When the Review Reads Too Well: Responding to AI-Generated Peer Review
You receive reviewer comments on a submitted manuscript that are polished and lengthy, but strikingly generic. The review offers broad recommendations without engaging meaningfully with the content. The style makes you wonder whether the review had been generated, or heavily drafted, by a large language model rather than reflecting independent expert assessment, although some comments are reasonable. What is the most ethically appropriate next step?
Authors
- Keshavamurthy Vinay (ORCID: https://orcid.org/0000-0001-6323-4988)
- Hitaishi Mehta (ORCID: https://orcid.org/0000-0002-7481-2330)
- Sejal V. Jain (ORCID: https://orcid.org/0000-0001-9175-6134)
Institutions
- Post Graduate Institute of Medical Education and Research (IN)
Publication Details
- Journal
- Clinical and Experimental Dermatology
- Published
- 2026-09-22
- DOI
- https://doi.org/10.1093/ced/llag422
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00