Face recognition ability does not predict person identification performance: using individual data in the interpretation of group results

Eilidh Noyes,Matthew Q Hill,Alice J O'Toole

doi:10.1186/s41235-018-0117-4

Eilidh Noyes, Matthew Q Hill + Show 1 more

Open Access

https://doi.org/10.1186/s41235-018-0117-4

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Abstract

There are large individual differences in people’s face recognition ability. These individual differences provide an opportunity to recruit the best face-recognisers into jobs that require accurate person identification, through the implementation of ability-screening tasks. To date, screening has focused exclusively on face recognition ability; however real-world identifications can involve the use of other person-recognition cues. Here we incorporate body and biological motion recognition as relevant skills for person identification. We test whether performance on a standardised face-matching task (the Glasgow Face Matching Test) predicts performance on three other identity-matching tasks, based on faces, bodies, and biological motion. We examine the results from group versus individual analyses. We found stark differences between the conclusions one would make from group analyses versus analyses that retain information about individual differences. Specifically, tests of correlation and analysis of variance suggested that face recognition ability was related to performance for all person identification tasks. These analyses were strikingly inconsistent with the individual differences data, which suggested that the screening task was related only to performance on the face task. This study highlights the importance of individual data in the interpretation of results of person identification ability.

Highlights

Human face-recognition ability varies widely from person to person
People with prosopagnosia are at the other end of the spectrum—these people experience severe difficulty with face recognition
From a more theoretical point of view, the dissociation we found between ability to identify people from face images, body images, and biological motion, is not entirely consistent with the neural hypotheses we considered

Summary

Introduction

Human face-recognition ability varies widely from person to person. People who perform with exceptionally high accuracy on face-recognition tasks are called “super”recognisers (see Noyes, Phillips, & O’Toole, 2017 for a review). People with prosopagnosia are at the other end of the spectrum—these people experience severe difficulty with face recognition (see Kress & Daum, 2003). The ability of the rest of the population is dispersed between these two extremes. Many jobs require accurate identifications to be made for security and legal purposes. Screening candidates for these jobs on their personidentification abilities would, in theory, create a workforce of people best skilled for the job. To date, screening has focused exclusively on face recognition. Real-world identification scenarios often include other information that can aid identification such as the body or a person’s movement

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