Harnessed Lightning

Harnessed Lightning
AUTHORS
Ryan Fedasiuk
Jennifer Melot
Ben MurphyHOW THE CHINESE MILITARY
IS ADOPTING ARTIFICIAL INTELLIGENCE
OCTOBER 2021
Center for Security and Emerging Technology2
Established in January 2019, the Center for Security and
Emerging Technology (CSET) at Georgetown’s Walsh
School of Foreign Service is a research organization fo -
cused on studying the security impacts of emerging tech -
nologies, supporting academic work in security and tech -
nology studies, and delivering nonpartisan analysis to the
policy community. CSET aims to prepare a generation of
policymakers, analysts, and diplomats to address the chal -
lenges and opportunities of emerging technologies. CSET
focuses on the effects of progress in artificial intelligence,
advanced computing, and biotechnology.
CSET.GEORGETOWN.EDU | CSET@GEORGETOWN.EDU
Harnessed LightningOCTOBER 2021
AUTHORS
Ryan Fedasiuk
Jennifer Melot
Ben MurphyHOW THE CHINESE MILITARY
IS ADOPTING ARTIFICIAL INTELLIGENCE
ACKNOWLEDGMENTS
This report would not have been possible without the input of Margarita Konaev
and Igor Mikolic-Torreira, who provided methodological advice and reviewed
multiple drafts; and Devon Colmer, who assisted with export control analysis.
The authors are especially grateful to Ritwik Gupta, Scott Harold, and Megan
Lamberth for their comprehensive reviews; and to Zachary Haver and Mark
Stokes for information about certain PLA units.
The authors would also like to thank Ashwin Acharya, Catherine Aiken, Rael
Baird, Jordan Brunner, Husanjot Chahal, Ben Chang, Dakota Cary, Shelton
Fitch, Andrew Imbrie, Adam Kline, Ngor Luong, Katerina Sedova, Helen Toner,
Matthew Mahoney, Maura McCarthy, Dewey Murdick, Lynne Weil, and Emily
Weinstein for their suggestions on style and content. For their guidance on using
the Elicit AI Assistant, they are grateful to Jungwon Byun and Ben Rachbach of
Ought. The authors alone bear responsibility for any errors.
AUTHORS
Ryan Fedasiuk is a research analyst at CSET, where Jennifer Melot is a senior
software engineer and Ben Murphy is the translation manager.
DISCLAIMER
The mention of any individual, company, organization, or other entity in this
report should not be construed to imply the violation of any law or international
agreement.
PRINT AND ELECTRONIC DISTRIBUTION RIGHTS
© 202 1 by the Center for Security and Emerging Technology. This work
is licensed under a Creative Commons Attribution-NonCommercial 4.0
International License.
To view a copy of this license, visit:
https://creativecommons.org/licenses/by-nc/4.0/ .
DOCUMENT IDENTIFIER
doi: 10.5 1 593/20200089
Cover image: VectorStock/HaseHoch2/IMAGE ID - 34453 1 35
Center for Security and Emerging TechnologyiEXECUTIVE SUMMARY
INTRODUCTION
1 | PREPARING FOR INTELLIGENTIZED WARFARE
2 | METHODOLOGY AND SCOPE
3 | AI PURCHASES BY APPLICATION
4 | SUPPLY AND DEMAND FOR INTELLIGENT EQUIPMENT IN THE PLA
5 | WHAT THE PLA’S BUYING HABITS SAY ABOUT ITS BATTLE PLANS
6 | FUNDAMENTAL TENSIONS IN CHINESE MILITARY MODERNIZATION
CONCLUSION
APPENDIX I: CLASSIFYING “INTELLIGENT” EQUIPMENT CONTRACTS
APPENDIX II: AI-RELATED PURCHASES BY SERVICE BRANCH
ENDNOTES Contents
III
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57
Center for Security and Emerging Technologyiv
Center for Security and Emerging Technologyiiirtificial intelligence (AI) is progressing at lightning speed. What
10 years ago would have been considered science fiction—
self-adapting computer algorithms with billions of parameters—
is now a central focus of military and intelligence services worldwide.1
Owing in part to AI’s fast-paced development, most analyses of its
military promise tend to focus more on states’ future aspirations than
present-day capabilities. This is particularly true for the Chinese People’s
Liberation Army (PLA), which has routinely made clear its desire to harness
AI for military advantage, and which prefers to keep a close hold over its
actual, technical capabilities.2 But as tensions mount between the United
States and China, and some experts warn of an impending crisis over Tai -
wan, it is crucial that U.S. policymakers and defense planners understand
the commercial off-the-shelf (COTS) AI technologies already available to
the Chinese military.3
This report offers a detailed look at the PLA’s adoption of AI by ana -
lyzing 343 AI-related equipment contracts, part of a broader sample of
more than 66,000 procurement records published by PLA units and state-
owned defense enterprises in 2020. The report identifies key AI defense
industry suppliers, highlights gaps in U.S. export control policies, and
contextualizes the PLA’s AI investments within China’s broader strategy to
compete with the United States. Key findings include:
1. Chinese military leaders are already procuring AI-related systems
and equipment to prepare for “intelligentized” warfare, but AI so
far represents a small fraction of overall purchasing activity.4 Executive Summary
A
Center for Security and Emerging Technologyiv• Approximately 1.9 percent of public PLA contracts awarded between
April 2020 and November 2020 are related to AI or autonomy.
• While we can only estimate a floor for Chinese military AI spending, it is
likely that the PLA spends more than $1.6 billion each year on AI-relat -
ed systems and equipment.
• The PLA seems most focused on procuring AI for intelligence analysis,
predictive maintenance, information warfare, and navigation and target
recognition in autonomous vehicles.
• Whereas some PLA officers have expressed serious reservations about
developing lethal autonomous weapons systems (LAWS), laboratories
affiliated with the Chinese military are actively pursuing AI-based target
recognition and fire control research, which may be used in LAWS.
2. Chinese leaders view AI as the key to transforming the PLA into a “world-
class,” globally competitive military force. PLA advances in AI and auton -
omy will create new vulnerabilities for the United States and allied forces
operating in the Indo-Pacific.
