Artificial Intelligence and National Security
Updated August 26, 2020
Congressional Research Service
https://crsreports.congress.gov
R45178

Artificial Intelligence and National Security

Summary
Artificial intelligence (AI) is a rapidly growing field of technology with potentially significant
implications for national security. As such, the U.S. Department of Defense (DOD) and other
nations are developing AI applications for a range of military functions. AI research is underway
in the fields of intelligence collection and analysis, logistics, cyber operations, information
operations, command and control, and in a variety of semiautonomous and autonomous vehicles.
Already, AI has been incorporated into military operations in Iraq and Syria. Congressional action
has the potential to shape the technology’s development further, with budgetary and legislative
decisions influencing the growth of military applications as well as the pace of their adoption.
AI technologies present unique challenges for military integration, particularly because the bulk
of AI development is happening in the commercial sector. Although AI is not unique in this
regard, the defense acquisition process may need to be adapted for acquiring emerging
technologies like AI. In addition, many commercial AI applications must undergo significant
modification prior to being functional for the military. A number of cultural issues also challenge
AI acquisition, as some commercial AI companies are averse to partnering with DOD due to
ethical concerns, and even within the department, there can be resistance to incorporating AI
technology into existing weapons systems and processes.
Potential international rivals in the AI market are creating pressure for the United States to
compete for innovative military AI applications. China is a leading competitor in this regard,
releasing a plan in 2017 to capture the global lead in AI development by 2030. Currently, China is
primarily focused on using AI to make faster and more well-informed decisions, as well as on
developing a variety of autonomous military vehicles. Russia is also active in military AI
development, with a primary focus on robotics.
Although AI has the potential to impart a number of advantages in the military context, it may
also introduce distinct challenges. AI technology could, for example, facilitate autonomous
operations, lead to more informed military decisionmaking, and increase the speed and scale of
military action. However, it may also be unpredictable or vulnerable to unique forms of
manipulation. As a result of these factors, analysts hold a broad range of opinions on how
influential AI will be in future combat operations. While a small number of analysts believe that
the technology will have minimal impact, most believe that AI will have at least an
evolutionary—if not revolutionary—effect.
Military AI development presents a number of potential issues for Congress:
 What is the right balance of commercial and government funding for AI
development?
 How might Congress influence defense acquisition reform initiatives that
facilitate military AI development?
 What changes, if any, are necessary in Congress and DOD to implement effective
oversight of AI development?
 How should the United States balance research and development related to
artificial intelligence and autonomous systems with ethical considerations?
 What legislative or regulatory changes are necessary for the integration of
military AI applications?
 What measures can Congress take to help manage the AI competition globally?

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Introduction1
Artificial intelligence (AI) is a rapidly growing field of technology that is capturing the attention
of commercial investors, defense intellectuals, policymakers, and international competitors alike,
as evidenced by a number of recent initiatives. On July 20, 2017, the Chinese government
released a strategy detailing its plan to take the lead in AI by 2030. Less than two months later
Vladimir Putin publicly announced Russia’s intent to pursue AI technologies, stating, “[W]hoever
becomes the leader in this field will rule the world.”2 Similarly, the U.S. National Defense
Strategy, released in January 2018, identified artificial intelligence as one of the key technologies
that will “ensure [the United States] will be able to fight and win the wars of the future.”3
The U.S. military is already integrating AI systems into combat via a spearhead initiative called
Project Maven, which uses AI algorithms to identify insurgent targets in Iraq and Syria.4 These
dynamics raise several questions that Congress addressed in hearings during 2017, 2018, and
2019: What types of military AI applications are possible, and what limits, if any, should be
imposed? What unique advantages and vulnerabilities come with employing AI for defense? How
will AI change warfare, and what influence will it have on the military balance with U.S.
competitors? Congress has a number of oversight, budgetary, and legislative tools available that it
may use to influence the answers to these questions and shape the future development of AI
technology.
AI Terminology and Background5
Almost all academic studies in artificial intelligence acknowledge that no commonly accepted
definition of AI exists, in part because of the diverse approaches to research in the field.
Likewise, although Section 238 of the FY2019 National Defense Authorization Act (NDAA)
directs the Secretary of Defense to produce a definition of artificial intelligence by August 13,
2019, no official U.S. government definition of AI yet exists.6 The FY2019 NDAA does,
however, provide a definition of AI for the purposes of Section 238:
1. Any artificial system that performs tasks under varying and unpredictable
circumstances without significant human oversight, or that can learn from
experience and improve performance when exposed to data sets.
2. An artificial system developed in computer software, physical hardware, or other
context that solves tasks requiring human-like perception, cognition, planning,
learning, communication, or physical action.

1 This report was originally written by Daniel S. Hoadley, U.S. Air Force Fellow. It has been updated by Kelley M.
Sayler, Analyst in Advanced Technology and Global Security.
2 China State Council, “A Next Generation Artificial Intelligence Development Plan,” July 20, 2017, translated by New
America, https://www.newamerica.org/documents/1959/translation-fulltext-8.1.17.pdf, and Tom Simonite, “For
Superpowers, Artificial Intelligence Fuels New Global Arms Race,” Wired, August 8, 2017, https://www.wired.com/
story/for-superpowers-artificial-intelligence-fuels-new-global-arms-race.
3 Department of Defense, Summary of the 2018 National Defense Strategy, p.3, https://dod.defense.gov/Portals/1/
Documents/pubs/2018-National-Defense-Strategy-Summary.pdf.
4 Marcus Weisgerber, “The Pentagon’s New Algorithmic Warfare Cell Gets Its First Mission: Hunt ISIS,” Defense
One, May 14, 2017, http://www.defenseone.com/technology/2017/05/pentagons-new-algorithmic-warfare-cell-gets-its-
first-mission-hunt-isis/137833/.
5 For a general overview of AI, see CRS In Focus IF10608, Overview of Artificial Intelligence, by Laurie A. Harris.
6 P.L. 115-232, Section 2, Division A, Title II, §238.
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3. An artificial system designed to think or act like a human, including cognitive
architectures and neural networks.
4. A set of techniques, including machine learning that is designed to approximate a
cognitive task.
5. An artificial system designed to act rationally, including an intelligent software
agent or embodied robot that achieves goals using perception, planning,
reasoning, learning, communicating, decision-making, and acting.7
This definition encompasses many of the descriptions in Table 1 below, which summarizes
various AI definitions in academic literature.
The field of AI research began in the 1940s, but an explosion of interest in AI began around 2010
due to the convergence of three enabling developments: (1) the availability of “big data” sources,
(2) improvements to machine learning approaches, and (3) increases in computer processing
power.8 This growth has advanced the state of Narrow AI, which refers to algorithms that address
specific problem sets like game playing, image recognition, and navigation. All current AI
systems fall into the Narrow AI category. The most prevalent approach to Narrow AI is machine
learning, which involves statistical algorithms that replicate human cognitive tasks by deriving
their own procedures through analysis of large training data sets. During the training process, the
computer system creates its own statistical model to accomplish the specified task in situations it
has not previously encountered.
Experts generally agree that it will be many decades before the field advances to develop General
AI, which refers to systems capable of human-level intelligence across a broad range of tasks.9
Nevertheless, the rapid advancements in Narrow AI have sparked a wave of investment, with U.S.
venture capitalists investing an estimated $8 billion in AI research in 2018 alone.10 Similarly,
DOD’s unclassified investments in AI have grown from just over $600 million in FY2016 to $2.5
billion in FY2021 (including investments in autonomy), with the Department reportedly
maintaining over 600 active AI projects.11
AI has a number of unique characteristics that may be important to consider as these technologies
enter the national security arena. First, AI has the potential to be integrated across a variety of
applications, improving the so-called “Internet of Things” in which disparate devices are
networked together to optimize performance.12 As Kevin Kelley, the founder of Wired magazine,

7 Ibid. For a critique of this definition, see Defense Innovation Board (DIB), “AI Principles: Recommendations on the
Ethical Use of Artificial Intelligence by the Department of Defense – Supporting Document,” November 2019, pp. 8-
10, https://media.defense.gov/2019/Oct/31/2002204459/-1/-1/0/
DIB_AI_PRINCIPLES_SUPPORTING_DOCUMENT.PDF. The DIB instead defines artificial intelligence as “a
variety of information processing techniques and technologies used to perform a goal-oriented task and the means to
reason in pursuit of that task.”
8 Executive Office of the President, National Science and Technology Council, Committee on Technology, Preparing
for the Future of Artificial Intelligence, October 12, 2016, p. 6, https://obamawhitehouse.archives.gov/sites/default/
files/whitehouse_files/microsites/ostp/NSTC/preparing_for_the_future_of_ai.pdf.
9 Ibid., pp. 7-9.
10 Deloitte, “Future in the balance? How countries are pursuing an AI advantage,” https://www2.deloitte.com/us/en/
insights/focus/cognitive-technologies/ai-investment-by-country.html.
11 See Govini, Department of Defense Artificial Intelligence, Big Data, and Cloud Taxonomy, December 3, 2017, p. 9;
Office of the Under Secretary of Defense (Comptroller)/Chief Financial Officer, Defense Budget Overview: United
States Department of Defense FY2021 Budget Request, February 2020, p. 1-9; and Brendan McCord, Eye on AI,
August 28, 2019, transcript available at https://static1.squarespace.com/static/5b75ac0285ede1b470f58ae2/t/
5d6aa8edb91b0c0001c7a05f/1567.
12 See Steve Ranger, “What is the IoT? Everything you need to know about the Internet of Things right now,”
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states, “[AI] will enliven inert objects, much as electricity did more than a century ago.
Everything that we formerly electrified we will now cognitize.”13 Second, many AI applications
are dual-use, meaning they have both military and civil applications. For example, image
recognition algorithms can be trained to recognize cats in YouTube videos as well as terrorist
activity in full motion video captured by uninhabited aerial vehicles over Syria or Afghanistan.14
Third, AI is a relatively transparent enabling capability, meaning that its integration into a product
may not be immediately recognizable. By and large, AI procurement will not result in countable
objects. Rather, the algorithm will be purchased separately and incorporated into a larger system.
As an expert in the field points out, “We will not buy AI. It will be used to solve problems, and
there will be an expectation that AI will be infused in most things we do.”15
AI Concepts
Table 1. Taxonomy of Historical AI Definitions
Systems That Think Like Humans
Systems That Think Rationally
“The automation of activities that we associate with
“The study of computations that make possible to
human thinking, activities such as decision making,
perceive, reason, and act.”
problem solving, and learning.”
—Winston, 1992
—Bellman, 1978
Systems That Act Like Humans
Systems That Act Rationally
“The art of creating machines that perform functions
“The branch of computer science that is concerned
that require intelligence when performed by people.” with the automation of intelligent behavior.”
—Kurzweil, 1990
—Luger and Stubblefield, 1993
Selected Definitions—Where possible, an official U.S. government document is cited.

Automated systems. “A physical system that functions with no (or limited) human operator involvement,
typically in structured and unchanging environments, and the system’s performance is limited to the specific
set of actions that it has been designed to accomplish ... typically these are well-defined tasks that have
predetermined responses according to simple scripted or rule-based prescriptions.”16

Autonomy. “The condition or quality of being self-governing in order to achieve an assigned task based on
the system’s own situational awareness (integrated sensing, perceiving, and analyzing), planning, and decision
making.”17

Autonomous Weapon System (aka Lethal Autonomous Weapon System, LAWS). “A weapon system
that, once activated, can select and engage targets without further intervention by a human operator.”18

ZDNet.com, August 21, 2018, https://www.zdnet.com/article/what-is-the-internet-of-things-everything-you-need-to-
know-about-the-iot-right-now/.
13 Kevin Kelly, “The Three Breakthroughs That Have Finally Unleashed AI on the World,” Wired, October 27, 2014,
https://www.wired.com/2014/10/future-of-artificial-intelligence.
14 Greg Allen and Taniel Chan, Artificial Intelligence and National Security, Belfer Center for Science and
International Affairs, July 2017, p. 47.
15 Steve Mills, Presentation at the Global Security Forum, Center for Strategic and International Studies, Washington,
DC, November 7, 2017.
16 Andrew Ilachinski, AI, Robots, and Swarms: Issues, Questions, and Recommended Studies, Center for Naval
Analysis, January 2017, p. 6.
17 Department of Defense, Joint Concept for Robotic and Autonomous Systems, October 19, 2016, p. A-3.
18 Department of Defense, Directive 3000.09, Autonomy in Weapon Systems, http://www.esd.whs.mil/Portals/54/
Documents/DD/issuances/DODd/300009p.pdf.
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
Human-Supervised Autonomous Weapon System. “An autonomous weapon system that is designed to
provide human operators with the ability to intervene and terminate engagements, including in the event
of a weapon system failure, before unacceptable levels of damage occur.”19

Semi-Autonomous Weapon System. “A weapon system that, once activated, is intended to only engage
individual targets or specific target groups that have been selected by a human operator.”20

Robot. “A powered machine capable of executing a set of actions by direct human control, computer
control, or a combination of both. At a minimum it is comprised of a platform, software, and a power
source.”21
Understanding the relationships between these terms can be challenging, as they may be used interchangeably in
the literature and definitions often conflict with one another. For example, some studies delineate between
automated systems and autonomous systems based on the system’s complexity, arguing that automated systems
are strictly rule-based, while autonomous systems exhibit artificial intelligence. Some, including the Department of
Defense, categorize autonomous weapon systems based not on the system’s complexity, but rather on the type of
function being executed without human intervention (e.g., target selection and engagement).22 Stil others describe
AI as a means of automating cognitive tasks, with robotics automating physical tasks. This framework, however,
may not be sufficient to describe how AI systems function, as such systems do not merely replicate human
cognitive functions and often produce unanticipated outputs. In addition, a robot may be automated or
autonomous and may or may not contain an AI algorithm. Figure 1 il ustrates these relationships, based on the
above selected definitions of each term.
Figure 1. Relationships of Selected AI Definitions

Source: CRS.

