title: Exploring relationships of human-automation interaction consequences on pilots: uncovering subsystems.
abstract: OBJECTIVE
  We attempted to understand the latent structure underlying the systems pilots use to operate in situations involving human-automation interaction (HAI).
  
  
  BACKGROUND
  HAI is an important characteristic of many modern work situations. Of course, the cognitive subsystems are not immediately apparent by observing a functioning system, but correlations between variables may reveal important relations.
  
  
  METHODS
  The current report examined pilot judgments of 11 HAI dimensions (e.g., Workload, Task Management, Stress/Nervousness, Monitoring Automation, and Cross-Checking Automation) across 48 scenarios that required airline pilots to interact with automation on the flight deck.
  
  
  RESULTS
  We found three major clusters of the dimensions identifying subsystems on the flight deck: a workload subsystem, a management subsystem, and an awareness subsystem.
  
  
  CONCLUSIONS
  Relationships characterized by simple correlations cohered in ways that suggested underlying subsystems consistent with those that had previously been theorized.
  
  
  CONCLUSIONS
  Understanding the relationship among dimensions affecting HAI is an important aspect in determining how a new piece of automation designed to affect one dimension will affect other dimensions as well.
authors: Georgia Institute of Technology, Atlanta, Georgia.
authors: Francis T
authors: FT
authors: Durso
authors: Georgia Institute of Technology, Atlanta, Georgia ericjstearman@gatech.edu.
authors: Eric J
authors: EJ
authors: Stearman
authors: University of Illinois at Urbana-Champaign, Champaign, Illinois.
authors: Daniel G
authors: DG
authors: Morrow
authors: San Francisco State University, San Francisco, California.
authors: Kathleen L
authors: KL
authors: Mosier
authors: Georgia Institute of Technology, Atlanta, Georgia.
authors: Ute
authors: U
authors: Fischer
authors: Georgia Institute of Technology, Atlanta, Georgia.
authors: Vlad L
authors: VL
authors: Pop
authors: Georgia Institute of Technology, Atlanta, Georgia.
authors: Karen M
authors: KM
authors: Feigh
mesh_terms: D001331:Automation; D001359:Aviation; D003071:Cognition; D019336:Cognitive Science; D003657:Decision Making; D006801:Humans; D008328:Man-Machine Systems
keywords: automation; aviation and aerospace; cognition; cognitive structure; expert systems; human-automation interaction; knowledge elicitation/acquisition; methods and skills; pilot decision making