Tag: artificial intelligence

Thaler Suit Against Copyright Office Asks for Analog Reading of Statute

Last February, the U.S. Copyright Office rejected the registration application filed by Stephen Thaler for a visual work entitled “A Recent Entrance to Paradise.” Thaler averred that the image was generated by an AI he designed called “Creativity Machine,” and on that basis, the Office affirmed the longstanding doctrine that copyright rights only attach to works of human authorship. In a series of cross motions, Thaler now argues that “non-humans have been authors under the statute for more than a hundred years.”

Broadly, Thaler asks the court for statutory interpretations based on proving a negative—namely that the Copyright Act does not explicitly state that an author must be human, or that an author cannot be non-human. His brief is peppered with examples in which the law does not expressly prohibit a non-human from having an “idea” or making creative “choices.” And he’s right. Nothing in the law makes such statements, but why would it? It is only very recently that law—and not just copyright law—must confront issues presented by sophisticated machines capable of performing functions ordinarily reserved for humans.

Prior to the present moment, it would have been absurd to affirmatively state that works of creativity or invention must be made by human beings. And it is frankly still absurd. Vehicular law does not explicitly state that the rules apply solely to human drivers (though we may have to address this one); marital law does not explicitly state that the parties must be human; and most relevant to this discussion, employment law does not explicitly state that non-discrimination and other rules of fairness apply only to human persons. Employment law is informative because Thaler’s primary claim of copyright in the visual work rests on the Work Made for Hire (WMFH) doctrine on the basis that “Creativity Machine” is the legal equivalent of an employee. But here, Thaler asks the court to read the law both strictly and metaphorically at the same time. Because nowhere in employment law are any rights vested in the analogous employee. For instance, the U.S. Equal Employment Opportunity Commission states:

Under the laws enforced by EEOC, it is illegal to discriminate against someone (applicant or employee) because of that person’s race, color, religion, sex (including gender identity, sexual orientation, and pregnancy), national origin, age (40 or older), disability or genetic information.

Title VII does not emphatically state that those qualities must describe human persons, but if we look to the definition of “persons,” we find …

The term “person” includes one or more individuals, governments, governmental agencies, political subdivisions, labor unions, partnerships, associations, corporations, legal representatives, mutual companies, joint-­stock companies, trusts, unincorporated organizations, trustees, trustees in cases under Title 11 [originally, bankruptcy], or receivers.

So, if we are following Thaler’s supposedly rigorous statutory interpretation, we can end the discussion by noting that there is no mention of computers, algorithms, machines, robots, etc. to support the argument that “Creativity Machine” is an employable “person” as an operation of law. Indeed, even the non-human entities in the definition above do not exist except as various means to organize the work or interests of human persons, and this is relevant to the copyright question presented.

While it is true that entities like corporations can own copyrights, the rights themselves do not exist until the moment of fixation of a human’s conception and the result of a human’s effort. Until then, there are no rights which may be transferred to the entity—either by independent or employment contract. Human authorship is not removed from the production of the work by the administrative formalities entailed with corporate ownership. On the contrary, human authorship must occur in order for the rights to exist at all.

This same principle applies to Thaler’s semantic game alleging that pseudonymous or anonymous works become works of non-human authorship merely because the term of protection is no longer based on the lifetime of the author. This makes no sense. Does Thaler argue that works made prior to the 1976 Act were not works of human authorship simply because they were protected under fixed terms unrelated to the life of the authors? He is conflating administrative rules (which are admittedly more complicated than necessary) with the doctrine of human authorship, which predates those rules by a few centuries.

Simply put, there is no concept of copyright law anywhere in western culture in which the utilitarian purpose of incentivizing authors to produce and disseminate works is not intertwined with the principle that the fruits of intellectual labor are the property of the author as a matter of natural right. The hyper-utilitarian view often overlooks the natural rights vested in the author, but the bundle of rights codified in Section 106 of the Copyright Act are as intangible and violable as any other civil right articulated by statute.  And such rights do not exist without humans.

Thaler and others are free to invoke philosophical debate as to whether an AI can have “ideas” or make creative “choices,” and it’s all fine chatter for a round of drinks, but even if it could be proven that the AI is “conscious enough” to make a choice to create and how to create, this is irrelevant as a matter of law. And we do not even need to confront AI per se. An elephant can make a painting, and a circus can own an elephant, but the circus cannot claim copyright in the painting as a WMFH because neither copyright rights nor an employment agreement exists between elephant and circus. And this is because no rights—copyright or otherwise—exist for the elephant that give her standing in court.

