Ethical Use of Artificial Intelligence in Academic Journal Writing: A Systematic Review Analysis

The rapid adoption of generative artificial intelligence (AI), particularly since ChatGPT's launch in December 2022, has transformed academic journal writing while introducing significant ethical challenges to scholarly publishing. This systematic literature review (SLR), adhering to PRISMA 2020 guidelines, examined 44 peer-reviewed studies (2021-2025) to comprehensively assess the ethical dimensions of AI-assisted academic writing. Analysis reveals that 96.7% of reviewed literature expresses substantial ethical concerns related to AI use, including plagiarism risks, loss of originality, authorship ambiguity, and AI-generated hallucinations. With 66.7% of studies focusing explicitly on generative AI and a sharp increase in publications in 2025, these findings confirm the urgent relevance of this issue.
Key findings indicate a fundamental redefinition of academic authenticity in AI-mediated writing, alongside a critical gap between institutional policies and actual practices. Publisher analysis reveals that only 20-30% of major publishers maintain comprehensive AI policies, while 30-50% lack formal guidance, creating regulatory fragmentation. Technical detection safeguards remain inadequate, with real-world accuracy averaging 26% despite claimed 94-99% performance, and 60.9% of detection research employing fragmented methods. Notably, fewer than 26% of ethical recommendations are consistently implemented in practice, highlighting a persistent theory-practice gap.
The review identifies eight critical research gaps requiring urgent attention: robust verification methods, psychological factors in ethical decision-making, discipline-specific guidelines, longitudinal impact assessment, global harmonization frameworks, faculty AI literacy, institutional sustainability, and assessment method adaptation. Recommendations converge on an integrated, principle-based approach emphasizing mandatory transparency and disclosure of AI use, sustained ethics education and AI literacy, adaptive discipline-specific frameworks, and meaningful human oversight. Rather than relying solely on detection-based enforcement, the literature advocates transparency-based approaches and ethical literacy as more effective long-term solutions for ensuring academic integrity in the AI era.

Artificial Intelligence; Generative AI; ChatGPT

1. P. Ntsobi, “Challenges, benefits and recommendations for using generative artificial intelligence in academic writing – A case of ChatGPT,” MCET, Oct. 2024. doi: 10.55162/mcet.07.236. [Google Scholar] [Crossref]

2. I. Dergaa, K. Chamari, P. Mijewski, and H. B. Saad, “From human writing to artificial intelligence generated text: Examining the prospects and potential threats of ChatGPT in academic writing,” Biology of Sport, Jan. 2023. doi: 10.5114/biolsport.2023.125623. [Google Scholar] [Crossref]

3. B. D. Lund, T. Wang, N. R. Mannuru, B. Nie, S. Shimray, and Z. Wang, “ChatGPT and a new academic reality: Artificial intelligence-written research papers and the ethics of large language models in scholarly publishing,” J. Assoc. Inf. Sci. Technol., Mar. 2023. doi: 10.1002/asi.24750. [Google Scholar] [Crossref]

4. M. Sallam, “ChatGPT utility in healthcare education, research, and practice: Systematic review on the promising perspectives and valid concerns,” Healthcare, vol. 11, no. 6, Mar. 2023. doi: 10.3390/healthcare11060887. [Google Scholar] [Crossref]

5. D. Cotton, P. A. Cotton, and J. R. Shipway, “Chatting and cheating: Ensuring academic integrity in the era of ChatGPT,” Innov. Educ. Teach. Int., Mar. 2023. doi: 10.1080/14703297.2023.2190148. [Google Scholar] [Crossref]

6. M. Perkins, “Academic integrity considerations of AI large language models in the post-pandemic era: ChatGPT and beyond,” Univ. of Wollongong, Jan. 2023. doi: 10.53761/1.20.02.07. [Google Scholar] [Crossref]

7. M. Imran and N. Almusharraf, “Analyzing the role of ChatGPT as a writing assistant at higher education level: A systematic review of the literature,” Contemp. Educ. Technol., Aug. 2023. doi: 10.30935/cedtech/13605. [Google Scholar] [Crossref]

8. M. Liebrenz, R. Schleifer, A. Buadze, D. Bhugra, and A. Smith, “Generating scholarly content with ChatGPT: Ethical challenges for medical publishing,” Lancet Digit. Health, Feb. 2023. doi: 10.1016/S2589-7500(23)00019-5. [Google Scholar] [Crossref]

9. C. A. Gao et al., “Comparing scientific abstracts generated by ChatGPT to real abstracts with detectors and blinded human reviewers,” npj Digit. Med., Apr. 2023. doi: 10.1038/s41746-023-00819-6. [Google Scholar] [Crossref]

