Is ChatGPT a “fire of Prometheus” for non-native English-speaking researchers in academic writing?
Open accessAbstract
Large language models (LLMs) such as ChatGPT have garnered considerable interest for their potential to aid non-native English-speaking researchers. These models can function as personal, round-the-clock English tutors, akin to how Prometheus in Greek mythology bestowed fire upon humans for their advancement. LLMs can be particularly helpful for non-native researchers in writing the Introduction and Discussion sections of manuscripts, where they often encounter challenges. However, using LLMs to generate text for research manuscripts entails concerns such as hallucination, plagiarism, and privacy issues; to mitigate these risks, authors should verify the accuracy of generated content, employ text similarity detectors, and avoid inputting sensitive information into their prompts. Consequently, it may be more prudent to utilize LLMs for editing and refining text rather than generating large portions of text. Journal policies concerning the use of LLMs vary, but transparency in disclosing artificial intelligence tool usage is emphasized. This paper aims to summarize how LLMs can lower the barrier to academic writing in English, enabling researchers to concentrate on domain-specific research, provided they are used responsibly and cautiously.
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AI tools may support multilingual writers, novice coders, and students entering unfamiliar conceptual terrain; large language models could lower the barrier to academic writing in English and reduce inequalities faced by second-language scholars.
“On one hand, AI tools may support multilingual writers, novice coders, and students entering unfamiliar conceptual terrain; some scholars have argued that large language models could lower the barrier to academic writing in English and reduce inequalities faced by second-language scholars (Hwang et al., 2023).”
From From production to verification: generative AI, doctoral formation, and the leadership of digital education (2026) · cites this paper as Hwang et al., 2023
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Experimental evidence on the productivity effects of generative artificial intelligence
Noy, S., & Zhang, W. (2023) · Science · doi:10.1126/science.adh2586 · Cited by 2,150 · cited 1× · see citing works
“One recent study showed that the degree of productivity boost obtained by using ChatGPT was larger in weaker writers than more competent ones [14], which sends a hopeful message for researchers who have struggled in manuscript writing.”
BackgroundChatGPT listed as author on research papers: many scientists disapprove
Stokel-Walker, C. (2023) · Nature · doi:10.1038/d41586-023-00107-z · Cited by 868 · see citing works
Writing for scholarly publication in English: The case of Hong Kong
Flowerdew, J. (1999) · Journal of Second Language Writing · doi:10.1016/s1060-3743(99)80125-8 · Cited by 250 · see citing works
Bouville, M. (2008) · Science and Engineering Ethics · doi:10.1007/s11948-008-9057-6 · Cited by 132 · cited 1× · see citing works
“Also, using LLMs for text generation is also vulnerable to the traditional definition of plagiarism in which a certain number of consecutive words (usually ranging from five to seven) from the source text is used in a subsequent manuscript [17]), either with or without citation.”
MethodZielinski, C., Winker, M. A., Aggarwal, R., Ferris, L. E., Heinemann, M., Lapeña Jr, J. F., Pai, S. A., Ing, E., Citrome, L., Alam, M., et al. (2023) · Colombia Medica · doi:10.25100/cm.v54i3.5868 · Cited by 127 · see citing works
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Research works printed but not linked: 17
- [2]Cho DW Science journal paper writing in an EFL context: the case of Korea English Specif Purp 2009 28 230 239
- [5]Dong YR Non-native graduate students' thesis/dissertation writing in science: self-reports by students and their advisors from two U.S. institutions English Specif Purp 1998 17 369 390
- [9]Doskaliuk B Zimba O Beyond the keyboard: academic writing in the era of ChatGPT J Korean Med Sci 2023 38 e207 37401498 PMC10318197
- [10]Májovský M Černý M Kasal M Komarc M Netuka D Artificial intelligence can generate fraudulent but authentic-looking scientific medical articles: Pandora's box has been opened J Med Internet Res 2023 25 e46924 37256685 PMC10267787
- [12]Salvagno M Taccone FS Gerli AG Can artificial intelligence help for scientific writing? Crit Care 2023 27 75 36841840 PMC9960412
- [13]Altmäe S Sola-Leyva A Salumets A Artificial intelligence in scientific writing: a friend or a foe? Reprod Biomed Online 2023 47 3 9 37142479
- [15]Athaluri SA Manthena SV Kesapragada VSRKM Yarlagadda V Dave T Duddumpudi RTS Exploring the boundaries of reality: investigating the phenomenon of artificial intelligence hallucination in scientific writing through ChatGPT references Cureus 2023 15 e37432 37182055 PMC10173677