19 Ibid.
20 Ibid.
21 Department of Defense, Joint Concept for Robotic and Autonomous Systems, p. A-3.
22 See Paul Scharre and Michael C. Horowitz, An Introduction to Autonomy in Weapon Systems, Center for a New
American Security, February 2015, pp. 6-7.
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Issues for Congress
A number of Members of Congress have called for action on military AI. During the opening
comments to a January 2018 hearing before the House Armed Services Subcommittee on
Emerging Threats, the subcommittee chair called for a “national level effort” to preserve a
technological edge in the field of AI.23 Former Deputy Secretary of Defense Robert Work argued
in a November 2017 interview that the federal government needs to address AI issues at the
highest levels, further stating that “this is not something the Pentagon can fix by itself.”24 Other
analysts have called for a national AI strategy to articulate AI objectives and drive whole-of-
government initiatives and cross-cutting investments.25
In the meantime, DOD has published a classified AI strategy and is carrying out multiple tasks
directed by DOD guidance and the FY2019 NDAA, including
 establishing a Joint Artificial Intelligence Center (JAIC), which now
“coordinate[s] the efforts of the Department to develop, mature, and transition
artificial intelligence technologies into operational use”;26
 publishing a strategic roadmap for AI development and fielding, as well as
guidance on “appropriate ethical, legal, and other policies for the Department
governing the development and use of artificial intelligence enabled systems and
technologies in operational situations”;27 and
 establishing a National Security Commission on Artificial Intelligence to conduct
a comprehensive assessment of militarily relevant AI technologies and provide
recommendations for strengthening U.S. competitiveness.28

23 U.S. Congress, House of Representatives Committee on Armed Services, Subcommittee on Emerging Threats and
Capabilities, Hearing on China’s Pursuit of Emerging Technologies, 115th Cong., 2nd sess., January 9, 2018, transcript
available at http://www.cq.com/doc/congressionaltranscripts-5244793?1; remarks by Rep. Joe Wilson.
24 Colin Clark, “Our Artificial Intelligence ‘Sputnik Moment’ is Now: Eric Schmidt and Bob Work,” Breaking
Defense, November 1, 2017, https://breakingdefense.com/2017/11/our-artificial-intelligence-sputnik-moment-is-now-
eric-schmidt-bob-work/.
25 Jack Corrigan, “U.S. Needs a National Strategy for Artificial Intelligence, Lawmakers and Experts Say,” Defense
One, July 14, 2018, https://www.defenseone.com/technology/2018/07/us-needs-national-strategy-artificial-intelligence-
lawmakers-and-experts-say/149644/.
26 Sydney J. Freedberg, Jr., “Pentagon Rolls Out Major Cyber, AI Strategies This Summer,” Breaking Defense, July 17,
2018, https://breakingdefense.com/2018/07/pentagon-rolls-out-major-cyber-ai-strategies-this-summer/; and P.L. 115-
232, Section 2, Division A, Title X, §1051.
27 P.L. 115-232, Section 2, Division A, Title II, §238. In support of this mandate, the Defense Innovation Board, an
independent federal advisory committee to the Secretary of Defense, has drafted recommendations for the ethical use of
artificial intelligence. See Defense Innovation Board, “AI Principles: Recommendations on the Ethical Use of Artificial
Intelligence by the Department of Defense,” October 31, 2019, https://media.defense.gov/2019/Oct/31/2002204458/-1/-
1/0/DIB_AI_PRINCIPLES_PRIMARY_DOCUMENT.PDF.
28 Ibid. and P.L. 115-232, Section 2, Division A, Title X, §1051. The Commission’s Interim Report, which assesses the
challenges and opportunities of militarily relevant AI technologies, is available at https://drive.google.com/file/d/
153OrxnuGEjsUvlxWsFYauslwNeCEkvUb/view. It identifies five key lines of effort for U.S. AI competitiveness: (1)
investing in research and development, (2) applying AI to national security missions, (3) training and recruiting AI
talent, (4) protecting and building upon U.S. technology advantages, and (5) marshalling global AI cooperation. The
commission is releasing recommendations for implementing these lines of effort every quarter. Its first quarter
recommendations, released in March 2020, are available at
https://drive.google.com/file/d/1wkPh8Gb5drBrKBg6OhGu5oNaTEERbKss/view. Second quarter recommendations,
released in July 2020, are available at
https://drive.google.com/file/d/1LDrd6T7H50ry9uXNA6cwhsrtnpQ63EWH/view.
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These initiatives will present a number of oversight opportunities for Congress.
In addition, Congress may consider the adequacy of current DOD funding levels for AI.
Lieutenant General John Shanahan, the former director of the JAIC, identified funding as a
barrier to future progress.29 Although DOD funding for AI has increased, beginning in 2018—to
include the JAIC’s $1.75 billion six-year budget and the Defense Advanced Research Projects
Agency’s (DARPA’s) $2 billion multiyear investment in over 20 AI programs—some experts
have argued that additional DOD funding will be required to keep pace with U.S. competitors and
avoid an “innovation deficit” in military technology.30
Critics of increased federal funding contend that significant increases to appropriations may not
be required, as the military should be leveraging research and development (R&D) conducted in
the commercial sector. The 2017 National Security Strategy identifies a need to “establish
strategic partnerships to align private sector R&D resources to priority national security
applications” and to reward government agencies that “take risks and rapidly field emerging
commercial technologies.”31 In addition, the Office of Management and Budget directed DOD in
preparing its FY2020 budget to “seek to rapidly field innovative technologies from the private
sector, where possible, that are easily adaptable to Federal needs, rather than reinventing solutions
in parallel.”32 Some experts in the national security community also argue that it would not be a
responsible use of taxpayer money to duplicate efforts devoted to AI R&D in the commercial
sector when companies take products 90% of the way to a useable military application.33 Others
contend that a number of barriers stand in the way of transitioning AI commercial technology to
DOD, and that reforming aspects of the defense acquisition process may be necessary.34 These
issues are discussed in more detail later in this report.35
One impediment to accurately evaluating funding levels for AI is the lack of a stand-alone AI
Program Element (PE) in DOD funding tables. As a result, AI R&D appropriations are spread
throughout generally titled PEs and incorporated into funding for larger systems with AI
components. For example, in the FY2019 National Defense Authorization Act, AI funding is
spread throughout the PEs for the High Performance Computing Modernization Program and

29 Justin Doubleday, “Project Maven Aims to Introduce AI tools into Services’ Intel Systems,” Inside Defense, January
5, 2018, https://insidedefense.com/inside-army/project-maven-aims-introduce-ai-tools-services-intel-systems, and
Jason Sherman, “ASB: S&T Funding Inadequate to Support ‘Big Bets’ on Disruptive Technologies,” Inside Defense,
December 15, 2017, https://insidedefense.com/inside-army/asb-st-funding-inadequate-support-big-bets-disruptive-
technologies.
30 “DARPA Announces $2 Billion Campaign to Develop Next Wave of AI Technologies,” DARPA, September 7,
2018, https://www.darpa.mil/news-events/2018-09-07; and Elsa B. Kania, “Battlefield Singularity: Artificial
Intelligence, Military Revolution, and China’s Future Military Power,” Center for a New American Security,
November 28, 2017, pp. 40-41, https://s3.amazonaws.com/files.cnas.org/documents/Battlefield-Singularity-November-
2017.pdf?mtime=20171129235804.
31 The White House, National Security Strategy of the United States of America, December 2017, p. 21,
https://www.whitehouse.gov/wp-content/uploads/2017/12/NSS-Final-12-18-2017-0905-2.pdf.
32 Executive Office of the President, Director, Office of Management and Budget, Memorandum for the Heads of
Executive Departments and Agencies, “FY 2020 Administration Research and Development Budget Priorities,” July
31, 2018, https://www.whitehouse.gov/wp-content/uploads/2018/07/M-18-22.pdf.
33 Dr. Matthijs Broer, Chief Technology Officer, Central Intelligence Agency, Comments at Defense One Summit,
November 9, 2017.
34 Testimony of Paul Scharre, House Armed Services Committee, Subcommittee on Emerging Threats and Capabilities,
Hearing on China’s Pursuit of Emerging Technologies.
35 For a discussion of recent defense acquisitions reform initiatives, see CRS Report R45068, Acquisition Reform in the
FY2016-FY2018 National Defense Authorization Acts (NDAAs), by Moshe Schwartz and Heidi M. Peters.
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Dominant Information Sciences and Methods, among others.36 On the other hand, a dedicated PE
for AI may lead to a false precision, as it may be challenging to identify exact investments in
enabling technologies like AI. The lack of an official U.S. government definition of AI could
further complicate such an assessment.
Congress may also consider specific policies for the development and use of military AI
applications. Many experts fear that the pace of AI technology development is moving faster than
the speed of policy implementation. Former Chairman of the House Armed Services Committee
Representative Mac Thornberry has echoed this sentiment, stating, “It seems to me that we’re
always a lot better at developing technologies than we are the policies on how to use them.”37
Congress may assess the need for new policies or modifications to existing laws to account for AI
developments and ensure that AI applications are free from bias.38 Perhaps the most immediate
policy concern among AI analysts is the absence of an independent entity to develop and enforce
AI safety standards and to oversee government-wide AI research.39 Former Secretary of Defense
Ashton B. Carter, for example, has suggested the need for an “AI czar” to coordinate such
efforts.40
Relatedly, Congress may consider debating policy options on the development and fielding of
Lethal Autonomous Weapons Systems (LAWS), which may use AI to select and engage targets.
Since 2014, the United States has participated in international discussions of LAWS at the United
Nations (U.N.) Convention on Certain Conventional Weapons (CCW). Approximately 30 state
parties have called for a treaty banning “fully autonomous weapon systems” due to ethical
considerations, while others have called for formal regulations or political declarations.41 Some
analysts are concerned that efforts to ban or regulate LAWS could impose strict controls on AI
applications that could be adapted for lethal use, thereby stifling development of other useful
military—or even commercial—technology. During recent testimony to the U.N., one expert
stated, “If we agree to foreswear some technology, we could end up giving up some uses of
automation that could make war more humane. On the other hand a headlong rush into a future of
increasing autonomy with no discussion of where it is taking us, is not in humanity’s interest
either.” He suggested the leading question for considering military AI applications ought to be,
“What role do we want humans to play in wartime decision making?”42

36 P.L. 115-232, Section 2, Division D, Title XLIII, §4301.
37 Morgan Chalfant, “Congress Told to Brace for Robotic Soldiers,” The Hill, March 1, 2017, http://thehill.com/policy/
cybersecurity/321825-congress-told-to-brace-for-robotic-soldiers.
38 See Parmy Olson, “Racist, Sexist AI Could Be a Bigger Problem than Lost Jobs,” Forbes, February 26, 2018,
https://www.forbes.com/sites/parmyolson/2018/02/26/artificial-intelligence-ai-bias-google/#3326a1951a01.
39 CRS discussion with Mike Garris, National Institute of Standards and Technology, Co-Chairman, Subcommittee on
Machine Learning and Artificial Intelligence, Committee on Technology, National Science and Technology Council,
October 2, 2017.
40 David Ignatius, “China’s application of AI should be a Sputnik moment for the U.S. But will it be?,” New York
Times, November 6, 2018, https://www.washingtonpost.com/opinions/chinas-application-of-ai-should-be-a-sputnik-
moment-for-the-us-but-will-it-be/2018/11/06/69132de4-e204-11e8-b759-3d88a5ce9e19_story.html?utm_term=
.88a808915d9c.
41 See “Country Views on Killer Robots,” Campaign to Stop Killer Robots, April 13, 2018,
https://www.stopkillerrobots.org/wp-content/uploads/2018/04/KRC_CountryViews_13Apr2018.pdf; and U.N. CCW
Working Papers and Statements at https://www.unog.ch/__80256ee600585943.nsf/(httpPages)/
7c335e71dfcb29d1c1258243003e8724?OpenDocument&ExpandSection=3#_Section3.
42 Paul Scharre, Remarks to the United Nations, Group of Governmental Experts on Lethal Autonomous Weapons
Systems, November 15, 2017, Geneva, Switzerland, https://s3.amazonaws.com/files.cnas.org/documents/Scharre-
Remarks-to-UN-on-Autonomous-Weapons-15-Nov-2017.pdf?mtime=20171120095806. For more information on
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Congress may consider the growth of international competition in the AI market and the danger
of foreign exploitation of U.S. AI technology for military purposes. In particular, the Chinese
government is reported to be aggressively pursuing AI investments in the United States. Amid
growing scrutiny of transactions involving Chinese firms in the semiconductor industry, in
September 2017 President Trump, following the recommendation of the Committee on Foreign
Investment in the United States (CFIUS), blocked a Chinese firm from acquiring Lattice
Semiconductor, a U.S. company that manufactures chips that are a critical design element for AI
technology.43 In this way, some experts believe that CFIUS may provide a means of protecting
strategically significant technologies like AI.44 Indeed, the Foreign Investment Risk Review
Modernization Act of 2018 (FIRRMA) expands CFIUS’s ability to review certain foreign
investments, including those involving “emerging and foundational technologies.” It also
authorized CFIUS to consider “whether a covered transaction involves a country of special
concern that has a demonstrated or declared strategic goal of acquiring a type of critical
technology or critical infrastructure that would affect United States leadership in areas related to
national security.”45 Congress may monitor the implementation of FIRRMA and assess whether
additional reforms might be necessary to maintain effective congressional oversight of sensitive
transactions.
In addition, many analysts believe that it may be necessary to reform federal data policies
associated with AI. Large data pools serve as the training sets needed for building many AI
systems, and government data may be particularly important in developing military AI
applications. However, some analysts have observed that much of this data is classified, access-
controlled, or otherwise protected on privacy grounds. These analysts contend that Congress
should implement a new data policy that balances data protection and privacy with the need to
fuel AI development.46
Closely related, AI development may increase the imperative for strict security standards. As
discussed later in this report, AI algorithms are vulnerable to bias, theft, and manipulation,
particularly if the training data set is not adequately curated or protected. During a February 2018
conference with defense industry CEOs, then-Deputy Defense Secretary Patrick Shanahan
advocated for higher cybersecurity standards in the commercial sector, stating, “[W]e want the
bar to be so high that it becomes a condition of doing business.”47 Some leading commercial

LAWS, see CRS Report R44466, Lethal Autonomous Weapon Systems: Issues for Congress, by Nathan J. Lucas.
43 Ana Swanson, “Trump Blocks China-Backed Bid to Buy U.S. Chip Maker,” The New York Times, September 13,
2017, https://www.nytimes.com/2017/09/13/business/trump-lattice-semiconductor-china.html.
44 Paul Scharre and Dean Cheng, Testimony to Subcommittee on Emerging Threats and Capabilities, Hearing on
China’s Pursuit of Emerging Technologies. For more information on CFIUS, see CRS Report RL33388, The
Committee on Foreign Investment in the United States (CFIUS), by James K. Jackson.
45 The specific technologies that qualify as “emerging and foundational technologies” are to be identified by an
interagency process led by the Department of Commerce. See P.L. 115-232, Title XVII, §1702(c). For more
information on FIRRMA, see CRS In Focus IF10952, CFIUS Reform: Foreign Investment National Security Reviews,
by James K. Jackson and Cathleen D. Cimino-Isaacs. Some entities, including the National Security Commission on
Artificial Intelligence, have argued that the U.S. government should consider alternative approaches to AI technology
protection, such as “heavier scrutiny of the potential end use and end user of specific items,” that could potentially
reduce the burden on U.S. corporations. See National Security Commission on Artificial Intelligence, Interim Report,
November 2019, https://drive.google.com/file/d/153OrxnuGEjsUvlxWsFYauslwNeCEkvUb/view.
46 Alexander Velez-Green and Paul Scharre, “The United States Can Be a World Leader in AI. Here’s How.,” The
National Interest, November 2, 2017, https://nationalinterest.org/feature/the-united-states-can-be-world-leader-ai-
heres-how-22921.
47 Marcus Weisgerber, “Pentagon Warns CEOs: Protect Your Data or Lose Our Contracts,” Defense One, February 6,
2018, http://www.defenseone.com/business/2018/02/pentagon-warns-ceos-protect-your-data-or-lose-our-contracts/
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technology companies have issued similar calls for increased scrutiny, with Microsoft president
Brad Smith arguing that a lack of regulation in this area could lead to “a commercial race to the
bottom, with tech companies forced to choose between social responsibility and market
success.”48
Finally, commercial companies have long cited the potential loss of intellectual property rights as
a key impediment to partnering with DOD. In recognition of this issue, Section 813 of the
FY2016 NDAA established a “government-industry advisory panel” to provide recommendations
on technical data rights and intellectual property reform.49 The panel’s report, released in
November 2018, offers a number of recommendations, including increased training in intellectual
property rights for acquisitions professionals and a pilot program for intellectual property
valuation in the procurement process.50
AI Applications for Defense
DOD is considering a number of diverse applications for AI. Currently, AI R&D is being left to
the discretion of research organizations in the individual services, as well as to DARPA and the
Intelligence Advanced Research Projects Agency (IARPA). However, DOD components are
required to coordinate with the JAIC regarding any planned AI initiatives costing more than $15
million annually.51 In addition, the JAIC has been tasked with overseeing the National Mission
Initiatives (NMI), projects that leverage AI to address pressing operational challenges.52 The
JAIC began work on its first two NMIs—predictive maintenance and humanitarian assistance and
disaster relief—in 2019. According to JAIC acting director Nand Mulchandani, the JAIC is
currently focused on joint warfighting and, in May 2020, was awarded an $800 million contract
to Booz Allen Hamilton to “bring AI to the battlefield.”53 AI is being incorporated into a number
of other intelligence, surveillance, and reconnaissance applications, as well as in logistics,
cyberspace operations, information operations, command and control, semiautonomous and
autonomous vehicles, and lethal autonomous weapon systems.

