Previous work looking at individual differences in face identity processing (FIP) has found that most commonly used lab-based performance assessments are unfortunately not sufficiently sensitive on their own for measuring performance in both the upper and lower tails of the general population simultaneously. So more recently, researchers have begun incorporating multiple testing procedures into their assessments. Still, though, the growing consensus seems to be that at the individual level, there is quite a bit of variability between test scores. The overall consequence of this is that extreme scores will still occur simply by chance in large enough samples. To mitigate this issue, our recent work has developed measures of intra-individual FIP consistency to refine selection of those with superior abilities (i.e. from the upper tail). For starters, we assessed consistency of face matching and recognition in neurotypical controls, and compared them to a sample of SRs. In terms of face matching, we demonstrated psychophysically that SRs show significantly greater consistency than controls in exploiting spatial frequency information than controls. Meanwhile, we showed that SRs’ recognition of faces is highly related to memorability for identities, yet effectively unrelated among controls. So overall, at the high end of the FIP spectrum, consistency can be a useful tool for revealing both qualitative and quantitative individual differences. Finally, in conjunction with collaborators from the Rheinland-Pfalz Police, we developed a pair of bespoke work samples to get bias-free measures of intraindividual consistency in current law enforcement personnel. Officers with higher composite scores on a set of 3 challenging FIP tests tended to show higher consistency, and vice versa. Overall, this suggests that not only is consistency a reasonably good marker of superior FIP abilities, but could present important practical benefits for personnel selection in many other domains of expertise.

Face matching tests have traditionally been developed to assess human face perception in the neurotypical range, but methods that underlie their development often make it difficult for these measures to be applied in atypical populations (developmental prosopagnosics, super recognizers) due to unadjusted difficulty. We have recently presented the development of the Oxford Face Matching Test, a measure that bases individual item-difficulty on algorithmically derived similarity of presented stimuli. The measure seems useful as it can be given online or in-laboratory, has good discriminability and high test-retest reliability in the neurotypical groups. In addition, it has good validity in separating atypical groups at either of the spectrum ends. In this talk, I examine the stability of the OFMT and other traditionally used measures in atypical groups. On top of the theoretical significance of determining whether reliability of tests is equivalent in atypical population, this is an important question because of the practical concerns of retesting the same participants across different lab groups. Theoretical and practical implications for further test development and data sharing are discussed.