Learning own- and other-race facial identities from natural variability

Abstract

Exposure to multiple varying face images of the same person encourages the formation of identity representations which are sufficiently robust to allow subsequent recognition from new, never-before seen images. While recent studies suggest that identity information is initially harder to perceive in images of other- relative to own-race identities, it remains unclear whether these difficulties propagate to face learning, that is, to the formation of robust face representations. We report two experiments in which Caucasian and East Asian participants sorted multiple images of own- and other-race persons according to identity in an implicit learning task and subsequently either matched novel images of learnt and previously unseen faces for identity (Experiment 1) or made old/new decisions for new images of learnt and unfamiliar identities (Experiment 2). Caucasian participants demonstrated own-race advantages during sorting, matching, and old/new recognition, while corresponding effects were absent in East Asian participants with substantial other-race expertise. Surprisingly, East Asian participants showed enhanced learning for other-race identities during matching in Experiment 1, which may reflect their increased motivation to individuate other-race faces. Thus, our results highlight the importance of perceptual expertise for own- and other-race processing, but may also lend support to recent suggestions on how expertise and socio-cognitive factors can interact.

Normative data for two challenging tests of face matching under ecological conditions

“…Additionally, alternate versions of the FICST could be developed. For example, to account for sex-dependent differences in variation across ambient images, parallel male and female versions could be included, as well as other-race versions (see Tüttenberg & Wiese, 2019). As processing proficiency deteriorates with other-race faces, assessing how the ability of top performers varies across races might provide information valuable for deployment in situations that require processing of faces from varied ethnic backgrounds (e.g., specialized thefts committed almost exclusively by a specific nationality; Green, personal communication (2019)).…”

Perceiving ingroup and outgroup faces within and across nations

“…In general, few studies have been conducted that include experimental designs that can differentiate between the effects of experience and motivation (Tüttenberg & Wiese, 2019). This issue is even more problematic when focusing on research across nations.…”

“…While our brief review provides some evidence for both experience and motivation as explanations for differences in processing ingroup and outgroup faces, such as the ORE and biases in emotion identification, it is clear that this support is neither strong nor consistent (Stelter et al, 2021). Given that these mechanisms may work alone or in conjunction to predict certain face processes, recent theories have attempted to integrate these mechanisms into a single framework (Hugenberg et al, 2013; Tüttenberg & Wiese, 2019). Hugenberg et al (2010), for example, explain how both experience and motivation can combine in their Categorization–Individuation Model to predict the ORE.…”

Understanding face identification through within-person variability in appearance: Introduction to a virtual special issue

“…The other articles in this virtual special issue were published subsequently and have adopted some or all of these suggestions. Broadly, these articles fall into three categories, comprising research that has directly examined the benefit of studying face identification with multiple images ( Andrews et al, 2015 , 2017 ; Dowsett et al, 2016 ; Jones et al, 2017 ; Longmore et al, 2017 ; Menon et al, 2015 ; Ritchie & Burton, 2017 ); research with designs that incorporate multiple images of faces across all conditions ( Bortolon et al, 2018 ; Hayward et al, 2017 ; Tuettenberg & Wiese, 2019 ); and recent work on voice recognition that is adapting these research methods from the face domain ( Johnson et al, 2020 ; Lavan et al, 2019 ; Stevenage et al, 2020 ).…”

“…These were used to study the learning of own- and other-race faces under conditions of greater ecological validity than could be achieved by previous studies that used only a single face image. Similarly, Tuettenberg and Wiese (2019) examined whether differences between own- and other-race faces during the identity-sorting of sets of photographs propagate to the subsequent matching and recognition of novel images of the learned identities. Bortolon et al (2018) employed several ambient images per identity to study self-recognition under more natural viewing conditions than in previous studies.…”