The extent to which people self-disclose depends on the valence and intimacy of that information. We developed a 16-item measure that features both dimensions to assess participants’ inclination to self-disclose to humans and robots across three studies, i.e., the VISS scale. We hypothesized that participants would prefer a human over a robot conversation partner, independent of the valence and intimacy of the topic. Using the VISS, participants reported equal willingness to self-disclose to a human and a robot. However, in one out of three studies, participants were more willing to self-disclose positive topics that are low in intimacy (PTLI) to a fellow human, whereas in two out of three studies, they were less prone to self-disclose negative topics that are high in intimacy (NTHI) to a human compared to a robot. Two out of three studies provide a plausible explanation for these differences: participants indicated more motives to self-disclose PTLI to a human than to a robot, with relationship development being one central motive that was more strongly indicated in relation to a human. Furthermore, participants perceived more risks to self-disclose NTHI to a human than to a robot, with the risk of rejection being most prevalent for a human.

Involving users in the design of novel technologies, for instance, by adapting them to personal preferences, can improve attitudes and trust towards them. Research on the customization of robot functionalities is still scarce, with existing work predominantly focusing on the impact of perceived, rather than actual user involvement in the design process. Furthermore, it is unclear whether the effects of customization depend on merely choosing options, or on actively implementing these options. Thus, in the present online experiment, we investigated whether actual time invested in choosing options (i.e., words that a robot would learn) and implementing them (i.e., defining the words to a robot in the individual’s own terms) influenced psychological ownership and trust towards the robot. Contrary to our hypotheses, time invested in choosing options slightly decreased perceived control and psychological ownership over the robot. This might be due to task difficulty, which hints at the role of perceived self-efficacy as a determinant of psychological ownership. No effect of time spent in implementing the chosen words by defining them has been found.

What make robots social and which psychological factors contribute to user perceptions of robots as social agents? We have tried to address these issues by means of experimental psychological research conducted in the Applied Social Psychology Lab at CITEC, Bielefeld University. In my presentation, I will combine a personal account of my journey into the field of HRI with a psychological perspective on developments in social robotics and HRI. To do so, I will shed light on the psychological underpinnings of the perception of robots as social agents, focusing mainly on the impact of design choices (e. g., indicators of robot group membership) on robot-related perceptions. Moreover, I will emphasize the relevance of user attitudes, - how to measure and to change them -, to promote acceptance of novel technologies. I will conclude by pointing out key lessons learned on the way, considering social and ethical implications of doing HRI research.

Various works show that proxemics occupies an important role in human-robot interaction and that appropriate proxemic interaction depends on many characteristics of humans and robots. However, there is none that shows the relationship between an emotional state expressed by a user and a proxemic reaction of the robot to it, in a social interaction between these interactants. In the current experiment (N = 82), we investigate this using an online study in which we examine which proxemic response (i.e., approaching, not moving, moving away) to a person’s expressed emotional state (i.e., anger, fear, disgust, surprise, sadness, joy) is perceived as appropriate. The quantitative and qualitative data collected suggests that the robot’s approach was considered appropriate for the expressed fear, sadness, and joy, whereas moving away was perceived as inappropriate in most scenarios. Further exploratory findings underline the importance of appropriate nonverbal behavior on the perception of the robot.

The generalizability of empirical research depends on the reproduction of findings across settings and populations. Consequently, generalizations demand resources beyond that which is typically available to any one laboratory. With collective interest in the joint Simon effect (JSE) -- a phenomenon that suggests people work more effectively with humanlike (as opposed to mechanomorphic) robots -- we pursued a multi-institutional research cooperation between robotics researchers, social scientists, and software engineers. To evaluate the robustness of the JSE in dyadic human-robot interactions, we constructed an experimental infrastructure for exact, lab-independent reproduction of robot behavior. Deployment of our infrastructure across three institutions with distinct research orientations (well-resourced versus resource-constrained) provides initial demonstration of the success of our approach and the degree to which it can alleviate technical barriers to HRI reproducibility. Moreover, with the three deployments situated in culturally distinct contexts (Germany, the U.S. Midwest, and the Mexico-U.S. Border), observation of a JSE at each site provides evidence its generalizability across settings and populations.

