Finding Needles in Haystacks: Identity Mismatch Frequency and Facial Identity Verification

Accurate person identification is central to all security, police, and judicial systems. A commonplace method to achieve this is to compare a photo-ID and the face of its purported owner. The critical aspect of this task is to spot cases in which these two instances of a face do not match. Studies of person identification show that these instances often go undetected when mismatches occur regularly in an experiment, but this differs from everyday operations in which identity mismatches are rare. The current study therefore examined whether infrequent identity mismatches are more likely to go undetected by observers. In Experiments 1 and 2, identity mismatches were detected equally under low (2%) and high (50%) mismatch prevalence. This pattern persisted when viewing conditions were optimized for person identification in Experiment 3, by using a card-sorting task in which all face identities could be viewed repeatedly, and also under increased task difficulty, by constraining viewing conditions temporally in Experiment 4. These results imply that the infrequent occurrence of identity mismatches in security settings such as passport control does not impair an observer’s ability to detect these important events.