Predicting political elections from rapid and unreflective face judgments

Abstract

Here we show that rapid judgments of competence based solely on the facial appearance of candidates predicted the outcomes of gubernatorial elections, the most important elections in the United States next to the presidential elections. In all experiments, participants were presented with the faces of the winner and the runner-up and asked to decide who is more competent. To ensure that competence judgments were based solely on facial appearance and not on prior person knowledge, judgments for races in which the participant recognized any of the faces were excluded from all analyses. Predictions were as accurate after a 100-ms exposure to the faces of the winner and the runner-up as exposure after 250 ms and unlimited time exposure (Experiment 1). Asking participants to deliberate and make a good judgment dramatically increased the response times and reduced the predictive accuracy of judgments relative to both judgments made after 250 ms of exposure to the faces and judgments made within a response deadline of 2 s (Experiment 2). Finally, competence judgments collected before the elections in 2006 predicted 68.6% of the gubernatorial races and 72.4% of the Senate races (Experiment 3). These effects were independent of the incumbency status of the candidates. The findings suggest that rapid, unreflective judgments of competence from faces can affect voting decisions.