Your question is Demographic Bias Mitigation. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
How do you account for demographic bias in training data to ensure equitable model performance?
Discuss a practical workflow for identifying representation and label bias, selecting appropriate subgroup fairness metrics, and mitigating disparities during model development. Explain how you would compare performance across demographic and intersectional groups, avoid leakage from sensitive attributes, and decide whether a fairness intervention is acceptable given its effect on overall model utility.
