Main Subcommittee Category
Policy, Standards, Management, and AcquisitionHow would you label your submission?
IndustryAbstract
One of the most effective, yet simple, frameworks to describe military operations, whether it be ground maneuver, aerial combat, or cyberspace operations, is the Boyd (Or OODA [Observe-Orient-Decide-Act]) Loop. The Boyd Loop paradigm describes the process individuals, commanders and units use to observe the situation, orient onto the conditions that exist, decide how to act, carry out the decision, and then to repeat the cycle. The simplicity of the Boyd Loop makes it an excellent tool to use in educating senior leaders and policy makers reference the employment of Machine Learning (ML) and Artificial intelligence (AI) into military operations. Both capabilities are increasingly being leveraged to support and facilitate command and control within military operations by increasing access to pertinent data and more importantly increasing the speed of each step of the loop in comparison to our adversary. Although the results have been positive, civilians, as well military leaders and policy makers, have nonetheless expressed doubt or caution as to their use for fear of “the machines taking over” or lack of humans in- or on-the loop to approve decisions. Similarly, the United States must make use of AI in its command and control systems as quickly as practical to keep pace with peer threats’ use of these capabilities. In pursuing a military advantage achieved though AI/ML aided Decision Dominance, western leaders, especially, must recognize, mitigate, and address the apprehension over the use of AI/ML for it to be effective. The purpose of this paper is to propose a framework using the Boyd Loop to explain AI to policy makers as well as describe the key conditions, characteristics, and capabilities needed to increase trust in its use. The paper will conclude with other potential uses of the framework and areas such as doctrine and policy development for continued development.