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.
"Models can be affected by poor confidence calibration [85], where the predicted probabilities do not accurately reflect the true likelihood of ground truth cor- rectness. This miscalibration makes it difficult to interpret the model’s predic- tions reliably, as high accuracy does not guarantee that the confidence levels are meaningful. This can cause overconfidence in incorrect predictions or un- derconfidence in correct ones."
Domain7. AI System Safety, Failures, & Limitations
Subdomain7.3 > Lack of capability or robustness
Entity3 - Other
Intent2 - Unintentional
Timing3 - Other
CategoryModel Development
SubcategoryTraining-related (Poor model confidence calibration)
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.
Included resource
Risk Sources and Risk Management Measures in Support of Standards for General-Purpose AI Systems
Original source
MIT AI Risk Repository
Open the public repository used for AI risk records and taxonomy fields.