APromptRiskDBThreat intelligence atlas
AI Risk

Risks from models and algorithms (Risks of explainability)

"AI algorithms, represented by deep learning, have complex internal workings. Their black-box or grey-box inference process results in unpredictable and untraceable outputs, making it challenging to quickly rectify them or trace their origins for accountability should any anomalies arise."

View related techniquesRead profile
AI Risk7. AI System Safety, Failures, & Limitations7.4 > Lack of transparency or interpretability3 - Other

Record summary

A quick snapshot of what this page covers.

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

How this risk is described and categorized.

Domain7. AI System Safety, Failures, & Limitations
Subdomain7.4 > Lack of transparency or interpretability
Entity2 - AI
Intent2 - Unintentional
Timing3 - Other
CategoryAI's inherent safety risks
SubcategoryRisks from models and algorithms (Risks of explainability)

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

Defenses that may help with related attacks.

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

Source

Research source for this risk, when available.