• The PLA hopes to use AI to generate asymmetric advantages vis-à-vis
the United States, which it regards as a “strong enemy” ( 强敌), but also
a role model for AI development.
• PLA units and military laboratories are focused on developing autono -
mous vehicles and surveillance systems in the undersea domain, where
the United States has traditionally had a significant advantage.
• The PLA is stepping up investment in information operations and adap -
tive radar systems to jam and blind U.S. sensor and information net -
works, which PLA leaders judge to be particularly vulnerable.
• To compensate for vulnerabilities in its own networks, the PLA may
adopt edge applications of AI (directly proximate to, or embedded
within a platform) that can operate semi- or fully autonomously.
3. China’s military-civil fusion ( 军民融合 ) development strategy is helping the
PLA acquire COTS technologies, both from private Chinese technology
companies and sources outside of China.
• Most of the PLA’s AI equipment suppliers are not state-owned defense
enterprises, but private Chinese tech companies founded after 2010.
Center for Security and Emerging Technologyv• Although most suppliers are not state-owned, many have benefited
from equipment, personnel, information, or capital provided directly or
indirectly by the state.
• Of the 273 PLA AI equipment suppliers identified in this study, just 8
percent are named in U.S. export control and sanctions regimes.
• Some Chinese suppliers make a business out of sourcing foreign data or
components and reselling them to sanctioned Chinese defense compa -
nies and PLA units.
• Lapses in due diligence and situational awareness may permit the
Chinese military and defense industry to access capital and technology
originating in the United States and partner nations, including advanced
computer chips.
Supported by a burgeoning AI defense industry, the Chinese military has made
extraordinary progress in procuring AI systems for combat and support functions.
Within the next five to 10 years, the PLA will likely continue investing in AI to dis -
rupt U.S. military information systems and erode the U.S. advantage in undersea
warfare.
Although PLA investment in the technology appears substantial—roughly
equivalent to that of the U.S. military—it remains to be seen how exactly AI might
alter the balance of military power in the Indo-Pacific. In addition to renewed
interest in counter-autonomy research, U.S. and allied efforts to regulate access to
semiconductor devices may hinder the utility and availability of AI systems for the
Chinese military.
Center for Security and Emerging Technology10
Center for Security and Emerging Technology1Introduction
n the early pages of Liu Cixin’s science fiction novel Ball Lightning ,
when asked what, exactly, goes on at System Review Department
No. 2, Dr. Lin Yun replies that she develops “new concept weap -
ons” ( 新概念武器 )—fantastical ideas with the potential to change war -
fare itself. As the mastermind behind the Chinese military’s eventually
catastrophic “lightning weapons” program, Lin is remembered for her
ends-justify-means personality and willingness to develop dangerous
weapons in the service of the state.5
Seventeen years after it was first published in Chinese, Liu’s novel has
been eclipsed by his more successful series, Remembrance of Earth’s Past .
A Hugo Award winner, he publicly decries any comparison between his
imagined universe and modern geopolitics.6 But there can be no denying
that Liu’s fictional depiction of a Chinese People’s Liberation Army bent
on mastering “lightning weapons” bears striking similarities to its quest for
artificial intelligence today. Chinese military leaders expect AI to funda -
mentally change warfare, and are leaning on the technology to transform
the PLA into a “world-class military” by 2050.7 AI’s revolutionary potential
and general-purpose application even led Andrew Ng, former chief scien -
tist at the Chinese internet company Baidu, to label it “the new electricity”
in 2017.8
Despite some anxiety within the PLA about developing intelligent or
automated weapons systems, concerns about technology misuse seem to
take a back seat to the needs of the state.9 The PLA’s rapid embrace of AI
raises questions about strategic stability and the future of warfare. While
analysts generally agree that AI forms the basis of the PLA’s modernization
strategy, questions linger about how far it may be willing to go in devel -I
Center for Security and Emerging Technology2oping lethal autonomous weapons systems (LAWS), and which of its new concept
weapons will eventually mature into programs of record.10
By examining 343 AI-related equipment contracts awarded by PLA units and
state-owned defense enterprises in 2020, this study offers a detailed view of how
the Chinese military is beginning to wield AI—and to what end. The report begins
by reviewing the budgetary constraints and modernization goals that have shaped
the PLA’s transition to “intelligentized” warfare, followed by a discussion of the
study’s methodology and limitations.
It then identifies seven primary application areas for which the Chinese military
is awarding AI-related equipment contracts: autonomous vehicles, intelligence
analysis, information warfare, logistics, training, command and control, and target
recognition. The bulk of the report discusses common trends and significant AI pur -
chases made within each of these fields.
A fourth section profiles 273 of the PLA’s known AI equipment suppliers, high -
lighting gaps in U.S. export control policy and prevailing technology transfer risks.
Finally, the report discusses how AI fits into the PLA’s broader concepts of oper -
ations, before concluding with a discussion of the policy tensions that will shape its
military competition with the United States.
