Estimating the reliability of eyewitness identifications from police lineups

Feeling the future of eyewitness research

For decades, eyewitness memory research has had the worthy goal of minimizing the chances that an innocent suspect is falsely identified. However, this is not the only goal. Partial receiver operating characteristic (ROC) curves provide a way to identify lineup procedures that keep the false alarm rate low while also maximizing the hit rate. Recently, there have been attempts to extend the ROC curve into high false alarm rate regions that fair lineups are intentionally designed to avoid. These new full ROCs could provide a way for the police to circumvent the protections offered by fillers in a fair lineup. Moreover, these attempts to extend the ROC curve are not based on a mathematically coherent model of latent diagnostic signals. In this article, we empirically demonstrate how this lack of a solid foundation can lead to dubious conclusions, such as eyewitnesses possessing precognition and being able to reliably identify the person they will see commit a crime in the future.

Improving the diagnostic value of lineup rejections

Erroneous eyewitness identification evidence is likely the leading cause of wrongful convictions. To minimize this error, scientists recommend collecting confidence. Research shows that eyewitness confidence and accuracy are strongly related when an eyewitness identifies someone from an initial and properly administered lineup. However, confidence is far less informative of accuracy when an eyewitness identifies no one and rejects the lineup instead. In this study, I aimed to improve the confidence-accuracy relationship for lineup rejections in two ways. First, I aimed to find the lineup that yields the strongest confidence-accuracy relationship for lineup rejections by comparing the standard, simultaneous procedure used by police worldwide to the novel "reveal" procedure designed by scientists to boost accuracy. Second, I aimed to find the best method for collecting confidence. To achieve this secondary aim, I made use of machine-learning techniques to compare confidence expressed in words to numeric confidence ratings. First, I find a significantly stronger confidence-accuracy relationship for lineup rejections in the reveal than in the standard procedure regardless of the method used to collect confidence. Second, I find that confidence expressed in words captures unique diagnostic information about the likely accuracy of a lineup rejection separate from the diagnostic information captured by numeric confidence ratings. These results inform models of recognition memory and may improve the criminal-legal system by increasing the diagnostic value of a lineup rejection.

New Insights on Expert Opinion About Eyewitness Memory Research

Experimental psychologists investigating eyewitness memory have periodically gathered their thoughts on a variety of eyewitness memory phenomena. Courts and other stakeholders of eyewitness research rely on the expert opinions reflected in these surveys to make informed decisions. However, the last survey of this sort was published more than 20 years ago, and the science of eyewitness memory has developed since that time. Stakeholders need a current database of expert opinions to make informed decisions. In this article, we provide that update. We surveyed 76 scientists for their opinions on eyewitness memory phenomena. We compared these current expert opinions to expert opinions from the past several decades. We found that experts today share many of the same opinions as experts in the past and have more nuanced thoughts about two issues. Experts in the past endorsed the idea that confidence is weakly related to accuracy, but experts today acknowledge the potential diagnostic value of initial confidence collected from a properly administered lineup. In addition, experts in the past may have favored sequential over simultaneous lineup presentation, but experts today are divided on this issue. We believe this new survey will prove useful to the court and to other stakeholders of eyewitness research.

When is memory more reliable? Scientific findings, theories, and myths

The question of whether human memory is reliable generated extensive research. Memory is open to reconstruction and false retrieval of unpresented information or unexperienced events. These can create problems in judgments and decisions that rely on memory accuracy. In the case of eyewitness testimony, these problems can result in injustice. Then again, memory is also reliable enough. Information acquisition, processing, and retrieval capacity of our memory made it possible to survive the course of evolution. Our memory also makes it possible to continue our daily lives, most of the time without major problems. In the present review, we suggest that the right question to ask may not be whether memory is reliable, but rather to ask when and under what circumstances memory is more reliable. The review's educational aim is to identify the conditions under which memory is more versus less reliable, and its theoretical aim is to discuss memory reliability. We reviewed the literature on situational, emotional, social, and individual difference variables that affect memory reliability, identified the conditions under which memory is more versus less reliable, summarized these outcomes as easy-to-reach items, and discussed them in the light of major theories. Our discussion also touched upon the differentiation of societal myths about the reliability of memory from scientific findings, since believing in memory myths can also affect the reliability of memory. Awareness of the specific circumstances under which memory is more reliable can lead to the consideration of how much memory can be trusted under those specific circumstances.

