Nonhuman “Authors” and Implications for the Integrity of Scientific Publication and Medical Knowledge
Open accessAbstract
Artificial intelligence (AI) technologies to help authors improve the preparation and quality of their manuscripts and published articles are rapidly increasing in number and sophistication.These include tools to assist with writing, grammar, language, references, statistical analysis, and reporting standards.Editors and publishers also use AI-assisted tools for myriad purposes, including to screen submissions for problems (eg, plagiarism, image manipulation, ethical issues), triage submissions, validate references, edit, and code content for publication in different media and to facilitate postpublication search and discoverability. 1 In November 2022, OpenAI released a new open source, natural language processing tool called ChatGPT. 2,3ChatGPT is an evolution of a chatbot that is designed to simulate human conversation in response to prompts or questions (GPT stands for "generative pretrained transformer").The release has prompted immediate excitement about its many potential uses 4 but also trepidation about potential misuse, such as concerns about using the language model to cheat on homework assignments, write student essays, and take examinations, including medical licensing examinations. 5n January 2023, Nature reported on 2 preprints and 2 articles published in the science and health fields that included ChatGPT as a bylined author. 6Each of these includes an affiliation for ChatGPT, and 1 of the articles includes an email address for the nonhuman "author."According to Nature, that article's inclusion of ChatGPT in the author byline was an "error that will soon be corrected." 6However, these articles and their nonhuman "authors" have already been indexed in PubMed and Google Scholar.Nature has since defined a policy to guide the use of large-scale language models in scientific publication, which prohibits naming of such tools as a "credited author on a research paper" because "attribution of authorship carries with it accountability for the work, and AI tools cannot take such responsibility." 7The policy also advises researchers who use these tools to document this use in the Methods or Acknowledgment sections of manuscripts. 7Other journals 8,9 and organizations 10 are swiftly developing policies that ban inclusion of these nonhuman technologies as "authors" and that range from prohibiting the inclusion of AI-generated text in submitted work 8 to requiring full transparency, responsibility, and accountability for how such tools are used and reported in scholarly publication. 9,10The International Conference on Machine Learning, which issues calls for papers to be reviewed and discussed at its conferences, has also announced a new policy: "Papers that include text generated from a large-scale language model (LLM) such as ChatGPT are
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Accountability in Research, JAMA, and Nature decided to adopt or pursue policies that allow using LLMs under conditions that promote transparency, accountability, fair assignment of credit, and honesty.
“While Accountability in Research, JAMA, and Nature decided to adopt or pursue policies that allow using LLMs under conditions that promote transparency, accountability, fair assignment of credit, and honesty, the editors of Science highlighted ethical problems created by LLMs and banned their use:”
From The ethics of disclosing the use of artificial intelligence tools in writing scholarly manuscripts (2023) · cites this paper as Flanagin et al., 2023
In the main text (page unavailable), the paper says JAMA updated its policies to require disclosure of AI-assisted writing and describes Nature’s policy requiring disclosure while barring AI tools from authorship credit. It does not identify Accountability in Research or establish its policy, and it does not explicitly describe honesty as a condition of these policies. (LLM, conf=0.85)
Experimental — accuracy not yet measuredMost publishers now allow AI tools for editing, readability, and grammar, often with disclosure.
“Most publishers now allow AI tools for editing, readability, and grammar often with disclosure.”
From Reimagining biomedical science workflows in the age of large language models (2026) · cites this paper as [29]
The paper’s main section says JAMA Network authors should disclose AI assistance with writing or editing, and it describes tools used for grammar and language. It does not establish that most publishers allow these uses; instead, it describes differing journal policies, including restrictions on AI-generated text. It also exempts basic grammar and spelling checks from JAMA’s disclosure requirement. No page number is available in our copy. (LLM, conf=0.86)
Experimental — accuracy not yet measuredJournals and funding agencies have introduced policies to guide responsible use of AI-assisted writing.
“As AI-assisted writing becomes more common, journals and funding agencies have introduced policies to guide responsible use [29][30][31] .”
From Reimagining biomedical science workflows in the age of large language models (2026) · cites this paper as [29]
The main text (page unavailable in our copy) says JAMA Network journals updated their policies for AI-assisted manuscript writing and describes policies at Nature and other journals. It does not identify funding agencies as having introduced such policies, so that part of the claim is unsupported. (LLM, conf=0.86)
Experimental — accuracy not yet measuredNearly all publishers agree that an LLM cannot be a co-author or bear responsibility for errors.
“While journal policies on AI use are evolving, nearly all publishers agree that an LLM cannot be a co-author or bear responsibility for errors 29 .”
From Reimagining biomedical science workflows in the age of large language models (2026) · cites this paper as [29]
In the main text (page not provided), the paper says Nature bars AI tools from credited authorship because they cannot take responsibility for the work, and that other journals and organizations are developing similar policies. It does not establish that nearly all publishers agree, so the claim overstates the breadth of that agreement. (LLM, conf=0.86)
Experimental — accuracy not yet measuredResearchers in recent publications struggle with how they should report text generation [69] and policies vary from banning text generation to mandatory labeling of AI-based text generation [32].
“Echoing this, researchers in recent publications struggle with how they should report text generation [69] and policies vary from banning text generation to mandatory labeling of AI-based text generation [32].”
