Let’s Stop Analogizing Human Creators to Machines

Of course, policy discussions usually begin with the existing framework, but in this instance, it can be a shaky starting place because generative AI presents some unique challenges—and not just for the practice of copyright law.

[Guest post by David Newhoff, author of The Illusion of More and Who Invented Oscar Wilde? The Photograph at the Center of Modern American Copyright.]

Just as it is folly to anthropomorphize computers and robots, it is also unhelpful to discuss the implications of generative AI in copyright law by analogizing machines to authors.[1] In 2019, I explored the idea that “machine learning” could be analogous to human reading if the human happens to have an eidetic memory. But this was a thought exercise, and in that post, I also imagined machine training that serves a computer science or research purpose—not necessarily generative AIs trained on protected works designed to produce works without authors.

In the present discussion, however, certain parties weighing in on AI and copyright seem to advocate policy that is premised on the language and principles of existing doctrine as applicable to the technological processes of both the input and output sides of the generative AI equation. Of course, policy discussions usually begin with the existing framework, but in this instance, it can be a shaky starting place because generative AI presents some unique challenges—and not just for the practice of copyright law.

We should be wary of analogizing machine functions to human activity for the simple reason that copyright law (indeed all law) has never been anything but anthropocentric. Although it is difficult to avoid speaking in terms of machines “learning” or “creating,” it is essential that we either constantly remind ourselves that these are weak, inaccurate metaphors, or that a new glossary is needed to describe what certain AIs may be doing in the world of creative production.

On the input (training) side of the equation, the moment someone says something like, “Humans learn to make art by looking at art, and generative AIs do the same thing,” the speaker should be directed to the break-out session on sci-fi and excused from any serious conversation about applicable copyright law. Likewise, on the output side, comparisons of AI to other technological developments—from the printing press to Photoshop—should be presumed irrelevant unless the AI at issue can plausibly be described as a tool of the author rather than the primary maker of a work of creative expression.

Copyright Office Guidance Highlights Some Key Difficulties

To emphasize the exceptional nature of this discussion, even experts are somewhat confused by both the doctrinal and administrative aspects in the new guidelines published by U.S. Copyright Office directing authors how to disclaim AI-generated material in a registration application. The confusion is hardly surprising because generative AI has prompted the Office to ask an unprecedented question—namely, How was this work made?

As noted in several posts, copyrightability has always been agnostic with regard to the creative process. Copyright rights attach to works that show a modicum of originality, and the Copyright Office does not generally ask what tools, methods, etc. the author used to make a work.[2] But this historic practice was then confronted by the now widely reported applications submitted by Stephen Thaler and Kris Kashtanova, both claiming copyright in visual works made with generative AI.

In both cases, the Copyright Office rejected registration applications for the visual works based on the longstanding, bright-line doctrine that copyright rights can only attach to works made by human beings. In Thaler’s case, the consideration is straightforward because the claimant affirmed that the image was produced entirely by a machine. Kashtanova, on the other hand, asserts more than de minimis authorship (i.e., using AI as a tool) to produce the visual works elements in a comic book.

Whether in response to Kashtanova—or certainly anticipating applications yet to come—the muddiness of the Office guidelines is an attempt to address the difficult question as to whether copyright attaches to a work that combines authorship and AI generation, and how to draw distinctions between the two. This is not only new territory for the Office as a doctrinal matter but is a potential mess as an administrative one.

The Copyright Office has never been tasked with separating the protectable expression attributable to a human from the unprotectable expression attributable to a machine. Even if it could be said that photography has always provoked this tension (a discussion on its own), the analysis has never been an issue for the Office when registering works, but only for the courts in resolving claims of infringement. In fact, Warhol v. Goldsmith, although a fair use case, is a prime example of how tricky it can be to separate the factual elements of a photograph from the expressive elements.

