ETIKA DAN RISIKO KECERDASAN ARTIFISIAL GENERATIF: IMPLIKASI DALAM PENDIDIKAN AGAMA ISLAM DAN MASYARAKAT DIGITAL

Authors

  • Shokhibul Mighfar Universitas Ibrahimy
  • Moh. Hafid Universitas Ibrahimy
  • Iklilah Qotrinnada World Moslem Studies Center

DOI:

https://doi.org/10.35316/edupedia.v10i2.7588

Keywords:

Generative AI, IRE, Ethics, Educational Technology, Artificial Intelligence

Abstract

Generative Artificial Intelligence (AI) has increasingly influenced educational practices, including Islamic Religious Education (IRE), by enabling automated content creation, AI-based assessment, and adaptive learning. However, its use also raises ethical concerns related to transparency, fairness, copyright, religious misinformation, data bias, and student privacy. This article critically examines the concepts, implementation, ethical dimensions, and potential risks of generative AI in education, with particular attention to its relevance within IRE. Employing a systematic literature review of indexed academic publications, international policy reports, and ethical frameworks for AI in education, the study finds that generative AI can serve as an effective supportive technology for IRE when used responsibly and grounded in core Islamic values, including trustworthiness (amanah), justice (‘adl), honesty (ṣidq), and public interest (maṣlaḥah). The findings reaffirm the central role of IRE teachers as moral guides, interpreters of Islamic teachings, and pedagogical decision-makers, while positioning generative AI as an assistive tool that enhances learning rather than replacing the educator’s moral and spiritual authority. This study contributes both theoretically and practically to the development of ethical, inclusive, and context-sensitive policies and practices for the use of generative AI in Islamic Religious Education.

References

AlAli, R., Wardat, Y., Al-Saud, K., & Alhayek, K. (2024). Generative AI in Education: Best Practices for Successful Implementation. International Journal of Religion, 5(9). https://doi.org/10.61707/pkwb8402.

AI Dungeon (2019). AI Dungeon (interactive text adventure). Latitude

Binns, R. (2018). Fairness in machine learning: Lessons from political philosophy. Proceedings of the 2018 Conference on Fairness, Accountability and Transparency. https://proceedings.mlr.press/v81/binns18a.html

Brown, T. et al. (2020). Language Models are Few-Shot Learners. arXiv preprint arXiv:2005.14165. Carlini, N., Tramer, F., Wallace, E., Jagielski, M., Herbert-Voss, A., Lee, K., ... & Erlingsson, U.

(2021). Extracting Training Data from Large Language Models. USENIX Security

Symposium.

Creswell, J. W. (2014). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches. Sage Publications.

Davoodifard, M., & Eskin, D. (2024). Exploring the Role of Generative AI in Second Language Education: Insights for Instruction, Learning, and Assessment. Studies in Applied Linguistics & TESOL,

24(1). https://doi.org/10.52214/salt.v24i1.12863

Dicoding Indonesia (2025), Belajar Dasar Artificial Intellegency, Decoding Academy.

Direktorat Jenderal Guru, Tenaga Kependidikan dan Pendidikan Guru Kementerian Pendidikan Dasar dan Menengah (2025) Modul 4 Pemrograman Kecerdasan Artifisial, (Bimbingan Teknis Guru Koding dan Kecerdasan Artifisial Jenjang SMA/SMK)

Floridi, L., & Cowls, J. (2019). A Unified Framework of Five Principles for AI in Society. Harvard Data Science Review.

Floridi, L., et al. (2018). AI4People—An ethical framework for a good AI society. Minds and Machines, 28(4). https://doi.org/10.1007/s11023-018-9482-5

Gebru, T. et al. (2018). Datasheets for Datasets. arXiv preprint arXiv:1803.09010.

Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., ... & Bengio, Y. (2014). Generative adversarial nets. Advances in Neural Information Processing Systems, 27. https://papers.nips.cc/paper_files/paper/2014

Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep Learning. Cambridge, MA: MIT Press

LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. Nature, 521(7553). https://doi.org/10.1038/nature14539

Meechan, D. (2024). Generative AI for Students: The Essential Guide to Using Artificial Intelligence for Study at University. London: Sage.

Mehrabi, N., Morstatter, F., Saxena, N., Lerman, K., & Galstyan, A. (2021). A Survey on Bias and Fairness in Machine Learning. ACM Computing Surveys, 54(6). https://doi.org/10.1145/345760

Miles, M. B., & Huberman, A. M. (2014). Qualitative Data Analysis. Sage Publications.

Minhaji, Kawakip, A. N., Nawafil, M., Asmuki, & Junaidi. (2025). Developing an Integrated E- Module on Religious Moderation to Address Rising Radicalism in Schools: Implications for Students’ Understanding. Jurnal Pendidikan Agama Islam, 22(2), 363–384. https:

/doi.org/10.14421/jpai.v22i2.11869

Mitchell, Tom M. (1997), Machine Learning. New York: McGraw-Hill

OECD. (2019). OECD Principles on Artificial Intelligence. Paris: OECD Publishing.

Russell, S., & Norvig, P. (2021). Artificial Intelligence: A Modern Approach (4th ed.). Harlow: Pearson Education Limited.

Samuelson, P. (2021). Generative AI and Copyright Law. Berkeley Technology Law Journal.

Sibuea, N., Suwianto, P., Rinanda, T., et al. (2024). Pemanfaatan Panduan Praktis Generative AI untuk Efektivitas Pembelajaran di Perguruan Tinggi. Jurnal PKM – Journal Liaison Academia and Society (J-LAS), 4(4)

Sinha, A., Goyal, S., Sy, Z., et al. (2024). BoilerTAI: A Platform for Enhancing Instruction Using Generative AI in Educational Forums. arXiv preprint arXiv:2409.13196

Stanford HAI. (2024). View of The Psychosocial Impacts of Generative AI Harms. Stanford University. Sugiyono. (2020). Metode Penelitian Kualitatif. Alfabeta.

Teaching AI Best Practices. (2024). University of Florida AI Initiative.

The Alan Turing Institute. (2024). Generative Artificial Intelligence in Education: Opportunities and Challenges. London: Turing Institute.

Undang-undang Nomor 27 tahun 2022 tentang Perlindungan Data Pribadi

UNESCO. (2023). Guidance for Generative AI in Education and Research. Paris: United Nations Educational, Scientific and Cultural Organization

University of Florida. (2024). Teaching AI: Best Practices. University of Florida AI Initiative. VanLehn, K. (2011). The Relative Effectiveness of Human Tutoring, Intelligent Tutoring Systems,

and Other Tutoring Systems. Educational Psychologist, 46(4).

https://doi.org/10.1080/00461520.2011.611369

Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., ... & Polosukhin, I. (2017). Attention is all you need. Advances in Neural Information Processing Systems, 30.

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Published

30-01-2026

How to Cite

Mighfar, S., Hafid, M., & Qotrinnada, I. (2026). ETIKA DAN RISIKO KECERDASAN ARTIFISIAL GENERATIF: IMPLIKASI DALAM PENDIDIKAN AGAMA ISLAM DAN MASYARAKAT DIGITAL. Edupedia : Jurnal Studi Pendidikan Dan Pedagogi Islam, 10(2), 275–294. https://doi.org/10.35316/edupedia.v10i2.7588