Bringing Human Robot Interaction towards _Trust and Social Engineering

Robots started their journey in books and movies; nowadays, they are becoming an important part of our daily lives: from industrial robots, passing through entertainment robots, and reaching social robotics in fields like healthcare or education. An important aspect of social robotics is the human counterpart, therefore, there is an interaction between the humans and robots. Interactions among humans are often taken for granted as, since children, we learn how to interact with each other. In robotics, this interaction is still very immature, however, critical for a successful incorporation of robots in society. Human robot interaction (HRI) is the domain that works on improving these interactions. HRI encloses many aspects, and a significant one is trust. Trust is the assumption that somebody or something is good and reliable; and it is critical for a developed society. Therefore, in a society where robots can part, the trust they could generate will be essential for cohabitation. A downside of trust is overtrusting an entity; in other words, an insufficient alignment of the projected trust and the expectations of a morally correct behaviour. This effect could negatively influence and damage the interactions between agents. In the case of humans, it is usually exploited by scammers, conmen or social engineers - who take advantage of the people's overtrust in order to manipulate them into performing actions that may not be beneficial for the victims. This thesis tries to shed light on the development of trust towards robots, how this trust could become overtrust and be exploited by social engineering techniques. More precisely, the following experiments have been carried out: (i) Treasure Hunt, in which the robot followed a social engineering framework where it gathered personal information from the participants, improved the trust and rapport with them, and at the end, it exploited that trust manipulating participants into performing a risky action. (ii) Wicked Professor, in which a very human-like robot tried to enforce its authority to make participants obey socially inappropriate requests. Most of the participants realized that the requests were morally wrong, but eventually, they succumbed to the robot'sauthority while holding the robot as morally responsible. (iii) Detective iCub, in which it was evaluated whether the robot could be endowed with the ability to detect when the human partner was lying. Deception detection is an essential skill for social engineers and professionals in the domain of education, healthcare and security. The robot achieved 75% of accuracy in the lie detection. There were also found slight differences in the behaviour exhibited by the participants when interacting with a human or a robot interrogator. Lastly, this thesis approaches the topic of privacy - a fundamental human value. With the integration of robotics and technology in our society, privacy will be affected in ways we are not used. Robots have sensors able to record and gather all kind of data, and it is possible that this information is transmitted via internet without the knowledge of the user. This is an important aspect to consider since a violation in privacy can heavily impact the trust. Summarizing, this thesis shows that robots are able to establish and improve trust during an interaction, to take advantage of overtrust and to misuse it by applying different types of social engineering techniques, such as manipulation and authority. Moreover, robots can be enabled to pick up different human cues to detect deception, which can help both, social engineers and professionals in the human sector. Nevertheless, it is of the utmost importance to make roboticists, programmers, entrepreneurs, lawyers, psychologists, and other sectors involved, aware that social robots can be highly beneficial for humans, but they could also be exploited for malicious purposes

Child–robot relationship formation: A narrative review of empirical research

This narrative review aimed to elucidate which robot-related characteristics predict relationship formation between typically-developing children and social robots in terms of closeness and trust. Moreover, we wanted to know to what extent relationship formation can be explained by children’s experiential and cognitive states during interaction with a robot. We reviewed 86 journal articles and conference proceedings published between 2000 and 2017. In terms of predictors, robots’ responsiveness and role, as well as strategic and emotional interaction between robot and child, increased closeness between the child and the robot. Findings about whether robot features predict children’s trust in robots were inconsistent. In terms of children’s experiential and cognitive states during interaction with a robot, robot characteristics and interaction styles were associated with two experiential states: engagement and enjoyment/liking. The literature hardly addressed the impact of experiential and cognitive states on closeness and trust. Comparisons of children’s interactions with robots, adults, and objects showed that robots are perceived as neither animate nor inanimate, and that they are entities with whom children will likely form social relationships. Younger children experienced more enjoyment, were less sensitive to a robot’s interaction style, and were more prone to anthropomorphic tendencies and effects than older children. Tailoring a robot’s sex to that of a child mainly appealed to boys

Calming Effects of Touch in Human, Animal, and Robotic Interaction—Scientific State-of-the-Art and Technical Advances

Small everyday gestures such as a tap on the shoulder can affect the way humans feel and act. Touch can have a calming effect and alter the way stress is handled, thereby promoting mental and physical health. Due to current technical advances and the growing role of intelligent robots in households and healthcare, recent research also addressed the potential of robotic touch for stress reduction. In addition, touch by non-human agents such as animals or inanimate objects may have a calming effect. This conceptual article will review a selection of the most relevant studies reporting the physiological, hormonal, neural, and subjective effects of touch on stress, arousal, and negative affect. Robotic systems capable of non-social touch will be assessed together with control strategies and sensor technologies. Parallels and differences of human-to-human touch and human-to-non-human touch will be discussed. We propose that, under appropriate conditions, touch can act as (social) signal for safety, even when the interaction partner is an animal or a machine. We will also outline potential directions for future research and clinical relevance. Thereby, this review can provide a foundation for further investigations into the beneficial contribution of touch by different agents to regulate negative affect and arousal in humans

