MEDICAL NEGLIGENCE IN DIGITAL HEALTHCARE: REDEFINING LIABILITY, STANDARD OF CARE, AND HUMAN JUDGMENT

Abstract

The inexorable assimilation of artificial intelligence into clinical praxis precipitates profound medico-legal conundrums, wherein algorithmic opacity obfuscates conventional negligence attribution while amplifying liability exposure across clinicians, institutions, and developers. This inquiry delineates hybrid liability paradigms stratifying culpability through three-tier frameworks calibrated to verification lapses, deployment deficiencies, and design pathologies, juxtaposed against enterprise pooling alternatives that internalize systemic risks via mutualized indemnity mechanisms. Central thereto remains preservation of human judgment supremacy, anchoring accountability through contextual reasoning, empathetic discernment, and outlier vigilance irreducible to computational mimicry, buttressed by mandatory AI disclosures and verification imperatives. Comparative jurisdictional scrutiny reveals divergent trajectories from stringent product liability constructs to risk-tiered regulatory scaffolds, culminating in prescriptive reforms encompassing validation registries and dual-signature protocols that harmonize innovation imperatives with patient safeguards. Keywords: medical negligence, artificial intelligence, liability attribution, standard of care, human judgment, digital healthcare, informed consent, algorithmic opacity