More Like this

1. Finding “H” in HRI: Examining Human Personality Traits, Robotic Anthropomorphism, and Robot Likeability in Human-Robot Interaction

   Arora, A. S.; Fleming, M.; Arora, A.; Taras, V.; Xu, J. (January 2021, International journal of intelligent information technologies)

   null (Ed.)

   The study examines the relationship between the big five personality traits (extroversion, agreeableness, conscientiousness, neuroticism, and openness) and robot likeability and successful HRI implementation in varying human-robot interaction (HRI) situations. Further, this research investigates the influence of human-like attributes in robots (a.k.a. robotic anthropomorphism) on the likeability of robots. The research found that robotic anthropomorphism positively influences the relationship between human personality variables (e.g., extraversion and agreeableness) and robot likeability in human interaction with social robots. Further, anthropomorphism positively influences extraversion and robot likeability during industrial robotic interactions with humans. Extraversion, agreeableness, and neuroticism were found to play a significant role. This research bridges the gap by providing an in-depth understanding of the big five human personality traits, robotic anthropomorphism, and robot likeability in social-collaborative robotics. 

   more » « less
2. The Dynamics of Trust and Verbal Anthropomorphism in Human-Autonomy Teaming

   https://doi.org/10.1109/ICHMS53169.2021.9582655  

   Cohen, Myke C.; Demir, Mustafa; Chiou, Erin K.; Cooke, Nancy J. (September 2021, 2021 IEEE 2nd International Conference on Human-Machine Systems (ICHMS))

   Trust in autonomous teammates has been shown to be a key factor in human-autonomy team (HAT) performance, and anthropomorphism is a closely related construct that is underexplored in HAT literature. This study investigates whether perceived anthropomorphism can be measured from team communication behaviors in a simulated remotely piloted aircraft system task environment, in which two humans in unique roles were asked to team with a synthetic (i.e., autonomous) pilot agent. We compared verbal and self-reported measures of anthropomorphism with team error handling performance and trust in the synthetic pilot. Results for this study show that trends in verbal anthropomorphism follow the same patterns expected from self-reported measures of anthropomorphism, with respect to fluctuations in trust resulting from autonomy failures. 

   more » « less
3. Applying Service-Dominant Logic and Conversation Management Principles to Social Robotics for Autism Spectrum Disorder

   https://doi.org/10.4018/IJIIT.296240  

   Arora, Anshu Saxena; Parnell, Chevell; Arora, Amit (January 2022, International Journal of Intelligent Information Technologies)

   Anthropomorphism in social robots amplifies the big five human personality traits (extraversion, conscientiousness, neuroticism, openness to experience, and agreeableness), consequently aiding with the social motivation needs of consumers (especially individuals with autism spectrum disorder or ASD). According to the social motivation theory of autism, consumers with ASD show deficits in orienting toward social stimuli, engaging with humans, and maintaining social relations. Robotic anthropomorphism has been found to be positively related to the big five human personality types and robot likeability in human-robot interaction (HRI) situations. This research focuses on the conversational approach of social robotics using service-dominant approach. Conversation-based perspectives have been studied extensively in organizational and management literature; however, these perspectives have not been utilized in the context of social robots, HRI, and autism. 

   more » « less
4. CONFIDANT: A Privacy Controller for Social Robots

   https://doi.org/10.1109/HRI53351.2022.9889540  

   Tang, Brian; Sullivan, Dakota; Cagiltay, Bengisu; Chandrasekaran, Varun; Fawaz, Kassem; Mutlu, Bilge (January 2022, Proceedings of the 2022 ACM/IEEE International Conference on Human-Robot Interaction)

   As social robots become increasingly prevalent in day-to-day environments, they will participate in conversations and appropriately manage the information shared with them. However, little is known about how robots might appropriately discern the sensitivity of information, which has major implications for human-robot trust. As a first step to address a part of this issue, we designed a privacy controller, CONFIDANT, for conversational social robots, capable of using contextual metadata (e.g., sentiment, relationships, topic) from conversations to model privacy boundaries. Afterwards, we conducted two crowdsourced user studies. The first study (n = 174) focused on whether a variety of human-human interaction scenarios were perceived as either private/sensitive or non-private/non-sensitive. The findings from our first study were used to generate association rules. Our second study (n = 95) evaluated the effectiveness and accuracy of the privacy controller in human-robot interaction scenarios by comparing a robot that used our privacy controller against a baseline robot with no privacy controls. Our results demonstrate that the robot with the privacy controller outperforms the robot without the privacy controller in privacy-awareness, trustworthiness, and social-awareness. We conclude that the integration of privacy controllers in authentic human-robot conversations can allow for more trustworthy robots. This initial privacy controller will serve as a foundation for more complex solutions. 

   more » « less
5. Why Should We Gender?: The Effect of Robot Gendering and Occupational Stereotypes on Human Trust and Perceived Competency

   https://doi.org/10.1145/3319502.3374778  

   Bryant, De'Aira; Borenstein, Jason; Howard, Ayanna (March 2020, HRI '20: Proceedings of the 2020 ACM/IEEE International Conference on Human-Robot Interaction)

   The attribution of human-like characteristics onto humanoid robots has become a common practice in Human-Robot Interaction by designers and users alike. Robot gendering, the attribution of gender onto a robotic platform via voice, name, physique, or other features is a prevalent technique used to increase aspects of user acceptance of robots. One important factor relating to acceptance is user trust. As robots continue to integrate themselves into common societal roles, it will be critical to evaluate user trust in the robot's ability to perform its job. This paper examines the relationship among occupational gender-roles, user trust and gendered design features of humanoid robots. Results from the study indicate that there was no significant difference in the perception of trust in the robot's competency when considering the gender of the robot. This expands the findings found in prior efforts that suggest performance-based factors have larger influences on user trust than the robot's gender characteristics. In fact, our study suggests that perceived occupational competency is a better predictor for human trust than robot gender or participant gender. As such, gendering in robot design should be considered critically in the context of the application by designers. Such precautions would reduce the potential for robotic technologies to perpetuate societal gender stereotypes. 

   more » « less