A risk analyst discovers that an AI-powered loan approval model produces significantly higher denial rates for applicants from zip codes with large minority populations. Which type of AI risk does this most directly represent?
Select an answer to reveal the explanation.
Short Explanation and Infographic
Here's the deal — b is correct because using zip code as a feature can act as a proxy for race, producing disparate impact even when race is not explicitly included — this is proximate discrimination via correlated features. A is wrong because drift refers to model performance degradation over time, not structural bias.
Full explanation below image
Full Explanation
B is correct because using zip code as a feature can act as a proxy for race, producing disparate impact even when race is not explicitly included — this is proximate discrimination via correlated features. A is wrong because drift refers to model performance degradation over time, not structural bias. C is wrong because adversarial perturbation is a deliberate attack on inputs, not a systemic bias pattern. D is wrong because concept drift refers to changes in the relationship between features and outcomes over time.