Policy consensus, disagreements, and gaps regarding the use of artificial intelligence in authors, reviewers, publishers, editors, readers, and scholarship dissemination: a narrative review focus on medical scholarly publishing, analyzing attitudes of 6 institutions, 8 publishers, 139 journals and hundreds of articles
- 1Editorial Office, AME Publishing Company, Hong Kong, China
Abstract
Background and Objective: Artificial intelligence (AI) integration in medical publishing has improved efficiency but raised ethical controversies. Lacking systematic comparisons on AI-use polices across roles, this narrative review aims to summarize existing consensus, major disagreements, and policy gaps to guide future AI policy updates.
Methods: We comprehensively searched English and Chinese literature from 2016 to Jan 12, 2026 in Web of Science, PubMed, Scopus, EMBASE, and CNKI, and analyzed AI polices from 6 major organizations up to Jun 15, 2026, 8 top publishers up to Mar 1, 2026, and 139 stratified randomly sampled journals up to Apr 10, 2026, covering 25 publishing sub-scenarios.
Key Content and Findings: (I) Core consensus: clear agreement exists on confidentiality, disclosure of AI use, human verification and accountability, and the ineligibility of AI authorship. (II) Authors: AI is permitted for language polishing, translation, formatting, structural layout, literature searching, methodology, and study design. However, substantial disagreements remain regarding data collection, extraction, analysis and statistics, figure/table preparation, and manuscript writing among institutions, publishers, and scholars. Idea generation and downstream activities like revision and response letter drafting remain policy gaps. (III) Reviewers: AI is strictly prohibited from independent decision-making. However, disagreements persist regarding using AI to generate or optimize review comments. Checking revisions and response letters remains a policy gap. (IV) Editors/publishers: large policy gaps exist. Limited polices tend to prohibit AI from independent decisions while permit to select reviewers and draft/refine editorial comments. However, substantial disagreements remain over using AI for technical/compliance checks and content/substantive review. (V) Readers/dissemination: policies are largely absent. Available rules show a positive attitude toward readers using AI to translate and exact key points, and disseminators using AI to generate social media content and visualizations.
Conclusions: While current AI policies have reached consensus in many scenarios, substantial gaps and disagreements for editors, publishers, and readers must be prioritized in future updates. Future revisions should enhance specificity, scenario-based design, clarity, and accessibility.
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BibTeX
@article{xie2026policy,
title = {{Policy consensus, disagreements, and gaps regarding the use of artificial intelligence in authors, reviewers, publishers, editors, readers, and scholarship dissemination: a narrative review focus on medical scholarly publishing, analyzing attitudes of 6 institutions, 8 publishers, 139 journals and hundreds of articles}},
author = {Shaoxia Xie and Binghan Shang and Yue Hu and Fangyuan Jiang and Yijie Chen and Kaiping Zhang},
journal = {Annals of Translational Medicine},
year = {2026},
month = oct,
doi = {10.21037/atm-2026-0169},
url = {https://doi.org/10.21037/atm-2026-0169},
note = {CC BY-NC-ND 4.0},
}
RIS
TY - JOUR
TI - Policy consensus, disagreements, and gaps regarding the use of artificial intelligence in authors, reviewers, publishers, editors, readers, and scholarship dissemination: a narrative review focus on medical scholarly publishing, analyzing attitudes of 6 institutions, 8 publishers, 139 journals and hundreds of articles
AU - Shaoxia Xie
AU - Binghan Shang
AU - Yue Hu
AU - Fangyuan Jiang
AU - Yijie Chen
AU - Kaiping Zhang
PY - 2026
DA - 2026/10/16
JO - Annals of Translational Medicine
DO - 10.21037/atm-2026-0169
UR - https://doi.org/10.21037/atm-2026-0169
AB - Background and Objective: Artificial intelligence (AI) integration in medical publishing has improved efficiency but raised ethical controversies. Lacking systematic comparisons on AI-use polices across roles, this narrative review aims to summarize existing consensus, major disagreements, and policy gaps to guide future AI policy updates. Methods: We comprehensively searched English and Chinese literature from 2016 to Jan 12, 2026 in Web of Science, PubMed, Scopus, EMBASE, and CNKI, and analyzed AI polices from 6 major organizations up to Jun 15, 2026, 8 top publishers up to Mar 1, 2026, and 139 stratified randomly sampled journals up to Apr 10, 2026, covering 25 publishing sub-scenarios. Key Content and Findings: (I) Core consensus: clear agreement exists on confidentiality, disclosure of AI use, human verification and accountability, and the ineligibility of AI authorship. (II) Authors: AI is permitted for language polishing, translation, formatting, structural layout, literature searching, methodology, and study design. However, substantial disagreements remain regarding data collection, extraction, analysis and statistics, figure/table preparation, and manuscript writing among institutions, publishers, and scholars. Idea generation and downstream activities like revision and response letter drafting remain policy gaps. (III) Reviewers: AI is strictly prohibited from independent decision-making. However, disagreements persist regarding using AI to generate or optimize review comments. Checking revisions and response letters remains a policy gap. (IV) Editors/publishers: large policy gaps exist. Limited polices tend to prohibit AI from independent decisions while permit to select reviewers and draft/refine editorial comments. However, substantial disagreements remain over using AI for technical/compliance checks and content/substantive review. (V) Readers/dissemination: policies are largely absent. Available rules show a positive attitude toward readers using AI to translate and exact key points, and disseminators using AI to generate social media content and visualizations. Conclusions: While current AI policies have reached consensus in many scenarios, substantial gaps and disagreements for editors, publishers, and readers must be prioritized in future updates. Future revisions should enhance specificity, scenario-based design, clarity, and accessibility.
SN - 2305-5839
SN - 2305-5847
ER -