AI infringement overwhelms court docket—regulation is key.

While it may seem like these new AI tools can conjure new material from the ether, that’s not quite the case. Generative AI platforms are trained on data lakes and question snippets — billions of parameters that are constructed by software processing huge archives of images and text. The AI platforms recover patterns and relationships, which they then use to create rules, and then make judgments and predictions, when responding to a prompt. This process comes with legal risks, including intellectual property infringement. In many cases, it also poses legal questions that are still being resolved. For example, does copyright, patent, trademark infringement apply to AI creations? Is it clear who owns the content that generative AI platforms create for you, or your customers? Before businesses can embrace the benefits of generative AI, they need to understand the risks — and how to protect themselves.

Where Generative AI Fits into Today’s Legal Landscape

Though generative AI may be new to the market, existing laws have significant implications for its use. Now, courts are sorting out how the laws on the books should be applied. There are infringement and rights of use issues, uncertainty about ownership of AI-generated works, and questions about unlicensed content in training data and whether users should be able to prompt these tools with direct reference other creators’ copyrighted and trademarked works by name without their permission. These claims are already being litigated. In a case filed in late 2022, Andersen v. Stability AI et al., three artists formed a class to sue multiple generative AI platforms on the basis of the AI using their original works without license to train their AI in their styles, allowing users to generate works that may be insufficiently transformative from their existing, protected works, and, as a result, would be unauthorized derivative works. If a court finds that the AI’s works are unauthorized and derivative, substantial infringement penalties can apply. Similar cases filed in 2023 bring claims that companies trained AI tools using data lakes with thousands — or even many millions — of unlicensed works. Getty, an image licensing service, filed a lawsuit against the creators of Stable Diffusion alleging the improper use of its photos, both violating copyright and trademark rights it has in its watermarked photograph collection. In each of these cases, the legal system is being asked to clarify the bounds of what is a “derivative work” under intellectual property laws — and depending upon the jurisdiction, different federal circuit courts may respond with different interpretations. The outcome of these cases is expected to hinge on the interpretation of the fair use doctrine, which allows copyrighted work to be used without the owner’s permission “for purposes such as criticism (including satire), comment, news reporting, teaching (including multiple copies for classroom use), scholarship, or research,” and for a transformative use of the copyrighted material in a manner for which it was not intended. This isn’t the first time technology and copyright law have crashed into each other. Google successfully defended itself against a lawsuit by arguing that transformative use allowed for the scraping of text from books to create its search engine, and for the time being, this decision remains precedential. But there are other, non-technological cases that could shape how the products of generative AI are treated. A case before the U.S. Supreme Court against the Andy Warhol Foundation — brought by photographer Lynn Goldsmith, who had licensed an image of the late musician, Prince — could refine U.S. copyright law on the issue of when a piece of art is sufficiently different from its source material to become unequivocally “transformative,” and whether a court can consider the meaning of the derivative work when it evaluates that transformation. If the court finds that the Warhol piece is not a fair use, it could mean trouble for AI-generated works. All this uncertainty presents a slew of challenges for companies that use generative AI. There are risks regarding infringement — direct or unintentional — in contracts that are silent on generative AI usage by their vendors and customers. If a business user is aware that training data might include unlicensed works or that an AI can generate unauthorized derivative works not covered by fair use, a business could be on the hook for willful infringement, which can include damages up to $150,000 for each instance of knowing use. There’s also the risk of accidentally sharing confidential trade secrets or business information by inputting data into generative AI tools.