Designing human oversight for ML systems

Human oversight is essential when models affect decisions. Data scientists must define who intervenes, when alerts fire, and what review processes exist. Discuss concrete escalation paths, interpreter-friendly outputs, and training for reviewers so human-in-the-loop checks reduce harm without becoming bottlenecks.

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