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Selecting police super-recognisers

People vary in their ability to recognise faces. These individual differences are consistent over time, heritable and associated with brain anatomy. This implies that face identity processing can be improved in applied settings by selecting high performers–‘super-recognisers’ (SRs)–but these selecti...

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Detalles Bibliográficos
Autores principales: Dunn, James D., Towler, Alice, Kemp, Richard I., White, David
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10191310/
https://www.ncbi.nlm.nih.gov/pubmed/37195905
http://dx.doi.org/10.1371/journal.pone.0283682
Descripción
Sumario:People vary in their ability to recognise faces. These individual differences are consistent over time, heritable and associated with brain anatomy. This implies that face identity processing can be improved in applied settings by selecting high performers–‘super-recognisers’ (SRs)–but these selection processes are rarely available for scientific scrutiny. Here we report an ‘end-to-end’ selection process used to establish an SR ‘unit’ in a large police force. Australian police officers (n = 1600) completed 3 standardised face identification tests and we recruited 38 SRs from this cohort to complete 10 follow-up tests. As a group, SRs were 20% better than controls in lab-based tests of face memory and matching, and equalled or surpassed accuracy of forensic specialists that currently perform face identification tasks for police. Individually, SR accuracy was variable but this problem was mitigated by adopting strict selection criteria. SRs’ superior abilities transferred only partially to body identity decisions where the face was not visible, and they were no better than controls at deciding which visual scene that faces had initially been encountered in. Notwithstanding these important qualifications, we conclude that super-recognisers are an effective solution to improving face identity processing in applied settings.