Unfamiliar face matching with photographs of infants and children

Face matching and self-insight: A Registered Report investigating individual differences in metacognitive sensitivity, efficiency, and bias

Deciding whether two face photographs depict the same person or not can be a challenging task, and there are substantial individual differences in face matching ability. Far less is known about differences in metacognitive ability; that is, how well people can estimate the quality of their own face matching judgements. The purpose of this Registered Report was to determine the relationship between first-order performance in a face matching task, and three metacognitive measures: metacognitive sensitivity (the information exploited by metacognition), metacognitive efficiency (the quality of metacognitive processing itself), and metacognitive bias (the overall tendency towards high or low confidence). Participants completed a 200-trial unfamiliar face matching task, providing a second-order (metacognitive) confidence rating after each first-order (cognitive) response. Cognitive performance and metacognitive sensitivity showed a substantial positive association (rs = .60), suggesting that they were based on overlapping information, with poorer performers having lower quality information available. Once these differences in the information available to metacognition were accounted for, the quality of metacognitive processing itself (metacognitive efficiency) did not vary systematically with cognitive performance (rs = .00). Moreover, poor performers were not less or more confident overall than good performers, as cognitive performance and metacognitive bias did not correlate significantly (rs = .11). These findings allow us to move beyond consideration of group-level insight and inform regarding individual differences in cognitive and metacognitive abilities.

Diagnostic Features for Human Categorisation of Adult and Child Faces

Knowing how humans differentiate children from adults has useful implications in many areas of both forensic and cognitive psychology. Yet, how we extract age from faces has been surprisingly underexplored in both disciplines. Here, we used a novel data-driven experimental technique to objectively measure the facial features human observers use to categorise child and adult faces. Relying on more than 35,000 trials, we used a reverse correlation technique that enabled us to reveal how specific features which are known to be important in face-perception - position, spatial-frequency (SF), and orientation - are associated with accurate child and adult discrimination. This showed that human observers relied on evidence in the nasal bone and eyebrow area for accurate adult categorisation, while they relied on the eye and jawline area to accurately categorise child faces. For orientation structure, only facial information of vertical orientation was linked to face-adult categorisation, while features of horizontal and, to a lesser extent oblique orientations, were more diagnostic of a child face. Finally, we found that SF diagnosticity showed a U-shaped pattern for face-age categorisation, with information in low and high SFs being diagnostic of child faces, and mid SFs being diagnostic of adult faces. Through this first characterisation of the facial features of face-age categorisation, we show that important information found in psychophysical studies of face-perception in general (i.e., the eye area, horizontals, and mid-level SFs) is crucial to the practical context of face-age categorisation, and present data-driven procedures through which face-age classification training could be implemented for real-world challenges.

Enhanced Matching of Children's Faces in "Super-Recognisers" But Not High-Contact Controls

Face matching is notoriously error-prone, and some work suggests additional difficulty when matching the faces of children. It is possible that individuals with natural proficiencies in adult face matching ("super-recognisers" [SRs]) will also excel at the matching of children's faces, although other work implicates facilitations in typical perceivers who have high levels of contact with young children (e.g., nursery teachers). This study compared the performance of both of these groups on adult and child face matching to a group of low-contact controls. High- and low-contact control groups performed at a remarkably similar level in both tasks, whereas facilitations for adult and child face matching were observed in some (but not all) SRs. As a group, the SRs performed better in the adult compared with the child task, demonstrating an extended own-age bias compared with controls. These findings suggest that additional exposure to children's faces does not assist the performance in a face matching task, and the mechanisms underpinning superior recognition of adult faces can also facilitate the child face recognition. Real-world security organisations should therefore seek individuals with general facilitations in face matching for both adult and child face matching tasks.

The performance of practitioners conducting facial comparisons on images of children across age

Determining the identity of children is critical to aid in the fight against child exploitation, as well as for passport control and visa issuance purposes. Facial image comparison is one method that may be used to determine identity. Due to the substantial amount of facial growth that occurs in childhood, it is critical to understand facial image comparison performance across both chronological age (the age of the child), and age variation (the age difference between images). In this study we examined the performance of 120 facial comparison practitioners from a government agency on a dataset of 23,760 image pairs selected from the agency's own database of controlled, operational images. Each chronological age in childhood (0-17 years) and age variations ranging from 0-10 years were examined. Practitioner performance was found to vary considerably across childhood, and depended on whether the pairs were mated (same child) or non-mated (different child). Overall, practitioners were more accurate and confident with image pairs containing older children, and also more accurate and confident with smaller age variations. Chronological age impacted on accuracy with mated pairs, but age variation did not. In contrast, both age and age variation impacted on accuracy with non-mated pairs. These differences in performance show that changes in the face throughout childhood have a significant impact on practitioner performance. We propose that improvements in accuracy may be achievable with a better understanding of which facial features are most appropriate to compare across childhood, and adjusting training and development programs accordingly.

Unfamiliar Face Matching With Driving Licence and Passport Photographs

Matching two different images of an unfamiliar face is difficult, although we rely on this process every day when proving our identity. Although previous work with laboratory photosets has shown that performance is error-prone, few studies have focussed on how accurately people carry out this matching task using photographs taken from official forms of identification. In Experiment 1, participants matched high-resolution, colour face photos with current UK driving licence photos of the same group of people in a sorting task. Averaging 19 mistaken pairings out of 30, our results showed that this task was both difficult and error-prone. In Experiment 2, high-resolution photographs were paired with either driving licence or passport photographs in a typical pairwise matching paradigm. We found no difference in performance levels for the two types of ID image, with both producing unacceptable levels of accuracy (around 75%-79% correct). The current work benefits from increased ecological validity and provides a clear demonstration that these forms of official identification are ineffective and alternatives should be considered.