Preserving the Authenticity of Quranic Exegesis Through Artificial Intelligence: A Proposed Framework for Digital Verification

Abstract

This article explores the potential application of Artificial Intelligence (AI) in preserving the authenticity of Quranic exegesis (tafsir) in the digital age. The widespread dissemination of unauthoritative tafsir texts across various online platforms poses significant risks to the Muslim public’s understanding of the Quranic message. To address this, the study proposes an AI-based framework utilizing Natural Language Processing (NLP) and Machine Learning (ML) techniques to filter, match and verify tafsir content against established authoritative sources such as the works of al-Ṭabarī, Ibn Kathīr and al-Qurṭubī. Employing a qualitative and conceptual analysis, the framework consists of five core modules including input processing, semantic matching and authentication evaluation. The study further addresses epistemological challenges, model bias risks and underscores the need for human-in-the-loop supervision to ensure scholarly integrity. In conclusion, AI technologies hold significant promise as a complementary tool to traditional scholarly authority in ensuring the trustworthy dissemination of authentic tafsir in the digital Islamic knowledge ecosystem.