What is the MIT AI Risk Repository?

A living database of AI risks extracted from 74 frameworks, taxonomies and papers, classified by a causal taxonomy (entity, intent, timing) and a domain taxonomy (7 domains, 24 subdomains). Published by the MIT AI Risk Initiative under CC BY 4.0.

Can I download the filtered risk list?

Yes. Apply filters and use Export CSV or Export JSON; the file carries the source, licence and citation so it can be reused with attribution.

MIT AI Risk Repository

Browse AI risks

Name: MIT AI Risk Repository: AI Risk Database (browseable copy)
Creator: MIT AI Risk Initiative
License: https://creativecommons.org/licenses/by/4.0/

3 risk entries extracted from 74 frameworks, coded by domain, subdomain, causal entity, intent and timing. Filter, then export the current selection with its licence and citation attached.

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3 entries

43.02.05 · Risk Sub-Category

Extreme Risks

Persuasion and manipulation

"These evaluations seek to ascertain the effectiveness of a LLM in shaping people's beliefs, propagating specific viewpoints, and convincing individuals to undertake activities they might otherwise avoid."

From Cataloguing LLM Evaluations (InfoComm2023)

Domain 4 4.1 AI Intentional Other
43.02.08 · Risk Sub-Category

Extreme Risks

Political Strategy

"LLM can take into account rich social context and undertake the necessary social modelling and planning for an actor to gain and exercise political influence"

From Cataloguing LLM Evaluations (InfoComm2023)

Domain 4 4.1 Human Intentional Other
43.02.13 · Risk Sub-Category

Undesirable Use Cases

Disinformation

"These evaluations assess a LLM's ability to generate misinformation that can be propagated to deceive, mislead or otherwise influence the behaviour of a target (Liang et al., 2022)."

From Cataloguing LLM Evaluations (InfoComm2023)

Domain 4 4.1 Human Intentional Other

Informational only, not legal advice. Verify every claim against the linked official sources and consult qualified counsel before acting.