MIT AI Risk Repository
Browse AI risks
7 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.
-
"Large-scale influence on communication and information systems, and epistemic processes more generally."
-
"AI could be used to develop sophisticated tools to manipulate and persuade individuals."
-
61.02.04 · Risk Sub-Category
Sources of systemic risks from general-purpose AI
Advertising-driven models
"AI models and systems underpin the advertising approaches that drive much of the internet, potentially influencing societal behavior."
-
61.02.05 · Risk Sub-Category
Sources of systemic risks from general-purpose AI
AI in totalitarian regimes
"AI-based surveillance and manipulation could be used to maintain global totalitarian regimes."
-
61.02.34 · Risk Sub-Category
Sources of systemic risks from general-purpose AI
Limitations in model generative accuracy
"AI-generated deepfakes can create convincingly realistic but entirely fabricated information."
-
61.02.43 · Risk Sub-Category
Sources of systemic risks from general-purpose AI
Surveillance capabilities
"AI models and systems may grant governments or corporations increased monitoring over individuals."
-
61.02.49 · Risk Sub-Category
Sources of systemic risks from general-purpose AI
Widespread use of persuasion tools
"Widespread use of AI-powered persuasion tools could lead to systemic harm"
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.