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Self-reported face recognition abilities
for own and other-race faces
Alejandro J. Estudillo
Abstract
Purpose –The other-race effect shows that people are better recognizing faces from their own-race
compared to other-race faces. This effect can have dramatic consequences in applied scenarios
whereby face identification is paramount, such as eyewitness identification. This paper aims to
investigate whether observers haveinsights into theirability to recognize other-race faces.
Design/methodology/approach –Chinese ethnic observers performed objective measures of own-
and other-race face recognition –the Cambridge Face Memory Test Chinese and the Cambridge Face
Memory Test original; the PI20 –a 20-items self-reported measured of general face recognition abilities;
and the ORE20 –a new developed 20-items self-reported measure of other-race face recognition.
Findings –Recognition of own-race faces was better compared to other-race faces. This effect was also
evident at a phenomenological level, as observers reported to be worse recognizing other-race faces
compared to own-race faces. Additionally, althougha moderate correlation was found between own-race
face recognition abilities and the PI20, individual differences in the recognition of other-race faces was
only poorly associated with observers’ scores in the ORE20.
Research limitations/implications –These results suggest that observers’ insights to recognize faces
are more consistent and reliable for own-race faces.
Practical implications –Self-reported measures of other-race recognition could produce misleading
results. Thus, when evaluating eyewitness’ accuracy identifying other-race faces, objective measures
should be used.
Originality/value –In contrast to own race recognition, people have very limited insights into their
recognition abilities for other race faces.
Keywords Face recognition, Eyewitness identification, Face identification, Other-race effect, PI20,
Self-reported face recognition
Paper type Research paper
Introduction
People are generally more efficient and accurate recognizing faces of their own-race
compared to other-race faces. This effect, which is known as the other-race effect (ORE,
Malpass and Kravitz, 1969), is evident across different cultures and countries (Meissner
and Brigham, 2001) and has been found with different paradigms, including perceptual
matching (Kokje et al., 2018;Megreya et al.,2011), face recognition (Chiroro and Valentine,
1995;Estudillo et al.,2020;Malpass and Kravitz, 1969;Wong et al., 2020) and line-up
identification tasks (Evans et al., 2009). A meta-analysis study comprising nearly 5000
participants across 39 different studies showed that people are 2.23 times more likely to
recognize own-race faces compared to other-race faces (Meissner and Brigham, 2001).
This evidence points that the ORE is a very robust effect.
Rather than being homogeneous, the size of the ORE presents substantial individual
differences across observers (Wan et al.,2017). For example, a recent study with
Caucasian and Asians observers showed the standard ORE at a group level, that is
recognition performance was better for own compared to other race faces (Wan et al.,
Alejandro J. Estudillo is
based at Department of
Psychology, Bournemouth
University –Talbot
Campus, Poole, UK and
Schoool of Psychology,
University of Nottingham,
Selangor, Malaysia.
Received 19 June 2020
Revised 15 August 2020
19 September 2020
Accepted 22 September 2020
Funding: The author received
no specific funding for this
work.
Conflict of interest: The author
declares no conflict of interest.
Ethical Approval: This study
has been run following the
Code of Ethics and Conduct
authorized by American
Psychological Association, and
it was approved by the ethics
committee of the University of
Nottingham Malaysia.
Informed Consent: Participants
gave their informed consent
and were debriefed at the end
of the study.
DOI 10.1108/JCP-06-2020-0025 ©Emerald Publishing Limited, ISSN 2009-3829 jJOURNAL OF CRIMINAL PSYCHOLOGY j
2017). However, an individual differences analysis showed that around 8% of these
observers performed so extremely poor at recognizing other-race faces that they could be
considered to suffer a specific type of face-blindness for other race faces. The authors
concluded that the lack of contact with other-race faces is the main cause of the ORE (Wan
et al.,2017
; see also Estudillo et al., 2020).
