Objective: The purpose of this work was to examine the relationship between self-concept and ingroup/outgroup categorization of robots. Background: Social psychological literature can improve Human–Robot Interaction (HRI) through investigations about cultural differences, intergroup dynamics, and more. Parallel to human–human interaction, people categorize robots as ingroup (“my group”) or outgroup (“not my group”) based on a myriad of variables. They favor ingroup robots by viewing them as more positive and human-like versus outgroup robots or humans. Previous work has examined the effect of robot anthropomorphism (i.e., human-likeness) on this categorization process with diverse findings. Method: Examining the self-concept via the two-baskets theory of self-cognitions, we compared the ingroup categorization of Humans, Machine-like robots, Medium Human-like robots, and High Human-like robots using a simple categorization task. Results: Results indicate that robots and human are categorized to the ingroup correlating with the uncanny valley effect, with humans being most likely to the ingroup followed by Medium Human-like, Machine-like, and High Human-like. Conclusions: Self-concept may not be as important for categorization as other factors; however, important categorization differences exist following the trend of the uncanny valley. Application: Those who design and utilize robots should take categorization differences into consideration when designing robots for public interactions. Further, those who purchase robots for use should be careful to consider the implications of visual similarities to human beings to ensure optimal acceptance OSF: ( https://osf.io/x9rqn/?view_only=fd0894404e304422a6c77ccffa013bcd ). Precis: Considering the uncanny valley, we examine the social categorization of humans and robots and the relation of this categorization to the self-concept in the form of self-cognitions. Results demonstrate important differences in the categorization of various types of human and robot images based strongly on the uncanny valley effect.

Past research with participants in the United States showed that, in competitive group tasks, they have more positive attitudes and behaviors toward robots on their team over humans in another team. Here we present a study in which two Japanese students and two robots, placed in a randomly assigned group, compete with another student-and-robot team in a digital game. We explored participants’ moral behavior towards the robots, measured through their assignment of loud noise blasts to human and robot participants, and their perceptions of and attitudes towards the robots. We then compared this data to that which was collected within the United States. Results indicated that participants in Japan favored their ingroup humans and robots over outgroup agents and differentiated ingroup members more than outgroup members, as within the US. Japanese participants also anthropomorphized robots more than US participants and treated them more positively than US participants.

Mobile robots are being introduced to industrial workplaces in roles that require copresence with humans. To develop effective robots that do not negatively impact humans, including their subjective experience and ability to get their work done, we must understand humans’ needs for working near these robots. In this paper, we examine what human workers need from copresent robots’ motion during work at a large warehouse. To do so, report and synthesize findings about robot motion from across five studies (e.g., focus group, observation, experiment). Results indicate that workers were most focused on robot movement, including consistency, distance, prioritizing people, and indicating when it sensed people. Researchers and practitioners can use these findings to prioritize what aspects of mobile robots to develop to improve human worker experiences around robots and team efficiency.

Mobile telepresence robots can help reduce loneliness by facilitating people to visit each other and have more social presence than visiting via video or audio calls. However, using new technology can be challenging for many older adults. In this article, we examine how older adults use and want to use mobile telepresence robots, how these robots affect their social connection, and how they can be improved for older adults’ use. We placed a mobile telepresence robot in the home of older adult primary participants ( N = 7; age 60 \(+\) ) for 7 months and facilitated monthly activities between them and a secondary participant ( N = 8; age 18 \(+\) ) of their choice. Participants used the robots as they liked between monthly activities. We collected diary entries and monthly interviews from primary participants and a final interview from secondary participants. Results indicate that older adults found many creative uses for the robots, including conversations, board games, and hide “n” seek. Several participants felt more socially connected with others and a few had improved their comfort with technology because of their use of the robot. They also suggested design recommendations and updates for the robots related to size, mobility, and more, which can help practitioners improve robots for older adults’ use.

As food delivery robots are spreading onto streets and college campuses worldwide, users' views of these robots will depend on their direct and indirect interactions with the robots and their conversations with other people, such as those with whom they are ordering food via a robot. We examined if being in a group of 2 to 3 people affects the acceptance and trust of the robot compared to being an individual user. First-time users of the food delivery robot service (N = 60) ordered food either as an Individual or in a Group. We measured the acceptance and trust of the robots after three Exposures (pre-exposure, after ordering food on the app, and after the robots delivered the food). Results indicated that Individual users had more acceptance and trust compared to Group users. Further, as hypothesized, groups had more variation in acceptance and trust compared to individual users, consistent with patterns of group polarization i.e., group members influencing each other's perceptions to become more positive or negative. Further analysis demonstrated that group members were highly influenced by their groupmates. Designers and restaurant operators should consider how to enhance group members' experience of delivery robots.