Identifying unfamiliar voices: Examining the system variables of sample duration and parade size

Voice identification parades can be unreliable due to the error-prone nature of earwitness responses. UK government guidelines recommend that voice parades should have nine voices, each played for 60 s. This makes parades resource-consuming to construct. In this article, we conducted two experiments to see if voice parade procedures could be simplified. In Experiment 1 (N = 271, 135 female), we investigated if reducing the duration of the voice samples on a nine-voice parade would negatively affect identification performance using both conventional logistic and signal detection approaches. In Experiment 2 (N = 270, 136 female), we first explored if the same sample duration conditions used in Experiment 1 would lead to different outcomes if we reduced the parade size to include only six voices. Following this, we pooled the data from both experiments to investigate the influence of target-position effects. The results show that 15-s sample durations result in statistically equivalent voice identification performance to the longer 60-s sample durations, but that the 30-s sample duration suffers in terms of overall signal sensitivity. This pattern of results was replicated using both a nine- and a six-voice parade. Performance on target-absent parades were at chance levels in both parade sizes, and response criteria were mostly liberal. In addition, unwanted position effects were present. The results provide initial evidence that the sample duration used in a voice parade may be reduced, but we argue that the guidelines recommending a parade with nine voices should be maintained to provide additional protection for a potentially innocent suspect given the low target-absent accuracy.

Metamnemonic predictions of lineup identification

After a crime is committed, investigators may query witnesses about whether they believe they will be to identify the perpetrator. However, we know little about how such metacognitive judgments are related to performance on a subsequent lineup identification task. The extant research has found the strength of this relationship to be small or nonexistent, which conflicts with the large body of literature indicating a moderate relationship between predictions and performance on memory tasks. In Studies 1-3, we induce variation in encoding quality by having participants watch a mock crime video with either low, medium, or high exposure quality, and then assess their future lineup performance. Calibration analysis revealed that assessments of future lineup performance were predictive of identification accuracy. This relationship was driven primarily by poor performance following low assessments. Studies 4 and 5 showed that these predictions are not based on a witness's evaluation of their encoding experience, nor on a contemporaneous assessment of memory strength. These results reinforce the argument that variation in memory quality is needed to obtain reliable relationships between predictions and performance. An unexpected finding is that witnesses who made a prediction shortly after encoding evinced superior memory compared to those who made a prediction later.

Deepfakes and scientific knowledge dissemination

Science misinformation on topics ranging from climate change to vaccines have significant public policy repercussions. Artificial intelligence-based methods of altering videos and photos (deepfakes) lower the barriers to the mass creation and dissemination of realistic, manipulated digital content. The risk of exposure to deepfakes among education stakeholders has increased as learners and educators rely on videos to obtain and share information. We field the first study to understand the vulnerabilities of education stakeholders to science deepfakes and the characteristics that moderate vulnerability. We ground our study in climate change and survey individuals from five populations spanning students, educators, and the adult public. Our sample is nationally representative of three populations. We found that 27-50% of individuals cannot distinguish authentic videos from deepfakes. All populations exhibit vulnerability to deepfakes which increases with age and trust in information sources but has a mixed relationship with political orientation. Adults and educators exhibit greater vulnerability compared to students, indicating that those providing education are especially susceptible. Vulnerability increases with exposure to potential deepfakes, suggesting that deepfakes become more pernicious without interventions. Our results suggest that focusing on the social context in which deepfakes reside is one promising strategy for combatting deepfakes.

Perceptual comparisons modulate memory biases induced by new visual inputs

It is well-established that stimulus-specific information in visual working memory (VWM) can be systematically biased by new perceptual inputs. These memory biases are commonly attributed to interference that arises when perceptual inputs are physically similar to VWM contents. However, recent work has suggested that explicitly comparing the similarity between VWM contents and new perceptual inputs modulates the size of memory biases above and beyond stimulus-driven effects. Here, we sought to directly investigate this modulation hypothesis by comparing the size of memory biases following explicit comparisons to those induced when new perceptual inputs are ignored (Experiment 1) or maintained in VWM alongside target information (Experiment 2). We found that VWM reports showed larger attraction biases following explicit perceptual comparisons than when new perceptual inputs were ignored or maintained in VWM. An analysis of participants' perceptual comparisons revealed that memory biases were amplified after perceptual inputs were endorsed as similar-but not dissimilar-to one's VWM representation. These patterns were found to persist even after accounting for variability in the physical similarity between the target and perceptual stimuli across trials, as well as the baseline memory precision between the distinct task demands. Together, these findings illustrate a causal role of perceptual comparisons in modulating naturally-occurring memory biases.