Regardless of its origin, it has become clear that the ORE can have catastrophic
consequences in applied scenarios whereby face identification is of paramount importance,
such as in eyewitness identification parades and id-verification settings (e.g. passport
control officers). A paradigmatic case illustrating this issue was Ronald Cotton’s wrongful
conviction case (see www.theinnocenceproject.org). Mr. Cotton is an African-American
citizen who was accused of sexual assault in 1984. The rape victim, a Caucasian lady,
misidentified Mr. Cotton as the rapist. As consequence, Mr. Cotton spent more than
10 years in prison for a crime he did not commit until he was exonerated by DNA evidence
in 1995. Thus, if an eyewitness and the perpetrator are from different races, it is crucial to
determine how reliable an eyewitness is recognizing faces from the perpetrator’s race.
Therefore, developing tools to assess eyewitnesses’ ability to recognize other-race faces is
an important endeavor for forensic scientists.
Recognition confidence (i.e. “how confident are you that you have done a correct recognition
decision?”) is a potential maker that can provide some hints about an eyewitness’s accuracy
identifying a perpetrator. Recognition confidence has been widely used in forensic research
and even police and lawyers consider that this marker can provide a reliable measure of
identification skills (Potter and Brewer, 1999;Sauer et al., 2019). These conclusions are
somehow supported by some research. For example, it has been found that recognition
confidence is positively associated with face identification accuracy (Wixted and Wells,
2017), but this association is modulated by participants’ face recognition abilities. This is such
that poor face recognizers are much more likely to make high confidence identification errors
compared to good face recognizers (Grabman et al., 2019). However, other authors have
shown that high recognition confidence can be misleading at individual level (Sauer et al.,
2019). This can be particularly important in other-race face identification, as it has been
shown that people are generally more overconfident when identifying other-race faces
compared to own-race faces (Dodson and Dobolyi, 2016).
In addition, findings about the reliability of recognition confidence for other-race faces are
mixed. For example, although some studies have recently found that high recognition
confidence is equally associated with the identification accuracy of own and other race
faces (Dodson and Dobolyi, 2016;Grabman et al., 2019), other studies reported that
observers not only tend to be less accurate in judging whether they will identify an other-
race face compared to an own-race face (Hourihan et al., 2012;Smith et al., 2001) but also
they tend to be have a less clear memory for other-race faces (Brigham et al.,2007;Smith
et al.,2004
). One feature of recognition confidence that might explain this disparity in the
results is its situation-specificity. In recognition confidence procedures, observers are
simply asked about their confidence about having seen a particular face. However, this
procedure is specific for the seen face and does not gather information about how good the
observer is recognizing either own- and other-race faces.
One potential alternative to recognition confidence could be self-reported measures of face
recognition (Bate et al., 2018;Bobak et al.,2019;Livingston and Shah, 2018;Shah et al.,
2015a; Ventura et al., 2018). These measures describe different daily life situations involving
face recognition abilities, so, in contrast to recognition confidence, self-reported measures
of face recognition are not situation-specific. For example, Sha and colleagues (Shah et al.,
2015a) introduced the PI20 questionnaire, a 20-statements self-reported measure of face
identification. Agreement with these statements is scaled on a five-point Likert-scale.
The authors reported strong negative correlations between the score in the PI20 and
objective measures of face identification, such as famous face recognition, the Cambridge
jJOURNAL OF CRIMINAL PSYCHOLOGY j
Face Memory Test (CFMT-Original, Duchaine and Nakayama, 2006) and the Glasgow Face
Matching Test (Shah et al.,2015b) –a perceptual measure of face identification that
simulates the id-verification scenarios and that it has been used in several applied studies
with police (Robertson et al.,2016) and passport control officers (White et al., 2014).
Interestingly, the PI20 has been translated to different languages, including Portuguese
(Ventura et al., 2018), Japanese (Nakashima et al.,2020) and Mandarin (Estudillo and
Wong, 2021). In general, studies using the PI20 have concluded that adults have moderate
to strong insights into their face recognition abilities (Livingston and Shah, 2018;Ventura
et al.,2018but see Bobak et al.,2019;Estudillo and Wong, 2021).
