Multi-dimensional Safety Verification System for AI: Dynamic Robustness and Antifragility Assessment through Interferometric Stress Testing

This paper proposes a dynamic AI safety verification framework that goes beyond static datasets and conventional simulations. By treating safety testing as an interferometric process, it generates synthetic threat vectors whose constructive interference amplifies hidden vulnerabilities that remain undetected in isolated tests. The framework evaluates dynamic robustness as phase cancellation against disturbances and introduces an Antifragility metric, measuring the AI’s ability to improve under socio-economic stress. This approach establishes a new safety standard focused on adaptive, self-correcting resilience for AI deployed in social infrastructure.