A roadmap for developing team trust metrics for human-autonomy teams

Schaefer, Kristin E.; Perelman, Brandon S.; Gremillion, Gregory M.; Marathe, Amar R.; Metcalfe, J. Stanley

doi:10.1016/b978-0-12-819472-0.00012-5

Cited by 10 publications

(11 citation statements)

References 57 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…64 There are not only emotional effects, as Mathur and Reichling showed through an “investment game” experiment that subtle social cues in the appearance of a robot’s face even affected people’s judgment of the robot’s trustworthiness. 27…”

Section: Discussionmentioning

confidence: 99%

“…23 In the appearance design of social robots, making robots look cuter and more trustworthy can also improve the HRI experience. 19,24 –28 For example, Natarajan and Gombolay found that behavior and anthropomorphism of the agent are the most significant factors in predicting trust in and compliance with the robot. 26 BSE can provide people with a cute and innocent impression, thereby enhancing their trustworthiness.…”

Section: Introductionmentioning

confidence: 99%

“…33 This also brings about the corresponding problem, that is, how to accurately and objectively measure people’s feelings of trustworthiness of robots is important to designers. Schaefer 27,28 aimed to establish a reliable and effective subjective scale to specifically measure human–machine trust that can be applied to multiple robotic fields, developing a 40-item trust scale to provide more sensitive and accurate trust scores which can be used in many robot applications from industry to military to everyday robots. Also, one study showed that behavior and personification are the most important factors predicting trust in and obedience to robots.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Research on the influence of the baby schema effect on the cuteness and trustworthiness of social robot faces

Chen

Jia

2023

International Journal of Advanced Robotic Systems

View full text Add to dashboard Cite

Exploring people’s attitudes toward the appearance design of social robots in a low-cost and efficient way, and enhancing the experience of human–robot interaction have always been topics of concern for robot developers and interaction designers. This study aimed to explore the influence of the baby schema effect on users’ perceptions of cuteness and trustworthiness pertinent to social robot faces through two experiments. Experiment 1 used 100 uniformly processed pictures of robot faces in the real world to help explore the linear relationship among the degree of baby face, cuteness, and trustworthiness, and received a total of 98 valid questionnaires via the Internet. Experiment 2 was a 5 × 3 within-subjects factorial design. The research variables were robot type (i.e. MAKI, RoboThespian, Flobi, Pepper, and iCat) and baby schema (low schema, uncontrolled, and high schema); their impact on users’ perceptions of cuteness and trustworthiness was investigated. A total of 175 valid questionnaires were collected via the Internet. The generated results are as follows: (1) The degree of baby face and perceived emotion of social robot faces had a positive impact on trustworthiness for most real-world robots. (2) This study obtained the correlation formula of baby face, cuteness, and trustworthiness from a quantitative point of view, thus providing a reference for research on the related credibility of communication robots. (3) In general, baby schema effect also existed in the cuteness evaluation of most real-world robots. Faces with high schema were considered cuter and more trustworthy than uncontrolled or low schema faces. (4) Robot type and baby schema had a significant interaction with cuteness and trustworthiness. (5) However, for certain types of robots, baby schema effect may also have a counter-effect, that is, an overly high baby schema may reduce users’ perceptions of the cuteness and trustworthiness of social robots.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Research on the influence of the baby schema effect on the cuteness and trustworthiness of social robot faces

Chen

Jia

2023

International Journal of Advanced Robotic Systems

View full text Add to dashboard Cite

show abstract

“…The subjective measures were trust, measured using the Schaefer 14-item trust scale ( Schaefer, 2013 ), and user satisfaction, measured using a four-item scale adapted from the PARADISE evaluation framework ( Walker et al, 1997 ).…”

Section: Methodsmentioning

confidence: 99%

“…Participants completed a trust questionnaire after each condition. We used the 14-item trust scale ( Schaefer, 2013 ), which yields a score free to vary from 0 to 100 and is continuous data representing user trust in the robot. This 14-item scale consists of a subset of items from, and positively correlating with, the 40-item scale by the same author.…”

