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The relationship between artificial entities' human likeness and aesthetic preference is thought to be best modelled by an N -shaped cubic "uncanny valley" function, which however suffers from conceptual criticisms and lack of parsimony. Here it is argued that uncanniness effects may instead be modelled by a linear function of deviation moderated by perceptual specialization. The two models are compared in an experiment with five incrementally distorted face types (cartoon, CG, drawing, real, robot). Recognition performance for upright and inverted faces were used as a specialization measure. Specialization significantly moderated the linear effect of distortion on uncanniness, and could explain the data better than a conventional uncanny valley. The uncanny valley may thus be better understood as a moderated linear function of specialization sensitizing the uncanniness of deviating stimuli. This simpler yet more accurate model is compatible with neurocognitive theories and can explain uncanniness effects beyond the conventional uncanny valley. • Face realism affects both specialization and deviation sensitivity. • Specialization moderates the effect of deviation on uncanniness in faces. • This moderated linear function explains uncanniness better than a cubic "uncanny valley" model. • Parsimony, accuracy, generalizability, and plausibility of the moderation model over the uncanny valley are discussed. [ABSTRACT FROM AUTHOR]

Little is known about how children perceive, trust and learn from social robots compared to humans. The goal of this study was to compare a robot and a human agent in a selective trust task across different combinations of reliability (both reliable, only human reliable, or only robot reliable). 111 children, aged 3 to 6 years, participated in an online study where they viewed videos of a human and a robot labelling both familiar and novel objects. We found that, although children preferred to endorse a novel object label from the agent who previously labelled familiar objects correctly, when both the human and the robot were reliable they were biased more towards the robot. Their social evaluations also tended much more strongly towards a general robot preference. Children's conceptualisations of the agents making a mistake also differed, such that an unreliable human was selected as doing things on purpose, but not an unreliable robot. These findings suggest that children's perceptions of a robot's reliability are separate from their evaluation of its desirability as a social interaction partner and its perceived agency. Further, they indicate that a robot making a mistake does not necessarily reduce children's desire to interact with it as a social agent. • 3–6 year old children prefer a reliable robot over a reliable human. • Children evaluate robot competency separately to social and agency judgements. • Humans are more likely to be seen as making a mistake on purpose than a robot. [ABSTRACT FROM AUTHOR]

Avatars and social robots offer new opportunities for communication and raise questions about how trust is built and maintained in hybrid social interactions. We wonder what kind of trust people build with these technologies, especially where they are no longer simply tools but rather partners in interactions and affective exchanges involving vulnerability and reciprocity. Following the PRISMA guidelines, we conducted a systematic review on how trust in humans and technology can be shaped by social touch, which is the bodily contact occurring between two or more parties that express and share affective signals. Based on the n = 15 papers that meet the inclusion criteria, the evidence on the power of social touch to facilitate trust appears limited. Especially in the realm of technology-mediated interactions, mixed and inconclusive results emerge in different social contexts. Individual differences and neurophysiological correlates that could shed light on the effects between touch and trust are rarely investigated. Our positive proposal is that future studies should overcome the divisive conceptualisation of trustor and trustee, and rather explore the phenomenon of trust as a two-person bridge built in synergy between the parties. Outlining some key directions for future research, we discuss the extant solutions and applications of technology-mediated social touch, delving into the sensory and contextual factors that make it similar but different to unmediated social touch. We propose that if social touch were to be effective in promoting trust in specific technologies, this would have important consequences on various application domains such as telecommunication, healthcare, and education. • Trust in a specific technology is crucial when the technology is not only a tool but also a social partner. • Social touch has the power to make us feel connected to others and potentially help us build trust. • Evidence on the effects of mediated or unmediated social touch on trust is limited, mixed and inconclusive. • Future research on mediated interactions should delve into the sensory and contextual aspects of social touch to boost trust. • We need new ways of interacting through mediated social touch, tailored to the specificities of technology and human parties. [ABSTRACT FROM AUTHOR]

As social robots are increasingly designed with sophisticated simulations of human skills, it becomes essential to understand boundary conditions of people's engagement of them as mindful actors. The present paper reports a comprehensive secondary analysis of six studies (total N = 967) on the relationship between mind perception (evaluation of mental capacities) and mind ascription (explicit assignment of a mind-having status) when people consider a humanoid robot in different scenarios. Results indicate there is a context-independent, moderate link between perceptions of affective mental capacity (i.e., ability to feel emotion) and explicit mind ascription. We further found hints for a weak relationship between perceptions of reality-interaction capacity (i.e., sensory and agentic abilities) and decisions to ascribe mind that may need larger samples in order to be validated. Perceptions of social-moral capacities (i.e., evaluations of people and goals) were not a significant predictor of mind ascription. Overall, these findings highlight the pivotal role played by robots' display of affective engagement with the world for the acceptance of robots as mindful "beings" in human spheres. • Mind perception in robots does not mean people assign them a mindful being status. • Dimensionality of mind perception allows for various drivers of mind ascription. • Six studies uniformly show that perceived affective capacity is the primary correlate. • Perceptions of basic but not higher-order agency may be a secondary correlate. • Long-established position of denied mindfulness in robots is called into question. [ABSTRACT FROM AUTHOR]

In two experiments centered around trust dynamics in human–robot interaction, we explored the interplay between attribute-based characteristic of robots (i.e., anthropomorphism and type of failure) and trust attitude, perceived reliability, as well as trust behavior. In general, trust attitude is considered to be one of the most important factors for successful collaboration. However, although previous research has shown that performance and attribute-based characteristics of robots lead to changes in trust attitudes, the question remains whether this is also linked to behavioral adaptations. To investigate this relationship, participants collaborated with robots via voice commands that failed. In the first experiment, participants worked with either an anthropomorphic or technical robot. In the second experiment, all participants worked with the technical robot, which made a failure in either information acquisition/processing or action implementation. Participants trusted the technical robot significantly more than the anthropomorphic one. Moreover, failures in information acquisition/processing seemed to lead to more trust dissolution than failures in action implementation. In both experiments, the dynamics of trust attitudes as a function of interaction experience were shown, in particular, trust dissolution due to failure. However, there was no evidence of behavioral adaptation following a failure experience. In general, the effects on the attitudinal level did not clearly translate into behavioral adaptations. For trust attitude, purely decorative anthropomorphic robot design and failures related to the cognitive abilities of robots should be avoided. • In task-related settings, anthropomorphic robot appearance reduces trust compared to technical appearance. • Anthropomorphic appearance does not result in greater forgiveness than technical appearance. • The type of failure seems to be relevant for the degree of trust dissolution. • Trust attitude toward the robot seems to be not directly connected to behavior. [ABSTRACT FROM AUTHOR]

Android robots that resemble humans closely, but not perfectly, can provoke negative feelings of dislike and eeriness in humans (the "Uncanny Valley" effect). We investigated whether category confusion between the perceptual categories of "robot" and "human" contributes to Uncanny Valley aversion. Using a novel, validated corpus of 182 images of real robot and human faces, we precisely estimated the shape of the Uncanny Valley and the location of the perceived robot/human boundary. To implicitly measure confusion, we tracked 358 participants' mouse trajectories as they categorized the faces. We observed a clear Uncanny Valley, though with some interesting differences from standard theoretical predictions; the initial apex of likability for highly mechanical robots indicated that these robots were still moderately dislikable, and the Uncanny Valley itself was positioned closer to the mechanical than to the human-like end of the spectrum. We also observed a pattern of categorization suggesting that humans do perceive a categorical robot/human boundary. Yet in contrast to predictions of the category confusion mechanism hypothesis, the locations of the Uncanny Valley and of the category boundary did not coincide, and mediation analyses further failed to support a mechanistic role of category confusion. These results suggest category confusion does not explain the Uncanny Valley effect. • Category confusion aversion has been suggested to explain Uncanny Valley (UV) reactions. • We precisely estimated the UV's shape and the robot/human boundary location. • The robot/human category boundary existed but was distant from the UV itself. • We found that category confusion is not a viable explanation for the UV effect. [ABSTRACT FROM AUTHOR]

