Instruction: Outline a system for continuously monitoring and detecting bias in deployed ML models, including corrective measures.
Context: This question assesses the candidate's expertise in implementing systems to ensure fairness and mitigate bias in ML models throughout their lifecycle.
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I would monitor bias post-deployment by tracking performance, calibration, decision rates, and error patterns across relevant groups or segments over time. The system needs both technical metrics and business-context metrics, because some fairness failures show up as workflow outcomes rather...