Artificial Intelligence Ethics in Islamic Society: Towards an Integrative Approach between Maqasid al-Shariah and International Standards for AI Governance

Sofiane Fellah (), Mebarka Bedarnia and Oulfa M’ziou
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Sofiane Fellah: University of Biskra
Mebarka Bedarnia: University of Laghouat
Oulfa M’ziou: University of Biskra

A chapter in Proceedings of the International Conference on Artificial Intelligence Applications in Business Administration in MENA Region (ICAIABA 2026), 2026, pp 27-35 from Springer

Abstract: Abstract Artificial intelligence (AI) is rapidly reshaping economic and institutional life in Muslim-majority societies, yet prevailing governance frameworks, including UNESCO’s AI Ethics Recommendation and the NIST AI Risk Management Framework, remain grounded in secular normative assumptions that do not adequately engage Islamic ethical traditions. This study examines the extent to which a selective and contextualized integration of Maqasid al-Shariah, the higher objectives of Islamic law as articulated by Al-Ghazali, Al-Shatibi, Auda, and Kamali, and international AI governance standards can contribute to the ethical regulation of AI in digital entrepreneurship and Islamic finance. Adopting a qualitative comparative methodology, the study maps five Maqasid objectives against corresponding AI governance principles, identifying functional convergences, normative divergences, and governance tensions. Key findings reveal shared concerns for harm prevention, human dignity, and accountability, while highlighting fundamental divergences: Maqasid ethics is grounded in divine accountability and absolute prohibitions, notably riba and gharar, whereas international standards rely on procedural governance and risk-based thresholds. The study proposes a Maqasid AI Filter Framework (MAFF) as a preliminary operational governance model with concrete policy recommendations for regulatory bodies in Islamic financial contexts.

Keywords: Artificial intelligence; AI governance; Islamic ethics; Maqasid al-Shariah; Islamic finance; Human-centered AI; Digital entrepreneurship; Algorithmic accountability (search for similar items in EconPapers)
Date: 2026
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DOI: 10.2991/978-94-6239-711-8_4

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