The Wisdom of the Crowd Can Unmask Faces

Abstract

Accurately determining whether two images show the same person is a surprisingly difficult task, which becomes even harder if one or both faces are wearing medical face masks. Attempts to improve unfamiliar face matching accuracy have generally had limited success. Although one brief training program improved masked face matching accuracy by 4.9%, this increase would not overcome the entire performance deficit caused by masks. Here, we investigate whether combining independent identification decisions from different individuals can improve masked face matching performance through the wisdom of the crowd effect. Accuracy gains emerged reliably after combining the decisions of three individuals, culminating in significant improvements of 11%–26% among the largest crowds. Despite creating crowds of up to 80 people, half of the eventual improvement had generally already occurred in crowds of 6 individuals. The wisdom of the crowd effect is a highly effective approach to improving accuracy when identifying masked faces.