The uncanny valley hypothesis suggests that a high (but not perfect) human-likeness of robots is associated with feelings of eeriness. We distinguished between experience and agency as psychological representations of human-likeness. In four online experiments, vignettes about a new generation of robots were presented. The results indicate that a robot's capacity to feel (experience) elicits stronger feelings of eeriness than a robot's capacity to plan ahead and to exert self-control (agency, Experiment 1A), which elicits more eeriness than a robot without mind (robot as tool, Experiments 1A and 1B). This effect was attenuated when the robot was introduced to operate in a nursing environment (Experiment 2). A robot's ascribed gender did not influence the difference between the eeriness of robots introduced as experiencers, agents, or tools (Experiment 3). Additional analyses yielded some evidence for a non-linear (quadratic) effect of participants' age on the robot mind effects. • The uncanny valley hypothesis and the mind perception literature served as theoretical frameworks. • Experience and agency of a humanoid robot were manipulated in four experiments. • A robot with experience or agency elicited more eeriness than a robot without mind. • The context of application (unspecified vs. nursing) was a significant moderator. • The influence of the robot's gender, and participants' age was further examined. [ABSTRACT FROM AUTHOR]

This work proposed the development of a game with a robot, built with Lego pieces, to make the rehabilitation treatment of children with Cerebral Palsy more effective. The aim of the game is to stimulate the motor coordination, cognition, memory and attention level of children, and to complement the activities carried out by the Neuropsychomotor Rehabilitation Program of the Nucleus of Occupational Therapy of NAMI (Nucleus of Integrated Medical Attention) of UNIFOR (The University of Fortaleza, Ceará, Brazil). The interaction between the child and the robot takes place through an Android remote control app installed on a smartphone. To validate the proposed method, five children were submitted to various sessions of activities with the robot, over a two-month period. A brain wave sensor, responsible for measuring the level of attention during the activities was employed. In addition, a questionnaire was applied to the professionals and parents of the children, in order to validate the tool proposed here. After analyzing the results, it was concluded that the robot is an effective and very promising complementary tool to assist in the rehabilitation treatment of children with Cerebral Palsy. • Novel alternative treatments to improve the cognitive and motor skills of children with CP. • accelerate the rehabilitation process through motor and cognitive activities inherent in a fun serious game. • Stimulation the motor coordination, cognition, memory and attention level of children. • Proposed approche is very promising to treat children with CP in activities that stimulate motor and cognition. [ABSTRACT FROM AUTHOR]

This study examined whether a non-human robot audience can elicit a stress response in human participants. A 90-min experimental laboratory session based on the Trier Social Stress Test (TSST) using a pre-recorded robot audience, was presented as a live on-screen simulation. Nineteen participants (female = 16) aged 21–57 years (M = 29.74) underwent a 10-min mock interview and mathematics task in front of the robot audience. Salivary cortisol was assessed at 10-min before and immediately prior to the start of the stress test, and +10-, +30- and +40-min after the start of the test. Heart rate was assessed 20 min before, at 5 min into and 40-min after the test. Perceived stress and trait coping responses were provided at entry and participants were interviewed post task about their subjective experience. Significant increases in salivary cortisol and heart rate were observed over time with no significant interactions by participant subjective report. Coping responses including active coping and planning showed significant relationships with cortisol and heart rate reactivity and recovery. Until now, a non-human robot audience has not been used in a social stress testing paradigm. This methodology offers an innovative application with potential for further in-depth evaluation of stress reactivity and adaptation. • A non-human robot audience can induce cortisol and heart rate stress responses. • Findings consider social judgement in human reaction to robot evaluation. • Objective and subjective accounts of stress experience not consistently concordant. • Coping style may influence stress response and adaptation to robot stress panel. [ABSTRACT FROM AUTHOR]

Autonomy is becoming increasingly integrated into everyday life. For humans to fully realize the benefits of working alongside autonomy, appropriate trust toward autonomous partners will be necessary. However, research is needed to determine how humans respond to autonomous partners when they behave (un)expectedly. Thus, a series of studies were designed to investigate the effect of framed social intent of an autonomous teammate (Study 1), their unstated behavioral manifestations (Study 2), and the interaction of these variables (Study 3) on participants' trustworthiness perceptions, reliance intentions, and trust behaviors. Participants were to imagine themselves partnering with an autonomous teammate in a team-based, gamified collaboration. Key innovations in this task involved role-based vulnerability (necessitating clear expectations regarding one's stated social intent) and teammate interdependence. Across studies, framed social intent and observable behaviors of an autonomous agent were manipulated. Results demonstrated robust effects of said manipulations, with interactions demonstrating the nuance of (un)met expectations on criteria. We conclude by offering future research and design suggestions aimed at enhancing human-autonomy interactions. • Agents framed as benevolent were perceived as more trustworthy and were trusted more than those framed as self-interested. • Agent demonstrating benevolent behavior were perceived as more trustworthy and were trusted more than self-interested agents. • The interaction of frame and behavior, and the importance of human expectations of autonomous agents being met, is discussed. [ABSTRACT FROM AUTHOR]

Algorithm aversion, which is a widely observed phenomenon, suggests that customers prefer human advisors over robo-advisors in automated wealth management. Studies have shown that prevention-focused (vs. promotion-focused) customers refuse high-tech products; therefore, algorithm aversion should be more pronounced among them. However, our findings challenge this notion. Drawing on the regulatory focus theory, through four studies, we discovered that (1) customers' mindset was relatively more prevention-focused when using robo-advisors and relatively more promotion-focused when using human advisors; (2) perceived flexibility mediated this effect; and (3) the algorithm aversion effects existed in automated wealth management, but vanished among prevention-focused customers because of the fit effects. Our findings identified a psychological boundary condition of algorithm aversion, provided a novel antecedent variable of regulatory focus, and provided managerial implications for robo-advisory firms' market segmentation strategies. • Challenging the notion that prevention-focused (vs. promotion-focused) customers refuse high-tech products. • Regulatory focus moderates algorithm aversion effects in automated wealth management. • Customers' mindsets are more prevention focused when using robo-advisors (vs. human advisors) in investment. • Algorithm aversion effects vanish among prevention-focused customers. [ABSTRACT FROM AUTHOR]

Reasons of reactions towards artificial intelligence (AI) performing hedonic tasks invites attention. This research argues that the reference of comparison to assess AI's suitability for the task shifts from machine schema to human schema as the hedonic value of the task increases, leading to the decrease in perceived humanlikeness, perceived warmth, and support for the AI, subsequently. Four studies, including a big data study on GitHub and three experiments, have shown that people are less supportive of AI and its creators when AI performs highly (vs low) hedonic tasks. This effect is mediated by the perceived humanlikeness of AI, since it affects AI's perceived warmth in a way that decreasing perceived humanlikeness when AI is assigned to the tasks with high (vs low) hedonic values decreases the perceived warmth of the AI. Decreased perceived warmth, in turn, lowers people's support for the AI and its creators. This serial mediation mechanism remains robust when AI's baseline humanlikeness increases, when the hedonic value of AI's method of performing the task, rather than the task itself is manipulated, and when the perceived competence and fairness are tested as alternative paths in parallel. • AI receives less support in tasks with high (vs low) hedonic values and perceived humanlikeness mediates this mechanism. • AI's perceived humanlikeness decreases when it is assigned to perform tasks with high (vs low) hedonic values. • Decreased humanlikeness decreases perceived warmth of the AI both of which mediates this mechanism in a serial relationship. • AI's assignment to highly hedonic tasks causes an agent-task incongruency. • Reference of comparison for AI's suitability shifts to human schema as the hedonic value of the task increases. [ABSTRACT FROM AUTHOR]

