MIT AI Risk Repository

The AI Risk Database captures 700+ risks extracted from 43 existing frameworks, with quotes and page numbers. The Causal Taxonomy of AI Risks classifies how, when, and why these risks occur. The Domain Taxonomy of AI Risks classifies these risks into seven domains (e.g., “Misinformation”) and 23 subdomains (e.g., “False or misleading information”).

This Database was produced by an interdisciplinary group at MIT that studies the foundations of progress in computing: what are the most important trends, how do they underpin economic prosperity, and how can we harness them to sustain and promote productivity growth.