AINeutralarXiv – CS AI · Mar 57/10
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When AI Fails, What Works? A Data-Driven Taxonomy of Real-World AI Risk Mitigation Strategies
Researchers analyzed 9,705 AI incident reports to create an expanded taxonomy of real-world AI risk mitigation strategies, identifying four new categories of responses including corrective actions, legal enforcement, financial controls, and avoidance tactics. The study expands existing mitigation frameworks by 67% and provides structured guidance for preventing cascading AI system failures in high-stakes deployments.