As artificial agents proliferate, there will be more and more situations in which they must communicate their capabilities to humans, including what they can “see.” Artificial agents have existed for decades in the form of computer-controlled agents in videogames. We analyze videogames in order to not only inspire the design of better agents, but to stop agent designers from replicating research that has already been theorized, designed, and tested in-depth. We present a qualitative thematic analysis of sight cues in videogames and develop a framework to support human-agent interaction design. The framework identifies the different locations and stimulus types – both visualizations and sonifications – available to designers and the types of information they can convey as sight cues. Insights from several other cue properties are also presented. We close with suggestions for implementing such cues with existing technologies to improve the safety, privacy, and efficiency of human-agent interactions.

Robots are being employed to assist people such as in doctors’ offices or hospitals. The robots will be most effective if people trust them. We examine how one understudied environmental factor, scent, can affect trust of a robot. In a room that was unscented or positively scented (lavender), participants (N = 22) answered the robot Nao's questions about their sleep quality, then indicated their trust of the robot. Results show that participants in the lavender scented room trusted the robot more than those in the unscented room. The researchers intend to collect more data, but these preliminary results indicate that researchers should be cautious of the scents in their experiments. Researchers and practitioners should also examine how to harness scents to enhance trust and acceptance of assistive robots.

As robots increasingly assist more people, tendencies of becoming attached to these robots and treat them well have risen; even to the point of treating robot teammates better than human opponents in laboratory settings. We examined how far this ingroup favoritism extends and how to mitigate it. We did this by making participants play an online game in teams of two humans and two robots against two humans and two robots. After the game, they selected someone to perform an additional unpleasant task (according to the results of our pilot test); we manipulated that task to be equally unpleasant for ingroup and outgroup members in one condition, and more unpleasant for outgroup than for ingroup members in the other condition. We did this to examine if the moral principle of utilitarianism (i.e., social justice and fairness) would outweigh ingroup favoritism. In the results, participants showed typical group dynamics like ingroup favoritism. The opportunity to behave in a utilitarian way failed to reverse the ingroup favoritism effect. Interestingly, participants sacrificed their ingroup robot more than they sacrificed even outgroup players. We speculate about why the study showed these unexpected findings and what it may mean for HRI.

There is increasingly heavy reliance on online social communication methods for reducing the sense of social isolation. However, this type of communication lacks one of the most critical elements of expressing emotion to comfort people: physical contact. In the current work, we examined people's perceptions of robots with an affective touch function for conveying sympathy from another person. We conducted two online studies to investigate how individuals evaluate imagined robot touch gestures sent to a friend from them (Study 1) and received by them from a friend (Study 2) in the United States and Japan. We found that sympathy senders preferred robot patting or rubbing the shoulder more than other types of touch, but would rather express sympathy through text or GIFs than by robot-mediated touch. In contrast, recipients perceived more sympathy and social support when they received robot touch gestures showing sympathy, compared to some other means to convey sympathy, short text in particular. The current findings highlight the different perspectives of senders and recipients on robot affective touch and potential cultural and individual differences in evaluations of robot affective touch.

Many people, particularly older adults, are negatively affected by social isolation and loneliness. Robots can facilitate social interaction between persons. In this on-going study, we interview middle and older adults in the US ($n=20$) and Japan ($n=4$) regarding their opinions of socially facilitative robots and how they want robots to assist in their social lives. Participants' desires for robots included robots that could act as an embodied avatar, teleconferencing robots that would be mobile and hands-free, and automated management of their social schedule. Some participants were opposed to the idea of socially facilitative robots, expressed concern regarding robot involvement in human social life, felt that robots were incapable of promoting social interactions between humans, or felt that robots were only for the very elderly and disabled and could not currently assist them. Emerging differences include that thus far, only US participants expressed a desire for pet robots or organizational robots, and all four current Japanese participants expressed the belief that robots were for the very elderly and disabled.

People often hold inaccurate mental models of robots. When such misconceptions regard a robot’s perceptual capabilities, they can lead to issues with safety, privacy, and interaction efficiency. This work is the first attempt to model users’ beliefs about a robot’s perceptual capabilities and make plans to improve their accuracy—i.e., to perform belief repair. We designed a new domain called the Robot Olympics, implemented it as a web-based game platform for collecting data about users’ beliefs, and developed an approach to estimating and influencing users’ beliefs about a virtual robot in that domain. We then conducted a study that collected user behavior and belief data from 240 online participants who played the game. Results revealed shortcomings in modeling the participant’s interpretations of the robot’s actions, as well as the decision making process behind their own actions. The insights from this work provide recommendations for designing further studies and improving user models to support belief repair in human-robot interaction.