Center for Security and Emerging Technology3Preparing for
Intelligentized
Warfare1
t $209 billion, China’s official 202 1 defense budget is second
only to that of the United States, and has grown more than 6
percent annually over the past decade.11 The largest portion of
PLA defense expenditure is not for personnel, training, or maintenance,
but equipment—which accounted for more than 41 percent of the PLA’s
budget in 2017 , the last year detailed data was made available.12 Equip -
ment was not always the dominant focus of Chinese military spending
(in the 1960s, it comprised just 20 percent of the annual defense bud -
get), but it has ascended slowly over the past six decades to become
the cornerstone of China’s military modernization.13 Moreover, the PLA’s
reported equipment spending is likely an understatement, as “the PRC’s
published military budget omits several major categories of expenditures
and its actual military-related spending is higher than what it states in its
official budget.”14
Different periods in recent Chinese history have necessitated that PLA
planners procure different kinds of equipment. These priorities are reflect -
ed in three interlinked and at times overlapping modernization phases—
mechanization ( 机械化 ), informatization ( 信息化 ), and intelligentization ( 智
能化—which are clarified in China’s periodic defense white papers:
• After being made a priority in the 1980s, mechanization sought
to equip PLA units with modern platforms, including electronic
warfare systems, as well as motorized, armored personnel carriers
and infantry fighting vehicles. Mechanization emphasized fixed
boundaries and armor operations, primarily for troops stationed
along China’s land borders, at the expense of naval and air oper -
ations.15 In 2020, the PLA announced it had “basically achieved”
mechanization.16 A
Center for Security and Emerging Technology4• Since the 1990s, the PLA’s dominant push has been informatization , in
which wars are won through information dominance, and the space and
cyber domains are the “commanding heights of strategic competition.”17
PLA operational concepts today emphasize the need to win “informatized
local wars” by using long-range, precision, smart, and unmanned weapons
and equipment.18 In 2020, the PLA announced its goal to become a “fully
mechanized and informatized” force by its centenary, the year 2027.19
• First mentioned in China’s 201 5 Defense White Paper, intelligentization
represents “a new round of military revolution” characterized by networked,
intelligent, and autonomous systems and equipment. It endeavors to build
on mechanized and informatized systems, creating “ubiquitous networks” in
which “‘human-on-human’ warfare will be replaced by ‘machine-on-human’
or ‘machine-on-machine warfare.’”21 In particular, AI forms the basis of the
PLA’s push toward intelligentization, and tops the list of emerging technologies
prioritized in recent Chinese strategy documents and development plans.22
Although these modernization goals represent “phases” of development,
there is significant overlap between them: “While some units of the PLA employ
data links, network-centric sensor-to-shooter system-of-systems, and field a variety
of UAVs, electronic warfare platforms, and advanced combat capabilities,” writes
Dean Cheng, “other units are still in the midst of simply shifting from towed artillery
to self-propelled guns, improving their main battle tanks and becoming fully mo -
torized.”23 Since 201 3, however, the PLA has placed significantly less emphasis on
mechanization and informatization, and is starting to phase in intelligentization as a
guiding concept, as evidenced in the 201 5 and 2019 defense white papers (Figure 1).24
Center for Security and Emerging Technology5At the same time, numerous reforms to China’s military and defense industry have
sought to streamline the PLA’s promotion of science and technology and acquisition
of intelligent equipment. Some of the most significant have included the creation of an
Equipment Development Department alongside an entirely new service branch, the
PLA Strategic Support Force (PLASSF).25 Renewed emphasis on military-civil fusion
(MCF; 军民融合 ), too, has expanded the PLA’s access to private-sector innovation
and enabled it to draw on the work of internet giants like Baidu, Alibaba, and Ten -
cent, and telecom giants like Huawei and ZTE.26 But even with reforms, contemporary
scholars have questioned whether China’s historically bloated and inefficient defense
industry can sufficiently adapt to the information age.27 FIGURE 1
Equipment Modernization Phases Mentioned in China’s Defense
White Papers
50
40
30
20
10
0
YEAR OF DEFENSE WHITE PAPER2000 2002NUMBER OF MENTION SFIGURE 1
Equipment Modernization Phases Mentioned in China ’s Defense White Papers
60
2004 2006 2008 2010 2012 2014 2016
Mechanizatio n صցԽ
 Informatization (৴ଉԽ) Intelligentization ஐೳԽ
Source: CSET keyword analysis of all nine Chinese defense white papers
published between 2000 and 2019.
Center for Security and Emerging Technology8
Center for Security and Emerging Technology7Methodology and
Scope2
rocurement information holds distinct advantages for those look -
ing to understand the Chinese military and its immediate capabil -
ities. First, defense contracts offer strong signals of both intent and
capability, as militaries willing to spend limited resources on commercial
off-the-shelf (COTS) solutions clearly deem them useful. Second, as it
does in the United States, the public procurement process shapes China’s
ability to acquire and harness AI for military advantage.28
To assess how China is adopting AI, this report analyzes a sample of
purchasing information published directly by the Chinese military in 2020.
In addition to capabilities identified in procurement contracts, the authors
draw on theoretical writings and research papers by PLA officers and de -
fense industry engineers to assess how the PLA may use the AI systems it is
purchasing, and how these systems fit into its concepts of operations.
CSET’s corpus of PLA procurement tenders spans 66,207 records pub -
lished between March 30 and December 1, 2020. These tender notices
run the gamut from technology requirements and requests for proposals
(RFPs) to announcements of equipment or software contracts that were
awarded to Chinese companies. Different types of procurement informa -
tion reflect different steps in the PLA’s technology acquisition process:
• Requirements, inquiries, and bid solicitations signal demand. They
reflect the PLA’s technological priorities and perceived gaps that
research institutions and service branches are trying to fill.29
• Contract awards signal supply and, ultimately, capability. They
represent weapon systems or components the PLA sought to ac -
quire and ostensibly received. In most cases, several companies
compete to win a contract through a competitive bidding pro -P
Center for Security and Emerging Technology8cess.30 More rarely, the PLA selects a single vendor as a contract recipient
without considering alternative suppliers (“sole source” procurement).
Of the 66,207 tenders in the CSET dataset, 2 1,086 announce contracts to
supply the PLA with equipment, including software and electronic components.31
Information about many of these purchases is limited. While 49,493 tenders in the
dataset are publicly available ( 公开), the rest are classified as confidential ( 秘密;
1 4,024 tenders) or secret ( 机密; 2,270 tenders).32
UNDERSTANDING PROCUREMENT IN THE PLA
This study primarily considers contract awards, but also makes use of RFPs and
bid solicitations filed by PLA service branches, scientific papers published by
research institutions, advertisements from Chinese defense companies, and theo -
retical articles published in outlets like People’s Liberation Army Daily (解放军报 ).