But now the Copyright Office is potentially tasked with a copyrightability question that, in practice, would ask both the author and the examiner to engage in a version of the idea/expression dichotomy analysis—first separating the machine generated material from the author’s material and then considering whether the author has a valid claim in the protectable expression.

This is not so easy to accomplish in a work that combines author and machine-made elements in a manner that may be subtly intertwined; it begs new questions about what the AI “contributed” to a given work; and the inquiry is further complicated by the variety of AI tools in the market or in development. Then, because neither the author/claimant nor the Office examiner is likely a copyright attorney (let alone a court), the inquiry is fraught with difficulty as an administrative process—and that’s if the author makes a good-faith effort to disclaim the AI-generated material in the first place.

Many independent authors are confused enough by the Limit of Claim in a registration application or the concept of “published” versus “unpublished.” Asking these same creators to delve into the metaphysics implied by the AI/Author distinction seems like a dubious enterprise, and one that is not likely to foster more faith in the copyright system than the average indie creator has right now.

Copyrightability Could Remain Blind But …

It is understandable that some creators (e.g., filmmakers using certain plug-ins) may be concerned that the Copyright Office has already taken too broad a view—connoting a per se rule that denies copyrightability for any work generated with any AI technology. This concern is a reminder that AI should not be discussed as a monolithic topic because not all AI enhanced products do the same thing. And again, this may imply a need for some new terms rather than the words we use to describe human activities.

In this light, one could follow a different line of reasoning and argue that the agnosticism of copyrightability vis-à-vis process has always implied a presumption of human authorship where other factors—from technological enhancements to dumb luck—invisibly contribute to the protectable expression. Relatedly, a photographer can add a filter or plug-in that changes the expressive qualities of her image, but doing so is considered part of the selection and arrangement aspect of her authorship and does not dilute the copyrightability of the image.

Some extraordinary visual work has already been produced by professional artists using AI to yield results that are too strikingly well-crafted to believe that the author has not exerted considerable influence over the final image. In this regard, then, perhaps the copyrightability question at the registration stage, no matter how sophisticated the “filter” becomes, should remain blind to process. The Copyright Office could continue to register works submitted by valid claimants without asking the novel How question.

But the more that works may be generated with little or no human spark, the more this agnostic, status-quo approach could unravel the foundation of copyright rights altogether. And it would not be the first time that major tech companies have sought to do exactly that. It is no surprise that an AI developer or a producer using AI would seek the financial benefits of copyright protection; but without a defensible presence of human expression in the work, the exclusive rights of copyright cannot vest in a person with the standing to defend those rights. Nowhere in U.S. law do non-humans have rights of any kind, and this foundational principle reminds us that although machine activity can be compared to human activity as an allegorical construct, this is too whimsical for a serious policy discussion.

Again, I highlight this tangle of administrative and doctrinal factors to emphasize the point that generative AI does not merely present new variations on old questions (e.g., photography), but raises novel questions that cannot easily be answered by analogies to the past. If the challenges presented by generative AI are to be resolved sensibly, and in a way that will serve independent creators, policymakers and thought leaders on copyright law should be skeptical of arguments that too earnestly attempt to transpose centuries of doctrine for human activity into principles applied to machine activity.

[1] I do not distinguish “human” authors, because there is no other kind.

[2] I say “generally” only because I cannot account for every conversation among claimants and examiners.

New AI Copyright Guidance

The Copyright Office is providing guidance to copyright applicants who wish to register works with AI-generated content in them.

On Thursday, March 16, 2023, the United States Copyright Office published new guidance regarding the registration of copyrights in AI-generated material. in the Federal Register. Here is the tl;dr version.

The Problem

Artificial intelligence (AI) technologies are now capable of producing content that would be considered expressive works if created by a human being. These technologies “train” on mass quantities of existing human-authored works and use patterns detected in them to generate like content. This creates a thorny question about authorship: To what extent can a person who uses AI technology to generate content be considered the “author” of such content?

