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.

Although research often explores how human-robot interaction influences cooperation in social dilemma scenarios such as the Public Goods Game, most research focuses on robots taking active roles in the game i.e. opponents or team-players. Considering the potential of assistant robots to influence human decision-making, this study explores how an assistant robot with prosocial or individualistic goals influences cooperation in a Public Goods Game. In a between-subjects study (N=60), participants interacted with the robot in one of three conditions: Prosocial, where the robot supported cooperative behavior; Individualistic, where it encouraged self-serving actions; and Control, where the robot provided feedback on the game state without expressing individual goals. Results revealed that participants in the Prosocial or Individualistic conditions contributed less to the public good compared to those in the Control condition. The Prosocial and Individualistic robots were perceived as warmer but evoking more discomfort compared to the Control. Notably, participants who played with the Prosocial robot reported increased trust, not only in the robot but also in their fellow players. These findings suggest that alignment between an assistant robot’s goals and expected social norms plays a key role in trust perception and it also shapes group dynamics. We discuss important considerations for designing assistant robots that provide moral recommendations.

Shape-changing skin is an exciting modality due to its accessible and engaging nature. Its softness and flexibility make it adaptable to different interactive devices that children with and without visual impairments can share. Although their potential as an emotionally expressive medium has been shown for sighted adults, their potential as an inclusive modality remains unexplored. This work explores the shape-emotional mappings in children with and without visual impairment. We conducted a user study with 50 children (26 with visual impairment) to investigate their emotional associations with five skin shapes and two movement conditions. Results show that shape-emotional mappings are dependent on visual abilities. Our study raises awareness of the influence of visual experiences on tactile vocabulary and emotional mapping among sighted, low-vision, and blind children. We finish discussing the causal associations between tactile stimuli and emotions and suggest inclusive design recommendations for shape-changing devices.

Research on robotic ostracism is still scarce and has only explored its effects on adult populations. Although the results revealed important carryover effects of robotic exclusion, there is no evidence yet that those results occur in child-robot interactions. This paper provides the first exploration of robotic ostracism with children. We conducted a study using the Robotic Cyberball Paradigm in a third-person perspective with a sample of 52 children aged between five to ten years old. The experimental study had two conditions: Exclusion and Inclusion. In the Exclusion condition, children observed a peer being excluded by two robots; while in the Inclusion condition, the observed peer interacted equally with the robots. Notably, even 5-year-old children could discern when robots excluded another child. Children who observed exclusion reported lower levels of belonging and control, and exhibited higher prosocial behaviour than those witnessing inclusion. However, no differences were found in children's meaningful existence, self-esteem, and physical proximity across conditions. Our user study provides important methodological considerations for applying the Robotic Cyberball Paradigm with children. The results extend previous literature on both robotic ostracism with adults and interpersonal ostracism with children. We finish discussing the broader implications of children observing ostracism in human-robot interactions.

Children with visual impairments often struggle to fully participate in group activities due to limited access to visual cues. They have difficulty perceiving what is happening, when, and how to act-leading to children with and without visual impairments being frustrated with the group activity, reducing mutual interactions. To address this, we created Touchibo, a tactile storyteller robot acting in a multisensory setting, encouraging touch-based interactions. Touchibo provides an inclusive space for group interaction as touch is a highly accessible modality in a mixed-visual ability context. In a study involving 107 children (37 with visual impairments), we compared Touchibo to an audio-only storyteller. Results indicate that Touchibo significantly improved children's individual and group participation perception, sparking touch-based interactions and the storyteller was more likable and helpful. Our study highlights touch-based robots' potential to enrich children's social interactions by prompting interpersonal touch, particularly in mixed-visual ability settings.

Collaborative coding environments foster learning, social skills, computational thinking training, and supportive relationships. In the context of inclusive education, these environments have the potential to promote inclusive learning activities for children with mixed-visual abilities. However, there is limited research focusing on remote collaborative environments, despite the opportunity to design new modes of access and control of content to promote more equitable learning experiences. We investigated the tradeoffs between remote and co-located collaboration through a tangible coding kit. We asked ten pairs of mixed-visual ability children to collaborate in an interdependent and asymmetric coding game. We contribute insights on six dimensions - effectiveness, computational thinking, accessibility, communication, cooperation, and engagement - and reflect on differences, challenges, and advantages between collaborative settings related to communication, workspace awareness, and computational thinking training. Lastly, we discuss design opportunities of tangibles, audio, roles, and tasks to create inclusive learning activities in remote and co-located settings.

Inclusion is key in group work and collaborative learning. We developed a mediator robot to support and promote inclusion in group conversations, particularly in groups composed of children with and without visual impairment. We investigate the effect of two mediation strategies on group dynamics, inclusion, and perception of the robot. We conducted a within-subjects study with 78 children, 26 experienced visual impairments, in a decision-making activity. Results indicate that the robot can foster inclusion in mixed-visual ability group conversations. The robot succeeds in balancing participation, particularly when using a highly intervening mediating strategy (directive strategy). However, children feel more heard by their peers when the robot is less intervening (organic strategy). We extend prior work on social robots to assist group work and contribute with a mediator robot that enables children with visual impairments to engage equally in group conversations. We finish by discussing design implications for inclusive social robots.