Research on robot groups has often applied psychological principles underlying group processes between humans to interactions with and between robots. However, such research has failed to test empirically whether these principles indeed apply to the robot context. For instance, the notion of a social group may be interpreted differently when facing human versus robot groups. Basic research on this issue is missing. Therefore, the present experiment aimed at integrating social psychological theorizing and research on robot groups by utilizing the principles of group entitativity. We examined the effect of robot number and similarity on the perception of these robots as a (social) group. To do so, participants saw pictures of one to ten robots, appearing low or high in similarity. Results showed that the aspects eliciting the perception of a social “group” in humans seem to differ from the factors evoking robot group perception. According to our findings, at least three robots seem necessary for the perception of a robot “group” to emerge. Social psychological research, however, has proposed that two persons suffice to elicit the notion of a human social group. Basic research is needed to substantiate assumptions drawn from social psychological theorizing before translating it into human-robot context.

Most robots currently being sold or developed are either stylized with white material or have a metallic appearance. In this research we used the shooter bias paradigm and several questionnaires to investigate if people automatically identify robots as being racialized, such that we might say that some robots are 'White' while others are 'Asian', or 'Black'. To do so, we conducted an extended replication of the classic social psychological shooter bias paradigm using robot stimuli to explore whether effects known from human-human intergroup experiments would generalize to robots that were racialized as Black and White. Reaction-time based measures revealed that participants demonstrated 'shooter-bias' toward both Black people and robot racialized as Black. Participants were also willing to attribute a race to the robots depending on their racialization and demonstrated a high degree of inter-subject agreement when it came to these attributions.

In the present study, we compared Japanese and German participants' perceptions of social robots. To do so, participants from both cultural backgrounds evaluated two types of service robots designed for use in the smart home context. One of the prototypes featured a rather technical appearance, whereas the other prototype featured a newly designed social robot head. Against our predictions, Japanese and German participants evaluated both robot types similarly. Japanese participants generally showed a stronger tendency to anthropomorphize nonhuman agents and attributed more mind, particularly on the experience dimension, to both robot types than German participants. Nonetheless, Japanese and German participants attributed similar levels of agency to both robot types. Unexpectedly, Japanese participants perceived the robots even as less humanlike than German participants. As predicted, Japanese participants reported less attitudinal robot acceptance and tended to show less trust toward both robot types than Germans. Japanese and Germans indicated similar levels of robot anxiety, perceived uncanniness, and robot likeability. Japanese and German participants generally perceived the robots rather as machines and tools than as human companions. Especially German participants wanted to use the robots for rather safe, boring, and simple tasks that do not require any direct interaction with them. Japanese and German participants were not yet familiar with robots and showed less positive attitudes toward them than widely believed (e.g., [1]). Implications how to gain a more realistic view on users' perceptions of robots to enable a fruitful and comfortable HRI are discussed.

Education research has documented a trend that reflects gender-based differences in the choice of fields of study. This, in turn, contributes to an imbalance in the representation of men and women in particular professions: In educational contexts, female teachers predominantly teach stereotypically female areas of study like social sciences and humanities, whereas male teachers are mainly represented in stereotypically male domains like mathematics. Research further provides evidence for the fact that this gender-stereotyped division of labor in education significantly impacts students' learning and motivation. Would gender-related stereotypes also bias learning processes with robots? This is plausible in light of the fact that social robots become more and more popular in learning settings. Thus, should the next generation of educational robots be 'gendered' and what impact would robot gender have on task performance, particularly in the context of a gender-stereotypical human-robot interaction (HRI) task? To investigate these issues, we examined the influence of robot gender on learning when completing either stereotypically female or stereotypically male learning tasks. 120 university students (60 females and 60 males) completed either stereotypically female or stereotypically male tasks with the support of a male vs. female instructor robot. The manipulation check indicated that participants recognized the robot's alleged gender correctly. Importantly, our results suggest that prevailing gender stereotypes associated with learning do not apply to robots that perform gender-stereotypical tasks. Interestingly, our findings indicated that a mismatch of robot gender and gender typicality of the respective task led to increased willingness to engage in prospective learning processes with the robot. We discuss these results with respect to future research on HRI and learning, and with regard to practical implications associated with the introduction of robots into higher education.

