Title

Augmenting Team Cognition In Human-Automation Teams Performing In Complex Operational Environments

Keywords

Automation technology; Cognitive processes; Human-automation interaction; Intelligent agents; Metacognitive processes; Semi-autonomous robots; Team coordination

Abstract

There is a growing reliance on automation (e.g., intelligent agents, semi-autonomous robotic systems) to effectively execute increasingly cognitively complex tasks. Successful team performance for such tasks has become even more dependent on team cognition, addressing both human-human and human-automation teams. Team cognition can be viewed as the binding mechanism that produces coordinated behavior within experienced teams, emerging from the interplay between each team member's individual cognition and team process behaviors (e.g., coordination, communication). In order to better understand team cognition in human-automation teams, team performance models need to address issues surrounding the effect of human-agent and human-robot interaction on critical team processes such as coordination and communication. Toward this end, we present a preliminary theoretical framework illustrating how the design and implementation of automation technology may influence team cognition and team coordination in complex operational environments. Integrating constructs from organizational and cognitive science, our proposed framework outlines how information exchange and updating between humans and automation technology may affect lower-level (e.g., working memory) and higher-level (e.g., sense making) cognitive processes as well as teams' higher-order "metacognitive" processes (e.g., performance monitoring). Issues surrounding human-automation interaction are discussed and implications are presented within the context of designing automation technology to improve task performance in human-automation teams. Copyright © by Aerospace Medical Association.

Publication Date

5-1-2007

Publication Title

Aviation Space and Environmental Medicine

Volume

78

Issue

5 II

Number of Pages

-

Document Type

Review

Personal Identifier

scopus

Socpus ID

34248137064 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/34248137064

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