Does automation bias decision-making?

By Linda J. Skitka, K. Mosier, M. D. Burdick. 1999

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Citations in the corpus

Rapid Trust Calibration through Interpretable and Uncertainty-Aware AI (2020, background): “Various studies have looked at different factors affecting automation bias, including the cognitive load of the user, 58 the accountability of the user in the decision process, 59,60 and their level of expertise and training.”
Automation and Accountability in Decision Support System Interface Design (2006, background): “For example, in perhaps one of the most well-known engineering accidents in the United States, the 1979 cooling malfunction of one of the Three Mile Island nuclear reactors, problems with information representation in the control room and human cognitive limitations were primary contributors to the…”
Misuse of automated decision aids: Complacency, automation bias and the impact of training experience (2008, background): “…from accident reports in aviation and from laboratory studies using multiple-task scenarios which simulate typical demands of cockpit work on different levels of fidelity (e.g., Parasuraman et al., 1993; Mosier et al., 1998; Funk et al., 1999; Skitka et al., 1999, 2000a; Prinzel et al., 2001).”
Automation Bias in Intelligent Time Critical Decision Support Systems (2004, background): “However, when the automation failed to detect and notify operators of an event, or incorrectly recommended action despite the availability of reliable confirmatory evidence, human error rates increased 19 .”
Understanding human management of automation errors (2013, background): “In a study by Skitka, Mosier, and Burdick (1999), participants either worked with an 88% reliable automated monitoring aid or were required to monitor the task manually without any automation.”
Human Performance Consequences of Automated Decision Aids (2012, background): “As has been described by Skitka, Mosier, and Burdick (1999), these errors “can be the result of not seeking out confirmatory or disconfirmatory information, or discounting other sources of information in the presence of computer-generated cues” (p. 993).”
Accountable Artificial Intelligence: Holding Algorithms to Account (2020, background): “…conceivably lead to unjustified deference of the decision-maker to algorithm predictions: “Automation bias” (Cummings 2006; Lyell and Coiera 2017; Skitka, Mosier, and Burdick 1999) is a well-documented phenomenon reported in psychological studies manifest in human over-reliance on automated…”
Fairness and Accountability Design Needs for Algorithmic Support in High-Stakes Public Sector Decision-Making (2018, background): “Over and under-reliance on decision support, extensively highlighted in the literature on automation bias [71, 18], featured considerably in informants’ responses.”
The Ethical Implications of Using Artificial Intelligence in Auditing (2020, background): “Skitka et al. (1999) propose that there are two types of errors that could be committed as a result of over-reliance on automated decision aids, such as AI.”
Complacency and Bias in Human Use of Automation: An Attentional Integration (2010, methodology): “However, the previously described findings of Skitka et al. (1999; Skitka, Mosier, & Burdick, 2000) do support the view that neglect of automation verification might constitute a major source of commission errors, as does a study by Bahner, Huper, et al. (2008), which we describe later.”
Automation bias and verification complexity: a systematic review (2017, unknown): “Tracking task (36) 80 students 8 * 8 mins P< .”
Quality at a Glance: An Audit of Web-Crawled Multilingual Datasets (2021, background): “Similarly, automation bias (Skitka et al., 1999), which refers to humans favoring decisions made by automated systems over decisions made by humans, might amplify the issues”
When combinations of humans and AI are useful: A systematic review and meta-analysis (2024, unknown): “For example, people often rely too much on AI systems (overreliance), using its suggestions as strong guidelines without seeking and processing more information 6,30,31 .”