Facial image comparison practitioners compare images of unfamiliar faces and decide whether or not they show the same person. Given the importance of these decisions for national security and criminal investigations, practitioners attend training courses to improve their face identification ability. However, these courses have not been empirically validated so it is unknown if they improve accuracy. Here, we review the content of eleven professional training courses offered to staff at national security, police, intelligence, passport issuance, immigration and border control agencies around the world. All reviewed courses include basic training in facial anatomy and prescribe facial feature (or ‘morphological’) comparison. Next, we evaluate the effectiveness of four representative courses by comparing face identification accuracy before and after training in novices ( n = 152) and practitioners ( n = 236). We find very strong evidence that short (1-hour and half-day) professional training courses do not improve identification accuracy, despite 93% of trainees believing their performance had improved. We find some evidence of improvement in a 3-day training course designed to introduce trainees to the unique feature-by-feature comparison strategy used by facial examiners in forensic settings. However, observed improvements are small, inconsistent across tests, and training did not produce the qualitative changes associated with examiners’ expertise. Future research should test the benefits of longer examination-focussed training courses and incorporate longitudinal approaches to track improvements caused by mentoring and deliberate practice. In the absence of evidence that training is effective, we advise agencies to explore alternative evidence-based strategies for improving the accuracy of face identification decisions.
Facial recognition errors jeopardize national security, criminal justice, public safety and civil rights. Here, we compare the most accurate humans and facial recognition technology in a detailed lab-based evaluation and international proficiency test for forensic scientists involving 27 forensic departments from 14 countries. We find striking cognitive and perceptual diversity between naturally skilled super-recognizers, trained forensic examiners and deep neural networks, despite them achieving equivalent accuracy. Clear differences emerged in super-recognizers’ and forensic examiners’ perceptual processing, errors, and response patterns: super-recognizers were fast, biased to respond ‘same person’ and misidentified people with extreme confidence, whereas forensic examiners were slow, unbiased and strategically avoided misidentification errors. Further, these human experts and algorithms disagreed on the similarity of faces, pointing to differences in their face representations. Our findings reveal there are multiple types of facial recognition expertise, some of which are better suited to particular real-world facial recognition roles than others.
Forensic face matching evidence has been presented in UK courts for over 30 years to provide crucial identification evidence in criminal investigations. To be admissible as evidence in UK courts, this evidence must be conducted by a suitably qualified expert using scientifically validated procedures. Contrary to this notion, however, the field has been largely self-regulated, with little empirical investigation into the validity of face matching procedures, with extensive criticism of forensic face matching procedures in the scientific literature. Practitioner working groups are now addressing these criticisms and standardising working practices, but further effort is required to ensure that the procedures used for forensic face matching are reliable and the limitations known. This chapter will provide a critical analysis of the forensic face matching procedures used in the UK and internationally by forensic face examiners, alongside studies and case examples that have challenged and tested the reliability and accuracy of these procedures.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.