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

65.14.05 · Risk Sub-Category

Output risks (misuse)

Nonconsensual use

"Generative AI models might be intentionally used to imitate people through deepfakes by using video, images, audio, or other modalities without their consent."

From AI Risk Atlas (IBM2025)

Domain 4 4.3 Human Intentional Post-deployment
65.23.02 · Risk Sub-Category

Non-technical risks (Societal impact)

Impact on education: plagiarism

"Easy access to high-quality generative models might result in students that use AI models to plagiarize existing work intentionally or unintentionally."

From AI Risk Atlas (IBM2025)

Domain 4 4.3 Human Other Post-deployment
65.23.05 · Risk Sub-Category

Non-technical risks (Societal impact)

Impact on education: bypassing learning

"Easy access to high-quality generative models might result in students that use AI models to bypass the learning process."

From AI Risk Atlas (IBM2025)

Domain 4 4.3 Human Intentional Post-deployment

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