145779/?oref=d-river. For more on cybersecurity legislation, see CRS Report R42114, Federal Laws Relating to
Cybersecurity: Overview of Major Issues, Current Laws, and Proposed Legislation, by Eric A. Fischer.
48 Brad Smith, “Facial recognition: It’s time for action,” Microsoft, December 6, 2018, https://blogs.microsoft.com/on-
the-issues/2018/12/06/facial-recognition-its-time-for-action/?mod=article_inline.
49 P.L. 114-92, Section 2, Division A, Title VIII, §813.
50 2018 Report, Government-Industry Advisory Panel on Technical Data Rights, November 21, 2018, p. 5,
https://sbtc.org/wp-content/uploads/2018/11/Final-Report_ExSum_TensionPapers_11132018.pdf.
51 This coordination threshold will be reviewed each year and adjusted upwards, as conditions warrant. Patrick
Shanahan, Deputy Secretary of Defense, Memorandum, “Establishment of the Joint Artificial Intelligence Center,”
June 27, 2018, https://admin.govexec.com/media/
establishment_of_the_joint_artificial_intelligence_center_osd008412-18_r.... pdf.
52 Ibid.
53 Other mission initiatives include warfighter health, business process transformation, threat reduction and protection,
joint logistics, and joint information warfare. Jackson Barnett, “The vast majority of JAIC’s money is going toward
warfighting,” Fedscoop, July 8, 2020, https://www.fedscoop.com/jaic-military-ai-money-war-warfighting-mission-
initative/.
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Intelligence, Surveillance, and Reconnaissance
AI is expected to be particularly useful in intelligence due to the large data sets available for
analysis.54 For example, Project Maven is intended to incorporate computer vision and machine
learning algorithms into intelligence collection cells that would comb through footage from
uninhabited aerial vehicles and automatically identify hostile activity for targeting. In this
capacity, AI is intended to automate the work of human analysts who currently spend hours
sifting through drone footage for actionable information, potentially freeing analysts to make
more efficient and timely decisions based on the data.55
The intelligence community also has a number of publicly acknowledged AI research projects in
progress. The Central Intelligence Agency alone has around 140 projects in development that
leverage AI in some capacity to accomplish tasks such as image recognition and predictive
analytics.56 IARPA is sponsoring several AI research projects intended to produce other analytic
tools within the next four to five years. Some examples include developing algorithms for
multilingual speech recognition and translation in noisy environments, geo-locating images
without the associated metadata, fusing 2-D images to create 3-D models, and building tools to
infer a building’s function based on pattern-of-life analysis.57
Logistics
AI may have future utility in the field of military logistics. The Air Force, for example, is
beginning to use AI for predictive aircraft maintenance. Instead of making repairs when an
aircraft breaks or in accordance with standardized fleet-wide maintenance schedules, the Air
Force is testing an AI-enabled approach that tailors maintenance schedules to the needs of
individual aircraft. This approach, currently used by the F-35’s Autonomic Logistics Information
System, extracts real-time sensor data embedded in the aircraft’s engines and other onboard
systems and feeds the data into a predictive algorithm to determine when technicians need to
inspect the aircraft or replace parts.58
Similarly, the Army’s Logistics Support Activity (LOGSA) has contracted IBM’s Watson (the
same AI software that defeated two Jeopardy champions) to develop tailored maintenance
schedules for the Stryker fleet based on information pulled from the 17 sensors installed on each
vehicle. In September 2017, LOGSA began a second project that will use Watson to analyze
shipping flows for repair parts distribution, attempting to determine the most time- and cost-
efficient means to deliver supplies. This task is currently done by human analysts, who have
saved the Army around $100 million a year by analyzing just 10% of shipping requests; with
Watson, the Army will have the ability to analyze 100% of shipping requests, potentially
generating even greater cost savings in a shorter period of time.59

54 CRS discussions with Dr. Richard Linderman, October 24, 2017.
55 Corrigan, “Three-Star General Wants AI in Every New Weapon System.”
56 Patrick Tucker, “What the CIA’s Tech Director Wants from AI,” Defense One, September 6, 2017,
http://www.defenseone.com/technology/2017/09/cia-technology-director-artificial-intelligence/140801/.
57 CRS discussions with Dr. Jason Matheny, IARPA Director, October 10, 2017, and https://www.iarpa.gov/index.php/
research-programs.
58 Marcus Weisgerber, “Defense Firms to Air Force: Want Your Planes’ Data? Pay Up,” Defense One, September 19,
2017, http://www.defenseone.com/technology/2017/09/military-planes-predictive-maintenance-technology/141133/.
59 Adam Stone, “Army Logistics Integrating New AI, Cloud Capabilities,” September 7, 2017,
https://www.c4isrnet.com/home/2017/09/07/army-logistics-integrating-new-ai-cloud-capabilities/.
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Cyberspace Operations
AI is likely to be a key technology in advancing military cyber operations. In his 2016 testimony
before the Senate Armed Services Committee, Commander of U.S. Cyber Command Admiral
Michael Rogers stated that relying on human intelligence alone in cyberspace is “a losing
strategy.”60 He later clarified this point, stating, “If you can’t get some level of AI or machine
learning with the volume of activity you’re trying to understand when you’re defending networks
... you are always behind the power curve.”61 Conventional cybersecurity tools look for historical
matches to known malicious code, so hackers only have to modify small portions of that code to
circumvent the defense. AI-enabled tools, on the other hand, can be trained to detect anomalies in
broader patterns of network activity, thus presenting a more comprehensive and dynamic barrier
to attack.62
DARPA’s 2016 Cyber Grand Challenge demonstrated the potential power of AI-enabled cyber
tools. The competition challenged participants to develop AI algorithms that could autonomously
“detect, evaluate, and patch software vulnerabilities before [competing teams] have a chance to
exploit them”—all within a matter of seconds, rather than the usual months.63 The challenge
demonstrated not only the potential speed of AI-enabled cyber tools but also the potential ability
of a singular algorithm to play offense and defense simultaneously. These capabilities could
provide a distinct advantage in future cyber operations.
Information Operations and “Deep Fakes”64
AI is enabling increasingly realistic photo, audio, and video forgeries, or “deep fakes,” that
adversaries could deploy as part of their information operations. Indeed, deep fake technology
could be used against the United States and U.S. allies to generate false news reports, influence
public discourse, erode public trust, and attempt to blackmail diplomats.65 Although most
previous deep fakes have been detectable by experts, the sophistication of the technology is
progressing to the point that it may soon be capable of fooling forensic analysis tools.66
In order to combat deep fake technologies, DARPA has launched the Media Forensics (MediFor)
project, which seeks to “automatically detect manipulations, provide detailed information about
how these manipulations were performed, and reason about the overall integrity of visual

60 Testimony of Michael Rogers, Senate Armed Services Committee, Hearing to Receive Testimony on Encryption and
Cyber Matters, September 13, 2016, https://www.armed-services.senate.gov/imo/media/doc/16-68_09-13-16.pdf.
61 Amaani Lyle, “National Security Experts Examine Intelligence Challenges at Summit,” September 9, 2016,
https://www.defense.gov/News/Article/Article/938941/national-security-experts-examine-intelligence-challenges-at-
summit/.
62 Scott Rosenberg, “Firewalls Don’t Stop Hackers, AI Might,” Wired, August 27, 2017, https://www.wired.com/story/
firewalls-dont-stop-hackers-ai-might/.
63 “’Mayhem’ Declared Preliminary Winner of Historic Cyber Grand Challenge,” August 4, 2016,
https://www.darpa.mil/news-events/2016-08-04.
64 For a more detailed discussion of information operations, see CRS Report R45142, Information Warfare: Issues for
Congress, by Catherine A. Theohary. For a more detailed discussion of deep fakes, see CRS In Focus IF11333, Deep
Fakes and National Security, by Kelley M. Sayler and Laurie A. Harris.
65 Kyle Rempfer, “Ever heard of ‘deep fake’ technology? The phony audio and video tech could be used to blackmail
US troops,” Military Times, July 19, 2018, https://www.militarytimes.com/news/your-air-force/2018/07/19/ever-heard-
of-deep-fake-technology-the-phony-audio-and-video-tech-could-be-used-to-blackmail-us-troops/.
66 Allen and Chan, p. 29.
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media.”67 MediFor has developed some initial tools for identifying AI-produced forgeries, but as
one analyst has noted, “a key problem … is that machine-learning systems can be trained to
outmaneuver forensics tools.”68 For this reason, DARPA plans to host follow-on contests to
ensure that forensic tools keep pace with deep fake technologies.69
Artificial intelligence could also be used to create full “digital patterns-of-life,” in which an
individual’s digital “footprint” is “merged and matched with purchase histories, credit reports,
professional resumes, and subscriptions” to create a comprehensive behavioral profile of
servicemembers, suspected intelligence officers, government officials, or private citizens.70 As in
the case of deep fakes, this information could, in turn, be used for targeted influence operations or
blackmail.
Command and Control
The U.S. military is seeking to exploit AI’s analytic potential in the area of command and control.
DOD is developing various systems in support of its concept of Joint All Domain Command and
Control (JADC2), which aims to centralize planning and execution of air-, space-, cyberspace-,
sea-, and land-based operations.71 In the immediate future, AI may be used to fuse data from
sensors in all of these domains to create a single source of information, also known as a “common
operating picture,” for decisionmakers.72 Currently, information available to decisionmakers
comes in diverse formats from multiple platforms, often with redundancies or unresolved
discrepancies. An AI-enabled common operating picture would theoretically combine this
information into one display, providing a comprehensive picture of friendly and enemy forces,
and automatically resolving variances from input data. Such a system could eventually enable
“any sensor to provide data to any shooter from any service, ally, or partner … to achieve effects
against any target.”73 The services have a number of related programs that are designed to
demonstrate the capabilities needed to execute JADC2, including the Army’s Project
Convergence and the Air Force’s Advanced Battle Management System.74 Similarly, DARPA’s
Mosaic Warfare program seeks to leverage AI to network systems and sensors, prioritize
incoming sensor data, and autonomously determine the optimal composition of forces. 75

67 “Media Forensics (MediFor),” DARPA, https://www.darpa.mil/program/media-forensics.
68 Will Knight, “The Defense Department has produced the first tools for catching deepfakes,” MIT Technology
Review, August 7, 2018, https://www.technologyreview.com/s/611726/the-defense-department-has-produced-the-first-
tools-for-catching-deepfakes/.
69 Ibid.
70 Clint Watts, “Artificial intelligence is transforming social media. Can American democracy survive?,” Washington
Post, September 5, 2018, https://www.washingtonpost.com/news/democracy-post/wp/2018/09/05/artificial-
intelligence-is-transforming-social-media-can-american-democracy-survive/?utm_term=.7e7a5ef245db.
71 For more information about JADC2, see CRS In Focus IF11493, Defense Capabilities: Joint All Domain Command
and Control, by John R. Hoehn and Nishawn S. Smagh.
72 Colin Clark, “‘Rolling the Marble’: BG Saltzman on Air Force’s Multi-Domain C2 System,” Breaking Defense,
August 8, 2017, https://breakingdefense.com/2017/08/rolling-the-marble-bg-saltzman-on-air-forces-multi-domain-c2-
system/.
73 Theresa Hitchens, “Air Force Expands 5G As It Transforms to Multi-Domain Ops: Donovan,” Breaking Defense,
September 4, 2019, https://breakingdefense.com/2019/09/air-force-expands-5g-as-it-transforms-to-multi-domain-ops-
donovan/.
74 Jay Koester, “JADC2 ‘Experiment 2’ provides looking glass into future experimentation,” U.S. Army, April 23,
2020,
https://www.army.mil/article/234900/jadc2_experiment_2_provides_looking_glass_into_future_experimentation.
75 “Strategic Technology Office Outlines Vision for ‘Mosaic Warfare,’” DARPA, August 4, 2017,
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Future AI systems may be used to identify communications links cut by an adversary and find
alternative means of distributing information. As the complexity of AI systems matures, AI
algorithms may also be capable of providing commanders with a menu of viable courses of action
based on real-time analysis of the battle-space, potentially improving the quality and speed of
wartime decisionmaking.76
Semiautonomous and Autonomous Vehicles
All U.S. military services are working to incorporate AI into semiautonomous and autonomous
vehicles, including fighter aircraft, drones, ground vehicles, and naval vessels. AI applications in
this field are similar to those for commercial semiautonomous vehicles, which use AI
technologies to perceive the environment, recognize obstacles, fuse sensor data, plan navigation,
and even communicate with other vehicles.77
The Air Force Research Lab completed phase-two tests of its Loyal Wingman program, which
pairs an older-generation, uninhabited fighter jet (in this case, an F-16) with an inhabited F-35 or
F-22. During this event, the uninhabited F-16 test platform autonomously reacted to events that
were not preprogrammed, such as weather and unforeseen obstacles.78 As the program progresses,
AI may enable the “loyal wingman” to accomplish tasks for its inhabited flight lead, such as
jamming electronic threats or carrying extra weapons.79
The Army and the Marine Corps tested prototypes of similar vehicles that follow soldiers or
vehicles around the battlefield to accomplish independent tasks.80 For example, the Marine Corps’
Multi-Utility Tactical Transport (MUTT) is a remote-controlled, ATV-sized vehicle capable of
carrying hundreds of pounds of extra equipment. Although the system is not autonomous in its
current configuration, the Marine Corps intends for follow-on systems to have greater
independence.81 Likewise, the Army plans to field a number of Robotic Combat Vehicles (RCVs)
with different types of autonomous functionality, including navigation, surveillance, and IED
removal. These systems are to be deployed as “wingmen” for the Optionally Manned Fighting
Vehicle.82
DARPA completed testing of the Anti-Submarine Warfare Continuous Trail Unmanned Vessel
prototype, or “Sea Hunter,” in early 2018 before transitioning program development to the
Navy.83 Sea Hunter has since been integrated into Surface Development Squadron 1, which has

https://www.darpa.mil/news-events/2017-08-04.
76 See, for example, “Generating Actionable Understanding of Real-World Phenomena with AI,” DARPA, January 4,
2019, https://www.darpa.mil/news-events/2019-01-04.
77 CRS Report R44940, Issues in Autonomous Vehicle Deployment, by Bill Canis, pp. 2-3.
78 David Axe, “US Air Force Sends Robotic F-16s into Mock Combat,” The National Interest, May 16, 2017,
http://nationalinterest.org/blog/the-buzz/us-air-force-sends-robotic-f-16s-mock-combat-20684.
79 Mark Pomerlau, “Loyal Wingman Program Seeks to Realize Benefits of Advancements in Autonomy,” October 19,
2016, https://www.c4isrnet.com/unmanned/uas/2016/10/19/loyal-wingman-program-seeks-to-realize-benefits-of-
advancements-in-autonomy/.
80 For an overview of semiautonomous and autonomous ground vehicles, see CRS Report R45392, U.S. Ground Forces
Robotics and Autonomous Systems (RAS) and Artificial Intelligence (AI): Considerations for Congress, coordinated by
Andrew Feickert.
81 Kristin Houser, “The Marines’ Latest Weapon is a Remote-Controlled Robot with a Machine Gun,” May 4, 2017,
https://futurism.com/the-marines-latest-weapon-is-a-remote-controlled-robot-with-a-machine-gun/.
82 CRS Report R45519, The Army’s Optionally Manned Fighting Vehicle (OMFV) Program: Background and Issues
for Congress, by Andrew Feickert.
83 “ACTUV ‘Sea Hunter’ Prototype Transitions to Office of Naval Research for Further Development,” DARPA,
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been tasked with overseeing “fleet familiarization, training and tactics development of [unmanned
surface vessels].” If Sea Hunter enters into service, it would provide the Navy with the ability to
autonomously navigate the open seas, swap out modular payloads, and coordinate missions with
other unmanned vessels—all while providing continuous submarine-hunting coverage for months
at a time.84 Some analysts estimate that Sea Hunter would cost around $20,000 a day to operate,
in contrast to around $700,000 for a traditionally inhabited destroyer.85
DOD is testing other AI-fueled capabilities to enable cooperative behavior, or swarming.
Swarming is a unique subset of autonomous vehicle development, with concepts ranging from
large formations of low-cost vehicles designed to overwhelm defensive systems to small
squadrons of vehicles that collaborate to provide electronic attack, fire support, and localized
navigation and communication nets for ground-troop formations.86 A number of different swarm
capabilities are currently under development. For example, in November 2016, the Navy
completed a test of an AI-enabled swarm of five unmanned boats that cooperatively patrolled a 4-
by-4-mile section of the Chesapeake Bay and intercepted an “intruder” vessel. The results of this
experiment may lead to AI technology adapted for defending harbors, hunting submarines, or
scouting in front of a formation of larger ships.87 The Navy also plans to test swarms of
underwater drones, and the Strategic Capabilities Office has successfully tested a swarm of 103
air-dropped micro-drones.88
Swarm Characteristics89