Previous research has shown that user features like affect, personality traits, user gender, technology commitment, perceived ease of technology use, and the feeling of being observed impact human-technology interaction (e.g., [1], [2]). To date, most studies have focused on the influence of user characteristics while interacting with single technical devices such as smart phones, audio players (e.g., [3]), or computers (e.g., [1]). To extend this work, we investigated the influence of individual user characteristics, the perceived ease of task completion, and the feeling of being observed on human-technology interaction and human-robot interaction (HRI) in particular. We explored how participants would solve seven tasks within a smart laboratory apartment. To do so, we collected video data and complemented this analysis with survey data to investigate naïve users' attitudes towards the smart home and the robot. User characteristics such as agreeableness, low negative affect, technology acceptance, low perceived competence regarding technology use, and the perceived ease of task were predictors of positive user experiences within the intelligent robotics apartment. Regression analyses revealed that a positive evaluation of the robot was predicted by positive affect and, to a lesser extent, by technology acceptance. Actual interactions with the robot were predicted by a positive evaluation of the robot and, to a lesser degree, by technology acceptance. Moreover, our findings show that user characteristics and, by tendency, the ease of task impact HRI within an intelligent apartment. Implications for future research on how to investigate the interplay of user and further task characteristics to improve HRI are discussed.

The act of revealing personal information, thoughts, and feelings is known as self-disclosure. Self-disclosure represents an important determinant of liking and is central to the development of close relationships among humans. The present study aimed to investigate the role of self-disclosure in human-robot interaction (HRI). 81 participants were randomly assigned to one of four experimental conditions in which they interacted with the humanoid robot NAO. We manipulated whether the robot disclosed personal information or whether the robot asked personal questions to the human interaction partner, so that the participant had to self-disclose. In two control conditions the robot either made factual statements or the robot asked factual questions. Contrary to the hypotheses, the results indicated no immediate statistically significant effects of self-disclosure on the dependent variables robot likability, human-robot interaction quality, future contact intentions, and mind attribution. However, when taking into account participants' tendency to anthropomorphize technology, nature, and the animal world as a covariate, self-disclosure was found to significantly affect participants' tendency to attribute mind to NAO. Furthermore, the results indicate that the form of engagement and dominance in an interaction (i.e., being in the role of a passive listener vs. conversing actively) may affect perceived HRI more than does the content of the verbal exchange. Thus, the paper highlights the importance of considering covariates (i.e., interindividual differences in the tendency to anthropomorphize nonhuman entities) in HRI analyses and points out possible relevant moderators of self-disclosure in HRI.

The attribution of mental states to humanoid robots is a complex psychological phenomenon, as it depends on several factors, including robot's appearance, its behaviour, its country of origin, as well as peoples' cultural background, and exposition to robots. In this paper, we present a cross-cultural study on mind attribution to androids comparing Italian and Japanese high school students' evaluations. Results suggest that the cultural in-group bias not necessarily applies to mind attribution, as some other factors, such as anthropomorphism of nature, and exposure to robots related popular culture, can modify how androids are perceived.

The film industry continuously strives to make visitors’ movie experience more immersive and thus, more captivating. This is realized through larger screens, sophisticated speaker systems, and high quality 2D and 3D content. Moreover, a recent trend in the film industry is to incorporate multiple interaction modalities, such as 4D film, to simulate rain, wind, vibration, and heat, in order to intensify viewers’ emotional reactions. In this context, humans’ sense of touch possesses significant potential for intensifying emotional reactions for the film experience beyond audio-visual sensory modalities. This article presents a framework for authoring tactile cues (tactile gestures as used in this article) and enabling automatic rendering of said gestures to intensify emotional reactions in an immersive film experience. To validate the proposed framework, we conducted an experimental study where tactile gestures are designed and evaluated for the ability to intensify four emotional reactions: high valence-high arousal, high valence-low arousal, low valence-high arousal, and low valence-low arousal. Using a haptic jacket, participants felt tactile gestures that are synchronized with the audio-visual contents of a film. Results demonstrated that (1) any tactile feedback generated a positive user experience; (2) the tactile feedback intensifies emotional reactions when the audio-visual stimuli elicit clear emotional responses, except for low arousal emotional response since tactile gestures seem to always generate excitement; (3) purposed tactile gestures do not seem to significantly outperform randomized tactile gesture for intensifying specific emotional reactions; and (4) using a haptic jacket is not distracting for the users.