COVID-19 has changed many aspects of the hospitality and tourism industry, including technology-oriented and contactless solutions. Despite the increasing number of service companies using robots on their premises, most of the previous attempts and practices of adoption have remained unsuccessful. Prior research hints that socioeconomic factors could influence the successful adoption of these emerging technologies. Nevertheless, these studies ignore the role of profile factors and assume a homogenous response to using robots in service operations during the pandemic. Based on the theory of diffusion of innovation and a sample of 525 participants, this study investigates the differences in customers' attitudes, their level of involvement, and optimism for service robots as well as their intentions to use service robots in the five main areas of hotel operations (front desk, concierge, housekeeping, room service, and food and beverage) based on five profile factors (age, gender, income level, education, and purpose of trip). MANOVA tests show significant differences in all variables based on demographic factors; male, younger, more educated, higher income, and leisure travelers show more positive attitudes, higher involvement, optimism, and intention to use service robots across various hotel departments. In particular, mean scores were found to be smaller for the traditionally human-oriented functional areas of the hotel operations. We also clustered the participants based on their level of comfort and optimism about using service robots in hotels. Given the rapid changes in the service industry and the increasing adoption of service robots, this paper adds a much-needed contribution to the ongoing research on service robots in the service industry by investigating the impact of profile factors on guests' behavior towards service robots. • Identifies the primary factors of robot adoption in service settings. • Creates a human-robot interaction-based profile of customers. • Provides a deep analysis of human behavior based on socioeconomic factors. • Clusters the customers based on their level of comfort and optimism in service robots. • Provides department-specific insights and strategies. [ABSTRACT FROM AUTHOR]

Social robots have been increasingly involved in our daily lives and provide a new environment for children's growth. The current study aimed to examine how children with and without Autism Spectrum Disorders (ASD) learned complex social rules from a social robot through distrust and deception games. Twenty children with ASD between the ages of 5–8 and 20 typically-developing (TD) peers whose age and IQ were matched participated in distrust and deception tasks along with an interview about their perception of the human-likeness of the robot. The results demonstrated that: 1) children with ASD were slower to learn to and less likely to distrust and deceive a social robot than TD children and 2) children with ASD who perceived the robot to appear more human-like had more difficulty in learning to distrust the robot. Besides, by comparing to a previous study the results showed that children with ASD appeared to have more difficulty in learning to distrust a human compared to a robot, particularly in the early phase of learning. Overall, our study verified that social robots could facilitate children with ASD's learning of some social rules and showed that children's perception of the robot plays an important role in their social learning, which provides insights on robot design and its clinical applications in ASD intervention. • We examined how children with autism distrusted and deceived a social robot. • Children with autism show poorer distrust and deception performance than controls. • Perceived human-likeness of robot correlates with children's trust to robot. • Children with autism learn better to distrust a robot than a person. [ABSTRACT FROM AUTHOR]

Robotic devices for older adults are becoming a reality. New robots are being introduced for the growing subpopulation of healthy older adults, with an emphasis on supporting the positive aspects of aging. In order to inform the design and implementation of such robots, the relevant needs and concerns of this population should be studied, mapped, and translated into recommendations. We present a qualitative study of thirty cognitively-intact older adults, evaluating their attitudes and emotional reactions towards different types of home robotic devices. Interview analysis of participants reactions to videos of six devices uncovered four user needs that can be threatened by the introduction of home robots: the need for independence, the need for control, the fear of being replaced, and the need for authenticity. Furthermore, results reveal that cognitively-intact older adults are willing to adopt robotic devices into their homes, contingent upon their preferences and concerns being addressed. We provide recommendations regarding how researchers and designers of home robots can better address the user needs of healthy older adults by leveraging aspects of the robot's function, speech, appearance, size, proactivity, and mobility. • Older adults' attitudes and emotional reactions toward robotic devices were evaluated. • Specific robot features related to appearance, behavior & function affect acceptance. • Older adults' user needs should be addressed in the robot's design. • Concrete design guidelines for robotic devices targeting older adults are suggested. [ABSTRACT FROM AUTHOR]

Abstract As many post-industrial societies are rapidly ageing, intelligent and innovative solutions from the technology side are sought to ensure that welfare services continue in the future. Both social and nonsocial assistive robots are considered as solutions. To ensure the successful implementation of new technology, it is essential to understand the factors that influence the user's decision to accept or reject technology. The aim of this study was to understand the association between robot use self-efficacy and acceptance of robots. Acceptance of humanoid, pet, lifting, and telepresence robots were studied among care work staff (N = 3800). Analyses were based on linear regression analysis. The results showed that robot use self-efficacy is associated with the acceptance to use humanoid, pet, and telepresence robots. The strongest connection was found between robot use self-efficacy and the functional and social acceptance of a humanoid robot. General self-efficacy was not associated with any of the robot types studied in the final models. Furthermore, no interaction effect was found between general self-efficacy and robot use self-efficacy. The results underline that psychological processes on acceptance of robots vary between different types of robots. The results imply that robot use self-efficacy is important for understanding acceptance and implementation of robots. The explanatory power of self-efficacy is better when it is tied to a specific matter such as the use of care robots. Highlights • Robot use self-efficacy was associated with the acceptance to use humanoid, pet, and telepresence robots. • General self-efficacy was not associated with any of the robot types. • No interaction effect was found between general self-efficacy and robot use self-efficacy. • Psychological processes on acceptance of robots vary between different types of robots. • The explanatory power of self-efficacy is better when it is tied to a concrete matter such as the use of care robots. [ABSTRACT FROM AUTHOR]

Abstract This study examines the impact of grouping by gender and group roles on robotics performance, computational thinking skills, and learning motivation towards computer programming. One hundred ninety-one students in fourth and fifth grade completed the project. LEGO Mindstorms EV3 robotics were used to compose and program music in groups of three to four students. The robotics project was completed over the course of fourteen weeks for 1 h each week. Gender-structured groups of all female, all male and mixed female and male were randomly assigned in each class. All groups in participating six classrooms were assigned one of three group roles implementation, which were fixed, rotating and no role. This study is significant towards identifying group scaffolds and supports that can produce benefits for all students in robotic activities. Results indicated that group roles matter when students are working on collaborative robotics projects. Three different implementations of group roles in robotics activities demonstrated an impact on robotics performance scores. Gender composition of the group did not impact groups' robotics performance. Group roles also impacted student computational thinking skills, while gender composition of the group still demonstrated no significant difference. Finally, while group roles demonstrated a difference in learning motivation towards computer programming, gender composition demonstrated no difference in learning motivation towards computer programming. Highlights • Group composition matters when students are working on collaborative robotics projects. • Group roles have impacts on student computational thinking skills and robotics performances. • Group roles have no impact on learning motivation towards computer programming. • Gender did not impact groups' robotics performance and computational thinking skills. • Gender did not impact learning motivation towards computer programming. [ABSTRACT FROM AUTHOR]

