Judgment Extremity and Accuracy under Epistemic versus Aleatory Uncertainty

People view uncertain events as either knowable in principle (epistemic uncertainty), as fundamentally random (aleatory uncertainty), or as some mixture of the two. We show that people make more extreme probability judgments (i.e., closer to 0 or 1) for events they view as entailing more epistemic uncertainty and less aleatory uncertainty. We demonstrate this pattern in a domain where there is agreement concerning the balance of evidence (pairings of teams according to their seed in a basketball tournament) but individual differences in the perception of the epistemicness/aleatoriness of that domain (Study 1), across a range of domains that vary in their perceived epistemicness/aleatoriness (Study 2), in a single judgment task for which we only vary the degree of randomness with which events are selected (Study 3), and when we prime participants to see events as more epistemic or aleatory (Study 4). Decomposition of Brier scores suggests that the greater judgment extremity of more epistemic events can manifest as a trade-off between higher resolution and lower calibration. We further relate our findings to the hard-easy effect and also show that differences between epistemic and aleatory judgment are amplified when judges have more knowledge concerning relevant events.