Autonomous (not under centralized control)

Capable of sensing their local environment and other
nearby swarm participants

Able to communicate locally with others in the swarm

Able to cooperate to perform a given task
Lethal Autonomous Weapon Systems (LAWS)
Lethal Autonomous Weapon Systems (LAWS) are a special class of weapon systems that use
sensor suites and computer algorithms to independently identify a target and employ an onboard
weapon system to engage and destroy the target without manual human control of the system.
Although these systems generally do not yet exist, it is believed they would enable military
operations in communications-degraded or -denied environments in which traditional systems

January 30, 2018, https://www.darpa.mil/news-events/2018-01-30a.
84 Ibid.
85 Julian Turner, “Sea Hunter: inside the US Navy’s autonomous submarine tracking vessel,” Naval Technology.
86 Mary-Ann Russon, “Google Robot Army and Military Drone Swarms: UAVs May Replace People in the Theatre of
War,” International Business Times, April 16, 2015, http://www.ibtimes.co.uk/google-robot-army-military-drone-
swarms-uavs-may-replace-people-theatre-war-1496615.
87 Sydney J. Freedberg Jr., “Swarm 2: The Navy’s Robotic Hive Mind,” Breaking Defense, December 14, 2016,
https://breakingdefense.com/2016/12/swarm-2-the-navys-robotic-hive-mind/.
88 Gidget Fuentes, “Navy Will Test Swarming Underwater Drones in Summer Exercise,” USNI News, June 26, 2018,
https://news.usni.org/2018/06/26/navy-will-test-swarming-underwater-drones-summer-exercise; and “Department of
Defense Announces Successful Micro-Drone Demonstration,” Department of Defense, January 9, 2017,
https://dod.defense.gov/News/News-Releases/News-Release-View/Article/1044811/department-of-defense-announces-
successful-micro-drone-demonstration/.
89 Ilachinski, p. 108.
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may not be able to operate. The U.S. military does not currently have LAWS in its inventory,
although there are no legal prohibitions on the development of LAWS.
DOD Directive 3000.09, “Autonomy in Weapon Systems,” outlines department policies for
semiautonomous and autonomous weapon systems.90 The directive requires that all systems,
regardless of classification, be designed to “allow commanders and operators to exercise
appropriate levels of human judgment over the use of force” and to successfully complete the
department’s weapons review process.91 Any changes to the system’s operating state require that
the system go through the weapons review process again to ensure that it has retained the ability
to operate as intended. Autonomous weapons and a limited type of semiautonomous weapons
must additionally be approved before both development and fielding by the Under Secretary of
Defense for Policy, the Chairman of the Joint Chiefs of Staff, and either the Under Secretary of
Defense for Acquisition and Sustainment or the Under Secretary of Defense for Research and
Engineering. Human-supervised autonomous weapons used for point defense of manned
installations or platforms—but that do not target humans—and autonomous weapons that “apply
non-lethal, non-kinetic force, such as some forms of electronic attack, against materiel targets”
are exempted from this senior-level review.92
Despite this policy, some senior military and defense leaders have expressed concerns about the
prospect of fielding LAWS. For example, in 2017 testimony before the Senate Armed Services
Committee, then-Vice Chairman of the Joint Chiefs of Staff General Paul Selva stated, “I do not
think it is reasonable for us to put robots in charge of whether or not we take a human life.”93
Regardless, General Selva explained that the military will be compelled to address the
development of this class of technology in order to find its vulnerabilities, given the fact that
potential U.S. adversaries are pursuing LAWS.94 Indeed, as Secretary of Defense Mark Esper has
noted, “Chinese weapons manufacturers are selling drones advertised as capable of full
autonomy, including the ability to conduct lethal targeted strikes.”95
Military AI Integration Challenges
From the Cold War era until recently, most major defense-related technologies, including nuclear
technology, the Global Positioning System (GPS), and the internet, were first developed by
government-directed programs before later spreading to the commercial sector.96 Indeed,

90 For a full explanation of the requirements of DOD Directive 3000.09, see CRS In Focus IF11150, Defense Primer:
U.S. Policy on Lethal Autonomous Weapon Systems, by Kelley M. Sayler.
91 Department of Defense, Directive 3000.09, Autonomy in Weapon Systems.
92 Ibid.
93 U.S. Congress, Senate Committee on Armed Services, Hearing to Consider the Nomination of General Paul J. Selva,
USAF, for Reappointment to the Grade of General and Reappointment to be Vice Chairman of the Joint Chiefs of Staff,
115th Cong., 1st sess., July 18, 2017 (Washington, DC: GPO, 2017).
94 Ibid. For a full discussion of LAWS, see CRS Report R44466, Lethal Autonomous Weapon Systems: Issues for
Congress, by Nathan J. Lucas.
95 Patrick Tucker, “SecDef: China Is Exporting Killer Robots to the Mideast,” Defense One, November 5, 2019,
https://www.defenseone.com/technology/2019/11/secdef-china-exporting-killer-robots-mideast/161100/.
96 William H. McNeill, The Pursuit of Power (Chicago: The University of Chicago Press, 1982), pp. 368-369. In this
history of technology, warfare, and international competition, McNeill discusses government mobilization of the
science and engineering community. The effort started in WWII with the creation of large research and development
organizations dedicated to creating war-winning technology. The government continued to invest large amounts of
money into research and development during the Cold War, as technological superiority was perceived as a key
measure of national strength. McNeill states, “The ultimate test of American society in its competition with the Soviets
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DARPA’s Strategic Computing Initiative invested over $1 billion between 1983 and 1993 to
develop the field of artificial intelligence for military applications, but the initiative was
ultimately cancelled due to slower-than-anticipated progress.97 Today, commercial companies—
sometimes building on past government-funded research—are leading AI development, with
DOD later adapting their tools for military applications.98 Noting this dynamic, one AI expert
commented, “It is unusual to have a technology that is so strategically important being developed
commercially by a relatively small number of companies.”99 In addition to the shift in funding
sources, a number of challenges related to technology, process, personnel, and culture continue to
impede the adoption of AI for military purposes.
Technology
A wide variance exists in the ease of adaptability of commercial AI technology for military
purposes. In some cases, the transition is relatively seamless. For example, the aforementioned
aircraft maintenance algorithms, many of which were initially developed by the commercial
sector, will likely require only minor data adjustments to account for differences between aircraft
types. In other circumstances, significant adjustments are required due to the differences between
the structured civilian environments for which the technology was initially developed and more
complex combat environments. For example, commercial semiautonomous vehicles have largely
been developed in and for data-rich environments with reliable GPS positions, comprehensive
terrain mapping, and up-to-date information on traffic and weather conditions obtained from
other networked vehicles.100 In contrast, the military variant of such a vehicle would need to be
able to operate in locations where map data are comparatively poor and in which GPS positioning
may be inoperable due to adversary jamming. Moreover, semiautonomous or autonomous
military ground vehicles would likely need the ability to navigate off-road in rough terrain—a
capability not inherent in most commercial vehicles.101
Process
Standing DOD processes—including those related to standards of safety and performance,
acquisitions, and intellectual property and data rights—present another challenge to the
integration of military AI. Often, civilian and military standards of safety and performance are
either not aligned or are not easily transferable. A failure rate deemed acceptable for a civilian AI
application may be well outside of tolerances in a combat environment—or vice versa. In
addition, a recent research study concluded that unpredictable AI failure modes will be

boiled down to finding out which contestant could develop superior skills in every field of human endeavor.... This
would guarantee prosperity at home and security abroad.” This effort had lingering effects that have persisted to some
extent in the wake of the Cold War.
97 Alex Roland with Philip Shiman, Strategic Computing: DARPA and the Quest for Machine Intelligence, 1983-1993
(Cambridge, Massachusetts: The MIT Press, 2002), p. 1 and p. 285.
98 For example, the foundational research that eventually led to the creation of Google was funded by a National
Science Foundation grant. David Hart, “On the Origins of Google,” National Science Foundation, August 17, 2004,
https://www.nsf.gov/discoveries/disc_summ.jsp?cntn_id=100660.
99 Dr. Ed Felten, Comments at the Global Security Forum, Center for Strategic and International Studies, Washington,
DC, November 7, 2017.
100 CRS In Focus IF10658, Autonomous Vehicles: Emerging Policy Issues, by Bill Canis.
101 Based on CRS discussions with Dr. Dai H. Kim, Associate Director for Advanced Computing, Office of the
Assistant Secretary of Defense for Research and Engineering, October 4, 2017.
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exacerbated in complex environments, such as those found in combat.102 Collectively, these
factors may create another barrier for the smooth transfer of commercially developed AI
technology to DOD.
DOD may need to continue to adjust its acquisitions process to account for rapidly evolving
technologies such as AI.103 A 2017 internal study of the process found that it takes an average of
91 months to move from the initial Analysis of Alternatives, defining the requirements for a
system, to an Initial Operational Capability.104 In contrast, commercial companies typically
execute an iterative development process for software systems like AI, delivering a product in six
to nine months.105 These findings prompted DOD to issue an interim software acquisition policy
intended to “[simplify] the acquisition model to enable continuous integration and delivery of
software capability on timelines relevant to the Warfighter/end user.”106
Furthermore, the commercial companies that are often at the forefront of AI innovation may be
reluctant to partner with DOD due to the complexity of the defense acquisition process. A
Government Accountability Office (GAO) study of this issue found that, of 12 U.S. commercial
companies who choose not to do business with DOD, all 12 cited the complexity of the defense
acquisition process as a rationale for their decision.107 DOD has created a number of avenues for
“rapid-acquisitions”—including the Strategic Capabilities Office, the Defense Innovation Unit,
and Project Maven—that are intended streamline cumbersome processes and accelerate the
acquisitions timeline.108 Project Maven, for example, was established in April 2017; by
December, the team was fielding a commercially acquired prototype AI system in combat.109
Although some analysts argue that these are promising developments, critics point out that the
department must replicate the results achieved by Project Maven at scale and implement more
comprehensive acquisitions reform.110
Commercial technology companies are also often reluctant to partner with DOD due to concerns
about intellectual property and data rights.111 As an official interviewed for a 2017 GAO report on
broader challenges in military acquisitions noted, intellectual property is the “life blood” of
commercial technology companies, yet “DOD is putting increased pressure on companies to grant

102 Allen and Chan, pp. 4-6.
103 Ilachinski, pp. 190-191.
104 Ibid, p. 189.
105 Defense Science Board, “Design and Acquisition of Software for Defense Systems,” February 2018,
https://www.acq.osd.mil/dsb/reports/2010s/DSB_SWA_Report_FINALdelivered2-21-2018.pdf.
106 Office of the Under Secretary of Defense for Acquisition and Sustainment, “Software Acquisition Pathway Interim
Policy and Procedures,” January 3, 2020, https://www.acq.osd.mil/ae/assets/docs/USA002825-
19%20Signed%20Memo%20(Software).pdf.
107 U.S. Government Accountability Office, Military Acquisitions, DOD is Taking Step to Address Challenges Faced
by Certain Companies, GAO-17-644, July 20, 2017, p. 9. Other rationales cited include unstable budget environment,
lengthy contracting timeline, government-specific contract terms and conditions, and inexperienced DOD contracting
workforce.
108 In certain circumstances, DOD may also use other transaction authorities (OTAs) to accelerate research,
prototyping, and production. For additional information about OTAs, see CRS Report R45521, Department of Defense
Use of Other Transaction Authority: Background, Analysis, and Issues for Congress, by Heidi M. Peters.
109 Marcus Weisgerber, “The Pentagon’s New Artificial Intelligence is Already Hunting Terrorists,” Defense One,
December 21, 2017, http://www.defenseone.com/technology/2017/12/pentagons-new-artificial-intelligence-already-
hunting-terrorists/144742/.
110 Ilachinski, p. 190.
111 U.S. Government Accountability Office, Military Acquisitions, DOD is Taking Steps to Address Challenges Faced
by Certain Companies.
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unlimited technical data and software rights or government purpose rights rather than limited or
restricted rights.”112 In an effort to manage these concerns, DOD released an instruction that
“establishes policy, assigns responsibilities, and prescribes procedures for the acquisition,
licensing, and management of IP.”113 The instruction additionally establishes a DOD IP Cadre to
advise and assist the acquisition workforce on matters related to IP and calls for the development
of an IP strategy to “identify and manage the full spectrum of IP and related matters” for each
acquisition program.114
Personnel
Some reports indicate that DOD and the defense industry also face challenges when it comes to
recruiting and retaining personnel with expertise in AI due to research funding and salaries that
significantly lag behind those of commercial companies.115 Other reports suggest that such
challenges stem from quality-of-life factors, as well as from a belief among many technology
workers that “they can achieve large-scale change faster and better outside the government than
within it.”116 This sentiment echoes the findings of the National Security Commission on
Artificial Intelligence, which notes that “AI experts would be willing to serve in government if
officials could create a more compelling sense of purpose and a technical environment within
government that would maximize their talents.”117 Regardless, observers note that if DOD and
defense industry are unable to recruit and retain the appropriate experts, military AI applications
could be delayed, “deficient, or lacking in appropriate safeguards and testing.”118
To address these challenges, the Obama Administration launched the Defense Digital Service in
2015 as a means of recruiting private sector technology workers to serve in DOD for one to two
year assignments—a “tour of duty for nerds,” according to former director Chris Lynch.119
Similarly, former Deputy Secretary of Defense Bob Work has proposed an “AI Training Corps,”
in which DOD “would pay for advanced technical education in exchange for two days a month of
training with government systems and two weeks a year for major exercises.” Participants in the
program could additionally be called to government service in the event of a national
emergency.120 Other analysts have recommended the establishment of new military training and

