BackModel prediction uncertainty
Model prediction uncertainty
Risk Domain
AI systems that fail to perform reliably or effectively under varying conditions, exposing them to errors and failures that can have significant consequences, especially in critical applications or areas that require moral reasoning.
"Uncertainty in model prediction plays an important role in affecting decision-making activities, and the quantified uncertainty is closely associated with risk assessment. In particular, uncertainty in model prediction underpins many crucial decisions related to life or safety- critical applications [73]."(p. 6)
Entity— Who or what caused the harm
Intent— Whether the harm was intentional or accidental
Timing— Whether the risk is pre- or post-deployment
Other risks from Zhang et al. (2022) (6)
Data bias
1.1 Unfair discrimination and misrepresentationAI systemUnintentionalPre-deployment
Dataset shift
7.3 Lack of capability or robustnessAI systemUnintentionalOther
Out-of-domain data
7.3 Lack of capability or robustnessAI systemUnintentionalOther
Adversarial attack
2.2 AI system security vulnerabilities and attacksHumanIntentionalOther
Model bias
1.1 Unfair discrimination and misrepresentationOtherUnintentionalPre-deployment
Model misspecification
7.3 Lack of capability or robustnessAI systemUnintentionalOther