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AI Risk

Lack of Interpretability

Due to the black box nature of most machine learning models, users typically are not able to understand the reasoning behind the model decisions

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AI Risk7. AI System Safety, Failures, & Limitations7.4 > Lack of transparency or interpretability2 - Post-deployment

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Techniques0Attack methods connected to this risk.
Mitigations0Defenses that may help with related attacks.
Domain7. AI System Safety, Failures, & LimitationsThe broad risk area this belongs to.

Risk profile

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Domain7. AI System Safety, Failures, & Limitations
Subdomain7.4 > Lack of transparency or interpretability
Entity2 - AI
Intent2 - Unintentional
Timing2 - Post-deployment
CategoryExplainability & Reasoning
SubcategoryLack of Interpretability

Related techniques

Attack methods connected to this risk.

No linked attack methods. No AI attack method is connected to this risk in the current data.

Suggested mitigations

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No propagated mitigations. No defense is available through the connected attack methods.

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