@mastersthesis {2018,
	title = {Examination of cognitive load in the human-machine teaming context},
	year = {2018},
	month = {06/2018},
	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{\textquoteright}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.},
	url = {https://hdl.handle.net/10945/59638},
	author = {Clarke, Alan J. and Knudson, Daniel F. III}
}
