Artificial Intelligence and Religious Policy: Ethical Governance in the Digital Public Sphere
DOI:
https://doi.org/10.61860/amuya.v2i2.122Keywords:
Algorithmic Governance, Artificial Intelligence, Digital Public Sphere, Religious Policy, Sociotechnical SystemsAbstract
Artificial intelligence increasingly mediates religious communication, knowledge, and participation in the digital public sphere, yet research remains fragmented across digital religion, human rights, and AI governance. This study examines how AI-mediated religious communication shapes authority, visibility, and participation; identifies associated ethical and rights-based concerns; and analyzes the institutional conditions relevant to its governance. Using a qualitative, non-experimental, exploratory-analytical design, the study draws on academic publications, policy documents, regulatory instruments, institutional guidelines, human-rights reports, and documented analyses of digital religious practices. Materials were purposively selected for substantive relevance and examined through structured reading and extraction, open and focused coding, thematic synthesis, source triangulation, and iterative cross-source comparison. The analysis identified three interconnected domains: access, visibility, and religious authority; religious freedom, inclusion, and algorithmic risks; and accountability, contestability, and institutional responsibility. AI-mediated technologies can broaden access to religious resources while simultaneously shaping the visibility and perceived authority of religious actors and interpretations. Expanded access can coexist with unequal representation, privacy risks, profiling, and constraints on meaningful participation, while distributed responsibility can create accountability gaps when consequential outcomes are difficult to explain or challenge. These relationships are context-dependent rather than predetermined effects of AI. By integrating sociotechnical and algorithmic-governance perspectives, the study provides an analytical framework for understanding ethical governance as the intersection of technological mediation, religious pluralism, fundamental rights, participation, and identifiable institutional responsibility.
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Alfrink, K., Keller, I., Kortuem, G., & Doorn, N. (2023). Contestable AI by design: Towards a framework. Minds and Machines, 33, 613–639. https://doi.org/10.1007/s11023-022-09611-z
Ashraf, C. (2022). Exploring the impacts of artificial intelligence on freedom of religion or belief online. The International Journal of Human Rights, 26(5), 757–791. https://doi.org/10.1080/13642987.2021.1968376
Batool, A., Zowghi, D., & Bano, M. (2025). AI governance: A systematic literature review. AI and Ethics, 5(3), 3265–3279. https://doi.org/10.1007/s43681-024-00653-w
Bowen, G. A. (2009). Document analysis as a qualitative research method. Qualitative Research Journal, 9(2), 27–40. https://doi.org/10.3316/QRJ0902027
Campbell, S., Greenwood, M., Prior, S., Shearer, T., Walkem, K., Young, S., Bywaters, D., & Walker, K. (2020). Purposive sampling: Complex or simple? Research case examples. Journal of Research in Nursing, 25(8), 652–661. https://doi.org/10.1177/1744987120927206
Carter, N., Bryant-Lukosius, D., DiCenso, A., Blythe, J., & Neville, A. J. (2014). The use of triangulation in qualitative research. Oncology Nursing Forum, 41(5), 545–547. https://doi.org/10.1188/14.ONF.545-547
Cheong, P. H., & Liu, L. (2025). Generative artificial intelligence and collaboration: Exploring religious human–machine communication and tensions in leadership practices. Human-Machine Communication, 11, 171–190. https://doi.org/10.30658/hmc.11.9
Coeckelbergh, M. (2025). Artificial intelligence, the common good, and the democratic deficit in AI governance. AI and Ethics, 5, 1491–1497. https://doi.org/10.1007/s43681-024-00492-9
Cohen, T., & Suzor, N. P. (2024). Contesting the public interest in AI governance. Internet Policy Review, 13(3). https://doi.org/10.14763/2024.3.1794
David, P., Choung, H., & Seberger, J. S. (2024). Who is responsible? US public perceptions of AI governance through the lenses of trust and ethics. Public Understanding of Science, 33(5), 654–672. https://doi.org/10.1177/09636625231224592
Denton, R., & Erete, S. (2023). Power and public participation in AI. In Proceedings of the 3rd ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization (Article 8, pp. 1–13). Association for Computing Machinery. https://doi.org/10.1145/3617694.3623228
Ergen, Y. (2024). Religious digital creatives in Türkiye: A research on the axis of algorithmic authority. Türkiye İletişim Araştırmaları Dergisi, (46), 23–44. https://doi.org/10.17829/turcom.1488194
Harianto, E., Lestari, R. D., Santoso, T. R., & Jamaludin. (2025). Algorithmic spiritual authority: Digital Sufism and the reconfiguration of sanad in Indonesia. ESENSIA: Jurnal Ilmu-Ilmu Ushuluddin, 26(2), 96–108. https://doi.org/10.14421/esensia.v26i2.7772
He, Y. (2024). Artificial intelligence and socioeconomic forces: Transforming the landscape of religion. Humanities and Social Sciences Communications, 11, Article 602. https://doi.org/10.1057/s41599-024-03137-8
