Since the advent of DNA analysis, organizations such as the Innocence Project have been able to exonerate people who were wrongfully convicted of crimes, often due to erroneous forensic evidence analysis. In many cases, analytical techniques, such as fingerprint analysis, toolmark analysis, or hair comparisons have been cited as nearly infallible sources of evidentiary fact. However, these methods rely on subjective interpretation by a forensic examiner and lack stringent, quantitative methods for ensuring reliability and accuracy. For most of these methods, the examiner is supplied only with the unknown sample from the crime scene, and a known sample from a suspect. This, combined with the influence of psychological factors such as confirmation bias, has resulted in the need for a reliable mechanism of ensuring the efficacy of a particular type of analysis as well as the objectivity, and competence of the analyst. One proposed method to resolve these issues is the use of a filler-control method, in which analysts are given an “evidence line-up” containing at least three samples: the unknown sample from the crime scene, a sample from the suspect, and at least one filler sample from an individual who is not involved in the investigation. This method provides a reliable method for estimating error rates for an analyst and can provide the analyst with direct feedback about their performance to accurately gauge their competence. This method also helps to prevent the introduction of confirmation bias, as the source of the samples is unknown to the analyst. The goal of the current research is to test the capacity of a filler-control method to lead to better confidence-calibration of examiners’ match judgements when compared to the conventional method. The hypothesis of this experiment is that participants using the filler control method will have improved performance and increased confidence calibration due to receiving feedback over the course of the trials when compared to participants using the traditional method.

In the legal system, the prediction of a person’s risk of committing a crime has mostly been based on expert judgment. However, newer techniques that employ machine learning (ML)—a type of artificial intelligence—are being implemented throughout the justice system. Yet, there is a lack of research on how the public perceives and uses machine learning risk assessments in legal settings. In two mock-trial vignette studies, the perception of ML-based risk assessments versus more traditional methods was assessed. Study 1 was a 2 (severity of crime: low, high) x 2 (risk assessment type: expert, machine learning) x 2 (risk outcome: low, high) between-subjects design. Participants expressed ethical concerns and discouraged the use of machine learning risk assessments in sentencing decisions, but punishment recommendations were not affected. Study 2 was a within-subjects design where participants were randomly assigned read through one of three crime scenarios (violent, white-collar, sex offense) and one of three risk assessment techniques (expert, checklist, machine learning). Consistent with Study 1, participants had ethical concerns and disagreed with the use of machine learning risk assessments in bail decisions, yet their own decisions and recommendations did not reflect these concerns. Overall, laypeople express skepticism toward these new methods, but do not appear to differentially rely on ML-based versus traditional risk assessments in their own judgments.

The purpose of this research was to investigate the effect of the type of crime (namely, its perceived immorality) a juvenile is suspected of on how juvenile suspects are perceived (in terms of moral character, immaturity, and suggestibility) and, in turn, interrogated. I expected act-person dissociation to influence that effect. To that end, perceptions of crime (i.e., immorality, seriousness) were also investigated. The study was first conducted with law enforcement officers (n = 55), then replicated with laypeople (n = 171). Participants were randomly assigned to one of three crime conditions: robbery, sexual assault, and murder. In each condition, participants read a probable cause statement involving a 15-year-old suspect. There were several key findings: (1) Murder was the most serious crime, whereas robbery and sexual assault were more immoral. (2) Act-person dissociation did not occur. (3) Participants were more likely to endorse the use of psychologically coercive tactics on the juvenile suspected of sexual assault than the juvenile suspected of murder. (4) The more favorably participants perceived a juvenile’s moral character, the less likely they were to endorse the use of psychologically coercive interrogation tactics. (4) Participants who more strongly agreed that juveniles are more immature and suggestible than adults were less likely to endorse the use of psychologically coercive tactics, more likely to endorse the use of tactics that encourage compliance with interrogators, and more likely to adhere to the PEACE model of juvenile interrogations. The implications and limitations of these findings are discussed, along with potential directions for future research.