Heather Heimbaugh's research while affiliated with University of Missouri - St. Louis and other places

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Publications (1)


I Trust It, but I Don't Know Why: Effects of Implicit Attitudes Toward Automation on Trust in an Automated System
  • Article

June 2013

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711 Reads

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243 Citations

Human Factors The Journal of the Human Factors and Ergonomics Society

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Heather Heimbaugh

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Jennifer LaChapell

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Deborah Lee

This study is the first to examine the influence of implicit attitudes toward automation on users' trust in automation. Past empirical work has examined explicit (conscious) influences on user level of trust in automation but has not yet measured implicit influences. We examine concurrent effects of explicit propensity to trust machines and implicit attitudes toward automation on trust in an automated system. We examine differential impacts of each under varying automation performance conditions (clearly good, ambiguous, clearly poor). Participants completed both a self-report measure of propensity to trust and an Implicit Association Test measuring implicit attitude toward automation, then performed an X-ray screening task. Automation performance was manipulated within-subjects by varying the number and obviousness of errors. Explicit propensity to trust and implicit attitude toward automation did not significantly correlate. When the automation's performance was ambiguous, implicit attitude significantly affected automation trust, and its relationship with propensity to trust was additive: Increments in either were related to increases in trust. When errors were obvious, a significant interaction between the implicit and explicit measures was found, with those high in both having higher trust. Implicit attitudes have important implications for automation trust. Users may not be able to accurately report why they experience a given level of trust. To understand why users trust or fail to trust automation, measurements of implicit and explicit predictors may be necessary. Furthermore, implicit attitude toward automation might be used as a lever to effectively calibrate trust.

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Citations (1)


... Still, from a legal perspective, and consistent with the definition provided regarding being informed, if the test driver had been watching the road rather than being on their phone, then they could have seen the pedestrian and taken control of the vehicle and averted the accident. The legal maneuver reveals that the driver was 'cooked', the human driver was expected to behave in a way that was difficult and unrealistic for a reasonable human to do -and over 70 years of human factors research on automation bias would support this (Endsley, 2017;Hoff & Bashir, 2015;Lee & See, 2004;Merritt et al., 2013). Human attention tends to wander when they are not actively engaged in a task. ...

Reference:

Bad, Mad, and Cooked
I Trust It, but I Don't Know Why: Effects of Implicit Attitudes Toward Automation on Trust in an Automated System
  • Citing Article
  • June 2013

Human Factors The Journal of the Human Factors and Ergonomics Society