Hallucinated citations produced by generative artificial intelligence may constitute research misconduct when citations function as data in scholarly papers
What You Should Know
Generative AI can make research and learning easier—but easier isn’t always better. This peer-reviewed article examines how generative AI systems can hallucinate citations, producing references that are inaccurate, incomplete, or entirely fabricated. It also considers how relying on AI to generate answers, write essays, or solve problems may reduce the effort, productive struggle, and discovery that contribute to meaningful learning. The article argues that AI should complement human effort, not replace it, and that all AI-generated citations must be carefully verified against reliable sources.
Why should educators care? The goal of education is to help students develop the ability to think, research, write, solve problems, and learn independently. Typerighter helps institutions create environments where AI can be used within clear boundaries—supporting students when appropriate while encouraging source verification and protecting the human effort and learning that shouldn’t be outsourced. Typerighter can also partner with institutions to direct students toward trusted research support, recommending that they take advantage of key library services such as librarian consultations, database instruction, citation guidance, and help evaluating sources. By connecting AI-supported learning with these established resources, institutions can encourage students to verify information, strengthen their research skills, and make informed use of the library services available to them.
In this article, we discuss the growing problem of hallucinated citations produced by Generative Artificial Intelligence (GenAI) in scholarly research and writing. We argue that GenAI hallucinated citations might qualify as a provable instance of research misconduct under the U.S. federal regulations when a) the researcher uses a GenAI tool to produce hallucinated (i.e., nonexistent) citations for a research document; b) the citations function as data because they directly support research findings, as in, for example, review articles or bibliometric studies; and c) the researcher demonstrates indifference to the risk of fabrication of the data (i.e. citations) because they did not check the GenAI’s output for veracity and accuracy. Other types of problematic citations such as bibliometrically incorrect citations, or contextually inaccurate citations, are indicative of poor scholarship and irresponsible behavior, but do not qualify as research misconduct. Recognizing that GenAI hallucinated citations could be regarded as research misconduct in certain cases will hopefully encourage researchers to take this problem more seriously than they do now. In partnership with scientific institutions, funders and professional societies, the scholarly community should work on establishing, promoting, and enforcing standards for responsible use of AI in research, including standards pertaining to citation practices. [Read the full article.]