MIT AI Risk Repository
Browse AI risks
4 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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"The concentration of military, economic, or political power of entities in possession or control of AI or AI-enabled technologies."
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61.02.07 · Risk Sub-Category
Sources of systemic risks from general-purpose AI
Algorithmic monoculture
"The dominance of specific AI models could lead to a lack of diversity in approaches, amplifying systemic risks if these models fail."
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61.02.19 · Risk Sub-Category
Sources of systemic risks from general-purpose AI
Dependency on providers
"Excessive reliance on specific AI providers can lead to vulnerabilities due to lack of alternatives or interoperability."
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61.02.50 · Risk Sub-Category
Sources of systemic risks from general-purpose AI
Winner-take-all dynamics
"The competitive nature of AI development could lead to significant eco- nomic and security advantages for a few entities."
Disclaimer: informational only, not legal advice. Verify every claim against the linked official sources and consult a qualified lawyer before acting.
Frequently asked questions
Where do these risk entries come from?
The MIT AI Risk Repository, which extracts risks from dozens of published frameworks, taxonomies and papers and codes each one by domain and subdomain, and by a causal taxonomy of entity, intent and timing. This is a browseable copy, attributed and openly licensed, not original research.
What do entity, intent and timing mean?
They are the causal coding. Entity is whether a human or the AI system is the cause; intent is whether the harm was intentional or not; timing is whether it arises before or after deployment. Together they let you separate misuse from malfunction.
Can I export the results?
Yes, any filtered set exports as CSV or JSON, and every export carries the upstream source, licence and citation with it, because attribution is a condition of the licence rather than a courtesy.
What is the MIT AI Risk Repository?
A living database of AI risks extracted from published frameworks, taxonomies and papers, classified by a causal taxonomy of entity, intent and timing and by a domain taxonomy of seven domains and 24 subdomains. It is published by the MIT AI Risk Initiative under CC BY 4.0.