Skip to content

CS Professional · Artificial Intelligence, Data Analytics and Cyber Security - Laws and Practice · Data Analytics

A lender builds a credit-scoring model trained on historical loan approvals. The model rejects applicants from certain pin codes at much higher rates, although pin code is not a legally protected attribute. Which ethical issue is most directly illustrated?

The issue is algorithmic bias through a proxy variable. Pin code can stand in for protected traits, so a model trained on biased past approvals reproduces discrimination even though no protected attribute is used directly.

  1. AAlgorithmic bias through a proxy variable that reproduces past discriminationCorrect
  2. BData localisation failure
  3. CEncryption weakness in data at rest
  4. DDenial of service on the scoring server

Explanation

Pin code can act as a proxy for community or income, so a model trained on biased history reproduces that bias even without using protected attributes. The issue concerns fairness of outputs, not storage location, encryption or availability.

Did you get it right without looking?

One question tells you little. A timed set on Data Analytics shows your real accuracy, how long you take and where you lose marks.

Practise Data AnalyticsFree diagnostic mock

More Data Analytics questions