Generative AI Copyright Concerns & 3 Best Practices in 2023

Organizations that manufacture generative AI tools like GitHub Copilot and ChatGPT train those tools on open source code, some of which is under strong copyleft licenses like GPL or AGPL. This has sparked some debate about whether generative AI output should be considered a derivative work of the code upon which it’s trained. A recent opinion from the DC District Court held that a valid copyright requires human—not machine—authorship. However, this Yakov Livshits rule’s application is not black and white because it largely depends on the amount of human control/contribution over the AI-generated output. The current generation of flashy AI applications, ranging from GitHub Copilot to Stable Diffusion, raise fundamental issues with copyright law. I am not an attorney, but these issues need to be addressed–at least within the culture that surrounds the use of these models, if not the legal system itself.

For Jason Allen to create his award-winning art, Midjourney was trained on 100 million prior works. Before its invention, artists could only try to portray the world through drawing, painting or sculpture. But on the other, many working artists consider the use of their art to train AI to be exploitative. Robert Mahari does not work for, consult, own shares in or receive funding from any company or organisation that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment. A court later ruled that photographers own the right to the photographs they create which led to photography becoming a new form of art on its own.

Generative AI and Copyright’s Uncertain Future

In past cases, Dr. Thaler has argued that his “Device for the Autonomous Bootstrapping of Unified Sentience” should be considered an inventor for patent purposes. That position was rejected by courts in the United States, Europe, Australia, and New Zealand, which have all so far held that only natural persons can be considered inventors. That is, the fanfiction writer is infringing on the characters and plotlines he borrows, but the copyright owner tolerates this infringement because it causes no harm.

• And even if it did involve copyright infringement, infringement is the trespass on a government-granted exclusive right, nothing akin to stealing personal property.
• Even if the creation of the AI system is not infringing, an artist might not want her creations used to “train” the AI as a matter of principle.
• The recent expansion of the scope and capabilities of generative artificial intelligence (AI) tools and platforms has introduced a number of legal challenges.
• The Copyright Office and US courts have repeatedly held that AI-generated work cannot be owned/authored by the AI itself because a valid copyright requires human authorship and creativity.

“This decision sets the first precedent that explicitly states that copyright law is fundamentally tied to human creativity,” said Violet Sullivan, vp of client engagement for Redpoint Cybersecurity and a privacy law professor at Baylor Law School. This ruling stands as the first legal guardrail in the nation for AI-generated artwork coming in the wake of the generative AI boom. With the rise of several tools, including OpenAI’s ChatGPT, Midjourney, and Stable Diffusion, this ruling will act as a template for future legal battles surrounding IP when applied to AI. The rise of AI-generative platforms such OpenAI Inc.’s ChatGPT, DALL-E, and Midjourney, has exacerbated legal headaches around appropriation art—a tradition in which one artist ostentatiously repurposes another’s creation. As Richard Prince and the estate of Andy Warhol can attest, the legal battles prompted from this work often find unsatisfying conclusions, with judges assuming the role of art critic. Where it was once artist versus artist, courts must now contend with the diffusion of millions of digital artworks by generative platforms.

It’s interesting to note here that in the Copyright Office listening session on text-based works, participants nearly universally agreed that outputs should not be protected by copyright, agreeing with the Copyright Office’s guidance. In particular, the participants in the listening sessions on audiovisual works and sound recordings were concerned about this issue. Creators who rely on their copyrights to defend and monetize their works should be permitted to use generative AI as a creative tool without losing that protection. While we believe that the human authorship requirement is sound, it would be helpful to have more clarity on the status of works that incorporate generative AI content. How much additional human creativity is needed to render an AI-generated work a work of human authorship, and how much can a creator use a generative AI tool as part of their creative process without foregoing copyright protection in the work they produce? The Copyright Office seems to be grappling with these questions as well and seeking to provide additional guidance, such as in a recent webinar with more in-depth registration guidance for creators relying on generative AI tools in their creative efforts.

Is It Possible to Copyright Works That Include AI-Generated Material?

Questions about copyright and GAIs are being grappled with around the world, with different countries taking different approaches. This will likely lead to more GAI development in Japan, and indeed some commenters believe the goal of this expansive approach is to facilitate more Japanese interaction with western-style works and to open up the vast, global array of Japanese media for AI generation. Closer to the middle of the spectrum, while China has not taken any legislative approach, recent court cases point towards an inquiry-based conditional fair use maximalist approach. Similarly, Singapore permits the use of Input Works protected by copyright and data mining without requiring permission or a license from the copyright owner, and the United Kingdom is considering a similar regulation.

They argue that GAIs train on the expression of the Input Works just as human authors take inspiration from other works. In this view, general artistic ideas that can be derived from analyzing many Input Works and are embodied in an Output Work are no more based on Input Works than any author might generate by working on the same general idea or taking inspiration from the same general facts, ideas or styles. For example, the Impressionist painting school arose as one painter inspired another until eventually enough painters shared enough “inspiration” to create a common style. Thus, the fair use maximalists reason, because only the expression of the Input Works themselves can be protected by copyright and not the underlying idea, the generation process is sufficiently transformative. This means that the unique Output Work only embodies the idea of the Input Works and thus cannot infringe on any copyrights related to the Input Works.

TikTok fined 345 million euros over handling of children’s data in Europe

Yakov Livshits
Founder of the DevEducation project
A prolific businessman and investor, and the founder of several large companies in Israel, the USA and the UAE, Yakov’s corporation comprises over 2,000 employees all over the world. He graduated from the University of Oxford in the UK and Technion in Israel, before moving on to study complex systems science at NECSI in the USA. Yakov has a Masters in Software Development.