Storytelling has the potential to be an inclusive and collaborative activity. However, it is unclear how interactive storytelling systems can support such activities, particularly when considering mixed-visual ability children. In this paper, we present an interactive multisensory storytelling system and explore the extent to which an emotional robot can be used to support inclusive experiences. We investigate the effect of the robot's emotional behavior on the joint storytelling process, resulting narratives, and collaboration dynamics. Results show that when children co-create stories with a robot that exhibits emotional behaviors, they include more emotive elements in their stories and explicitly accept more ideas from their peers. We contribute with a multisensory environment that enables children with visual impairments to engage in joint storytelling activities with their peers and analyze the effect of a robot's emotional behaviors on an inclusive storytelling experience.

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.

Abstract Understanding how to design agents that sustain cooperation in multi-agent systems has been a long-lasting goal in distributed artificial intelligence. Proposed solutions rely on identifying free-riders and avoiding cooperating or interacting with them. These mechanisms of social control are traditionally studied in games with linear and deterministic payoffs, such as the prisoner’s dilemma or the public goods game. In reality, however, agents often face dilemmas in which payoffs are uncertain and non-linear, as collective success requires a minimum number of cooperators. The collective risk dilemma (CRD) is one of these games, and it is unclear whether the known mechanisms of cooperation remain effective in this case. Here we study the emergence of cooperation in CRD through partner-based selection. First, we discuss an experiment in which groups of humans and robots play a CRD. This experiment suggests that people only prefer cooperative partners when they lose a previous game (i.e., when collective success was not previously achieved). Secondly, we develop an evolutionary game theoretical model pointing out the evolutionary advantages of preferring cooperative partners only when a previous game was lost. We show that this strategy constitutes a favorable balance between strictness (only interact with cooperators) and softness (cooperate and interact with everyone), thus suggesting a new way of designing agents that promote cooperation in CRD. We confirm these theoretical results through computer simulations considering a more complex strategy space. Third, resorting to online human–agent experiments, we observe that participants are more likely to accept playing in a group with one defector when they won in a previous CRD, when compared to participants that lost the game. These empirical results provide additional support to the human predisposition to use outcome-based partner selection strategies in human–agent interactions.

This paper explores the role of prosocial behaviour when people team up with robots in a collaborative game that presents a social dilemma similar to a public goods game. An experiment was conducted with the proposed game in which each participant joined a team with a prosocial robot and a selfish robot. During 5 rounds of the game, each player chooses between contributing to the team goal (cooperate) or contributing to his individual goal (defect). The prosociality level of the robots only affects their strategies to play the game, as one always cooperates and the other always defects. We conducted a user study at the office of a large corporation with 70 participants where we manipulated the game result (winning or losing) in a between-subjects design. Results revealed two important considerations: (1) the prosocial robot was rated more positively in terms of its social attributes than the selfish robot, regardless of the game result; (2) the perception of competence, the responsibility attribution (blame/credit), and the preference for a future partner revealed significant differences only in the losing condition. These results yield important concerns for the creation of robotic partners, the understanding of group dynamics and, from a more general perspective, the promotion of a prosocial society.

This PhD project aims at investigating how a social robot can adapt its behaviours to the group members in order to achieve more positive group dynamics, which we identify as group intelligence. This goal is supported by our previous work, which contains relevant data and insightful results to the understanding of group interactions between humans and robots. Finally, we examine and discuss the future work we have planned and what are the contributions to Human-Robot Interaction (HRI) field.

Our goal is to disseminate an exploratory investigation that examined how physical presence and collaboration can be important factors in the development of assistive robots that can go beyond information-giving technologies. In particular, this video exhibits the setting and procedures of a user study that explored different types of collaborative interactions between robots and blind people.

In this paper we sought to understand how the display of different levels of warmth and competence, as well as, different roles (opponent versus partner) portrayed by a robot, affect the display of emotional responses towards robots and how they can be used to predict future intention to work. For this purpose we devised an entertainment card-game group scenario involving two humans and two robots (n=54). The results suggest that different levels of warmth and competence are associated with distinct emotional responses from users and that these variables are useful in predicting future intention to work, thus hinting at the importance of considering warmth and competence stereotypes in Human-Robot Interaction.

This paper explores how robotic teammates can enhance and promote cooperation in collaborative settings. It presents a user study in which participants engaged with two fully autonomous robotic partners to play a game together, named “For The Record”, a variation of a public goods game. The game is played for a total of five rounds and in each of them, players face a social dilemma: to cooperate i.e., contributing towards the team's goal while compromising individual benefits, or to defect i.e., favouring individual benefits over the team's goal. Each participant collaborates with two robotic partners that adopt opposite strategies to play the game: one of them is an unconditional cooperator (the pro-social robot), and the other is an unconditional defector (the selfish robot). In a between-subjects design, we manipulated which of the two robots criticizes behaviours, which consists of condemning participants when they opt to defect, and it represents either an alignment or a misalignment of words and deeds by the robot. Two main findings should be highlighted (1) the misalignment of words and deeds may affect the level of discomfort perceived on a robotic partner; (2) the perception a human has of a robotic partner that criticizes him is not damaged as long as the robot displays an alignment of words and deeds.

