List of taxonomies
Applied Taxonomies
Center for Security and Emerging Technology (CSETv1) The CSET AI Harm Taxonomy characterizes AI incidents and classifies harms of relevance to the public policy community.
Goals, Methods, and Failures (GMF). This is a taxonomy detailing the technological and process factors producing an incident.
MIT AI Risk Repository The MIT AI Risk Repository contains detailed records of AI-related risks extracted from a variety of sources, categorized into high-level and mid-level taxonomies. Its high-level Causal Taxonomy includes attributes such as the entity responsible for the risk (human, AI, or other), the intent (intentional, unintentional, or other), and the timing (pre-deployment, post-deployment, or other). Its mid-level Domain Taxonomy categorizes risks into 23 specific domains like discrimination, misinformation, malicious use, and human-computer interaction issues.
About Taxonomies
Taxonomies are contributed to the AI Incident Database by persons and organizations working to structure the data and provide views into the data. Each taxonomy must be of sufficient quality and completeness to be included in the AI Incident Database, but the taxonomies are the responsibility of the persons and organizations contributing them.