BackOpacity
Opacity
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.
"Stems from the mismatch between mathematical optimization in high-dimensionality characteristic of machine learning and the demands of human-scale reasoning and styles of semantic interpretation."(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
Power
6.1 Power centralization and unfair distribution of benefitsHumanIntentionalOther