Instruction: Discuss your methods for identifying, assessing, and reducing bias in ML models throughout their lifecycle.
Context: This question is intended to understand the candidate's awareness and strategies for addressing bias in machine learning models.
Official answer available
Preview the opening of the answer, then unlock the full walkthrough.
The way I'd approach it in an interview is this: I manage bias as a system property, not just a dataset issue. That means checking data representation, label quality, feature proxies, model behavior across groups, and whether the deployment context amplifies...