1. Bias & Fairness Controls advanced

    A lending model shows different approval rates across demographic groups. The business asks you to "make it fair". What do you do?

    2 min answer fairnessmlgovernance
  2. Bias & Fairness Controls intermediate

    A lending team's fairness dashboard shows approval-rate parity across protected groups, refreshed monthly, green for six months. Review it. What would you remove, what would you change, and what would you leave alone?

    3 min answer fairnessmetricsmonitoringproxies
  3. Bias & Fairness Controls advanced

    A model used in underwriting must be demonstrably fair. What controls are architectural, and what is the hard part?

    2 min answer digitfairnesssubgroupsproxies
  4. Bias & Fairness Controls advanced

    A model's outcomes differ across demographic groups. What can architecture actually do about it?

    2 min answer fairnessbiasmeasurementtradeoffs
  5. Bias & Fairness Controls beginner Multiple choice

    A team removes the ethnicity field from a credit model's training data and tells the risk committee the model can no longer discriminate. What is the most accurate response?

    2 min answer fairnessproxy-variablesunawarenessmonitoring
  6. Bias & Fairness Controls advanced

    An interviewer says — you run architecture for a consumer lending platform. The regulator expects evidence that your model is not producing disparate outcomes across ethnic groups. Legal tells you that you may not collect applicants' ethnicity. Where do you take this?

    3 min answer fairnessproxy-inferencebisgmeasurement