10. C. Ganjavi et al., “Publishers’ and journals’ instructions to authors on use of generative AI in academic and scientific publishing: A bibliometric analysis,” BMJ, Jan. 2024. doi: 10.1136/bmj-2023-077192. [Google Scholar] [Crossref]

11. R. Michel-Villarreal, E. L. Vilalta-Perdomo, D. E. Salinas-Navarro, R. Thierry-Aguilera, and F. S. Gerardou, “Challenges and opportunities of generative AI for higher education as explained by ChatGPT,” Educ. Sci., Aug. 2023. doi: 10.3390/educsci13090856. [Google Scholar] [Crossref]

12. J. Q. Liu et al., “The great detectives: Humans versus AI detectors in catching large language model-generated medical writing,” Int. J. Educ. Integrity, May 2024. doi: 10.1007/s40979-024-00155-6. [Google Scholar] [Crossref]

13. P. R. Krausman, Managing Artificial Intelligence. Wiley, Sep. 2023. doi: 10.1002/jwmg.22492. [Google Scholar] [Crossref]

14. U. Sodangi and A. Ismail, “Responsible integration of generative artificial intelligence in academic writing: A narrative review and synthesis,” J. Artif. Intell. Mach. Learn. Neural Netw., Jul. 2025. doi: 10.55529/jaimlnn.52.13.23. [Google Scholar] [Crossref]

15. C. K. Y. Chan and W. Hu, “Students’ voices on generative AI: Perceptions, benefits, and challenges in higher education,” Int. J. Educ. Technol. High. Educ., Jul. 2023. doi: 10.1186/s41239-023-00411-8. [Google Scholar] [Crossref]

16. Z. Chen et al., “Research integrity in the era of artificial intelligence: Challenges and responses,” Medicine, Jul. 2024. doi: 10.1097/MD.0000000000038811. [Google Scholar] [Crossref]

17. S.-J. Kim, “Research ethics and issues regarding the use of ChatGPT-like artificial intelligence platforms by authors and reviewers: A narrative review,” Sci. Editing, Aug. 2024. doi: 10.6087/kcse.343. [Google Scholar] [Crossref]

18. D. B. Resnik and M. Hosseini, “The ethics of using artificial intelligence in scientific research: New guidance needed for a new tool,” AI Ethics, May 2024. doi: 10.1007/s43681-024-00493-8. [Google Scholar] [Crossref]

19. J. Crawford, M. Cowling, and K. Allen, “Leadership is needed for ethical ChatGPT: Character, assessment, and learning using artificial intelligence,” Univ. of Wollongong, Mar. 2023. doi: 10.53761/1.20.3.02. [Google Scholar] [Crossref]

20. B. H. Nam and Q. Bai, “ChatGPT and its ethical implications for STEM research and higher education: A media discourse analysis,” Int. J. STEM Educ., Nov. 2023. doi: 10.1186/s40594-023-00452-5. [Google Scholar] [Crossref]

21. I. Mahama et al., “ChatGPT in academic writing: A threat to human creativity and academic integrity?” IJIAS, Oct. 2023. doi: 10.47540/ijias.v3i3.1005. [Google Scholar] [Crossref]

22. S. Diner, “The use and ethical implications of artificial intelligence in scientific research and academic writing,” Sep. 2024. doi: 10.14527/edure.2024.10. [Google Scholar] [Crossref]

23. Z. Koak, “Publication ethics in the era of artificial intelligence,” J. Korean Med. Sci., Jul. 2024. doi: 10.3346/jkms.2024.39.e249. [Google Scholar] [Crossref]

24. L. Yan et al., “Practical and ethical challenges of large language models in education: A systematic scoping review,” Brit. J. Educ. Technol., Aug. 2023. doi: 10.1111/bjet.13370. [Google Scholar] [Crossref]

25. F. Kamalov, D. S. Calonge, and I. Gurrib, “New era of artificial intelligence in education: Towards a sustainable multifaceted revolution,” Sustainability, Aug. 2023. doi: 10.3390/su151612451. [Google Scholar] [Crossref]

26. S. Grassini, “Shaping the future of education: Exploring the potential and consequences of AI and ChatGPT in educational settings,” Educ. Sci., Jul. 2023. doi: 10.3390/educsci13070692. [Google Scholar] [Crossref]

27. A. Munir, “Artificial intelligence and its transformative impact on scientific publishing,” IJP IHS, Feb. 2025. doi: 10.56536/ijpihs.v6i1.214. [Google Scholar] [Crossref]

28. E. S. Rentier, “To use or not to use: Exploring the ethical implications of using generative AI in academic writing,” AI Ethics, 2024. doi: 10.1007/s43681-024-00649-6. [Google Scholar] [Crossref]