There is some case law that provides that copyright holders may use or exploit an unauthorized derivative work without compensation to the author of the derivative work (although the Supreme Court found no infringement or inducement of infringement when applied to companies manufacturing VHS systems). One possibility to avoid a tangled web of ownership rights is to develop a remittance scheme to compensate authors of Input Works for the training of GAIs and production of Output Works (perhaps in a similar manner to the remittance scheme for VHS systems that was ultimately struck down in the same case). Under this approach, legislators, agencies or the judiciary would also need to consider whether the user generating and/or exploiting an Output Work should be subject to liability for vicarious infringement and whether a GAI can induce copyright infringement. The Silverman case alleges, among other things, that OpenAI may have scraped the comedian’s memoir, Bedwetter, via “shadow libraries” that host troves of pirated ebooks and academic papers. If the court finds in favor of Silverman and her fellow plaintiffs, the ruling could set new precedent for how the law views the data sets used to train AI models, says Matthew Sag, a law professor at Emory University.

Meanwhile, artists Sarah Anderson, Kelly McKernan and Karla Ortiz have filed a class-action copyright infringement lawsuit against both Stability AI and Midjourney, both of which use Stable Diffusion to generate their images. The suit claims that these artists’ work was wrongfully used to train Stable Diffusion, and that the images generated in the style of those authors directly compete with their own work — an important point in the matter of fair use. Allen appealed to the Board, arguing that the Copyright Office ignored his creative input into Midjourney, placed “a value judgment on the utility of various tools” and overlooked the applicability of the fair use doctrine coming from his transformation of the AI-generated raw material.

In addition, a conditional fair use maximalist approach would be friendly toward an approach where an Output Work is generated based on Input Works that are mostly owned or controlled by the rightsholder with perhaps a small sampling of third-party Input Works. The underlying reasoning would be that the Output Work might benefit from some variety that derives from the third-party Input Works, but the overall style and content would be largely dictated by the contribution of the owned or controlled Input Works. “To change the human authorship requirement, these cases would need to be overturned by a subsequent case, which is unlikely given the [Thaler v. Perlmutter] opinion that addressed this very issue,” Charleston told Decrypt in an email. How might tech companies respond to the accusations of copyright infringement that are being leveled against them?

Ultimately, though, the technology is not going away, and copyright can only remedy some of its consequences. As Stephanie Bell, a research fellow at the nonprofit Partnership on AI, notes, setting a precedent where creative works can be treated like uncredited data is “very concerning.” To fully address a problem like this, the regulations AI needs aren’t yet on the books. If an AI image generator produces art that resembles the work of Georgia O’Keefe, for example, that means it had to be trained using the actual art of Georgia O’Keefe. Similarly, for an AI content generator to write in the style of Toni Morrison, it has to be trained with words written by Toni Morrison. Intellectual Property law is a special set of legislation safeguarding and enforcing the rights of creators and owners of creative works such as inventions, writings, music, designs and other intellectual property.

Over the past several months, platforms like ChatGPT, Dall-E 2, Midjourney and Stable Diffusion have been making waves within the world of advertising for their ability to quickly and competently produce content from text-based user inputs. And at the most recent Cannes Lions festival – the ad industry’s biggest annual event – the tech was the undisputed center of attention. No — AI content and any works created solely by AI cannot be copyrighted in the United States. If the use of creators’ work in generative AI models continues to go unchecked, many experts in this space believe it could spell big trouble — not only for the human creators themselves, but the technology too. Creative work that is the result of a collaboration between a human and machine, which is often the case with AI-generated creations, is a complicated matter.

Generative AI Copyright Concerns & 3 Best Practices in 2023

Rowling” generating a derivative Output Work than the prompt “write a story about a teenage wizard prodigy” without the specific reference to an author. The fair use maximalist approach reduces risks for GAI providers by effectively providing that Output Works do not infringe Input Works. As a result, the fair use maximalist approach would likely spur the development of GAIs trained on a wide array of Input Works – such as large language models and text-to-image models – and would be least likely to provide compensation for creators of Input Works. Machine learning algorithms then detect patterns in the compositions of Input Works and create probabilities and complex correlations that the GAI uses to predict a suitable response to a user’s prompt. For example, large language models are often trained on billions of human-authored documents that allow those models to eventually recognize differences in human expression between an email or a newspaper article and adjust their output accordingly. These lawsuits, even if they are unsuccessful, are likely to provoke generative AI companies into taking steps to avoid them.

It wants to resolve several issues it has identified with regard to copyright and AI, including training data, whether AI generated material is eligible for copyright, liability for infringement by AI systems and how to treat AI outputs that “imitate the identity or style of human artists.” Here, Stephen Thaler developed and owns a generative AI called the “Creativity Machine” that is capable of producing visual artwork. Thaler used “Creativity Machine” to generate a piece of artwork entitled “A Recent Entrance to Paradise.” Subsequently, Thaler attempted to obtain a copyright registration for the artwork, but these attempts were denied by the USCO. The most high-profile of these recent lawsuits came earlier this month when comedian Sarah Silverman, alongside four other authors in two separate filings, sued OpenAI, claiming the company trained its wildly popular ChatGPT system on their works without permission.

It is the reason why today’s AI leaders have chosen to build their innovative products in the United States, rather than elsewhere. Upsetting that balance through legislation that expands the scope of intellectual property protection would jeopardize our role as the global leader of AI development and hamper our ability to compete on the international stage. It would cede our current technological advantage to other nations, some of whom are not our friends.