A question that arises is whether these insights can be generalized to other-race face
recognition. At a theoretical level this has important consequence for models of
metacognition. For example, according to the well-known Dunning–Kruger effect, unskilled
people (i.e. non-experts in a specific field) present very poor insights about their actual
performance (Dunning et al.,2003;Fakcharoenphol et al.,2015). This effect which, has
been found in different domains, including humour, logic, grammar knowledge and face
perception (Dunning et al.,2003;Pennycook et al.,2017;Zhou and Jenkins, 2020), makes a
clear prediction about our study: as people are generally experts recognizing own-race
faces, but not other-race faces (Estudillo et al., 2020;Tanaka et al.,2013), people would
have more accurate insights into their recognition abilities for own-race faces compared to
other-race faces. Thus, this study also allows us to test the Dunning–Kruger effect from a
different domain: the recognition of own- and other-races faces. From a more applied
perspective, having insights to recognize other-race faces would be important in forensic
scenarios, such as during the identification of other-race perpetrators or during id
verification processes, as it could provide information about how reliable an observer is
identifying other-race faces. However, to date, self-reported measures of face recognition
abilities have not been adapted to other-race faces.
The present study aims to explore observers’ insight to recognize own- and other-race
faces. To achieve this, we used the PI20 to evaluate observers’ own-race face recognition
and a new developed self-reported measure for evaluating other-race face recognition (the
ORE20). Given the high reliability and construct validity of the PI20 (Shah et al., 2015a), the
ORE20 is a partial adaptation of the PI20. Participants performed objective measures for
the recognition of own- and other-race faces, the PI20 and the ORE20. We expect
participants to be better recognizing own- than other-race faces. Following previous
research with the PI20, we also expect that participants will have moderate to strong
insights into their face recognition abilities for own-race faces. This would be evident by a
negative association between the objective measure of own-race face recognition and the
PI20. Finally, if participants have insights into their recognition for other-race faces we would
expect that the ORE20 would be associated with their performance in the objective
measure of the recognition of other-race faces.
Methods
Participants
Eighty-five Chinese ethnic participants (58 females) from the University of Nottingham
Malaysia took part in this study for course credits. Observers mean age was of 21 yeas
(SD = 3). All observers reported having normal or corrected-to-normal vision. Participants
gave their informed consent and were debriefed at the end of the study. This study was
approved by the ethics committee of the University of Nottingham Malaysia.
Materials, apparatus and procedure
This study involves an objective face recognition stage and a self-reported face recognition
abilities stage. The order of these stages was counterbalanced across participants.
jJOURNAL OF CRIMINAL PSYCHOLOGY j
Testable platform was used to present stimuli and to record observers’ responses. As
English is the teaching language at the University of Nottingham Malaysia, all the
instructions and questionnaires in this study were in English.
Objective face recognition stage
In this stage, observers performed both the CFMT-Original (Duchaine and Nakayama,
2006) and the CFMT-Chinese (McKone et al.,2012) in a counter-balanced order. Both tests
follow an identical format, but they use Caucasian and Chinese faces as stimuli,
respectively. These tests are valid measures of face recognition as they require the
recognition of faces across different images, and no simple pictorial recognition (Bruce,
1982;Estudillo, 2012;Estudillo and Bindemann, 2014;Longmore et al.,2008). Participants
are required to learn and recognize different unfamiliar faces in three different stages. In the
same image stage, observers are asked to learn a target identity, which is presented in
three different orientations (i.e. mid-profile left, frontal and mid-profile right). Observers are
then presented with a three-alternative forced-choice task, whereby they are required to
select the studied target identity among two foils, with one trial per orientation. This stage is
repeated for each of six target identities, giving a total of 18 trials. In the novel images
stage, observers are presented with the same six target identities all in once for 20 s. Then,
they have to identify a novel instance of the target face among two distractors. This stage
contains a total of 30 trials. The last stage is identical to the previous stage, but faces at test
are presented with visual noise to make the task more challenging. This stage contains a
total of 24 trials, thus the maximum score an observer can obtain is 72. Internal reliability
analysis showed alpha values of 0.86 for the CFMT-Original and 0.90 for the CFMT-Chinese.
