Face recognition algorithms and the other‐race effect: computational mechanisms for a developmental contact hypothesis

People recognize faces of their own race more accurately than faces of other races. The “contact” hypothesis suggests that this “other‐race effect” occurs as a result of the greater experience we have with own‐ versus other‐race faces. The computational mechanisms that may underlie different versions of the contact hypothesis were explored in this study. We replicated the other‐race effect with human participants and evaluated four classes of computational face recognition algorithms for the presence of an other‐race effect. Consistent with the predictions of a developmental contact hypothesis, “experience‐based models” demonstrated an other‐race effect only when the representational system was developed through experience that warped the perceptual space in a way that was sensitive to the overall structure of the model's experience with faces of different races. When the model's representation relied on a feature set optimized to encode the information in the learned faces, experience‐based algorithms recognized minority‐race faces more accurately than majority‐race faces. The results suggest a developmental learning process that warps the perceptual space to enhance the encoding of distinctions relevant for own‐race faces. This feature space limits the quality of face representations for other‐race faces.     

A competence framework for artificial intelligence research

ABSTRACT

While over the last few decades AI research has largely focused on building tools and applications, recent technological developments have prompted a resurgence of interest in building a genuinely intelligent artificial agent – one that has a mind in the same sense that humans and animals do. In this paper, I offer a theoretical and methodological framework for this project of investigating “artificial minded intelligence” (AMI) that can help to unify existing approaches and provide new avenues for research. I first outline three desiderata that a framework for AMI research should satisfy. In Section 1, I further motivate the desiderata as well as the need for a new framework. Section 2 develops a general methodological approach, the “generative methodology,” and Section 3 develops a version of this methodology, the “Competence Framework for AI research” (CFAI).     

Picturing ourselves in the world: Drawings,interpretative phenomenological analysis and the relational mapping interview

ABSTRACT

Some aspects of experience can be challenging for research participants to verbalise. Interpretative phenomenological analysis (IPA) researchers need to get experience-near to meet their phenomenological commitments, capturing the “texture” and quality of existence, and placing participants in relation to events, objects, others, and the world. Incorporating drawing into IPA designs provides a vehicle through which participants can better explore and communicate their lifeworlds. IPA researchers also require rich accounts to fulfil their interpretative commitments. Drawing taps into multiple sensory registers simultaneously, providing polysemous data, which in turn lends itself to hermeneutic analysis. This article outlines a multimodal method, the relational mapping interview, which was developed to understand the relational context of various forms of distress and disruption. We illustrate how the approach results in richly nuanced visual and verbal accounts of relational experience. Drawing on an “expanded hermeneutic phenomenology,” we suggest how visual data can be analysed within an IPA framework to offer significant experiential insights.     

Salivary progesterone is associated with reduced coherence of attentional, cognitive, and motivational systems

The present study tested whether the hypothesis that high levels of progesterone (P) have a decoupling effect on the function of the brain hemispheres (Hausmann & Gunturkun, 2000) also extends to attentional functions, referential connections between verbal and nonverbal representations and the degree to which implicit motivational needs match a person's explicit goal commitments. Participants (28 women on oral contraceptives, 14 naturally cycling women, 50 men) completed the Lateralized Attention Network Task (Greene et al., 2008), a measure of the alerting, orienting, and conflict-resolution functions of attention for each hemisphere; a measure of referential competence (i.e., the ability to quickly name nonverbal information); a measure of the implicit motives power, achievement, and affiliation; and a content-matched personal goal inventory. In addition, they provided a saliva sample that was assayed for P and cortisol (C). Higher levels of P were associated with lower interhemispheric correlations for alerting and orienting, but with a higher correlation of conflict-resolution performance. Higher P was also associated with longer interhemispheric transfer time, lower congruence between implicit motives and explicit goal commitments and, after controlling for C, with lower referential competence. These results suggest that (a) P is associated with the degree to which attentional functions are correlated between hemispheres, although in a different direction for more posterior (alerting and orienting: decoupling) than for more anterior functions (conflict resolution: coupling), (b) that high P is associated with other indicators of reduced functional coherence between cognitive systems (longer interhemispheric transfer time, lower referential competence), and (c) that high P is also associated with low coherence between implicit and explicit motivational systems.     

