EVALUATION OF THE SAFETY RISKS IN DEVELOPING AND IMPLEMENTING AUTOMATED BATTLE MANAGEMENT AIDS FOR AIR AND MISSILE DEFENSE
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Authors
Cruz, Luis A.
Hoopes, Angela L.
Pappa, Ryane M.
Shilt, Savanna L.
Wuornos, Samuel I.
Subjects
artificial intelligence
AI
machine learning
safety risks
battle management aids
failure modes
air and missile defense
AI
machine learning
safety risks
battle management aids
failure modes
air and missile defense
Advisors
Johnson, Bonnie W.
Date of Issue
2021-09
Date
Publisher
Monterey, CA; Naval Postgraduate School
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Abstract
The modern battlefield is more complex than ever, and the technological advancement of weapons is accelerating. In order to win the next fight, faster response time to an adversary's actions is critical. Artificial intelligence (AI) has the potential to enable warfighters to outpace enemy decision cycles and reduce information overload, thus overcoming the "fog of war." When developing combat systems, reliability could be the difference between life and death. Therefore, it is of utmost importance that these weapon systems (especially novel systems such as AI) are developed with the highest standards of reliability and safety, long before they are introduced to the battlespace and entrusted to protect our nation's warfighters. This project utilizes a Systems Engineering approach to identify potential hazards and risks associated with AI and its role in the battlespace. Using an established Risk Management Framework (RMF), the team provides some mitigation strategies that developers must consider as they foster this technology for future use in U.S. weapon systems and processes.
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Distribution Statement
Approved for public release. Distribution is unlimited.
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.