Evaluating earwitness identification procedures: adapting pre-parade instructions and parade procedure

Voice identification parades can be unreliable, as earwitness responses are error-prone. In this paper we tested performance across serial and sequential procedures, and varied pre-parade instructions, with the aim of reducing errors. The participants heard a target voice and later attempted to identify it from a parade. In Experiment 1 they were either warned that the target may or may not be present (standard warning) or encouraged to consider responding "not present" because of the associated risk of a wrongful conviction (strong warning). Strong warnings prompted a conservative criterion shift, with participants less likely to make a positive identification regardless of whether the target was present. In contrast to previous findings, we found no statistically reliable difference in accuracy between serial and sequential parades. Experiment 2 ruled out a potential confound in Experiment 1. Taken together, our results suggest that adapting pre-parade instructions provides a simple way of reducing the risk of false identifications.

Toward a more comprehensive modeling of sequential lineups

Sequential lineups are one of the most commonly used procedures in police departments across the USA. Although this procedure has been the target of much experimental research, there has been comparatively little work formally modeling it, especially the sequential nature of the judgments that it elicits. There are also important gaps in our understanding of how informative different types of judgments can be (binary responses vs. confidence ratings), and the severity of the inferential risks incurred when relying on different aggregate data structures. Couched in a signal detection theory (SDT) framework, the present work directly addresses these issues through a reanalysis of previously published data alongside model simulations. Model comparison results show that SDT modeling can provide elegant characterizations of extant data, despite some discrepancies across studies, which we attempt to address. Additional analyses compare the merits of sequential lineups (with and without a stopping rule) relative to showups and delineate the conditions in which distinct modeling approaches can be informative. Finally, we identify critical issues with the removal of the stopping rule from sequential lineups as an approach to capture within-subject differences and sidestep the risk of aggregation biases.

Simulated viewing distance impairs the confidence-accuracy relationship for long, but not moderate distances: support for a model incorporating the role of feature ambiguity

There is an increasing need in eyewitness identification research to identify factors that not only influence identification accuracy but may also impact the confidence–accuracy (CA) relationship. One such variable that has a notable impact on memory for faces is viewing distance, with faces encoded from a shorter distance remembered better than faces encoded at longer differences. In four pre-registered experiments, using both laboratory and online samples, we compared faces viewed at a simulated viewing distance at two different levels (medium and far) to faces that were viewed at a very near-simulated distance. Distance was simulated using a Gaussian blur function with higher levels of blur corresponding to greater simulated distance. We found that both medium and far simulated distances impaired memory performance overall relative to no simulated distance, with increased distance resulting in poorer memory. However, only far simulated distances impaired the CA relationship. In a fourth experiment, we found that a pre-test warning did not ameliorate this impairment of the CA relationship for faces viewed at a far simulated distance. These findings suggest that even high-confidence identifications made for faces viewed from long distances should be disregarded, and that estimator variables that impact memory may degrade the CA relationship when memory is reduced to critical levels.

Deepfake detection by human crowds, machines, and machine-informed crowds

The recent emergence of machine-manipulated media raises an important societal question: How can we know whether a video that we watch is real or fake? In two online studies with 15,016 participants, we present authentic videos and deepfakes and ask participants to identify which is which. We compare the performance of ordinary human observers with the leading computer vision deepfake detection model and find them similarly accurate, while making different kinds of mistakes. Together, participants with access to the model's prediction are more accurate than either alone, but inaccurate model predictions often decrease participants' accuracy. To probe the relative strengths and weaknesses of humans and machines as detectors of deepfakes, we examine human and machine performance across video-level features, and we evaluate the impact of preregistered randomized interventions on deepfake detection. We find that manipulations designed to disrupt visual processing of faces hinder human participants' performance while mostly not affecting the model's performance, suggesting a role for specialized cognitive capacities in explaining human deepfake detection performance.

A Signal Detection Approach to Understanding the Identification of Fake News

Researchers across many disciplines seek to understand how misinformation spreads with a view toward limiting its impact. One important question in this research is how people determine whether a given piece of news is real or fake. In the current article, we discuss the value of signal detection theory (SDT) in disentangling two distinct aspects in the identification of fake news: (a) ability to accurately distinguish between real news and fake news and (b) response biases to judge news as real or fake regardless of news veracity. The value of SDT for understanding the determinants of fake-news beliefs is illustrated with reanalyses of existing data sets, providing more nuanced insights into how partisan bias, cognitive reflection, and prior exposure influence the identification of fake news. Implications of SDT for the use of source-related information in the identification of fake news, interventions to improve people's skills in detecting fake news, and the debunking of misinformation are discussed.

Metamemory: Rats know the strength of their memory

Assessing the quality of one's own memories is a core cognitive function, but it has been unclear whether rodents possess this ability. Evidence that they do has come from research using a new behavioural paradigm in which rats make temporal bets guided by memory confidence.