These values are in agreement with previous research (e.g. Bowles et al., 2009;Estudillo
et al.,2020
).
Self-reported face recognition abilities stage
In this stage, observers filled in both the PI20 and the ORE20 questionnaires in a counter-
balanced order. The PI20 (Shah et al.,2015a) is a self-reported measure of face
recognition. It contains 20 items describing the experience of face recognition. In the
instructions of this test, we emphasized that these items refer to the recognition of Chinese
peers (i.e. own-race faces for our sample).
The ORE20 questionnaire was developed to conduct this study. This questionnaire is a self-
reported measure of face recognition abilities for other-race faces. The questionnaire
comprises 20 items reporting different situations describing the experience of recognizing
Caucasian faces (other-race faces for our sample). Most of the items of the ORE20 were
adapted from the PI20 (e.g. Item 2 ORE20: to recognize Caucasian people, I rely on non-
facial cues, such as voice, Item 10 PI20: Without hearing people’s voices, I struggle to
recognize them; Item 10 ORE20: My face recognition ability is similar for Caucasians and
Chinese faces, Item 2 PI20: My face recognition ability is worse than most people).
However, this adaptation is not possible for some of the PI20 items (e.g. PI20 item 11:
Anxiety about face recognition has led me to avoid certain social or professional situations;
PI20 Item 13: I am very confident in my ability to recognize myself in photographs; Item 15:
My friends and family think I have bad face recognition or bad face memory). Thus, other
items of the ORE20 were created with the aim of capturing different aspects involved in the
processing of other races faces, such as learning (e.g. Item 20 ORE20: I have to try harder
to memorise Caucasian faces than Chinese faces), recognition (e.g. Item 13 ORE20: I
struggled to recognise my Caucasian classmates or colleagues), discrimination (e.g. Item
14 ORE20: I find that most Caucasian faces look alike) and race categorization (e.g. Item 9
ORE20: I mistake familiar Caucasian people as Chinese people when they change their
hairstyle).
jJOURNAL OF CRIMINAL PSYCHOLOGY j
Observers were asked to rate their agreement with each statement of the PI20 and the
ORE20 on a five-point Likert-scale (1 = strongly agree, 5 = strongly disagree). In both
questionnaires, higher total scores reflect lower recognition abilities. However, for the sake
of simplicity, the scores of the positive items were reversed (PI20: items 1, 2, 3, 4, 5, 6, 7,
10, 11, 12, 14, 15, 16, 18, 20; ORE20: items 2, 3, 4, 5, 7, 8, 9, 11, 13, 14, 15, 16, 17, 18, 20),
so that higher scores in both questionnaires indicate better self-perceived face recognition
abilities. Internal reliability analysis revealed alpha values of 0.84 and 0.89, for the PI20 and
the ORE20, respectively.
Results
In a first part of our analysis, we compared observers’ recognition performance for own and
other-race faces. Observers were better recognizing own- compared to other-race faces
[t(84) = 7.77, p<.001, d = 0.68, CI =0.48 - 0.88] [Figure 1(a)]. Interestingly, the same
pattern was also obtained at a phenomenological level as observers reported to be worse
recognizing other-race faces –as reflected by their scores in the ORE20 –compared to
own-race faces –as reflected by their scores in the PI20 [t(84)= 6.30, p<. 001, d = 0.65,
CI = 0.42 - 0.88] [Figure 1(b)].
