{"doi":"10.1016/j.mcpdig.2023.10.002","title":"Equity in Scientific Publishing: Can Artificial Intelligence Transform the Peer Review Process?","abstract":"Chat Generative Pre-Trained Transformer (ChatGPT), a large language model developed by OpenAI, is gaining global recognition for its ability to read and perform writing tasks with human-like precision. Recently, this artificial intelligence (AI) tool has made important inroads into health care, helping streamline administrative tasks like writing referrals and previous authorizations, classifying skin conditions, and devising patient-specific care plans. Although ChatGPT has also been used as a research aid, largely underexplored are its potential applications in evaluating manuscripts for publication. Although there are inherent quality control concerns, using generative AI tools for peer review could rectify inequities in the research process and help create more inclusive scholarly discourse. Peer review, a cornerstone of academic research, is a labor-intensive endeavor. In 2020, reviewers spent 100 million hours, or 15,000 years, working on these reviews, summing up to 1.5 billion dollars of time for US-based reviewers alone.1Aczel B. Szaszi B. Holcombe A.O. A billion-dollar donation: estimating the cost of researchers’ time spent on peer review.Res Integr Peer Rev. 2021; 6: 14https://doi.org/10.1186/s41073-021-00118-2Crossref PubMed Google Scholar With no financial compensation, scholars often decline review requests, leading to a shortage of peer reviewers and the inflating time to publication. The predominant nonblinded peer review model also favors Western authors with established reputations, introducing bias against those from low-income and middle-income countries (LMICs).2Fox C.W. Meyer J. Aimé E. Double-blind peer review affects reviewer ratings and editor decisions at an ecology journal.Funct Ecol. 2023; 37: 1144-1157https://doi.org/10.1111/1365-2435.14259Crossref Scopus (14) Google Scholar These scholars’ work may be further dismissed because of surface-level differences, given that English may not be the primary language for some LMIC authors. The prominence of Western authors in premier journals often overshadows voices from less-resourced nations. This phenomenon is commonly referred to as academic ventriloquism.3Silverio S, Wilkinson C, Wilkinson S. Academic Ventriloquism: Tensions Between Inclusion, Representation, and Anonymity in Qualitative Research. Paper presented at: The British Psychological Society Qualitative Methods in Psychology conference; July 2022; Leicester, United Kingdom.Google Scholar This was particularly true during the COVID-19 pandemic, where Western perspectives dominated the global discourse despite disparate experiences among LMICs.4Benjamens S. de Meijer V.E. Pol R.A. Haring M.P.D. Are all voices heard in the COVID-19 debate?.Scientometrics. 2021; 126: 859-862https://doi.org/10.1007/s11192-020-03730-zCrossref PubMed Scopus (3) Google Scholar Limited contributions from resource-poor settings bearing a disproportionate disease burden highlight the need for broader academic discourse. Artificial intelligence models like ChatGPT could help mitigate some of these biases in academic publishing. For instance, AI can detect language errors by suggesting revisions to grammar, readability, and formatting discrepancies, pausing the submission, and allowing authors to make suggested edits. These services could be coupled with an AI-assisted author blinding process to ensure scientists properly leave their names off manuscripts and obscure identifying references. Allowing reviewers to focus more on the quality of the research question rather than superficial issues or who the authors are could help reduce review time and, thus, potentially, gender disparities in academic career advancement. Indeed, women accept review invitations more frequently than men,5Schmaling K.B. Blume A.W. Gender differences in providing peer review to two behavioural science journals, 2006-2015.Learn Publ. 2017; 30: 221-225https://doi.org/10.1002/leap.1104Crossref Scopus (5) Google Scholar diverting time toward this un","journal":"Mayo Clinic Proceedings Digital Health","year":2023,"id":353277,"datarank":0.4770510884564656,"base_score":2.1972245773362196,"endowment":2.1972245773362196,"self_citation_contribution":0.32958368660043297,"citation_network_contribution":0.14746740185603263,"self_endowment_contribution":0.32958368660043297,"citer_contribution":0.14746740185603263,"corpus_percentile":null,"corpus_rank":null,"citation_count":8,"citer_count":7,"citers_with_citation_signal":3,"citers_with_endowment":3,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.955,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":364568,"name":"Simar S. Bajaj","orcid":"0000-0002-8498-9674","position":1,"is_corresponding":false},{"id":233855,"name":"Fatima Cody Stanford","orcid":"0000-0003-4616-533X","position":2,"is_corresponding":false},{"id":4662,"name":"Leo Anthony Celi","orcid":"0000-0001-6712-6626","position":3,"is_corresponding":false},{"id":775111,"name":"Cameron Sabet","orcid":"0000-0003-2299-1426","position":0,"is_corresponding":true}],"reference_count":8,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-19T01:12:58.542950Z","pmid":"40206303","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}