The Effects of Presenting Imprecise Probabilities in Intelligence Forecasts

How to assess and present analytic uncertainty to policymakers has emerged as an important topic in risk and policy analysis. Due to the complexity and deep uncertainty present in many forecasting domains, these reports are often fraught with analytic uncertainty. In three studies, we explore the effect of presenting probability assessments and analytic uncertainty through probability ranges. Participants were presented with mock intelligence forecasts that include narrative evidence as well as numerical probability assessments. Participants were sensitive to the ambiguity communicated through the confidence range. The narrative appeared to have a smaller effect on judgments when accompanied by a probability range as opposed to a point assessment. In one study, participants also thought that the probability range was more useful for decision making at a higher probability whereas the point estimate was more useful at a lower probability. When evaluating a forecast in hindsight, decisionmakers tended to report lower levels of blame and higher levels of source credibility for forecasts that reported ranges as compared to point assessments. These findings suggest that decisionmakers are not necessarily "ambiguity averse" in the forecasting context. Presenting ranges of probability may have distinct advantages as a way to communicate probability and analytic confidence to decisionmakers.