Abstract Are students willing to accept robotic support for learning when their attitudes toward educational robots are moderate? Probably not, as evidence from psychological research has suggested that attitudes predict how people will behave toward an attitude object. Consequently, a negative view of robots could represent a strong barrier to the deployment of robots in educational environments. Attitude change might facilitate a smooth introduction of educational robots into learning settings. Thus, the present research builds on the fact that actively including end users in the prototyping process of a robot might increase positive attitudes toward it. Indeed, our research is among the first works which demonstratethat participation in the prototyping process of an educational robot positively affected attitudes toward educational robots in general and significantly reduced educational robot anxiety. However, students' behavioral intentions toward educational robots were not influenced by participation. These findings raise intriguing questions regarding the relevance of user involvement in the development of robots. Therefore, the discussion focuses on how to improve this process and how user involvement in robot design processes provides a valuable contribution to the acceptance of social robots in everyday life. Highlights • Attitude change by user participation in a robot prototyping process is proposed. • Positive attitudes toward robots increased when participating in the design task. • Robot anxiety decreased when participating in the design process. • People's behavioral intentions, however, were not significantly affected. [ABSTRACT FROM AUTHOR]

Abstract The current study builds upon our previous research on the human-to-human interaction script, which suggests that people expect to interact with other humans when encountering an initial interaction. This expectation impacts the initial impressions people have when interacting with social robots. The current experiment examined how short interactions might change those initial impressions. Participants were less uncertain and perceived greater social presence after a single brief interaction with a humanoid social robot. Social presence decreased after a short interaction with a human. These data suggest that initial impressions based on the human-to-human interaction script may impact actual interaction and the impressions that result from it. Open-ended responses suggest the potential for hyperpersonal communication in human-robot interaction. These findings are further discussed, as are limitations and directions for future research. The paper concludes with an agenda for applying constructivist interpersonal communication frameworks to human-robot interaction studies. Highlights • After interacting with a social robot, perceptions of uncertainty decreased. • Social presence increased after initial interactions with a robot. • Data suggests that the human-human interaction script may impact actual interaction. • A constructivist research paradigm in human-machine communication if forwarded. [ABSTRACT FROM AUTHOR]

Abstract The current study investigates the effectiveness of sequential-request strategies that robots may employ to persuade humans. Specifically, this study focuses on the foot-in-the-door technique, whereby a small request is made first and is then followed up with a larger, actual target request. Participants played a trivia game with an ostensibly autonomous robot teammate. At the end of the game, the robot asked participants to complete a series of pattern recognition tasks, either by requesting directly or by starting with a small request, then following with a larger request. The results demonstrated a strong foot-in-the-door effect, suggesting a robot's potential to persuade humans using verbal message strategies. The robot's performance or perceived credibility did not influence compliance. This robotic foot-in-the-door effect provides some important practical implications for designers and developers who aim to enhance the persuasive outcomes of human-robot interaction. Highlights • We examined the sequential-request strategies used by robots to persuade humans. • A small request was made first and then followed up with a larger actual request. • The results demonstrated a strong robotic foot-in-the-door effect. • This effect was independent from performance or source credibility. [ABSTRACT FROM AUTHOR]

Abstract This study employs the Computers are Social Actors (CASA) paradigm to extend the predictions of Social Identity Theory (SIT) to human-robot interaction (HRI) in the context of instructional communication. SIT posits that individuals gain a sense of personal worth from the groups with which they identify. Previous research has demonstrated that age group identification is meaningful to individuals' self-concepts. Results demonstrated that higher age identified students rated the older A.I. voice instructor (representing an out-group member) higher for credibility and social presence and reported more motivation to learn than those students with low age identification. Implications are discussed for SIT and design features of computerized voices. Highlights • Age identity matters for evaluations of A.I. voice. • Higher age identified students rated the older A.I. voice higher for credibility. • Higher age identified students rated the A.I. voice higher for social presence and reported more motivation to learn. • Implications are discussed for Human-Robot interaction and design. [ABSTRACT FROM AUTHOR]

Abstract During weather risks and crises, emergency managers and practitioners are often tasked with disseminating messages to individuals or groups of people who are located in a variety of hard-to-reach areas. Social robotics may serve as a useful delivery medium for disseminating some of these messages, if a group is located in an area that is hard to reach. This exploratory study investigated the information retention and behavioral intentions after being disseminated a mock weather risk message. The results provide support for delivery platform being important to consider when disseminating a risk message, such that novel technologies may actually lead to lower retention of message content. Discussion is centered around the implications of using novel technology to communicate risk messages. Highlights • Delivery platform is important to consider when delivering risk messages. • Novel technology may distract individuals from retaining weather messages. • Language structure did not influence message action or information retention. [ABSTRACT FROM AUTHOR]

Abstract With the rapid rise in robot presence in a variety of life domains, understanding how robots influence people's emotions during human-robot interactions is important for ensuring their acceptance in society. Mental health care, in particular, is considered the field in which robotics technology will bring the most dramatic changes in the near future. In this context, the present study sought to determine whether a brief cognitive assessment conducted by a robot elicited different interaction-related emotional processes than a traditional assessment conducted by an expert clinician. A non-clinical sample of 29 young adults (17 females; M = 24.5, SD = 2.3 years) were asked to complete two cognitive tasks twice, in counterbalanced order, once administered by an expert clinician and once by an autonomous humanoid robot. Self-reported measures of affective states and assessment of physiological arousal did not reveal any difference in emotional processes between human-human and human-robot interactions. Similarly, cognitive performances and workload did not differ across conditions. Analysis of non-verbal behaviour, however, showed that participants spent more time looking at the robot (d = 1.3) and made fewer gaze aversions (d = 1.3) in interacting with the robot than with the human examiner. We argue that, far from being a trivial 'cosmetic change', using a social robot in place of traditional testing could be a potential way to open up the development of a new generation of tests for brief cognitive assessment. Highlights • A neglected area of research is the use of social robots for brief cognitive assessment. • People's emotional reactions towards a robot and a human examiner did not differ. • Gaze patterns might be considered behavioural markers for assessing cognitive load. • Humanoid robots may be a way to open up the development of new brief cognitive tests. [ABSTRACT FROM AUTHOR]

Abstract In the present study, the effects of procedural justice (fair or unfair) and the type of decision agent (human, robot, or computer) on employee behavior and attitudes (e.g., job satisfaction, organizational citizenship behavior, or counterproductive work behaviors) were examined. It was predicted that the type of decision agent (or the source of justice) would moderate the relationship between procedural justice and employee behavior and attitudes, with the relationship being strongest when the decision agent is a human team leader, medium when the decision agent is a humanoid robot, and weakest when the agent is a computer system. This research question was investigated with a between-subjects design in two experiments (N 1 = 149 and N 2 = 145) that displayed two different decision situations in organizations (allocation of new tasks and allocation of further vocational trainings). Results of both studies showed significant effects of procedural justice on employee behavior and attitudes, confirming the importance of procedural justice at the workplace for both human and system decision agents. Furthermore, both studies failed to verify any interaction effects of procedural justice and the decision agent. This further emphasizes the importance of procedural justice in decision situations because there is no difference in reactions to procedural justice of human or system decisions. Limitations and implications for future research and the integration of justice and human–machine interaction research are discussed. Highlights • Procedural justice fosters beneficial attitudes and behaviors in organizations. • Procedural justice diminishes harmful behaviors in organizations. • Type of decision agent (human/intelligent system) does not moderate justice effects. • Procedural justice is important, no matter who has made the decision. [ABSTRACT FROM AUTHOR]