Test a Witness's Memory of a Suspect Only Once

Eyewitness misidentifications are almost always made with high confidence in the courtroom. The courtroom is where eyewitnesses make their last identification of defendants suspected of (and charged with) committing a crime. But what did those same eyewitnesses do on the first identification test, conducted early in a police investigation? Despite testifying with high confidence in court, many eyewitnesses also testified that they had initially identified the suspect with low confidence or failed to identify the suspect at all. Presenting a lineup leaves the eyewitness with a memory trace of the faces in the lineup, including that of the suspect. As a result, the memory signal generated by the face of that suspect will be stronger on a later test involving the same witness, even if the suspect is innocent. In that sense, testing memory contaminates memory. These considerations underscore the importance of a newly proposed recommendation for conducting eyewitness identifications: Avoid repeated identification procedures with the same witness and suspect. This recommendation applies not only to additional tests conducted by police investigators but also to the final test conducted in the courtroom, in front of the judge and jury.

He did it! Or did I just see him on Twitter? Social media influence on eyewitness identification

Eyewitness identification is fallible, and suggestive post-event information is known to facilitate error; however, whether social media valence affects identification decisions is unknown. After viewing crime videos of various race perpetrators, participants saw post-event Twitter photos of the perpetrator or a foil that varied in valence. Participants attempted identification from a lineup including both individuals and rated the confidence and source (i.e., video, Twitter) of their selection. Results showed that Twitter photos of the perpetrator increased the likelihood of accurate identification and related confidence, whereas seeing the foil reduced the likelihood of a correct identification and related confidence. Remembering the perpetrator from the crime influenced correct identification, while remembering other incorrect sources (e.g., Twitter) only lead to misidentification. Twitter valence and perpetrator race did not impact outcomes. Results suggest that difficulty in identifying a perpetrator is underpinned by source monitoring confusion which is exacerbated by viewing social media that includes innocent suspects.

Eyewitness Identification Is a Visual Search Task

The simultaneous six-pack photo lineup is a standard eyewitness identification procedure, consisting of one police suspect plus five physically similar fillers. The photo lineup is either a target-present array (the suspect is guilty) or a target-absent array (the suspect is innocent). The eyewitness is asked to search the six photos in the array with respect to a target template stored in memory (namely, the memory of the perpetrator's face). If the witness determines that the perpetrator is in fact in the lineup (detection), then the next step is to specify the position of the perpetrator's face in the lineup (localization). The witness may also determine that the perpetrator is not present and reject the lineup. In other words, a police lineup is a detection-plus-localization visual search task. Signal detection concepts that have long guided thinking about visual search have recently had a significant impact on our understanding of police lineups. Expected final online publication date for the Annual Review of Vision Science, Volume 7 is September 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Eyewitness confidence may not be ready for the courts: a reply to Wixted et al

Wixted et al. (in press. Doing right by the eyewitness evidence: A response to Berkowitz et al. Memory) remind us that they are aware of some conditions in which confidence does not trump all but suggest that initial high-confidence errors should be rare. In this reply, we draw attention to new lab research that continues to cast doubt on the value of an initial eyewitness identification made with high confidence. Additional data from field studies of police lineups lead us to conclude that it is far too risky in real-world cases to assume that eyewitnesses who have high initial confidence are also highly accurate. As a final point, we dispute Wixted et al.'s interpretation of "initial low confidence" in the DNA exoneration cases.

Doing right by the eyewitness evidence: a response to Berkowitz et al

Berkowitz et al. (Berkowitz, S. R., Garrett, B. L., Fenn, K. M., & Loftus, E. F. (2020). Convicting with confidence? Why we should not over-rely on eyewitness confidence. Memory. https://doi.org/10.1080/09658211.2020.1849308) attribute to us the claim that "confidence trumps all", and the few out-of-context quotations they selected can certainly be used to create that false impression. However, it is easily disproved, and we do so here. The notion that "confidence trumps all" is the mistake that the jurors made in the DNA exoneration cases, not a position that we have ever advocated.

