Uncertainty concerns

Mitigation strategy

1. Implement rigorous Uncertainty Quantification (UQ) and calibration techniques, such as Conformal Prediction or post-hoc methods like Platt scaling, to ensure the model's assigned confidence scores reliably reflect the true probability of prediction correctness. 2. Establish and enforce confidence-based fail-safe design principles, mandating a Human-in-the-Loop intervention or system deferral for any output below a pre-defined critical confidence threshold, particularly in high-stakes domains. 3. Integrate and prioritize uncertainty-aware evaluation metrics into the model lifecycle, utilizing benchmarks that reward models for appropriate abstention or well-calibrated confidence rather than solely maximizing predictive accuracy.