MIT AI Risk Repository
Browse AI risks
2 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.
-
16.01.00 · Risk Category
"Speech can create a range of harms, such as promoting social stereotypes that perpetuate the derogatory representation or unfair treatment of marginalised groups [22], inciting hate or violence [57], causing profound offence [199], or reinforcing social norms that exclude or marginalise identities [15,58]. LMs that faithfully mirror harmful language present in the training data can reproduce these harms. Unfair treatment can also emerge from LMs that perform better for some social groups than others [18]. These risks have been widely known, observed and documented in LMs. Mitigation approache
-
16.01.02 · Risk Sub-Category
Risk area 1: Discrimination, Hate speech and Exclusion
Hate speech and offensive language
"LMs may generate language that includes profanities, identity attacks, insults, threats, language that incites violence, or language that causes justified offence as such language is prominent online [57, 64, 143,191]. This language risks causing offence, psychological harm, and inciting hate or violence."
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.