BackExplainability
Explainability
Risk Domain
Challenges in understanding or explaining the decision-making processes of AI systems, which can lead to mistrust, difficulty in enforcing compliance standards or holding relevant actors accountable for harms, and the inability to identify and correct errors.
"Any action or procedure performed by a model with the intention of clarifying or detailing its internal functions."(p. 31)
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 Teixeira et al. (2022) (15)
Accountability
7.4 Lack of transparency or interpretabilityOtherOtherOther
Manipulation
4.1 Disinformation, surveillance, and influence at scaleAI systemIntentionalPost-deployment
Accuracy
7.3 Lack of capability or robustnessAI systemUnintentionalPost-deployment
Moral
7.3 Lack of capability or robustnessOtherUnintentionalPost-deployment
Bias
1.1 Unfair discrimination and misrepresentationAI systemUnintentionalPre-deployment
Opacity
7.4 Lack of transparency or interpretabilityAI systemUnintentionalPost-deployment