It isn’t a hypothetical problem. The Copyright Office has already started receiving applications for registration of copyrights in works that are either wholly or partially AI-generated.

The U.S. Copyright Act gives the Copyright Office power to determine whether and what kinds of additional information it may need from a copyright registration applicant in order to evaluate the existence, ownership and duration of a purported copyright. On March 16, 2023, the Office exercised that power by publishing Copyright Registration Guidance: Works Containing Material Generated by Artificial Intelligence in the Federal Register. [Copyright Registration Guidance: Works Containing Material Generated by Artificial Intelligence, 88 Fed. Reg. 16190 (March 16, 2023)]

Sorry, HAL, No Registration for You

Consistent with judicial rulings, the U.S. Copyright Office takes the position that only material that is created by a human being is protected by copyright. In other words, copyrights only protect human authorship. If a monkey can’t own a copyright in a photograph and an elephant can’t own a copyright in a portrait it paints, a computer-driven technology cannot own a copyright in the output it generates. Sorry, robots; it’s a human’s world.

As stated in the Compendium of Copyright Office Practices:

The Copyright Office “will not register works produced by a machine or mere mechanical process that operates randomly or automatically without any creative input or intervention from a human author.”

U.S. Copyright Office, Compendium of U.S.
Copyright Office Practices
sec. 313.2 (3d ed. 2021)

Partially AI-Generated Works

A work that is the product of a human being’s own original conception, to which s/he gave visible form clearly has a human author. A work that is entirely the result of mechanical reproduction clearly does not. Things get murkier when AI technology is used to generate content to which a human being applies some creativity.

According to the new guidance, merely prompting an AI technology to generate a poem, drawing or the like, without more, is not enough to establish human authorship if the AI technology determines the expressive elements of its output. This kind of content is not protected by copyright and a registration applicant therefore will need to disclaim it in the application.

On the other hand, if a human being selects and arranges AI-generated content, the selection and arrangement may be protected by copyright even if the content itself is not. Similarly, if a human being makes significant modifications to AI-generated content, then those modifications may receive copyright protection. In all cases, of course, the selection, arrangement or modification must be sufficiently creative in order to qualify for copyright protection.

Disclosure required

The new guidance imposes a duty on copyright registration applicants to disclose the inclusion of AI-generated content in any work submitted for registration.

Standard application

If you use AI technology to any extent in creating the work, you will need to use the Standard application, not the Single application, to register the copyright in it.

Claims and disclaimers

The applicant will need to describe the human author’s contributions to the work in the “Author Created” field of the application. A claim should only be made in this.

Any significant AI-generated content must be explicitly excluded (disclaimed), in the “Limitations of the Claim” section of the application, in the “Other” field, under the “Material Excluded” heading.

Previously filed applications

If you have already filed an application for a work that includes AI-generated material, you will need to make sure that it makes an adequate disclosure about that. The newly-issued guidance says you should contact the Copyright Office’s Public Information Office and report that you omitted AI information from the application. This will cause a notation to the record to be made. When an examiner sees the notation, s/he may contact you to obtain additional information if necessary.

If a registration has already been issued, you should submit a supplemntary registration form to correct it. Failing to do that could result in your registration being cancelled, if the Office becomes aware that information essential to its evaluation of registrability has been omitted. In addition, a court may ignore a registration in an infringement action if it concludes that you knowingly provided the Copyright Office with false information.

Need help with a copyright application or registration?

Contact attorney Tom James.

A Recent Entrance to Complexity

The United States Copyright Office recently reaffirmed its position that it will not register AI-generated content, because it is not created by a human. The rule is easy to state; the devil is in the details. Attorney Thomas James explains.

Last year, the United States Copyright Office issued a copyright registration to Kristina Kashtanova for the graphic novel, Zarya of the Dawn. A month later, the Copyright Office issued a notice of cancellation of the registration, along with a request for additional information.

