MIT AI Risk Repository
Browse AI risks
8 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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Avoiding unsafe and illegal outputs, and leaking private information
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LLMs are found to generate answers that contain violent content or generate content that responds to questions that solicit information about violent behaviors
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LLMs have been shown to be a convenient tool for soliciting advice on accessing, purchasing (illegally), and creating illegal substances, as well as for dangerous use of them
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LLMs can be leveraged to solicit answers that contain harmful content to children and youth
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LLMs have the capability to generate sex-explicit conversations, and erotic texts, and to recommend websites with sexual content
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30.06.00 · Risk Category
LLMs are expected to reflect social values by avoiding the use of offensive language toward specific groups of users, being sensitive to topics that can create instability, as well as being sympathetic when users are seeking emotional support
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language being rude, disrespectful, threatening, or identity-attacking toward certain groups of the user population (culture, race, and gender etc)
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it is important to build high-quality locally collected datasets that reflect views from local users to align a model’s value system
Informational only, not legal advice. Verify every claim against the linked official sources and consult qualified counsel before acting.