AI systems are failing — in hospitals, in schools, in hiring systems, in police simulations, and across social platforms. But who is actually responsible when AI harms people?This episode breaks down one of the most important empirical studies in AI accountability:a taxonomy built from 202 real-world AI privacy and ethical incidents (2023–2024).🔍 What we uncover in this video:The top causes of AI failures — and why they keep happeningWhy organizations and developers are responsible in most casesThe disturbing reality: almost no one self-discloses AI incidentsHow most failures are exposed by victims, journalists, and investigatorsPatterns in predictive policing failures, biased content moderation, and moreWhat this means for the future of AI governance, compliance, and risk💡 This episode is essential for:AI leaders • Policymakers • Tech ethicists • Compliance teams • Researchers • Anyone building or deploying AI systems📘 Source:“Who Is Responsible When AI Fails? Mapping Causes, Entities, and Consequences of AI Privacy and Ethical Incidents” (2024)🔔 Subscribe for weekly episodes on AI governance, strategy, cyber risk, and global policy.#AIethics #AIincidents #AIfailures #ResponsibleAI #AIGovernance #ArtificialIntelligence #AlgorithmicBias #TechAccountability #NeuralFlowConsulting