Examination Of Cognitive Load In The Human Machine Teaming Context

Abstract

The Department of Defense (DoD) is increasingly hoping to employ unmanned systems and artificial intelligence to achieve a strategic advantage over adversaries. While some tasks may be suitable for machine substitution, many parts of the DoD's mission continue to require boots on the ground and humans in the loop working in interdependent human-machine teams. The commercial unmanned systems marketplace and active UxS and autonomous systems offer military research and acquisitions professionals promising technical solutions, but may integrate poorly in a human-machine team application. The authors developed a framework for analyzing task-to-technology matches and team design for military human-machine teams. The framework is grounded in the cognitive theories of situational awareness and decision making, team dynamics, and functional allocation literature. Additionally, the research recommends developing a shared DoD-wide understanding of autonomous systems terms and taxonomy, and educating operational leaders, acquisitions staff, and executives about realistic expectations and employment of autonomous systems in human-machine environments.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2018
Accession Number
AD1059810

Entities

People

  • Alan J. Clarke
  • Daniel Iii F. Knudson

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Aircrafts
  • Artificial Intelligence
  • Artificial Intelligence Software
  • Automata Theory
  • Cognition
  • Cognitive Science
  • Cognitive Workload
  • Computational Science
  • Computer Languages
  • Control Systems
  • Human Factors Engineering
  • Human-Machine Interfaces
  • Information Science
  • Information Systems
  • Ontologies
  • Psychology
  • Unmanned Systems

Fields of Study

  • Computer science

Readers

  • Defense Acquisition Program Management
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.
  • Unmanned Aerial System (UAS) Autonomous Capabilities and Mission Reconnaissance.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - DoD AI Strategy
  • Autonomy
  • Autonomy - Human-Robot Interaction