Gijsbert Bijlstra

Presentation and validation of the Radboud Faces Database

Many research fields concerned with the processing of information contained in human faces would benefit from face stimulus sets in which specific facial characteristics are systematically varied while other important picture characteristics are kept constant. Specifically, a face database in which displayed expressions, gaze direction, and head orientation are parametrically varied in a complete factorial design would be highly useful in many research domains. Furthermore, these stimuli should be standardised in several important, technical aspects. The present article presents the freely available Radboud Faces Database offering such a stimulus set, containing both Caucasian adult and children images. This face database is described both procedurally and in terms of content, and a validation study concerning its most important characteristics is presented. In the validation study, all frontal images were rated with respect to the shown facial expression, intensity of expression, clarity of expression, genuineness of expression, attractiveness, and valence. The results show very high recognition of the intended facial expressions.

Do Robot Performance and Behavioral Style affect Human Trust? : A Multi-Method Approach

An important aspect of a robot’s social behavior is to convey the right amount of trustworthiness. Task performance has shown to be an important source for trustworthiness judgments. Here, we argue that factors such as a robot’s behavioral style can play an important role as well. Our approach to studying the effects of a robot’s performance and behavioral style on human trust involves experiments with simulated robots in video human–robot interaction (VHRI) and immersive virtual environments (IVE). Although VHRI and IVE settings cannot substitute for the genuine interaction with a real robot, they can provide useful complementary approaches to experimental research in social human robot interaction. VHRI enables rapid prototyping of robot behaviors. Simulating human–robot interaction in IVEs can be a useful tool for measuring human responses to robots and help avoid the many constraints caused by real-world hardware. However, there are also difficulties with the generalization of results from one setting (e.g., VHRI) to another (e.g. IVE or the real world), which we discuss. In this paper, we use animated robot avatars in VHRI to rapidly identify robot behavioral styles that affect human trust assessment of the robot. In a subsequent study, we use an IVE to measure behavioral interaction between humans and an animated robot avatar equipped with behaviors from the VHRI experiment. Our findings reconfirm that a robot’s task performance influences its trustworthiness, but the effect of the behavioral style identified in the VHRI study did not influence the robot’s trustworthiness in the IVE study.

Stereotype Associations and Emotion Recognition

We investigated whether stereotype associations between specific emotional expressions and social categories underlie stereotypic emotion recognition biases. Across two studies, we replicated previously documented stereotype biases in emotion recognition using both dynamic (Study 1) and static (Study 2) expression displays. Stereotype consistent expressions were more quickly decoded than stereotype inconsistent expression on Moroccan and White male faces. Importantly, we found consistent and novel evidence that participants’ associations between ethnicities and emotions, as measured with a newly developed emotion Implicit Association Test (eIAT), predicted the strength of their ethnicity-based stereotype biases in expression recognition. In both studies, as perceivers’ level of Moroccan-anger and Dutch-sadness associations (compared with the opposite) increased, so did perceivers’ tendency to decode anger more readily on Moroccan faces and sadness on White faces. The observed stereotype effect seemed to be independent of implicit prejudice (Study 2), suggesting dissociable effects of prejudices and stereotypes in expression perception.

Stereotypes and prejudice affect the recognition of emotional body postures.

Most research on emotion recognition focuses on facial expressions. However, people communicate emotional information through bodily cues as well. Prior research on facial expressions has demonstrated that emotion recognition is modulated by top-down processes. Here, we tested whether this top-down modulation generalizes to the recognition of emotions from body postures. We report three studies demonstrating that stereotypes and prejudice about men and women may affect how fast people classify various emotional body postures. Our results suggest that gender cues activate gender associations, which affect the recognition of emotions from body postures in a top-down fashion.

Children's helping behavior in an ethnic intergroup context: Evidence for outgroup helping

Two studies examined when and why children (10–13 years) help ethnic in-group and out-group peers. In Study 1 (n = 163) children could help an out-group or in-group peer with a word-guessing game by entering codes into a computer. While children evaluated the out-group more negatively than the in-group, they helped out-group peers more than in-group peers. Study 2 (n = 117) conceptually replicated the findings of Study 1. Additionally the results suggest that when children endorsed the stereotype that the out-group is “less smart,” this increased their intention to help out-group peers and it decreased their intention to enter codes for in-group peers. The results suggest that the specific content of a negative stereotype can guide helping responses toward out-group and in-group members.

Warning signals for poor performance improve human-robot interaction

The present research was aimed at investigating whether human-robot interaction (HRI) can be improved by a robots nonverbal warning signals. Ideally, when a robot signals that it cannot guarantee good performance, people could take preventive actions to ensure the successful completion of the robots task. In two experiments, participants learned either that a robots gestures predicted subsequent poor performance, or they did not. Participants evaluated a robot that uses predictive gestures as more trustworthy, understandable, and reliable compared to a robot that uses gestures that are not predictive of their performance. Finally, participants who learned the relation between gestures and performance improved collaboration with the robot through prevention behavior immediately after a predictive gesture. This limits the negative consequences of the robots mistakes, thus improving the interaction.

Evaluations versus stereotypes in emotion recognition: a replication and extension of Craig and Lipp’s (2018) study on facial age cues

ABSTRACT Recently, Cognition and Emotion published an article demonstrating that age cues affect the speed and accuracy of emotion recognition. The authors claimed that the observed effect of target age on emotion recognition is better explained by evaluative than stereotype associations. Although we agree with their conclusion, we believe that with the research method the authors employed, it was impossible to detect a stereotype effect to begin with. In the current research, we successfully replicate previous findings (Study 1). Furthermore, by changing the comparative context, Study 2 provides a first test of age-stereotypes affecting emotions recognition. We discuss recommendations for future studies in the domain of social categorisation and emotion recognition.