As routinely working with robots spreads globally, it becomes important to understand how best to customize robots to each culture to maximize collaboration between humans and robots. In two distinct cultures (United States and Portugal) we examined group-based emotions toward robots with participants self-categorizing three different ways (ingroup, outgroup, and neutral). We tested and confirmed our baseline assumptions that Portuguese participants are more collectivistic and less individualistic, and feel closer with a team in negative, but not positive, scenarios, compared to United States participants. Supporting our hypotheses, the results showed that participants rated more positive emotions toward the robot in the ingroup condition than in the outgroup or neutral conditions. Moreover, an interaction effect between culture and self-categorization revealed that Portuguese participants had more positive group-based emotions toward the robot than United States participants when self-categorizing as an ingroup. We discuss the implications in terms of human-robot teaming and potential future research directions.

As artificial agents proliferate into society, there will be more and more situations in which they need to communicate their capabilities to humans, including what they can “see.” Humans do this with each other by using mental models of human capabilities coupled with social cues that enable situation awareness. In order to design better agents, we analyze video games, which have been communicating to humans about agent visual perception for decades. We present preliminary findings from a qualitative thematic analysis of sight cues in video games. We focus on three cue properties that warrant further study: whether the cue specifies the perceiver, whether the stimulus’ primary purpose is to be a sight cue, and the communication of non-binary sighting information. We close with an additional call for future work: on the effects of using multiple sight cues in combination.

This paper proposes a street-style study method to conduct human-robot interaction studies in-the-wild where the robots conduct their own experiments by recruiting their audience, conducting the study and gathering data. This street-style study method was implemented using multi-robot comedy as the platform deployed at an arts and technology festival to validate the concept. Twelve robot comedy shows occurred over seven hours with two robots on stage, who queried the audience during and at the end of each show. The multi-robot aspect enabled the robots to act out interactions relative each other, oneself and the audience. The final street-style study method evolved from pilots at a local farmer’s market, with hardware designed for portability and easy replication. The robots conducted their own human experiments in that they queried the audience after displaying experimentally balanced episodes of relational humor, with permutations of who was the ‘butt of the joke.’ Our study results explore the relational humor of the two robots and the audience, asking the audience to agree or disagree with particular perspectives. Delivered as part of the show, the robots invite the audience to vote via a show of hands. ANOVA analyses of the percent-agreement results find that (1) audiences were generally positive about all aspects of the show unless both robots were being negative, and (2) audiences were more ready to protect the robot comedian’s ego than their own, strongly supporting the statement that the robot was doing a good job.New Abstract

As robots, both individually and in groups, become more prevalent in everyday contexts (e.g., schools, workplaces, educational and caregiving institutions), it is possible that they will be perceived as outgroups, or come into competition for resources with humans. Research indicates that some of the psychological effects of intergroup interaction common in humans translate to human-robot interaction (HRI). In this paper, we examine how intergroup competition, like that among humans, translates to HRI. Specifically, we examined how Number of Humans (1, 3) and Number of Robots (1, 3) affect behavioral competition on dilemma tasks and survey ratings of perceived threat, emotion, and motivation (fear, greed, and outperformance). We also examined the effect of perceived group entitativity (i.e., cohesiveness) on competition motivation. Like in social psychological literature, these results indicate that groups of humans (especially entitative groups) showed more greed-based motivation and competition toward robots than individual humans did. However, we did not find evidence that number of robots had an effect on fear-based motivation or competition against them unless the robot groups were perceived as highly entitative. Our data also show the intriguing finding that participants displayed more fear of and competed slightly more against robots that matched their number. Future research should more deeply examine this novel pattern of results compared to one-on-one HRI and typical group dynamics in social psychology.

Robots are expected to become present in society in increasing numbers, yet few studies in human-robot interaction (HRI) go beyond one-to-one interaction to examine how characteristics of robot groups will affect HRI. In particular, people may show more negative or aggressive behavior toward entitative (i.e., cohesive) robot groups, like they do toward entitative human groups, compared to diverse groups. Furthermore, because people in collectivist (e.g., Japan) and individualistic (e.g., US) cultures respond to groups and to cues of entitativity differently, entitative robot groups may affect people differently across such cultures. This study examines how robot Entitativity Condition (Single Robots, Diverse Group, Entitative Group) and Country (USA, Japan) affect emotions toward, mind attributions to, and willingness to interact with robots. Results indicate that Entitative robot groups, compared to Single robots, were viewed more negatively. Entitative robots were also more threatening than Diverse robots. Diverse robot groups, compared to Single robots, were viewed as having more mind, and participants were more willing to interact with them. These findings were similar in the USA and Japan. This indicates that robot group entitativity and diversity is critical to keep in mind when designing robots.

