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Recent advances in artificial intelligence (AI) enable the generation of realistic facial images that can be used in police lineups. The use of AI image generation offers pragmatic advantages in that it allows practitioners to generate filler images directly from the description of the culprit using text-to-image generation, avoids the violation of identity rights of natural persons who are not suspects and eliminates the constraints of being bound to a database with a limited set of photographs. However, the risk exists that using AI-generated filler images provokes more biased selection of the suspect if eyewitnesses are able to distinguish AI-generated filler images from the photograph of the suspect’s face. Using a model-based analysis, we compared biased suspect selection directly between lineups with AI-generated filler images and lineups with database-derived filler photographs. The results show that the lineups with AI-generated filler images were perfectly fair and, in fact, led to less biased suspect selection than the lineups with database-derived filler photographs used in previous experiments. These results are encouraging with regard to the potential of AI image generation for constructing fair lineups which should inspire more systematic research on the feasibility of adopting AI technology in forensic settings.

The you of my imagination was forever one-legged, hopping to the bathroom every morning of your life rattling every window in the house since childhood since childhood buying a pair of shoes and leaving one tied onto the manufactured leg each night. No truth, only clues like the smiling young recruit in an army cap in a sepia-toned photo, a stranger in a picture frame. Olin Dodson (MA, Sonoma State University; MA, San Francisco Theological Seminary) is an avid grandfather, retired psychotherapist, and author of the memoir, Melissa's Gift (2012).

Eyewitness-identification studies have focused on the idea that unfair lineups (i.e., ones in which the police suspect stands out) make witnesses more willing to identify the police suspect. We examined whether unfair lineups also influence subjects' ability to distinguish between innocent and guilty suspects and their ability to judge the accuracy of their identification. In a single experiment (N = 8,925), we compared three fair-lineup techniques used by the police with unfair lineups in which we did nothing to prevent distinctive suspects from standing out. Compared with the fair lineups, doing nothing not only increased subjects' willingness to identify the suspect but also markedly impaired subjects' ability to distinguish between innocent and guilty suspects. Accuracy was also reduced at every level of confidence. These results advance theory on witnesses' identification performance and have important practical implications for how police should construct lineups when suspects have distinctive features.

Laboratory-based mock crime studies have often been interpreted to mean that (i) eyewitness confidence in an identification made from a lineup is a weak indicator of accuracy and (ii) sequential lineups are diagnostically superior to traditional simultaneous lineups. Largely as a result, juries are increasingly encouraged to disregard eyewitness confidence, and up to 30% of law enforcement agencies in the United States have adopted the sequential procedure. We conducted a field study of actual eyewitnesses who were assigned to simultaneous or sequential photo lineups in the Houston Police Department over a 1-y period. Identifications were made using a three-point confidence scale, and a signal detection model was used to analyze and interpret the results. Our findings suggest that (i) confidence in an eyewitness identification from a fair lineup is a highly reliable indicator of accuracy and (ii) if there is any difference in diagnostic accuracy between the two lineup formats, it likely favors the simultaneous procedure.

The conceptual frameworks provided by both the lineups-as-experiments analogy and signal detection theory have proven important to understanding how eyewitness lineups work. The lineups-as-experiments analogy proposes that when investigators use a lineup procedure, they are acting as experimenters and should therefore follow the same tried-and-true procedures that experimenters follow when executing an experiment. Signal detection theory offers a framework for distinguishing between factors that improve the trade-off between culprit and innocent-suspect identifications and factors that affect the frequency of suspect identifications. We integrate these two conceptual frameworks. We argue that an eyewitness lineup procedure is characterized by two simultaneous signal detection tasks. On one hand, the witness is tasked with determining whether the culprit is present in the lineup and identifying that person. On the other hand, the investigator knows which lineup member is the suspect and which lineup members are known-innocent fillers and is therefore tasked only with determining whether the suspect is the culprit. The investigator uses the witness’s identification decision and associated level of confidence to decide whether the suspect is the culprit. We leverage this realization to demonstrate a method for creating full receiver operating characteristic curves for eyewitness lineup procedures.