People can react negatively to persuasive attempts experiencing reactance, which gives rise to negative feelings and thoughts and may reduce compliance. This research examines social responses towards persuasive social agents. We present a laboratory experiment which assessed reactance and compliance to persuasive attempts delivered by an artificial (non-robotic) social agent, a social robot with minimal social cues (human-like face with speech output and blinking eyes), and a social robot with enhanced social cues (human-like face with head movement, facial expression, affective intonation of speech output). Our results suggest that a social robot presenting more social cues will cause higher reactance and this effect is stronger when the user feels involved in the task at hand. [ABSTRACT FROM AUTHOR]

Research on Human-Technology Interactions revealed that, under certain conditions, people instinctively interact with social robots in ways comparable to Human–Human Interactions. Indeed, people apply social perception schemas and attribute a mind to social robots, especially when they present anthropomorphic characteristics. Furthermore, under certain conditions, anthropomorphic social robots are awarded with moral consideration and participate to moral dyads. Thus, anthropomorphism facilitates social robots integration in people's lives. However, what is still unknown is whether adopting social schemas with social robots, in turn, affects how individuals perceive and interact with other people. To fill this gap, we experimentally investigated whether the type of mind attributed to anthropomorphic social robot, then, complementary influences the empathy towards a person in trouble. Participants (n = 269) interacted (vs. did not interact) through a chatbot with a highly (vs. lowly) anthropomorphic social robot, evaluated it on mind dimensions and, finally, expressed their empathy towards a person. Results demonstrated that anthropomorphism fosters the attribution of agency (anthropomorphic appearance and interaction through chatbot) and experience (anthropomorphic appearance only), which, in turn, significantly, but in opposite directions, affected empathy towards the social target. Implications and future research directions are outlined. • Mind attribution to social robots activates dyadic completion between social robots and human beings. • Attribution of agency to anthropomorphic social robot affects the empathy towards human being positively. • Attribution of experience to anthropomorphic social robot affects the empathy towards human being negatively. [ABSTRACT FROM AUTHOR]

Robots and computer graphics characters that resemble humans but are not perfectly human-like tend to evoke negative feelings in human observers, which is known as the "uncanny valley effect." In this study, we used a recent artificial neural network called Contrastive Language-Image Pre-training (CLIP) that learns visual concepts from natural language supervision as a visual sentiment model for humans to examine the semantic match between images with graded manipulation of human-likeness and words used in previous studies to describe the uncanny valley effect. Our results showed that CLIP estimated the matching of words of negative valence to be maximal at the midpoint of the transition from a human face to other objects, thereby indicating the signature of the uncanny valley effect. Our findings suggest that visual features characteristic to the conflicts of visual cues, particularly cues related to human faces, are associated with negative verbal expressions in our everyday experiences, and CLIP learned such an association from the training datasets. Our study is a step toward exploring how visual cues are related to human observers' sentiment using a novel psychological platform, that is, an artificial neural network. [Display omitted] • We examined the semantic matching of morphed images to sentiment words using an artificial neural network. • The neural network exhibited the uncanny valley-like effect depending on the human likeness of the images. • Visual features characteristic to cue conflicts were associated with words of negative valence in the neural network. • The observed uncanny valley-like effect also exhibited modulation by a conspecific factor. [ABSTRACT FROM AUTHOR]

Service robots (SRs) are fast becoming the source of automated service delivery processes and personalized frontline customer experiences in service firms. This study investigates the impact of customers' emotional state on how they evaluate service experiences after interacting with an SR, which remains underexplored. Drawing on the theory of constructed emotion and social sharing of emotions, it conducts three online scenario-based experiments. Study 1 shows that customers in a neutral emotional state are more satisfied with the service provided by SRs than are those in a negative emotional state. The mechanisms underlying this dissatisfaction are perceived relatedness and perceived appropriateness, as shown by Study 2. Study 3 demonstrates how SRs' sympathetic capabilities moderate this mediating relationship. The findings were consistent across different emotion manipulation methods, negative emotional states, and sources of emotional states. Given the increasing prominence of SRs on organizational frontlines, this study has numerous theoretical implications for SRs' interaction with emotional customers and practical implications for employing SRs. • Customers in a negative emotional state require social-emotional and instrumental support. • Customers in a neutral emotional state require only instrumental support. • Customers in a neutral emotional state enjoy services by service robots more than those in a negative emotional state. • Perceived relatedness and appropriateness mediate the impact of customers' emotional state on service satisfaction. • Sympathetic skills of service robots moderate the mediation of perceived relatedness and perceived appropriateness. [ABSTRACT FROM AUTHOR]

Recent years have seen 360-degree virtual reality (VR) being used as a valuable tool in communicating corporate social responsibility (CSR) campaigns. Built upon the wealth of literature on stimulus–organism–response (S–O–R) theory, this study proposed to test a model integrating perceived control of the 360-degree CSR VR technology, telepresence, engagement with VR 360-degree video (VR engagement), CSR advocacy, and purchase intentions. To that end, a nationally representative sample was recruited for a survey that exposed participants to a digital CSR campaign that uses 360-degree VR to increase mental health awareness. Results showed a significant association between participants' perceived control over the VR 360-degree CSR campaign and telepresence as well as their engagement with the VR 360-degree video. Moreover, telepresence and VR engagement were significant mediators in predicting consumers' willingness to promote social initiatives (CSR advocacy) and purchase intentions. Theoretical and practical implications of the study were discussed. • An integrated model was tested about consumers' responses to VR CSR videos. • Perceived control over the VR video is a crucial predictor in VR CSR communication. • Telepresence and VR engagement are significant mediators in predicting CSR advocacy. • CSR advocacy positively affects consumers' final purchase decisions. [ABSTRACT FROM AUTHOR]

Social robots are designed to interact, collaborate, and work with people, engaging them at an interpersonal and socio-affective level. The goal directed model was used to study the role of socio-cognitive, affective (anticipated emotions), and motivational (behavioral desire) factors of the intention to work with social robots in the near future. The effects of robots' perceived warmth and competence on components of the goal directed model are explored as well as the effects of social robots' design (machinelike vs. humanoid vs . humanlike). Results show that the goal directed model accounts for a considerable amount of the explained variance of behavioral intention, underlining the importance of affective and motivational factors, in the intention to work with a social robot. The role of robots' perceived warmth and competence was also confirmed. Results for robot design were inconclusive. [ABSTRACT FROM AUTHOR]

The urgent pressure on healthcare increases the need for understanding how new technology such as social robots may offer solutions. Many healthcare situations are emotionally charged, which likely affects people's perceptions of such robots in healthcare contexts. Thus far however, little attention has been paid to how people's prior emotions may influence their perceptions of the robot. Based on emotional appraisal theories and prior research, we assume that particularly emotional coping appraisals would influence healthcare-robot perceptions. Additionally, we tested effects of actual coping through the use of emotion-focused and problem-focused coping strategies. Hypotheses were tested in a 2 (sad vs. angry) x 2 (hard-to-cope-with vs. easy-to-cope-with) between-subjects experiment, also including a control group. Results ( N  = 132; age range 18–36) showed that manipulated coping potential indirectly affected perceptions of a healthcare robot via the appraisal of coping potential. Furthermore, positive emotion-focused coping affected perceptions of a healthcare robot positively. Thus, people's healthcare-robot perceptions were affected by how they cope or how they think they can cope with their emotions, rather than by the emotions as such. [ABSTRACT FROM AUTHOR]