The Copyright Office, consistent with judicial decisions, takes the position that copyright requires human authorship. The Office requested additional information regarding the creative process that resulted in the novel because parts of it were AI-generated. Kashtanova complied with the request for additional information.

This week, the Copyright Office responded with a letter explaining that the registration would be cancelled, but that a new, more limited one will be issued. The Office explained that its concern related to the author’s use of Midjourney, an AI-powered image generating tool, to generate images used in the work:

Because Midjourney starts with randomly generated noise that evolves into a final image, there is no guarantee that a particular prompt will generate any particular visual output”

U.S. Copyright Office letter

The Office concluded that the text the author wrote, as well as the author’s selection, coordination and arrangement of written and visual elements, are protected by copyright, and therefore may be registered. The images generated by Midjourney, however, would not be registered because they were “not the product of human authorship.” The new registration will cover only the text and editing components of the work, not the AI-generated images.

A Previous Entrance to Paradise

Early last year, the Copyright Office refused copyright registration for an AI-generated image. Steven Thaler had filed an application to register a copyright in an AI-generated image called “A Recent Entrance to Paradise.” He listed himself as the copyright owner. The Copyright Office denied registration on the grounds that the work lacked human authorship. Thaler filed a lawsuit in federal court seeking to overturn that determination. The lawsuit is still pending. It is currently at the summary judgment stage.

The core issue

The core issue, of course, is whether a person who uses AI to generate content such as text or artwork can claim copyright protection in the content so generated. Put another way, can a user who deploys artificial intelligence to generate a seemingly expressive work (such as artwork or a novel) claim authorship?

This question is not as simple as it may seem. There can be different levels of human involvement in the use of an AI content generating mechanism. At one extreme, there are programs like “Paint,” in which users provide a great deal of input. These kinds of programs may be analogized to paintbrushes, pens and other tools that artists traditionally have used to express their ideas on paper or canvas. Word processing programs are also in this category. It is easy to conclude that the users of these kinds of programs are the authors of works that may be sufficiently creative and original to receive copyright protection.

At the other end of the spectrum are AI services like DALL-E and ChatGPT. Text and images can be generated by these systems with minimal human input. If the only human input is a user’s directive to “Write a story” or “Draw a picture,” then it would be difficult to claim that the author contributed any creative expression. That is to say, it would be difficult to claim that the user authored anything.

Peering into the worm can

The complicating consideration with content-generative AI mechanisms is that they have the potential to allow many different levels of user involvement in the generation of output. The more details a user adds to the instructions s/he gives to the machine, the more it begins to appear that the user is, in fact, contributing something creative to the project.

Is a prompt to “Write a story about a dog” a sufficiently creative contribution to the resulting output to qualify the user as an “author”? Maybe not. But what about, “Write a story about a dog who joins a traveling circus”? Or “Write a story about a dog named Pablo who joins a traveling circus”? Or “Write a story about a dog with a peculiar bark that begins, ‘Once upon a time, there was a dog named Pablo who joined a circus,’ and ends with Pablo deciding to return home”?

At what point along the spectrum of user-provided detail does copyright protectable authorship come into existence?

A question that is just as important to ask is: How much, if at all, should the Copyright Office involve itself with ascertaining the details of the creative process that were involved in a work?

In a similar vein, should copyright registration applicants be required to disclose whether their works contain AI-generated content? Should they be required to affirmatively disclaim rights in elements of AI-generated content that are not protected by copyright?

Expanding the Rule of Doubt

Alternatively, should the U.S. Copyright Office adopt something like a Rule of Doubt when copyright is claimed in AI-generated content? The Rule of Doubt, in its current form, is the rule that the U.S. Copyright Office will accept a copyright registration of a claim containing software object code, even though the Copyright Office is unable to verify whether the object code contains copyrightable work. If effect, if the applicant attests that the code is copyrightable, then the Copyright Office will assume that it is and will register the claim. Under 37 C.F.R. § 202.20(c)(2)(vii)(B), this may be done when an applicant seeks to register a copyright in object code rather than source code. The same is true of material that is redacted to protect a trade secret.

