Social Conformity Effects on Trust in Simulation-Based Human-Robot Interaction

Volante, William G.; Sosna, Janine; Kessler, Theresa T.; Sanders, Tracy; Hancock, Peter A.

doi:10.1177/0018720818811190

Cited by 13 publications

(2 citation statements)

References 45 publications

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“…In terms of human-related factors, individual differences in personal attitudes and cognition may impact trust, and therefore team performance. Pre-existing negative attitudes toward robots have been shown to coincide with decreased ratings of trust in robots (Volante et al, 2019). Based on this, it is important to understand how attitudes toward robots impact performance and trust with different levels of autonomy.…”

Section: Trust In Human-autonomous Teamsmentioning

confidence: 99%

Maybe I Can Do Better Myself: The Impact of Automation Levels on HRI

Benton

McDonald

Sackett

et al. 2022

Proceedings of the Human Factors and Ergonomics Society Annual

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Although previous studies have developed scales to measure levels of robot autonomy and ways to quantify trust in human-robot teams, there is still much interest in determining how trust, individual differences, and levels of autonomy impact these teams. The primary objective of this study is to identify how pre-existing attitudes about robots, individual differences in normal cognition, and levels of robot autonomy affect performance, communication, and trust with a robot teammate. This study pairs participants with a robot teammate to compete against two robotic opponents in a simulated game of capture the flag. Game performance and interactions with the robot teammate will be collected as outcome measures. Subjective measures will include pre-existing negative attitudes toward robots (Nomura et al., 2006a) and trust (Schaefer, 2016).

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Section: Trust In Human-autonomous Teamsmentioning

confidence: 99%

Maybe I Can Do Better Myself: The Impact of Automation Levels on HRI

Benton

McDonald

Sackett

et al. 2022

Proceedings of the Human Factors and Ergonomics Society Annual

View full text Add to dashboard Cite

show abstract

“…Systems with sufficient intelligence to operate autonomously are difficult for the human operator to understand and anticipate, implying that tolerating ambiguity and complexity may be important for trust ( Matthews et al, 2016 ). In addition, some systems exert social agency, i.e., they can evaluate the status of the human operator and respond with teaming behaviors such as taking on additional tasks, signaling their goals and intended actions, and communicating their willingness to support the human ( Wang and Lewis, 2007 ; Chen and Barnes, 2014 ; Volante et al, 2019 ). Wynne and Lyons (2018) highlight the need for further research on humans’ perceptions of intelligent robots.…”

Section: Introductionmentioning

confidence: 99%

Trust in the Danger Zone: Individual Differences in Confidence in Robot Threat Assessments

et al. 2022

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Effective human–robot teaming (HRT) increasingly requires humans to work with intelligent, autonomous machines. However, novel features of intelligent autonomous systems such as social agency and incomprehensibility may influence the human’s trust in the machine. The human operator’s mental model for machine functioning is critical for trust. People may consider an intelligent machine partner as either an advanced tool or as a human-like teammate. This article reports a study that explored the role of individual differences in the mental model in a simulated environment. Multiple dispositional factors that may influence the dominant mental model were assessed. These included the Robot Threat Assessment (RoTA), which measures the person’s propensity to apply tool and teammate models in security contexts. Participants (N = 118) were paired with an intelligent robot tasked with making threat assessments in an urban setting. A transparency manipulation was used to influence the dominant mental model. For half of the participants, threat assessment was described as physics-based (e.g., weapons sensed by sensors); the remainder received transparency information that described psychological cues (e.g., facial expression). We expected that the physics-based transparency messages would guide the participant toward treating the robot as an advanced machine (advanced tool mental model activation), while psychological messaging would encourage perceptions of the robot as acting like a human partner (teammate mental model). We also manipulated situational danger cues present in the simulated environment. Participants rated their trust in the robot’s decision as well as threat and anxiety, for each of 24 urban scenes. They also completed the RoTA and additional individual-difference measures. Findings showed that trust assessments reflected the degree of congruence between the robot’s decision and situational danger cues, consistent with participants acting as Bayesian decision makers. Several scales, including the RoTA, were more predictive of trust when the robot was making psychology-based decisions, implying that trust reflected individual differences in the mental model of the robot as a teammate. These findings suggest scope for designing training that uncovers and mitigates the individual’s biases toward intelligent machines.

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A Systematic Review of Attitudes, Anxiety, Acceptance, and Trust Towards Social Robots

Naneva

Gou

Webb

et al. 2020

Int J of Soc Robotics

206

116

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As social robots become more common, there is a need to understand how people perceive and interact with such technology. This systematic review seeks to estimate people's attitudes toward, trust in, anxiety associated with, and acceptance of social robots; as well as factors that are associated with these beliefs. Ninety-seven studies were identified with a combined sample of over 13,000 participants and a standardized score was computed for each in order to represent the valence (positive, negative, or neutral) and magnitude (on a scale from 1 to − 1) of people's beliefs about robots. Potential moderating factors such as the robots' domain of application and design, the type of exposure to the robot, and the characteristics of potential users were also investigated. The findings suggest that people generally have positive attitudes towards social robots and are willing to interact with them. This finding may challenge some of the existing doubt surrounding the adoption of robotics in social domains of application but more research is needed to fully understand the factors that influence attitudes. Keywords Attitudes toward technology • Social robots • Systematic review • Human-robot interaction Stanislava Naneva and Marina Sarda Gou have contributed equally to this work.

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Social Conformity Effects on Trust in Simulation-Based Human-Robot Interaction

Cited by 13 publications

References 45 publications

Maybe I Can Do Better Myself: The Impact of Automation Levels on HRI

Maybe I Can Do Better Myself: The Impact of Automation Levels on HRI

Trust in the Danger Zone: Individual Differences in Confidence in Robot Threat Assessments

A Systematic Review of Attitudes, Anxiety, Acceptance, and Trust Towards Social Robots

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