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Full-Text Articles in Experimental Analysis of Behavior
The Effects Of Automation Transparency And Reliability On Task Shedding And Operator Trust, William Everett Lehman
The Effects Of Automation Transparency And Reliability On Task Shedding And Operator Trust, William Everett Lehman
Psychology Theses & Dissertations
Because automation use is common in many domains, understanding how to design it to optimize human-automation system performance is vital. Well-calibrated trust ensures good performance when using imperfect automation. Two factors that may jointly affect trust calibration are automation transparency and perceived reliability. Transparency information that explains automated processes and analyses to the operator may help the operator choose appropriate times to shed task control to automation. Because operator trust is positively correlated with automation use, behaviors such as task shedding to automation can indicate the presence of trust. This study used a 2 (reliability; between) × 3 (transparency; within) …
The Effects Of Automation Transparency And Ethical Outcomes On User Trust And Blame Towards Fully Autonomous Vehicles, Nathan Andrew Hatfield
The Effects Of Automation Transparency And Ethical Outcomes On User Trust And Blame Towards Fully Autonomous Vehicles, Nathan Andrew Hatfield
Psychology Theses & Dissertations
The current study examined the effect of automation transparency on user trust and blame during forced moral outcomes. Participants read through moral scenarios in which an autonomous vehicle did or did not convey information about its decision prior to making a utilitarian or non-utilitarian decision. Participants also provided moral acceptance ratings for autonomous vehicles and humans when making identical moral decisions.
It was expected that trust would be highest for utilitarian outcomes and blame would be highest for non-utilitarian outcomes. When the vehicle provided information about its decision, trust and blame were expected to increase. Results showed that moral outcome …