When the Office issues a registration under the Rule of Doubt, it adds an annotation to the certificate and to the public record indicating that the copyright was registered under the Rule of Doubt.

Under the existing rule, the applicant must file a declaration stating that material for which registration is sought does, in fact, contain original authorship.

This approach allows registration but leaves it to courts (not the Copyright Office) to decide on a case-by-case basis whether material for which copyright is claimed contains copyrightable authorship.  

Expanding the Rule of Doubt to apply to material generated at least in part by AI might not be the most satisfying solution for AI users, but it is one that could result in fewer snags and delays in the registration process.


The Copyright Office has said that it soon will be developing registration guidance for works created in part using material generated by artificial intelligence technology. Public notices and events relating to this topic may be expected in the coming months.

Need help with a copyright matter? Contact attorney Thomas James.

Why Machine Training AI with Protected Works is Not Fair Use

… 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.

Guest blogger David Newhoff lays out the argument against the claim that training AI systems with copyright-protected works is fair use. David is the author of Who Invented Oscar Wilde? The Photograph at the Center of Modern American Copyright (Potomac Books 2020) and is a copyright advocate/writer at The Illusion of More.

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 Andy Warhol Foundation 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 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

David Newhoff comments on generative AI (artificial intelligence) and public policy.

A guest post written by David Newhoff. AI, of course, stands for “artificial intelligence.” David is the author of Who Invented Oscar Wilde? The Photograph at the Center of Modern American Copyright (Potomac Books 2020) and a copyright advocate/writer at The Illusion of More.

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 the author.

View the original article on The Illusion of More.

Contact attorney Tom James for copyright help

Need help registering a copyright or a group of copyrights in the United States, or enforcing a copyright in the United States? Contact attorney Tom James.

Getty Images Litigation Update

Getty Images has now filed a lawsuit for copyright infringement in the United States.

In a previous post, I reported on a lawsuit that Getty Images had filed in the United Kingdom against Stability AI. Now the company has filed similar claims against the company in the United States.

The complaint, which has been filed in federal district court in Delaware, alleges claims of copyright infringement; providing false copyright management information; removal or alteration of copyright management information; trademark infringement; trademark dilution; unfair competition; and deceptive trade practices. Both monetary damages and injunctive relief are being sought.

An interesting twist in the Getty litigation is that AI-generated works allegedly have included the Getty Images trademark.

Getty Images logo on AI-generated image
(Reproduction of a portion of the Complaint filed in Getty Images v. Stability AI, Inc. in U.S. district court for the district of Delaware, case no. Case 1:23-cv-00135-UNA (2023). The image has been cropped to avoid reproducing the likenesses of persons appearing in the image and to display only what is needed here for purposes of news reporting and commentary,)

Getty Images, which is in the business of collecting and licensing quality images, alleges (among other things) that affixing its trademark to poor quality AI-generated images tarnishes the company’s reputation. If proven, this could constitute trademark dilution, which is prohibited by the Lanham Act.

Does AI Infringe Copyright?

A previous blog post addressed the question whether AI-generated creations are protected by copyright. This could be called the “output question” in the artificial intelligence area of copyright law. Another question is whether using copyright-protected works as input for AI generative processes infringes the copyrights in those works. This could be called the “input question.” Both kinds of questions are now before the courts. Minnesota attorney Tom James describes a framework for analyzing the input question.

The Input Question in AI Copyright Law

by Thomas James, Minnesota attorney

In a previous blog post, I discussed the question whether AI-generated creations are protected by copyright. This could be called the “output question” in the artificial intelligence area of copyright law. Another question is whether using copyright-protected works as input for AI generative processes infringes the copyrights in those works. This could be called the “input question.” Both kinds of questions are now before the courts. In this blog post, I describe a framework for analyzing the input question.

