The Department Of Defense Posture For Artificial Intelligence

In this report, the authors assess the state of artificial intelligence (AI) relevant to DoD, conduct an independent assessment of the Department of Defense's posture in AI, and put forth a set of recommendations to enhance that posture.

In this report, RAND Corporation researchers assess the state of artificial intelligence relevant to the U.S. Department of Defense and provide recommendations for the future of the department's artificial intelligence posture.

Artificial intelligence (AI) is on everybody’s minds these days. Most of the world’s leading companies are making massive investments in it. Governments are scrambling to catch up. Every single one of us who uses Google Search or any of the new digital assistants on our smartphones has witnessed first-hand how quickly these developments now go. Many analysts foresee truly disruptive changes in education, employment, health, knowledge generation, mobility, etc. But what will AI mean for defense and security? In a new study HCSS offers a unique perspective on this question. Most studies to date quickly jump from AI to autonomous (mostly weapon) systems. They anticipate future armed forces that mostly resemble today’s armed forces, engaging in fairly similar types of activities with a still primarily industrial-kinetic capability bundle that would increasingly be AI-augmented. The authors of this study argue that AI may have a far more transformational impact on defense and security whereby new incarnations of ‘armed force’ start doing different things in novel ways. The report sketches a much broader option space within which defense and security organizations (DSOs) may wish to invest in successive generations of AI technologies. It suggests that some of the most promising investment opportunities to start generating the sustainable security effects that our polities, societies and economies expect may lie in in the realms of prevention and resilience. Also in those areas any large-scale application of AI will have to result from a preliminary open-minded (on all sides) public debate on its legal, ethical and privacy implications. The authors submit, however, that such a debate would be more fruitful than the current heated discussions about ‘killer drones’ or robots. Finally, the study suggests that the advent of artificial super-intelligence (i.e. AI that is superior across the board to human intelligence), which many experts now put firmly within the longer-term planning horizons of our DSOs, presents us with unprecedented risks but also opportunities that we have to start to explore. The report contains an overview of the role that ‘intelligence’ - the computational part of the ability to achieve goals in the world - has played in defense and security throughout human history; a primer on AI (what it is, where it comes from and where it stands today - in both civilian and military contexts); a discussion of the broad option space for DSOs it opens up; 12 illustrative use cases across that option space; and a set of recommendations for - especially - small- and medium sized defense and security organizations.

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.

Advancements in commercial technology are changing the global national security landscape, and the DoD is collaborating with industry to ensure our defense capabilities take advantage of changing technological innovation. Technology alone, however, will not secure the United States military advantage. Technological adoption within the DoD depends on the organizational culture and competencies that enable the ready force to leverage and accelerate technological advancements. Large-scale AI culture and competency development requires targeted upskilling across the entire DoD workforce to unlock the potential of those who will carry the Department forward into the Digital Age. Establishing an overarching AI Education Strategy for the DoD workforce is a pivotal step toward ensuring the U.S. remains ready to fight.

This report presents the results of a survey of software engineers and other technical staff to learn their views toward the defense community and their willingness to contribute to artificial intelligence projects for the U.S. Department of Defense.

An international and interdisciplinary perspective on the adoption and governance of artificial intelligence (AI) and machine learning (ML) in defence and military innovation by major and middle powers. Advancements in AI and ML pose pressing questions related to evolving conceptions of military power, compliance with international humanitarian law, peace promotion, strategic stability, arms control, future operational environments, and technology races. To navigate the breadth of this AI and international security agenda, the contributors to this book include experts on AI, technology governance, and defence innovation to assess military AI strategic perspectives from major and middle AI powers alike. These include views of how the United States, China, Japan, South Korea, the European Union, and Russia see AI/ML as a technology with the potential to reshape military affairs and power structures in the broader international system. This diverse set of views aims to help elucidate key similarities and differences between AI powers in the evolving strategic context. A valuable read for scholars of security studies, public policy, and STS studies with an interest in the impacts of AI and ML technologies.

"On December 3, 2020, the former Under Secretary of Defense for Acquisition and Sustainment (OUSD[A&S]), Ellen M. Lord, stated a need for a new and different acquisition approach that leverages speed, innovation and risk-taking to give United States (U.S.) forces the capabilities needed for future operations (Vergun, 2020). She noted that the U.S. technological advantage was starting to diminish during her speech at the 2020 Training and Simulation Industry Symposium (TSIS) held by National Training and Simulation Association. She also added that the DoD’s “acquisition system was too slow and risk averse for us to keep up with our adversaries” (Vergun, 2020, para. 2). In support of giving the U.S. forces the capabilities needed for future operations, General Q. Brown Jr., United States Air Force (USAF) chief of staff, and General David H. Berger, United States Marine Corps (USMC) commandant, recommended utilizing AI to leverage the military’s data-rich environment adding to readiness metrics new layers of analysis (Brown and Berger, 2021). They argued that “to compete the People’s Republic of China and Russia, the U.S. military requires a new framework for assessing readiness” (Brown and Berger, 2021, para. 6). As a starting point, they recommended leveraging AI to assist with this new framework. This paper focuses on leveraging AI to speed up the DoD procurement process. It reviews literature regarding the use of AI in federal procurement in relation to increasing speed and agility, potential applications to the DoD procurement activities, and recommendations for its use to reduce the DoD acquisition timeline."--Background.