An Islamic Model of Artificial Intelligence Governance Oriented toward Gender Justice: Integrating Islamic Teachings and International Experiences

Document Type : Original Article

Authors

1 Bachelor’s Degree in Information Technology Engineering; Level 3, Qom Seminary; Artificial Intelligence Department, Specialized Center for Studies of Religion and Cyberspace, Qom Seminary, Qom, Iran

2 PhD., Department of Artificial Intelligence, Research Institute for Digital Islamic and Human Sciences, Noor Computer Research Center for Islamic Sciences, Qom, Iran

3 Professor, School of Computer Engineering, Iran University of Science and Technology, Tehran, Iran

Abstract

This study aims to design and evaluate an integrated conceptual–operational model for the Islamic governance of artificial intelligence (AI) oriented toward gender justice. The proposed model establishes a coherent link between Islamic normative foundations and international experiences to protect women from AI-related risks while enabling them to benefit from the technology’s capabilities and opportunities. Alongside opportunities for women’s empowerment, employment growth, and enhanced social participation, the expanding use of AI has intensified challenges such as algorithmic bias and discrimination, privacy violations, sexual exploitation and abuse, and inequitable access to scientific and technological opportunities. Despite extensive scholarship on AI governance and gender-responsive governance, together with initiatives by international organizations and leading countries, a significant gap remains: the absence of a comprehensive, systematic model grounded in Islamic teachings at the intersection of AI governance, gender governance,
and Islamic teachings. Moreover, many existing models and frameworks rest on anthropocentric foundations and gender-equality paradigms, with limited attention to the potential of divine and Islamic principles to redefine gender justice and translate it into governance requirements and mechanisms. Accordingly, the central research question is: What model and governance mechanisms can be developed by drawing on Islamic teachings and successful international experiences to mitigate and prevent AI-related threats to women while enabling them to benefit from the technology’s opportunities? This exploratory, interdisciplinary study used library research for data collection and a descriptive–analytical approach incorporating qualitative methods for data analysis. Model 
development proceeded through five stages: (1) systematic examination of international experiences; (2) extraction of Islamic principles; (3) comparative analysis and clarification of the rationale for integration; (4) integration and model formulation; and (5) evaluation and validation. International experiences were purposively selected on the basis of leadership and innovation, drawing on the United Nations, UNESCO, the International Labour Organization (ILO), the Convention on the Elimination of All Forms of Discrimination against Women (CEDAW), the European Union, and the United States, China, Singapore, South Africa, and Malaysia. The operational mechanisms identified in these sources were then coded.




292                                                                    Islamic Governance Studies, Vol. 2, No. 2, 2026




Islamic principles were derived through systematic thematic interpretation following the approach of Martyr Muhammad Baqir al-Sadr. This process comprised seven stages: (1) identifying the central question; (2) collecting relevant Qur’anic verses; (3) categorizing the verses; (4) consulting authoritative exegetical sources; (5) extracting preliminary principles; (6) validating these principles against narrations and the conduct of the Infallibles; and (7) formulating the final principles. A subsequent four-stage process involved analyzing similarities and differences between the two domains, distinguishing the role of each source, resolving fundamental tensions, and using Islamic principles as the “why” and international experiences as the “how” in formulating governance mechanisms. The proposed model was evaluated across four dimensions—construct validity, internal validity, external validity, and reliability—through directed content analysis and the documentation of theoretical and operational evidence.
The findings yielded ten gender-related principles derived from Islamic teachings. Among the most important are justice; the proportionality of women’s and men’s rights to their respective innate characteristics; inherent human dignity; respect for women; women’s education and encouragement to pursue learning; privacy protection; and the prohibition of harassment and violence against women. Integrating these ten principles with 16 operational measures and mechanisms identified in international experiences produced a model comprising 13 overarching strategies across three complementary, interacting domains:
(1) Policy and legal domain: developing national and international policy documents; upholding fundamental principles; formulating supportive policies for women; prohibiting gender-based exploitation and abuse; and mobilizing indigenous capacities.
(2) Technical and regulatory domain: establishing gender-monitoring centers; requiring gender-impact testing of AI systems; maintaining gender balance in machine learning; ensuring transparency and explainability; and designing safe products tailored to women’s needs.
(3) Educational and cultural domain: educating and empowering women; promoting their participation in AI management and development; and fostering public awareness, discourse, and participation.
Evaluation using the four-dimensional framework indicated that the proposed model adequately represents gender-related concepts, exhibits logical coherence between its components and expected outcomes, has broad applicability at the macro level, and is based on a replicable development process. However, a definitive assessment of its effectiveness requires empirical validation.The proposed model demonstrates that gender-responsive AI governance within an Islamic framework can move beyond the dichotomy of imitating existing models or remaining isolated from global experiences by systematically linking “value foundations” with “implementation mechanisms.” Within this framework, Islamic teachings serve not merely as ethical recommendations but as the basis for defining governance objectives, boundaries, and overarching orientations, as well as criteria for resolving conflicts. International experiences, in turn, provide implementation and regulatory mechanisms through which these orientations can be operationalized. From the Islamic perspective adopted in this framework, gender justice entails the proportionality of rights to the innate characteristics of women and men rather than numerical equality, in contrast to the dominant Western approach. Accordingly, the model emphasizes not only the prevention of discrimination and exploitation but also proportionate protection, empowerment, agency, and women’s participation throughout the AI development and governance lifecycle. The study thus offers a coherent model for policymaking, regulation, and implementation that can inform empirical research, field testing, and the development of future strategies and implementation programs

