Assistive artificial intelligence (AI) technologies hold significant promise for transforming healthcare by aiding physicians in diagnosing, managing, and treating patients. For example, some neonatal intensive care units have adopted early warning systems to predict infections and recommend treatments. Leveraging AI’s superior diagnostic accuracy in certain specialties, these assistive AI systems aim to reduce medical errors, while also promising to address physician fatigue by alleviating cognitive load and time pressures.

Despite this promise, the current trend of assistive AI implementation may actually worsen challenges related to error prevention and physician burnout. Healthcare organizations are adopting AI at a much faster pace than laws and regulations governing its use are evolving. Consequently, although scholars have proposed recommendations for shaping AI regulations, the reality is that in the absence of clear policies or established legal standards, future liability will largely hinge on societal perceptions of blameworthiness. This regulatory gap imposes an immense, almost superhuman, burden on physicians: they are expected to rely on AI to minimize medical errors, yet bear responsibility for determining when to override or defer to these systems.