29. S. Sabbaghan and S. E. Eaton, “Navigating the ethical frontier: Graduate students’ experiences with generative AI-mediated scholarship,” 2025. doi: 10.1007/s40593-024-00454-6. [Google Scholar] [Crossref]

30. M. Pantsar, “The need for ethical guidelines in mathematical research in the time of generative AI,” 2025. doi: 10.1007/s43681-025-00660-5. [Google Scholar] [Crossref]

31. P. Holzmann, P. Gregori, and E. J. Schwarz, “Students’ little helper: Investigating continuous-use determinants of generative AI and ethical judgment,” 2025. doi: 10.1007/s10639-025-13708-0. [Google Scholar] [Crossref]

32. C. D. Bobier and R. D. Hurst, “Artificial intelligence policies in bioethics and health humanities: A comparative analysis of publishers and journals,” 2025. doi: 10.1186/s12910-025-01239-9. [Google Scholar] [Crossref]

33. T. Knöchel et al., “Core principles of responsible generative AI usage in research,” 2025. doi: 10.1007/s43681-025-00768-8. [Google Scholar] [Crossref]

34. Y. Reina Marín et al., “Ethical challenges associated with the use of artificial intelligence in university education,” 2025. doi: 10.1007/s10805-025-09660-w. [Google Scholar] [Crossref]

35. M. M. Alnsour et al., “Artificial intelligence usage and ethical concerns among Jordanian university students,” 2025. doi: 10.1007/s40979-025-00206-6. [Google Scholar] [Crossref]

36. S. Bjelobaba et al., “Maintaining research integrity in the age of GenAI,” 2025. doi: 10.1007/s40979-025-00191-w. [Google Scholar] [Crossref]

37. M. M. Alnsour et al., “AI in education: Enhancing learning potential and addressing ethical considerations among academic staff,” 2025. doi: 10.1007/s40979-025-00189-4. [Google Scholar] [Crossref]

38. H. S. Sætra, “The rise of the research automaton: Science as process or product in the era of generative AI?” 2025. doi: 10.1007/s00146-025-02557-7. [Google Scholar] [Crossref]

39. S. Friederich and J. Symons, “Norms for academic writing in the era of advanced artificial intelligence,” 2023. doi: 10.1007/s44206-023-00079-7. [Google Scholar] [Crossref]

40. F. Lorenz et al., “Generative artificial intelligence in management research: A practical guide on mistakes to avoid,” 2024. doi: 10.1007/s11301-024-00469-2. [Google Scholar] [Crossref]

41. S. Ebadi et al., “Exploring the impact of generative AI on peer review: Insights from journal reviewers,” 2025. doi: 10.1007/s10805-025-09604-4. [Google Scholar] [Crossref]

42. Y. Reina Marín et al., “Ethical challenges associated with the use of artificial intelligence in university education,” 2025. doi: 10.1007/s10805-025-09660-w. [Google Scholar] [Crossref]

43. L. Lymar et al., “Academic misconduct and artificial intelligence use by medical students, interns and PhD students,” 2025. doi: 10.1186/s12909-025-08100-y. [Google Scholar] [Crossref]

44. B. H. Nam and Q. Bai, “ChatGPT and its ethical implications for STEM research,” 2023. doi: 10.1186/s40594-023-00452-5. [Google Scholar] [Crossref]

45. T. Mishra et al., “Use of large language models as AI tools in academic research and publishing among global clinical researchers,” 2024. doi: 10.1038/s41598-024-81370-6. [Google Scholar] [Crossref]

46. J. A. Teixeira da Silva and J. Wang, “Verification of AI use: A stakeholders’ perspective,” 2025. doi: 10.1007/s43681-025-00823-4. [Google Scholar] [Crossref]

47. V. J. Owan et al., “Acceptance and use of artificial intelligence for self-directed research learning among postgraduate students in Nigerian public universities,” 2025. doi: 10.1007/s44217-025-00770-6. [Google Scholar] [Crossref]

48. S. Karkoulian, N. Sayegh, and N. Sayegh, “ChatGPT unveiled: Understanding perceptions of academic integrity in higher education—A qualitative approach,” 2024. doi: 10.1007/s10805-024-09543-6. [Google Scholar] [Crossref]

49. M. Daoudi, “Ethical limits and suggestions for improving the use of AI in scientific research, academic publishing, and the peer review process,” 2025. doi: 10.1007/s44217-025-00696-z. [Google Scholar] [Crossref]

50. D. Mezzadri, “The paradox of ethical AI-assisted research,” 2025. doi: 10.1007/s10805-025-09671-7. [Google Scholar] [Crossref]

