Artificial Intelligence (AI): The Bumpy Path Through Defense Acquisition - The Construction of Systems Which Act Rationally, Behave Humanly, and Adapt, DoD Essentials of Mobility and Algorithms

This fascinating and comprehensive December 2017 report has been professionally converted for accurate flowing-text e-book format reproduction.

The use of artificial intelligence systems is ready to transition from basic science research and a blooming commercial industry to strategic implementation in the Defense Acquisition system. The purpose of this research is to determine the problems awaiting artificial intelligence (AI) systems inherent to defense acquisition. AI is a field of scientific study focused on the construction of systems that can act rationally, behave humanly, and adapt. To achieve AI behavior takes AI essentials, which consider mobility, system perspective, and algorithms. Unfortunately, AI essentials are under addressed in the concept of operations that fuels the Joint Capabilities Integration and Development System. Influences to the concept of operations analyzed in this research include strategic documentation, joint technology demonstrations, and exercises that aim to capture technology-based lessons learned. Failure to address AI essentials causes problems in defense acquisition: system requirements are impossible to define; transition of AI technology fails; testing cannot be evaluated with confidence; and life cycle planning is at best a guess. To address these issues, the Department of Defense needs improved planning, acquisition personnel training, and AI-supported acquisition processes to achieve cost, schedule, and performance goals.

Chapter II, "Literature Review" provides a snapshot of AI today. It works to provide a general understanding of the scientific field and technology that is AI, the spectrum of behaviors expected from AI systems, what composition of an AI system, and the identities of AI industry leaders. The reader should be able to understand a working definition of AI systems, a general sense of AI technology readiness, and the emerging industry surrounding AI.

Next, Chapter III, "JCIDS," examines the ability for DOD processes to develop requirements for AI applications. Requirements developments starts at a strategic level, directing military resources to achieve present and future military needs. The JCIDS clarifies strategic direction, identifying capability gaps and validating needs (CJCS, 2012, p. 2). This chapter outlines how the JCIDS builds validated requirement documents, then focuses on grading AI elements in the joint CONOPs. The reader should leave this section with an understanding of CONOPs AI maturity and its influence on validated requirements headed for the DAS. Chapter IV, "DAS," focuses on the DAS and the processes that PMs use to manage system acquisition. The DAS is defined by DOD regulation, and gives direction for management of systems engineering, financial management, and contracting efforts (DOD, 2017, p. 51). This chapter analyzes the general process for developing and purchasing defense systems and the seminal areas inside of the DAS where software-intensive systems have struggled. The reader should leave this section understanding the consequences that poorly defined AI requirements would have on program cost, performance, and schedule.

Chapter V, "Conclusion," integrates the ideas uncovered from the research in order to answer the secondary research questions and then the primary research question. Next, it makes recommendations based on the research that should help to prepare JCIDS and DAS for success with AI systems. Lastly, Chapter V proposes future areas of research that will generate more comprehensive information about the definition of AI requirements and how to meet cost, schedule, and performance during system fielding.

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