Feedback Loops and Model Degradation Questions

Explain causes and mitigations for model degradation that arise from interactions between models and their environment. Topics include policy induced distribution shift and covariate shift, bandit and logged feedback challenges, label bias and selection bias, detection techniques for drift and degradation, counterfactual evaluation and importance weighting, strategies for automated retraining and human in the loop interventions, design patterns such as holdout populations and exploration policies, and considerations for adversarial or strategic behavior and long term stability.