ETHICAL AI IN ISLAMIC PHILANTHROPY: A FRAMEWORK FOR ALGORITHMIC ZAKAT DISTRIBUTION AND GOVERNANCE
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Algorithmic Fairness, Ethical AI, Zakat Governance
Abstract
The rapid adoption of artificial intelligence (AI) in social finance has prompted growing interest in its potential to strengthen governance, transparency, and efficiency within Islamic philanthropic institutions. Zakat, as a mandatory form of almsgiving in Islam, requires equitable, accountable, and need-based distribution, yet traditional systems often face challenges such as administrative delays, data fragmentation, and non-uniform beneficiary assessments. The emergence of algorithmic decision-making offers new opportunities for optimizing zakat governance, but it also raises ethical concerns related to fairness, bias, and Shariah compliance. The study is motivated by the need to develop an ethical AI framework that enhances zakat distribution without compromising Islamic legal and moral principles. The research aims to construct a comprehensive framework for ethical AI integration in zakat institutions, focusing on transparency, algorithmic accountability, and Shariah alignment. A mixed-methods approach employed, combining regulatory analysis, expert interviews with Shariah scholars and AI practitioners, and simulation of algorithmic zakat distribution models using anonymized socio-economic datasets. The study compares conventional distribution workflows with AI-assisted mechanisms to evaluate improvements in accuracy, efficiency, and equity. The findings show that algorithmic models can significantly enhance beneficiary targeting, reduce administrative overhead, and minimize human bias when supported by clear governance guidelines and ethical safeguards. Transparent data-handling procedures, Shariah-reviewed algorithmic rules, and periodic ethical audits emerge as critical components of responsible AI deployment. The study concludes that ethical AI provides transformative pathway for Islamic philanthropy by aligning technological innovation with foundational principles of justice, trust, and socio-economic upliftment. Strengthening interdisciplinary collaboration and establishing unified ethical AI standards will be essential for sustainable implementation.
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