112 Ibid., p. 20.
113 Office of the Under Secretary of Defense for Acquisition and Sustainment, “DOD Instruction 5010.44 Intellectual
Property (IP) Acquisition and Licensing,” October 16, 2019,
https://www.esd.whs.mil/Portals/54/Documents/DD/issuances/dodi/501044p.PDF?ver=2019-10-16-144448-070.
114 Ibid., pp. 8-11.
115 M.L. Cummings, “Artificial Intelligence and the Future of Warfare,” Chatham House, January 2017, p. 11,
https://www.chathamhouse.org/sites/default/files/publications/research/2017-01-26-artificial-intelligence-future-
warfare-cummings-final.pdf.
116 Amy Zegart and Kevin Childs, “The Divide between Silicon Valley and Washington Is a National-Security Threat,”
The Atlantic, December 13, 2018, https://www.theatlantic.com/ideas/archive/2018/12/growing-gulf-between-silicon-
valley-and-washington/577963/.
117 National Security Commission on Artificial Intelligence, Interim Report, November 2019, p. 35,
https://drive.google.com/file/d/153OrxnuGEjsUvlxWsFYauslwNeCEkvUb/view.
118 Amy Zegart and Kevin Childs, “The Divide between Silicon Valley and Washington Is a National-Security Threat.”
119 Jim Garamone, “Defense Digital Service Emphasizes Results for Service Members,” DOD News, June 26, 2018,
https://dod.defense.gov/News/Article/Article/1560057/defense-digital-service-emphasizes-results-for-service-members/
.
120 Ignatius, “China’s Application of AI.”
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occupational specialties to cultivate AI talent, as well as the creation of government fellowships
and accelerated promotion tracks to reward the most talented technology workers.121
Culture
An apparent cultural divide between DOD and commercial technology companies may also
present challenges for AI adoption. A recent survey of leadership in several top Silicon Valley
companies found that nearly 80% of participants rated the commercial technology community’s
relationship with DOD as poor or very poor.122 This was due to a number of factors, including
process challenges, perceptions of mutual distrust, and differences between DOD and commercial
incentive structures.123
Moreover, some companies are refusing to work with DOD due to ethical concerns over the
government’s use of AI in surveillance or weapon systems. Notably, Google canceled existing
government contracts for two robotics companies it acquired—Boston Dynamics and Schaft—
and prohibited future government work for DeepMind, a Google-acquired AI software startup.124
In May 2018, Google employees successfully lobbied the company to withdraw from Project
Maven and refrain from further collaboration with DOD.125 Other companies, however, have
pledged to continue supporting DOD contracts, with Amazon CEO Jeff Bezos noting that “if big
tech companies are going to turn their back on the U.S. Department of Defense, this country is
going to be in trouble.”126
Cultural factors within the defense establishment itself may also impede AI integration. The
integration of AI into existing systems alters standardized procedures and upends well-defined
personnel roles. Members of Project Maven have reported a resistance to AI integration because
integration can be disruptive without always providing an immediately recognizable benefit.127
Deputy Director for CIA technology development Dawn Meyerriecks has also expressed concern
about the willingness of senior leaders to accept AI-generated analysis, arguing that the defense
establishment’s risk-averse culture may pose greater challenges to future competitiveness than the
pace of adversary technology development.128
Finally, some analysts are concerned that DOD will not capitalize on AI’s potential to produce
game-changing warfighting benefits and will instead simply use AI to incrementally improve
existing processes or reinforce current operational concepts. Furthermore, the services may reject
certain AI applications altogether if the technology threatens service-favored hardware or

121 Kania, “Battlefield Singularity,” p. 36; and Zegart and Childs, “The Divide between Silicon Valley and
Washington.”
122 Loren DeJonge Schulman, Alexandra Sander, and Madeline Christian, “The Rocky Relationship Between
Washington and Silicon Valley: Clearing the Path to Improved Collaboration,” Center for a New American Security,
July 19, 2017, p. 4, https://s3.amazonaws.com/files.cnas.org/documents/COPIA-CNAS-Rocky-Relationship-Between-
Washington-And-Silicon-Valley.pdf?mtime=20170719145206.
123 Ibid., pp. 4-7.
124 Allen and Chan, p. 52.
125 Daisuke Wakabayashi and Scott Shane, “Google Will Not Renew Pentagon Contract That Upset Employees,” New
York Times, June 1, 2018, https://www.nytimes.com/2018/06/01/technology/google-pentagon-project-maven.html.
126 Nitasha Tiku, “Amazon’s Jeff Bezos Says Tech Companies Should Work with the Pentagon,” Wired, October 15,
2018, https://www.wired.com/story/amazons-jeff-bezos-says-tech-companies-should-work-with-the-pentagon/.
127 CRS discussion with Major Colin Carroll.
128 Patrick Tucker, “What the CIA’s Tech Director Wants from AI,” Defense One, September 6, 2017,
http://www.defenseone.com/technology/2017/09/cia-technology-director-artificial-intelligence/140801/.
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missions.129 Members of Congress may explore the complex interaction of these factors as DOD
moves beyond the initial stages of AI adoption.
International Competitors
As military applications for AI grow in scale and complexity, many in Congress and the defense
community are becoming increasingly concerned about international competition. In his opening
comments at “The Dawn of AI” hearing before the Senate Subcommittee on Space, Science, and
Competitiveness, Senator Ted Cruz stated, “Ceding leadership in developing artificial intelligence
to China, Russia, and other foreign governments will not only place the United States at a
technological disadvantage, but it could have grave implications for national security.”130
Since at least 2016, AI has been consistently identified as an “emerging and disruptive
technology” at the Senate Select Intelligence Committee’s annual hearing on the “Worldwide
Threat Assessment.”131 In his written testimony for the 2017 hearing, Director of National
Intelligence Daniel Coates asserted, “The implications of our adversaries’ abilities to use AI are
potentially profound and broad. They include an increased vulnerability to cyberattack, difficulty
in ascertaining attribution, facilitation of advances in foreign weapon and intelligence systems,
the risk of accidents and related liability issues, and unemployment.”132 Consequently, it may be
important for Congress to understand the state of rival AI development—particularly because
U.S. competitors may have fewer moral, legal, or ethical qualms about developing military AI
applications.133
China
China is by far the United States’ closest competitor in the international AI market.134 China’s
2017 “Next Generation AI Development Plan” describes AI as a “strategic technology” that has
become a “focus of international competition.”135 According to the document, China will seek to
develop a core AI industry worth over 150 billion RMB136—or approximately $21.7 billion—by
2020 and will “firmly seize the strategic initiative” and reach “world leading levels” of AI
investment by 2030.

129 CRS discussion with Paul Scharre, Center for a New American Security, September 28, 2017.
130 U.S. Congress, Senate Subcommittee on Space, Science, and Competitiveness, Committee on Commerce, Science,
and Transportation, Hearing on the Dawn of Artificial Intelligence, 114th Cong., 2nd sess., November 30, 2016
(Washington, DC: GPO, 2016) p. 2.
131 U.S. Congress, Senate Committee on Intelligence, Hearing on Current and Projected National Security Threats to
the United States, 114th Cong., 2nd sess., February 9, 2016 (Washington, DC: GPO, 2016), p. 4, and U.S. Congress,
Senate Committee on Intelligence, Statement for the Record, Worldwide Threat Assessment of the US Intelligence
Community, 115th Cong., 1st sess., May 11, 2017, p. 3, https://www.intelligence.senate.gov/sites/default/files/
documents/os-coats-051117.pdf.
132 Ibid.
133 See, for example, Kania, “Battlefield Singularity,” p. 6.
134 See, for example, Kai-Fu Lee, AI Superpowers: China, Silicon Valley, and the New World Order (Boston, MA:
Houghton Mifflin Co., 2018).
135 China State Council, “A Next Generation Artificial Intelligence Development Plan,” p. 2.
136 Ibid., pp. 2-6. It should be noted that this sum refers to the aspirational total value of China’s AI industry in 2020.
Credible information about Chinese funding levels for military-specific AI applications is not available in the open
source.
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Recent Chinese achievements in the field demonstrate China’s potential to realize its goals for AI
development. In 2015, China’s leading AI company, Baidu, created AI software capable of
surpassing human levels of language recognition, almost a year in advance of Microsoft, the
nearest U.S. competitor.137 In 2016 and 2017, Chinese teams won the top prize at the Large Scale
Visual Recognition Challenge, an international competition for computer vision systems.138 Many
of these systems are now being integrated into China’s domestic surveillance network and social
credit system, which aims to monitor and, based on social behavior, “grade” every Chinese
citizen by 2021.139
China is researching various types of air, land, sea, and undersea autonomous vehicles. In the
spring of 2017, a civilian Chinese university with ties to the military demonstrated an AI-enabled
swarm of 1,000 uninhabited aerial vehicles at an airshow. A media report released after the fact
showed a computer simulation of a similar swarm formation finding and destroying a missile
launcher.140 Open-source publications indicate that the Chinese are also developing a suite of AI
tools for cyber operations.141
Chinese development of military AI is influenced in large part by China’s observation of U.S.
plans for defense innovation and fears of a widening “generational gap” in comparison to the U.S.
military.142 Similar to U.S. military concepts, the Chinese aim to use AI for exploiting large troves
of intelligence, generating a common operating picture, and accelerating battlefield
decisionmaking.143 The close parallels between U.S. and Chinese AI development have some
DOD leaders concerned about the prospects for retaining conventional U.S. military superiority
as envisioned in current defense innovation guidance.144
Analysts do, however, point to a number of differences that may influence the success of military
AI adoption in China. Significantly, unlike the United States, China has not been involved in
active combat for several decades. While on the surface this may seem like a weakness, some
argue that it may be an advantage, enabling the Chinese to develop more innovative concepts of
operation. On the other hand, Chinese military culture, which is dominated by centralized
command authority and mistrust of subordinates, may prove resistant to the adoption of
autonomous systems or the integration of AI-generated decisionmaking tools.145
China’s management of its AI ecosystem stands in stark contrast to that of the United States.146 In
general, few boundaries exist between Chinese commercial companies, university research

137 Jessi Hempel, “Inside Baidu’s Bid to Lead the AI Revolution,” Wired, December 6, 2017, https://www.wired.com/
story/inside-baidu-artificial-intelligence/?mbid=nl_120917_daily_list1_p4.
138 Aaron Tilley, “China’s Rise in the Global AI Race Emerges as it Takes Over the Final ImageNet Competition,”
Forbes, July 31, 2017, https://www.forbes.com/sites/aarontilley/2017/07/31/china-ai-imagenet/#1c1419b9170a.
139 “Beijing to Judge Every Resident Based on Behavior by End of 2020,” Bloomberg, November 21, 2018,
https://www.bloomberg.com/news/articles/2018-11-21/beijing-to-judge-every-resident-based-on-behavior-by-end-of-
2020. It should be noted that Chinese technology companies such as ZTE Corp are working with other authoritarian
regimes to develop similar social-control systems. See, for example, Angus Berwick, “How ZTE helps Venezuela
create China-style social control,” Reuters, November 14, 2018, https://www.reuters.com/investigates/special-report/
venezuela-zte/.
140 Kania, “Battlefield Singularity,” p. 23.
141 Ibid., p. 27.
142 Ibid., pp. 12-14.
143 Ibid., p. 13.
144 CRS discussion with Dr. Richard Linderman.
145 Kania, “Battlefield Singularity,” p. 17.
146 Ibid., p. 6.
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laboratories, the military, and the central government. As a result, the Chinese government has a
direct means of guiding AI development priorities and accessing technology that was ostensibly
developed for civilian purposes. To further strengthen these ties, the Chinese government created
a Military-Civil Fusion Development Commission in 2017, which is intended to speed the
transfer of AI technology from commercial companies and research institutions to the military.147
In addition, the Chinese government is leveraging both lower barriers to data collection and lower
costs to data labeling to create the large databases on which AI systems train.148 According to one
estimate, China is on track to possess 30% of the world’s share of data by 2030.149
China’s centrally directed effort is fueling speculation in the U.S. AI market, where China is
investing in companies working on militarily relevant AI applications—potentially granting it
lawful access to U.S. technology and intellectual property.150 Figure 2 depicts Chinese venture
capital investment in U.S. AI companies between 2010 and 2017, totaling an estimated $1.3
billion. The CFIUS reforms introduced in FIRRMA are intended to provide increased oversight of
such investments to ensure that they do not threaten national security or grant U.S. competitors
undue access to critical technologies.151
Figure 2. Chinese Investment in U.S. AI Companies, 2010-2017

Source: Michael Brown and Pavneet Singh, China’s Technology Transfer Strategy: How Chinese Investments in
Emerging Technology Enable a Strategic Competitor to Access the Crown Jewels of U.S. Innovation, Defense
Innovation Unit Experimental, January 2018, p. 29,
https://admin.govexec.com/media/diux_chinatechnologytransferstudy_jan_2018_(1).pdf.

147 Yujia He, “How China is Preparing for an AI-Powered Future,” The Wilson Center, June 20, 2017,
https://www.scribd.com/document/352605730/How-China-is-Preparing-for-an-AI-Powered-Future#from_embed, and
Kania, “Battlefield Singularity,” p. 19.
148 Will Knight, “China’s AI Awakening,” MIT Technology Review, October 10, 2017,
https://www.technologyreview.com/s/609038/chinas-ai-awakening; and Li Yuan, “How Cheap Labor Drives China’s
A.I. Ambitions,” The New York Times, November 25, 2018, https://www.nytimes.com/2018/11/25/business/china-
artificial-intelligence-labeling.html.
149 Kania, “Battlefield Singularity,” p. 12.
150 Paul Mozur and John Markoff, “Is China Outsmarting America in AI?,” The New York Times, May 27, 2017,
https://www.nytimes.com/2017/05/27/technology/china-us-ai-artificial-intelligence.html.
151 “Reform and Rebuild: The Next Steps, National Defense Authorization Act FY-2019,” House Armed Services
Committee, July 25, 2018, p. 18, https://armedservices.house.gov/sites/republicans.armedservices.house.gov/files/
wysiwyg_uploaded/FY2019%20NDAA%20Conference%20Summary%20.pdf.
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Even with these reforms, however, China may likely gain access to U.S. commercial
developments in AI given its extensive history of industrial espionage and cyber theft. China has
reportedly stolen design plans in the past for a number of advanced military technologies and
continues to do so despite the 2015 U.S.-China Cyber Agreement, in which both sides agreed that
“neither country’s government will conduct or knowingly support cyber-enabled theft of
intellectual property.”152 Furthermore, as Assistant Attorney General John Demers has testified to
Congress, “from 2011-2018, more than 90 percent of the [Justice] Department’s cases alleging
economic espionage by or to benefit a state involve China, and more than two-thirds of the
Department’s theft of trade secrets cases have had a nexus to China.”153
While most analysts view China’s unified, whole-of-government effort to develop AI as having a
distinct advantage over the United States’ AI efforts, many contend that it does have
shortcomings. For example, some analysts characterize the Chinese government’s funding
management as inefficient. They point out that the system is often corrupt, with favored research
institutions receiving a disproportionate share of government funding, and that the government
has a potential to overinvest in projects that produce surpluses that exceed market demand.154
In addition, China faces challenges in recruiting and retaining AI engineers and researchers. Over
half of the data scientists in the United States have been working in the field for over 10 years,
while roughly the same proportion of data scientists in China have less than 5 years of
experience. Furthermore, fewer than 30 Chinese universities produce AI-focused experts and
research products.155 Although China surpassed the United States in the quantity of research
papers produced from 2011 to 2015, the quality of its published papers, as judged by peer
citations, ranked 34th globally.156 China is, however, making efforts to address these deficiencies,
with a particular focus on the development of military AI applications. Indeed, the Beijing
Institute of Technology—one of China’s premier institutes for weapons research—recently
established the first educational program in military AI in the world.157
Some experts believe that China’s intent to be the first to develop military AI applications may
result in comparatively less safe applications, as China will likely be more risk-acceptant
throughout the development process. These experts stated that it would be unethical for the U.S.
military to sacrifice safety standards for the sake of external time pressures, but that the United

