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Automated face recognition assists with low-prevalence face identity mismatches but can bias users

Bibliographic Data

ID5267010
AuthorsMelina Mueller (Psychology, Faculty of Natural Sciences University of Stirling Stirling UK), Peter Hancock (0000-0003-0229-5669, University of Stirling), Peter J B Hancock (Psychology, Faculty of Natural Sciences University of Stirling Stirling UK), Emily K Cunningham (Psychology, Faculty of Natural Sciences University of Stirling Stirling UK), E Cunningham (University of Stirling), Roger J Watts, R J Watt (0000-0001-8660-1875, University of Stirling), Daniel Carragher (School of Psychology, Faculty of Health and Medical Sciences University of Adelaide Adelaide South Australia Australia), Daniel J Carragher (0000-0003-2265-4737, The University of Adelaide), Anna K Bobak (0000-0002-4100-5807, Psychology, Faculty of Natural Sciences University of Stirling Stirling UK, corresponding author)
Year2024
Volume117
Issue2
Pages567-584
Publication date2024-11-15
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueBritish Journal of Psychology (JOURNAL)
Journal identifiersISSN: 0007-1269 • E-ISSN: 2044-8295
PublisherWiley (PUBLISHER • GB)
DOI10.1111/bjop.12745
PMID39545786
OpenAlexW4404394760
LanguageEN
Citations received3
References cited55

We present three experiments to study the effects of giving information about the decision of an automated face recognition (AFR) system to participants attempting to decide whether two face images show the same person. We make three contributions designed to make our results applicable to real-word use: participants are given the true response of a highly accurate AFR system; the face set reflects the mixed ethnicity of the city of London from where participants are drawn; and there are only 10% of mismatches. Participants were equally accurate when given the similarity score of the AFR system or just the binary decision but shifted their bias towards match and were over-confident on difficult pairs when given only binary information. No participants achieved the 100% accuracy of the AFR system, and they had only weak insight about their own performance

Cognitive psychology · Face (sociological concept) · Facial recognition system · Identity (music) · Image (mathematics) · Linguistics · Pattern recognition (psychology) · Set (abstract data type) · Similarity (geometry) · Artificial Intelligence · Computer Science · Evolutionary Psychology and Human Behavior · Face Recognition and Perception · Names, Identity, and Discrimination Research · Psychology · Social Psychology

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Unique citing works3
Citations per year3
Citation span2026 - 2026 (1)
Citation velocitycurrent
Highly citedNo
Citation typesNeutral: 3

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