Initial experimental evidence that the ability to choose between items alters attraction to familiar versus novel persons in different ways for men and women

Nonhuman species may respond to novel mates with increased sexual motivation (‘The Coolidge Effect1). In humans, novel technological advances, such as online dating platforms, are thought to result in ‘Choice Overload’2. This may undermine the goal of finding a meaningful relationship3, orienting the user toward novel possible partners versus committing to a partner. Here, we used a paradigm measuring change in attraction to familiar faces (i.e. rated on second viewing4) to investigate Coolidge-like phenomena in humans primed with choice of potential online dating partners. We examined two pre-registered hypotheses (https://osf.io/xs74r/files/). First, whether experimentally priming choice (viewing a slideshow of online dating images) directly reduces the attractiveness of familiar preferred sex faces compared to our control condition. Second, whether the predicted effect is stronger for men than women given the role of the Coolidge effect in male sexual motivation5.<br/

Why (and how) Superman hides behind glasses: the difficulties of face matching

As a mild-mannered reporter, Clark Kent is able to blend into human society without drawing much attention to himself. Although he utilises several methods of disguise (clothing, posture, hair style), perhaps his most famous is a simple pair of glasses (see Figure 1). We know that wearing glasses can make you look more educated and intelligent (e.g., Hellström & Tekle, 1994), but for Superman, the goal is primarily to hide his true identity. Of course, one of the cornerstones of enjoying superhero fiction is that we suspend our disbelief and try to ignore the obvious questions (for example, how useful or plausible is it that Squirrel Girl can communicate with and understand squirrels?!). However, the scientist inside us sometimes breaks through and we are given the opportunity to investigate. Here, we tackle the question that comic book fans have been asking for decades – could Superman really hide his identity using a pair of glasses

Having options alters the attractiveness of familiar versus novel faces:sex differences and similarities

Although online dating allows us to access a wider pool of romantic partners, choice could induce an ‘assessment mindset’, orienting us toward ‘optimal’ or alternative partners and undermining our willingness to commit or remain committed to someone. Contextual changes in judgements of facial attractiveness can shed light on this issue. We directly test this proposal by activating a context where participants imagine choosing between items in picture slideshows (dates or equally attractive desserts), observing its effects on attraction to i) faces on second viewing and ii) novel versus familiar identities. Single women, relative to single men, were less attracted to the same face on second viewing (Experiments 2 and 4), with this sex difference only observed after imagining not ‘matching’ with any romantic dates in our slideshow (i.e., low choice, Experiment 4). No equivalent sex differences were observed in the absence of experimental choice slideshows (Experiment 3), and these effects (Experiment 2) were not moderated by slideshow content (romantic dates or desserts) or choice set size (five versus fifteen items). Following slideshows, novel faces were more attractive than familiar faces (Experiment 1), with this effect stronger in men than in women (Experiment 2), and stronger across both sexes after imagining ‘matching’ with desired romantic dates (i.e., high choice, Experiment 4). Our findings suggest that familiarity does not necessarily ‘breed liking’ when we have the autonomy to choose, revealing lower-order socio-cognitive mechanisms that could underpin online interactions, such as when browsing profiles and deciding how to allocate effort to different users

Viewers extract the mean from images of the same person: a route to face learning

Research on ensemble encoding has found that viewers extract summary information from sets of similar items. When shown a set of four faces of different people, viewers merge identity information from the exemplars into a representation of the set average. Here, we presented sets containing unconstrained images of the same identity. In response to a subsequent probe, viewers recognized the exemplars accurately. However, they also reported having seen a merged average of these images. Importantly, viewers reported seeing the matching average of the set (the average of the four presented images) more often than a nonmatching average (an average of four other images of the same identity). These results were consistent for both simultaneous and sequential presentation of the sets. Our findings support previous research suggesting that viewers form representations of both the exemplars and the set average. Given the unconstrained nature of the photographs, we also provide further evidence that the average representation is invariant to several high-level characteristics

Unfamiliar faces might as well be another species: Evidence from a face matching task with human and monkey faces

Humans are good at recognizing familiar faces, but are more error-prone at recognizing an unfamiliar person across different images. It has been suggested that familiar and unfamiliar faces are processed qualitatively differently. But are unfamiliar faces at least processed differently from monkey faces? Here we tested 366 volunteers on a face matching test – two images presented side-by-side with participants judging whether the images show the same identity or two different identities – comparing performance with familiar and unfamiliar human faces, and monkey faces. The results showed that performance was most accurate for familiar faces, and was above chance for monkey faces. Although accuracy was higher for unfamiliar humans than monkeys on different identity trials, there was no unfamiliar human advantage over monkeys on same identity trials. The results give new insights into unfamiliar face processing, showing that in some ways unfamiliar faces might as well be another species