Extracting Low-Dimensional Psychological Representations from Convolutional Neural Networks

Convolutional neural networks (CNNs) are increasingly widely used in psychology and neuroscience to predict how human minds and brains respond to visual images. Typically, CNNs represent these images using thousands of features that are learned through extensive training on image datasets. This raises a question: How many of these features are really needed to model human behavior? Here, we attempt to estimate the number of dimensions in CNN representations that are required to capture human psychological representations in two ways: (1) directly, using human similarity judgments and (2) indirectly, in the context of categorization. In both cases, we find that low-dimensional projections of CNN representations are sufficient to predict human behavior. We show that these low-dimensional representations can be easily interpreted, providing further insight into how people represent visual information. A series of control studies indicate that these findings are not due to the size of the dataset we used and may be due to a high level of redundancy in the features appearing in CNN representations.     

Acquiring variation in an artificial language: Children and adults are sensitive to socially conditioned linguistic variation

Languages exhibit sociolinguistic variation, such that adult native speakers condition the usage of linguistic variants on social context, gender, and ethnicity, among other cues. While the existence of this kind of socially conditioned variation is well-established, less is known about how it is acquired. Studies of naturalistic language use by children provide various examples where children’s production of sociolinguistic variants appears to be conditioned on similar factors to adults’ production, but it is difficult to determine whether this reflects knowledge of sociolinguistic conditioning or systematic differences in the input to children from different social groups. Furthermore, artificial language learning experiments have shown that children have a tendency to eliminate variation, a process which could potentially work against their acquisition of sociolinguistic variation. The current study used a semi-artificial language learning paradigm to investigate learning of the sociolinguistic cue of speaker identity in 6-year-olds and adults. Participants were trained and tested on an artificial language where nouns were obligatorily followed by one of two meaningless particles and were produced by one of two speakers (one male, one female). Particle usage was conditioned deterministically on speaker identity (Experiment 1), probabilistically (Experiment 2), or not at all (Experiment 3). Participants were given tests of production and comprehension. In Experiments 1 and 2, both children and adults successfully acquired the speaker identity cue, although the effect was stronger for adults and in Experiment 1. In addition, in all three experiments, there was evidence of regularization in participants’ productions, although the type of regularization differed with age: children showed regularization by boosting the frequency of one particle at the expense of the other, while adults regularized by conditioning particle usage on lexical items. Overall, results demonstrate that children and adults are sensitive to speaker identity cues, an ability which is fundamental to tracking sociolinguistic variation, and that children’s well-established tendency to regularize does not prevent them from learning sociolinguistically conditioned variation.     

Priming effects of arithmetic signs in 10- to 15-year-old children

In this research, 10- to 12- and 13- to 15-year-old children were presented with very simple addition and multiplication problems involving operands from 1 to 4. Critically, the arithmetic sign was presented before the operands in half of the trials, whereas it was presented at the same time as the operands in the other half. Our results indicate that presenting the ‘x’ sign before the operands of a multiplication problem does not speed up the solving process, irrespective of the age of children. In contrast, presenting the ‘+’ sign before the operands of an addition problem facilitates the solving process, but only in 13 to 15-year-old children. Such priming effects of the arithmetic sign have been previously interpreted as the result of a pre-activation of an automated counting procedure, which can be applied as soon as the operands are presented. Therefore, our results echo previous conclusions of the literature that simple additions but not multiplications can be solved by fast counting procedures. More importantly, we show here that these procedures are possibly convoked automatically by children after the age of 13 years. At a more theoretical level, our results do not support the theory that simple additions are solved through retrieval of the answers from long-term memory by experts. Rather, the development of expertise for mental addition would consist in an acceleration of procedures until automatization.