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She argues that "social robots designed for reciprocity use reciprocity as an instrumental value to enhance acceptability of the robot", and that this is ethically questionable. As Balle also reasons, one can only make a weak claim of moral patienthood for robots, i.e., it should be regarded as "permissible rather than obligatory and individual rather than universal" as far as it happens to occur in human-robot interactions. Problematizing socio-emotional relationships with robots Social robots influence human-robot and human-human relations. Challenging sociality in human-robot interactions In exploring dimensions of human-robot relations, the two final contributions to this Special Issue question the basic premise of what (social) robots are and should be. [Extracted from the article]

Robotic and artificially intelligent (AI) systems are becoming prevalent in our day-to-day lives. As human interaction is increasingly replaced by human–computer and human–robot interaction (HCI and HRI), we occasionally speak and act as though we are blaming or praising various technological devices. While such responses may arise naturally, they are still unusual. Indeed, for some authors, it is the programmers or users—and not the system itself—that we properly hold responsible in these cases. Furthermore, some argue that since directing blame or praise at technology itself is unfitting, designing systems in ways that encourage such practices can only exacerbate the problem. On the other hand, there may be good moral reasons to continue engaging in our natural practices, even in cases involving AI systems or robots. In particular, daily interactions with technology may stand to impact the development of our moral practices in human-to-human interactions. In this paper, we put forward an empirically grounded argument in favor of some technologies being designed for social responsiveness. Although our usual practices will likely undergo adjustments in response to innovative technologies, some systems which we encounter can be designed to accommodate our natural moral responses. In short, fostering HCI and HRI that sustains and promotes our natural moral practices calls for a co-developmental process with some AI and robotic technologies. [ABSTRACT FROM AUTHOR]

Engagement is important to the success of applications, systems and artefacts as diverse as robotics, pedagogy, games, interactive installations, and virtual reality applications. Yet engagement has proved to be remarkably difficult to define as it can take many forms, so many that it is difficult to isolate what these different instantiations have in common. Instead of pursuing an empirical perspective, the human side of engagement, namely, involvement is considered from a broadly Heideggerian perspective. As Heidegger has a deserved reputation for philosophical obscurity, all of the concepts adopted from his work are mapped onto the more familiar languages and vocabularies of psychology, human-computer interaction and cognitive science. It is argued that technology is engaging and our response to it is to be involved (with it). This resulting involvement- engagement dyad is thus an explicitly holistic account recognising roles for affordance, purpose, identity, affect and embodiment. [ABSTRACT FROM AUTHOR]

Robot enthusiasts envision robots will become a 'race unto themselves' as they cohabit with the humankind one day. Profound questions arise surrounding one of the major areas of research in the contemporary world-that concerning artificial intelligence. Fascination and anxiety that androids impose upon us hinges on how we come to conceive of the 'Cultural Other.' Applying the notion of the 'other' in multicultural research process, we will explore how the 'Other' has been used to illustrate values and theories about robots, as a mirror for the self. In this paper, we focus on the social, cultural, and religious implications of humans' attitudes toward relationships between humans with robots. Six major views on humanoid robots are proposed: (1) robots as the 'Frightening Other,' (2) robots as the 'Subhuman Other,' (3) robots as the 'Human Substitute,' (4) robots as the 'Sentient Other,' (5) robots as the 'Divine Other,' and (6) robots as the 'Co-evolutionary Path to Immortality.' The likely and preferable scenario is the last one, which is compatible with an optimistic posthuman world in our evolutionary future. We imagine whether humans will meet the challenge of loving all living and non-living beings (including mechanical entities) might be the key to the co-evolution of both species and the ultimate happiness. [ABSTRACT FROM AUTHOR]

Psychological attitudes towards service and personal robots are selectively examined from the vantage point of psychoanalysis. Significant case studies include the uncanny valley effect, brain-actuated robots evoking magic mental powers, parental attitudes towards robotic children, idealizations of robotic soldiers, persecutory fantasies involving robotic components and systems. Freudian theories of narcissism, animism, infantile complexes, ego ideal, and ideal ego are brought to bear on the interpretation of these various items. The horizons of Human-robot Interaction are found to afford new and fertile grounds for psychoanalytic theorizing beyond strictly therapeutic contexts. [ABSTRACT FROM AUTHOR]

For a robot to cohabit with people, it should be able to learn people's nonverbal social behavior from experience. In this paper, we propose a novel machine learning method for recognizing gestures used in interaction and communication. Our method enables robots to learn gestures incrementally during human-robot interaction in an unsupervised manner. It allows the user to leave the number and types of gestures undefined prior to the learning. The proposed method (HB-SOINN) is based on a self-organizing incremental neural network and the hidden Markov model. We have added an interactive learning mechanism to HB-SOINN to prevent a single cluster from running into a failure as a result of polysemy of being assigned more than one meaning. For example, a sentence: ''Keep on going left slowly'' has three meanings such as, ''Keep on (1)'', ''going left (2)'', ''slowly (3)''. We experimentally tested the clustering performance of the proposed method against data obtained from measuring gestures using a motion capture device. The results show that the classification performance of HB-SOINN exceeds that of conventional clustering approaches. In addition, we have found that the interactive learning function improves the learning performance of HB-SOINN. [ABSTRACT FROM AUTHOR]