How unique are hallucinated citations offered by generative Artificial Intelligence models?
For researchers and academics, this study quantifies the recurrence and patterns of hallucinated citations, revealing that current AI models still produce non-existent references at a non-trivial rate.
This paper analyzes hallucinated citations in generative AI, finding that nearly 30% of phantom references are duplicated and that 9.2% of references in AI-generated essays remain fabricated, highlighting persistent risks to academic integrity.
This paper investigates how generative AI produces and propagates hallucinated academic references, focusing on the recurring non-existent citation 'Education Governance and Datafication' attributed to Ben Williamson and Nelli Piattoeva. Drawing on 137 accessible source papers identified through Google Scholar and Google searches, the study analyses the structure, recurrence, and onward citation of this phantom reference. It shows that hallucinated citations are not random inventions but patterned recombinations of real authors, journals, dates, and keywords, with duplication occurring in nearly 30% of cases. The paper also reports a structured interrogation of ChatGPT 5-mini about how it generates citations and finds that, absent verification, the model reconstructs plausible references from learned patterns rather than factual recall. Finally, ten AI-generated essays on datafication and school governance were examined: while most references were genuine or partly accurate, 9.2% remained hallucinated, including an exact match to the most common phantom citation. The findings highlight ongoing risks to academic integrity and show that web-enabled AI still does not fully eliminate fabricated references.