The low prevalence effect in fingerprint comparison amongst forensic science trainees and novices

The low prevalence effect is a phenomenon whereby target prevalence affects performance in visual search (e.g., baggage screening) and comparison (e.g., fingerprint examination) tasks, such that people more often fail to detect infrequent target stimuli. For example, when exposed to higher base-rates of ‘matching’ (i.e., from the same person) than ‘non-matching’ (i.e., from different people) fingerprint pairs, people more often misjudge ‘non-matching’ pairs as ‘matches’–an error that can falsely implicate an innocent person for a crime they did not commit. In this paper, we investigated whether forensic science training may mitigate the low prevalence effect in fingerprint comparison. Forensic science trainees (n = 111) and untrained novices (n = 114) judged 100 fingerprint pairs as ‘matches’ or ‘non-matches’ where the matching pair occurrence was either high (90%) or equal (50%). Some participants were also asked to use a novel feature-comparison strategy as a potential attenuation technique for the low prevalence effect. Regardless of strategy, both trainees and novices were susceptible to the effect, such that they more often misjudged non-matching pairs as matches when non-matches were rare. These results support the robust nature of the low prevalence effect in visual comparison and have important applied implications for forensic decision-making in the criminal justice system

Statistical feature training improves fingerprint-matching accuracy in novices and professional fingerprint examiners

AbstractForensic science practitioners compare visual evidence samples (e.g. fingerprints) and decide if they originate from the same person or different people (i.e. fingerprint ‘matching’). These tasks are perceptually and cognitively complex—even practising professionals can make errors—and what limited research exists suggests that existing professional training is ineffective. This paper presents three experiments that demonstrate the benefit of perceptual training derived from mathematical theories that suggest statistically rare features have diagnostic utility in visual comparison tasks. Across three studies (N = 551), we demonstrate that a brief module training participants to focus on statistically rare fingerprint features improves fingerprint-matching performance in both novices and experienced fingerprint examiners. These results have applied importance for improving the professional performance of practising fingerprint examiners, and even other domains where this technique may also be helpful (e.g. radiology or banknote security).</jats:p

Public attitudes towards the use of automatic facial recognition technology in criminal justice systems around the world

Automatic facial recognition technology (AFR) is increasingly used in criminal justice systems around the world, yet to date there has not been an international survey of public attitudes toward its use. In Study 1, we ran focus groups in the UK, Australia and China (countries at different stages of adopting AFR) and in Study 2 we collected data from over 3,000 participants in the UK, Australia and the USA using a questionnaire investigating attitudes towards AFR use in criminal justice systems. Our results showed that although overall participants were aligned in their attitudes and reasoning behind them, there were some key differences across countries. People in the USA were more accepting of tracking citizens, more accepting of private companies’ use of AFR, and less trusting of the police using AFR than people in the UK and Australia. Our results showed that support for the use of AFR depends greatly on what the technology is used for and who it is used by. We recommend vendors and users do more to explain AFR use, including details around accuracy and data protection. We also recommend that governments should set legal boundaries around the use of AFR in investigative and criminal justice settings

Forensic Feature-Comparison Expertise: Statistical Learning Facilitates Visual Comparison Performance

Forensic feature-comparison examiners in select disciplines are more accurate than novices when comparing visual evidence samples. This paper examines a key cognitive mechanism that may contribute to this superior visual comparison performance: the ability to learn how often stimuli occur in the environment (distributional statistical learning). We examined the relation-ship between distributional learning and visual comparison performance, and the impact of training about the diagnosticity of distributional information in visual comparison tasks. We compared performance between novices given no training (uninformed novices; n = 32), accu-rate training (informed novices; n = 32) or inaccurate training (misinformed novices; n = 32) in Experiment 1; and between forensic examiners (n = 26), informed novices (n = 29) and unin-formed novices (n = 27) in Experiment 2. Across both experiments, forensic examiners and nov-ices performed significantly above chance in a visual comparison task where distributional learning was required for high performance. However, informed novices outperformed all par-ticipants and only their visual comparison performance was significantly associated with their distributional learning. It is likely that forensic examiners’ expertise is domain-specific and doesn’t generalise to novel visual comparison tasks. Nevertheless, diagnosticity training could be critical to the relationship between distributional learning and visual comparison performance

Improving expert evidence: the role of open science and transparency

Both science and expert evidence law are undergoing significant changes. In this article, the authors compare these two movements – the open science movement and the evidence-based evidence movement. The open science movement encompasses the recent discovery of many irreproducible findings in science and the subsequent move towards more transparent methods. The evidence-based evidence movement is the discovery that many forms of expert evidence are unreliable, and that they have contributed to wrongful convictions. The authors identify similarities between these movements, which suggest how courts and legal actors may learn from the open science movement to produce more accurate results. Expert witnesses should comport themselves as rigorous open scientists to produce evidence that is more susceptible to evaluation. Parties should be subjected to more specific and rigorous disclosure requirements because research has shown that even leading scientists find it easy to discount and suppress findings that do not support their hypotheses. And trial judges, as gatekeepers, should not defer to the generally accepted practices that have proven insufficient in the mainstream sciences