In this paper we compare the strategies applied by two successful biological components of the ecosystem, the viruses and the human beings, to interact with the environment. Viruses have had and still exert deep and vast actions on the ecosystem especially at the genome level of most of its biotic components. We discuss on the importance of the human being as contraptions maker in particular of robots, hence of machines capable of automatically carrying out complex series of actions. Beside the (...) relevance of designing and assembling these contraptions, it is of basic importance the goal for which they are assembled and future scenarios of their possible impact on the ecosystem. We can’t procrastinate the development and implementation of a highly inspired and stringent “ethical code” for human beings and humanoid robots because it will be a crucial aspect for the wellbeing of the mankind and of the entire ecosystem. (shrink)

Social appropriateness is an important topic – both in the human-human interaction (HHI), and in the human-machine interaction (HMI) context. As sociosensitive and socioactive assistance systems advance, the question arises whether a machine’s behavior should include considerations regarding social appropriateness. However, the concept of social appropriateness is difficult to define, as it is determined by multiple aspects. Thus, to date, a unified perspective, encompassing and combining multidisciplinary findings, is missing. When translating results from HHI to HMI, it remains unclear whether (...) such insights into the dynamics of social appropriateness between humans may in fact apply to sociosensitive and socioactive assistance systems. To shed light on this matter, we propose the Five Factor Model of Social Appropriateness (FASA) which provides a multidisciplinary perspective on the notion of social appropriateness and its implementation into technical systems. Finally, we offer reflections on the applicability and ethics of the FASA Model, highlighting both strengths and limitations of the framework. (shrink)

The diversified methodology and expertise of interdisciplinary research teams provide the opportunity to overcome the limited perspectives of individual disciplines. This is particularly true at the interface of Robotics, Neuroscience, and Psychology as the three fields have quite different perspectives and approaches to offer. Nonetheless, aligning backgrounds and interdisciplinary expectations can present challenges due to varied research cultures and practices. Overcoming these challenges stands at the beginning of each productive collaboration and thus is a mandatory step in cognitive neurorobotics. In (...) this article, we share eight lessons that we learned from our ongoing interdisciplinary project on human-robot and robot-robot interaction in social settings. These lessons provide practical advice for scientists initiating interdisciplinary research endeavors. Our advice can help to avoid early problems and deal with differences between research fields, prepare for and anticipate challenges, align project expectations, and speed up research progress, thus promoting effective interdisciplinary research across Robotics, Neuroscience, and Psychology. (shrink)

“Integrative Social Robotics” (ISR) is a new approach or general method for generating social robotics applications in a responsible and “culturally sustainable” fashion. Currently social robotics is caught in a basic difficulty we call the “triple gridlock of description, evaluation, and regulation”. We briefly recapitulate this problem and then present the core ideas of ISR in the form of five principles that should guide the development of applications in social robotics. Characteristic of ISR is to intertwine a mixed method approach (...) (i.e., conducting experimental, quantitative, qualitative, and phenomenological research for the same envisaged application) with conceptual and axiological analysis as required in professional studies in applied ethics; moreover, ISR is value-driven and abides by the “Non-Replacement Principle”: Social robots may only do what humans should but cannot do. We briefly compare ISR to other value-sensitive or value-directed design models, with a view to the task of overcoming the triple gridlock. Finally, working from an advanced classification of pluridiscplinary research, we argue that ISR establishes a research format that can turn social robotics into a new transdiscipline. (shrink)