Discrete-state versus continuous models of the confidence-accuracy relationship in recognition memory

The relationship between confidence and accuracy in recognition memory is important in real-world settings (e.g., eyewitness identification) and is also important to understand at a theoretical level. Signal detection theory assumes that recognition decisions are based on continuous underlying memory signals and therefore inherently predicts that the relationship between confidence and accuracy will be continuous. Almost invariably, the empirical data accord with this prediction. Threshold models instead assume that recognition decisions are based on discrete-state memory signals. As a result, these models do not inherently predict a continuous confidence-accuracy relationship. However, they can accommodate that result by adding hypothetical mapping relationships between discrete states and the confidence rating scale. These mapping relationships are thought to arise from a variety of factors, including demand characteristics (e.g., instructing participants to distribute their responses across the confidence scale). However, until such possibilities are experimentally investigated in the context of a recognition memory experiment, there is no sense in which threshold models adequately explain confidence ratings at a theoretical level. Here, we tested whether demand characteristics might account for the mapping relationships required by threshold models and found that confidence was continuously related to accuracy (almost identically so) both in the presence of strong experimenter demands and in their absence. We conclude that confidence ratings likely reflect the strength of a continuous underlying memory signal, not an attempt to use the confidence scale in a manner that accords with the perceived expectations of the experimenter.

Line-Up Image Position in Simultaneous and Sequential Line-Ups: The Effects of Age and Viewing Distance on Selection Patterns

It is known that children and older adults produce more false alarms in target absent line-ups and that weaker facial encoding increases choosing bias. However, there has been no investigation of how age or facial encoding strength impacts line-up position selections in either sequential or simultaneous line-ups. In the present study, we presented participants with four live targets (one by one) while manipulating sequential and simultaneous line-ups between participants and target present and target absent line-ups within participants. In order to investigate facial encoding strength, we presented the targets at distances between 5 and 110 m. Our main hypotheses were that children due to deficits with inhibition would be more biased toward indiscriminate selections in the first position of sequential line-ups compared with subsequent line-up positions and that first position selections would increase for all age groups as facial encoding became weaker. In simultaneous line-ups, we expected to find a top row bias. In our sample (N = 1,588 participants; 6–77 years), we found that younger children (6–11 years) and the oldest adults (60–77 years) showed a first position bias in sequential line-ups, and as facial encoding became weaker, all age groups (6–11, 12–17, 18–44, 45–59, and 60–77 years) showed an increased tendency to make first position selections. We also found a weak top row preference in simultaneous line-ups, which was moderated by age and increased distance. The main finding is that the results suggest that younger children and the oldest adults had a tendency toward a first position selection bias in sequential line-ups. Based on the combined results, we recommend caution when using sequential line-ups with younger children or older adults.

sdtlu: An R package for the signal detection analysis of eyewitness lineup data

In a standard eyewitness lineup scenario, a witness observes a culprit commit a crime and is later asked to identify the culprit from a set of faces, the lineup. Signal detection theory (SDT), a powerful modeling framework for analyzing data, has recently become a common way to analyze lineup data. The goal of this paper is to introduce a new R package, sdtlu (Signal Detection Theory - LineUp), that streamlines and automates the SDT analysis of lineup data. sdtlu provides functions to process lineup data, determine the best-fitting SDT parameters, compute model-based performance measures such as area under the curve (AUC) and diagnosticity, use bootstrapping to determine uncertainty intervals around these parameters and measures, and compare parameters across two different data sets. The package incorporates closed-form solutions for both simultaneous and sequential lineups that allow for model-based analyses without Monte Carlo simulation. Show-ups are also supported. The package can estimate the base-rate of lineups that include a guilty suspect when the guilt or innocence of each suspect in the data set is unknown, as in "real-world" lineups. The package can also produce a full set of graphs, including data and model-based ROC curves and the underlying SDT model.

Estimating the proportion of guilty suspects and posterior probability of guilt in lineups using signal-detection models

BACKGROUND

The majority of eyewitness lineup studies are laboratory-based. How well the conclusions of these studies, including the relationship between confidence and accuracy, generalize to real-world police lineups is an open question. Signal detection theory (SDT) has emerged as a powerful framework for analyzing lineups that allows comparison of witnesses' memory accuracy under different types of identification procedures. Because the guilt or innocence of a real-world suspect is generally not known, however, it is further unknown precisely how the identification of a suspect should change our belief in their guilt. The probability of guilt after the suspect has been identified, the posterior probability of guilt (PPG), can only be meaningfully estimated if we know the proportion of lineups that include a guilty suspect, P(guilty). Recent work used SDT to estimate P(guilty) on a single empirical data set that shared an important property with real-world data; that is, no information about the guilt or innocence of the suspects was provided. Here we test the ability of the SDT model to recover P(guilty) on a wide range of pre-existing empirical data from more than 10,000 identification decisions. We then use simulations of the SDT model to determine the conditions under which the model succeeds and, where applicable, why it fails.

