People’s Liberation Army Operational Concepts

EDMUND J. BURKE, KRISTEN GUNNESS, CORTEZ A. COOPER III, MARK COZAD

Joint Warfighting Capabilities (JWCA) Integration

Report on Phase 1 Research

Military Operations:

Status of DOD's Efforts to Develop Future Warfighting Capability

Pursuant to a legislative requirement, GAO provided information on the Department of Defense's (DOD) efforts to develop future warfighting capability, focusing on the: (1) status of DOD's efforts to implement its joint experimentation program; (2) factors that GAO believes contribute to the success of a joint experimentation program; and (3) extent of DOD's support for future warfighting.

Proposed Analytical Products for the Air Force Warfighting Integration Capability

Developing and Presenting Options for Future Force Design and Capability Development

by Debra Knopman, Don Snyder, Irv Blickstein, David E. Thaler, James A. Leftwich, Colby P. Steiner, Quentin E. Hodgson, Elaine Simmons, Krista Romita Grocholski, Yvonne K. Crane

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The Air Force has long faced a challenge integrating force design and capability development planning with programming. The consequences of not executing the integration function well can lead to imbalances in capabilities, vulnerabilities in subsystems, and insufficient funding for investment in new capabilities. Over the past several years, Air Force leaders have recognized the need to improve both the quantity and quality of the Air Force's enterprise-level analysis and decisionmaking on future force planning. In February 2018, the Vice Chief of Staff of the Air Force and Deputy Chief of Staff for Strategy, Integration and Requirements asked RAND Project Air Force (PAF) to assist the Air Force Warfighting Integration Capability (AFWIC) in conceptualizing and executing analytical and other products to support options for future force design and capability development and their links to planning and programming.

To this end, PAF team members spoke to AFWIC leaders and key staff, other Air Force stakeholders, and individuals familiar with integration efforts in the other services. The team developed a roadmap of analytical and other product elements that could enable AFWIC to sustain its integrating role in future force design. In this report, the authors present their findings, recommendations, and vision for AFWIC's analytical processes and products. For AFWIC to succeed and endure, senior leaders will need to create favorable conditions for independent analysis of new concepts and options for future force design in support of the joint force and their practical implications for Air Force near-term planning, programming, budgeting, and execution.

Key Findings

Senior leadership must play a major role

The success of enterprise-level future concept development requires advocacy by — and continuous engagement with — the highest levels of senior leadership, including the Secretary of the Air Force (SECAF), Chief of Staff of the Air Force (CSAF), and Vice Chief of Staff of the Air Force (VCSAF).

AFWIC analysis should be of the highest quality

AFWIC should aim to become the organization within the Air Force with the highest standards for quality of analysis. No critique of a proposed future concept of operations (CONOPS) or force structure option should come from a source outside AFWIC or the Air Force that was not already identified and assessed within AFWIC.

The products of the analysis should be — and should be perceived to be — Air Force products rather than AFWIC products.

AFWIC must reduce barriers to innovation

Large institutions, such as the Air Force, must break down barriers between organizational units and cultures to achieve agreement on innovative, enterprise-wide solutions to future problems.

AFWIC should stay above the fray of current operations

To successfully address future challenges, CONOPS, and force structure options, AFWIC needs to stay above the fray of current operations and work in a time frame beyond the Future Years Defense Program. However, any solutions identified by AFWIC eventually will need to shape the Program Objective Memorandum and be plausible enough to gain stakeholder buy-in. These considerations are somewhat in tension with one another.

Recommendations

AFWIC should have frequent, direct access to the SECAF, CSAF, and VCSAF. Although senior leaders cannot directly participate in the analysis, the more they are involved in the foundations of the analysis, the more they will have confidence in the results and be equipped to advocate for those results.

AFWIC and its leadership should cultivate a culture of skepticism and introspection within the organization, expose analysis to rigorous internal and external reviews to reveal weaknesses in evidence and logic, and be frank in expressing any uncertainties and limitations of its analysis to senior leadership.

Senior leadership should create incentives for career development for personnel in AFWIC and those seconded to AFWIC by major commands (MAJCOMs). This would encourage the best talent in the Air Force to work on AFWIC problems and would persuade MAJCOMs to contribute to that talent.

