The Choice to Use Automation: Improvements from Evidence Accumulation.
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| Title: | The Choice to Use Automation: Improvements from Evidence Accumulation. |
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| Authors: | Patton, Colleen E. (AUTHOR), Clegg, Benjamin A. (AUTHOR), Davis, Blake C. (AUTHOR), Caglar, Turgay (AUTHOR), Siebert, Caspian (AUTHOR), Blanchard, Nathaniel (AUTHOR) |
| Source: | International Journal of Human-Computer Interaction. Oct2025, Vol. 41 Issue 19, p12014-12031. 18p. |
| Subjects: | Automation, Machine learning, Self-confidence, Decision support systems, Acquisition of data, Decision making, Compliant behavior |
| Abstract: | This study examined discretionary automation – the choice to engage optional, automated support. In a dynamic decision-making task, after manual and aided trials, participants chose whether to engage a machine learning decision aid. The aid improved performance but participants frequently disused automation and lagged in compliance. Experiment 2 forced greater evidence accumulation, improving compliance, automation use, and performance. Experiment 3 required an initial judgment coupled with subsequent evidence accumulation. This reduced automation use but retained higher levels of compliance and performance. Across experiments, trust in automation and self-confidence influenced use decisions, but task difficulty had little impact. Implications for human-automation systems are discussed. [ABSTRACT FROM AUTHOR] |
| Copyright of International Journal of Human-Computer Interaction is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Psychology and Behavioral Sciences Collection |
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| Abstract: | This study examined discretionary automation – the choice to engage optional, automated support. In a dynamic decision-making task, after manual and aided trials, participants chose whether to engage a machine learning decision aid. The aid improved performance but participants frequently disused automation and lagged in compliance. Experiment 2 forced greater evidence accumulation, improving compliance, automation use, and performance. Experiment 3 required an initial judgment coupled with subsequent evidence accumulation. This reduced automation use but retained higher levels of compliance and performance. Across experiments, trust in automation and self-confidence influenced use decisions, but task difficulty had little impact. Implications for human-automation systems are discussed. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 10447318 |
| DOI: | 10.1080/10447318.2025.2452189 |