In a second part of our analysis, we explored observers’ insight to recognize own- and
other-race faces. Scores in the PI20 were moderately associated with the scores in the
CFMT-Chinese [r= 0.45, p<0.001, CI = 0.26 - 0.60] [Figure 2(a)]. On the other hand,
scores in the ORE20 were only poorly associated with the scores in the CFMT-Original
[r= 0.21, p = 0.04, CI =0.00 - 0.41] [Figure 2(b)]. The differences between both correlations
were explored using Silver and colleagues’ test of non-overlapping dependent correlations
(Diedenhofen and Musch, 2015;Silver et al.,2004). This test showed that the magnitude of
the association between own-race face recognition and the PI20 was stronger that the
magnitude of the association between other-race face recognition and the ORE20 (z= 2.08,
p<0.05). The PI20 was also associated with observers’ performances in the CFMT-Original
[r= 0.37, p<0.001, CI = 0.17 - 0.54] [Figure 2(c)]. However, Hittner and colleagues’ test of
overlapping dependent correlations (Diedenhofen and Musch, 2015;Hittner et al., 2003)
Figure 1 (a) Mean scores in the CFMT-Chinese and in the CFMT-Original; (b) mean
scores in the ORE20 and PI20
jJOURNAL OF CRIMINAL PSYCHOLOGY j
showed no differences between the magnitudes of this association and the association
between the ORE20 and the CFMT-Original [z= 1.58, p = 0.11].
We also explored whether scores in the ORE20 questionnaire predict the other-race
effect magnitude. We first considered the magnitude of the other-race effect as the
difference between accuracy performance in the CFMT-Chinese and the CFMT-Original
(i.e. subtraction method). In this sense, it would be expected that higher scores in the
ORE20 would be negatively associated with the other-race effect magnitude
[Figure 2(d)]. We found that the score in the ORE20 was not associated with the other-
race effect magnitude [r=0.11, p = 0.26, CI = 0.31 - 0.10]. However, it has been
argued that the subtraction method for calculating the other-race effect might hinder the
contribution of the two components of the other-race effect, namely the own-race
advantage and other-race decrement (DeGutis et al.,2013a). On the contrary,
calculating the other-race effect with a regression method allows the isolation of these
two components by regressing other- from own-race performance to produce own-race
advantage residuals and own- from other-race to produce other-race decrement
residuals (DeGutis et al., 2013a; DeGutis et al.,2013b). Thus, once the residuals for both
components were calculated, they were correlated with the scores in the ORE20
[Figure 2(e) and 2(f)]. We found that scores in the ORE20 were not associated either with
the other-race decrement [r= 0.19, p= 0.07, CI = 0.15 - 0.39] nor with the own-race
advantage [r=0.05, p=0.61,CI= 0.26 - 0.16].
Figure 2 (a) Simple correlationbetween the own-race face recognition measure (CFMT-
Chinese) and the PI20; (b) simple correlation between the other-race face
recognition measure (CFMT-Original) and theORE20; (c) simple correlation
between the other-raceface recognition measure (CFMT-Original) and the PI20;
(d) simple correlation between the other-race face effect magnitude(CFMT-
Chinese –CFMT-Original) and the ORE20; (e) simple correlation between the
other-race decrement (residuals from regressing own- from other-race
performance) and the ORE20; (f) simple correlation between the own-race
decrement (residuals from regressing other- from own-race performance) and
the ORE20
jJOURNAL OF CRIMINAL PSYCHOLOGY j
In conclusion, although our results show that observers have moderate insights into their
recognition abilities for own-race faces, their insights to recognize other-race faces are very
limited.
Discussion
In recent years, there has been a growing interest in phenomenological measures of
face recognition. The PI20 questionnaire was created for this aim and has been used
with normal and prosopagnosic population (Shah et al., 2015a). Using this instrument,
several studies have shown that human observers have moderate to good insights into
their face recognition abilities (Livingston and Shah, 2018;Shah et al., 2015b; Ventura
et al., 2018). The present study aimed to explore whether observers also have insights
into their recognition of other-race faces. For this aim, we created the ORE20, a 20-item
self-reported measure of the recognition of other-race faces (Caucasian faces in our
case).
Our results show that our observers were better recognizing own-race faces compared
other-race faces. This pattern of results replicates the ORE observed in other studies
(e.g. Chiroro and Valentine, 1995;Estudillo et al., 2020;Malpass and Kravitz, 1969;
Meissner and Brigham, 2001;Wong et al., 2020). Interestingly, the ORE observed in our
study was also evident at a phenomenological level as observers reported to be worse
recognizing other-race faces compared to own-race faces. We also found a moderate
association between our objective measure of face recognition (i.e. the CFMT-Chinese in
our case) and the PI20, replicating previous research with a Chinese ethnic population.