Personally, I believe the courts have gone too far in blurring the line between corporate and human personhood—e.g., vesting Hobby Lobby, Inc. with the right of religious exercise, but even in that controversial case, human persons, as owners of a closely held company, remain at the center of the finding. This is not so in Thaler’s claim of copyright in the visual work at issue. “Creativity Machine” is not a “person” by any statutory definition and cannot, therefore, have agreed to an employment contract in which it was understood that the employee would produce visual works under the WMFH doctrine. It is an absurdity on its face scratching at pencil shavings of statutory meaning, and Thaler’s appeal to history does him no favors.

I suspect the courts will find Thaler’s reading of the law to be untenable and will further advise that only Congress can change the Copyright Act. And if Congress were to do so in this context, I would hope that they affirmatively state that authorship must be human. If elephants don’t have such rights, why should robots?

Robot image by: sarah5

Why Machine Training AI with Protected Works is Not Fair Use

As most copyright watchers already know, two lawsuits were filed at the start of the new year against AI visual works companies. In the U.S., a class-action was filed by visual artists against DeviantArt, Midjourney, and Stability AI; and in the UK, Getty Images is suing Stability AI. Both cases allege infringing use of large volumes of protected works fed into the systems to “train” the algorithms. Regardless of how these two lawsuits might unfold, I want to address the broad defense, already being argued in the blogosphere, that training generative AIs with volumes of protected works is fair use. I don’t think so.

Copyright advocates, skeptics, and even outright antagonists generally agree that the fair use exception, correctly applied, supports the broad aim of copyright law to promote more creative work. In the language of the Constitution, copyright “promotes the progress of science,” but a more accurate, modern description would be that copyright promotes new “authorship” because we do not tend to describe literature, visual arts, music, etc. as “science.”

The fair use doctrine, codified in the federal statute in 1976, originated as judge-made law, and from the seminal Folsom v. Marsh to the contemporary AWF v. Goldsmith, the courts have restated, in one way or another, their responsibility to balance the first author’s exclusive rights with a follow-on author’s interest in creating new expression. And as a matter of general principle, it is held that the public benefits from this balancing act because the result is a more diverse market of creative and cultural works.

Fair use defenses are case-by-case considerations and while there may be specific instances in which an AI purpose may be fair use, there are no blanket exceptions. More broadly, though, if the underlying goal of copyright’s exclusive rights and the fair use exception is to promote new “authorship,” this is doctrinally fatal to the proposal that training AIs on volumes of protected works favors a finding of fair use. Even if a court holds that other limiting doctrines render this activity by certain defendants to be non-infringing, a fair use defense should be rejected at summary judgment—at least for the current state of the technology, in which the schematic encompassing AI machine, AI developer, and AI user does nothing to promote new “authorship” as a matter of law.

The definition of “author” in U.S. copyright law means “human author,” and there are no exceptions to this anywhere in our history. The mere existence of a work we might describe as “creative” is not evidence of an author/owner of that work unless there is a valid nexus between a human’s vision and the resulting work fixed in a tangible medium. If you find an anonymous work of art on the street, absent further research, it has no legal author who can assert a claim of copyright in the work that would hold up in any court. And this hypothetical emphasizes the point that the legal meaning of “author” is more rigorous than the philosophical view that art without humans is oxymoronic. (Although it is plausible to find authorship in a work that combines human creativity with AI, I address that subject below.)

As a matter of law, the AI machine itself is disqualified as an “author” full stop. And the although the AI owner/developer and AI user/customer are presumably both human, neither is defensibly an “author” of the expressions output by the AI. At least with the current state of technologies making headlines, nowhere in the process—from training the AI, to developing the algorithm, to entering prompts into the system—is there an essential link between those contributions and the individual expressions output by the machine. Consequently, nothing about the process of ingesting protected works to develop these systems in the first place can plausibly claim to serve the purpose of promoting new “authorship.”

But What About the Google Books Case?

