AI, Brain Death Detection, and Islamic Law
This article, published on arXiv, investigates the application of machine learning in identifying hidden consciousness in patients with neurological injuries, bridging the fields of clinical medicine, AI ethics, and Islamic law. The authors contend that AI transforms the assessment of brain states from definitive clinical judgments to probabilistic and time-sensitive evaluations, which complicates established legal and theological principles. To tackle this issue, they introduce three essential concepts from Islamic legal epistemology: bayyina (clear evidence), yaqin (certainty of knowledge), and a theologically required agnosticism about the soul (ruh). The paper reviews existing technical literature on AI-driven consciousness detection, aligns these insights with current Islamic brain death studies, and highlights significant challenges in merging these areas. It also examines the ramifications for AI-based surrogate decision-making systems, emphasizing the necessity for interdisciplinary conversations among technology, medicine, and religious law.
Key facts
- The paper is titled 'AI, Brain Death Detection, and Islamic Law'.
- It addresses machine learning systems for detecting covert consciousness in neurologically injured patients.
- AI shifts clinical verdicts from binary to probabilistic, temporally granular neural-state estimates.
- The paper proposes using bayyina, yaqin, and agnosticism about the soul as foundational constructs.
- It surveys technical literature on AI-based consciousness detection.
- The findings are mapped onto the landscape of Islamic brain death scholarship.
- Key challenges at the intersection of AI and Islamic jurisprudence are identified.
- Implications for AI surrogate decision systems are discussed.
- The paper is hosted on arXiv under the Computer Science and Computers and Society category.
Entities
Institutions
- arXiv