Training Humans to Detect Children's Lies Through Their Facial Expressions

Abstract

The accurate detection of children's truthful and dishonest reports is essential as children can serve as important providers of information. Research using automated facial coding and machine learning found that children who were asked to lie about an event were more likely to look surprised when hearing the first question during an interview about said event. The present studies explored if humans can be trained to look for surprised expressions to detect children's deception. Participants made lie-detection judgments after seeing children's expressions in very brief clips. In Study 1, we compared performance across a training condition and control condition, and in Study 2 we modified the training. With training, adults could detect children's lies at above-chance levels by viewing their facial expressions. Detection accuracy was further improved with modified training (Study 2), but participants held a consistent lie bias. Challenges with using facial expressions to detect deceit are discussed.