In our daily lives, we are continually involved in decision-making situations, many of which take place in the context of social interaction. Despite the ubiquity of such situations, there remains a gap in our understanding of how decision-making unfolds in social contexts, and how communicative signals, such as social cues and feedback, impact the choices we make. Interestingly, there is a new social context to which humans are recently increasingly more frequently exposed—social interaction with not only other humans but also (...) artificial agents, such as robots or avatars. Given these new technological developments, it is of great interest to address the question of whether—and in what way—social signals exhibited by non-human agents influence decision-making. The present study aimed to examine whether robot non-verbal communicative behavior has an effect on human decision-making. To this end, we implemented a two-alternative-choice task where participants were to guess which of two presented cups was covering a ball. This game was an adaptation of a “Shell Game.” A robot avatar acted as a game partner producing social cues and feedback. We manipulated robot's cues (pointing toward one of the cups) before the participant's decision and the robot's feedback (“thumb up” or no feedback) after the decision. We found that participants were slower (compared to other conditions) when cues were mostly invalid and the robot reacted positively to wins. We argue that this was due to the incongruence of the signals (cue vs. feedback), and thus violation of expectations. In sum, our findings show that incongruence in pre- and post-decision social signals from a robot significantly influences task performance, highlighting the importance of understanding expectations toward social robots for effective human–robot interactions. (shrink)

Artificial agents are progressively becoming more present in everyday-life situations and more sophisticated in their interaction affordances. In some specific cases, like Google Duplex, GPT-3 bots or Deep Mind’s AlphaGo Zero, their capabilities reach or exceed human levels. The use contexts of everyday life necessitate making such agents understandable by laypeople. At the same time, displaying human levels of social behavior has kindled the debate over the adoption of Dennett’s ‘intentional stance’. By means of a comparative analysis of the literature (...) on robots and virtual agents, we defend the thesis that approaching these artificial agents ‘as if’ they had intentions and forms of social, goal-oriented rationality is the only way to deal with their complexity on a daily base. Specifically, we claim that this is the only viable strategy for non-expert users to understand, predict and perhaps learn from artificial agents’ behavior in everyday social contexts. Furthermore, we argue that as long as agents are transparent about their design principles and functionality, attributing intentions to their actions is not only essential, but also ethical. Additionally, we propose design guidelines inspired by the debate over the adoption of the intentional stance. (shrink)

It is frequently demanded that AI-based Decision Support Tools (AI-DSTs) ought to be both explainable to, and trusted by, those who use them. The joint pursuit of these two principles is ordinarily believed to be uncontroversial. In fact, a common view is that AI systems should be made explainable so that they can be trusted, and in turn, accepted by decision-makers. However, the moral scope of these two principles extends far beyond this particular instrumental connection. This paper argues that if (...) we were to account for the rich and diverse moral reasons that ground the call for explainable AI, and fully consider what it means to “trust” AI in a descriptively rich sense of the term, we would uncover a deep and persistent tension between the two principles. For explainable AI to usefully serve the pursuit of normatively desirable goals, decision-makers must carefully monitor and critically reflect on the content of an AI-DST’s explanation. This entails a deliberative attitude. Conversely, calls for trust in AI-DSTs imply the disposition to put questions about their reliability out of mind. This entails an unquestioning attitude. As such, the joint pursuit of explainable and trusted AI calls on decision-makers to simultaneously adopt incompatible attitudes towards their AI-DST, which leads to an intractable implementation gap. We analyze this gap and explore its broader implications: suggesting that we may need alternate theoretical conceptualizations of what explainability and trust entail, and/or alternate decision-making arrangements that separate the requirements for trust and deliberation to different parties. (shrink)

Despite the increasing number of studies on user experience and user interfaces, few studies have examined emotional interaction between humans and deformable objects. In the current study, we investigated how the anthropomorphic design of a flexible display interacts with emotion. For 101 unique 3D images in which an object was bent at different axes, 281 participants were asked to report how strongly the object evoked five elemental emotions (e.g., happiness, disgust, anger, fear, and sadness) in an online survey. People rated (...) the object’s shape using three emotional categories: happiness, disgust–anger, and sadness–fear. It was also found that a combination of axis of bending (horizontal or diagonal axis) and convexity (bending convexly or concavely) predicted emotional valence, underpinning the anthropomorphic design of flexible displays. Our findings provide empirical evidence that axis of bending and convexity can be an important antecedent of emotional interaction with flexible objects, triggering at least three types of emotion in users. (shrink)

While we applaud the careful breakdown by Clark and Fischer of the representation of social robots held by the human user, we emphasise that a neurocognitive perspective is crucial to fully capture how people perceive and construe social robots at the behavioural and brain levels.

