Thin-Slice Accuracy Depends on the Wisdom of Crowds: Aggregate Judgments Outperform Individual Judgments when Inferring Athletic Performance Based on Nonverbal Behavior

Abstract The present paper aims to resolve ambiguous findings on the accuracy or inaccuracy of human judgments based on sparse information by arguing that accurate thin-slice judgments can be understood as driven by the wisdom of the crowd. To test this hypothesis, participants estimated the performance of track and field athletes in different competitions based on thin slices of pre- and post-performance nonverbal behavior. Results suggest that averaged judgments based on thin slices of athletes’ nonverbal behavior (NVB) are correlated with actual performance and that averaged judgments are better than individual judgments, thus validating the wisdom of the crowd hypothesis. Taken together, the present paper suggests that understanding thin-slice judgments from a wisdom of the crowd perspective has the potential to resolve the apparent contradiction regarding the accuracy or inaccuracy of human judgments. Furthermore, the paper highlights the potential of averaged thin-slice judgments of naturally occurring NVB as an addition to resource consuming coding procedures.