A Meta-Analysis of Factors Influencing the Development of Trust in Automation: Implications for Human-Robot Interaction

Schaefer, Kristin E.; Billings, Deborah R.; Szalma, James L.; Adams, Jeffrey K.; Sanders, Tracy; Jessie, Y. C.; Hancock, Peter A.

doi:10.21236/ada607926

Cited by 41 publications

(38 citation statements)

References 135 publications

(182 reference statements)

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“…Factors Influencing the Calibration of Trust in Automation Lee and See (2004) define trust in automation as "the attitude that an agent will help to achieve an individual's goal in a situation characterized by uncertainty and vulnerability" (p. 51). The psychological process, in which trust in automation is built up prior and during the interaction with an automated system is subject to several theoretical reviews and frameworks (e.g., Lee and See, 2004;Schaefer et al, 2014;Hoff and Bashir, 2015) FIGURE 1 | Investigated relationship of personality, state anxiety and trust in automation. It is hypothesized that the relationship of depression, self-esteem, self-efficacy, and locus of control to initial learned trust in automation is mediated by the extent of an individual experience of anxiety at the time when a new and unfamiliar automated driving system is introduced.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

Scared to Trust? – Predicting Trust in Highly Automated Driving by Depressiveness, Negative Self-Evaluations and State Anxiety

Kraus¹,

Scholz²,

Meßner

et al. 2020

Front. Psychol.

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The advantages of automated driving can only come fully into play if these systems are used in an appropriate way, which means that they are neither used in situations they are not designed for (misuse) nor used in a too restricted manner (disuse). Trust in automation has been found to be an essential psychological basis for appropriate interaction with automated systems. Well-balanced system use requires a calibrated level of trust in correspondence with the actual ability of an automated system. As for these far-reaching implications of trust for safe and efficient system use, the psychological processes, in which trust is dynamically calibrated prior and during the use of automated technology, need to be understood. At this point, only a restricted body of research investigated the role of personality and emotional states for the formation of trust in automated systems. In this research, the role of the personality variables depressiveness, self-efficacy, self-esteem, and locus of control for the experience of anxiety before the first experience with a highly automated driving system were investigated. Additionally, the relationship of the investigated personality variables and anxiety to subsequent formation of trust in automation was investigated. In a driving simulator study, personality variables and anxiety were measured before the interaction with an automated system. Trust in the system was measured after participants drove with the system for a while. Trust in the system was significantly predicted by state anxiety and the personality characteristics self-esteem and selfefficacy. The relationships of self-esteem and self-efficacy were mediated by state anxiety as supported by significant specific indirect effects. While for depression the direct relationship with trust in automation was not found to be significant, an indirect effect through the experience of anxiety was supported. Locus of control did not show a significant association to trust in automation. The reported findings support the importance of considering individual differences in negative self-evaluations and anxiety when being introduced to a new automated system for individual differences in trust in automation. Implications for future research as well as implications for the design of automated technology in general and automated driving systems are discussed.

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Section: Theoretical Backgroundmentioning

confidence: 99%

Scared to Trust? – Predicting Trust in Highly Automated Driving by Depressiveness, Negative Self-Evaluations and State Anxiety

Kraus¹,

Scholz²,

Meßner

et al. 2020

Front. Psychol.

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“…Trust in a nonhuman agent's ability to support a given task was also shown to depend on the extent to which it was deemed appropriate to handle the situation (Liu, 2010), and to support the user to achieve his goals (Lee & Morray, 1992). In addition, trust in non-human agents is higher when they are perceived as specialized expert systems as op-posed to general-purpose novice systems (Shaefer et al, 2014;Koh & Sundar, 2010;Madhavan & Wiegmann, 2007).…”

Section: Introductionmentioning

confidence: 99%

Good advice is beyond all price, but what if it comes from a machine?

Hertz

Wiese

2019

Journal of Experimental Psychology: Applied

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As nonhuman agents become integrated into the workforce, the question becomes whether humans are willing to consider their advice, and to what extent advice-seeking depends on the perceived agent-task fit. To examine this, participants performed social and analytical tasks and received advice from human, robot, and computer agents in two conditions: in the Agent First condition, participants were first asked to choose advisors and were then informed which task to perform; in the Task First condition, they were first informed about the task and then asked to choose advisors. In the Agent First condition, we expected participants to prefer human to nonhuman advisors, and to subsequently trust their advice more if they were assigned the social as opposed to the analytical task. In the Task First condition, we expected advisor choices to be guided by stereotypical assumptions regarding the agents' expertise for the tasks, accompanied by higher trust in their suggestions. The findings indicate that in the Agent First condition, the human was chosen significantly more often than the machines, while in the Task First condition advisor choices were calibrated based on perceived agent-task fit. Trust was higher in the social task, but only showed variations with the human partner.

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“…For example, in social transactions, how and when one can place trust in such a system is a major issue, as mentioned earlier [24,36,39]. For humans, to truly trust and have confidence in someone else, one has to have an understanding of what motivates the other [47].…”

Section: Previous Work On Intrinsic Human Motivationmentioning

confidence: 99%

Intrinsic Motivation for Truly Autonomous Agents

Sun

2018

Foundations of Trusted Autonomy

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A Meta-Analysis of Factors Influencing the Development of Trust in Automation: Implications for Human-Robot Interaction

Cited by 41 publications

References 135 publications

Scared to Trust? – Predicting Trust in Highly Automated Driving by Depressiveness, Negative Self-Evaluations and State Anxiety

Scared to Trust? – Predicting Trust in Highly Automated Driving by Depressiveness, Negative Self-Evaluations and State Anxiety

Good advice is beyond all price, but what if it comes from a machine?

Intrinsic Motivation for Truly Autonomous Agents

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