The main goal of many political and intelligence forecasts is to effectively communicate risk information to decision makers (i.e. consumers). Standard reporting most often consists of a narrative discussion of relevant evidence concerning a threat, and rarely involves numerical estimates of uncertainty (e.g. a 5% chance). It is argued that numerical estimates of uncertainty will lead to more accurate representations of risk and improved decision making on the part of intelligence consumers. Little work has focused on how well consumers understand and use forecasts that include numerical estimates of uncertainty. Participants were presented with simulated intelligence forecasts describing potential terrorist attacks. These forecasts consisted of a narrative summary of the evidence related to the attack and numerical estimates of likelihood and potential harm. The primary goals were to explore how the structure of the narrative summary, the format of likelihood information, and the numerical ability (numeracy) of consumers affected perceptions of intelligence forecasts. Consumers perceived forecasts with numerical estimates of likelihood and potential harm as more useful than forecasts with only a narrative evidence summary. However, consumer's risk and likelihood perceptions were more greatly affected by the narrative evidence summary than the stated likelihood information. These results show that even "precise" numerical estimates of likelihood are not necessarily evaluable by consumers and that perceptions of likelihood are affected by supporting narrative information. Numeracy also moderated the effects of stated likelihood and the narrative evidence summary. Consumers higher in numeracy were more likely to use the stated likelihood information and consumers lower in numeracy were more likely to use the narrative evidence to inform their judgments. The moderating effect of likelihood format and consumer's perceptions of forecasts in hindsight are also explored.

Explicit estimates of uncertainty are not necessarily useful to all intelligence consumers, particularly when presented with supporting narrative evidence. How consumers respond to intelligence forecasts depends on the structure of any supporting narrative information, the format of the explicit uncertainty information, and the numerical ability of the individual consumer. Forecasters should be sensitive to these three issues when presenting forecasts to consumers.