arXiv:2608.16903v1 Announce Type: cross
Abstract: The deployment of machine learning systems capable of detecting covert consciousness in neurologically injured patients creates a profound challenge at the intersection of clinical medicine, AI ethics, and Islamic jurisprudence. We argue that the shift from binary clinical verdicts to probabilistic, temporally granular neural-state estimates should be addressed through three foundational constructs in Islamic legal epistemology: bayyina (clear evidentiary proof), yaqin (epistemic certainty), and the theologically mandated agnosticism about there (soul). We survey the current technical literature on AI-based consciousness detection, map it onto the landscape of Islamic brain death scholarship, and identifykey challenges. We also discuss its implications for AI surrogate decision systems.
Abstract: The deployment of machine learning systems capable of detecting covert consciousness in neurologically injured patients creates a profound challenge at the intersection of clinical medicine, AI ethics, and Islamic jurisprudence. We argue that the shift from binary clinical verdicts to probabilistic, temporally granular neural-state estimates should be addressed through three foundational constructs in Islamic legal epistemology: bayyina (clear evidentiary proof), yaqin (epistemic certainty), and the theologically mandated agnosticism about there (soul). We survey the current technical literature on AI-based consciousness detection, map it onto the landscape of Islamic brain death scholarship, and identifykey challenges. We also discuss its implications for AI surrogate decision systems.
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