RESULTS

For both empirical and simulated studies, the model was able to accurately estimate P(guilty) when the lineups were fair (the guilty and innocent suspects did not stand out) and identifications of both suspects and fillers occurred with a range of confidence levels. Simulations showed that the model can accurately recover P(guilty) given data that matches the model assumptions. The model failed to accurately estimate P(guilty) under conditions that violated its assumptions; for example, when the effective size of the lineup was reduced, either because the fillers were selected to be poor matches to the suspect or because the innocent suspect was more familiar than the guilty suspect. The model also underestimated P(guilty) when a weapon was shown.

CONCLUSIONS

Depending on lineup quality, estimation of P(guilty) and, relatedly, PPG, from the SDT model can range from poor to excellent. These results highlight the need to carefully consider how the similarity relations between fillers and suspects influence identifications.

Regaining Consensus on the Reliability of Memory

In the last 20 years, the consensus about memory being essentially reliable has been neglected in favor of an emphasis on the malleability and unreliability of memory and on the public’s supposed unawareness of this. Three claims in particular have underpinned this popular perspective: that the confidence people have in their memory is weakly related to its accuracy, that false memories of fictitious childhood events can be easily implanted, and that the public wrongly sees memory as being like a video camera. New research has clarified that all three claims rest on shaky foundations, suggesting there is no reason to abandon the old consensus about memory being malleable but essentially reliable.

Exposure to air pollution during the first 1000 days of life and subsequent health service and medication usage in children

BACKGROUND

Evidence of health effects following early life exposure to short-to-medium duration of high pollution levels is extremely limited.

OBJECTIVES

We aimed to evaluate the associations between: 1. intrauterine exposure to fine particulate matter (PM_2.5) from coal mine fire emissions and the frequencies of general practitioner attendances and dispensations of prescribed asthma inhalers, steroid skin creams, and antibiotics during the first year of life; 2. infant exposure and those outcomes during the year following the fire.

METHODS

All participants were recruited from the Latrobe Valley of Victoria, Australia. Participants' 24-h average and hourly peak mine fire-specific PM_2.5 exposures from 09/02/2014 to 31/03/2014 were estimated using chemical transport modelling. Outcome data were obtained from the Australian Medicare Benefits Schedule and Pharmaceutical Benefits Scheme from each child's birth to 31/12/2016. We used negative binomial and logistic regression models to independently assess risks of the outcomes associated with every 10 and 100 μg m^-3 increase in average or peak PM_2.5 exposure, respectively, while adjusting for potential confounders.

RESULTS

We included 286 of 311 children whose parents consented to be linked, comprising 77 with no exposure, 88 with intrauterine exposure and 121 with exposure in infancy. 10- and 100- μg m^-3 increases in average and peak PM_2.5 exposure during infancy were associated with greater incidence of antibiotics being dispensed during the year following the fire: the adjusted incidence rate ratios were 1.24 (95% CI 1.02, 1.50, p = 0.036) and 1.14 (1.00, 1.31, p = 0.048) respectively. No other significant associations were observed.

CONCLUSION

Exposure to coal mine fire emissions during infancy was associated with increased dispensing of antibiotics. This could reflect increased childhood infections or increased prescriptions of antibiotics in the year following the fire.

The effect of educational priming on face recognition from a silver alert

In a between-subjects' experimental design, we manipulated whether participants viewed an educational video on the importance of Silver Alerts before viewing an older Caucasian female in a Silver Alert. We also examined associations of target recognition with individual difference variables, including gender, ethnicity, Attitudes Towards Older People (ATOP), empathy, conscientiousness, as well as contact and experience with older adults. The results showed an advantage of the priming condition compared to the no-priming condition for correctly identifying the missing woman. Additionally, females correctly identified the missing woman more than males, and Caucasian participants correctly identified the missing woman more than African American participants. Lastly, participants who reported more experience with older adults were more likely to recognize the missing woman. The results suggest that preceding Silver Alerts with information about their importance may increase their effectiveness. Further research is needed to investigate how individual difference variables relate to recognition of missing senior citizens.

Rethinking the Confident Eyewitness: A Reply to Wixted, Mickes, and Fisher

In the current issue, Wixted, Mickes, and Fisher make the claim that eyewitness memory is not inherently unreliable. They also describe specific conditions under which an eyewitness's confidence can be a reliable indicator of accuracy in the context of both recall and recognition. We argue, however, that calculating the probative value of eyewitness evidence is more complicated than the authors acknowledge. In this commentary, we raise several concerns about the collection and assessment of eyewitness confidence in the real world. We also discuss how frequently the conditions specified by Wixted et al. are met in real cases. The potential for memory contamination is commonplace and can likely be outside the control of investigators. Moreover, there is reason to doubt that legal decision makers are sensitive to the myriad ways that eyewitness memory can be influenced. Because of this, we think eyewitness-memory scientists would do well to further research the intricacies of eyewitness confidence in the real world.

