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Calibration

The degree to which a model's predicted probabilities match the actual likelihood of outcomes, ensuring that a model's confidence levels reflect its true accuracy.

In plain language

When a model says it is 90 percent confident, a well-calibrated model is right about 90 percent of the time. A poorly calibrated model might be right only 70 percent of the time while claiming 90 percent confidence.

Why this matters

Calibration directly impacts the quality of human decision-making that relies on AI recommendations. A well-calibrated model helps decision makers appropriately weight AI advice. Your governance framework should require calibration assessment as part of model validation before deployment.

Relevance

Implementation

Calibration is a measurable property assessed during model validation that determines how much weight decision makers should place on AI recommendations.

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