Analysis of Retracted Publications on Artificial Intelligence: Trends, Ethical Concerns, and Scientific Integrity

Abstract

BACKGROUND: Artificial intelligence (AI) has promoted progress across various fields. The number of papers regarding AI has risen in recent years. This study examines retracted publications regarding AI by analyzing trends, journals, and reasons. METHODS: This descriptive cross-sectional study thoroughly investigated retracted AI-related papers listed in PubMed. The data extraction comprised bibliographic data, reasons for retraction, citation metrics, journal indexing status, and Altmetric Attention Scores (AASs). Retraction notices were classified according to particular reasons. Descriptive statistics were employed to evaluate retraction trends, geographic distribution, and citation impact. RESULTS: A total of 764 retracted AI-related papers were examined, with the most retractions occurring in 2023 (n = 667). China had the highest number (n = 551), followed by India (n = 40) and Bangladesh (n = 23). Journals focusing on mathematical and computational biology, neurosciences, and healthcare sciences had the most retractions. The most common retraction reasons were peer review issues (n = 716) and data concerns (n = 714), followed by irrelevant citations (n = 571) and unethical AI use (n = 238). The median time to retraction was 510 days (18-4,200). The median citation and AAS scores were (0-167) and 0 (0-191). CONCLUSION: The high number of retractions from China highlights the need for higher research standards. Deficits in peer review and data issues emerged as the main reasons for retraction, underscoring persistent challenges in maintaining research integrity and quality assurance. For scientific literature integrity, academic institutions, publishers, and researchers should stress transparency, ethics, and rigorous post-publication inspection.

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