BackData bias
Data bias
Risk Domain
Unequal treatment of individuals or groups by AI, often based on race, gender, or other sensitive characteristics, resulting in unfair outcomes and unfair representation of those groups.
"Specifically, data bias refers to certain groups or certain types of elements that are over-weighted or over-represented than others in AI/ ML models, or variables that are crucial to characterize a phenomenon of interest, but are not properly captured by the learned models."(p. 2)
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)
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
Model prediction uncertainty
7.3 Lack of capability or robustnessAI systemUnintentionalOther