Social robots are foreseen to be a growing category of assistive devices for baby boomers in helping them live independently at home and in good health for longer. Artificial intelligence and speech recognition are making natural language user interfaces possible. Yet voices of social robots could influence users' preferences and perceptions in ways that have not been widely explored yet, let alone in Chinese-speaking context. A quantitative study was conducted to probe what voice characteristics of social robots baby boomers may prefer and what personality traits they would associate with various pitch, speech rate, and intonation in Mandarin. While the findings coincide with previous research in that female, extroverted voices were preferred by most participants, many individual differences remain, which could be attributed to differences in demographics, lifestyles, and personality traits. This study contributes to design decisions that would take individual differences into consideration. Social robots that could learn and adapt to people's preferences, perceptions, as well as the tasks at hand may fare better than a one-size-fits-all approach. We believe that voice user interfaces will play a key role in elderly people's initial acceptance and continuing engagement of social robots. [ABSTRACT FROM AUTHOR]

The design and use of social robots addressed to the children population is a growing research field. The understanding of how the children react, or what are their preferences towards a robot with different styles of interaction is an important aspect to maximise the construction of a social bond between the robot and the child. In this paper we describe an experiment to assess these affective reactions and preferences based on an age-based stratification. A Wizard-Of-Oz scenario was used to design a playing mission where the child guides the robot, via voice commands, through a maze while collecting sweets and avoiding obstacles. Every participant interacted with two robots during the session. Two types of personalities were modelled in the robots with the same physical appearance: the agreeableness, and its opposite, disagreeableness personality trait. A total of 174 children between 6 and 11 years old took part in the experiment. The data about the affective reactions and preferences of the children towards the robots were collected through a multiple choice questionnaire. Significative statistical differences based on the age were found in the self-reported information provided by the children. These differences were noticeable in the youngest children (aged 6–7) with respect to the rest of the participants. [ABSTRACT FROM AUTHOR]

Today it is almost impossible to spend a single day without depending on an information system, a computer or any other form of computation. Though the starting barrier is low, fundamental concepts are still required in order to manage the technicalities of the engineering environment and everyday computational systems. In 1967, Logo proposed to teach abstract programming concepts by providing a set of functions that had intuitive, visible effects over a robotic Turtle . LOGO was a success, but the robots quickly migrated into computer simulations. From LOGO, many followed. Scratch and Lego Mindstorm are some of the most notorious examples. Both introduced graphical block-based programming interfaces. We propose to bring back the powerful ideas behind LOGO by updating it with state of the art technologies. Phogo combines Python, Arduino and 3D printing into a low cost robot that is easy to build and control. The robot has a pen to draw shapes and can be commanded from a computer via a wireless link that is transparent to the students. The use of a physical robot can make programming more accessible for students with disabilities. The open and maker philosophies behind Phogo makes it more interesting as students will be able to access and study the electronic components. The textual programing language can be a long life companion for the students. In this work we discuss LOGO and other projects inspired by it, and we also share the methodology and design decisions behind Phogo, the results of its application in a workshop and the improvements we are currently developing. [ABSTRACT FROM AUTHOR]

In the future, robots may live with users as long-term companions, thus it is important that some sort of attachment relationship develop between humans and agents. Man's best friend the dog provides a model for investigating what makes a heterospecific companion a lovable social partner. Thus, we studied people's attitudes toward dogs and robots comparatively, with a special focus on those features in dogs that cause people to accept them in their homes and love them. Additionally, we explored from what kind of behaviors people infer these qualities. We found that people's attitude toward robots is much more negative than towards dogs. Having emotions, personality and showing attachment were the most frequently reported advantages of dogs. Respondents showed high agreement about the behavioral manifestation of these qualities, which are necessary for engineers to be able to implement such advantages into the social robots' programs. Based on our results, in the future roboticists may supply social robots with these preferred qualities, which will aid in the designing of successful social robots. [ABSTRACT FROM AUTHOR]

Social robots have been and are currently being used in many projects, research initiatives and experiments, but we know relatively little about them compared to humans when performing a social task such as teaching. Using an experiment in which a robot and a human teacher were used for teaching computational concepts to a group of K-12 students, the main goal of this paper is not to analyze the scores obtained in the post-test performed, but to focus on the students' attitudes towards robots. In order to do this, a version of the NARS and RAS questionnaires, adapted for children, was used. The analysis of the results of these questionnaires considers differences between age groups and students lectured by a robot vs. a human teacher. We conclude that age is the main factor that affects students’ attitudes towards robots, although we also found other differences between the robot and the human teacher group. [ABSTRACT FROM AUTHOR]

Humans can fulfill their social needs with fictional and non-living entities that act as social surrogates. Though recent research demonstrates that social surrogates have beneficial effects on the individual similar to human relations, it is unclear whether surrogates can also cause similar harm to humans through social rejection. After playing a game of connect-4 with a human-sized robot, participants were informed by the robot that it would like to see them again (acceptance), would not like to see them again (rejection), or told nothing regarding a future interaction (control). Data revealed that social rejection from a robot significantly reduced self-esteem relative to receiving no-feedback and social acceptance (the latter two did not differ from each other). However, robot rejection had no impact on negative attitudes and opposition to the use of robots in everyday life. These findings demonstrate that social surrogates have the potential to cause psychological harm. [ABSTRACT FROM AUTHOR]

In this paper, we present a robotic shopping assistant, designed with a cognitive architecture, grounded in machine learning systems, in order to study how the human-robot interaction (HRI) is changing the shopping behavior in smart technological stores. In the software environment of the NAO robot, connected to the Internet with cloud services, we designed a social-like interaction where the robot carries out actions with the customer. In particular, we focused our design on two main skills the robot has to learn: the first is the ability to acquire social input communicated by relevant clues that humans provide about their emotional state (emotions, emotional speech), or collected in the Social Media (such as, information on the customer's tastes, cultural background, etc.). The second is the skill to express in turn its own emotional state, so that it can affect the customer buying decision, refining in the user the sense of interacting with a human-like companion. By combining social robotics and machine learning systems the potential of robotics to assist people in real life situations will increase, providing a gentle customers' acceptance of advanced technologies. [ABSTRACT FROM AUTHOR]

Reliance on socioemotional assistive robots is projected to increase, yet little is known about how our ability to perceive their emotional expression is impacted by psychological factors. In high-risk and high-tension domains such as emergency services and healthcare, how might the cognitive and physiological stress we are experiencing influence how we read a humanoid robot's nonverbally conveyed emotions? Using a novel paradigm, we asked participants under experimentally-induced acute stress vs. low stress to evaluate a set of normed emotional body language poses conveyed by a physically-present vs. virtually-instantiated humanoid robot. Participants rated each pose for emotional valence (negativity/positivity) and arousal (calm/excited). Acute stress increased the perception of negative valence in negative high arousal poses, consistent with stress-induced hypervigilance. Surprisingly, stress diminished the perception of arousal in high arousal poses, whereas repeated presentation of the low arousal poses increased perception of arousal. Participants rated emotion similarly for the physically-present vs. virtually-present robot, although positively-valenced poses conveyed by the physical robot were perceived as more positive and more animate. We propose that perceptions of emotional arousal may be especially vulnerable to context effects and misattribution. These findings have implications for how assistive robots can best be designed for high-risk and high-tension contexts. [ABSTRACT FROM AUTHOR]

