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What You Don't Know Can Hurt You: Factors Impacting Diagnosis in the Automated Cockpit

San Francisco State University, San Francisco, California, kmosier{at}sfsu.edu

Nikita Sethi

San Francisco State University, San Francisco, California

Shane McCauley

San Francisco State University, San Francisco, California

Len Khoo

San Francisco State University, San Francisco, California

Judith M. Orasanu

NASA Ames Research Center, Moffett Field, California

Objective: We examined the impact of operational variables on diagnosis and decision-making processes, focusing on information search. Background: Arguably, the "best" decision-making processes in high-technology cockpits would be those that are both correspondent (objectively accurate) and coherent (rationally sound). In the electronic world, coherence in terms of identification and incorporation of all relevant information is both a prerequisite to and a limiting factor for accurate diagnosis and decision making. Method: Regional carrier pilots (N = 93) responded to six scenarios by accessing information to determine a diagnosis and decision. Results: Time pressure, a common operational variable, had a strong negative effect on information search and diagnosis accuracy, and the presence of noncongruent information heightened these negative effects. Unexpectedly, source of initial information (automated or other) did not impact any of the dependent variables. Diagnosis confidence was unrelated to accuracy and was negatively related to amount of information accessed. Conclusion: Results confirm both the need for coherence in diagnostic processes and the difficulty of maintaining it under time pressure. Application: One implication of the results of this study is that pilots in high-technology cockpits must be trained to utilize coherent diagnostic processes as standard operating procedure. Additionally, because thorough information search for diagnosis in an automated environment is essential, automated systems must be designed to foster coherent, and thus accurate, diagnostic processes.

Human Factors: The Journal of the Human Factors and Ergonomics Society, Vol. 49, No. 2, 300-310 (2007)
DOI: 10.1518/001872007X312513


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