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I trust it, but I don't know why: effects of implicit attitudes toward automation on trust in an automated system
Stephanie M Merritt1, Heather Heimbaugh, Jennifer LaChapell
1Department of Psychology, University of Missouri-St. Louis, 421 Stadler Hall, 8001 Natural Bridge Road, St. Louis, MO 63121, USA. merritts@umsl.edu
Objective:
This study is the first to examine the influence of implicit attitudes toward automation on users' trust in automation.
Background:
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).
Method:
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.
Results:
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.
Conclusion:
Implicit attitudes have important implications for automation trust.
Application:
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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