An Emerging Issue in Journal Publishing: The Use of Artificial Intelligence to Generate Letters to the Editor
Letters to the editor (letters) of journals are a common means to advance scholarly conversations, and most biomedical journals include letters as publications that are indexed in Medline and related indices.With the advent of artiZcial intelligence (AI), and its ability to rapidly summarize text and compose "human-sounding" manuscripts, it is now possible for people to generate many letters by systematically combing the literature for new papers, having AI critique the text, and generating letters to the editor.Anecdotally, concern about this phenomenon has been a topic of discussion among journal editors, and a recent story in The New York Times, along with a study published on a preprint server, has highlighted the scope of the issue.At the PRiMER journal, the editorial team encountered such an instance in the summer of 2025, and believe it important to report to the Zeld, in advance of what may be an emerging problem.As a group, the editorial management team of PRiMER (the editor in chief [EiC], associate editors [AEs], and the production manager), wish to share our recent experience with an AI-generated letter.A letter was submitted that commented on a paper that had been published a few weeks prior, and immediately caught the attention of the EiC, as it was critical and incisive beyond what is normally seen following peer and editorial review and publication.While many letters will draw out a speciZc issue, or add a perspective, this particular submission seemed to be more of a
Authors
- Julie Phillips (ORCID: https://orcid.org/0000-0001-5566-2384)
- Sam Grammer
- Jacob Prunuske (ORCID: https://orcid.org/0000-0001-5638-5227)
- Joel J. Heidelbaugh
- Christopher P. Morley (ORCID: https://orcid.org/0000-0003-0185-7148)
- Andrea Wendling (ORCID: https://orcid.org/0000-0001-5136-6465)
- Amy L. Lee (ORCID: https://orcid.org/0000-0001-7956-4746)
- Amanda Kost (ORCID: https://orcid.org/0000-0002-2385-5293)
- Tyler Barreto (ORCID: https://orcid.org/0000-0002-9636-3230)
- John W. Epling (ORCID: https://orcid.org/0000-0001-9445-8669)
- Kristen L. Bene
Institutions
- Tufts University (US)
- University of South Dakota (US)
- University of Washington (US)
- SUNY Upstate Medical University (US)
- University of Michigan (US)
- University of Colorado Health (US)
- Society of Teachers of Family Medicine (US)
- Family Support Network (US)
- Western Washington University (US)
- Carilion Clinic (US)
- Virginia Tech (US)
- Michigan State University (US)
Publication Details
- Journal
- PRiMER
- Published
- 2025-11-14
- DOI
- https://doi.org/10.22454/primer.2025.391630
- Citations
- 2
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 1.31