Bridging Revelation and Algorithm: Integrating Artificial Intelligence and Malakah in the Epistemology of Ḥadīth Criticism - A'thoina, Inna; Hasballah, Farah; Fadillah, Nur Aisyah (Universitas Islam Negeri Sultan Maulana Hasanuddin Banten, 2025)
This study explores the epistemological and methodological integration of Artificial Intelligence (AI) within ḥadīth criticism, focusing on its relationship with the classical Islamic concept of malakah—the intellectual and spiritual faculty enabling a muḥaddith to discern authenticity and hidden defects (ʿillah) within prophetic narrations. Employing a qualitative descriptive approach and library research method, the study analyses both classical Islamic scholarship and contemporary AI research to construct an integrative framework for AI-assisted ḥadīth analysis. The research demonstrates that AI, particularly through Natural Language Processing (NLP) and Machine Learning (ML), offers significant potential to enhance the analytical precision, scalability, and efficiency of ḥadīth authentication. However, it contends that AI must be situated as an epistemological instrument rather than an autonomous interpretive authority. The study argues that while AI can replicate heuristic and linguistic reasoning, it cannot emulate the moral and spiritual intuition inherent in malakah. Consequently, it proposes a hybrid epistemic model where AI serves as a supportive analytical tool, guided by Islamic epistemological principles rooted in tawḥīd, ʿadl, and scholarly ethics. This integration reaffirms the role of human interpretive authority while ensuring that technological innovation in ḥadīth studies remains consistent with the ethical and intellectual heritage of Islamic scholarship.