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

Drama, a connectionist model for robot learning: experiments on grounding communication through imitation in autonomous robots

The present dissertation addresses problems related to robot learning from demonstra¬ tion. It presents the building of a connectionist architecture, which provides the robot with the necessary cognitive and behavioural mechanisms for learning a synthetic lan¬ guage taught by an external teacher agent. This thesis considers three main issues: 1) learning of spatio-temporal invariance in a dynamic noisy environment, 2) symbol grounding of a robot's actions and perceptions, 3) development of a common symbolic representation of the world by heterogeneous agents.We build our approach on the assumption that grounding of symbolic communication creates constraints not only on the cognitive capabilities of the agent but also and especially on its behavioural capacities. Behavioural skills, such as imitation, which allow the agent to co-ordinate its actionn to that of the teacher agent, are required aside to general cognitive abilities of associativity, in order to constrain the agent's attention to making relevant perceptions, onto which it grounds the teacher agent's symbolic expression. In addition, the agent should be provided with the cognitive capacity for extracting spatial and temporal invariance in the continuous flow of its perceptions. Based on this requirement, we develop a connectionist architecture for learning time series. The model is a Dynamical Recurrent Associative Memory Architecture, called DRAMA. It is a fully connected recurrent neural network using Hebbian update rules. Learning is dynamic and unsupervised. The performance of the architecture is analysed theoretically, through numerical simulations and through physical and simulated robotic experiments. Training of the network is computationally fast and inexpensive, which allows its implementation for real time computation and on-line learning in a inexpensive hardware system. Robotic experiments are carried out with different learning tasks involving recognition of spatial and temporal invariance, namely landmark recognition and prediction of perception-action sequence in maze travelling.The architecture is applied to experiments on robot learning by imitation. A learner robot is taught by a teacher agent, a human instructor and another robot, a vocabulary to describe its perceptions and actions. The experiments are based on an imitative strategy, whereby the learner robot reproduces the teacher's actions. While imitating the teacher's movements, the learner robot makes similar proprio and exteroceptions to those of the teacher. The learner robot grounds the teacher's words onto the set of common perceptions they share. We carry out experiments in simulated and physical environments, using different robotic set-ups, increasing gradually the complexity of the task. In a first set of experiments, we study transmission of a vocabulary to designate actions and perception of a robot. Further, we carry out simulation studies, in which we investigate transmission and use of the vocabulary among a group of robotic agents. In a third set of experiments, we investigate learning sequences of the robot's perceptions, while wandering in a physically constrained environment. Finally, we present the implementation of DRAMA in Robota, a doll-like robot, which can imitate the arms and head movements of a human instructor. Through this imitative game, Robota is taught to perform and label dance patterns. Further, Robota is taught a basic language, including a lexicon and syntactical rules for the combination of words of the lexicon, to describe its actions and perception of touch onto its body

How robots change our minds

Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2009.Includes bibliographical references (p. 169-174).This thesis explores the extent to which socially capable humanoid robots have the potential to influence human belief, perception and behavior. Sophisticated computational systems coupled with human-like form and function render such robots as potentially powerful forms of persuasive technology. Currently, there is very little understanding of the persuasive potential of such machines. As personal robots become a reality in our immediate environment, a better understanding of the mechanisms behind, and the capabilities of, their ability to influence, is becoming increasingly important. This thesis proposes some guiding principles by which to qualify persuasion. A study was designed in which the MDS (Mobile Dexterous Social) robotic platform was used to solicit visitors for donations at the Museum of Science in Boston. The study tests some nonverbal behavioral variables known to change persuasiveness in humans, and measures their effect in human-robot interaction. The results of this study indicate that factors such as robot-gender, subject-gender, touch, interpersonal distance, and the perceived autonomy of the robot, have a huge impact on the interaction between human and robot, and must be taken into consideration when designing sociable robots. This thesis applies the term persuasive robotics to define and test the theoretical and practical implications for robot-triggered changes in human attitude and behavior. Its results provide for a vast array of speculations with regard to what practical applications may become available using this framework.by Michael Steven Siegel.S.M

Do People Change their Behavior when the Handler is next to the Robot?

It is increasingly common for people to work alongside robots in a variety of situations. When a robot is completing a task, the handler of the robot may be present. It is important to know how people interact with the robot when the handler is next to the robot. Our study focuses on whether handler’s presence can affect human’s behavior toward the robot. Our experiment targets two different scenarios (handler present and handler absent) in order to find out human’s behavior change toward the robot. Results show that in the handler present scenario, people are less willing to interact with the robot. However, when people do interact with the robot, they tend to interact with both the handler and the robot. This suggests that researchers should consider the presence of a handler when designing for human-robot interactions

Humanization of robots: is it really such a good idea?

