On reviewing the literature regarding acceptance and trust in human-robot interaction (HRI), there are a number of open questions that needed to be addressed in order to establish effective collaborations between humans and robots in real-world applications. In particular, we identified four principal open areas that should be investigated to create guidelines for the successful deployment of robots in the wild. These areas are focused on: (1) the robot’s abilities and limitations; in particular when it makes errors with different severity (...) of consequences, (2) individual differences, (3) the dynamics of human-robot trust, and (4) the interaction between humans and robots over time. In this paper, we present two very similar studies, one with a virtual robot with human-like abilities, and one with a Care-O-bot 4 robot. In the first study, we create an immersive narrative using an interactive storyboard to collect responses of 154 participants. In the second study, 6 participants had repeated interactions over three weeks with a physical robot. We summarise and discuss the findings of our investigations of the effects of robots’ errors on people’s trust in robots for designing mechanisms that allow robots to recover from a breach of trust. In particular, we observed that robots’ errors had greater impact on people’s trust in the robot when the errors were made at the beginning of the interaction and had severe consequences. Our results also provided insights on how these errors vary according to the individuals’ personalities, expectations and previous experiences. (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)

To realize a successful and collaborative interaction between human and robots remains a big challenge. Emotional reactions of the user provide crucial information for a successful interaction. These reactions carry key factors to prevent errors and fatal bidirectional misunderstanding. In cases where human–machine interaction does not proceed as expected, negative emotions, like frustration, can arise. Therefore, it is important to identify frustration in a human–machine interaction and to investigate its impact on other influencing factors such as dominance, sense of control (...) and task performance. This paper presents a study that investigates a close cooperative work situation between human and robot, and explore the influence frustration has on the interaction. The task for the participants was to hand over colored balls to two different robot systems. The robot systems had to throw the balls into appropriate baskets. The coordination between human and robot was controlled by various gestures and words by means of trial and error. Participants were divided into two groups, a frustration- and a no frustration- group. Frustration was induced by the behavior of the robotic systems which made errors during the ball handover. Subjective and objective methods were used. The sample size of participants was N = 30 and the study was conducted in a between-subject design. Results show clear differences in perceived frustration in the two condition groups and different behavioral interactions were shown by the participants. Furthermore, frustration has a negative influence on interaction factors such as dominance and sense of control. The study provides important information concerning the influence of frustration on human–robot interaction for the requirements of a successful, natural, and social HRI. The results are discussed in favor of how a successful und effortless interaction between human and robot can be realized and what relevant factors, like appearance of the robot and influence of frustration on sense of control, have to be regarded. (shrink)

Background The twenty first- century marked the exponential growth in the use of intelligent robots and artificial intelligent in nursing compared to the previous decades. To the best of our knowledge, this article is first in responding to question, “Can nurses in clinical practice ascribe responsibility to intelligent robots and artificial intelligence when they commit errors?”. Purpose The objective of this article is to present two worldviews (anthropocentrism and biocentrism) in responding to the question at hand chosen based on the (...) roles of the entities involved in the use of intelligent robots and artificial intelligence in nursing. Methods The development of this article was motivated by the immense discoveries, the current landscape, and nurses’ role in relation to advanced technologies in healthcare. The paper begins the discussion by situating the use of intelligent robots and artificial intelligence in nursing and healthcare and presenting its ethical and moral implications. Then, we presented the two worldviews: anthropocentrism and biocentrism which are used to respond to the task at hand. Results Anthropocentrism puts humans in the center in terms of moral standing and thus responsibility rests on them alone. Biocentrism declares that all creations deserve moral consideration and thus responsibility is equally allocated to all entities. Within these two worldviews, consensus development was offered to resolve these issues. Consensus provides clarity and democracy between and among the societies. Conclusions The findings of this article can be basis in (1) instituting mechanisms of robust peer review and a rigorous series of simulation before adopting or implementing intelligent robots and artificial intelligence in clinical practice; (2) education and training of highly specialized nurse practitioners who can be focal persons in responding to ethical and moral issues with regard to these advanced technologies; and (3) harmonization of robotics research, manufacturing, and clinical practice. (shrink)