AFWIC should develop more-sophisticated means of communication to establish connections and credibility with key audiences.

AFWIC should be selective in its choice of problems. Topics should force enterprise-wide thinking across mission and functional disciplines and should be responsive to both near-term and longer-term decisionmaking needs.

Analysis of problems should be set by the changing military, technological, and political environments that the Air Force must respond to and shape. AFWIC's work tempo should follow those driving factors and should be conducive to consistent, high-quality analysis.

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Quality Over Quantity：A New PLA Modernization Methodology

A History of the Third Offset, 2014–2018

by Gian Gentile, Michael Shurkin, Alexandra T. Evans, Michelle Grisé, Mark Hvizda, Rebecca Jensen

The Third Offset emerged at a time of transition within the U.S. Department of Defense (DoD). In 2014, the U.S. wars in Afghanistan and Iraq seemed to be winding down. At the same time, it had become clear to U.S. defense planners that for the previous two decades, while the U.S. military was concentrated on Afghanistan and Iraq, China and Russia had significantly increased their warfighting capabilities. The aim of the Third Offset, as envisioned by former Deputy Secretary of Defense Robert O. Work, one of its key creators and advocates, was to draw on U.S. advanced technologies to offset China's and Russia's technological advances. This report documents the history of the Third Offset from 2014 to 2018.

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A key finding in this history is that the Third Offset was less a military strategy for offsetting what were perceived to be the recently acquired military advantages of China and Russia and more a mechanism for intellectual change within DoD at a time when changes in thinking about future warfare were needed. As a result, this history focuses on institutional efforts to effect change within DoD and the key defense leaders who strove to bring that change to fruition. These efforts were successful in that the 2018 National Defense Strategy (NDS) embraced many of the fundamental tenets of technological advances and organizational changes developed by the Third Offset. In that sense, this history provides an example of how to effect organizational and process changes in large military institutions like DoD.

Key Findings

The Third Offset referred loosely to a set of ideas

One of these ideas was the conviction that China and Russia — but especially China — were strategic competitors and needed to be treated as such.

The corollary to this idea was the conviction that the United States must develop a strategy to compete with China and Russia.

This meant, among other things, refocusing the military on the kind of military capabilities required to confront peer adversaries. In particular, there was concern with countering China's and Russia's anti-access/area denial technologies.

Another idea pertained to DoD's diminished role in driving innovation; the Third Offset featured a drive to find new ways to cultivate technological innovations and interact with the commercial world, including Silicon Valley.

During its brief lifespan, the Third Offset did not result in a set of capabilities that offset Chinese and Russian capabilities; however, it promoted many ideas that shaped the 2018 NDS

Work gave these ideas — from the return to great-power competition to the need to shake up DoD business practices — a focus and a direction that, up to that point, were lacking.

The Third Offset was less a military strategy for offsetting Russian and Chinese military advances and more a mechanism for intellectual change within DoD at a time when changes in thinking about future warfare were needed.

The history of the Third Offset showcases the importance of positive, inspired leadership in effecting organizational change.

Table of Contents

Chapter One

Introduction

Chapter Two

Setting the Scene

Chapter Three

Making It Happen: Work's Internal Initiative

Chapter Four

Conclusion

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Exploring the Feasibility and Utility of Machine Learning-Assisted Command and Control

Volume 1, Findings and Recommendations

by Matthew Walsh, Lance Menthe, Edward Geist, Eric Hastings, Joshua Kerrigan, Jasmin Léveillé, Joshua Margolis, Nicholas Martin, Brian P. Donnelly

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This report concerns the potential for artificial intelligence (AI) systems to assist in Air Force command and control (C2) from a technical perspective. The authors present an analytical framework for assessing the suitability of a given AI system for a given C2 problem. The purpose of the framework is to identify AI systems that address the distinct needs of different C2 problems and to identify the technical gaps that remain. Although the authors focus on C2, the analytical framework applies to other warfighting functions and services as well.

