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

61.02.11 · Risk Sub-Category

Sources of systemic risks from general-purpose AI

Centralized platforms deployed at scale

"The widespread use of common AI platforms can create centralized points of failure, making systems more vulnerable to disruptions or attacks"

From A Taxonomy of Systemic Risks from General-Purpose AI (Uuk2025)

Domain 2 2.2 Human Unintentional Post-deployment
61.02.33 · Risk Sub-Category

Sources of systemic risks from general-purpose AI

Limitations in adversarial robustness

"AI models and systems are vulnerable to manipulation through adversarial inputs."

From A Taxonomy of Systemic Risks from General-Purpose AI (Uuk2025)

Domain 2 2.2 Human Intentional Post-deployment
61.02.42 · Risk Sub-Category

Sources of systemic risks from general-purpose AI

Risks from network interconnectivity

"The interconnectedness of AI networks can create vulnerabilities, where issues in one part of the network can have cascading effects across the system."

From A Taxonomy of Systemic Risks from General-Purpose AI (Uuk2025)

Domain 2 2.2 Other Other Other

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