Partnership on AI - AI Incident Database
Summary
Partnership on AI created the AI Incident Database to collect and learn from AI system failures across different domains. The database allows researchers, engineers, and product managers to understand past mistakes and mitigate future risks.
Review
The AI Incident Database (AIID) represents a critical infrastructure for documenting and learning from AI system failures, drawing inspiration from incident tracking approaches in aviation and cybersecurity. By providing a centralized repository of AI incidents across domains like transportation, healthcare, and law enforcement, the database enables practitioners to understand potential risks and develop more robust systems. The database's open-source approach and community-driven model are particularly innovative, allowing diverse stakeholders like product managers, risk officers, engineers, and researchers to contribute and learn from past failures. By making incidents searchable and referenceable, the AIID creates a mechanism for collective learning and proactive risk mitigation, potentially reducing negative consequences of AI deployment and promoting responsible AI development.
Key Points
- First comprehensive, centralized database tracking AI system failures across multiple domains
- Enables learning from past mistakes to improve future AI development
- Open-source platform allowing community contributions and collaborative safety improvement