Adversarial Validation in AI Safety: Continuous Testing to Reduce Model Risk, Bias, and Emergent Failure Modes
Adversarial validation is a safety engineering and risk-management framework used to detect whether training and deployment data come from different underlying distributions, and to stress-test models against inputs that can systematically trigger failure. In medical terms, it is analogous to pre-implementation screening and ongoing pharmacovigilance: the goal is not to assert that a system is… Read More »