When it's between a robot on your team and a human member of a competing team, who will you favor? Past research indicates that people favor and behave more morally toward ingroup than outgroup members. Conversely, people typically indicate that they have more moral responsibilities toward humans than nonhumans. This study puts participants into two competing teams, each consisting of two humans and two robots, to examine how people behave toward others depending on Group (ingroup, outgroup) and Agent (human, robot) variables. Measures of behavioral aggression used in previous studies (i.e., noise blasts) and reported liking and anthropomorphism evaluations of humans and robots indicated that participants favored the ingroup over the outgroup, and humans over robots. Group had a greater effect than Agent, so participants preferred ingroup robots to outgroup humans.

Research in HRI indicates that people follow a robot's instructions even when they are incorrect. However, when a robot's instructions or requests contradict those of a human (e.g. an authoritative experimenter), people obey the human instead. This might be due to the experimenter's perceived ingroup status, or to their higher presumed authority compared to the robot. This study manipulated experimenter authority (high, low) and robot group membership (ingroup, neutral) to test how they affected responses to conflicting orders from the two agents depending on the request's importance (big, small). While there was no main effect of group membership and authority on most participant behavior, when experimenter authority was low and the robot an ingroup member, participants defied the experimenter's instructions to turn off an ingroup robot at the end of the experiment, following the robot's instructions instead. Further, request importance affected participant behavior. Participants typically followed the robot's low-importance requests (e.g., moving from one chair to another), but not high-importance requests (e.g., how to perform a simulated task of diagnosing and talking to patients).

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.

Robots are expected to become present in society in increasing numbers, yet few studies in human-robot interaction (HRI) go beyond one-to-one interaction to examine how emotions, attitudes, and stereotypes expressed toward groups of robots differ from those expressed toward individuals. Research from social psychology indicates that people interact differently with individuals than with groups. We therefore hypothesize that group effects might similarly occur when people face multiple robots. Further, group effects might vary for robots of different types. In this exploratory study, we used videos to expose participants in a between-subjects experiment to robots varying in Number (Single or Group) and Type (anthropomorphic, zoomorphic, or mechanomorphic). We then measured participants' general attitudes, emotions, and stereotypes toward robots with a combination of measures from HRI (e.g., Godspeed Questionnaire, NARS) and social psychology (e.g., Big Five, Social Threat, Emotions). Results suggest that Number and Type of observed robots had an interaction effect on responses toward robots in general, leading to more positive responses for groups for some robot types, but more negative responses for others.

With robots becoming more prevalent, it is important to understand human attitudes toward robots not only when humans directly interact with the robots as most research examines, but when robots are performing nonsocial tasks (e.g., cleaning) within sight and hearing of humans. This study examined how presumed robot communication style in such situations of human-robot co-location affects human perceptions of a group of robots. Results suggest that communication style of robots did not affect perceptions of robots, but further studies should use different techniques to manipulate supposed communication style.

We performed an experimental study (n=48) of the effects of context congruency on human perceptions of robotic facial expressions across cultures (Western and East Asian individuals). We found that context congruency had a significant effect on human perceptions, and that this effect varied by the emotional valence of the context and facial expression. Moreover, these effects occurred regardless of the cultural background of the participants. In short, there were predictable patterns in the effects of congruent/incongruent environmental context on perceptions of robot affect across Western and East Asian individuals. We argue that these findings fit with a dynamical systems view of social cognition as an emergent phenomenon. Taking advantage of such context effects may ease the constraints for developing culturally-specific affective cues in human-robot interaction, opening the possibility to create culture-neutral models of robots and affective interaction.

With robots becoming more prevalent in daily life, it is important to understand human attitudes toward robots not only when humans interact with them directly, as most research examines, but also when people are indirectly exposed to robots performing nonsocial tasks (e.g., cleaning) in their vicinity. Because minimalistic robots are at present more likely to be found in households than human-like robots, this study examined human reactions to nonsocial, nonanthropomorphic robots. The specific focus of this study was on how robot communication style during human-robot co-location affects human perceptions of a group of robots. This paper also evaluates the relationship between participants' scores on the Negative Attitudes toward Robots Scale (NARS) and their behavioral response to and perceptions of robots in their environment. Our results suggest that robot communication style did not affect perceptions of robots and that responses on the NARS may not translate directly to behavior toward robots.