Humanoid-based protocols to study social cognition

Social cognition is broadly defined as the way humans understand and process their interactions with other humans. In recent years, humans have become more and more used to interact with non-human agents, such as technological artifacts. Although these interactions have been restricted to human-controlled artifacts, they will soon include interactions with embodied and autonomous mechanical agents, i.e., robots. This challenge has motivated an area of research related to the investigation of human reactions towards robots, widely referred to as Human-Robot Interaction (HRI). Classical HRI protocols often rely on explicit measures, e.g., subjective reports. Therefore, they cannot address the quantification of the crucial implicit social cognitive processes that are evoked during an interaction. This thesis aims to develop a link between cognitive neuroscience and human-robot interaction (HRI) to study social cognition. This approach overcomes methodological constraints of both fields, allowing to trigger and capture the mechanisms of real-life social interactions while ensuring high experimental control. The present PhD work demonstrates this through the systematic study of the effect of online eye contact on gaze-mediated orienting of attention. The study presented in Publication I aims to adapt the gaze-cueing paradigm from cognitive science to an objective neuroscientific HRI protocol. Furthermore, it investigates whether the gaze-mediated orienting of attention is sensitive to the establishment of eye contact. The study replicates classic screen-based findings of attentional orienting mediated by gaze both at behavioral and neural levels, highlighting the feasibility and the scientific value of adding neuroscientific methods to HRI protocols. The aim of the study presented in Publication II is to examine whether and how real-time eye contact affects the dual-component model of joint attention orienting. To this end, cue validity and stimulus-to-onset asynchrony are also manipulated. The results show an interactive effect of strategic (cue validity) and social (eye contact) top-down components on the botton-up reflexive component of gaze-mediated orienting of attention. The study presented in Publication III aims to examine the subjective engagement and attribution of human likeness towards the robot depending on established eye contact or not during a joint attention task. Subjective reports show that eye contact increases human likeness attribution and feelings of engagement with the robot compared to a no-eye contact condition. The aim of the study presented in Publication IV is to investigate whether eye contact established by a humanoid robot affects objective measures of engagement (i.e. joint attention and fixation durations), and subjective feelings of engagement with the robot during a joint attention task. Results show that eye contact modulates attentional engagement, with longer fixations at the robot’s face and cueing effect when the robot establishes eye contact. In contrast, subjective reports show that the feeling of being engaged with the robot in an HRI protocol is not modulated by real-time eye contact. This study further supports the necessity for adding objective methods to HRI. Overall, this PhD work shows that embodied artificial agents can advance the theoretical knowledge of social cognitive mechanisms by serving as sophisticated interactive stimuli of high ecological validity and excellent experimental control. Moreover, humanoid-based protocols grounded in cognitive science can advance the HRI community by informing about the exact cognitive mechanisms that are present during HRI

Robots in Service and Nursing Care - An Investigation into Japan’s Robot Use and Development