Indeed. In the fair use defenses AI developers will present, we should expect to see them lean substantially on the holding in Authors Guild v. Google Books—a decision which arguably exceeds the purpose of fair use to promote new authorship. The Second Circuit, while acknowledging that it was pushing the boundaries of fair use, found the Google Books tool to be “transformative” for its novel utility in presenting snippets of books; and because that utility necessitates scanning whole books into its database, a defendant AI developer will presumably want to make the comparison. But a fair use defense applied to training AIs with volumes of protected works should fail, even under the highly utilitarian holding in Google Books.

While people of good intent can debate the legal merits of that decision, the utility of the Google Books search engine does broadly serve the interest of new authorship with a useful research tool—one I have used many times myself. Google Books provides a new means by which one author may research the works of another author, and this is immediately distinguishable from the generative AI which may be trained to “write books” without authors. Thus, not only does the generative AI fail to promote authorship of the individual works output by the system, but it fails to promote authorship in general.

Although the technology is primitive for the moment, these AIs are expected to “learn” exponentially and grow in complexity such that AIs will presumably compete with or replace at least some human creators in various fields and disciplines. Thus, an enterprise which proposes to diminish the number of working authors, whether intentionally or unintentionally, should only be viewed as devastating to the purpose of copyright law, including the fair use exception.

AI proponents may argue that “democratizing” creativity (i.e., putting these tools in every hand) promotes authorship by making everyone an author. But aside from the cultural vacuum this illusion of more would create, the user prompting the AI has a high burden to prove authorship, and it would really depend on what he is contributing relative to the AI. As mentioned above, some AIs may evolve as tools such that the human in some way “collaborates” with the machine to produce a work of authorship. But this hypothetical points to the reason why fair use is a fact-specific, case-by-case consideration. AI Alpha, which autonomously creates, or creates mostly without human direction, should not benefit from the potential fair use defense of AI Beta, which produces a tool designed to aid, but not replace, human creativity.

Broadly Transformative? Don’t Even Go There

Returning to the constitutional purpose of copyright law to “promote science,” the argument has already been floated as a talking point that training AI systems with protected works promotes computer science in general and is, therefore, “transformative” under fair use factor one for this reason. But this argument should find no purchase in court. To the extent that one of these neural networks might eventually spawn revolutionary utility in medicine or finance etc., it would be unsuitable to ask a court to hold that such voyages of general discovery fit the purpose of copyright, to say nothing of the likelihood that the adventure strays inevitably into patent law. Even the most elastic fair use findings to date reject such a broad defense.

It may be shown that no work(s) output by a particular AI infringes (copies) any of the works that went into its training. It may also be determined that the corpus of works fed into an AI is so rapidly atomized into data that even fleeting “reproduction” is found not to exist, and, thus, the 106(1) right is not infringed. Those questions are going to be raised in court before long, and we shall see where they lead. But to presume fair use as a broad defense for AI “training” is existentially offensive to the purpose of copyright, and perhaps to law in general, because it asks the courts to vest rights in non-humans, which is itself anathema to caselaw in other areas.[1]

It is my oft-stated opinion that creative expression without humans is meaningless as a cultural enterprise, but it is a matter of law to say that copyright is meaningless without “authors” and that there is no such thing as non-human “authors.” For this reason, the argument that training AIs on protected works is inherently fair use should be denied with prejudice.

[1] Cetaceans v. Bush holding that animals do not have standing in court was the basis for rejecting PETA’S complaint against photographer Slater for infringing the copyright rights of the monkey in the “Monkey Selfie” fiasco.

A Thousand Cuts: AI and Self-Destruction

I woke up the other day thinking about artificial intelligence (AI) in context to the Cold War and the nuclear arms race, and curiously enough, the next two articles I read about AI made arms race references. Where my pre-caffeinated mind had gone was back to the early 1980s when, as teenagers, we often asked that futile question as to why any nation needed to stockpile nuclear weapons in quantities that could destroy the world many times over.

Every generation of adolescents believes—and at times confirms—that the adults have no idea what the hell they’re doing; and watching the MADness of what often seemed like a rapturous embrace of nuclear annihilation was, perhaps, the unifying existential threat which shaped our generation’s world view. Since then, reasonable arguments have been made that nuclear stalemate has yielded an unprecedented period of relative global peace, but the underlying question remains:  Are we powerless to stop the development of new modes of self-destruction?