This association was stronger in magnitude compared to the weak association found
between our objective measure of other-race face recognition (i.e. the CFMT-Original)
and the ORE20, demonstrating that the self-reported face recognition abilities are
stronger for own-races compared to other-race faces. We also found no association
between the other-race effect magnitude (calculated by both subtractions and
regression methods) and the ORE20.
Our results are in agreement with previous studies showing that observers tend to report
that their memory is less clear when they have to recognize other-race faces compared to
own-race faces (Smith et al., 2004). In fact, observers’ metamnemonic accuracy is also
worse for other-race faces (Hourihan et al., 2012). These results, in conjunction with our own
results suggests that observers do not only have remarkable problems to recognize other-
race faces but also that their insights for the recognition of other-race faces can be highly
misleading.
The weak association found between the recognition of other-race faces (CFMT-Original)
and the ORE20 cannot be explained by the psychometric properties of these tests, as our
reliability analysis showed that both tests have a strong internal consistency. However, it is
important to note that the limited insight to recognize other-race faces contrasts with the
moderated-to-good insights observers have into their general face recognition abilities, as
shown by others (Livingston and Shah, 2018;Shah et al.,2015b; Ventura et al.,2018) and
the results of the present study. These general insights into face recognition abilities can
also explain the association found between the PI20 and the recognition of other-race faces.
Despite the large differences found in terms of accuracy, research has shown that the
recognition of own- and other-race faces share around 45% of variance ( Wan et al., 2017).
Thus, the association between the PI20 and the CFMT-Original seem to reflect these
general face recognition processes, and not the specific processes of recognizing other-
race faces. From these results, it could be argued that, compared to the ORE20, the PI20 is
a better proxy of other-race face recognition and, therefore, could be potentially used as an
index of the recognition of other-race faces. However, one should be cautious about this
conclusion, as the magnitude of the association found between other-race face recognition
jJOURNAL OF CRIMINAL PSYCHOLOGY j
and the PI20 was not different to that found between other-race face recognition and the
ORE20.
Our results support theories of metacognition that claims that insights about performance
are modulated by experience (Dunning et al., 2003). Specifically, as human observers
tend to have extensive experience with own-race faces, they have considerable number
of opportunities to evaluate their face recognition skills for own-race face. The lack of
experience with other-race faces, thus, limits their evaluation of face recognition skills
with other-race faces. This lack of experience also explains why our observers are still
aware that, in comparison to the recognition of own-race faces, they are worse
recognizing other-race faces. Lack of experience with a particular racial group produces
problems to discriminate faces from that group. This is such that people without
experience with a racial group tend to report that faces from that group tend to look alike
(Meissner and Brigham, 2001). Thus, observers would know that they will not be able to
recognize other-race faces. For this reason, they will rate worse their recognition abilities
for other-race faces compared to own-race faces. Although given the differences
between the PI20 and the ORE20 questionnaires, we are cautious about this conclusion,
converging evidence from expertise research seems to support this hypothesis, as
experts have greater metacognitive awareness of their expertise ability compared to
novices (Dunning et al., 2003;Fakcharoenphol et al.,2015;Persky and Robinson, 2017).
To determine whether and how experience with other-race faces affects the insights into
other-race face recognition, future research should include measures of contact with
other races (Zhao et al.,2014).
In conclusion, our results show that although observers have moderate insights into their
recognition abilities for own-race faces, their insights for other-race face recognition abilities
are limited. These results have important consequences in applied face recognition
settings. For example, in forensic settings, such as line-up identification parades, it might
be necessary to assess an eyewitness ability to recognize faces. In these scenarios, self-
reported measures of other-race recognition could produce misleading results. For this
reason, when evaluating eyewitness’ accuracy identifying other-race faces, objective
measures should be used. Although, self-reported measures of own-race faces could
provide some indication of observers’ actual face recognition abilities, at the best, these
measures should be used as a complement of objective face recognition measures.
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Corresponding author
Alejandro J. Estudillo can be contacted at: aestudillo@bournemouth.ac.uk
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