A wealth of social psychology studies suggests that moving in synchrony with another person can positively influence their likeability and prosocial behavior towards them. Recently, human-robot interaction researchers have started to develop real-time, adaptive synchronous movement algorithms for social robots. However, little is known how socially beneficial synchronous movements with a robot actually are. We predicted that moving in synchrony with a robot would improve its likeability and participants’ social motivation towards the robot, as measured by the number of questions (...) asked during a free interaction period. Using a between-subjects design, we implemented the synchrony manipulation via a drawing task. Contrary to predictions, we found no evidence that participants who moved in synchrony with the robot rated it as more likeable or asked it more questions. By including validated behavioral and neural measures, future studies can generate a better and more objective estimation of synchrony’s effects on rapport with social robots. (shrink)

Background: The surge in the development of social robots gives rise to an increased need for systematic methods of assessing attitudes towards robots. Aim: This study presents the development of a questionnaire for assessing attitudinal stance towards social robots: the ASOR. Methods: The 37-item ASOR questionnaire was developed by a task-force with members from different disciplines. It was founded on theoretical considerations of how social robots could influence five different aspects of relatedness. Results: Three hundred thirty-nine people responded to the (...) survey. Factor analysis of the ASOR yielded a three-factor solution consisting of a total of 25 items: “ascription of mental capacities”, “ascription of socio-practical capacities”, and “ascription of socio-moral status”. This data was further triangulated with data from interviews (n = 10). Conclusion: the ASOR allows for assessment of three distinct facets of ascription of capacities to social robots and offers a new type of assessment of attitudes towards social robots. It appeared that ASOR not only assesses ascription of capacities to social robots but it also gauged overall positive attitudes towards social robots. (shrink)

Studying trust in the context of human-robot interaction is of great importance given the increasing relevance and presence of robotic agents in the social sphere, including educational and clinical. We investigated the acquisition, loss and restoration of trust when preschool and school-age children played with either a human or a humanoid robot in-vivo. The relationship between trust and the representation of the quality of attachment relationships, Theory of Mind, and executive function skills was also investigated. Additionally, to outline children’s beliefs (...) about the mental competencies of the robot, we further evaluated the attribution of mental states to the interactive agent. In general, no substantial differences were found in children’s trust in the play-partner as a function of agency (human or robot). Nevertheless, 3-years-olds showed a trend toward trusting the human more than the robot, as opposed to 7-years-olds, who displayed the reverse pattern. These findings align with results showing that, for 3 and 7-year-olds, the cognitive ability to switch was significantly associated with trust restoration in the human and the robot, respectively. Additionally, supporting previous findings, we found a dichotomy between attributions of mental states to the human and robot and children’s behavior: while attributing to the robot significantly lower mental states than the human, in the trusting game children behaved in a similar way when they related to the human and the robot. Altogether, the results of this study highlight that similar psychological mechanisms are at play when children are to establish a novel trustful relationship with a human and robot partner. Furthermore, the findings shed light on the interplay – during development – between children’s quality of attachment relationships and the development of a Theory of Mind, which act differently on trust dynamics as a function of the children’s age as well as the interactive partner’s nature (human vs. robot). (shrink)

This paper discuss the phenomenon of empathy in social robotics and is divided into three main parts. Initially, I analyse whether it is correct to use this concept to study and describe people’s reactions to robots. I present arguments in favour of the position that people actually do empathise with robots. I also consider what circumstances shape human empathy with these entities. I propose that two basic classes of such factors be distinguished: biological and socio-cognitive. In my opinion, one of (...) the most important among them is a sense of group membership with robots, as it modulates the empathic responses to representatives of our- and other- groups. The sense of group membership with robots may be co-shaped by socio-cognitive factors such as one’s experience, familiarity with the robot and its history, motivation, accepted ontology, stereotypes or language. Finally, I argue in favour of the formulation of a pragmatic and normative framework for manipulations in the level of empathy in human–robot interactions. (shrink)