Super-recognizers
From the lab to the world and back again
Bibliographic Data
| ID | 5267693 |
|---|---|
| Authors | Meike Ramon (0000-0001-5753-5493, Applied Face Cognition Lab University of Fribourg Switzerland), Anna K Bobak (0000-0002-4100-5807, Psychology Faculty of Natural Sciences University of Stirling UK, corresponding author), David White (0000-0002-6366-2699, UNSW Sydney New South Wales Australia) |
| Year | 2019 |
| Volume | 110 |
| Issue | 3 |
| Pages | 461-479 |
| Publication date | 2019-08-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | British Journal of Psychology (JOURNAL) |
| Journal identifiers | ISSN: 0007-1269 • E-ISSN: 2044-8295 |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1111/bjop.12368 |
| PMID | 30893478 |
| OpenAlex | W2924010481 |
| Language | EN |
| Citations received | 10 |
| References cited | 66 |
The recent discovery of individuals with superior face processing ability has sparked considerable interest amongst cognitive scientists and practitioners alike. These 'Super-recognizers' (SRs) offer clues to the underlying processes responsible for high levels of face processing ability. It has been claimed that they can help make societies safer and fairer by improving accuracy of facial identity processing in real-world tasks, for example when identifying suspects from Closed Circuit Television or performing security-critical identity verification tasks. Here, we argue that the current understanding of superior face processing does not justify widespread interest in SR deployment: There are relatively few studies of SRs and no evidence that high accuracy on laboratory-based tests translates directly to operational deployment. Using simulated data, we show that modest accuracy benefits can be expected from deploying SRs on the basis of ideally calibrated laboratory tests. Attaining more substantial benefits will require greater levels of communication and collaboration between psychologists and practitioners. We propose that translational and reverse-translational approaches to knowledge development are critical to advance current understanding and to enable optimal deployment of SRs in society. Finally, we outline knowledge gaps that this approach can help address
Cognition · Computer security · Data science · Face (sociological concept) · Identity (music) · SAFER · Sociology · Software deployment · Software engineering · Computer Science · Face recognition and analysis · Face Recognition and Perception · Neuroscience · Psychology · Visual Attention and Saliency Detection
The role of attentional interventions and individual differences in the detection of low prevalence fake IDs
Match me if you can
Stable individual differences in unfamiliar face identification
Robust Medusa effect across facial manipulations
We need to talk about super‐recognizers Invited commentary on
A task‐ and role‐based perspective on super‐recognizers
Towards a ‘manifesto’ for super‐recognizer research
Breaking face processing tasks apart to improve their predictive value in the real world
Automated face recognition assists with low-prevalence face identity mismatches but can bias users
Redefining super recognition in the real world
Configurational Information in Face Perception
Parts and Wholes in Face Recognition
Forest before trees
Variability in photos of the same face
Looking at upside-down faces.
Development and validation of measures of social phobia scrutiny fear and social interaction anxiety11Editor’s note
The “Reading the Mind in the Eyes” Test Revised Version
Individual differences in perceiving and recognizing faces—One element of social cognition
Wisdom of the social versus non-social crowd in face identification
Unfamiliar face matching
| Unique citing works | 10 |
|---|---|
| Citations per year | 1,43 |
| Citation span | 2019 - 2026 (8) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 10 |