Of course, push-button extinction is easy to imagine and, in a way, easy to ignore. If something were to go terribly wrong, and the missiles fly, it’s game over in a matter of minutes with no timeouts left. So, it is possible to “stop worrying” if not quite “love the bomb” (h/t Strangelove); but today’s technological threats preface outcomes that are less merciful than swift obliteration. Instead, they offer a slow and seemingly inexorable decline toward the dystopias of science fiction—a future in which we are not wiped out in a flash but instead “amused to death” (h/t Postman) as we relinquish humanity itself to the exigencies of technologies that serve little or no purpose.

The first essay I read about AI, written by Anja Kaspersen and Wendell Wallach for the Carnegie Council, advocates a “reset” in ethical thinking about AI, arguing that giant technology investments are once again building systems with little consideration for their potential effect on people. “In the current AI discourse we perceive a widespread failure to appreciate why it is so important to champion human dignity. There is risk of creating a world in which meaning and value are stripped from human life,” the authors write. Later, they quote Robert Oppenheimer …

It is not possible to be a scientist unless you believe that the knowledge of the world, and the power which this gives, is a thing which is of intrinsic value to humanity, and that you are using it to help in the spread of knowledge, and are willing to take the consequences.

I have argued repeatedly that generative AI “art” is devoid of meaning and value and that the question posed by these technologies is not merely how they might influence copyright law, but whether they should exist at all. It may seem farfetched to contemplate banning or regulating the development of AI tech, but it should not be viewed as an outlandish proposal. If certain AI developments have the capacity to dramatically alter human existence—perhaps even erode what it means to be human—why is this any less a subject of public policy than regulating a nuclear power plant or food safety?

Of course, public policy means legislators, and it is quixotic to believe that any Congress, let alone the current one, could sensibly address AI before the industry causes havoc. At best, the tech would flood the market long before the most sincere, bipartisan efforts of lawmakers could grasp the issues; and at worst, far too many politicians have shown that they would sooner exploit these technologies for their own gain than they would seek to regulate it in the public interest. “AI applications are increasingly being developed to track and manipulate humans, whether for commercial, political, or military purposes, by all means available—including deception,” write Kaspersen and Wallach. I think it’s fair to read that as Cambridge Analytica 2.0 and to recognize that the parties who used the Beta version are still around—and many have offices on Capitol Hill.

Kaspersen and Wallach predict that we may soon discover that generative AI will have the same effect on education that “social media has had on truth.” In response, I would ask the following: In the seven years since the destructive power of social media became headline news, have those revelations significantly changed the conversation, let alone muted the cyber-libertarian dogma of the platform owners? I suspect that AI in the classroom threatens to exacerbate rather than parallel the damage done by social media to truth (i.e., reason). If social media has dulled Socratic skills with the flavors of narcissism, ChatGPT promises a future that does not remember what Socratic skills used to mean.

And that brings me to the next article I read in which Chris Gillard and Pete Rorabaugh, writing for Slate, use “arms race” as a metaphor to criticize technological responses to the prospect of students cheating with AI systems like ChatGPT. Their article begins:

In the classroom of the future—if there still are any—it’s easy to imagine the endpoint of an arms race: an artificial intelligence that generates the day’s lessons and prompts, a student-deployed A.I. that will surreptitiously do the assignment, and finally, a third-party A.I. that will determine if any of the pupils actually did the work with their own fingers and brain. Loop complete; no humans needed. If you were to take all the hype about ChatGPT at face value, this might feel inevitable. It’s not.

In what I feared might be another tech-apologist piece labeling concern about AI a “moral panic,” Gillard and Rorabaugh make the opposite point. Their criticism of software solutions to mitigate student cheating is that it is small thinking which erroneously accepts as a fait accompli that these AI systems are here to stay whether we like it or not. “Telling us that resistance to a particular technology is futile is a favorite talking point for technologists who release systems with few if any guardrails out into the world and then put the onus on society to address most of the problems that arise,” they write.

In other words, here we go again. The ethical, and perhaps legal, challenges posed by AI are an extension of the same conversation we generally failed to have about social media and its cheery promises to be an engine of democracy. “It’s a failure of imagination to think that we must learn to live with an A.I. writing tool just because it was built,” Gillard and Rorabaugh argue. I would like to agree but am skeptical that the imagination required to reject certain technologies exists outside the rooms where ethicists gather. And this is why I wake up thinking about AI in context to the Cold War, except of course that the doctrine of Mutually Assured Destruction was rational by contrast.

Photo by author.