152 “Fact Sheet: President Xi Jinping’s State Visit to the United States,” The White House, September 25, 2015,
https://obamawhitehouse.archives.gov/the-press-office/2015/09/25/fact-sheet-president-xi-jinpings-state-visit-united-
states.
153 Testimony of John C. Demers, Senate Committee on the Judiciary, Hearing on China’s Non-traditional Espionage
against the United States: The Threat and Potential Policy Responses, https://www.justice.gov/sites/default/files/
testimonies/witnesses/attachments/2018/12/18/12-05-2018_john_c._demers_testimony_re_china_non-
traditional_espionage_against_the_united_states_the_threat_and_potential_policy_responses.pdf.
154 He, p. 13.
155 Dominic Barton and Jonathan Woetzel, “Artificial Intelligence: Implications for China,” McKinsey Global Institute,
April 2017, p. 8, https://www.mckinsey.com/~/media/McKinsey/Global%20Themes/China/
Artificial%20intelligence%20Implications%20for%20China/MGI-Artificial-intelligence-implications-for-China.ashx.
156 Simon Baker, “Which Countries and Universities are Leading on AI Research?” Times Higher Education, World
University Rankings, May 22, 2017, https://www.timeshighereducation.com/data-bites/which-countries-and-
universities-are-leading-ai-research.
157 Stephen Chen, “China’s brightest children are being recruited to develop AI ‘killer bots,’” South China Morning
Post, November 8, 2018, https://www.scmp.com/news/china/science/article/2172141/chinas-brightest-children-are-
being-recruited-develop-ai-killer.
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States’ more conservative approach to AI development may result in more capable systems in the
long run.158
Russia
Like China, Russia is actively pursuing military AI applications. At present, Russian AI
development lags significantly behind that of the United States and China, with no Russian AI
startup ranking in the top 100.159 However, Russia is initiating plans to close the gap. As part of
this effort, Russia has released a national strategy for artificial intelligence, which outlines 5- and
10-year benchmarks for improving the country’s AI expertise, educational programs, datasets,
infrastructure, and legal regulatory system.160 Russia will also continue to pursue its 2008 defense
modernization agenda, with the aim of robotizing 30% of its military equipment by 2025.161
Russia is establishing a number of organizations devoted to the development of military AI. In
March 2018, the Russian government released a 10-point AI agenda, which calls for the
establishment of an AI and Big Data consortium, a Fund for Analytical Algorithms and Programs,
a state-backed AI training and education program, a dedicated AI lab, and a National Center for
Artificial Intelligence, among other initiatives.162 In addition, Russia recently created a defense
research organization, roughly equivalent to DARPA, dedicated to autonomy and robotics called
the Foundation for Advanced Studies, and initiated an annual conference on “Robotization of the
Armed Forces of the Russian Federation.”163 Some analysts have noted that this recent
proliferation of research institutions devoted to AI may, however, result in overlapping
responsibilities and bureaucratic inertia, hindering AI development rather than accelerating it.164
The Russian military has been researching a number of AI applications, with a heavy emphasis on
semiautonomous and autonomous vehicles. In an official statement on November 1, 2017, Viktor
Bondarev, chairman of the Federation Council’s Defense and Security Committee, stated that
“artificial intelligence will be able to replace a soldier on the battlefield and a pilot in an aircraft
cockpit” and later noted that “the day is nearing when vehicles will get artificial intelligence.”165
Bondarev made these remarks in close proximity to the successful test of Nerehta, an uninhabited
Russian ground vehicle that reportedly “outperformed existing [inhabited] combat vehicles.”
Russia plans to use Nerehta as a research and development platform for AI and may one day

158 Dr. Caitlin Surakitbanharn, Comments at AI and Global Security Summit, Washington, DC, November 1, 2017; and
CRS discussion with Dr. Jason Matheny.
159 AI 100: The Artificial Intelligence Startups Redefining Industries, CB Insights, March 3, 2020,
https://www.cbinsights.com/research/artificial-intelligence-top-startups/.
160 Office of the President of the Russian Federation, “Decree of the President of the Russian Federation on the
Development of Artificial Intelligence in the Russian Federation” (Center for Security and Emerging Technology,
Trans.), October 10, 2019, https://cset.georgetown.edu/wp-content/uploads/Decree-of-the-President-of-the-Russian-
Federation-on-the-Development-of-Artificial-Intelligence-in-the-Russian-Federation-.pdf.
161 Simonite, “For Superpowers, Artificial Intelligence Fuels New Global Arms Race.”
162 Samuel Bendett, “Here’s How the Russian Military Is Organizing to Develop AI,” Defense One, July 20, 2018,
https://www.defenseone.com/ideas/2018/07/russian-militarys-ai-development-roadmap/149900/.
163 Samuel Bendett, “Red Robots Rising: Behind the Rapid Development of Russian Unmanned Military Systems,” The
Strategy Bridge, December 12, 2017, https://thestrategybridge.org/the-bridge/2017/12/12/red-robots-rising-behind-the-
rapid-development-of-russian-unmanned-military-systems.
164 Ibid.
165 Samuel Bendett, “Should the US Army Fear Russia’s Killer Robots?,” The National Interest, November 8, 2017,
http://nationalinterest.org/blog/the-buzz/should-the-us-army-fear-russias-killer-robots-23098.
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deploy the system in combat, intelligence gathering, or logistics roles.166 Russia has also
reportedly built a combat module for uninhabited ground vehicles that is capable of autonomous
target identification—and, potentially, target engagement—and plans to develop a suite of AI-
enabled autonomous systems.167
In addition, the Russian military plans to incorporate AI into uninhabited aerial, naval, and
undersea vehicles and is currently developing swarming capabilities.168 It is also exploring
innovative uses of AI for remoting sensing and electronic warfare, including adaptive frequency
hopping, waveforms, and countermeasures.169 Finally, Russia has made extensive use of AI
technologies for domestic propaganda and surveillance, as well as for information operations
directed against the United States and U.S. allies, and can be expected to continue to do so in the
future.170
Despite its aspirations, analysts argue that it may be difficult for Russia to make significant
progress in AI development given fluctuations in Russian military spending. In 2017, Russian
military spending dropped by 20% in constant dollars, with subsequent cuts in 2018.171 Spending
then rose in 2019, but is expected to drop in constant dollars from 2020 through 2022.172 In
addition, many analysts note that Russian academics have produced few research papers on AI
and that the Russian technology industry has yet to produce AI applications that are on par with
those produced by the United States and China.173 Others analysts counter that such factors may
be irrelevant, arguing that while Russia has never been a leader in internet technology, it has still

166 Patrick Tucker, “Russia Says It Will Field a Robot Tank that Outperforms Humans,” Defense One, November 8,
2017, https://www.defenseone.com/technology/2017/11/russia-robot-tank-outperforms-humans/142376/; and Bendett,
“Red Robots Rising.”
167 Tristan Greene, “Russia is Developing AI Missiles to Dominate the New Arms Race,” The Next Web, July 27, 2017,
https://thenextweb.com/artificial-intelligence/2017/07/27/russia-is-developing-ai-missiles-to-dominate-the-new-arms-
race/; and Kyle Mizokami, “Kalashnikov Will Make an A.I.-Powered Killer Robot,” Popular Mechanics, July 19, 2017,
https://www.popularmechanics.com/military/weapons/news/a27393/kalashnikov-to-make-ai-directed-machine-guns/.
168 Bendett, “Red Robot Rising.”
169 Dougherty and Jay, “Russia Tries to Get Smart”; and Margarita Konaev and Samuel Bendett, “Russian AI-Enabled
Combat: Coming to a City Near You?” War on the Rocks, July 31, 2019, https://warontherocks.com/2019/07/russian-
ai-enabled-combat-coming-to-a-city-near-you/.
170 Alina Polyakova, “Weapons of the Weak: Russia and AI-driven Asymmetric Warfare,” Brookings Institution,
November 15, 2018, https://www.brookings.edu/research/weapons-of-the-weak-russia-and-ai-driven-asymmetric-
warfare/; and Chris Meserole and Alina Polyakova, “Disinformation Wars,” Foreign Policy, May 25, 2018,
https://foreignpolicy.com/2018/05/25/disinformation-wars/.
171 Some analysts have argued that Russia’s 2016 peak in military spending was the result of overdue payments to the
arms industry, and thus reflect an artificial inflation. However, Russian military spending in 2017 was also lower than
that in 2014 and 2015. See Siemon T. Wezeman, “Russia’s military spending: Frequently asked questions,” Stockholm
International Peace Research Institute, April 27, 2020, https://www.sipri.org/commentary/topical-
backgrounder/2020/russias-military-spending-frequently-asked-questions.
172 “Military expenditure by country, in constant (2018) US$ m., 1988-2019,” Stockholm International Peace Research
Institute,
https://www.sipri.org/sites/default/files/Data%20for%20all%20countries%20from%201988%E2%80%932019%20in%
20constant%20%282018%29%20USD.pdf; and Siemon T. Wezeman, “Russia’s military spending: Frequently asked
questions,” Stockholm International Peace Research Institute, April 27, 2020,
https://www.sipri.org/commentary/topical-backgrounder/2020/russias-military-spending-frequently-asked-questions.
173 Leon Bershidsky, “Take Elon Musk Seriously on the Russian AI Threat,” Bloomberg, September 5, 2017,
https://www.bloomberg.com/view/articles/2017-09-05/take-elon-musk-seriously-on-the-russian-ai-threat; and
Polyakova, “Weapons of the Weak.”
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managed to become a notably disruptive force in cyberspace.174 Russia may also be able to draw
upon its growing technological cooperation with China.175
International Institutions
A number of international institutions have examined issues surrounding AI, including the Group
of Seven (G7), the Asia-Pacific Economic Cooperation (APEC), and the Organisation for
Economic Co-operation and Development (OECD), which has developed principles for the
development of trustworthy AI.176 The U.N. CCW, however, has made the most concerted effort
to consider certain military applications of AI, with a particular focus on LAWS. In general, the
CCW is charged with “banning or restricting the use of specific types of weapons that are
considered to cause unnecessary or unjustifiable suffering to combatants or to affect civilian
populations” and has previously debated weapons such as mines, cluster munitions, and blinding
lasers.177 The CCW began discussions on LAWS in 2014 with informal annual “Meetings of
Experts.”178 In parallel, the International Committee of the Red Cross (ICRC) held similar
gatherings of interdisciplinary experts on LAWS that produced reports for the CCW on technical,
legal, moral, and humanitarian issues.179 During the CCW’s April 2016 meeting, state parties
agreed to establish a formal Group of Governmental Experts (GGE), with an official mandate to
“assess questions related to emerging technologies in the area of LAWS.”180 Although the GGE
has now convened five times, it has not produced an official definition of LAWS or issued official
guidance for their development or use. As a result, one observer cautioned that the international
community is in danger of “the pace of diplomacy falling behind the speed of technological
advancement.”181 The U.S. government, however, maintains that existing international
humanitarian law is sufficient to govern the development or use of LAWS.182

174 Allen, “Putin and Musk Are Right.”
175 See Samuel Bendett and Elsa Kania, A New Sino-Russian High-tech Partnership, Australian Strategic Policy
Institute, October 29, 2019, https://www.aspi.org.au/report/new-sino-russian-high-tech-partnership.
176 The United States is one of 42 countries to have adopted the OECD AI Principles. Organisation for Economic Co-
operation and Development, “OECD Principles on AI,” June 2019, https://www.oecd.org/going-digital/ai/principles/.
177 “The Convention on Certain Conventional Weapons,” https://www.unog.ch/80256EE600585943/(httpPages)/
4F0DEF093B4860B4C1257180004B1B30?OpenDocument.
178 “Background on Lethal Autonomous Weapons Systems in the CCW,” https://www.unog.ch/80256EE600585943/
(httpPages)/8FA3C2562A60FF81C1257CE600393DF6?OpenDocument.
179 See “Autonomous Weapons Systems: Technical, Military, Legal, and Humanitarian Aspects,” Expert Meeting,
International Committee of the Red Cross, March 28, 2014, https://www.icrc.org/en/download/file/1707/4221-002-
autonomous-weapons-systems-full-report.pdf, and “Autonomous Weapons Systems: Implications of Increasing
Autonomy in the Critical Functions of Weapons,” Expert Meeting, International Committee of the Red Cross, March
16, 2016, https://www.icrc.org/en/download/file/21606/ccw-autonomous-weapons-icrc-april-2016.pdf.
180 “Background on Lethal Autonomous Weapons Systems in the CCW,” https://www.unog.ch/80256EE600585943/
(httpPages)/8FA3C2562A60FF81C1257CE600393DF6?OpenDocument.
181 Paul Scharre, “We’re Losing Our Chance to Regulate Killer Robots,” Defense One, November 14, 2017,
http://www.defenseone.com/ideas/2017/11/were-losing-our-chance-regulate-killer-robots/142517/.
182 See U.S. Government, “Implementing International Humanitarian Law in the Use of Autonomy in Weapon
Systems,” March 28, 2019, https://www.unog.ch/80256EDD006B8954/
(httpAssets)/B2A09D0D6083CB7CC125841E0035529D/$file/CCW_GGE.1_2019_WP.5.pdf.
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AI Opportunities and Challenges
AI poses a number of unique opportunities and challenges within a national security context.
However, its ultimate impact will likely be determined by the extent to which developers, with
the assistance of policymakers, are able to maximize its strengths while identifying options to
limit its vulnerabilities.
Autonomy
Many autonomous systems incorporate AI in some form. Such systems were a central focus of the
Obama Administration’s “Third Offset Strategy,” a framework for preserving the U.S. military’s
technological edge against global competitors.183 Depending on the task, autonomous systems are
capable of augmenting or replacing humans, freeing them up for more complex and cognitively
demanding work. In general, experts assert that the military stands to gain significant benefits
from autonomous systems by replacing humans in tasks that are “dull, dangerous, or dirty.”184
Specific examples of autonomy in military systems include systems that conduct long-duration
intelligence collection and analysis, clean up environments contaminated by chemical weapons,
or sweep routes for improvised explosive devices.185 In these roles, autonomous systems may
reduce risk to warfighters and cut costs, providing a range of value to DOD missions, as
illustrated in Figure 3.186 Some analysts argue these advantages create a “tactical and strategic
necessity” as well as a “moral obligation” to develop autonomous systems.187

183 For more information on the Third Offset Strategy, see CRS In Focus IF10790, What Next for the Third Offset
Strategy?, by Lisa A. Aronsson.
184 Mick Ryan, “Integrating Humans and Machines,” The Strategy Bridge, January 2, 2018,
https://thestrategybridge.org/the-bridge/2018/1/2/integrating-humans-and-machines.
185 Defense Science Board, “Summer Study on Autonomy,” June 9, 2016, p. 12, https://www.acq.osd.mil/dsb/reports/
2010s/DSBSS15.pdf.
186 Office of Technical Intelligence, Office of the Assistant Secretary of Defense for Research and Engineering,
“Technical Assessment: Autonomy,” February 2015, p. 4, https://apps.dtic.mil/dtic/tr/fulltext/u2/a616999.pdf.
187 Mick Ryan, “Building a Future: Integrating Human-Machine Military Organization,” The Strategy Bridge,
December 11, 2017, https://thestrategybridge.org/the-bridge/2017/12/11/building-a-future-integrated-human-machine-
military-organization, and CRS discussion with Paul Scharre.
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Figure 3. Value of Autonomy to DOD Missions