Postponed access: the file will be accessible after 2020-11-30We are currently seeing a rapid growth in the investment and development of robots to assist or replace human workers and efforts in many aspects of life. Due to Japan’s proportionally large and growing elderly population along with a shrinking workforce, the Japanese government has chosen to promote the research, development, and use of robots in fields such as nursing care. Other countries are also facing the same problems as Japan but have not chosen to promote the alternative futuristic solution to the same extent. In a pursuit to better understand the impact that robots already have and will have on society and everyday life, we have researched the topic of assistive robots in the service and nursing care context. Through a design science framework and mixed methods approach, performing semi-structured interviews with robot developers, professors in robotics and nursing care staff, observations on the use of robots in real-life settings, case studies, and one experiment, we have developed a comprehensive analysis and understanding of the research problem. To analyze the data, content analysis and the grounded theory were used. An experiment and two case studies were used to investigate attitudes, perceived benefits, and disadvantages of using robots. Furthermore, interviews and observations were conducted at nursing care facilities to investigate the possibility of assisting or even substituting humans with robots in settings that usually require a sense of human warmth and care. Previous research often focusses on individual robots or on literature review without field data. It would seem like the literature is lacking a deeper perspective, while at the same time, painting a wider picture of the domain itself. Therefore, this research investigated the development and experiences with robots that already exist and have been tested in real-world settings. The findings of the study summarized the literature on robots in nursing care, attitudes towards robots across countries and Japan’s strategy for further integrating robots into their society. Other results include real experience with the use of robots in nursing facilities and theories grounded in the ideas and thoughts behind the development of robots commonly used today. An experiment exploring empathy towards robots demonstrated the distinctiveness of robots, as compared to dolls, in enhanced empathy towards them. Two case studies captured views from university students and primary school pupils based on interaction with the humanoid robot Pepper. Pupils found Pepper to be useful and likable, while university students found the interaction to be fun, but frustrating at times. Based on the field studies, we could conclude that Japanese robot developers and researches recommend robots to be inferior to users in terms of intelligence and relationship, but also capable of easy interaction and ideally reading between lines in communication. In nursing care, robots are currently taking the role of pets (Paro and Qoobo), a child (Pepper, Paro, PALRO, RoBoHon, and Smibi) and even as a staff member (Pepper), capable of entertaining and accompanying elderly to help with mental well-being. There might be a current lack of ethical and safety standards for such robots. However, safety and ethical issues are considered by developers and professors in terms of privacy, deception, attachment, mechanical safety. Current robots have different levels of cognitive capacities depending on purpose and interaction style. Goals for the future include improvement in aspects such as intelligence, marketing strategies, and educating users on robots’ capabilities and limitations.Masteroppgave i informasjonsvitenskapINFO390MASV-IKTMASV-INF

iRobot : conceptualising SERVBOT for humanoid social robots

Services are intangible in nature and, as a result, it is often difficult to measure the quality of the service. The service is usually delivered by a human to a human customer and the service literature shows SERVQUAL can be used to measure the quality of the service. However, the use of social robots during the pandemic is speeding up the process of employing social roots in frontline service settings. An extensive review of the literature shows there is a lack of an empirical model to assess the perceived service quality provided by a social robot. Furthermore, the social robot literature highlights key differences between human service and social robots. For example, scholars have highlighted the importance of entertainment and engagement in the adoption of social robots in the service industry. However, it is unclear whether the SERVQUAL dimensions are appropriate to measure social robots’ service quality. This master’s project will conceptualise the SERVBOT model to assess a social robot’s service quality. It identifies reliability, responsiveness, assurance, empathy, and entertainment as the five dimensions of SERVBOT. Further, the research will investigate how these five factors influence emotional and social engagement and intention to use the social robot in a concierge service setting. To conduct the research, a 2 x 1 (CONTROL vs SERVBOT) x (Concierge) between-subject experiment was undertaken and a total of 232 responses were collected for both stages. The results indicate that entertainment has a positive influence on emotional engagement when service is delivered by a human concierge. Further, assurance had a positive influence on social engagement when a human concierge provided the service. When a social robot concierge delivered the service, empathy and entertainment both influenced emotional engagement, and assurance and entertainment impacted social engagement favourably. For both CONTROL (human concierge) and SERVBOT (social robot concierge), emotional and social engagement had a significant influence on intentions to use. This study is the first to propose the SERVBOT model to measure social robots’ service quality. The model provides a theoretical underpinning on the key service quality dimensions of a social robot and gives scholars and managers a method to track the service quality of a social robot. The study also extends the literature by exploring the key factors that influence the use of social robots (i.e., emotional and social engagement)

Applications of Affective Computing in Human-Robot Interaction: state-of-art and challenges for manufacturing

The introduction of collaborative robots aims to make production more flexible, promoting a greater interaction between humans and robots also from physical point of view. However, working closely with a robot may lead to the creation of stressful situations for the operator, which can negatively affect task performance. In Human-Robot Interaction (HRI), robots are expected to be socially intelligent, i.e., capable of understanding and reacting accordingly to human social and affective clues. This ability can be exploited implementing affective computing, which concerns the development of systems able to recognize, interpret, process, and simulate human affects. Social intelligence is essential for robots to establish a natural interaction with people in several contexts, including the manufacturing sector with the emergence of Industry 5.0. In order to take full advantage of the human-robot collaboration, the robotic system should be able to perceive the psycho-emotional and mental state of the operator through different sensing modalities (e.g., facial expressions, body language, voice, or physiological signals) and to adapt its behaviour accordingly. The development of socially intelligent collaborative robots in the manufacturing sector can lead to a symbiotic human-robot collaboration, arising several research challenges that still need to be addressed. The goals of this paper are the following: (i) providing an overview of affective computing implementation in HRI; (ii) analyzing the state-of-art on this topic in different application contexts (e.g., healthcare, service applications, and manufacturing); (iii) highlighting research challenges for the manufacturing sector