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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"Economic disruptions ranging from large impacts on the labor market to broader economic changes that could lead to exacerbated wealth inequality, instability in the financial system, labor exploitation or other economic dimensions."
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61.02.01 · Risk Sub-Category
Sources of systemic risks from general-purpose AI
Ability to automate jobs
"The ability to automate jobs by AI models and systems can lead to significant job displacement, economic disruption, and social inequality."
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61.02.10 · Risk Sub-Category
Sources of systemic risks from general-purpose AI
Capabilities that enable substitution of humans
"The progressive replacement of human roles by AI models and systems can lead to societal disruption."
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61.02.25 · Risk Sub-Category
Sources of systemic risks from general-purpose AI
Exploitation in AI development
"Outsourcing tasks like data labeling to low-income countries can perpetuate inequality."
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.