Of the 2 1,086 contract awards included in the CSET dataset, 1 8,354 are “public”
and include information such as the requesting unit, intended end user, project
budget, tendering agency, and contract winner. A full list of variables can be
found in Appendix I. Most of these contracts were not awarded by PLA units, but
by defense state-owned enterprises including the Aviation Industry Corporation
of China (AVIC), China Aerospace Science and Technology Corporation (CASC),
and hundreds of their subsidiaries.33 Just 3,726 of the 1 8,354 public equipment
contracts in the dataset were awarded by PLA service branches, while the remain -TABLE 1
Types of Procurement Information Published by the PLA,
April-November 2020
Source: CSET corpus of PLA procurement activity.TABLE 1
Types of Pr ocurement Information Published by the PLA, April-November 2020
Announcement Type Public (ޜᔰ) Conﬁdential (〈ᇶ) Secret (ᵪᇶ) Total
Award (Bid) 15,028 1,855 356 17,239
Award (Sole Source) 3,545 272 30 3,847
Bid Solicitation 7,508 2,767 416 10,691
Inquiry 12,268 659 4 12,931
Requirement 2,705 2,509 406 5,620
Modiﬁcation or Annulment 2,143 600 102 2,845
Other 6,716 5,362 956 13,034
Total 49,913 14,024 2,270 66,207
 ANNOUNCEMENT T YPE PUBLIC ( Ҹڐ)C ONFIDENTIAL ( ॢإ) SECRET (ᵪᇶ) TOTAL
Center for Security and Emerging Technology9 Center for Security and Emerging Technologying 1 4,628 contracts were awarded by defense SOEs; theater commands; and re -
search institutes and academic institutions under the control of the Central Military
Commission, including the Academy of Military Sciences and the National Uni -
versity of Defense Technology (NUDT).
The 1 8,354 public contracts in our dataset include all manner of supplies and
equipment ranging from toilet seats and ball bearings to completed, off-the-shelf
CH-4 Rainbow ( 彩虹) combat UAVs. We do not claim to have a complete history
of the PLA’s purchase records for this period of time. However, by examining trends
among a sample of public contracts awarded in 2020, this paper aims to illuminate
the specific types of AI-related equipment the PLA is purchasing, and to explore their
potential application.
IDENTIFYING AI AND “INTELLIGENT” EQUIPMENT PURCHASES
Several limitations constrain our assessment of the Chinese military’s AI-related
procurement activity. First, definitions of “AI” are not consistent even within the
U.S. defense enterprise. The U.S. Department of Defense’s (DOD) 2020 AI strat -
egy defines AI as “the ability of machines to perform tasks that normally require
human intelligence”—a description that includes “decades-old DoD AI” such as
autopilot and signal processing systems, but also modern deep learning tech -
niques.34 Second, Chinese defense engineers frequently conflate terminology
surrounding unmanned and autonomous systems, making it difficult to distinctly
analyze the latter. Finally, some project titles are ambiguous and difficult to cat -
egorize. The PLA’s contract notices offer very little information about each prod -
uct’s technical specifications or envisioned use, though manufacturers sometimes
advertise this information.35 This study therefore adopts a broad definition of AI,
including most contracts that describe “intelligent” systems and equipment.
Despite these constraints, we identify PLA procurement projects related to AI
and autonomy by using keyword searches and an AI assistant, “Elicit.”36 We first
searched for contracts with names that included any of 1 4 broad keywords: algo -
rithm ( 算法), automatic ( 自动), autonomous ( 自主), autonomy (自治 ), intelligent ( 智
能), human-machine ( 人机), unmanned ( 无人), prediction ( 预测), artificial intelligence
(人工智能 ), computer vision ( 计算机视觉 ), robot ( 机器人 ), intelligence ( 智慧), learning
(学习), and the English-language abbreviation “AI.” Of the 1 8,354 public equip -
ment contracts in the dataset, 523 contained one or more of these phrases.37
However, some of these keywords are excessively broad, and upon closer
examination, many of the projects that mention them are not strictly related to AI
development. For example, “learning” ( 学习) returned contracts related to machine
learning ( 机器学习 ), but also military education. “Automatic” ( 自动) and “robot” ( 机
器人) likewise returned contracts about automated manufacturing, machinery, tools,
and robotic projects that likely do not feature AI or autonomy. We therefore elimi -
Center for Security and Emerging Technology10nated 1 80 extraneous “intelligent” equipment contracts, for a total of 343 contracts
related to AI and autonomy. These AI-related contracts represent 1.9 percent of
PLA-wide public contract awards from April–November 2020. For a full explana -
tion of the coding and labeling process, see Appendix I.
PRICING CHINESE MILITARY AI DEVELOPMENT
Of the 343 AI contract notices in the dataset, 205 (60 percent) listed the mon -
etary value of the contract. Public AI contracts in the dataset were typically
awarded through a competitive bidding process, as opposed to sole-source
procurement. They ranged in value from $1,300 (RMB 9,000, for an intelligent
sound-and-light alarm detection system) to $3 million (RMB 2 1 million, for an
intelligent UAV data access and management platform), with the average con -
tract amounting to $240,000 (RMB 1.7 million). These contracts are noticeably
small, even when adjusted for purchasing power parity.38 It is likely that the PLA’s
equivalent of major defense acquisition programs are classified or otherwise not
captured in this dataset.39
Approximately 2 percent of all public equipment contracts in the dataset ap -
pear related to AI, broadly defined. The PLA’s five main service branches—as
opposed to theater commands, research institutes, or defense SOEs—award the
majority of public AI contracts. As in the United States, these service branches are
tasked with procuring equipment used in military operations. Among the PLA Air
Force, Ground Force, Navy, Rocket Force, and Strategic Support Force, approxi -
mately one in 20 public equipment contracts appear related to AI.
The PLA spends more than 41 percent (approximately $86 billion) of its official
$209 billion budget on equipment, and provides no additional information about
how that funding is distributed.40 If public contracts reflect how the PLA prioritizes
different emerging technologies, then it is likely the PLA spends more than $1.6
billion each year on AI-enabled systems.41 However, because it is still an emerging
technology, the PLA’s true spending on AI likely exceeds this number, as more fund -
ing is captured in research and development rather than off-the-shelf technology
procurement. Moreover, the most resource-intensive AI projects are likely classified.
