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Plot your organisation's AI risks on a likelihood-by-impact matrix across all seven domains of MIT's AI Risk Repository, a catalogue of more than 1,700 documented AI risks. Fourteen quick ratings give you the matrix, a Low-to-Critical rating, and a next step for every domain.
A risk matrix separates two questions that usually get mixed together: how likely a risk is, and how much damage it would do. You rate each of MIT's seven domains for likelihood (1 to 5) and impact (1 to 5); likelihood times impact gives a score out of 25, rated Low, Moderate, High, or Critical. The one-pager summarises all seven for a board.
Sources: MIT AI Risk Repository (more than 1,700 risks from 74 frameworks, sorted into 7 domains and 24 subdomains; the tool's domains follow it directly); Slattery et al., The AI Risk Repository (2024) (the peer-reviewed meta-review behind it, from MIT FutureTech).