1,368 AI Failures and What They Teach About Evals — Vishal Srivastava & Tanmay Sah, New York Life

Vishal Srivastava and Tanmay Sah studied 1,368 incidents from a public AI incident database to ask what real failures say about how AI systems should be tested. They sort failures across three areas (technical strength, deployment controls and business impact) and 13 sub-areas that cover about 98% of incidents. Weak deployment controls, such as human review and monitoring, are the most closely tied to harm. They show how to rank use cases by how much is at stake, why the evaluator itself needs checking, and a build-break-fix loop that tries to prove a system wrong instead of right, applied to