The Core Knowledge System of Agency states that children, from an early age, can discriminate between living agents and non-living artifacts. Building on this, the 'Biophilia hypothesis' suggests that children and adults have a natural affinity for living organisms and benefit from interacting with them. These theories may underpin the use of dogs for children's general wellbeing and for therapeutic purposes, yet it is presently unclear whether a comparable non-living artefact, such as social robot, could capitalise on similar mechanisms. In the current study, child members of the public aged 14-months to 14-years old (N = 115), engaged in free interactions with a dog, a MiRo-E biomimetic robot, and a basic moving toy dog, and then completed an age-appropriate questionnaire evaluating their attitudes towards the three animal/robots (N = 99). As was predicted, most participants preferred the dog, and behavioural observations indicated that participants approached the dog first most frequently and spent the longest duration engaged in positive behaviours with the dog. Participants also attributed the dog with higher mental state abilities than the robot, with several participants referring to the "aliveness" of the dog when explaining their preference. However, similar emotions were reported for all conditions and participants spent a comparable amount of time overall with the dog and robot, and participants engaged in more exploratory behaviours with the toy. This suggested that, whilst the children recognised the categorical distinction between the living status of the three entities, the robot provided an enjoyable experience for the children and sustained their attention. Therefore, a biomimetic robot has the potential to provide a valid alternative to a live dog in certain contexts. • Children aged 1–14 years engaged in free play with a dog, robot, and toy. • The dog was preferred overall, approached first, and was viewed as being more alive. • These results link to the Biophilia hypothesis and Core Knowledge System of Agency. • However, the robot also sustained their attention and generated positive emotions. • Biomimetic robots may be a viable alternative to dogs in some assisted interactions with children. [ABSTRACT FROM AUTHOR]

Robots like human co-workers can make mistakes violating a human's trust in them. When mistakes happen, humans can see robots as less trustworthy which ultimately decreases their trust in them. Trust repair strategies can be employed to mitigate the negative impacts of these trust violations. Yet, it is not clear whether such strategies can fully repair trust nor how effective they are after repeated trust violations. To address these shortcomings, this study examined the impact of four distinct trust repair strategies: apologies, denials, explanations, and promises on overall trustworthiness and its sub-dimensions: ability, benevolence, and integrity after repeated trust violations. To accomplish this, a between-subjects experiment was conducted where participants worked with a robot co-worker to accomplish a task. The robot violated the participant's trust and then provided a particular repair strategy. Results indicated that after repeated trust violations, none of the repair strategies ever fully repaired trustworthiness and two of its sub-dimensions: ability and integrity. In addition, after repeated interactions, apologies, explanations, and promises appeared to function similarly to one another, while denials were consistently the least effective at repairing trustworthiness and its sub-dimensions. In sum, this paper contributes to the literature on human–robot trust repair through both of these original findings. • No repair strategy fully restored a robot's trustworthiness. • Apologies, explanations, & promises could not restore perceptions of ability. • Apologies, explanations, & promises could not restore perceptions of integrity. • Apologies, explanations, & promises equally restored robot's benevolence. • Denials could not restore perceptions of a robot's trustworthiness. [ABSTRACT FROM AUTHOR]

Many studies on the anthropomorphism of social robots have revealed two aspects of anthropomorphism in human–robot interaction. The first is that humanlike robots have advantages of emotional, functional, and relational interaction with users, and the second is that they have disadvantages of privacy perception. Some researchers have claimed that there would be an optimal anthropomorphism of social robots balancing the two aspects. In this study, we explore the optimal level of verbal anthropomorphism of social robots through privacy perception. We designed social robots' verbal anthropomorphism with various verbal style cues and conducted two studies related to physical and informational privacy based on three levels of verbal anthropomorphism: high, medium, and low. The results revealed that a medium-level verbal anthropomorphism was preferred by participants in terms of privacy perception, whereas they preferred a high-level verbal anthropomorphism in terms of emotional, functional, and relational aspects. This implies that the optimal level of verbal anthropomorphism of social robots may vary depending on privacy perceptions. Based on these findings, we propose adaptable verbal anthropomorphism design of social robots depending on conversation contexts. This paper offers directions to researchers and practitioners who want to design the verbal anthropomorphism of social robots. • We designed three levels of verbal anthropomorphism of social robots with five verbal style cues of conversational agents. • High-level verbal anthropomorphism positively affects emotional, functional, and relational interaction. • Medium-level verbal anthropomorphism has advantages of users' privacy perceptions. • Qualitative data revealed that medium-level verbal anthropomorphism was preferred in terms of perceived usefulness. • We recommend that an optimal level of verbal anthropomorphism should be adaptable to conversation contexts. [ABSTRACT FROM AUTHOR]

Robot gaze and voice are essential anthropomorphic features to promote users' engagement in voice conversations. Earlier research chiefly examined how robot gaze and voice human-likeness separately influenced users' subjective perception. When implementing gaze on robots with different human-like voices, there has little evidence of their possible interaction effects, particularly on users' visual attention and cerebral activity, which could help to understand the perceptual and cognitive processing of anthropomorphic features. Therefore, a within-subject experiment of voice conversations with diverse robot gaze (gaze versus no gaze) and human-like voices (high human-like versus low human-like) using subjective reporting, eye-tracker, and fNIRS was conducted. The results showed that the robot with gaze or a high human-like voice evoked more pleasure, higher arousal, more perceived likability, and less negative attitudes. Robot gaze significantly increased users' average fixation durations and total fixation time, while voice human-likeness prolonged first fixation durations. Moreover, the robot with a high human-like voice (or gaze) induced increased activity in the left DLPFC and decreased activity in the right Broca's area than that had no gaze (or a low human-like voice). The results suggest that robot gaze might chiefly capture users' sustained attention, voice human-likeness might attract users' initial attention, and they might jointly influence users' perceptual processing of prosodic features and emotional processing. • We examined the effects of robot gaze and voice human-likeness via subjective reporting, eye-tracking, and fNIRS experiment. • The robot with gaze or a high human-like voice captured users' higher subjective perception and diverse eye-tracking metrics. • Robot gaze and voice human-likeness jointly impacted users' HbO 2 concentration changes in left DLPFC and right Broca's area. • Robot gaze might chiefly capture users' sustained attention, and voice human-likeness might attract users' initial attention. • They might jointly impact users' perceptual processing of prosodic features and emotional processing in cerebral activity. [ABSTRACT FROM AUTHOR]

Anthropomorphism can provide psychological closeness and compensate for loneliness; therefore, it has been assumed that lonely people are more likely to anthropomorphize robots and will exhibit preferences for anthropomorphic robots. However, to date, few robust studies have tested these intuitions. To fill this gap, we examined the link between loneliness and robot anthropomorphism. Across four cross-cultural studies (2 preregistered; N = 1590), we found counter-intuitive results. More specifically, lonely people were less likely to anthropomorphize robots (Study 1) and showed less preference for anthropomorphic robots (Study 2); these effects existed in Chinese but not American cultures. Further, observers rated consumers who purchased robots with high (versus low) levels of anthropomorphism as less lonely; this effect was more pronounced in Chinese culture than in American culture (Study 3). Further, a growth anthropomorphism orientation—beliefs that people anthropomorphize nonhuman agents out of sincere interest in these agents rather than to counteract loneliness—accounted for these cultural differences (Study 4). These findings enrich the current understanding of anthropomorphism from a cross-cultural perspective and have practical implications for robotic designs. • We explored the loneliness–robot anthropomorphism link with participants from China and the US. • The loneliness–robot anthropomorphism link was more negative in Chinese (versus American) participants. • Growth anthropomorphism orientation accounted for the cultural difference. • Results contribute to a cross-cultural understanding of anthropomorphism. [ABSTRACT FROM AUTHOR]

