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An Exploratory Diagnosis of Artificial Intelligence Risks for a Responsible Governance

Teixeira et al. (2022)

SourceDOI
Category
Risk Domain
1Discrimination & Toxicity
1.3Unequal performance across groups

Accuracy and effectiveness of AI decisions and actions are dependent on group membership, where decisions in AI system design and biased training data lead to unequal outcomes, reduced benefits, increased effort, and alienation of users.

"Impartial and just treatment without favouritism or discrimination."(p. 31)

Entity— Who or what caused the harm

Human

Due to a decision or action made by humans

AI system

Due to a decision or action made by an AI system

Other

Due to some other reason or is ambiguous

Intent— Whether the harm was intentional or accidental

Intentional

Due to an expected outcome from pursuing a goal

Unintentional

Due to an unexpected outcome from pursuing a goal

Other

Without clearly specifying the intentionality

Timing— Whether the risk is pre- or post-deployment

Pre-deployment

Occurring before the AI is deployed

Post-deployment

Occurring after the AI model has been trained and deployed

Other

Without a clearly specified time of occurrence

Other risks from Teixeira et al. (2022) (15)

Accountability

7.4 Lack of transparency or interpretability
OtherOtherOther

Manipulation

4.1 Disinformation, surveillance, and influence at scale
AI systemIntentionalPost-deployment

Accuracy

7.3 Lack of capability or robustness
AI systemUnintentionalPost-deployment

Moral

7.3 Lack of capability or robustness
OtherUnintentionalPost-deployment

Bias

1.1 Unfair discrimination and misrepresentation
AI systemUnintentionalPre-deployment

Opacity

7.4 Lack of transparency or interpretability
AI systemUnintentionalPost-deployment
View all 15 risks from this paper →