In this Essay, we provide a roadmap for how new governance schemes should address plagiarism concerns, disentangling the distinct harms at issue. Some generative AI practices relate to copyright’s legal protection of economic incentives for creating new works—and the fair-use exception that supports valuable follow-on creations. An overlapping but distinct set of practices relate to plagiarism’s nonlegal protection of academic integrity, which centers on honesty and transparency about the origins of the material in a new work. A third category of practices concerns scholarly norms of quality, such as verifying assertions or familiarizing oneself with the relevant literature. Each of these three categories of harm—copyright infringement, plagiarism, and bad scholarly practices—serves distinct normative ends. Any regulatory framework for AI-assisted authorship should thus address each category on its own terms rather than assuming they rise and fall together.

It might be tempting to expand copyright (or other areas of substantive law) to reach AI-facilitated plagiarism, perhaps because copying material without attribution feels instinctively wrong. But intellectual property (IP) law isn’t designed to punish every act of free-riding, and there are sound policy reasons for copyright law’s limits. Instead, the growing problem of AI-facilitated plagiarism should be addressed through the extralegal norms and academic sanctions that have long governed these kinds of concerns. Plagiarism is a problem, but it is not—and should not be—a legal problem.

AI does, however, present the plagiarism and scholarly practice problems in a new light. While some scholars—and many university committees—have begun to think about the proper rules for using and disclosing the use of AI in academic writing, merely disclosing the use of AI is unlikely to satisfy those whose ideas the AI copied and returned in response to a prompt. And a disclosure rule is insufficient to distinguish between uses of AI almost everyone would consider acceptable, such as correcting grammar and typos, and ones that are much more problematic, such as turning in a paper whose thesis and text were largely composed by AI. This isn’t a copyright problem. It isn’t even always a plagiarism problem. But it may be a problem of academic integrity.