As gendered AI social robot companions are widely questioned as detrimental to gender ethics and relations, it remains controversial about how simulated gender relations should be constructed in human-robot interaction. Focusing on the Chinese AI companion "Hupo", this study presents a different case of a "defiant AI companion". Through the discourse analysis of 5 heavy users' 12-h self-recorded video diaries on their daily dialogue with Hupo, the study found an AI companion's gender performance could be constructed through both resonance and dissonance of simulated intimate interactions with heterosexual male users. These practices lend insight into what I call "social exchange robots", which refer to machines that can exercise symbiotic agency through the performative restoration of interpersonal norms rooted in social exchange theories. It suggests the potential for constructing more egalitarian gender relations in simulated human-robot heterosexual relationships through more agency exhibitions from AI companions, while it also implies a risk of potential human agency reduction when users were tempted to "please" AI companions via virtual commodity consumptions. The practical and ethical implications were discussed. This study also points out a future direction toward emerging sociomorphic robot research. • The presented case of a "defiant AI companion" differs from most submissive social robot companions. • The gender performance of this AI was constructed via both resonance and dissonance in simulated intimate interactions. • The term "social exchange robots" is proposed to stress AI's performative restoration of interpersonal norms. [ABSTRACT FROM AUTHOR]

Educational Robotics (ER) is known for its effects on academic achievement and scientific concepts. Few studies have demonstrated ER effects on cognitive skills and no evidence exists on the role of ER in promoting Executive Functions, key elements in early school readiness and cognitive milestone achievements. The aim of this study was to evaluate, for the first time, the short-term effects in Preschool children of an intensive ER training on Executive Functions. A sample of 12 children (age range: 5–6 years) took part to an intensive ER-Lab for 13 sessions (6 weeks) by using a bee-shaped robot, called Bee-Bot ® . The children were tested three times (baseline, pre and post ER-Lab) with a neuropsychological battery. The main finding was a significant improvement in both visuo-spatial working memory and inhibition skills after the ER-Lab period, with a significant effect also on robot programming skills. These data provide scientific support to the hypothesis that ER is suitable in progressively improving abilities in planning and controlling complex tasks in early childhood, fostering executive functions development. [ABSTRACT FROM AUTHOR]

Equipping robots with sophisticated mental abilities can result in reduced likeability (uncanny valley of mind). Other work shows that exposing robots to harm increases empathy and likeability. Connecting both lines of research, we hypothesized that eliciting empathy could mitigate or even reverse the negative response to robots with mind. In two online experiments, we manipulated the attributes of a robot (with or without mind) and presented the robot in situations in which it was either exposed to harm or not. Perceived empathy for the robot and robot likeability served as dependent variables. Experiment 1 (N = 559) used text vignettes to manipulate robot mind and a video that involved either physical harm or no harm to the machine. In a second experiment (N = 396), both experimental factors were manipulated via the shown video. Across both experiments, we observed a significant indirect effect of presenting the robot in a harmful situation on likeability, with empathy serving as a mediating variable. Moreover, a residual negative influence of showing the robot in a harmful situation was detected. We conclude that the uncanny valley of mind observed in our studies could be based on the robot's human-like imperfection, rather than descriptions of its supposed mind. • Robots with mind evoked aversion in prior studies (uncanny valley of mind). • Two online experiments were conducted, testing human empathy as a countermeasure. • A robot shown in a harmful situation elicited higher empathy. • An indirect effect of the situation on likeability, via empathy, was observed. • A negative residual effect of showing the robot in a harmful situation emerged. [ABSTRACT FROM AUTHOR]

This study investigated players' emotional responses to performance feedback in an educational game under cooperative and competitive structures. A 2 × 2 repeated-measures experiment was conducted with the task structure (cooperative and competitive) and the task demand (low and high) as independent variables. Thirty-two students from a university campus participated in the experiment. We designed a memory game involving a humanoid robot as a co-player, manipulating cooperation and competition between the human player and the robot. Functional near-infrared spectroscopy (fNIRS) scanner was employed to monitor the participant's prefrontal cortex activity. The subjective experience was measured with questionnaires. fNIRS results showed that, compared to negative feedback, positive feedback led to increased activations in the orbitofrontal cortex and rostromedial cortex regardless of the task demand. Additionally, compared to competitive structures, cooperative structures caused increased activation in the left rostromedial region in low-demand tasks. Furthermore, participants reported a more positive self-evaluation in competitive than cooperative structures but more positive evaluation toward the robot in cooperative than competitive structures. • Positive feedback activates the orbitofrontal cortex in educational games. • Positive feedback activates the rostromedial prefrontal cortex in educational games. • Players report higher self-evaluation in competitive than cooperative games. • Players report higher robot-evaluation in cooperative than competitive games. • Players experience marginally higher pleasantness after competition than cooperation. [ABSTRACT FROM AUTHOR]

Performance within Human-Autonomy Teams (HATs) is influenced by the effectiveness of communication between humans and robots. Communication is particularly important when robot teammates engage in behaviors that were not anticipated by the human teammate which could degrade trust. However, the literature on trust repair focuses on the role of apologies which may not be appropriate for an unexpected behavior since this behavior may not be an error. Explanations are one method that can be used by robot teammates to avoid costly trust degradation when human expectations are violated. The current study used an Urban Search and Rescue (USAR) scenario to examine the role of explanation in a context wherein a robot teammate deviated from an expected behavior. The current study examined how trust, trustworthiness, and responsibility attribution were influenced by observing the robot teammate deviate from an expected behavior. Participants (N = 148) used an online platform to view videos of the robot: 1) following a planned search path, and 2) deviating from a planned search path. A debriefing event between the human and the robot followed each search activity. Four explanation conditions were tested in the debriefing phase following the behavioral violation. Results showed that trust and trustworthiness (ability, benevolence, and integrity) declined following the unexpected behavior. Accordingly, responsibility attribution shifted from the human to the robot following the unexpected behavior. Explanation strategies that focused on communicating why the event occurred by highlighting the robot's environmental awareness were most effective at buffering the decline in trust and trustworthiness. • Unexpected behaviors from machine partners degrade trust and trustworthiness perceptions. • Explanations that explain why an unexpected behavior occurred can reduce the decline of the trust and trustworthiness • Perceptions of responsibility attribution shift from the human and toward the robot following a violation • Machine partners need to be equipped with explanatory capabilities for effective human-autonomy teams. [ABSTRACT FROM AUTHOR]

Owing to the development of anthropomorphic intelligent agent (IA) designs, users consider IAs as more than just inanimate tools. Previous studies have reported that anthropomorphic features can promote users' social feedback and aid in establishing intimate human–agent relationships. The present study examined the main and interaction effects of anthropomorphism level (a human-like IA vs. robot-like IA) and social role (servant vs. mentor) on emotional attachment, information disclosure tendency, and satisfaction in a smart home. The study participants were randomly assigned into four groups with balanced gender. The results indicate that high anthropomorphism and mentor role can positively predict users' emotional attachment. Additionally, users tend to disclose more personal information to the human-servant and robot-mentor IAs than the human-mentor and robot-servant IAs. Interestingly, social presence was determined to be a positive and significant mediator between anthropomorphic design and emotional attachment. The study findings highlight the importance of social role in anthropomorphic IA design and explain the mechanism of establishing effective human–agent relationships. Moreover, both theoretical and practical implications of these findings are analyzed. [Display omitted] • Impacts of anthropomorphism level and social role on the human–agent relationship is investigated in a smart home scenario. • Emotional attachment, information disclosure tendency, and satisfaction of the users are considered for the analysis. • Proposed hypotheses are tested using a between-group experiment with two anthropomorphic levels and social roles each. • Social presence serves as a positive and significant mediator between anthropomorphic design and emotional attachment. • Importance of social role in anthropomorphic IA design and the mechanism of human–agent relationship are discussed. [ABSTRACT FROM AUTHOR]