FROM MANUSCRIPT TO MACHINE INTELLIGENCE: DIGITAL MEDIATION AND THE FUTURE OF ISLAMIC KNOWLEDGE SYSTEMS
Abstract
The transition of Islamic intellectual heritage from physical manuscripts to machine intelligence marks a significant epistemological shift in the preservation and dissemination of sacred knowledge. This research addresses the challenges of maintaining textual integrity and scholarly authority within increasingly automated digital environments. The study aims to evaluate the impact of digital mediation on classical hermeneutics and the traditional chain of authority known as the isnad. Utilizing a mixed-methods approach, the methodology combines qualitative hermeneutical analysis with quantitative algorithmic auditing of Large Language Models (LLMs) across 5,000 digitized manuscript folios. Results indicate that while machine intelligence enhances retrieval speed by 300%, it frequently introduces “semantic flattening” and “algorithmic hallucinations” in complex theological exegesis. Furthermore, current models exhibit a 32% failure rate in accurately verifying non-linear marginalia and historical narrator chains. This research concludes that machine intelligence currently serves as an efficient indexer rather than a sophisticated exegete, necessitating a hybrid model of “augmented scholarship.” The findings propose a “Digital Isnad Framework” to safeguard epistemic authenticity, asserting that the future of Islamic knowledge systems depends on a synergistic relationship between computational power and traditional human expertise to prevent the erosion of intellectual depth.
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