Learning to Quantify Uncertainty. Comment on Wisdom/Madness of Crowds and Perils of Point Forecasts by Roger Cooke.

Uncertainty quantification is an essential part of decision making, and when data is scarce or completely missing, uncertainty quantification is typically provided by experts in their assessments. Is uncertainty quantification a task that can be performed well or modestly? Can performance on this task be objectively measured? If so, can experts be trained to perform this task better and is this important for uncertainty quantification? The Classical Model for Structured Expert Judgment (SEJ, Cooke 1991) uses two performance measures, statistical accuracy and informativeness and assessments associated with higher statistical accuracy and informativeness reflect better uncertainty quantification. Cooke (2026) suggests that good uncertainty quantification is beneficial for achieving low absolute percentage error in point forecasts. In this comment, experiences on the effect of training from two recent studies are described. Experts who followed training appear to perform better at uncertainty quantification.