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Applying Intellectual Property Law to AI: An Interview with Betsy Rosenblatt

Last Updated on February 23, 2023, 10:19 am ET

collage of OTW logosFor Fair Use/Fair Dealing Week 2023, Betsy Rosenblatt, professor at University of Tulsa College of Law, shared her expertise on intellectual property law and her analysis of its application to artificial intelligence, with Katherine Klosek, ARL’s director of Information Policy. Betsy Rosenblatt is the legal chair for the Organization for Transformative Works (OTW), a nonprofit dedicated to preserving fan works. OTW and ARL are members of the Re:Create Coalition, whose members advocate for balanced copyright. The interview with Betsy follows.

Katherine: When you think about AI technology, fan works, and copyright, what excites you? And, what keeps you up at night?

Betsy: One of the things that excites me—which is probably a bit off to the side of what most people are talking about with AI and copyright—is that AIs are reading fan fiction now. For a long time, machine learning relied almost exclusively on data sources that were known to be in the copyright public domain, such as works published prior to 1927 and public records. The result of that was that machines were often learning archaic ideas—learning to associate certain professions with certain races and genders, for example. Now, machine learning is turning to broader sources from across the internet, including fan works. That means that machines will learn how to describe and express a much more contemporary, broad, inclusive, and diverse set of ideas.

I’m also intrigued by some of the expressive possibilities that AI may create. Will DALL·E or ChatGPT become characters in fan fiction? Surely they will. I want to read the fan-created stories where DALL·E and ChatGPT fall in love with each other (or don’t), get into arguments (or don’t), buy a house together (or don’t), team up to solve (or perpetrate!) crimes….

As for what keeps me up at night, I remain mostly optimistic. I think it would be a very sad turn of events if some of the newly begun litigation about data crawling and scraping ended up preventing machines from building contemporary, inclusive, broad-based data pools to draw on. I think it would be very sad if people turned to AI-created works instead of finding, exploring, and making fan works of their own. But I don’t think either of those things is very likely to happen. Fans make fan works because they love doing it. They feel compelled to tell the stories they imagine, and they want to share those with communities of other fans. They use fan work creation to build skills and find their own voices. I don’t think that the emergence of new technologies will stop them from doing that.

Katherine: Artists have filed a class-action lawsuit alleging that AI companies violate copyright law when they create databases of copyrighted images to “train” their AI image products. At least one of the companies in the suit, Stability AI, says that this is a fair use: “Anyone that believes that this isn’t fair use does not understand the technology and misunderstands the law.” What questions would you like to see a court ask when analyzing whether ingesting copyrighted works to create AI-training databases is a fair use?

Betsy: I tend to agree with Stability AI’s statement. I would like to see courts consider the “training” process separately from the process of generating works. It is, of course, possible that a machine could generate an infringing work. But the process of training that machine involves something very different—turning expressive works into data and creating relationships based on that data collection. We call it machine “learning” for a reason. A well-trained machine won’t generate an infringing work, but it needs as large a pool of data to work from as possible to do that. The mere fact that an AI can create something infringing doesn’t determine whether the gathering of information is infringement. Consider the classic Sony v. Betamax case: The VCR can be used to infringe, but it has noninfringing (fair) uses, and therefore the VCR does not inherently infringe. I recognize that the analogy isn’t perfect, but I find it persuasive. In general, courts have found that “interim” copying isn’t infringement—that is, copying isn’t infringement when it occurs inside a machine and does not, itself, make copyrighted works perceptible to people—and I think courts should continue to follow that logic.

Katherine: Will the Supreme Court’s 2021 Google v. Oracle decision have any bearing on this case?

Betsy: I hope so. That case highlighted that we shouldn’t be locked into one definition of “transformative” work, and that copying for the purpose of engaging in a different technological use can be transformative copying.

Katherine: What would you say to online creators who might be discouraged by AI technology?

Betsy: You will always make your work better than an AI can. What matters about your work is that it comes from you. That makes your work irreplaceable, and it will always remain so.

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