Although it is widely accepted that robots will be used in everyday contexts in near future, many people feel anxious and hold negative attitudes toward robots. This negative reaction might be stronger when users come into direct physical contact with them, particularly when touch is required between robots and humans, (e.g., when using robots as assistants to help elderly people at home). Intergroup contact research in social psychology has proposed various forms of contact as a means to reduce negative feelings toward outgroup members. The present study examined how Contact Type (Actual vs. Imagined) and Contact Modality (Look vs. Touch) with a NAO robot would impact attitudes toward NAO compared to a no-contact control condition. Results showed that nearly any type of contact effectively reduced negative emotions compared to the control condition. However, for participants with preexisting negative emotions toward robots, contact sometimes produced more negative attitudes. We discuss these findings and the resulting implications for future research.

We conducted a human-robot interaction (HRI) experiment in which we tested the effect of inclusionary status (social inclusion vs. social exclusion) and a dispositional correlate of anthropomorphism on social needs fulfillment and the evaluation of a social robot, respectively. The experiment was initiated by an interaction phase including free play between the user and the zoomorphic robot Pleo. This was followed by the experimental manipulation according to which participants were exposed to an experience of social inclusion or social exclusion during a computer game. Subsequently, participants evaluated the robot regarding psychological anthropomorphism, mind perception, and reported the experienced fulfillment of social needs as well as their individual disposition to anthropomorphize. The present research aimed at demonstrating that situationally induced inclusionary status should predominantly influence experienced social needs fulfillment, but not anthropomorphic inferences about a robot. Analogously, we presumed that evaluations of the robot should mainly be driven by the individual disposition to anthropomorphize nonhuman entities, whereas inclusionary status should not affect these judgments. As predicted, inclusionary status only affected experienced social needs fulfillment, whereas the experimental manipulation did not affect robot-related evaluations. In a similar vein, participants low (vs. high) in anthropomorphism differed in their assessment of humanity and mind perception of the robot prototype, whereas inclusionary status did not affect these anthropomorphic inferences. Results are discussed in light of the existing literature on social exclusion, social needs fulfillment, and anthropomorphization of robots.

In an experiment, we tested whether anthropomorphism would reduce psychological stress associated with human-robot interactions (HRI). Participants anticipated (vs. did not anticipate) an interaction with a humanlike versus machinelike robot type, and their electrodermal activity (EDA), a physiological indicator of psychological stress, was measured. Results indicate that anticipating an HRI increased psychological stress independent of robot type.

Negative attitudes towards robots are common and pose an obstacle for successful and pleasant human-robot interaction. To reduce negative attitudes in the context of social robotics, we draw upon social psychological methods of attitude change. Imagined contact represents one such paradigm which to date has mostly been tested and validated in the human-human intergroup context. In the present experiment, we have therefore examined the effectiveness of imagined contact (i.e., the mere mental simulation of contact with a human or nonhuman target) in changing robot-related attitudes, robot anxiety, contact intentions, and psychological anthropomorphism. To do so, participants had to briefly imagine a restaurant scenario as detailed and lively as possible. Crucially, we manipulated the content of the imagined contact scenario as follows: In the control conditions, participants imagined an interaction with a human target or a technical device. In the experimental condition, in contrast, participants imagined an interaction with a robot target. We predicted that imagined contact with a robot (versus a human target versus a technical device) would result in more positive attitudes towards the robot, stronger contact intentions, and higher psychological anthropomorphism whereas robot anxiety should decrease. Contrary to our predictions, however, we found that participants who had imagined contact with a human target reported more positive attitudes and higher contact intentions with a robot prototype than participants who had imagined contact with a technical device. Furthermore, imagined contact with a robot had no effect on the dependent measures. We interpret these findings in light of potential ceiling effects, fluency effects, and the activation of elicited agent knowledge.

In an experiment we manipulated a robot's voice in two ways: First, we varied robot gender; second, we equipped the robot with a human-like or a robot-like synthesized voice. Moreover, we took into account user gender and tested effects of these factors on human-robot acceptance, psychological closeness and psychological anthropomorphism. When participants formed an impression of a same-gender robot, the robot was perceived more positively. Participants also felt more psychological closeness to the same-gender robot. Similarly, the same-gender robot was anthropomorphized more strongly, but only when it utilized a human-like voice. Results indicate that a projection mechanism could underlie these effects.