Blind people rely on sighted peers and different assistive technologies to accomplish everyday tasks. In this paper, we explore how assistive robots can go beyond information-giving assistive technologies (e.g., screen readers) by physically collaborating with blind people. We first conducted a set of focus groups to assess how blind people perceive and envision robots. Results showed that, albeit having stereotypical concerns, participants conceive the integration of assistive robots in a broad range of everyday life scenarios and are welcoming of this type of technology. In a second study, we asked blind participants to collaborate with two versions of a robot in a Tangram assembly task: one robot would only provide static verbal instructions whereas the other would physically collaborate with participants and adjust the feedback to their performance. Results showed that active collaboration had a major influence on the successful performance of the task. Participants also reported higher perceived warmth, competence and usefulness when interacting with the physically assistive robot. Overall, we provide preliminary results on the usefulness of assistive robots and the possible role these can hold in fostering a higher degree of autonomy for blind people.

Providing social robots an internal model of emotions can help them guide their behaviour in a more humane manner by simulating the ability to feel empathy towards others. Furthermore, the growing interest in creating robots that are capable of collaborating with other humans in team settings provides an opportunity to explore another side of human emotion, namely, group-based emotions. This paper contributes with the first model on group-based emotions in social robotic partners. We defined a model of group-based emotions for social robots that allowed us to create two distinct robotic characters that express either individual or group-based emotions. This paper also contributes with a user study where two autonomous robots embedded the previous characters, and formed two human-robot teams to play a competitive game. Our results showed that participants perceived the robot that expresses group-based emotions as more likeable and attributed higher levels of group identification and group trust towards their teams, when compared to the robotic partner that expresses individual-based emotions.

This study investigated non-verbal behavior and socioemotional interactions in small-groups of humans and robots. Sixty-participants were involved in a group setting in which they were required to play a card game with another human and two robots (playing as partners or as opponents). The two robots displayed different goal orientations: a competitive robot (named Emys-) and a relationship-driven cooperative robot (named Glin+). Video recordings of the interactions were analyzed in three game play sessions. Eye gaze and socioemotional support behaviors were coded based on Bales» Interaction Process Analysis. Results indicated that gaze behavior towards partners was more frequently displayed to the relationship-driven robot than to the competitive robot and the human partners. In contrast, gaze towards opponents occurred more often towards the competitive robot than to the relationship-driven robot and the human opponents. Socioemotional support occurred more frequently towards partners than opponents, and was also displayed more often towards humans than towards robots. Moreover, in the sessions where the robots were opponents, participants provided more support to the competitive robot. This investigation in small groups of humans and robots provided evidence of different interaction patterns towards robots displaying distinct orientation goals, which can be useful in guiding the successful design of social robots.

In this paper, we study the influence of a handshake in the human emotional bond to a robot. In particular, we evaluate the human willingness to help a robot whether the robot first introduces itself to the human with or without a handshake. In the tested paradigm the robot and the human have to perform a joint task, but at a certain stage, the robot needs help to navigate through an obstacle. Without requesting explicit help from the human, the robot performs some attempts to navigate through the obstacle, suggesting to the human that it requires help. In a study with 45 participants, we measure the human's perceptions of the social robot Vizzy, comparing the handshake vs non-handshake conditions. In addition, we evaluate the influence of a handshake in the pro-social behaviour of helping it and the willingness to help it in the future. The results show that a handshake increases the perception of Warmth, Animacy, Likeability, and the tendency to help the robot more, by removing the obstacle.

In this video we present a social robotic player that is able to play a traditional card game in a social manner. The interaction takes place in a rich environment in which two teams of two players each compete to win the card game. Therefore, the robotic game player has a partner, and an opponent team of two other players. During each game, the robot explores both competitiveness with the opponent team and cooperation with its partner, conciliating the performance of players and the social dynamics that emerge during the game-play.

Robots are currently being developed to enter our lives and interact with us in different tasks. For humans to be able to have a positive experience of interaction with such robots, they need to trust them to some degree. In this paper, we present the development and evaluation of a social robot that was created to play a card game with humans, playing the role of a partner and opponent. This type of activity is especially important, since our target group is elderly people - a population that often suffers from social isolation. Moreover, the card game scenario can lead to the development of interesting trust dynamics during the interaction, in which the human that partners with the robot needs to trust it in order to succeed and win the game. The design of the robot's behavior and game dynamics was inspired in previous user-centered design studies in which elderly people played the same game. Our evaluation results show that the levels of trust differ according to the previous knowledge that players have of their partners. Thus, humans seem to significantly increase their trust level towards a robot they already know, whilst maintaining the same level of trust in a human that they also previously knew. Henceforth, this paper shows that trust is a multifaceted construct that develops differently for humans and robots.