51. S. Bhattacharyya, “Designing research and publication ethics assignments for doctoral students in higher education institutes,” 2025. doi: 10.1007/s44217-025-00884-x. [Google Scholar] [Crossref]

52. H. Zwart et al., “Consortium authorship: Ethical tensions in emerging authorship practices in interdisciplinary collaborative research,” 2024. doi: 10.1007/s10805-024-09592-x. [Google Scholar] [Crossref]

53. J. Park, “Towards a transparent and reproducible AI-assisted research paper writing,” 2025. doi: 10.1186/s44342-025-00057-0. [Google Scholar] [Crossref]

54. L. Nannini et al., “Mapping the landscape of ethical considerations in explainable AI research,” 2024. doi: 10.1007/s10676-024-09773-7. [Google Scholar] [Crossref]

55. L. A. Meyerson et al., “Quantifying reviewer declines in scientific publishing: Twenty-one years of data,” 2025. doi: 10.1007/s10530-025-03679-1. [Google Scholar] [Crossref]

56. F. Richards and N. Harwood, “Proofreading student writing: A research-based stakeholder tool focused on ethical practice,” 2024. doi: 10.1007/s40979-024-00165-4. [Google Scholar] [Crossref]

57. M. Färber and L. Tampakis, “Analyzing the impact of companies on AI research based on publications,” 2023. doi: 10.1007/s11192-023-04867-3. [Google Scholar] [Crossref]

58. M. Thelwall and Z. Kurt, “Research evaluation with ChatGPT: Is it age, country, length, or field biased?” 2025. doi: 10.1007/s11192-025-05393-0. [Google Scholar] [Crossref]

59. G. Sertel, E. Karadag, and S. K. Ciftci, “Educational researchers’ perceptions of editorial ethics and attitudes in Turkish academic journals,” 2025. doi: 10.1007/s40979-025-00194-7. [Google Scholar] [Crossref]

60. R. W. Byard, “The art of peer reviewing,” 2024. doi: 10.1007/s12024-024-00905-5. [Google Scholar] [Crossref]

61. S. Bhattacharyya, N. Chatterjee, and A. Ramanathan, “Understanding the patterns and magnitude of life science publication retractions,” 2025. doi: 10.1007/s40979-025-00193-8. [Google Scholar] [Crossref]

62. B. Okuyan et al., “Research priorities of the European Society of Clinical Pharmacy,” 2025. doi: 10.1007/s11096-025-01954-8. [Google Scholar] [Crossref]

63. B. A. Sabel et al., “Fake publications in biomedical science: Red-flagging method indicates mass production,” 2025. doi: 10.1007/s00210-025-04275-9. [Google Scholar] [Crossref]

64. Z. Reza Khan, J. Priya, and C. Tuffnell, “Culture of integrity – Institutional response during COVID-19,” 2022. doi: 10.1007/s40979-022-00118-9. [Google Scholar] [Crossref]

65. M. Schmidt, J. K. McDonald, and S. Moore, “The research we don’t need will persist until we dismantle the systems that sustain it,” 2025. doi: 10.1007/s12528-025-09446-4. [Google Scholar] [Crossref]

66. M. H. Aljanahi and E. Y. Mahmoud, “I’m not guarding the dungeon: Faculty members’ perspectives on contract cheating in the UAE,” 2024. doi: 10.1007/s40979-024-00156-5. [Google Scholar] [Crossref]

67. M. Davis, “Examining and improving inclusive practice in institutional academic integrity policies,” 2022. doi: 10.1007/s40979-022-00108-x. [Google Scholar] [Crossref]

68. Z. Reza Khan et al., “Initiating count down – Gamification of academic integrity,” 2021. doi: 10.1007/s40979-020-00068-0. [Google Scholar] [Crossref]

69. S. Vaccino-Salvadore and R. Hall Buck, “Moving from plagiarism police to integrity coaches,” 2021. doi: 10.1007/s40979-021-00085-7. [Google Scholar] [Crossref]

70. M. Dadhich et al., “Why management papers face rejection? An advanced guide to publishing manuscripts in high-impact management journals,” 2025. doi: 10.1007/s11135-025-02221-8. [Google Scholar] [Crossref]

71. B. Krieger et al., “Are firms withdrawing from basic research? An analysis of firm-level publication behaviour in Germany,” 2021. doi: 10.1007/s11192-021-04147-y. [Google Scholar] [Crossref]

72. M. Senftleben et al., “Towards a European Research Freedom Act: A reform agenda for research exceptions in the EU copyright acquis,” 2025. doi: 10.1007/s40319-025-01604-6. [Google Scholar] [Crossref]

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