Section: Methodsmentioning

confidence: 99%

Seeing eye to eye: trustworthy embodiment for task-based conversational agents

Robb,

Lopes,

Ahmad

et al. 2023

Front. Robot. AI

View full text Add to dashboard Cite

Smart speakers and conversational agents have been accepted into our homes for a number of tasks such as playing music, interfacing with the internet of things, and more recently, general chit-chat. However, they have been less readily accepted in our workplaces. This may be due to data privacy and security concerns that exist with commercially available smart speakers. However, one of the reasons for this may be that a smart speaker is simply too abstract and does not portray the social cues associated with a trustworthy work colleague. Here, we present an in-depth mixed method study, in which we investigate this question of embodiment in a serious task-based work scenario of a first responder team. We explore the concepts of trust, engagement, cognitive load, and human performance using a humanoid head style robot, a commercially available smart speaker, and a specially developed dialogue manager. Studying the effect of embodiment on trust, being a highly subjective and multi-faceted phenomena, is clearly challenging, and our results indicate that potentially, the robot, with its anthropomorphic facial features, expressions, and eye gaze, was trusted more than the smart speaker. In addition, we found that embodying a conversational agent helped increase task engagement and performance compared to the smart speaker. This study indicates that embodiment could potentially be useful for transitioning conversational agents into the workplace, and further in situ, “in the wild” experiments with domain workers could be conducted to confirm this.

show abstract

Autonomous Systems and Technology Resistance: New Tools for Monitoring Acceptance, Trust, and Tolerance

Cappuccio,

Galliott,

Eyssel

et al. 2023

Int J of Soc Robotics

View full text Add to dashboard Cite

We introduce the notion of Tolerance for autonomous artificial agents (and its antithetical concept, Intolerance), motivating its theoretical adoption in the fields of social robotics and human—agent interaction, where it can effectively complement two contiguous, but essentially distinct, constructs—Acceptance and Trust—that are broadly used by researchers. We offer a comprehensive conceptual model of Tolerance, construed as a user’s insusceptibility or resilience to Autonomy Estrangement (i.e., the uncanny sense of isolation and displacement experienced by the humans who believe, for right or wrong reasons, that robots can subvert and/or control their lives). We also refer to Intolerance to indicate the opposite property, that is the user’s susceptibility or proneness to Autonomy Estrangement. Thus, Tolerance and Intolerance are inverse representations of the same phenomenological continuum, with Intolerance increasing when Tolerance decreases and vice versa. While Acceptance and Trust measure how the user’s interaction with a particular robot is satisfying and efficacious, the dyad Tolerance/Intolerance reflects how the user’s attitude is affected by deeply held normative beliefs about robots in general. So defined, a low Tolerance (that is a high Intolerance) is expected to correlate to antagonistic responses toward the prospect of adoption: specifically, Intolerant attitudes predict the kind of anxious and hostile behaviours toward Agents that originate from the concerns that autonomous systems could deeply disrupt the lives of humans (affecting their work cultures, ways of living, systems of values, etc.) or dominate them (making humans redundant, undermining their authority, threatening their uniqueness, etc.). Thus, Negative beliefs and worldviews about Agents are the cause of the Intolerant attitude toward Agents, which predicts Autonomy Estrangement, which in turn correlates to low Adoption Propensity and avoidance and rejection behaviours.

show abstract

A roadmap for developing team trust metrics for human-autonomy teams

Cited by 10 publications

References 57 publications

Research on the influence of the baby schema effect on the cuteness and trustworthiness of social robot faces

Research on the influence of the baby schema effect on the cuteness and trustworthiness of social robot faces

Seeing eye to eye: trustworthy embodiment for task-based conversational agents

Autonomous Systems and Technology Resistance: New Tools for Monitoring Acceptance, Trust, and Tolerance

Contact Info

Product

Resources

About