Keywords

References

قرآن کریم.
آقاجانی، مریم (۱۴۰۰). هوش مصنوعی، از مقدماتی تا پیشرفته. تهران: نشر نسل روشن.
اصغری، فیروزه؛ هنردوست، عطیه (۱۳۹۳). مطالعه تطبیقی وضعیت و جایگاه زنان در ایران و مالزی براساس شاخص نابرابری جنسیتی. زن در توسعه و سیاست، شماره ۱، ص۷۵-۹۲.
الوانی، مهدی؛ شمس، لیلا (۱۴۰۳).‌ مبانی حکمرانی، نظریه‌ها و کاربردها. تهران: انتشارات دانشگاه علامه طباطبایی.
بشیر، حسن؛ راوی، محمدجواد (۱۴۰۴). مرور نظام‌مند چارچوب‌ها و سازوکارهای حکمرانی راهبردی هوش مصنوعی در مطالعات سال‌های ۲۰۱۷-۲۰۲۵. مطالعات فضای مجازی و رسانه‌های اجتماعی، شماره ۳، ص۹-۵۴.
ترخان، قاسم؛ موسوی، سید داود (۱۴۰۳). سنت جعل امامت و حکمرانی بر فضای سایبر و فناوری‌های نوین. آیین حکمرانی، شماره ۴، ص۹۳-۱۲۰.
حاجیلو، افسانه (۱۴۰۳). تحلیل و بررسی سند ملی هوش مصنوعی و ارائه توصیه‌های سیاستی. در: مجموعه مقالات نخستین همایش ملی الگوی حکمرانی تمدنی علم و فناوری، ص۶۴۹-۶۶۱.
حرّ عاملی، محمد بن حسن (۱۴۱۳ق). تفصیل وسائل الشیعه الی تحصیل مسائل الشریعه. (ج 18). قم ‫: موسسه آل البیت(ع) لاحیاء التراث.
حسنی، حسین (۱۴۰۳). سیاستگذاری هوش مصنوعی در اتحادیه اروپا: اصول بنیادین، سازوکار حکمرانی و اصول اخلاقی. سیاست‌گذاری عمومی، شماره ۲، ص۱۸۷-۲۰۳.
حســینی اکبرنژاد، هاله؛ حسینی اکبرنژاد، حوریه (۱۳۹۶). نگاهی بر رویه نهادهای بین‌المللی در هنجارســازی و توسیع مفاهیم حوزه زنان. شورای فرهنگی اجتماعی زنان و خانواده، 19(76)، ص۱۳۷-۱۵۸.
حیدری ترک‌آباد، فهیمه؛ زمانی، سید قاسم (آماده انتشار). واکاوی ظرفیت‌ها و چالش‌های اثرگذاری هوش مصنوعی بر حق زنان بر برابری. تحقیقات حقوقی.
سلیمان‌زاده، سعید؛ اسلامی، محسن؛ موسوی شفایی، مسعود؛ گل‌محمدی، ولی (۱۴۰۳). حکمرانی هوش مصنوعی در عصر دیجیتال: واکاوی راهبردها و رویکردهای آمریکا. روابط خارجی، شماره ۲، ص۱۹۳-۲۲۴.
سیفی، آناهیتا؛ رزم‌خواه، نجمه (۱۴۰۰). تأمین و اجرایی شدن حق اشتغال زنان در پرتو توسعه و گسترش هوش مصنوعی. مطالعات حقوق بشر اسلامی، 10(2)، ص۱۵۳-۱۸۰.
شکاری، فاطمه؛ رضازهی، ماجده؛ رونده، حسین (۱۴۰۳). نقش قوای قانون‌گذاری، اجرایی و قضایی در تنظیم و نظارت بر استفاده از فناوری‌های هوش مصنوعی. مطالعات علوم اجتماعی، شماره ۴، ص۶۰-۷۱.
شکرالهی، شیوا؛ معتمدنژاد، رؤیا (۱۴۰۴). حکمرانی جهانی هوش مصنوعی در خدمت منافع بشریت و نقش سازمان ملل. علوم خبری، شماره ۵۳، ص۴۶-۷۱.
صادقیان، امیرعباس (۱۴۰۴). حکمرانی هوش مصنوعی و هوش مصنوعی در حکمرانی. رویکردهای نو در مدیریت دولتی، شماره ۷، ص۶-۳۵.
صدر، سید محمدباقر (۱۴۳۴ق). المدرسة ‌القرآنیة. قم: موسسة دارالکتاب ‌الاسلامی.
طباطبایی، سید محمدحسین (۱۳۵۲). المیزان فی تفسیر القرآن. (ج18). بیروت: مؤسسة الاعلمی.
کاظمی، فرشته؛ نعمت‌الهی، هاجر (1402). عدالت جنسیتی و حکمرانی مطلوب در ایران با مقایسه اتحادیه اروپا و خاورمیانه. در: چهارمین کنفرانس بین‌المللی مطالعات نوین در علوم انسانی، علوم تربیتی، حقوق و مطالعات اجتماعی.
کلینی، محمد بن یعقوب (۱۳۶۳). الکافی. (ج5). تهران: دارالکتب الاسلامیة.
کیسینجر، هنری؛ اشمیت، اریک؛ لاکر، هاتن (۱۴۰۱). عصر هوش مصنوعی و آینده ما انسان‌ها. ترجمه سید حسین علوی لنگرودی. تهران: آماره.
