Not All Authors Are Equal: Moral Judgments of Plagiarism From AI and Human Sources

Abstract Generative AI tools are increasingly being used for creative and academic work. How do people morally evaluate plagiarism involving AI-generated content, and do they judge it differently than when the source is a human? Investigating these questions can provide insight into why people condemn plagiarism; for instance, whether this is due to harm to the original creator or the false benefit gained by the plagiarizer. We examined people’s moral evaluations of plagiarism involving AI-generated content in five experiments (N = 1705). In each experiment, participants read scenarios about a poet submitting someone else’s poem to a contest without credit. We compared three source types: a friend, ChatGPT, and a little-known poetry blog. In Experiments 1–3, participants judged plagiarism from the blog as more immoral than plagiarism from a friend or ChatGPT, with little difference between the latter two. Moral condemnation increased with the amount of content copied and remained stable when compared to other moral transgressions. In Experiments 4 and 5, moral judgments became harsher when human sources (friend or blog) denied permission, but not when ChatGPT did, suggesting that its refusal was not treated as morally meaningful. When all sources granted permission, differences between conditions disappeared. Overall, these findings support both the harm and false benefit accounts of why people condemn plagiarism. The findings also advance knowledge about how, and when, permission from the source affects condemnation of plagiarism.