KidAID: A Dataset of Real World AI Incidents Involving Children and Adolescents

KidAID (Kids AI Incidents Database) is a curated dataset of real-world incidents in which AI systems measurably impacted children and adolescents, spanning child-facing products, general audience platforms used by minors, and public sector deployments affecting youth. Incidents are systematically collected from credible sources and normalized into structured fields such as system/deployer/developer, sector and setting, harm category, failure mode, severity, and evidence type. The dataset is designed to support governance and safety research, including trend analysis, risk pathway modeling, sociotechnical failure clustering, evaluation of safeguards, and benchmarking of child-specific safety interventions. It provides a foundation for reproducible measurement of child-related AI harms and for developing practical mitigations across the AI lifecycle.