Generative AI ethics guidelines for academic writing
A content analysis of international publisher policies and a roadmap for the Indonesian context
Bibliographic Data
| ID | 22095102 |
|---|---|
| Authors | Lamhot Naibaho (0000-0001-9893-7165, Universitas Kristen Indonesia), Fahrus Zaman Fadhly (0000-0003-2004-8223, Universitas Kuningan), Taufiqulloh Taufiqulloh (0000-0001-7258-6037, Universitas Pancasakti Tegal), Ahdi Riyono (Muria Kudus University), Nur Alfayn Fathan Qarieba (Petro-Canada), Nur Fathiyya Zahira Mujahidah (Niğde Ömer Halisdemir Üniversitesi) |
| Year | 2026 |
| Volume | 16 |
| Issue | 1 |
| Pages | 16-28 |
| Publication date | 2026-05-25 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Indonesian Journal of Applied Linguistics (JOURNAL) |
| Journal identifiers | ISSN: 2301-9468 • E-ISSN: 2502-6747 |
| Publisher | Universitas Pendidikan Indonesia (UPI) (PUBLISHER) |
| DOI | 10.17509/9n6vsa84 |
| OpenAlex | W7167597051 |
| Language | EN |
The rapid rise of generative artificial intelligence (AI) tools such as ChatGPT and Grammarly has affected academic writing and literacy, a core concern in applied linguistics that encompasses genre conventions, authorial voice, and scholarly textual practices. While these tools enhance linguistic quality and efficiency, they pose ethical risks, including inadvertent plagiarism, reduced originality, and algorithmic bias. This study employs discourse analysis to examine AI ethics policies from five leading international publishers, Elsevier, Springer Nature, Wiley, Taylor & Francis, and SAGE. It focuses on how these policies linguistically construct norms of AI use through modality, lexical choice, and author accountability. Results reveal convergences (e.g., prohibition of AI as author, mandatory disclosure, human accountability) and divergences (e.g., Wiley’s documentation requirements, Springer’s confidentiality rules for reviewers, Taylor & Francis’ explicit mention of generative tools, and SAGE’s broader scope). This roadmap also advances applied linguistics research on GenAI and textual patterns, including corpus-based detection of AI-generated academic text in non-native English contexts. Recommendations include policy harmonization, editor training, and disclosure templates to ensure ethical integration of AI in scholarly publishing
Applied linguistics · Content analysis · Context (archaeology) · Discourse analysis · Documentation · Generative grammar · Indonesian · Quality (philosophy) · Academic integrity and plagiarism · Artificial Intelligence in Healthcare and Education · Ethics and Social Impacts of AI
| Highly cited | No |
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