For these reasons, we can only approximate a floor for Chinese military AI spend -
ing. Using a different methodology and set of source documents, past CSET analysis
estimated a ceiling for Chinese defense-related AI research at “no more than about
19 billion RMB ($2.7 billion)” in 201 8, “and possibly much less.”42 Our analysis
supports the conclusion that annual Chinese military spending on AI is in the low
billions of U.S. dollars.
Comparisons between Chinese and U.S. military spending are inherently
complicated, as both countries define AI differently, discuss intelligent and autono -
Center for Security and Emerging Technology11mous systems in different ways, publish different degrees of information about their
equipment spending, count that spending differently, and use currencies with differ -
ent degrees of purchasing power. However, if the PLA does spend between $1.6
billion and $2.7 billion on AI-related technologies each year, then its AI spending
is likely on par with that of the U.S. military. Various analyses of DOD budgets for
procurement and research indicate that it spent between $800 million and $1.3
billion on AI in 2020, with an additional $1.7 billion to $3.5 billion for unmanned
and autonomous systems.43
Center for Security and Emerging Technology12
Center for Security and Emerging Technology13rior analysis has highlighted the PLA’s plan to use AI in a variety
of military applications, including intelligent and autonomous
unmanned systems; intelligence analysis; simulation, war-gam -
ing, and training; information warfare; and decision support.44 Yet there
are many ways to taxonomize AI applications for military use. CSET’s
2020 study Chinese Perspectives on AI and Future Military Capabilities
identified 1 2 specific AI applications of interest to Chinese military and
defense industry researchers, including cybersecurity and intelligent
munitions.45 The DOD’s Communities of Interest on autonomy include four
AI application areas: machine perception, reasoning, and intelligence;
human-machine collaboration; scalable autonomous system teaming;
and test, evaluation, validation, and verification.46
This study builds on prior taxonomies of AI applications, consolidat -
ing some fields while adding others. After reviewing the 343 AI-related
contracts in our dataset, we arrived at seven discrete application areas for
which the PLA is adopting AI:
1. Intelligent and Autonomous Vehicles
2. Intelligence, Surveillance, and Reconnaissance (ISR)
3. Predictive Maintenance and Logistics
4. Information and Electronic Warfare
5. Simulation and Training
6. Command and Control (C2)
7. Automated Target RecognitionAI Purchases by
Application3
P
Center for Security and Emerging Technology14The resulting taxonomy is imprecise. Working with limited information, we
adopted an iterative labeling process to characterize each contract, which is
described in more detail in Appendix I. Contracts that did not clearly fit in any of
these seven categories were marked “Other.” Despite some labeling uncertainty,
this report finds that autonomous vehicles, ISR, predictive maintenance, and infor -
mation warfare are priorities within the PLA’s intelligentization strategy. To a lesser
extent, PLA units also appear interested in using AI for simulation, target recognition,
and command and control systems. Appendix II includes more detailed information
about how each of the PLA’s service branches are adopting AI, while the remainder
of this section discusses each application in detail.
FIGURE 2
Number of PLA AI Contracts by Application Area
Source: CSET corpus of PLA procurement activity (343 AI contracts).Automate d
Target Recognitio nCommand and Contro lSimulation and TrainingInformation and
Electronic WarfarePredictive Maintenance
 and Logistic s
0 20FIGURE 2
Number of PLA AI Contr acts by Application Area
Other
40 60 80 100 120 140ISRIntelligent an d
Autonomous Vehicles
Center for Security and Emerging Technology15INTELLIGENT AND AUTONOMOUS VEHICLES
Since it first unveiled the Wing Loong-1 combat UAV in 2009, the PLA has made
significant progress in developing intelligent and autonomous systems in the air
and maritime domains. Of the 343 AI equipment contracts considered in this
study, 35 percent (1 2 1) are related to intelligent or autonomous vehicles. Market
research firms estimate that military and security services today account for more
than 40 percent of the Chinese UAV market, and procurement records confirm
that several PLA units and defense SOEs purchase COTS autonomous vehicles
through a public purchasing platform called the Drone Network ( 无人机网 ).47
Most of the unmanned and autonomous vehicle contracts in our dataset are for
airborne systems. While it is difficult to distinguish between contracts for remotely pi -
loted or truly autonomous aircraft, some PLA units have funded research into auton -
omous flight, and others have purchased “intelligentized” microwave interference,
reconnaissance, and data processing modules, which may be attached to remotely
piloted or self-flying aircraft.48 Myriad Chinese suppliers advertise unmanned or
autonomous aerial vehicles for combat or surveillance, including private enterprises,
SOEs, and state-run research and design centers. Examples of such systems include
the ASN-301—a reverse-engineered copy of the IAI Harpy loitering munition49—
and the GJ-1 1 “Sharp Sword” combat UAV.50 The Chinese Academy of Sciences
(CAS) Shenyang Institute of Automation (SIA) is at the forefront of state-backed
autonomous vehicle research.51 In 2020, it was awarded contracts to supply a “3D
intelligent collision avoidance system” for CASC, and “intelligent self-flying machin -
ery” for the PLA Air Force (PLAAF).52
The Chinese defense industry is also developing coordinated swarms of fixed-
wing UAVs and rotorcraft.53 Whereas scholars in the late 2010s speculated about
hypothetical swarm applications, the technology has progressed significantly, and
some limited swarm applications now appear operational.54 In 2020, multiple PLA
units and CASC institutes awarded contracts for air-launched drone clusters and
subsystems used in swarms, including self-organizing UAV communications systems,
group node management and control software, AI-based radar coincidence im -
aging, and collision avoidance sensors.55 In October 2020, the PLA Ground Force
(PLAGF) placed a $900,000 order to construct “drone swarm targets.”56 It is not
clear from the contract what such a swarm engagement would look like in practice.
The Drone Network also advertises COTS software and hardware for use in UAV
group operations, such as “SwarmLink”—a network gateway that can support more
than three hundred vehicles.57 Beyond COTS systems, several Chinese universities
have conducted swarm-related research, including Beihang University, Nanjing
University of Aeronautics and Astronautics, and Zhejiang University’s Institute of
Center for Security and Emerging Technology16UAV Systems and Control.58 Notably, multiple lines of research focus on contesting
and jamming U.S. military swarm projects such as LOCUST and Gremlins.59
Although most information about such systems is likely to be classified, some
public procurement records also indicate that the PLA is purchasing unmanned and
autonomous underwater vehicles (UUVs and AUVs). Five contracts in our dataset
were for AUV platforms, and another contract was for an intelligent ship integration
system.60 In the summer of 2020, for example, the PLASSF placed orders for AUVs
from Tianhe Defense, a company which seems to be emerging as China’s national
champion in A/UUVs.61 Tianhe advertises a “shadowless AUV solution,” which
it claims is capable of autonomously diving below 200 meters.62 In addition to
contract awards, advertisements from Chinese industry suppliers indicate that they
are developing small- and medium-sized, fully autonomous underwater vehicles—
possibly for sale abroad. Today, none of the top 10 companies selling AUVs in the
international market are Chinese.63 Yet several COTS AUV models are advertised
on the Drone Network, and some PLA units may purchase them for undersea detec -
tion and reconnaissance. Examples include the ZF-01 AUV, which can apparently
dive to 100 meters with a towed sonar array64; and Kawasaki’s SPICE AUV, which
comes equipped with a robotic arm for underwater fiber-optic cable and pipeline
inspection.65
FIGURE 3
AUV Likely Ordered by the Strategic Support Force in 2020
Source: Phoenix New Media and Tianhe Defense.66
Center for Security and Emerging Technology17Finally, at least four public contracts in our dataset were related to developing
“intelligent satellites” that can autonomously adjust their orbit or engage in ren -
dezvous and proximity operations with other space assets. For example, in August
2020, the PLA Academy of Military Sciences awarded an “intelligent satellite sim -
ulation software” contract to Hunan Gaozhi Technology Co., Ltd. ( 湖南高至科技有
限公司 ).67 The company sells high-resolution cameras and intelligent video analysis
servers, and holds several patents related to intelligent or automatic servo control in
satellite systems.68 In August 2020, the CASC Shanghai Academy of Space Tech -
nology likewise awarded a contract for an “on-orbit satellite data acquisition and
prediction subsystem”; while other CASC institutes awarded contracts for intelligent
or automatic inclination adjustment, high-precision attitude determination, and small
satellite positioning systems.69
Although nearly all of the vehicle contracts reviewed in this study are described
as “intelligent” (智能 ), the true nature of this intelligence—and the machine learning
methods that may or may not be involved in their operation—is unclear. The PLA has
long procured unmanned, remotely-piloted vehicles for reconnaissance and strike
missions. But in the 2020s, Chinese leaders hope that improvements in autonomous
navigation and online, real-time learning will cement unmanned vehicles as the
backbone of intelligentized, machine-on-machine warfare.70
INTELLIGENCE, SURVEILLANCE, AND RECONNAISSANCE
AI promises to revolutionize military ISR, perhaps more than any other applica -
tion area. That potential is reflected in the PLA’s procurement activity, as nearly
one in five AI contracts canvassed in this study (63) appear related to ISR. U.S.
military and intelligence services recognize the importance of using AI in foreign
media and geospatial imagery analysis, and PLA units are adopting AI toward
similar ends. According to Liu Linshan, a researcher at the PLA Academy of Mili -
tary Sciences, “battlefield situational awareness . . . includes not only the results
of one’s own reconnaissance, surveillance, and intelligence activities, but also
massive amounts of geographic information data, human social and cultural data,
and social media data” that can be fused to improve situational awareness at all
levels of operation.71
A significant number of the PLA’s AI-based ISR contracts concern remote sens -
ing and geospatial imagery analysis, consistent with U.S. intelligence community
assessments of China’s space strategy.72 Throughout 2020, CASC institutes and
PLASSF units placed orders for polarized surface detection, imagery analysis,
distance measurement, and multisource data fusion systems to be embedded in
satellites.73 In August, for example, the PLASSF awarded a “geospatial information
perception and intelligent analysis subsystem” contract to Beijing Uxsino Software
Center for Security and Emerging Technology18Co., Ltd. (“Uxsino,” 北京优炫软件股份有限公司 ).74 The company produces data
processing systems analogous to those made by Oracle in the United States.75
CASC institutes are also developing microsatellites with edge AI information pro -
cessing applications. One CASC subsidiary, Shenzhen Aerospace Dongfanghong
HIT Satellite Ltd. ( 深圳航天东方红海特卫星有限公司 ), advertises a constellation of 80
“intelligent autonomous operation and management” MV-1 microsatellites capable
of “full color, multi-spectral, and hyperspectral imaging” at resolutions of 1 to 5
meters.76
In the maritime domain, the PLA is interested in using AI for underwater in -
spection and deep-sea sensing. State-run research institutes in this study awarded
contracts for intelligent pipeline detection and identification, multisource informa -
tion processing and scene analysis, and automated coordinate measuring units
for underwater vehicles. In July 2020, the PLA Navy (PLAN) awarded an ocean
mapping contract to Startest Marine ( 星天海洋 ), which offers several products
related to undersea surveying and mapping.77 One of its products, GeoSide1 400,
is a side-scanning UUV that “uses the backscattered echoes of seabed targets for
detection.”78 A video on Startest Marine’s website depicts GeoSide1 400 being
towed by a fishing boat and patrolling the subsurface coastline, an application that
could be used to detect U.S. undersea forces in a crisis.79 The company also adver -
tises services for undersea mapping and hydrological data collection depicted in
Figure 4.80
FIGURE 4
Undersea Sensor Systems Offered by a PLA Contractor
Source: Startest Marine.81
Center for Security and Emerging Technology19Finally, the PLA is using AI in multisource data fusion for foreign military analysis,
including textual analysis of foreign-language documents.82 In the fall of 2020, the
PLAGF awarded two contracts for “foreign military equipment intelligent document
data resources”; and in November, an unspecified PLASSF unit ordered a “mul -
tilingual intelligent text processing system” from Nanjing Glaucus-Tech Co., Ltd.