The Cases

The Getty Images lawsuit

Getty Images is a stock photograph company. It licenses the right to use the images in its collection to those who wish to use them on their websites or for other purposes. Stability AI is the creator of Stable Diffusion, which is described as a “text-to-image diffusion model capable of generating photo-realistic images given any text input.” In January, 2023, Getty Images initiated legal proceedings in the United Kingdom against Stability AI. Getty Images is claiming that Stability AI violated copyrights by using their images and metadata to train AI software without a license.

The independent artists lawsuit

Another lawsuit raising the question whether AI-generated output infringes copyright has been filed in the United States. In this case, a group of visual artists are seeking class action status for claims against Stability AI, Midjourney Inc. and DeviantArt Inc. The artists claim that the companies use their images to train computers “to produce seemingly new images through a mathematical software process.” They describe AI-generated artwork as “collages” made in violation of copyright owners’ exclusive right to create derivative works.

The GitHut Copilot lawsuit

In November, 2022, a class action lawsuit was filed in a U.S. federal court against GitHub, Microsoft, and OpenAI. The lawsuit claims the GitHut Copilot and OpenAI Codex coding assistant services use existing code to generate new code. By training their AI systems on open source programs, the plaintiffs claim, the defendants have allegedly infringed the rights of developers who have posted code under open-source licenses that require attribution.

How AI Works

AI, of course, stands for artificial intelligence. Almost all AI techniques involve machine learning. Machine learning, in turn, involves using a computer algorithm to make a machine improve its performance over time, without having to pre-program it with specific instructions. Data is input to enable the machine to do this. For example, to teach a machine to create a work in the style of Vincent van Gogh, many instances of van Gogh’s works would be input. The AI program contains numerous nodes that focus on different aspects of an image. Working together, these nodes will then piece together common elements of a van Gogh painting from the images the machine has been given to analyze. After going through many images of van Gogh paintings, the machine “learns” the features of a typical Van Gogh painting. The machine can then generate a new image containing these features.

In the same way, a machine can be programmed to analyze many instances of code and generate new code.

The input question comes down to this: Does creating or using a program that causes a machine to receive information about the characteristics of a creative work or group of works for the purpose of creating a new work that has the same or similar characteristics infringe the copyright in the creative work(s) that the machine uses in this way?

The Exclusive Rights of Copyright Owners

In the United States, the owner of a copyright in a work has the exclusive rights to:

  • reproduce (make copies of) it;
  • distribute copies of it;
  • publicly perform it;
  • publicly display it; and
  • make derivative works based on it.

(17 U.S.C. § 106). A copyright is infringed when a person exercises any of these exclusive rights without the copyright owner’s permission.

Copyright protection extends only to expression, however. Copyright does not protect ideas, facts, processes, methods, systems or principles.

Direct Infringement

Infringement can be either direct or indirect. Direct infringement occurs when somebody directly violates one of the exclusive rights of a copyright owner. Examples would be a musician who performs a copyright-protected song in public without permission, or a cartoonist who creates a comic based on the Batman and Robin characters and stories without permission.

The kind of tool an infringer uses is not of any great moment. A writer who uses word-processing software to write a story that is simply a copy of someone else’s copyright-protected story is no less guilty of infringement merely because the actual typewritten letters were generated using a computer program that directs a machine to reproduce and display typographical characters in the sequence a user selects.

Contributory and Vicarious Infringement

Infringement liability may also arise indirectly. If one person knowingly induces another person to infringe or contributes to the other person’s infringement in some other way, then each of them may be liable for copyright infringement. The person who actually committed the infringing act could be liable for direct infringement. The person who knowingly encouraged, solicited, induced or facilitated the other person’s infringing act(s) could be liable for contributory infringement.

