Face-Matching Lineups: A Method to Control Mistaken Identifications in Video Evidence

When crime is caught on video, suspects can be identified by matching their faces to the perpetrator in the footage. However, errors in face-matching decisions have led to wrongful arrests. We tested face-matching in a nonprofessional student sample from a Canadian university (N = 905) with one-to-one comparisons and lineups. On the basis of findings in the eyewitness identification literature, we hypothesized that if face-matching lineups were fair and included known-innocent fillers (i.e., nonsuspects), they would control the error rate on trials with innocent suspects and increase the accuracy of suspect "match" responses. This hypothesis was supported. However, the accuracy of suspect-nonmatch responses was greater for one-to-one comparisons than for lineups. Additionally, we found that applying wisdom-of-crowd approaches to multiple independent decisions could eliminate errors in both match and nonmatch responses. Whether to control face-matching errors with lineups, with the wisdom-of-crowds, or with both depends on practical considerations.