The safety failures we are not instrumenting: a perspective on hidden safety-critical challenges in modern AI systems

Researchers argue that modern AI systems face hidden safety-critical challenges, including quieter failures that are plausible and distributed across components. A proposed five-layer framework identifies under-recognized risk patterns, such as overreliance and uncertainty laundering. The framework aims to shift AI safety from model-centric evaluation to socio-technical reliability.