Vicarious infringement occurs when the law holds one person responsible for the conduct of another because of the nature of the legal relationship between them. The employment relationship is the most common example. An employer generally is held responsible for an employee’s conduct,  provided the employee’s acts were performed within the course and scope of the employment. Copyright infringement is not an exception to that rule.

Programmer vs. User

Direct infringement liability

Under U.S. law, machines are treated as extensions of the people who set them in motion. A camera, for example, is an extension of the photographer. Any images a person causes a camera to generate by pushing a button on it is considered the creation of the person who pushed the button, not of the person(s) who manufactured the camera, much less of the camera itself. By the same token, a person who uses the controls on a machine to direct it to copy elements of other people’s works should be considered the creator of the new work so created. If using the program entails instructing the  machine to create an unauthorized derivative work of copyright-protected images, then it would be the user, not the machine or the software writer, who would be at risk of liability for direct copyright infringement.

Contributory infringement liability

Knowingly providing a device or mechanism to people who use it to infringe copyrights creates a risk of liability for contributory copyright infringement. Under Sony Corp. v. Universal City Studios, however, merely distributing a mechanism that people can use to infringe copyrights is not enough for contributory infringement liability to attach, if the mechanism has substantial uses for which copyright infringement liability does not attach. Arguably, AI has many such uses. For example, it might be used to generate new works from public domain works. Or it might be used to create parodies. (Creating a parody is fair use; it should not result in infringement liability.)

The situation is different if a company goes further and induces, solicits or encourages people to use its mechanism to infringe copyrights. Then it may be at risk of contributory liability. As the United States Supreme Court has said, “one who distributes a device with the object of promoting its use to infringe copyright, as shown by clear expression or other affirmative steps taken to foster infringement, is liable for the resulting acts of infringement by third parties.” Metro-Goldwyn-Mayer Studios Inc. v. Grokster, Ltd., 545 U.S. 913, 919 (2005). (Remember Napster?)

Fair Use

If AI-generated output is found to either directly or indirectly infringe copyright(s), the infringer nevertheless might not be held liable, if the infringement amounts to fair use of the copyrighted work(s) that were used as the input for the AI-generated work(s).

Ever since some rap artists began using snippets of copyright-protected music and sound recordings without permission, courts have embarked on a treacherous expedition to articulate a meaningful dividing line between unauthorized derivative works, on one hand, and unauthorized transformative works, on the other. Although the Copyright Act gives copyright owners the exclusive right to create works based on their copyrighted works (called derivative works), courts have held that an unauthorized derivative work may be fair use if it is “transformative.: This has caused a great deal of uncertainty in the law, particularly since the U.S. Copyright Act expressly defines a derivative work as one that transforms another work. (See 17 U.S.C. § 101: “A ‘derivative work’ is a work based upon one or more preexisting works, . . . or any other form in which a work may be recast, transformed, or adapted.” (emphasis added).)

When interpreting and applying the transformative use branch of Fair Use doctrine, courts have issued conflicting and contradictory decisions. As I wrote in another blog post, the U.S. Supreme Court has recently agreed to hear and decide Andy Warhol Foundation for the Visual Arts v. Goldsmith. It is anticipated that the Court will use this case to attempt to clear up all the confusion around the doctrine. It is also possible the Court might take even more drastic action concerning the whole “transformative use” branch of Fair Use.

Some speculate that the questions the Justices asked during oral arguments in Warhol signal a desire to retreat from the expansion of fair use that the “transformativeness” idea spawned. On the other hand, some of the Court’s recent decisions, such as Google v. Oracle, suggest the Court is not particularly worried about large-scale copyright infringing activity, insofar as Fair Use doctrine is concerned.


To date, it does not appear that there is any direct legal precedent in the United States for classifying the use of mass quantities of works as training tools for AI as “fair use.” It seems, however, that there soon will be precedent on that issue, one way or the other. In the meantime, AI generating system users should proceed with caution.

%d bloggers like this: