Theoretical Considerations and Development of a Questionnaire to Measure Trust in Automation

By Moritz Körber. 2018

356 citations recorded by the source corpus.

The increasing number of interactions with automated systems has sparked the interest of researchers in trust in automation because it predicts not only whether but also how an operator interacts with an automation. In this work, a theoretical model of trust in automation is established and the development and evaluation of a corresponding questionnaire (Trust in Automation, TiA) are described.

Subfields: Radiological and Ultrasound Technology, Social Psychology, Statistics and Probability

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Citations in the corpus

Making deep neural networks right for the right scientific reasons by interacting with their explanations (2020, methodology): “To assess the participant’s trust in the model’s skills we used the Trust in Automation Questionnaire (TiA) [24].”
Measurement of Trust in Automation: A Narrative Review and Reference Guide (2021, background): “High trust results in longer reaction times because over-reliance on the automation causes the operator to be unprepared to respond, requiring greater mental effort and duration to switch tasks (Beller et al., 2013; Helldin et al., 2013; Körber et al., 2018).”
Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty (2020, background): “Factors communities have a long history of studying trust in automation [74, 99, 106].”