From The AI Ghostwriter Effect: When Users do not Perceive Ownership of AI-Generated Text but Self-Declare as Authors (2024) · cites this paper as [32]
AI tools cannot be listed as authors, and human authors remain responsible for accuracy.
“AI tools cannot be listed as authors, and human authors remain responsible for accuracy.”
From Reimagining biomedical science workflows in the age of large language models (2026) · cites this paper as [29]
Transparency about the use of generative AI tools in the academic writing process is a cornerstone of academic integrity.
“Firstly, and perhaps most importantly, transparency about the use of generative AI tools in the academic writing process is a cornerstone of academic integrity [7, 9, 11].”
From Artificial intelligence-assisted academic writing: recommendations for ethical use (2025) · cites this paper as [7]
The International Committee of Medical Journal Editors, JAMA Network Journals, and the World Association of Medical Editors have all issued specific guidelines on the use of generative AI.
“Further, and especially relevant to the work of academic writers in healthcare simulation, the International Committee of Medical Journal Editors [10], JAMA Network Journals [7], and the World Association of Medical Editors [11] have all issued specific guidelines on the use of generative AI.”
From Artificial intelligence-assisted academic writing: recommendations for ethical use (2025) · cites this paper as [7]
Generative AI tools do not meet the generally agreed standards of authorship of academic research.
“Another core principle reflected in these statements is that, despite their ability to generate novel and new text, generative AI tools do not meet the generally agreed standards of authorship of academic research [7, 9, 11, 12].”
From Artificial intelligence-assisted academic writing: recommendations for ethical use (2025) · cites this paper as [7]
Generative AI tools have the ability to produce novel written content on their own.
“Unlike these previous tools, however, generative AI tools have introduced a challenge to traditional notions of academic integrity: rather than simply helping researchers more efficiently conduct or complete research tasks, generative AI tools now have the ability to produce novel written content on their own [5–8].”
From Artificial intelligence-assisted academic writing: recommendations for ethical use (2025) · cites this paper as [7]
ChatGPT is based on a transformer architecture that uses introspection mechanisms to capture long-range dependencies between words and sentences and to generate coherent and contextual responses.
“The model is based on a transformer architecture that uses introspection mechanisms to capture long-range dependencies between words and sentences and to generate coherent and contextual responses.23)”
From Application of ChatGPT for Orthopedic Surgeries and Patient Care (2024) · cites this paper as [23]
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Cites
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Self-citationEXPOSITION AS APPLIED TO MEDICINE
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Flagged first, then by citations
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- Fourth International Conference on Machine Learning. Clarification on large language model policy LLM. Accessed January 26, 2023. https:// icml.cc/Conferences/2023/llm-policy
- Davis P. Did ChatGPT just lie to me? Scholarly Kitchen blog. January 13, 2023. Accessed January 25, 2023. https://scholarlykitchen.sspnet.org/ 2023/01/13/did-chatgpt-just-lie-to-me/ 13. Carpenter TA. Thoughts on AI's impact on scholarly communications? an interview with ChatGPT. Scholarly Kitchen blog. January 11, 2023. Accessed January 25, 2023. https:// scholarlykitchen.sspnet.org/2023/01/11/chatgpt- thoughts-on-ais-impact-on-scholarly- communications/ 14. Kendrick CL. Guest post-the efficacy of ChatGPT: is it time for the librarians to go home? Scholarly Kitchen blog. January 26, 2023. Accessed January 26, 2023. https://scholarlykitchen.sspnet. org/2023/01/26/guest-post-the-efficacy-of- chatgpt-is-it-time-for-the-librarians-to-go-home/? informz=1&nbd=411f2c31-57eb-46fb-a55c- 93d4b350225a&nbd_source=informz 15. Instructions for Authors. JAMA. Updated January 30, 2023. Accessed January 30, 2023. https://jamanetwork.com/journals/jama/pages/ instructions-for-authors
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- Authors
- Flanagin, A., Bibbins-Domingo, K., Berkwits, M., & Christiansen, S. L.
- Affiliations
- Ms Flanagin is Executive Managing Editor, Dr Bibbins-Domingo is Editor in Chief, and Dr Berkwits is Electronic Editor, JAMA and the JAMA Network, and Ms Christiansen is Managing Editor, JAMA
- Corresponding author
- Flanagin, Annette
- Venue
- JAMA
- Publisher
- American Medical Association (AMA)
- Published
- 2023-02-28
- Volume
- 329
- Issue
- 8
- Pages
- 637
- ISSN
- 0002-9955 (ISSN-L)
- 0098-7484
- OpenAlex
- W4318671267
- Cited by
- 420
- References
- 10
- Citations by year
- 2026: 67 · 2025: 77 · 2024: 109 · 2023: 164 · 2022: 1 · 2020: 1
- FWCI
- 104.11
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- JAMA (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Social Sciences › Safety Research › Academic integrity and plagiarism
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Social Sciences › Decision Sciences › Information Systems and Management › Academic Publishing and Open Access
- Keywords
- ChatGPT, large language models, AI-generated text, authorship attribution, artificial intelligence in medical education, medical licensing examinations, AI ethics, plagiarism, generative AI in research, journal editorial policy
- MeSH terms
- Authorship, Medicine, Publications, Publishing, Software, Scientific Misconduct, Knowledge, Knowledge Bases
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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