Hjaltalin, I. T., & Sigurdarson, H. T. (2024). The strategic use of AI in the public sector: A public values analysis of national AI strategies. Government Information Quarterly, 41(1), 101914. https://doi.org/10.1016/j.giq.2024.101914
Lahusen, C., Maggetti, M., & Slavkovik, M. (2024). Trust, trustworthiness and AI governance. Scientific Reports, 14, Article 20752. https://doi.org/10.1038/s41598-024-71761-0
Morgan, H. (2022). Conducting a qualitative document analysis. The Qualitative Report, 27(1), 64–77. https://doi.org/10.46743/2160-3715/2022.5044
Novelli, C., Taddeo, M., & Floridi, L. (2024). Accountability in artificial intelligence: What it is and how it works. AI & Society, 39, 1871–1882. https://doi.org/10.1007/s00146-023-01635-y
Nowell, L. S., Norris, J. M., White, D. E., & Moules, N. J. (2017). Thematic analysis: Striving to meet the trustworthiness criteria. International Journal of Qualitative Methods, 16, 1–13. https://doi.org/10.1177/1609406917733847
Olmos-Vega, F. M., Stalmeijer, R. E., Varpio, L., & Kahlke, R. (2023). A practical guide to reflexivity in qualitative research: AMEE Guide No. 149. Medical Teacher, 45(3), 241–251. https://doi.org/10.1080/0142159X.2022.2057287
Papagiannidis, E., Mikalef, P., & Conboy, K. (2025). Responsible artificial intelligence governance: A review and research framework. The Journal of Strategic Information Systems, 34(2), Article 101885. https://doi.org/10.1016/j.jsis.2024.101885
Pasmore, W. A., & Khalsa, G. S. (1993). The contributions of Eric Trist to the social engagement of social science. Academy of Management Review, 18(3), 546–569. https://doi.org/10.5465/amr.1993.9309035150
Quirós-Fons, A. (2025). Religious freedom in the age of AI and surveillance: Mapping the field and charting future research directions. The Review of Faith & International Affairs, 23(4), 104–116. https://doi.org/10.1080/15570274.2025.2545140
Rähme, B., & Prohl, I. (2025). Religious studies approaches to the intersection of artificial intelligence and religion: Formations analogous to religion. Religion, 55(3), 573–595. https://doi.org/10.1080/0048721X.2025.2506893
Roche, C., Wall, P. J., & Lewis, D. (2023). Ethics and diversity in artificial intelligence policies, strategies and initiatives. AI and Ethics, 3, 1095–1115. https://doi.org/10.1007/s43681-022-00218-9
Saldaña, J. (2021). The coding manual for qualitative researchers (4th ed.). SAGE.
Siebert, L. C., Lupetti, M. L., Aizenberg, E., Beckers, N., Zgonnikov, A., Veluwenkamp, H., Abbink, D., Giaccardi, E., Houben, G.-J., Jonker, C. M., van den Hoven, J., Forster, D., & Lagendijk, R. L. (2023). Meaningful human control: Actionable properties for AI system development. AI and Ethics, 3, 241–255. https://doi.org/10.1007/s43681-022-00167-3
Sigfrids, A., Leikas, J., Salo-Pöntinen, H., & Koskimies, E. (2023). Human-centricity in AI governance: A systemic approach. Frontiers in Artificial Intelligence, 6, Article 976887. https://doi.org/10.3389/frai.2023.976887
Sun, T. Q., & Medaglia, R. (2019). Mapping the challenges of artificial intelligence in the public sector: Evidence from public healthcare. Government Information Quarterly, 36(2), 368–383. https://doi.org/10.1016/j.giq.2018.09.008
Thomas, J., & Harden, A. (2008). Methods for the thematic synthesis of qualitative research in systematic reviews. BMC Medical Research Methodology, 8, Article 45. https://doi.org/10.1186/1471-2288-8-45
Trattner, C., Jannach, D., Motta, E., Costera Meijer, I., Diakopoulos, N., Elahi, M., Opdahl, A. L., Tessem, B., Borch, N., Fjeld, M., Øvrelid, L., De Smedt, K., & Moe, H. (2022). Responsible media technology and AI: Challenges and research directions. AI and Ethics, 2, 585–594. https://doi.org/10.1007/s43681-021-00126-4
Trist, E. L. (1981). The evolution of socio-technical systems: A conceptual framework and an action research program (Occasional Paper No. 2). Ontario Ministry of Labour, Ontario Quality of Working Life Centre.
Trist, E. L., & Bamforth, K. W. (1951). Some social and psychological consequences of the longwall method of coal-getting: An examination of the psychological situation and defences of a work group in relation to the social structure and technological content of the work system. Human Relations, 4(1), 3–38. https://doi.org/10.1177/001872675100400101
Tsuria, R., & Tsuria, Y. (2024). Artificial intelligence’s understanding of religion: Investigating the moralistic approaches presented by generative artificial intelligence tools. Religions, 15(3), Article 375. https://doi.org/10.3390/rel15030375
Wahyudi, M. D. R., Hasan, N., & Fatwanto, A. (2025). From pulpit to platform: Algorithmic mediation and the transformation of religious authority on YouTube. Profetik: Jurnal Komunikasi, 18(2), 352–377. https://doi.org/10.14421/pjk.v18i2.3622
Yeung, K. (2018). Algorithmic regulation: A critical interrogation. Regulation & Governance, 12(4), 505–523. https://doi.org/10.1111/rego.12158
Zuiderwijk, A., Chen, Y.-C., & Salem, F. (2021). Implications of the use of artificial intelligence in public governance: A systematic literature review and a research agenda. Government Information Quarterly, 38(3), 101577. https://doi.org/10.1016/j.giq.2021.101577
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