The goal of C2 is to enable what is operationally possible by planning, synchronizing, and integrating forces in time and purpose. The authors first present a taxonomy of problem characteristics and apply them to numerous games and C2 processes. Recent commercial applications of AI systems underscore that AI offers real-world value and can function successfully as components of larger human-machine teams. The authors outline a taxonomy of solution capabilities and apply them to numerous AI systems.

While primarily focusing on determining alignment between AI systems and C2 processes, the report's analysis of C2 processes is also informative with respect to pervasive technological capabilities that will be required of Department of Defense (DoD) AI systems. Finally, the authors develop metrics — based on measures of performance, effectiveness, and suitability — that can be used to evaluate AI systems, once implemented, and to demonstrate and socialize their utility.

Key Findings

C2 processes are very different from many of the games and environments used to develop and demonstrate AI systems

Game-playing algorithms exploit regularity to achieve superhuman performance, but nature and the adversary intervene to break this simplifying assumption in military tasks.

Characterizing and developing representative problems and environments will enable research, development, testing, and evaluation of AI systems under conditions representative of DoD problem sets, thereby increasing transferability to operational environments.

The distinctive nature of C2 processes calls for AI systems different from those optimized for game play

Understanding the capabilities and limitations of existing AI systems will allow the Air Force to identify systems that are suitable for different C2 processes.

Choosing the right approach at problem outset can substantially reduce application development time, increase solution quality, and decrease risk associated with transitioning the solution.

New guidance, infrastructure, and metrics are needed to evaluate applications of AI to C2

Establishing and operationalizing measures of merit will enable the evaluation and comparison of potential AI systems.

Additionally, measures of merit provide a way to communicate the return on investment of AI-enabled C2.

Hybrid approaches are needed to deal with the multitude of problem characteristics that are present in C2 processes

Given the generality of the analytical framework and the emergence of Joint All-Domain C2, all these conclusions and recommendations extend to the pursuit of AI across DoD.

Recommendations

Use the structured method described in this report to systematically analyze the characteristics of games, problems, and C2 processes to determine where existing AI test beds are representative and nonrepresentative of C2 tasks.

Develop new AI test beds with problem characteristics that are representative of C2 tasks in kind and in intensity.

Use the structured method described in this report to identify and invest in high-priority solution capabilities called for across a wide range of C2 processes and not currently available (e.g., robustness and assuredness).

Use the structured method described in this report to evaluate alignment between the characteristics of potential AI systems and particular C2 processes to prioritize which systems to develop.

Develop metrics for AI solutions that assess capabilities beyond algorithm soundness and optimality (e.g., robustness and explainability).

Use the structured method described in this report to identify key measures of performance, effectiveness, and suitability for a given C2 process.

Perform a comprehensive assessment of AI systems for a given C2 process based on identified measures of merit.

Identify, reuse, and combine algorithmic solutions that confer critical AI system capabilities.

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Exploring the Feasibility and Utility of Machine Learning-Assisted Command and Control

Volume 2, Supporting Technical Analysis

by Matthew Walsh, Lance Menthe, Edward Geist, Eric Hastings, Joshua Kerrigan, Jasmin Léveillé, Joshua Margolis, Nicholas Martin, Brian P. Donnelly

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This volume serves as the technical analysis to a report concerning the potential for artificial intelligence (AI) systems to assist in Air Force command and control (C2) from a technical perspective. The authors detail the taxonomy of ten C2 problem characteristics. They present the results of a structured interview protocol that enabled scoring of problem characteristics for C2 processes with subject-matter experts (SMEs). Using the problem taxonomy and the structured interview protocol, they analyzed ten games and ten C2 processes. To demonstrate the problem taxonomy and the structured interview protocol for a C2 problem, they then applied them to sensor management as performed by an air battle manager.

The authors then turn to eight AI system solution capabilities. As for the C2 problem characteristics, they created a structured protocol to enable valid and reliable scoring of solution capabilities for a given AI system. Using the solution taxonomy and the structured interview protocol, they analyzed ten AI systems.

The authors present additional details about the design, implementation, and results of the expert panel that was used to determine which of the eight solution capabilities are needed to address each of the ten problem characteristics. Finally, they present three technical case studies that demonstrate a wide range of computational, AI, and human solutions to various C2 problems.

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