Source: Defense Science Board, “Summer Study on Autonomy,” June 9, 2016, p. 12, https://www.acq.osd.mil/
dsb/reports/2010s/DSBSS15.pdf.
Speed and Endurance
AI introduces a unique means of operating in combat at the extremes of the time scale. It provides
systems with an ability to react at gigahertz speed, which in turn holds the potential to
dramatically accelerate the overall pace of combat.188 As discussed below, some analysts contend
that a drastic increase in the pace of combat could be destabilizing—particularly if it exceeds
human ability to understand and control events—and could increase a system’s destructive
potential in the event of a loss of system control.189 Despite this risk, some argue that speed will
confer a definitive warfighting advantage, in turn creating pressures for widespread adoption of
military AI applications.190 In addition, AI systems may provide benefits in long-duration tasks
that exceed human endurance. For example, AI systems may enable intelligence gathering across
large areas over long periods of time, as well as the ability to autonomously detect anomalies and
categorize behavior.191
Scaling
AI has the potential to provide a force-multiplying effect by enhancing human capabilities and
infusing less expensive military systems with increased capability. For example, although an
individual low-cost drone may be powerless against a high-tech system like the F-35 stealth
fighter, a swarm of such drones could potentially overwhelm high-tech systems, generating
significant cost-savings and potentially rendering some current platforms obsolete.192 AI systems

188 Allen and Chan, p. 24.
189 Paul Scharre, Autonomous Weapons and Operational Risk, Center for a New American Security, February 2016, p.
35.
190 “Highlighting Artificial Intelligence: An Interview with Paul Scharre,” Strategic Studies Quarterly, Vol. 11, Issue 4,
November 28, 2017, pp. 18-19.
191 Office of Technical Intelligence, “Technical Assessment: Autonomy,” p. 6.
192 Ryan, “Building a Future: Integrated Human-Machine Military Organization.”
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could also increase the productivity of individual servicemembers as the systems take over
routine tasks or enable tactics like swarming that require minimal human involvement.193
Finally, some analysts caution that the proliferation of AI systems may decouple military power
from population size and economic strength. This decoupling may enable smaller countries and
nonstate actors to have a disproportionately large impact on the battlefield if they are able to
capitalize on the scaling effects of AI.194
Information Superiority
AI may offer a means to cope with an exponential increase in the amount of data available for
analysis. According to one DOD source, the military operates over 11,000 drones, with each one
recording “more than three NFL seasons worth” of high-definition footage each day.195 However,
the department does not have sufficient people or an adequate system to comb through the data in
order to derive actionable intelligence analysis.
This issue will likely be exacerbated in the future as data continue to accumulate. According to
one study, in 2020, every human on the planet will generate 1.7 megabytes of information every
second, growing the global pool of data to almost 44.0 zettabytes, up from 4.4 zettabytes in
2015.196 AI-powered intelligence systems may provide the ability to integrate and sort through
large troves of data from different sources and geographic locations to identify patterns and
highlight useful information, significantly improving intelligence analysis.197 In addition, AI
algorithms may generate their own data to feed further analysis, accomplishing tasks like
converting unstructured information from polls, financial data, and election results into written
reports. AI tools of this type thus hold the potential to bestow a warfighting advantage by
improving the quality of information available to decisionmakers.198
Predictability
AI algorithms often produce unpredictable and unconventional results. In March 2016, the AI
company DeepMind created a game-playing algorithm called AlphaGo, which defeated a world-
champion Go player, Lee Sedol, four games to one. After the match, Sedol commented that
AlphaGo made surprising and innovative moves, and other expert Go players subsequently stated
that AlphaGo overturned accumulated wisdom on game play.199 AI’s capacity to produce

193 Ronald C. Arklin, “A Roboticist’s Perspective on Lethal Autonomous Weapons Systems,” Perspectives on Lethal
Autonomous Weapon Systems, United Nations Office for Disarmament Affairs, Occasional Papers, No. 30, November
2017, p. 36.
194 Allen and Chan, p. 23.
195 Jon Harper, “Artificial Intelligence to Sort through ISR Data Glut,” National Defense, January 16, 2018,
http://www.nationaldefensemagazine.org/articles/2018/1/16/artificial-intelligence-to—sort-through-isr-data-glut.
196 Bernard Marr, “Big Data: 20 Mind-Boggling Facts Everyone Must Read,” Forbes, September 30, 2015,
https://www.forbes.com/sites/bernardmarr/2015/09/30/big-data-20-mind-boggling-facts-everyone-must-read/
#539121d317b1. For reference 1 zettabyte = 1 trillion gigabytes. For a visualization of data usage, see “Data Never
Sleeps 8.0,” Domo, 2020, https://web-assets.domo.com/blog/wp-content/uploads/2020/08/20-data-never-sleeps-8-final-
01-Resize.jpg.
197 Allen and Chan, p. 27, and Ilachinski, p. 140.
198 Allen and Chan, p. 32.
199 Cade Metz, “In Two Moves, AlphaGo and Lee Sedol Redefined the Future,” Wired, March 16, 2016,
https://www.wired.com/2016/03/two-moves-alphago-lee-sedol-redefined-future/.
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similarly unconventional results in a military context may provide an advantage in combat,
particularly if those results surprise an adversary.
However, AI systems can fail in unexpected ways, with some analysts characterizing their
behavior as “brittle and inflexible.”200 Dr. Arati Prabhakar, the former DARPA Director,
commented, “When we look at what’s happening with AI, we see something that is very
powerful, but we also see a technology that is still quite fundamentally limited ... the problem is
that when it’s wrong, it’s wrong in ways that no human would ever be wrong.”201
AI-based image recognition algorithms surpassed human performance in 2010, most recently
achieving an error rate of 2.5% in contrast to the average human error rate of 5%; however, some
commonly cited experiments with these systems demonstrate their capacity for failure.202 As
illustrated in Figure 4, researchers combined a picture that an AI system correctly identified as a
panda with random distortion that the computer labeled “nematode.” The difference in the
combined image is imperceptible to human eyes, but resulted in the AI system labeling the image
as a gibbon with 99.3% confidence.
Figure 4. AI and Image Classifying Errors

Source: Andrew Ilachinski, AI, Robots, and Swarms: Issues Questions, and Recommended Studies, Center for Naval
Analyses, January 2017, p. 61.

200 Paul Scharre, “A Security Perspective: Security Concerns and Possible Arms Control Approaches,” Perspectives on
Lethal Autonomous Weapon Systems, United Nations Office for Disarmament Affairs, Occasional Papers, No. 30,
November 2017, p. 24.
201 Quoted in Mark Pomerlau, “DARPA Director Clear-Eyed and Cautious on AI,” Government Computer News, May
10, 2016, https://gcn.com/articles/2016/05/10/darpa-ai.aspx.
202 AI Index, “2017 Annual AI Index Report,” November 2017, p. 26, http://cdn.aiindex.org/2017-report.pdf.
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In another experiment, an AI system
described the picture in Figure 5 as “a young
Figure 5. AI and Context
boy is holding a baseball bat,” demonstrating
“A Young Boy is Holding a Baseball Bat”
the algorithm’s inability to understand
context. Some experts warn that AI may be
operating with different assumptions about
the environment than human operators, who
would have little awareness of when the
system is outside the boundaries of its
original design.203
Similarly, AI systems may be subject to
algorithmic bias as a result of their training
data. For example, researchers have
repeatedly discovered instances of racial bias

in AI facial recognition programs due to the
Source: John Launchbury, “A DARPA Perspective on
lack of diversity in the images on which the
Artificial Intelligence,” https://www.darpa.mil/
systems were trained, while some natural
attachments/AIFul .pdf, p. 23.
language processing programs have
developed gender bias.204 This could hold significant implications for AI applications in a military
context, particularly if such biases remain undetected and are incorporated into systems with
lethal effects.
“Domain adaptability,” or the ability of AI systems to adjust between two disparate environments,
may also present challenges for militaries. For example, one AI system developed to recognize
and understand online text was trained primarily on formal language documents like Wikipedia
articles. The system was later unable to interpret more informal language in Twitter posts.205
Domain adaptability failures could occur when systems developed in a civilian environment are
transferred to a combat environment.206
AI system failures may create a significant risk if the systems are deployed at scale. One analyst
noted that although humans are not immune from errors, their mistakes are typically made on an
individual basis, and they tend to be different every time. However, AI systems have the potential
to fail simultaneously and in the same way, potentially producing large-scale or destructive
effects.207 Other unanticipated results may arise when U.S. AI systems interact with adversary AI
systems trained on different data sets with different design parameters and cultural biases.208

203 Defense Science Board, “Summer Study on Autonomy,” p. 14.
204 Brian Barrett, “Lawmakers Can’t Ignore Facial Recognition’s Bias Anymore,” Wired, July 26, 2018,
https://www.wired.com/story/amazon-facial-recognition-congress-bias-law-enforcement/; and Will Knight, “How to
Fix Silicon Valley’s Sexist Algorithms,” MIT Technology Review, November 23, 2016,
https://www.technologyreview.com/s/602950/how-to-fix-silicon-valleys-sexist-algorithms/.
205 Aaron M. Bornstein, “Is Artificial Intelligence Permanently Inscrutable?,” Nautilus, September 1, 2016,
http://nautil.us/issue/40/learning/is-artificial-intelligence-permanently-inscrutable.
206 Paul Scharre, “The Lethal Autonomous Weapons Governmental Meeting, Part 1: Coping with Rapid Technological
Change,” Just Security, November 9, 2017, https://www.justsecurity.org/46889/lethal-autonomous-weapons-
governmental-meeting-part-i-coping-rapid-technological-change/.
207 Paul Scharre, Autonomous Weapons and Operational Risk, Center for a New American Security, February 2016, p.
23.
208 Kania, p. 44.
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Analysts warn that if militaries rush to field the technology prior to gaining a comprehensive
understanding of potential hazards, they may incur a “technical debt,” a term that refers to the
effect of fielding AI systems that have minimal risk individually but compounding collective risk
due to interactions between systems.209 This risk could be further exacerbated in the event of an
AI arms race.210
Explainability
Further complicating issues of predictability, the types of AI algorithms that have the highest
performance are currently unable to explain their processes. For example, Google created a cat-
identification system, which achieved impressive results in identifying cats on YouTube;
however, none of the system’s developers were able to determine which traits of a cat the system
was using in its identification process.211 This lack of so-called “explainability” is common across
all such AI algorithms. To address this issue, DARPA is conducting a five-year research effort to
produce explainable AI tools.212
Other research organizations are also attempting to do a backwards analysis of these types of
algorithms to gain a better understanding of their internal processes. In one such study,
researchers analyzed a program designed to identify curtains in images and discovered that the AI
algorithm first looked for a bed rather than a window, at which point it stopped searching the
image. Researchers later learned that this was because most of the images in the training data set
that featured curtains were bedrooms.213 The project demonstrated the possibility that training sets
could inadvertently introduce errors into a system that might not be immediately recognized or
understood by users.
Explainability can create additional issues in a military context, because the opacity of AI
reasoning may cause operators to have either too much or too little confidence in the system.
Some analysts are particularly concerned that humans may be averse to making a decision based
entirely on AI analysis if they do not understand how the machine derived the solution. Dawn
Meyerriecks, Deputy Director for Science and Technology at the CIA, expressed this concern,
arguing, “Until AI can show me its homework, it’s not a decision quality product.”214 Increasing
explainability will thus be key to humans building appropriate levels of trust in AI systems. As a
U.S Army study of this issue concludes, only “prudent trust” will confer a competitive advantage
for military organizations.215

209 The MITRE Corporation, “Perspectives on Research in Artificial Intelligence and Artificial General Intelligence
Relevant to DOD,” Office of the Assistant Secretary of Defense for Research and Engineering, January 2017, p. 32.
210 Dr. Dario Amodei, Comments at AI and Global Security Summit, Washington, DC, November 1, 2017.
211 John Markoff, “How Many Computers to Identify a Cat? 16,000.” The New York Times, June 25, 2012,
http://www.nytimes.com/2012/06/26/technology/in-a-big-network-of-computers-evidence-of-machine-learning.html.
212 David Gunning, “Explainable AI Program Description,” November 4, 2017, https://www.darpa.mil/attachments/
XAIIndustryDay_Final.pptx.
213 Bornstein, “Is Artificial Intelligence Permanently Inscrutable?”
214 Dawn Meyerriecks, Comments at the Machine Learning and Artificial Intelligence Workshop, National Geospatial
Intelligence Agency, November 13, 2017.
215 Eric Van Den Bosch, “Human Machine Decision Making and Trust,” in Closer than You Think: The Implications of
the Third Offset Strategy for the US Army (Carlisle, PA: US Army War College Press, 2017), p.111.
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Additional human-machine interaction issues that may be challenged by insufficient
explainability in a military context include the following:
 Goal Alignment. The human and the machine must have a common
understanding of the objective. As military systems encounter a dynamic
environment, the goals will change, and the human and the machine must adjust
simultaneously based on a shared picture of the current environment.216
 Task Alignment. Humans and machines must understand the boundaries of one
another’s decision space, especially as goals change. In this process, humans
must be consummately aware of the machine’s design limitations to guard
against inappropriate trust in the system.217
 Human Machine Interface. Due to the requirement for timely decisions in
many military AI applications, traditional machine interfaces may slow down
performance, but there must be a way for the human and machine to coordinate
in real time in order to build trust.218
Finally, explainability could challenge the military’s ability to “verify and validate” AI system
performance prior to fielding. Due to their current lack of an explainable output, AI systems do
not have an audit trail for the military test community to certify that a system is meeting
performance standards.219 DOD is currently developing a framework to test AI system lifecycles
and building methods for testing AI systems in diverse environments with complex human-
machine interactions.220 In addition, the National Security Commission on Artificial Intelligence
is to provide recommendations for operationalizing predictability and explainability in AI
systems. As the interim report notes, “recommendations might include identifying gaps in current
processes, providing guidance on needed policy and technical standards, and identifying areas
where future R&D and workforce training is necessary.”221

216 U.S. Air Force, Office of the Chief Scientist, “Autonomous Horizons, System Autonomy in the Air Force,” p. 17.
217 Ibid.
218 Ilachinski, p. 187.
219 DSB Study on Autonomy, pp. 14-15.
220 Ilachinski, p. 204.
221 National Security Commission on Artificial Intelligence, Interim Report, p. 48. Similarly, the Defense Innovation
Board has recommended that the use of DOD AI systems be responsible, equitable, traceable, reliable, and governable.
Defense Innovation Board, “AI Principles: Recommendations on the Ethical Use of Artificial Intelligence by the
Department of Defense,” p. 8.
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Exploitation
AI systems present unique pathways for
adversary exploitation. First, the proliferation
Figure 6. Adversarial Images
of AI systems will increase the number of
“hackable things,” including systems that
carry kinetic energy (e.g., moving vehicles),
which may in turn allow exploitive actions to
induce lethal effects. These effects could be
particularly harmful if an entire class of AI
systems all have the same exploitable
vulnerability.222
In addition, AI systems are particularly
vulnerable to theft by virtue of being almost
entirely software-based. As one analyst points

out, the Chinese may be able to steal the plans
for an F-35, but it will take them years to find
Source: Evan Ackerman, “Slight Street Sign
Modifications Can Completely Fool Machine Learning
the materials and develop the manufacturing
Algorithms,” IEEE Spectrum, August 4, 2017,
processes to build one. In contrast, stolen
https://spectrum.ieee.org/cars-that-think/
software code can be used immediately and
transportation/sensors/slight-street-sign-
reproduced at will.223 This risk is amplified by
modifications-can-fool-machine-learning-algorithms.
the dual-use nature of the technology and the fact that the AI research community has been
relatively open to collaboration up to this point. Indeed, numerous AI tools developed for civilian
use—but that could be adapted for use in weapon systems—have been shared widely on
unclassified internet sites, making them accessible to major military powers and nonstate actors
alike.224
Finally, adversaries may be capable of deliberately introducing the kinds of image classification
and other errors discussed in the “Predictability” section above. In one such case, researchers who
had access to the training data set and algorithm for an image classifier on a semiautonomous
vehicle used several pieces of strategically placed tape (as illustrated in Figure 6) to cause the
system to identify a stop sign as a speed limit sign. In a later research effort, a team at MIT
successfully tricked an image classifier into thinking that a picture of machine guns was a
helicopter—without access to the system’s training data or algorithm.225 These vulnerabilities
highlight the need for robust data security, cybersecurity, and testing and evaluation processes as
military AI applications are developed.

