MIT AI Risk Repository
Browse AI risks
9 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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10.01.00 · Risk Category
"The decision process used by AI systems has the potential to present biased choices, either because it acts from criteria that will generate forms of bias or because it is based on the history of choices."
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10.02.00 · Risk Category
"Poorly designed intelligent systems can cause moral, psychological, and physical harm. For example, the use of predictive policing tools may cause more people to be arrested or physically harmed by the police."
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10.03.00 · Risk Category
"The risks associated with the use of AI are still unpredictable and unprecedented, and there are already several examples that show AI has made discriminatory decisions against minorities, reinforced social stereotypes in Internet search engines and enabled data breaches."
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10.06.00 · Risk Category
"AI is providing more and more solutions for complex activities, and by taking advantage of this process, people are becoming able to perform a greater number of activities more quickly and accurately. However, the result of this innovation is enabling choices that were once exclusively human responsibility to be made by AI systems."
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10.04.00 · Risk Category
"Eliminated jobs in various types of companies."
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10.09.00 · Risk Category
"The production process of these devices requires raw materials such as nickel, cobalt, and lithium in such high quantities that the Earth may soon no longer be able to sustain them in sufficient quantities."
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10.05.00 · Risk Category
"In situations in which the development and use of AI are not explained to the user, or in which the decision processes do not provide the criteria or steps that constitute the decision, the use of AI becomes inexplicable."
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[not defined in text]
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10.08.00 · Risk Category
[not defined in text]
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.