- [16]Brainard J As scientists explore AI-written text, journals hammer out policies accessed on August 14, 2023 Available at: https://www.science.org/content/article/scientists-explore-ai-written-text-journals-hammer-policies
- [23]Miller K Gunn E Cochran A Burstein H Friedberg JW Wheeler S Use of large language models and artificial intelligence tools in works submitted to Journal of Clinical Oncology J Clin Oncol 2023 41 3480 3481 37200609
- [25]Kaiser J Science funding agencies say no to using AI for peer review accessed on August 8, 2023 Available at: https://www.science.org/content/article/science-funding-agencies-say-no-using-ai-peer-review
- [26]JAMA Instructions for authors accessed on August 8, 2023 Available at: https://jamanetwork.com/journals/jama/pages/instructions-for-authors
- [27]Park SH Use of generative artificial intelligence, including large language models such as ChatGPT, in scientific publications: policies of KJR and prominent authorities Korean J Radiol 2023 24 715 718 37500572 PMC10400373
- [28]Tools such as ChatGPT threaten transparent science; here are our ground rules for their use Nature 2023 613 612 36694020
- [29]Nature For authors: initial submission accessed on July 10, 2023 Available at: https://www.nature.com/nature/for-authors/initial-submission
- [30]American Association for the Advancement of Science Science journals: editorial policies accessed on August 17, 2023 Available at: https://www.science.org/content/page/science-journals-editorial-policies
- [32]International Committee of Medical Journal Editors Recommendations accessed on August 17, 2023 Available at: https://www.icmje.org/recommendations PMC12093628 40704003
- [34]Vessal K Habibzadeh F Rules of the game of scientific writing: fair play and plagiarism Lancet 2007 369 641 17321306
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Monib, W. K., Qazi, A., & Mahmud, M. M. (2025) · Education and Information Technologies · doi:10.1007/s10639-024-13065-4 · Cited by 80 · see citing works
Shalong, W., Yi, Z., Bin, Z., Ganglei, L., Jinyu, Z., Yanwen, Z., Zequn, Z., Lianwen, Y., & Feng, R. (2025) · Medical Teacher · doi:10.1080/0142159x.2024.2413023 · Cited by 45 · see citing works
Yin, S., Huang, S., Xue, P., Xu, Z., Lian, Z., Ye, C., Ma, S., Liu, M., Hu, Y., Lu, P., et al. (2025) · BMC Medicine · doi:10.1186/s12916-025-03899-1 · Cited by 21 · see citing works
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Zhu, L., Lai, Y., Xie, J., Mou, W., Huang, L., Qi, C., Yang, T., Jiang, A., Gan, W., Zeng, D., et al. (2025) · Clinical and Translational Discovery · doi:10.1002/ctd2.70067 · Cited by 15 · see citing works
Cheng, H., Sheng, B., Lee, A., Chaudary, V., Atanasov, A. G., Liu, N., Qiu, Y., Wong, T. Y., Tham, Y.-C., & Zheng, Y. (2024) · doi:10.1101/2024.03.25.586710 · Cited by 15 · see citing works
Matsui, K. (2025) · Perspectives on Medical Education · doi:10.5334/pme.1929 · Cited by 6 · see citing works
Hsu, H.-Y., Hakouz, A., & Fotouhi, G. (2025) · AI and Ethics · doi:10.1007/s43681-025-00794-6 · Cited by 5 · see citing works
Lin, A., Chen, Z., Jiang, A., Tang, B., Qi, C., Zhu, L., Mou, W., Gan, W., Zeng, D., Xiao, M., et al. (2026) · International Journal of Surgery · doi:10.1097/js9.0000000000003839 · Cited by 2 · see citing works
Wu, E. (2026) · Frontiers in Education · doi:10.3389/feduc.2026.1890769 · Cited by 2 · see citing works
Hallucinations in large language models within academic contexts: A systematic review.
Lai, K. E., Mustaffa, N., Preece, C. N., & Wong, F. Y. (2026) · Journal of Science and Technology Policy Management · doi:10.1108/jstpm-01-2026-0015 · Cited by 1 · see citing works
- Authors
- Hwang, S. I., Lim, J. S., Lee, R. W., Matsui, Y., Iguchi, T., Hiraki, T., & Ahn, H.
- Affiliations
- Seoul National University (KR)
- Asan Medical Center (KR)
- Inha University (KR)
- Okayama University (JP)
- Corresponding author
- Lim, Joon Seo
- ORCID
- Venue
- Korean Journal of Radiology
- Publisher
- XMLink
- Published
- 2023
- Volume
- 24
- Issue
- 10
- Pages
- 952
- ISSN
- 1229-6929 (ISSN-L)
- 2005-8330
- PMC
- PMC10550740
- OpenAlex
- W4387029265
- Cited by
- 107
- References
- 5
- Citations by year
- 2026: 22 · 2025: 49 · 2024: 35 · 2023: 1
- FWCI
- 18.27
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Korean Journal of Radiology (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Funders
- Japan Society for the Promotion of Science (22K07772)
- Topics
- Social Sciences › Arts and Humanities › History and Philosophy of Science › Academic Writing and Publishing
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Keywords
- ChatGPT, large language models, non-native English speakers, academic writing, hallucinations, plagiarism, text similarity detection, English as a second language
- MeSH terms
- Artificial Intelligence, Humans, Writing
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