Video-Recordings of Eyewitness Identification in Actual Cases: The Postdictive Value of Eyewitness Behaviors

Iowa State University, Ames IA

Investigators

Abstract

Over 70% of DNA exonerations have been cases of mistaken eyewitness identification. Based on recommendations from eyewitness scientists, a large number of jurisdictions across the country have reformed their identification procedures to address this problem. Nevertheless, even the best lineup procedures fail to weed out all mistaken identifications. Hence, police and prosecutors still must attempt to sort between reliable identifications and unreliable identifications even when the best lineup procedures are followed. It is important to determine what variables can help police and prosecutors with this task. Postdiction variables are a particularly promising class of variables. Postdiction variables are variables that are influenced by the presence or absence of the guilty suspect in the lineup. These include eyewitness behaviors such as expressed level of confidence, the amount of time it takes the witness to make an identification decision, visible evidence of effort, verbal utterances, among others. The purpose of the present work is to examine how well postdiction variables extracted from video recordings of real-world witnesses making identification decisions can sort between reliable and unreliable identification decisions. To the extent that postdiction variables prove useful for sorting between reliable identifications and unreliable identifications, these findings would also encourage jurisdictions that are not yet video recording identification procedures to begin doing so. Indeed, only by video recording the entirety of the identification procedure can these jurisdictions ensure a complete and accurate record of these variables that can be used to sort between reliable and unreliable identifications. The goal of this research is to determine what combination of postdictors best sort between reliable eyewitness identifications and unreliable eyewitness identifications in real-world lineups. The findings will then be leveraged to develop an algorithm that police and prosecutors can use to assess the reliability of eyewitness identifications in future investigations. The District Attorney’s Office of Santa Clara County, CA and the San Jose Police Department will provide video-recordings of witnesses completing actual police lineups. Santa Clara County is unique as an early adopter of best-practice eyewitness identification procedures (a requirement for valid assessment of postdiction variables) and more recently implementing a policy of video-recording all lineups. As these videos become available, blind scorers (blind as to whether the identified person is the suspect or a filler) will assess a host of known postdiction variables. These postdiction scores will then be regressed on the outcome variable of whether the witness identified the suspect or a known-innocent filler. A critical mass of suspect identifications are likely to be culprit identifications whereas all identifications of fillers are definitive instances of mistaken identifications. Accordingly, postdiction variables that are useful for separating accurate from mistaken identifications should distinguish between suspect identifications and filler identifications. In addition to examining the predictive validity of known postdiction variables (e.g., confidence, decision time, verbal utterances), we will use an extensive coding scheme to code for numerous other eyewitness behaviors and we will examine whether these additional eyewitness behaviors can improve classification performance over and above the performance achieved with know postdiction variables. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.