When leaders disclose uncertainty: Effects of expressing internal and external uncertainty about a decision.

It is generally assumed that decision-makers appear more competent and trustworthy when exuding confidence in their choices. However, many decisions are by their nature uncertain. Is it possible for a decision-maker to admit uncertainty and still be trusted? We propose that the communicated type of uncertainty may matter. Internal uncertainty, which signals lack of knowledge or a low degree of belief, may be viewed more negatively than external uncertainty, which is associated with randomness and complexity. The results of a series of experiments suggested that people viewed leaders as more competent when they expressed uncertainty about a decision in external ("It is uncertain") rather than internal terms ("I am uncertain"), overall effect size d = 0.45 [0.16, 0.74]. Paradoxically, when asked directly, participants expressed that leaders should be open about uncertainty rather than exuding confidence and downplaying uncertainty. A final study suggested that decision makers were more willing to reveal uncertainty about a choice to others when they perceived the uncertainty as more external and less internal and expected more positive and fewer negative consequences from expressing external rather than internal uncertainty.

People prefer to predict middle, most likely quantitative outcomes (not extreme ones), but they still over-estimate their likelihood.

Past work showed a tendency to associate verbal probabilities (e.g., possible, unlikely) with extreme quantitative outcomes, and to over-estimate the outcomes' probability of occurrence. In the first four experiments (Experiment 1, Experiments 2a-c), we tested whether this "extremity effect" reflects a general preference for extreme (vs central or less extreme) values of a distribution. Participants made predictions based on a frequency distribution in two scenarios. We did not find a preference for extreme outcomes. Instead, most of the participants made a prediction about the middle, most frequent outcome of the distribution (i.e., the modal outcome), but still over-estimated the outcomes' probabilities. In Experiment 3, we tested whether the over-estimation could be better explained by an "at least"/"at most" reading of the predictions. We found that only a minority of participants interpreted predictions as the lower/upper bounds of an open interval and that these interpretations were not associated with heightened probability estimates. In the final three experiments (Experiments 4a-c), we tested whether participants perceived extreme outcome predictions as more correct, useful and interesting than modal outcome predictions. We found that extreme and modal predictions were considered equally correct, but modal predictions were judged most useful, whereas extreme predictions were judged to be more interesting. Overall, our results indicate that the preference for extreme outcomes is limited to specific verbal probability expressions, whereas the over-estimation of the probability of quantitative outcomes may be more general than anticipated and applies to non-extreme values as well.