Time to exonerate eyewitness memory

Understandably enough, most people are under the impression that eyewitness memory is unreliable. For example, research shows that memory is malleable, so much so that people can come to confidently remember traumatic events that never actually happened. In addition, eyewitness misidentifications made with high confidence in a court of law are known to have played a role in more than 70% of the 358 wrongful convictions that have been overturned based on DNA evidence since 1989. However, recent research demonstrates that eyewitness confidence is highly indicative of accuracy on an initial, uncontaminated, properly administered photo lineup. In other words, low confidence indicates that the test result (i.e., the ID) is inconclusive, whereas high confidence indicates that the test result is far more conclusive. Critically, for the DNA exonerees who were misidentified by an eyewitness in a court of law, in every case where their initial confidence can be determined, the eyewitness appropriately expressed low confidence. For any other kind of evidence (e.g., DNA, fingerprints), an inconclusive test result like that would have been the end of it. By contrast, in the case of eyewitness evidence, investigators repeatedly tested (and therefore unwittingly contaminated) memory until a seemingly conclusive high-confidence ID could be presented to the jury. Blaming eyewitness memory for the failure of the criminal justice system to accept the inconclusive nature of the initial (uncontaminated) eyewitness evidence seems misguided. In addition to exonerating the innocent defendants who were wrongfully convicted, the time has come to exonerate eyewitness memory too.

Models of lineup memory

Face recognition memory is often tested by the police using a photo lineup, which consists of one suspect, who is either innocent or guilty, and five or more physically similar fillers, all of whom are known to be innocent. For many years, lineups were investigated in lab studies without guidance from standard models of recognition memory. More recently, signal detection theory has been used to conceptualize lineup memory and to motivate receiver operating characteristic (ROC) analysis of lineup performance. Here, we describe three competing signal-detection models of lineup memory, derive their likelihood functions, and fit them to empirical ROC data. We also introduce the notion that memory signals generated by the faces in a lineup are likely to be correlated because, by design, those faces share features. The models we investigate differ in their predictions about the effect that correlated memory signals should have on the ability to discriminate innocent from guilty suspects. A popular compound signal detection model known as the Integration model predicts that correlated memory signals should impair discriminability. Empirically, this model performed so poorly that, going forward, it should probably be abandoned. The best-fitting model incorporates a principle known as "ensemble coding," which predicts that correlated memory signals should enhance discriminability. The ensemble model aligns with a previously proposed theory of eyewitness identification according to which the simultaneous presentation of faces in a lineup enhances discriminability compared to when faces are presented in isolation because it permits eyewitnesses to detect and discount non-diagnostic facial features.

Rethinking the Reliability of Eyewitness Memory

Although certain pockets within the broad field of academic psychology have come to appreciate that eyewitness memory is more reliable than was once believed, the prevailing view, by far, is that eyewitness memory is unreliable—a blanket assessment that increasingly pervades the legal system. On the surface, this verdict seems unavoidable: Research convincingly shows that memory is malleable, and eyewitness misidentifications are known to have played a role in most of the DNA exonerations of the innocent. However, we argue here that, like DNA evidence and other kinds of scientifically validated forensic evidence, eyewitness memory is reliable if it is not contaminated and if proper testing procedures are used. This conclusion applies to eyewitness memory broadly conceived, whether the test involves recognition (from a police lineup) or recall (during a police interview). From this perspective, eyewitness memory has been wrongfully convicted of mistakes that are better construed as having been committed by other actors in the legal system, not by the eyewitnesses themselves. Eyewitnesses typically provide reliable evidence on an initial, uncontaminated memory test, and this is true even for most of the wrongful convictions that were later reversed by DNA evidence.

Theoretical vs. empirical discriminability: the application of ROC methods to eyewitness identification

Receiver operating characteristic (ROC) analysis was introduced to the field of eyewitness identification 5 years ago. Since that time, it has been both influential and controversial, and the debate has raised an issue about measuring discriminability that is rarely considered. The issue concerns the distinction between empirical discriminability (measured by area under the ROC curve) vs. underlying/theoretical discriminability (measured by d’ or variants of it). Under most circumstances, the two measures will agree about a difference between two conditions in terms of discriminability. However, it is possible for them to disagree, and that fact can lead to confusion about which condition actually yields higher discriminability. For example, if the two conditions have implications for real-world practice (e.g., a comparison of competing lineup formats), should a policymaker rely on the area-under-the-curve measure or the theory-based measure? Here, we illustrate the fact that a given empirical ROC yields as many underlying discriminability measures as there are theories that one is willing to take seriously. No matter which theory is correct, for practical purposes, the singular area-under-the-curve measure best identifies the diagnostically superior procedure. For that reason, area under the ROC curve informs policy in a way that underlying theoretical discriminability never can. At the same time, theoretical measures of discriminability are equally important, but for a different reason. Without an adequate theoretical understanding of the relevant task, the field will be in no position to enhance empirical discriminability.

