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Effects of information source, pedigree, and reliability on operator interaction with decision support systems
Poornima Madhavan1, Douglas A Wiegmann
1University of Illinois at Urbana-Champaign, Champaign, Illinois, USA. madhavan@andrew.cmu.edu
Human Factors
|October 6, 2007
Summary
Preconceived beliefs about automation impact how operators use decision aids. Trust in automation varies, with expert automation sometimes leading to decreased reliance after errors, influencing optimal human-automation interaction.
Area of Science:
- Human-Computer Interaction
- Automation Psychology
- Decision Support Systems
Background:
- Automation biases influence human interaction with automated systems.
- Differentiating preconceived vs. post hoc biases is crucial for understanding advice acceptance.
Purpose of the Study:
- To examine operators' perceptions of decision aids.
- To investigate how preconceived and post hoc biases affect advice acceptance from automation.
Main Methods:
- Study 1: Assessed trust and reliability perceptions of human vs. automation (expert/novice) based on descriptions.
- Study 2: Evaluated post hoc trust, reliability, and dependence after experiencing automation reliability (90%/70%) in a task.
Main Results:
- Automation perceived as more reliable than humans initially.
- Trust varied: automated novices trusted more, but human experts trusted more than automated experts.
- Post hoc, perceived reliability depended on expertise, while trust favored automation; novice automation acceptance was higher, but expert automation errors reduced reliance.
Conclusions:
- Preconceived expectations significantly influence the utilization of automation in real-world tasks.
- Findings offer a basis for developing optimal user interaction models and trust frameworks for decision support systems.
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