The aim of this review was to examine the pros and cons of humanizing social robots following a psychological perspective. As such, we had six goals. First, we defined what social robots are. Second, we clarified the meaning of humanizing social robots. Third, we presented the theoretical backgrounds for promoting humanization. Fourth, we conducted a review of empirical results of the positive effects and the negative effects of humanization on human–robot interaction (HRI). Fifth, we presented some of the political and ethical problems raised by the humanization of social robots. Lastly, we discussed the overall effects of the humanization of robots in HRI and suggested new avenues of research and development.info:eu-repo/semantics/publishedVersio

Imaginative play with blended reality characters

Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 132-137).The idea and formative design of a blended reality character, a new class of character able to maintain visual and kinetic continuity between the fully physical and fully virtual; the technical underpinnings of its unique blended physical and digital play context and the evaluation of its impact on children's play are the contents of this thesis. A play test study with thirty-four children aged three and a half to seven was conducted using non-reactive, unobtrusive observational methods and a validated evaluation instrument. Our claim is that young children have accepted the idea, persistence and continuity of blended reality characters. Furthermore, we found that children are more deeply engaged with blended reality characters and are more fully immersed in blended reality play as co-protagonists in the experience, in comparison to interactions with strictly screen-based representations. As substantiated through the use of quantitative and qualitative analysis of drawings and verbal utterances, the study showed that young children produce longer, detailed and more imaginative descriptions of their experiences following blended reality play. The desire to continue engaging in blended reality play as expressed by children's verbal requests to revisit and extend their play time with the character positively affirms the potential for the development of an informal learning platform with sustained appeal to young children.by David Yann Robert.S.M

An Edutainment Robotics System with Online Self-learning

東京都立大

Creating robotic characters for long-term interaction

Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 177-181).Researchers studying ways in which humans and robots interact in social settings have a problem: they don't have a robot to use. There is a need for a socially expressive robot that can be deployed outside of a laboratory and support remote operation and data collection. This work aims to fill that need with DragonBot - a platform for social robotics specifically designed for long-term interactions. This thesis is divided into two parts. The first part describes the design and implementation of the hardware, software, and aesthetics of the DragonBot-based characters. Through the use of a mobile phone as the robot's primary computational device, we aim to drive down the hardware cost and increase the availability of robots "in the wild". The second part of this work takes an initial step towards evaluating DragonBot's effectiveness through interactions with children. We describe two different teleoperation interfaces for allowing a human to control DragonBot's behavior differing amounts of autonomy by the robot. A human subject study was conducted and these interfaces were compared through a sticker sharing task between the robot and children aged four to seven. Our results show that when a human operator is able to focus on the social portions of an interaction and the robot is given more autonomy, children treat the character more like a peer. This is indicated by the fact that more children re-engaged the robot with the higher level of autonomy when they were asked to split up stickers between the two participants.by Adam Setapen.S.M

Conversational affective social robots for ageing and dementia support

Socially assistive robots (SAR) hold significant potential to assist older adults and people with dementia in human engagement and clinical contexts by supporting mental health and independence at home. While SAR research has recently experienced prolific growth, long-term trust, clinical translation and patient benefit remain immature. Affective human-robot interactions are unresolved and the deployment of robots with conversational abilities is fundamental for robustness and humanrobot engagement. In this paper, we review the state of the art within the past two decades, design trends, and current applications of conversational affective SAR for ageing and dementia support. A horizon scanning of AI voice technology for healthcare, including ubiquitous smart speakers, is further introduced to address current gaps inhibiting home use. We discuss the role of user-centred approaches in the design of voice systems, including the capacity to handle communication breakdowns for effective use by target populations. We summarise the state of development in interactions using speech and natural language processing, which forms a baseline for longitudinal health monitoring and cognitive assessment. Drawing from this foundation, we identify open challenges and propose future directions to advance conversational affective social robots for: 1) user engagement, 2) deployment in real-world settings, and 3) clinical translation

User Experience Design and Evaluation of Persuasive Social Robot As Language Tutor At University : Design And Learning Experiences From Design Research

Human Robot Interaction (HRI) is a developing field where research and innovation are progressing. One domain where Human Robot Interaction has focused is in the educational sector. Various research has been conducted in education field to design social robots with appropriate design guidelines derived from user preferences, context, and technology to help students and teachers to foster their learning and teaching experience. Language learning has become popular in education due to students receiving opportunities to study and learn any interested subjects in any language in their preferred universities around the world. Thus, being the reason behind the research of using social robots in language learning and teaching in education field. To this context this thesis explored the design of language tutoring robot for students learning Finnish language at university. In language learning, motivation, the learning experience, context, and user preferences are important to be considered. This thesis focuses on the Finnish language learning students through language tutoring social robot at Tampere University. The design research methodology is used to design the persuasive language tutoring social robot teaching Finnish language to the international students at Tampere University. The design guidelines and the future language tutoring robot design with their benefits are formed using Design Research methodology. Elias Robot, a language tutoring application designed by Curious Technologies, Finnish EdTech company was used in the explorative user study. The user study involved Pepper, Social robot along with the Elias robot application using Mobile device technology. The user study was conducted in university, the students include three male participants and four female participants. The aim of the study was to gather the design requirements based on learning experiences from social robot tutor. Based on this study findings and the design research findings, the future language tutoring social robot was co-created through co design workshop. Based on the findings from Field study, user study, technology acceptance model findings, design research findings, student interviews, the persuasive social robot language tutor was designed. The findings revealed all the multi modalities are required for the efficient tutoring of persuasive social robots and the social robots persuade motivation with students to learn the language. The design implications were discussed, and the design of social robot tutor are created through design scenarios