Automation Bias and Errors: Are Crews Better Than Individuals?
By Linda J. Skitka, K. Mosier, Mark Burdick, Bonnie Rosenblatt. 2000
122 citations recorded by the source corpus.
Subfields: Management Science and Operations Research, Radiological and Ultrasound Technology, Social Psychology
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Management Science and Operations Research
- Dietrich Manzey
- Suresh Venkatasubramanian
- Raja Parasuraman
- Sorelle A. Friedler
- D. boyd
- Stephen H. Fairclough
In Radiological and Ultrasound Technology
- Wendy A. Rogers
- Arthur D. Fisk
- Sara E. McBride
- Dietrich Manzey
- Raja Parasuraman
- Barry Strauch
- Jennifer Elin Bahner
- Anke-Dorothea Hüper
In Social Psychology
- Sara E. McBride
- Wendy A. Rogers
- Arthur D. Fisk
- Dietrich Manzey
- Barry Strauch
- Raja Parasuraman
- Enrico W. Coiera
- David Lyell
Citations in the corpus
- Fairness and Abstraction in Sociotechnical Systems (2019, background): “Different judges might exhibit automation bias [16, 62], deviate from recommendations in biased ways, or ignore them entirely.”
- Automation bias and verification complexity: a systematic review (2017, background): “05 Not reported Waypoints task (37) 144 students 4 trials P> .”
- Misuse of automated decision aids: Complacency, automation bias and the impact of training experience (2008, methodology): “Skitka et al. (2000a) investigated the effect of social accountability on automation bias and automation verification behavior when using an automated monitoring aid.”
- Complacency and Bias in Human Use of Automation: An Attentional Integration (2010, result): “…available knowledge about the impact of task context factors on automation bias, thus far, has been obtained in a series of studies conducted by Mosier, Skitka, and colleagues (Mosier, Skitka, Dunbar, & McDonnell, 2001; Skitka, Mosier, & Burdick, 2000; Skitka, Mosier, Burdick, & Rosenblatt, 2000).”
- I Think I Get Your Point, AI! The Illusion of Explanatory Depth in Explainable AI (2021, background): “Even though the IOED itself received little attention in the context of intelligent systems and XAI, there is prior research on cognitive biases of explanations from intelligent systems investigating automation [9, 31, 40, 49, 52], anchoring [19, 27, 57], framing [26], and confirmation biases [23, 5”
- The Automation-by-Expertise-by-Training Interaction (2017, background): “Researchers have also described a unique error, automation bias, that results from extended operator use of and reliance upon automation (e.g., Mosier & Skitka, 1996; Mosier, Skitka, Heers, & Burdick, 1998; Parasuraman & Riley, 1997; Skitka & Mosier, 2000).”
- Understanding human management of automation errors (2013, background): “Inafollowing investigation, Skitka et al. (2000) adjusted their experimental manipulation of accountability and examined the effect of general versus specific accountability instructions on performance.”