The European Educational Researcher

AI in Academia – Balancing between Effectiveness and Responsibility

The European Educational Researcher, Online-First Articles, pp. 25-32
OPEN ACCESS VIEWS: 235 DOWNLOADS: 65 Publication date: 15 Oct 2025
ABSTRACT
In this article, I examine how Generative AI (GenAI) is shaping the contemporary academic landscape through an overview of the most widely discussed themes. I focus not only on emerging opportunities and risks for academic work, including research, writing, and publishing, with particular attention to academic integrity, authorship, and scholarly voice, but also on the broader ethical implications of AI. I make a case for more awareness, reflection, and criticality and emphasise that the significance of AI goes beyond pragmatic concerns over productivity, effectiveness, and clarity as the topic is inherently tied to broader fundamental issues of ethics and social justice in both in the real world and global academic knowledge construction. This points to the shared responsibility of both developers and users of AI.
KEYWORDS
Generative AI, Writing for Research and Publication Purposes, Academic Publishing, Ethics
CITATION (APA)
Károly, A. (2025). AI in Academia – Balancing between Effectiveness and Responsibility. The European Educational Researcher. https://doi.org/10.31757/euer.832
REFERENCES
  1. Aczel, B., Barwich, A.-S., Diekman, A. B., Fishbach, A., Goldstone, R. L., Gomez, P., Gundersen, O. E., Von Hippel, P. T., Holcombe, A. O., Lewandowsky, S., Nozari, N., Pestilli, F., & Ioannidis, J. P. A. (2025). The present and future of peer review: Ideas, interventions, and evidence. Proceedings of the National Academy of Sciences, 122(5), e2401232121. https://doi.org/10.1073/pnas.2401232121
  2. Anson, C., & Straume, I. (2022). Amazement and trepidation: Implications of AI-based natural language production for the teaching of writing. Journal of Academic Writing, 12(1), 1–9. https://doi.org/10.18552/joaw.v12i1.820
  3. Arenas-Castro, H., Berdejo-Espinola, V., Chowdhury, S., Rodríguez-Contreras, A., James, A. R. M., Raja, N. B., Dunne, E. M., Bertolino, S., Emidio, N. B., Derez, C. M., Drobniak, S. M., Fulton, G. R., Henao-Diaz, L. F., Kaur, A., Kim, C. J. S., Lagisz, M., Medina, I., Mikula, P., Narayan, V. P., … Amano, T. (2024). Academic publishing requires linguistically inclusive policies. Proceedings of the Royal Society B: Biological Sciences, 291(2018), 20232840. https://doi.org/10.1098/rspb.2023.2840
  4. Bauer, E., Greiff, S., Graesser, A. C., Scheiter, K., & Sailer, M. (2025). Looking beyond the hype: Understanding the effects of AI on learning. Educational Psychology Review, 37(2), 45. https://doi.org/10.1007/s10648-025-10020-8
  5. Belcher, D. (2024). The promising and problematic potential of generative AI as a leveler of the publishing playing field. Journal of English for Research Publication Purposes, 5(1–2), 93–105. https://doi.org/10.1075/jerpp.00025.bel
  6. Botes, E., Dewaele, J.-M., Colling, J., & Teuber, Z. (2025). Initial indications of generative AI writing in linguistics research publications. PsyArXiv. https://doi.org/10.31234/osf.io/4yvbp_v1
  7. Güneş, A., & Kaban, A. L. (2025). A Delphi study on ethical challenges and ensuring academic integrity regarding AI research in higher education. Higher Education Quarterly, 79(4), e70057. https://doi.org/10.1111/hequ.70057
  8. Ithaka S+R (2025, August 1). Generative AI Licensing Agreement Tracker. https://sr.ithaka.org/our-work/generative-ai-licensing-agreement-tracker/
  9. Jenks, C. (2025). Communicating the cultural other: Trust and bias in generative AI and large language models. Applied Linguistics Review, 16(2), 787–795. https://doi-org.ezproxy.jyu.fi/10.1515/applirev-2024-0196
  10. Jones, R. H. (2025, July 3–7). Going mindfully meta: The place of language education in an AI powered world [Keynote address]. International Summit on the Use of AI in Learning and Teaching Language and Other Subjects, Hong Kong Polytechnic University. http://dx.doi.org/10.13140/RG.2.2.23830.46406
  11. Kosmyna, N., Hauptmann, E., Yuan, Y. T., Situ, J., Liao, X.-H., Beresnitzky, A. V., Braunstein, I., & Maes, P. (2025). Your brain on ChatGPT: Accumulation of cognitive debt when using an AI assistant for essay writing task. arXiv. https://doi.org/10.48550/arXiv.2506.08872
  12. Kuteeva, M., & Andersson, M. (2024). Diversity and standards in writing for publication in the age of AI—Between a rock and a hard place. Applied Linguistics, 45(3), 561–567. https://doi.org/10.1093/applin/amae025
  13. Lepp, H., & Smith, D. S. (2025). “You cannot sound like GPT”: Signs of language discrimination and resistance in computer science publishing. FAccT '25: Proceedings of the 2025 ACM Conference on Fairness, Accountability, and Transparency, 3162–3181. https://doi.org/10.1145/3715275.3732202
  14. Lund, B. (2024). Large Language Models are a democratizing force for researchers: A call for equity and inclusivity in journal publishers’ AI policies. InfoScience Trends, 1(1), 4–7. https://doi.org/10.61186/IST.202401.01.02
  15. Lund, B. D., Lee, T. H., Mannuru, N. R., & Arutla, N. (2025). AI and academic integrity: Exploring student perceptions and implications for higher education. Journal of Academic Ethics, 23(3), 1545–1565. https://doi.org/10.1007/s10805-025-09613-3
  16. Makransky, G., Shiwalia, B. M., Herlau, T., & Blurton, S. (2025). Beyond the “Wow” Factor: Using Generative AI for Increasing Generative Sense-Making. Educational Psychology Review, 37(3), 60. https://doi.org/10.21203/rs.3.rs-5622133/v1
  17. Moorhouse, B. L., Consoli, S., & Curle, S. M. (2025). Generative AI and the future of writing for publication: Insights from applied linguistics journal editors. Applied Linguistics Review. Advance online publication. https://doi.org/10.1515/applirev-2025-0021
  18. O’Regan, J. P., & Ferri, G. (2025). Artificial intelligence and depth ontology: Implications for intercultural ethics. Applied Linguistics Review, 16(2), 797–807. https://doi.org/10.1515/applirev-2024-0189
  19. Peters, U., & Chin-Yee, B. (2025). Generalization bias in large language model summarization of scientific research. Royal Society Open Science, 12(4), 241776. https://doi.org/10.1098/rsos.241776
  20. United Nations Environment Programme (2024). Artificial Intelligence (AI) end-to-end: The environmental impact of the full AI lifecycle needs to be comprehensively assessed. https://wedocs.unep.org/20.500.11822/46288.
  21. Wiley (2025). ExplanAItions: An AI study by Wiley. https://www.wiley.com/en-us/ai-study
  22. Yan, L., Pammer-Schindler, V., Mills, C., Nguyen, A., & Gašević, D. (2025). Beyond efficiency: Empirical insights on generative AI’s impact on cognition, metacognition and epistemic agency in learning. British Journal of Educational Technology, 56(5), 1675–1685. https://doi.org/10.1111/bjet.70000
LICENSE
Creative Commons License