مجیدی نظامی، سید مهدی (۱۴۰۵). از هژمونی الگوریتمی تا حاکمیت فناورانه: نقد اقتصاد سیاسی حکمرانی درونی هوش مصنوعی و طراحی استاندارد پیشنهادی «الگوریتم پارسا». مطالعات حکمرانی اسلامی، ۲(۱)، ص۳۳۷-۳۶۲.
محمودی، مصطفی؛ اکبری، ایمان؛ مهربان هلان، محمدمهدی (۱۴۰۳). حکمرانی هوش مصنوعی (۲): مفاهیم، ابعاد و مولفه‌ها. گزارش‌های کارشناسی مرکز پژوهش‌های مجلس شورای اسلامی، شماره ۱۰.
موسوی خامنه، مرضیه؛ عجمی، راضیه (۱۴۰۲). مطالعه تحلیلی-تطبیقی شاخص‌های جنسیتی و رابطه‌ی آن‌ها با حکمرانی خوب. مطالعات توسعه اجتماعی اقتصادی، شماره ۲، ص۱۹-۵۰.
میدری، احمد؛ خیرخواهان، جعفر (۱۳۸۳). حکمرانی خوب بنیان توسعه. تهران: مرکز پژوهش‌های مجلس شورای اسلامی.
نوریجانی، علی؛ اسلامی، حسین؛ افشانی، سید علیرضا؛ دهقان دهنوی، حسن (۱۴۰۲). ارائه الگوی مطلوب حکمرانی دیجیتال در عصر جامعه شبکه‌ای. مطالعات رسانه‌های نوین، شماره ۳۴، ص399-429.
وفائی، اعظم؛ جوکار، محبوبه (۱۳۹۰). فلسفه برخی تفاوت‌های تشریعی زن و مرد، با ابتناءبه تفاوت‌های تکوینی. بانوان شیعه، شماره 27، ص95-122.
هاشمی، شکوه السادات؛ حافظی، بهار؛ شریفی رنانی، حسین (1403). اثر آستانه‌ای حکمرانی خوب بر برابری جنسیتی در ایران با تأکید بر نابرابری درآمدی. سیاست‌ها و تحقیقات اقتصادی، شماره ۳، ص۴۸-۷۶.
Ashworth, G. (1996). Gendered governance: an agenda for change. New York: Mar.
Camilleri, M. (2023). Artificial intelligence governance: Ethical considerations and implications for social responsibility. Expert Systems, no. 41. https://doi.org/10.1111/exsy.13406
Coombs, E., & Abraha, H. (2022). Governance of AI and Gender: Building on International Human Rights Law and Relevant Regional Frameworks. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4150879
Cronbach, L. J. & Meehl, P. E. (1955). Construct validity in psychological tests. Psychological Bulletin, 52(4), p. 281–302. https://doi.org/10.1037/h0040957
De Almeida, P., Santos, C. & Farias, J. (2021). Artificial Intelligence Regulation: a framework for governance. Ethics and Information Technology, no. 23, p. 505-525.       
https://doi.org/10.1007/s10676-021-09593-z
Ebrahimi, M., Rahimi, B., Sharifi, M., Sadat, D., Amiri, N. Khalil, S. & Quraishi, T. (2024). Empowering Women through Artificial Intelligence: Opportunities and Challenges”. Journal Electrical and Computer Experiences, 2(2), p. 38-46.              
https://doi.org/10.59535/jece.v2i2.346
Erman, E. & Furendal, M. (2022). The Global Governance of Artificial Intelligence: Some Normative Concerns. Moral Philosophy and Politics, no. 9, p. 267-291.                   
https://doi.org/10.1515/mopp-2020-0046
European Union. (2021). EU Artificial Intelligence Law: Legal framework for the development, use and supervision of artificial intelligence technologies. Retrieved from:  
https://eur-lex.europa.eu