(Glaucus-Tech; 南京国业科技有限公司 ). On its website, Glaucus-Tech advertises the
“GL-AI Speech Recognition System 001,” which can apparently translate foreign
languages into Chinese with 80 percent accuracy, at a rate of 20 words every 1 50
milliseconds.83 The company’s products rely on NVIDIA processors as components,
including the Tesla P40 GPU.84
On balance, Chinese military AI contracts for ISR applications exhibit priorities
similar to those stated by the U.S. intelligence community, such as network manage -
ment, image classification, and transcription of foreign languages.85 However, in
part because of its lack of operational experience, the PLA has struggled to access
certain types of data required for some weapons systems, such as radar signa -
ture-based target recognition.86
PREDICTIVE MAINTENANCE AND LOGISTICS
As in the United States, the Chinese military is using AI for equipment maintenance
and logistics. Of the 343 AI contracts in our dataset, 1 1 percent (38) were related
to maintenance, repair, logistics, or sustainment. Newly established PLA contrac -
tors have developed AI-based applications for leak detection, fault diagnosis,
and “smart warehouses” intended to predict and fill orders for materiel.87 In
March 2020, for example, the Academy of Military Sciences awarded Anwise
Global Technology ( 安怀信科技 ) a contract for an automated code testing plat -
form.88 Established in 2016, Anwise is one of China’s largest intelligent equipment
manufacturers, and primarily services the military aerospace and electronics in -
dustries.89 Its products include AI-based software for soldering fault diagnosis and
a virtual prototype library for testing and evaluation of aerospace weaponry.90
In November 2020, the PLAGF and PLASSF awarded predictive maintenance
contracts to Wego ( 威高), which produces medical devices and fault diagnosis
equipment; and Sucheon Technologies ( 硕橙科技 ), which focuses on using AI in
mechanical noise recognition.91
Center for Security and Emerging Technology20Predictive maintenance is also emerging as an edge application for otherwise
inaccessible, remotely piloted, or autonomous platforms. In 2020, multiple PLA
research institutes fielded orders for automatic test equipment on satellites and un -
derwater vehicles that cannot easily be reached for diagnostic testing and repair.93
CASC, for example, awarded two $800,000 contracts for ATE systems on unspec -
ified constellations of Earth observation satellites in geosynchronous and low earth
orbit.
PLA officers predict drastic decreases in equipment and materials stockpile
requirements as a result of intelligentized maintenance and logistics systems. “With
the development of information technology such as big data and cloud comput -
ing,” write two PLA logistics officers, “it is not necessary to establish a large-scale
resource reserve . . . all materials need only be supplied to the required place at
the required time.”94 Consistent with this thinking, CASC and the PLA Ground Force
placed orders for intelligent procurement systems for bullets and Internet of Things
(IoT) devices throughout 2020.95
INFORMATION OPERATIONS AND ELECTRONIC WARFARE
The U.S. military considers electronic warfare to be a component of informa -
tion operations, and designates information, data, knowledge, and influence as
“information-related capabilities.”96 Approximately 8 percent of public PLA AI
contracts in this study (29) are related to IO, broadly defined. However, AI stands
to affect each of these capabilities in different ways. Some AI projects support the
PLA’s public opinion warfare ( 舆论战 ) and psychological warfare ( 心理战 ) strat -FIGURE 5
Intelligent Maintenance Systems Offered by a PLA Contractor
Source: Anwise Global Technology Co., Ltd.92

Center for Security and Emerging Technology21egies, whereas others focus on electromagnetic spectrum dominance or defense
and intrusion in cyberspace.97
Public opinion manipulation is a longstanding focus of the PLA and the Chinese
Communist Party (CCP) more broadly.98 CSET’s report Truth, Lies, and Automa -
tion found that, with breakthroughs in AI, “humans now have able help in mixing
truth and lies in the service of disinformation.”99 Procurement records and research
papers indicate that the Chinese military is actively exploring this capability.100 In
November 2020, for example, the PLASSF’s Information Engineering University
awarded a contract for an “internet public opinion AI clustering system” to Zheng -
zhou Meicheng Electronic Technology Co. ( 郑州美诚电子科技有限公司 ), an elec -
tronics wholesaler. It showcases three products related to “online behavior manage -
ment” that range in price from $6,000 to $56,000.101 Each is a computer processor
produced by Ruijie Networks ( 锐捷网络 ), advertised as being able to “intelligently”
track source and destination IP addresses, website URL visits, and search history;
and perform “real-name online behavior auditing.”102 AI-based sentiment analysis
software is also common among PLA units and defense SOEs. KnowleSys ( 乐思网
络), one of China’s largest public opinion management software companies, claims
Dalian Naval Academy as a customer.103 Its products can apparently analyze
trends and predict “hotspots” on both Chinese and foreign social media platforms.
