SignificanceThis study measures face identification accuracy for an international group of professional forensic facial examiners working under circumstances that apply in real world casework. Examiners and other human face “specialists,” including forensically trained facial reviewers and untrained superrecognizers, were more accurate than the control groups on a challenging test of face identification. Therefore, specialists are the best available human solution to the problem of face identification. We present data comparing state-of-the-art face recognition technology with the best human face identifiers. The best machine performed in the range of the best humans: professional facial examiners. However, optimal face identification was achieved only when humans and machines worked in collaboration.

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Face identification is more accurate when people collaborate in social dyads than when they work alone (Dowsett & Burton, 2015, Br. J. Psychol., 106, 433). Identification accuracy is also increased when the responses of two people are averaged for each item to create a 'non-social' dyad (White, Burton, Kemp, & Jenkins, 2013, Appl. Cogn. Psychol., 27, 769; White et al., 2015, Proc. R. Soc. B Biol. Sci., 282, 20151292). Does social collaboration add to the benefits of response averaging for face identification? We compared individuals, social dyads, and non-social dyads on an unfamiliar face identity-matching test. We also simulated non-social collaborations for larger groups of people. Individuals and social dyads judged whether face image pairs depicted the same- or different identities, responding on a 5-point certainty scale. Non-social dyads were constructed by averaging the responses of paired individuals. Both social and non-social dyads were more accurate than individuals. There was no advantage for social over non-social dyads. For larger non-social groups, performance peaked at near perfection with a crowd size of eight participants. We tested three computational models of social collaboration and found that social dyad performance was predicted by the decision of the more accurate partner. We conclude that social interaction does not bolster accuracy for unfamiliar face identity matching in dyads beyond what can be achieved by averaging judgements.

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