Assisting People of Determination and the Elderly Using Social Robot: A Case Study

A technological innovation that has recently garnered attention in the literature is social humanoid robots' applications. Ever since their commercialization, social robots have been viewed as a valuable tool to assist individuals in their daily activities. As people grow older, their capabilities to accomplish everyday activities gradually deteriorate. Consequently, there is a pressing need for research on the positive benefits offered by humanoid robots. This paper explores the implications of a social robot, Zenbo, in the United Arab Emirates (UAE). We propose that the Zenbo be helpful in assisting vulnerable elderly populations, ordinary citizens, and People of Determination. This study can guide the UAE policymakers to allow elderly peoples and disabled individuals to use Zenbo to ensure their safety and well-being. This technological advancement can help transform the traditional support systems offered to the vulnerable populations in the Middle East

HRI – "In the wild” In Rural India: A Feasibility Study

This work was conducted to investigate the technological acceptance and social perception of a robot helper in a rural context. A feasibility study was carried out in a rural village in India with 11 participants with a water carrying task for the robot. A strong cultural influence was found in terms of gender perception of the robot, most participants perceived the robot’s gender as a female despite of the robot having a male’s voice. The overall social perception and usefulness of the robot was observed to be positive. We report some initial results and also some practical and logistical challenges while running such studies “in the wild” with rural subjects in this paper

Keep an eye on the task! How Gender Typicality of Tasks Influence Human–Robot Interactions

Kuchenbrandt D, Häring M, Eichberg J, Eyssel FA, André E. Keep an eye on the task! How Gender Typicality of Tasks Influence Human–Robot Interactions. International Journal of Social Robotics. 2014;6(3):417-427

Effects of Victim Gendering and Humanness on People’s Responses to the Physical Abuse of Humanlike Agents

With the deployment of robots in public realms, researchers are seeing more cases of abusive disinhibition towards robots. Because robots embody gendered identities, poor navigation of antisocial dynamics may reinforce or exacerbate gender-based marginalization. Consequently, it is essential for robots to recognize and effectively head off abuse. Given extensions of gendered biases to robotic agents, as well as associations between an agent\u27s human likeness and the experiential capacity attributed to it, we quasi-manipulated the victim\u27s humanness (human vs. robot) and gendering (via the inclusion of stereotypically masculine vs. feminine cues in their presentation) across four video-recorded reproductions of the interaction. Analysis from 422 participants, each of whom watched one of the four videos, indicates that intensity of emotional distress felt by an observer is associated with their gender identification and support for social stratification, along with the victim\u27s gendering—further underscoring the criticality of robots\u27 social intelligence

Investigating Older Adults\u27 Trust, Causal Attributions, and Perception of Capabilities in Robots as a Function of Robot Appearance, Task, and Reliability

The purpose of the current study was to examine the extent to which the appearance, task, and reliability of a robot is susceptible to stereotypic thinking. Stereotypes can influence the types of causal attributions that people make about the performance of others. Just as causal attributions may affect an individual’s perception of other people, it may similarly affect perceptions of technology. Stereotypes can also influence perceived capabilities of others. That is, in situations where stereotypes are activated, an individual’s perceived capabilities are typically diminished. The tendency to adjust perceptions of capabilities of others may translate into levels of trust placed in the individual’s abilities. A cross-sectional factorial survey using video vignettes was used to assess young adults’ and older adults’ attitudes toward a robot’s behavior and appearance. Trust and capability ratings of the robot were affected by participant age, reliability, and domain. Patterns of causal reasoning within the human-robot interaction (HRI) context differed from causal reasoning patterns found in human-human interaction, suggesting a major caveat in applying human theories of social cognition to technology

User Perceptions and Stereotypic Responses to Gender and Age of Voice Assistants

Technologies such as voiced automation can aid older adults aging in place by assisting with basic home and health tasks in daily routines. However, currently available voice assistants have a common design - they are vastly represented as young and female. Prior work has shown that humans apply stereotypes to human-computer interactions similarly to human-human interactions. When these stereotypes are activated, users may lose trust or confidence in the device or stop using it all together. The purpose of this study was to investigate if users can detect age and gender cues of voiced automation and to understand the extent to which gender, age, and reliability elicit stereotypic responses which were assessed using history-based trust. A series of health-related voice automation scenarios presented users with voice assistants varying in gender, age, and reliability. Results showed differences in age and gender perceptions across participant age groups but no differences for overall trust. A three-way interaction showed that when voiced automation reliability was low, participants rated the young female voice assistant as significantly more trustworthy than all other voice assistants. This work contributes to our understanding of how anthropomorphic characteristics like age and gender in emerging technologies can elicit varied trust responses from younger and older adults

Trusting Robocop: Gender-Based Effects on Trust of an Autonomous Robot

Little is known regarding public opinion of autonomous robots. Trust of these robots is a pertinent topic as this construct relates to one’s willingness to be vulnerable to such systems. The current research examined gender-based effects of trust in the context of an autonomous security robot. Participants (N = 200; 63% male) viewed a video depicting an autonomous guard robot interacting with humans using Amazon’s Mechanical Turk. The robot was equipped with a non-lethal device to deter non-authorized visitors and the video depicted the robot using this non-lethal device on one of the three humans in the video. However, the scenario was designed to create uncertainty regarding who was at fault – the robot or the human. Following the video, participants rated their trust in the robot, perceived trustworthiness of the robot, and their desire to utilize similar autonomous robots in several different contexts that varied from military use to commercial use to home use. The results of the study demonstrated that females reported higher trust and perceived trustworthiness of the robot relative to males. Implications for the role of individual differences in trust of robots are discussed

Keep an eye on the task! How gender typicality of tasks influence human-robot interactions

Kuchenbrandt D, Häring M, Eichberg J, Eyssel FA, André E. Keep an eye on the task! How gender typicality of tasks influence human-robot interactions. In: Ge SS, Khatib O, Cabibihan JJ, Simmons R, Williams MA, eds. Social robotics. Lecture Notes in Computer Science. Vol 7621. Berlin, Heidelberg: Springer; 2012: 448-457

Effects of Robot Facial Characteristics and Gender in Persuasive Human-Robot Interaction

The growing interest in social robotics makes it relevant to examine the potential of robots as persuasive agents and, more specifically, to examine how robot characteristics influence the way people experience such interactions and comply with the persuasive attempts by robots. The purpose of this research is to identify how the (ostensible) gender and the facial characteristics of a robot influence the extent to which people trust it and the psychological reactance they experience from its persuasive attempts. This paper reports a laboratory study where SociBot™, a robot capable of displaying different faces and dynamic social cues, delivered persuasive messages to participants while playing a game. In-game choice behavior was logged, and trust and reactance toward the advisor were measured using questionnaires. Results show that a robotic advisor with upturned eyebrows and lips (features that people tend to trust more in humans) is more persuasive, evokes more trust, and less psychological reactance compared to one displaying eyebrows pointing down and lips curled downwards at the edges (facial characteristics typically not trusted in humans). Gender of the robot did not affect trust, but participants experienced higher psychological reactance when interacting with a robot of the opposite gender. Remarkably, mediation analysis showed that liking of the robot fully mediates the influence of facial characteristics on trusting beliefs and psychological reactance. Also, psychological reactance was a strong and reliable predictor of trusting beliefs but not of trusting behavior. These results suggest robots that are intended to influence human behavior should be designed to have facial characteristics we trust in humans and could be personalized to have the same gender as the user. Furthermore, personalization and adaptation techniques designed to make people like the robot more may help ensure they will also trust the robot