User agreement with incorrect expert system advice

By J. J. Dijkstra. 1999

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Citations in the corpus

Algorithm appreciation: People prefer algorithmic to human judgment (2019, unknown): “This preference for algorithmic output persisted, even after they saw the algorithm err (Dijkstra, 1999).”
Influence Processes for Information Technology Acceptance: An Elaboration Likelihood Model (2006, background): “decision making, or knowledge acceptance (e.g., Mak et al. 1997; Dijkstra 1999; Sussman and Siegel 2003), this study is the first to apply this theory to the IT acceptance domain.”
Persuasion in crowdfunding: An elaboration likelihood model of crowdfunding performance (2017, background): “While support for the moderating effects of both motivation and ability on elaboration likelihood has been found, elaboration likelihood is state-based and context dependent (Crano and Prislin, 2006; Dijkstra, 1999; Petty and Cacioppo, 1984).”
When do people rely on algorithms (2016, background): “Conflicting evidence finds that people rely more on algorithmic “expert systems” than on a person (Dijkstra, Leibrand, Timminga, 1998; Dijkstra, 1999).”
Similarities and differences between human–human and human–automation trust: an integrative review (2007, methodology): “A follow-up study by Dijkstra (1999) using a similar experimental paradigm in a legal context revealed that participants often agreed with the incorrect advice of an expert system in spite of alternative and more accurate written information presented to them through human advisors.”
Organizational Behavior and Human Decision Processes (2019, unknown): “This preference for algorithmic output persisted, even after they saw the algorithm err (Dijkstra, 1999).”
Effects of Information Source, Pedigree, and Reliability on Operator Interaction With Decision Support Systems (2007, background): “…et al., 1997) and the effects of framing on automation trust (e.g., Dzindolet et al., 2002; Lacson, Wiegmann, & Madhavan, 2003), we hypothesized trust in automation to be higher than in humans when portrayed as novices, as automation is perceived as more rational than humans (e.g., Dijkstra, 1999).”
Almost human: Anthropomorphism increases trust resilience in cognitive agents. (2016, background): “1080/014492999118832 Dijkstra, J., Liebrand, W., & Timminga, E. (1998). Persuasiveness of expert systems.”