Skilled or unskilled, but still unaware of it: How perceptions of difficulty drive miscalibration in relative comparisons.

It is proposed that a noise-plus-bias model of judgment is sufficient to explain the relation between skill level and accuracy of judgments of relative standing, and that judges at all skill levels are subject to similar degrees of error.

Abstract

People are inaccurate judges of how their abilities compare to others'. J. Kruger and D. Dunning (1999, 2002) argued that unskilled performers in particular lack metacognitive insight about their relative performance and disproportionately account for better-than-average effects. The unskilled overestimate their actual percentile of performance, whereas skilled performers more accurately predict theirs. However, not all tasks show this bias. In a series of 12 tasks across 3 studies, the authors show that on moderately difficult tasks, best and worst performers differ very little in accuracy, and on more difficult tasks, best performers are less accurate than worst performers in their judgments. This pattern suggests that judges at all skill levels are subject to similar degrees of error. The authors propose that a noise-plus-bias model of judgment is sufficient to explain the relation between skill level and accuracy of judgments of relative standing.