MIT AI Risk Repository
Browse AI risks
6 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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"Content might not be clearly disclosed as AI generated."
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"Without access to the training data, the types of explanations a model can provide are limited and more likely to be incorrect."
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"The content of the training data used for generating the model’s output is not accessible."
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"Explanations for model output decisions might be difficult, imprecise, or not possible to obtain."
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"Source attribution is the AI system's ability to describe from what training data it generated a portion or all its output. Since current techniques are based on approximations, these attributions might be incorrect."
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"Lack of model transparency is due to insufficient documentation of the model design, development, and evaluation process and the absence of insights into the inner workings of the model."
Informational only, not legal advice. Verify every claim against the linked official sources and consult qualified counsel before acting.