Who is Responsible When AI Fails? Mapping Causes, Entities, and Consequences of AI Privacy and Ethical Incidents

The dominant paradigm in AI ethics and governance posits that the risks and harms of AI systems can be managed through structured frameworks, principles, and taxonomies that guide policy and practice. This paradigm assumes that by identifying, classifying, and understanding AI failures, practitioners and policymakers can develop effective preventative and mitigative strategies. Research