222 Allen and Chan, p. 23.
223 Ibid., p. 25.
224 Amy Nordrum, “Darpa Invites Techies to Turn Off-the-Shelf Products into Weapons in New ‘Improv’ Challenge,”
IEEE Spectrum, March 11, 2016, https://spectrum.ieee.org/tech-talk/aerospace/military/darpa-invites-techies-to-turn-
offtheshelf-products-into-weapons-in-new-improv-challenge.
225 Louise Matsakis, “Researchers Fooled a Google AI into Thinking a Rifle was a Helicopter,” Wired, December 20,
2017, https://www.wired.com/story/researcher-fooled-a-google-ai-into-thinking-a-rifle-was-a-helicopter/?mbid=
nl_122117_daily_list1_p2.
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AI’s Potential Impact on Combat
Although AI has not yet entered the combat arena in a serious way, experts are predicting the
potential impact that AI will have on the future of warfare. This influence will be a function of
many factors, including the rate of commercial investment, the drive to compete with
international rivals, the research community’s ability to advance the state of AI capability, the
military’s general attitude toward AI applications, and the development of AI-specific warfighting
concepts.226
Many experts assert that there is a “sense of inevitability” with AI, arguing that it is bound to be
substantially influential.227 Nevertheless, in January 2016, then-Vice Chairman of the Joint Chiefs
of Staff General Paul Selva, intimated that it may be too early to tell, pointing out that DOD is
still evaluating AI’s potential. He stated, “The question we’re trying to pose now is, ‘Do the
technologies that are being developed in the commercial sector principally provide the kind of
force multipliers that we got when we combined tactical nuclear weapons or precision and
stealth?’ If the answer is yes, then we can change the way that we fight.... If not, the military will
seek to improve its current capabilities slightly to gain an edge over its adversaries.”228 There are
a range of opinions on AI’s trajectory, and Congress may consider these future scenarios as it
seeks to influence and conduct oversight of military AI applications.
Minimal Impact on Combat
While many analysts admit that military AI technology is in a stage of infancy, it is difficult to
find an expert who believes that AI will be inconsequential in the long run.229 However, AI critics
point to a number of trends that may minimize the technology’s impact. From a technical
standpoint, there is a potential that the current safety problems with AI will be insurmountable
and will make AI unsuitable for military applications.230 In addition, there is a chance the
perceived current inflection point in AI development will instead lead to a plateau. Some experts
believe that the present family of algorithms will reach its full potential in another 10 years, and
AI development will not be able to proceed without significant leaps in enabling technologies,
such as chips with higher power efficiency or advances in quantum computing.231 The technology
has encountered similar roadblocks in the past, resulting in periods called “AI Winters,” during
which the progress of AI research slowed significantly.
As discussed earlier, the military’s willingness to fully embrace AI technology may pose another
constraint. Many academic studies on technological innovation argue that military organizations
are capable of innovation during wartime, but they characterize the services in peacetime as large,

226 “War at Hyperspeed, Getting to Grips with Military Robotics,” The Economist, January 25, 2018,
https://www.economist.com/news/special-report/21735478-autonomous-robots-and-swarms-will-change-nature-
warfare-getting-grips.
227 Allen and Chan, p. 50.
228 Andrew Clevenger, “The Terminator Conundrum: Pentagon Weighs Ethics of Paring Deadly Force, AI,” Defense
News, January 23, 2016, https://www.defensenews.com/2016/01/23/the-terminator-conundrum-pentagon-weighs-
ethics-of-pairing-deadly-force-ai/.
229 Brian Bergstein, “The Great AI Paradox,” MIT Technology Review, December 15, 2017,
https://www.technologyreview.com/s/609318/the-great-ai-paradox/.
230 “Highlighting Artificial Intelligence: An Interview with Paul Scharre,” p. 17.
231 CRS Discussions with Dr. Dai Kim.
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inflexible bureaucracies that are prone to stagnation unless there is a crisis that spurs action.232
Members of the Defense Innovation Board, composed of CEOs from leading U.S. commercial
companies, remarked in their most recent report, “DOD does not have an innovation problem, it
has an innovation adoption problem” with a “preference for small cosmetic steps over actual
change.”233
Another analysis asserts that AI adoption may be halted by poor expectation management. The
report asserts that overhyped AI capabilities may cause frustration that will “diminish people’s
trust and reduce their willingness to use the system in the future.”234 This effect could have a
significant chilling effect on AI adoption.
Evolutionary Impact on Combat
Most analysts believe that AI will at a minimum have significant impact on the conduct of
warfare. One study describes AI as a “potentially disruptive technology that may create sharp
discontinuities in the conduct of warfare,” further asserting that the technology may “produce
dramatic improvements in military effectiveness and combat potential.”235 These analysts point to
research projects to make existing weapon systems and processes faster and more efficient, as
well as providing a means to cope with the proliferation of data that complicate intelligence
assessments and decisionmaking. However, these analysts caution that in the near future AI is
unlikely to advance beyond narrow, task-specific applications that require human oversight.236
Some AI proponents contend that although humans will be present, their role will be less
significant, and the technology will make combat “less uncertain and more controllable,” as
machines are not subject to the emotions that cloud human judgment.237 However, critics point to
the enduring necessity for human presence on the battlefield in some capacity as the principle
restraining factor that will keep the technology from upending warfare. An academic study of this
trend argues
At present, even an AI of tremendous power will not be able to determine outcomes in a
complex social system, the outcomes are too complex – even without allowing for free will
by sentient agents.... Strategy that involves humans, no matter that they are assisted by
modular AI and fight using legions of autonomous robots, will retain its inevitable human
flavor.238

232 Gautam Mukunda, “We Cannot Go On: Disruptive Innovation and the First World War Royal Navy,” Security
Studies, Vol. 19, Issue 1, February, 23, 2010, p. 136. For more on this topic, see Barry R. Posen, The Sources of
Military Doctrine: France, Britain, and Germany Between the World Wars (Cornell: Cornell University Press, 1986),
and Stephen P. Rosen, Winning the Next War: Innovation and the Modern Military (Cornell: Cornell University Press,
1994).
233 Patrick Tucker, “Here’s How to Stop Squelching New Ideas, Eric Schmidt’s Advisory Board Tells DOD,” Defense
One, January 17, 2018, http://www.defenseone.com/technology/2018/01/heres-how-stop-squelching-new-ideas-eric-
schmidts-advisory-board-tells-DOD/145240/.
234 “Artificial Intelligence and Life in 2030,” One Hundred Year Study on AI, Report of the 2015 Study Panel, Stanford
University, September 2016, p. 42.
235 Robert O. Work and Shawn Brimley, 20YY Preparing for War in the Robotic Age, Center for a New American
Security, January 2014, p. 7.
236 Ibid., p. 25.
237 “War at Hyperspeed, Getting to Grips with Military Robotics.”
238 Kareem Ayoub and Kenneth Payne, “Strategy in the Age of Artificial Intelligence,” The Journal of Strategic
Studies, Vol. 39. No. 5, November 2015, p. 816.
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Pointing to another constraining factor, analysts warn of the psychological impact that
autonomous systems will have on an adversary, especially in conflict with cultures that place a
premium on courage and physical presence. One study on this topic quotes a security expert from
Qatar who stated, “How you conduct war is important. It gives you dignity or not.”239
In addition, experts highlight that the balance of international AI development will affect the
magnitude of AI’s influence. As one analyst states, “[T]he most cherished attribute of military
technology is asymmetry.”240 In other words, military organizations seek to develop technological
applications or warfighting concepts that confer an advantage for which their opponent possesses
no immediate countermeasure. Indeed, that is the U.S. military’s intent with the current wave of
technological development as it seeks “an enduring competitive edge that lasts a generation or
more.”241 For this reason, DOD is concerned that if the United States does not increase the pace
of AI development and adoption, it will end up with either a symmetrical capability or a
capability that bestows only a fleeting advantage, as U.S. competitors like China and Russia
accelerate their own respective military AI programs.242
The democratization of AI technology will further complicate the U.S. military’s pursuit of an AI
advantage. As the 2018 National Defense Strategy warns, “The fact that many technological
developments will come from the commercial sector means that state competitors and nonstate
actors will also have access to them, a fact that risks eroding the conventional overmatch to which
our Nation has grown accustomed.”243 In these circumstances, AI could still influence warfighting
methods, but the technology’s overall impact may be limited if adversaries possess comparable
capabilities.
Revolutionary Impact on Combat
A sizeable contingent of experts believe that AI will have a revolutionary impact on warfare. One
analysis asserts that AI will induce a “seismic shift on the field of battle” and “fundamentally
transform the way war is waged.”244 The 2018 National Defense Strategy counts AI among a
group of emerging technologies that will change the character of war, and Frank Hoffman, a
professor at the National Defense University, takes this a step further, arguing that AI may “alter
the immutable nature of war.”245
Statements like this imply that AI’s transformative potential is so great that it will challenge long-
standing, foundational warfighting principles. In addition, members of the Chinese military

239 Peter W. Singer, Wired for War, The Robotics Revolution and Conflict in the Twenty-First Century (New York:
Penguin Press, 2009), pp. 305-311.
240 Mark Grimsley, “Surviving the Military Revolution: The US Civil War,” in The Dynamics of Military Revolution,
1300-2050 (Cambridge: Cambridge University Press, 2001), p.74.
241 Christian Davenport, “Robots, Swarming Drones, and Iron Man: Welcome to the New Arms Race,” The
Washington Post, June 17, 2016, https://www.washingtonpost.com/news/checkpoint/wp/2016/06/17/robots-swarming-
drones-and-iron-man-welcome-to-the-new-arms-race/?hpid=hp_rhp-more-top-stories_no-
name%3Ahomepage%2Fstory&utm_term=.00284eba0a01.
242 Department of Defense, Joint Concept for Robotic and Autonomous Systems, p. 18, and Elsa Kania, “Strategic
Innovation and Great Power Competition,” The Strategy Bridge, January 31, 2018, https://thestrategybridge.org/the-
bridge/2018/1/31/strategic-innovation-and-great-power-competition.
243 Summary of the 2018 National Defense Strategy, p. 3.
244 John R. Allen and Amir Husain, “On Hyperwar,” Proceedings, July 2017, p. 30.
245 Summary of the 2018 National Defense Strategy, p. 3, and “War at Hyperspeed, Getting to Grips with Military
Robotics.”
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establishment assert that AI “will lead to a profound military revolution.”246 Proponents of this
position point to several common factors when making their case. They argue that the world has
passed from the Industrial Era of warfare into the Information Era, in which gathering, exploiting,
and disseminating information will be the most consequential aspect of combat operations.
In light of this transition, AI’s potential ability to facilitate information superiority and “purge
combat of uncertainty” will be a decisive wartime advantage, enabling faster and higher-quality
decisions.247 As one study of information era warfare states, “[W]inning in the decision space is
winning in the battlespace.”248 Members of this camp argue that AI and autonomous systems will
gradually distance humans from a direct combat role, and some even forecast a time in which
humans will make strategic-level decisions while AI systems exclusively plan and act at the
tactical level. In addition, analysts contend that AI may contest the current preference for quality
over quantity, challenging industrial era militaries built around a limited number of expensive
platforms with exquisite capabilities, instead creating a preference for large numbers of adequate,
less expensive systems.249
A range of potential consequences flow from the assumptions surrounding AI’s impact on
warfighting. Some studies point to overwhelmingly positive results, like “near instantaneous
responses” to adversary operations, “perfectly coordinated action,” and “domination at a time and
place of our choosing” that will “consistently overmatch the enemy’s capacity to respond.”250
However, AI may create an “environment where weapons are too fast, small, numerous, and
complex for humans to digest ... taking us to a place we may not want to go but are probably
unable to avoid.”251 In other words, AI systems could accelerate the pace of combat to a point in
which machine actions surpass the rate of human decisionmaking, potentially resulting in a loss
of human control in warfare.252
There is also a possibility that AI systems could induce a state of strategic instability. The speed
of AI systems may put the defender at an inherent disadvantage, creating an incentive to strike
first against an adversary with like capability. In addition, placing AI systems capable of
inherently unpredictable actions in close proximity to an adversary’s systems may result in
inadvertent escalation or miscalculation.253
Although these forecasts project dramatic change, analysts point out that correctly assessing
future impacts may be challenging. Historians of technology and warfare emphasize that previous
technological revolutions are apparent only in hindsight, and the true utility of a new application
like AI may not be apparent until it has been used in combat.254

246 Kania, “Battlefield Singularity,” p. 8.
247 Williamson Murray and MacGregor Knox, “The Future Behind Us,” in The Dynamics of Military Revolution, 1300-
2050 (Cambridge: Cambridge University Press, 2001), p. 178.
248 James W. Mancillas, “Integrating AI into Military Operations: A Boyd Cycle Framework,” in Closer than You
Think: The Implications of the Third Offset Strategy for the US Army (Carlisle, PA: US Army War College Press,
2017), p. 74.
249 Joint Chiefs of Staff, Joint Operating Environment 2035, The Joint Force in a Contested and Disordered World,
July 14, 2016, p. 18, http://www.jcs.mil/Portals/36/Documents/Doctrine/concepts/joe_2035_july16.pdf?ver=2017-12-
28-162059-917.
250 Allen and Husain, pp. 31-33.
251 Singer, p. 128.
252 Scharre, “A Security Perspective: Security Concerns and Possible Arms Control Approaches,” p. 26.
253 Jurgen Altmann and Frank Sauer, “Autonomous Weapons and Strategic Stability,” Survival, Vol. 59, No. 5, October
– November 2017, pp. 121-127.
254 Williamson Murray, p. 154 and p. 185.
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Nevertheless, given AI’s disruptive potential, for better or for worse, it may be incumbent on
military leaders and Congress to evaluate the implications of military AI developments and
exercise oversight of emerging AI trends. Congressional actions that affect AI funding,
acquisitions, norms and standards, and international competition have the potential to
significantly shape the trajectory of AI development and may be critical to ensuring that advanced
technologies are in place to support U.S. national security objectives and the continued efficacy
of the U.S. military.

Author Information

Kelley M. Sayler

Analyst in Advanced Technology and Global
Security

Acknowledgments
This report was originally written by Daniel S. Hoadley while he was a U.S. Air Force Fellow at the
Congressional Research Service. It has been updated by Kelley M. Sayler.

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