The primary argument for including large numbers of known-to-be innocent fillers in lineups is that guessing-based selections are dispersed among a large number of lineup members, leading to low innocent-suspect identification rates. However, a recent study using the two-high threshold eyewitness identification model has demonstrated advantages of smaller lineups at the level of the processes underlying the observable responses. Participants were more likely to detect the presence of the culprit and less likely to select lineup members based on guessing in smaller than in larger lineups. Nonetheless, at the level of observable responses, the rate of innocent-suspect identifications was higher in smaller compared to larger lineups due to the decreased dispersion of guessing-based selections among the lineup members. To address this issue, we combined smaller lineups with lineup instructions insinuating that the culprit was unlikely to be in the lineup. The goal was to achieve a particularly low rate of guessing-based selections. These lineups were compared to larger lineups with neutral instructions. In two experiments, culprit-presence detection occurred with a higher probability in smaller compared to larger lineups. Furthermore, instructions insinuating that the culprit was unlikely to be in the lineup reduced guessing-based selection compared to neutral instructions. At the level of observable responses, the innocent-suspect identification rate did not differ between smaller lineups with low-culprit-probability instructions and larger lineups with neutral instructions. The rate of culprit identifications was higher in smaller lineups with low-culprit-probability instructions than in larger lineups with neutral instructions.

The two-high threshold eyewitness identification model was applied to investigate the effects of lineup position on the latent cognitive processes underlying eyewitness responses in lineups. In two experiments with large sample sizes and random assignment of culprits and innocent suspects to all possible lineup positions, we examined how detection-based and non-detection-based processes vary across the positions of six-person photo lineups. Experiment 1 ( N  = 2586) served to investigate position effects in simultaneous lineups in which all photos were presented in a single row. Experiment 2 ( N  = 2581) was focused on sequential lineups. In both experiments, lineup position had no effect on the detection of the presence of the culprit. Guessing-based selection, in contrast, differed as a function of lineup position. Specifically, a lineup member placed in the first position in a lineup was significantly more likely to be selected based on guessing than lineup members placed in other positions. These results justify the practice of avoiding to place the suspect in the first position in a lineup, as this placement increases the suspect’s chance of being selected based on guessing.

Eyewitness identification is a pivotal issue in applied research because, in practice, a correct identification can help to remove a dangerous criminal from society, but a false identification can lead to the erroneous conviction of an innocent suspect. Consequently, psychologists have tried to ascertain the best procedures for collecting identification evidence, evaluating them using measures based on the ratio of correct to false identification rates. Unfortunately, ratio-based measures are ambiguous because they change systematically as a function of a witness's willingness to choose. In other words, a measure thought to index discriminability is instead fully confounded with response bias. A better method involves constructing receiver operating characteristic (ROC) curves. Using ROC curves, researchers can trace out discriminability across levels of response bias for each procedure. We illustrate the shortcomings of ratiobased measures and demonstrate why ROC analysis is required. In recent studies, researchers comparing simultaneous and sequential lineup procedures using ROC analyses have provided no evidence for the sequential superiority effect and instead have shown that the simultaneous procedure may be diagnostically superior. It is not yet clear which lineup procedure will prove to be generally superior, but it is clear that ROC analysis is the only way to make that determination.

Clark (2012) highlights an important issue that has received inadequate attention in the eyewitness memory literature: lineup procedures that reduce the false identification rate (a desirable effect) often tend to reduce the correct identification rate as well (an undesirable effect). Determining which procedure is diagnostically superior under those conditions is not easy. Clark (2012) showed that the procedure with the lower false identification rate could be associated with higher overall costs to society once costs and benefits are both taken into consideration. Beyond the issue of cost, we argue that Clark's (2012) observation has far reaching implications for evaluating the diagnostic performance of a lineup procedure. Specifically, the field of eyewitness memory has attempted to differentiate between lineup procedures by using various measures of probative value (such as the diagnosticity ratio). However, contrary to intuition, probative value is not a relevant consideration. Instead, lineup procedures should be compared using receiver operating characteristic analysis, as is routinely done in other applied fields (such as radiology).

A typical police lineup contains a photo of one suspect (who is innocent in a target-absent lineup and guilty in a target-present lineup) plus photos of five or more fillers who are known to be innocent. To create a fair lineup in which the suspect does not stand out, two filler selection methods are commonly used. In the first, fillers are selected if they are similar in appearance to the suspect. In the second, fillers are selected if they possess facial features included in the witness’s description of the culprit (e.g., “20-y-old white male”). The police sometimes use a combination of the two methods by selecting description-matched fillers whose appearance is also similar to that of the suspect in the lineup. Decades of research on which approach is better remains unsettled. Here, we tested a counterintuitive prediction made by a formal model based on signal detection theory: From a pool of acceptable description-matched photos, selecting fillers whose appearance is otherwise dissimilar to the suspect should increase the hit rate without affecting the false-alarm rate (increasing discriminability). In Experiment 1, we confirmed this prediction using a standard mock-crime paradigm. In Experiment 2, the effect on discriminability was reversed (as also predicted by the model) when fillers were matched on similarity to the perpetrator in both target-present and target-absent lineups. These findings suggest that signal-detection theory offers a useful theoretical framework for understanding eyewitness identification decisions made from a police lineup.