A recent theoretical framework on anthropomorphism emphasizes the role of elicited agent knowledge in anthropomorphic inferences about nonhuman entities. According to the Three-Factor Model of psychological Anthropomorphism, people use anthropocentric knowledge structures when judging unfamiliar objects (e.g., robots). In the present research, our goal was to manipulate the accessibility of such elicited agent knowledge by varying features of a robot's voice: Specifically, we examined effects of vocal cues that reflected both gender of robot (i.e., a male vs. female voice) and voice type (i.e., a human-like vs. robot-like voice). This was done to test the impact of these vocal features on anthropomorphic inferences about the robot and on human-robot interaction (HRI) acceptance. Our results demonstrate that a robot's vocal cues clearly influence subsequent judgments of the robot and particularly so, when participant gender taken into account. Implications of our research for robotics will be discussed.

In the present study, we experimentally investigated whether the mental simulation of an interaction with the robot NAO would improve human-robot interaction (HRI) acceptance, and would reduce negative attitudes and anxiety toward robots in general. Participants were introduced to the robot NAO and were then instructed to imagine for two minutes either a cooperative or a competitive interaction with the robot or a neutral scenario that did not include an HRI. Our results showed that, independent of its content, imagining contact with NAO improved HRI acceptance. Moreover, after imagining contact with the robot, participants indicated less negative attitudes and less anxiety toward robots in general. These effects were strongest for cooperative imagined contact. Theoretical and practical implications for research on HRI will be discussed.

Recent research has shown that anthropomorphism represents a means to facilitate HRI. Under which conditions do people anthropomorphize robots and other nonhuman agents? This research question was investigated in an experiment that manipulated participants' anticipation of a prospective human-robot interaction (HRI) with a robot whose behavior was characterized by either low or high predictability. We examined effects of these factors on perceptions of anthropomorphism and acceptance of the robot. Innovatively, the present research demonstrates that anticipation of HRI with an unpredictable agent increased anthropomorphic inferences and acceptance of the robot. Implications for future research on psychological determinants of anthropomorphism are discussed.

In an experiment we empirically tested one key determinant of Epley's Three-Factor Theory of Anthropomorphism: Specifically, we investigated the interplay of both dispositional and situational facets of effectance motivation in predicting anthropomorphic inferences about the robot NAO. That is, we manipulated the predictability of the robot's behavior and whether participants anticipated an interaction with NAO. Innovatively, we also examined interindividual differences in participants' desire for control, a dispositional aspect of effectance motivation. Taken together, we go beyond previous work by (1) increasing ecological validity of the experimental setting; by (2) extending the range of measures to assess anthropomorphism, and by (3) examining the role of contextual and dispositional components of effectance motivation for anthropomorphism. Because this is the first work to study the interplay between these factors, our work contributes to a better theoretical and empirical understanding of psychological anthropomorphism.

We examined the effects of a robots' nonverbal response on evaluations of anthropomorphism and other dimensions (e.g., liking, closeness, pleasantness of human-robot interaction) in a case study. Our work both conceptually replicates and extends previous research: On the one hand, we replicated previous findings and generalized them to a different robot type, the iCat. On the other hand, our work extends existing research in that it includes a wider range of dependent variables, with a particular focus on perceptions of anthropomorphism. Taken together, most of our results support the experimental hypotheses for the dependent measures: That is, a robot that provided emotional feedback during the interaction was perceived to be superior to a robot that responded neutrally. Thus, our findings highlight the importance of the interplay of form and function in the attribution of humanness to robots.

This paper introduces the industrial design of the social robot `Flobi'. In total, three key concepts influenced the industrial design: First, the robot head of Flobi appears as a cartoon-like character and has a `hole-free' design without any visible conjunctions. Second, Flobi has dynamic features to display not only primary emotions, but also shame, a typical secondary emotion. Third, the structural design implements exchangeable modular parts. Through modular design, the underlying hardware is quickly accessible and the visual features of the robot (e.g., hairstyle, facial features) can be altered easily. A first study demonstrated the successful implementation of Flobi's dynamic features, whereas a second study demonstrates that the exchangeable hair modules influence gender-schematic perceptions of the robot.