getting a computer to write a poem or make a picture? Talk about whimpers instead of bangs.

There are two reasons that sentiment is not raw Ludditism. The first is that it does not dismiss all AI development in the creative industry as useless; and the second is that the “copyright stifles innovation” bullet point is a generalization that should never be uttered again—especially in light of its direct role in fostering the above-mentioned prospect of democracy’s collapse. We’ve heard all this before—specifically from SS&S and their colleagues in academia and the “digital rights” organizations. We’ve been told that copyright stifles the free and open internet, access to information, and the speech right.

But in addition to the fact that the premise itself was false, the grand social media experiment in the “democratization of everything” must be recognized as an abysmal failure, and its cheerleaders should muster the humility to stifle their tiresome and dangerous refrains in context to AI. Social media companies and their friends in academia—and here, I must include President Obama’s Google-friendly administration—share considerable blame for the heedless, tech-enabled populism that has fostered so many social hazards, including a literal seditionist now leading one of America’s two political parties.

Notably, the FTC report does not mention copyright very much, and in fact, many of the creative professionals who participated in the discussions acknowledged that because they are not copyright owners (e.g., voice actors and screenwriters for hire were among the representatives), they do not have rights currently protecting them against generative AI resulting in the kind of unfair outcomes, which the FTC is charged with mitigating. It would take too long a post to respond to all the critiques presented by SS&S, but I wanted to focus on this statement:

We are concerned especially about the suggestion in the FTC’s Comments that AI training might be a Section 5 violation where it “diminishes the value of [a creator’s] existing or future works.” A hallmark of competition is that it diminishes the returns that producers are likely to garner relative to a less competitive marketplace. This is just as likely to be true in markets for creative goods, such as novels and paintings, as it is in markets for ordinary tangible goods like automobiles and groceries. AI agents that produce outputs that are not substantially similar to any work on which the AI agent was trained, and are thus not infringing on any particular copyright owner’s rights, are lawful competition for the works on which they are trained.  Surely the FTC does not plan to have Section 5 displace the judgments of copyright law on what is and what is not lawful competition?

To summarize, that paragraph declares that it does not matter if generative AI displaces human authors, that in fact, it is a threshold we should be eager to cross. Notwithstanding the fact that two of the high-profile lawsuits present compelling evidence of substantially similar outputs,[1] the more concerning implication of that paragraph is that SS&S endorse the inevitability that generative AI will devalue human creators and/or eliminate them altogether. Moreover, calling this eventuality a form of “competition” reveals an unsettling perspective consistent with every anti-copyright paper I have ever read—namely, that the production of creative works is no different than the production of any other product or service.

I’ve said many times that copyright critics don’t understand artists, and here, the inapt word competition demonstrates why this axiom endures. For instance, publishers are in competition with one another to an extent, but authors are not—at least not in the sense that the concept applies in other industries—least of all Big Tech. No novelist, for instance, wants to hold the undivided and exclusive attention of all readers the way Meta wants eyeballs never to stray for long from its platforms. Artists thrive in a diverse market of other artists, consumers benefit as a result, and copyright is an engine of that diversity, not a barrier to it. Artists may feel competitive or jealous at times, or even behave in a competitive manner (because they’re human), but the reality is that they need one another to exist at a scale that is not comparable to other “businesses.” True to form, copyright critics like to cite the interdependence of authors to highlight copyright’s limitations but then ignore the same principle in support of tech giants swallowing all creative enterprise whole.

The primary concern expressed by SS&S appears to be that the FTC alleges that AI training with copyrighted works is an act of infringement. Unsurprisingly, this same trio submitted comments to the Copyright Office arguing that AI training with protected works is fair use, but as that very question is already presented in several court cases, I assume SS&S are primarily concerned with optics here. The trio states, “The FTC has no authority to determine what is and what is not copyright infringement, or what is or is not fair use. Under governing law, that is a judicial function.”

Exactly. And the question is now before the courts. So, what’s the problem? That the FTC should not even raise the issue? According to tweets by Samuelson and Sprigman, they argue that the FTC’s report is one-sided, that it is too creator-focused and does not account for the testimony or opinions of the technology companies developing AI. But while I certainly agree that multistakeholder hearings etc. are the proper approach to developing new policy, it is impossible to tolerate a complaint about lack of balance coming from the anti-copyright crowd at all, and from these individuals in particular. For instance, readers may not remember the American Law Institute Restatement of Copyright, initiated by Samuelson and led by Sprigman, but critics of the project—some of the most prominent names in copyright scholarship—specifically cite the opacity of the restatement process and deafness of its managers to the concerns and recommendations of their colleagues.

More broadly, it must be said that if, indeed, the FTC lately gave more attention to the creators than they did to the tech companies, then this was a long overdue anomaly. Between at least the mid-late 1990s and 2016, the tech companies were treated with kid gloves, handed the keys to Washington, and feted like the economic and democratic engines they claimed to be. Since 2016, sentiment began to swing in the other direction, as many Americans began to see how disinformation plus data manipulation can become a wrecking ball for a whole society.

If Big Tech lost the previously undeserved benefit of the doubt, good. AI has the potential to exacerbate many of the same Web 2.0 harms at unprecedented speed and scale, and if the FTC, the USCO, the courts, or Congress look askance at the developers, then it is a mistrust well earned. And again, at least with regard to generative AI designed to make creative works, none of the parties empowered to write policy in this area should forget the bottom line:  that when it comes to producing creative work, we truly do not need generative AI.

[1] Concord et al. v. Anthropic and NYT v. Open AI, et al

SEE ALSO: The Washington Post reported this month that Big Tech continues to significantly fund and influence academia in these policy areas.

Photo by: Jollier