Gamble, S. (2006). The Routledge Companion to Feminism and Postfeminism. London & New York: Routledge.
Gasser, U. & Almeida, V. (2017). A Layered Model for AI Governance. IEEE Internet Computing, no. 21, p. 58-62. https://doi.org/10.1109/mic.2017.4180835
Geloven, N. van, Giardiello, D., Bonneville, E. F., Teece, L., Ramspek, C. L., Smeden, M. van, … Steyerberg, E. (2022). Validation of prediction models in the presence of competing risks: a guide through modern methods. British Medical Journal. Retrieved from: https://hdl.handle.net/1887/3304235
Infocomm Media Development Authority & AI Verify Foundation. (2024). Model AI Governance Framework for Generative AI (Final version, May 30, 2024).
Ismail, O. & Aḥmad, N. (2025). Ethical and Governance Frameworks for Artificial Intelligence: A Systematic Literature Review. International Journal of Interactive Mobile Technologies (iJIM). https://doi.org/10.3991/ijim.v19i14.56981.
Kaya, C. (2015). Internal validity: A must in research designs. Educational Research Review, no. 10, p. 111-118. https://doi.org/10.5897/err2014.1835
Lemay, A., Hoebel, K., Bridge, C., Befano, B., De Sanjos'e, S., Egemen, D., Rodriguez, A., Schiffman, M., Campbell, J. & Kalpathy-Cramer, J. (2022). Improving the repeatability of deep learning models with Monte Carlo dropout. NPJ Digital Medicine, no. 5. https://doi.org/10.1038/s41746-022-00709-3
Lessig, L. (1999). Code and other laws of cyberspace. Basic Books.
Lutz, F. (2022). Gender equality and artificial intelligence in Europe. Addressing direct and indirect impacts of algorithms on gender-based discrimination. ERA Forum, no. 23,
p. 33-52. https://doi.org/10.1007/s12027-022-00709-6
Maheswari, A. (2025). Beyond Algorithms: A G.E.N.D.E.R. AI Framework for Advancing Workplace Equity in Automation. International Journal of Global Research Innovations & Technology. https://doi.org/10.62823/ijgrit/03.2(ii).7624
Ministry of Science, Technology and Innovation Malaysia (MOSTI). (2022). National Guidelines on AI Governance and Ethics. URL= https://ai.gov.my/governance
National Science and Technology Council. (2016). Preparing for the Future of Artificial Intelligence. Executive Office of the President of the United States of America. URL= https://obamawhitehouse.archives.gov/sites/default/files/whitehouse_files/microsites/ostp/NSTC/preparing_for_the_future_of_ai.pdf
Nwafor, I. (2024). Gender Mainstreaming into African Artificial Intelligence Policies: Egypt, Rwanda and Mauritius as Case Studies. Law, Technology and Humans.              
https://doi.org/10.5204/lthj.3496
Papagiannidis, E., Mikalef, P., & Conboy, K. (2025). Responsible artificial intelligence governance: A review and research framework. J. Strateg. Inf. Syst., no. 34.        