Decision time and confidence predict choosers' identification performance in photographic showups

In vast contrast to the multitude of lineup studies that report on the link between decision time, confidence, and identification accuracy, only a few studies looked at these associations for showups, with results varying widely across studies. We therefore set out to test the individual and combined value of decision time and post-decision confidence for diagnosing the accuracy of positive showup decisions using confidence-accuracy characteristic curves and Bayesian analyses. Three-hundred-eighty-four participants viewed a stimulus event and were subsequently presented with two showups which could be target-present or target-absent. As expected, we found a negative decision time-accuracy and a positive post-decision confidence-accuracy correlation for showup selections. Confidence-accuracy characteristic curves demonstrated the expected additive effect of combining both postdictors. Likewise, Bayesian analyses, taking into account all possible target-presence base rate values showed that fast and confident identification decisions were more diagnostic than slow or less confident decisions, with the combination of both being most diagnostic for postdicting accurate and inaccurate decisions. The postdictive value of decision time and post-decision confidence was higher when the prior probability that the suspect is the perpetrator was high compared to when the prior probability that the suspect is the perpetrator was low. The frequent use of showups in practice emphasizes the importance of these findings for court proceedings. Overall, these findings support the idea that courts should have most trust in showup identifications that were made fast and confidently, and least in showup identifications that were made slowly and with low confidence.

Evidence for a confidence–accuracy relationship in memory for same- and cross-race faces

Discrimination accuracy is usually higher for same- than for cross-race faces, a phenomenon known as the cross-race effect (CRE). According to prior research, the CRE occurs because memories for same- and cross-race faces rely on qualitatively different processes. However, according to a continuous dual-process model of recognition memory, memories that rely on qualitatively different processes do not differ in recognition accuracy when confidence is equated. Thus, although there are differences in overall same- and cross-race discrimination accuracy, confidence-specific accuracy (i.e., recognition accuracy at a particular level of confidence) may not differ. We analysed datasets from four recognition memory studies on same- and cross-race faces to test this hypothesis. Confidence ratings reliably predicted recognition accuracy when performance was above chance levels (Experiments 1, 2, and 3) but not when performance was at chance levels (Experiment 4). Furthermore, at each level of confidence, confidence-specific accuracy for same- and cross-race faces did not significantly differ when overall performance was above chance levels (Experiments 1, 2, and 3) but significantly differed when overall performance was at chance levels (Experiment 4). Thus, under certain conditions, high-confidence same-race and cross-race identifications may be equally reliable.

Why eyewitnesses fail

Eyewitness identifications play an important role in the investigation and prosecution of crimes, but it is well known that eyewitnesses make mistakes, often with serious consequences. In light of these concerns, the National Academy of Sciences recently convened a panel of experts to undertake a comprehensive study of current practice and use of eyewitness testimony, with an eye toward understanding why identification errors occur and what can be done to prevent them. The work of this committee led to key findings and recommendations for reform, detailed in a consensus report entitled Identifying the Culprit: Assessing Eyewitness Identification In this review, I focus on the scientific issues that emerged from this study, along with brief discussions of how these issues led to specific recommendations for additional research, best practices for law enforcement, and use of eyewitness evidence by the courts.

Is the bias for function-based explanations culturally universal? Children from China endorse teleological explanations of natural phenomena

Young children in Western cultures tend to endorse teleological (function-based) explanations broadly across many domains, even when scientifically unwarranted. For instance, in contrast to Western adults, they explicitly endorse the idea that mountains were created for climbing, just like hats were created for warmth. Is this bias a product of culture or a product of universal aspects of human cognition? In two studies, we explored whether adults and children in Mainland China, a highly secular, non-Western culture, show a bias for teleological explanations. When explaining both object properties (Experiment 1) and origins (Experiment 2), we found evidence that they do. Whereas Chinese adults restricted teleological explanations to scientifically warranted cases, Chinese children endorsed them more broadly, extending them across different kinds of natural phenomena. This bias decreased with rising grade level across first, second, and fourth grades. Overall, these data provide evidence that children's bias for teleological explanations is not solely a product of Western Abrahamic cultures. Instead, it extends to other cultures, including the East Asian secular culture of modern-day China. This suggests that the bias for function-based explanations may be driven by universal aspects of human cognition.