BackFairness & Bias
Fairness & 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.
"The potential for AI systems to make decisions that systematically disadvantage certain groups or individuals. Bias can stem from training data, algorithmic design, or deployment practices, leading to unfair outcomes and possible legal ramifications."(p. 23048)
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 Sherman & Eisenberg (2023) (8)
Abuse & Misuse
4.2 Cyberattacks, weapon development or use, and mass harmHumanIntentionalPost-deployment
Compliance
6.5 Governance failureAI systemOtherPost-deployment
Environmental & Societal Impact
6.0 Socioeconomic & EnvironmentalOtherOtherPost-deployment
Explainability & Transparency
7.4 Lack of transparency or interpretabilityAI systemOtherOther
Long-term & Existential Risk
7.1 AI pursuing its own goals in conflict with human goals or valuesOtherOtherPost-deployment
Performance & Robustness
7.3 Lack of capability or robustnessAI systemUnintentionalPost-deployment