Uncertainty Quantification

Definitions

1. The formal measurement and expression of uncertainty in model outputs, predictions, or system behavior. Uncertainty quantification is important in high-stakes domains where decisions should reflect confidence level, not just point predictions.

   In plain English: Measuring and expressing how uncertain the model is.

   Example: "The medical triage project required stronger uncertainty quantification before model scores could be shown to clinicians."

Related Terms

• Gaussian Process
• AI Metric
• Goodhart's Law AI
• Hallucination Rate
• Model Metric
• Token Count
• Uncertainty
• Uncertainty Estimation
• Validation Metric