https://doi.org/10.1016/j.jsis.2024.101885
Rai, S.M. (2004). Gendering Global Governance. International Feminist Journal of Politics,
no. 6, p. 579-601.
Russell, S.J. & Norvig, P. (1988). Artificial Intelligence: A Modern Approach. 3rd Ed. England: Pearson.
Rutherford, B., & Buss, D. (2019). Gendered governance and socio-economic differentiation among women artisanal and small-scale miners in Central and East Africa. Third World Thematics: A TWQ Journal, no. 4, p. 63-79.
Samman, D., Merloa, R. & Ernst, E. (2018). The Economics of Artificial Intelligence: Implications for the Future of work, ILO Future of Work Research Paper series. International Labour Office Geneva. URL= www.ilo.org
Shadish, W. R., Cook, T. D. & Campbell, D. T. (2002). Experimental and Quasi-Experimental Designs for Generalized Causal Inference. Houghton Mifflin.
Shahbazi, H., Hakimi, M. Ulusi, H., Rahimi, B. & Quraishi, T. (2024). Exploring the Impact of Artificial Intelligence on Women's Empowerment: A Comprehensive Survey. Journal of Emerging Issues and Trends in Education, 1(2), p. 108–120.         
https://doi.org/10.59110/edutrend.333
Sharma, P. (2024). Artificial Intelligence as a Catalyst for Gender Equality: Empowering Women across Healthcare, Education, and Entrepreneurship. Mind and Society, 13(03), p. 34–41. https://doi.org/10.56011/mind-mri-133-20245
Sheehan, M. (2023). China’s AI regulations and how they get made. Horizons: Journal of International Relations and Sustainable Development, no. 24, p. 108-125.
Sutko, D. (2019). Theorizing femininity in artificial intelligence: a framework for undoing technology’s gender troubles. Cultural Studies, no. 34, p. 567-592.           
https://doi.org/10.1080/09502386.2019.1671469
Taeihagh, A. (2021). Governance of artificial intelligence. Policy and Society, no. 40,
p. 137-157. https://doi.org/10.1080/14494035.2021.1928377
Tusalem, R. F. (2022). Gendered Governance: Examining the Relationship between Women Legislators and Effective Public Goods Provision from a Global Sample. American Political Science Review, 116(4), 1501–1516. https://doi.org/10.1086/718579
United Nations Educational, Scientific and Cultural Organization (UNESCO). (2021). Recommendation on the Ethics of Artificial Intelligence. URL=
https://unesdoc.unesco.org/ark:/48223/pf0000392790
Universal Declaration of Human Rights. (2021). United Nation Organization. URL=          
www.un.org
Wajcman, J. (1991). Feminism confronts technology. Pennsylvania State University Press.
Zhang, B. H. & et al. (2018). Mitigating Unwanted Biases with Adversarial Learning. AAAI/ACM Conference on AI, Ethics, and Society.

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