Inter-rater agreement in trait judgements from faces

Researchers have long been interested in how social evaluations are made based upon first impressions of faces. It is also important to consider the level of agreement we see in such evaluations across raters and what this may tell us. Typically, high levels of inter-rater agreement for facial judgements are reported, but the measures used may be misleading. At present, studies commonly report Cronbach’s α as a way to quantify agreement, although problematically, there are various issues with the use of this measure. Most importantly, because researchers treat raters as items, Cronbach’s α is inflated by larger sample sizes even when agreement between raters is fixed. Here, we considered several alternative measures and investigated whether these better discriminate between traits that were predicted to show low (parental resemblance), intermediate (attractiveness, dominance, trustworthiness), and high (age, gender) levels of agreement. Importantly, the level of inter-rater agreement has not previously been studied for many of these traits. In addition, we investigated whether familiar faces resulted in differing levels of agreement in comparison with unfamiliar faces. Our results suggest that alternative measures may prove more informative than Cronbach’s α when determining how well raters agree in their judgements. Further, we found no apparent influence of familiarity on levels of agreement. Finally, we show that, like attractiveness, both trustworthiness and dominance show significant levels of private taste (personal or idiosyncratic rater perceptions), although shared taste (perceptions shared with other raters) explains similar levels of variance in people’s perceptions. In conclusion, we recommend that researchers investigating social judgements of faces consider alternatives to Cronbach’s α but should also be prepared to examine both the potential value and origin of private taste as these might prove informative

Within-person variability promotes learning of internal facial features and facilitates perceptual discrimination and memory

Recent research indicates that exposure to within-person variability is essential for developing robust representations of new faces. For example, people perform better on a face matching task after exposure to highly variable photos, compared to less variable photos. However, the specific aspects of face processing that benefit from variability remain unclear. We investigated whether within-person variability improves the ability to match and recognise individual faces, and whether it promotes learning of internal facial features. In one exploratory and one confirmatory experiments, we tested matching and recognition performance of participants after they learned 4 individual faces in a high variability condition and another 4 in a low variability condition. Further, to assess if variability promotes robust learning of invariant facial features (e.g., eyes, nose), we compared performance with and without external facial features (full headshots vs cropped images showing only internal features). We found a large benefit of variability in the recognition task, and a smaller effect on the matching task, but the size of the benefit was comparable with and without the presence of external features. Therefore, within-person variability improves a variety of face recognition skills, and it encourages the encoding of internal facial features

Investigating the other race effect: Human and computer face matching and similarity judgements

The other race effect (ORE) in part describes how people are poorer at identifying faces of other races compared to own-race faces. While well-established with face memory, more recent studies have begun to demonstrate its presence in face matching tasks, with minimal memory requirements. However, several of these studies failed to compare both races of faces and participants in order to fully test the predictions of the ORE. Here, we utilised images of both Black and White individuals, and Black and White participants, as well as tasks measuring perceptions of face matching and similarity. In addition, human judgements were directly compared with computer algorithms. First, we found only partial support for an ORE in face matching. Second, a deep convolutional neural network (residual network with 29 layers) performed exceptionally well with both races. The DCNN’s representations were strongly associated with human perceptions. Taken together, we found that the ORE was not robust or compelling in our human data, and was absent in the computer algorithms we tested. We discuss our results in the context of ORE literature, and the importance of state-of-the-art algorithms

Searching for faces in crowd chokepoint videos

Investigations of face identification have typically focussed on matching faces to photographic IDs. Few researchers have considered the task of searching for a face in a crowd. In Experiment 1, we created the Chokepoint Search Test to simulate real‐time search for a target. Performance on this test was poor (39% accuracy) and showed moderate associations with tests of face matching and memory. In addition, trial‐level confidence predicted accuracy, and for those participants who were previously familiar with one or more targets, higher familiarity was associated with increased accuracy. In Experiment 2, we found improvements in performance on the test when three recent images of the target, but not three social media images, were displayed during searches. Taken together, our results highlight the difficulties inherent in real‐time searching for faces, with important implications for those security personnel who carry out this task on a daily basis

Familiarity does not inhibit image-specific encoding of faces

When matching and recognising familiar faces, performance is unaffected by changes to image-specific details such as lighting, head angle, and expression. In contrast, these changes have a substantial impact on performance when faces are unfamiliar. What process can account for this difference? Recent evidence shows a memory disadvantage for remembering specific images of familiar people compared to unfamiliar people, suggesting that image invariance in familiar face processing may be supported by loss of image-specific details in memory. Here, we examine whether this cost results from loss of image specific details during encoding of familiar faces. Participants completed four tasks that required participants to retain image-specific information in working memory: duplicate detection (Experiment 1), change detection (Experiment 2), short-term recognition memory (Experiment 3 & 5), and visual search (Experiment 4). Across all experiments (combined n = 270), our results consistently show equivalent memory performance for specific images of familiar and unfamiliar faces. We conclude that familiarity does not influence encoding of pictorial details, suggesting that loss of image-specificity reported in previous work is a result of longer-term storage mechanisms