Expediting the Targeting Process Responsibly using Artificial Intelligence

被引:0
|
作者
Lowrance, Christopher J. [1 ]
Harris, Elliott R. [1 ]
Pfaff, C. Anthony [1 ]
机构
[1] US Army War Coll, 47 Ashburn Dr, Carlisle, PA 17013 USA
来源
ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING FOR MULTI-DOMAIN OPERATIONS APPLICATIONS IV | 2022年 / 12113卷
关键词
AI-enabled targeting process; military artificial intelligence; Department of Defense modernization; fires warfighting function; fuzzy control and decision making;
D O I
10.1117/12.2619098
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Absent the use of artificial intelligence (AI), each stage of the targeting process requires human input, which consumes time - a precious resource during high-intensity conflict. To counter that problem, the application of AI and related technologies could rapidly automate certain steps within the targeting process. The challenge, however, becomes how to responsibly speed up the process using AI, while also maintaining appropriate levels of human oversight based on level of risk acceptable to the commander. We address this challenge with the introduction of a fuzzy logic controller that is designed to automatically adapt and optimize the level of human-machine interaction based on the current targeting conditions. The logic controller uses the confidence of the AI algorithm at each stage of the targeting process, as well as the commander's risk tolerance at the time, to automatically determine what stages of the targeting process can be trusted for AI to accelerate and which ones require explicit human verification. The final stage of verifying and authorizing a fire mission is reserved for humans only to make.
引用
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页数:12
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