AI-enabled sentiment analysis systems like these will grow in importance as the CCP
continues to expand its overseas information operations.104 “In the era of artificial
intelligence,” writes a professor at NUDT, “audience information can be intelligently
collected and analyzed by machines, various data about public opinion warfare
opponents can also be obtained through network detection and deep data analy -
sis; and public opinion warfare happens in real-time.”105
In addition to psychological operations and social media manipulation, the PLA
is purchasing AI-related systems for use in electronic warfare. The PLA Navy Sub -
marine Academy, for example, has awarded several contracts related to adaptive
beamforming techniques, using AI to produce a dynamic filter that will cancel the
effect of interfering signals.106 Other PLA units awarded contracts for automatic
frequency modulation, microwave jamming, broadband automatic gain control,
and multisource signal separation.107 Chinese experts broadly believe AI will rev -
olutionize electronic warfare by replacing today’s passive, adaptive technology
with systems defined by more active, cognitive algorithm development.108 Research
papers published in 2020 by PLASSF Units 91 404, 63610, and 93 175109 discuss
using adaptive, self-correcting systems to conduct operations related to “battlefield
situational awareness, electromagnetic target reconnaissance, electronic counter -
measures, electronic defense, and electromagnetic spectrum management.”11 0
Center for Security and Emerging Technology22Cybersecurity and network exploitation are also focal points in the PLA’s adop -
tion of AI, and are key elements of information warfare. Prior CSET research has
found that “machine learning has the potential to increase both the scale and suc -
cess rate of spearphishing and social engineering attacks,”111 and several Chinese
universities are cooperating with the PLA to advance related research.112 Throughout
2020, PLA units and state-owned research institutes in our dataset awarded con -
tracts for intelligent terminal inspection systems; autonomous, self-configuring soft -
ware; and software control management systems.113 In November, for example, the
PLASSF awarded a contract for an AI-based “cyber threat intelligent sensing and
early warning platform” to EverSec ( 恒安嘉新（北京）科技股份公司 ). The company
serves as a national-level “Cybersecurity Emergency Service Support Unit” ( 网络
安全应急服务支撑单位 ) for the Chinese government’s National Computer Network
Emergency Response Technical Team/Coordination Center.114 In this capacity,
EverSec’s role seems analogous to that of FireEye or CrowdStrike’s support for the
Cybersecurity and Infrastructure Security Agency in the United States.115 Beyond its
adaptive cybersecurity products, the company also advertises services for peta -
byte-scale data storage and processing, AI-based open source data mining, and
internet blocking and censorship protocols.11 6 EverSec claims that its products are
used in all 3 1 Chinese provinces, autonomous regions, and provincial-level mu -
nicipalities, and evidently PLASSF units also purchase some of these services.117 The
U.S.-based venture capital firm Sequoia Capital is an investor in EverSec.118
SIMULATION AND TRAINING
The PLA has long had a problem with training its enlisted service members and
officers. A lack of suitable aircraft, friction when conducting joint operations, rigid
organizational culture, and seasonal tides in recruitment each affect its force pos -
ture and readiness.119 While improvements in technology can remedy only some of
these issues, AI nonetheless stands to save precious time and training costs. Of the
343 PLA contracts considered in this study, 6 percent (22) concerned using AI for
simulation and training.
Among the PLA officer corps, war-gaming is a well-established tradition, and
is growing in importance given China’s relative lack of real-world combat experi -
ence. It is no surprise that the PLA has awarded contracts for proprietary, AI-based
war-gaming software for use in professional military education programs. DataExa
(渊亭科技 ), for example, advertises an AI-based war-gaming simulator called
“AlphaWar,” inspired by DeepMind’s Starcraft-playing AI system, AlphaStar.12 0 The
PLA’s preoccupation with war-gaming grew out of the Information Operations and
Command Training Department of NUDT, which created “computer-based, war-
zone level, intranet-based campaign exercises” throughout the 2000s.121 According
Center for Security and Emerging Technology23to Chen Hangui, a researcher at the PLA Army Command College, one of the prin -
cipal uses of AI will be in “war-game systems” to “more effectively test and optimize
combat plans.”122
FIGURE 6
“War Game in Taiwan Strait 2019” Using CMO
Source: Chinese Institute of Command and Control.123 CICC generated this simulation by using
“Command: Modern Operations (CMO),” an $80 computer game available on Steam.
PLA units are also using AI in virtual and augmented reality systems to train fighter
pilots and drone operators. In August 2020, for example, Naval Aviation University
awarded a contract to eDong AI ( 翼动智能 ) for a “human-machine integrated control
algorithm model and simulation service.”124 The company primarily designs and builds
VR/AR simulation centers, and also advertises stand-alone training software.125 A simi -
lar contract was awarded to AOSSCI ( 傲势科技 ), which produces an “X-Matrix” UAV
flight simulator for PLA pilots.126 In June 202 1, Chinese media reported that an AI system
had defeated a top PLA pilot in a simulated dogfight similar to the Defense Advanced
Research Projects Agency’s Air Combat Evolution program.127 Public contract awards
indicate that AI-based simulation systems are becoming more common within the PLA.
While AI for simulation and training promises to save military services time and re -
sources, deep learning systems rely heavily on data, are incapable of learning common
Center for Security and Emerging Technology24sense, and lack interpretability—limitations acknowledged by Chinese defense
contractors.128 Still, even with these limitations, it is likely that advances in AI will
continue to supplement or stand in for the PLA’s often cited experience gap.
COMMAND AND CONTROL
Chinese military scholars and strategists expect the speed, efficiency, and flex -
ibility afforded by AI to revolutionize battlefield decision-making.129 Despite the
PLA’s emphasis on C2, however, public procurement data does not indicate that
it is a priority: Just 4 percent (1 5) of the contracts in our dataset appear related
to C2, and most included only limited information alongside nebulous names
such as “intelligent control equipment,” “smart management systems,” and “au -
tonomous mission planning.” The few projects for which we could find adequate
details seem primarily designed to support human decision-making processes, not
replace them outright.
It is likely that the PLA’s most significant AI-enabled C2 projects are classi -
fied, and therefore not included in our dataset. In the following paragraphs, we
supplement analysis of public procurement records with outside information,
such as defense industry advertisements, to better understand the scope of
China’s AI-enabled C2 capabilities. Several Chinese enterprises outside of our
dataset advertise AI systems capable of automating some elements of com -
mand and control—including knowledge mapping, decision support, weapon
target assignment, and combat tasking. While we could not use procurement
records to confirm that PLA units have purchased each of the systems specified
below, each of the following companies publicly claims the Chinese military as a
partner or client.
Knowledge mapping is a visual representation of information designed to aid
decision-making. DataExa, for example, advertises several services for AI-based
knowledge mapping and combat decision support, such as encyclopedic informa -
tion and real-time prediction about the movement of foreign weapons platforms.13 0
In July 2020, the company’s knowledge mapping software passed licensing review
from the China Academy of Information and Communications Technology, and
DataExa today lists the PLASSF and the Science and Technology Commission of
the PLA Central Military Commission among its clients.131 One of its products, the
DataExa-Sati Knowledge Map, provides “information about U.S. aircraft carrier
equipment, such as submarines, destroyers, cruisers, and frigates accompanying
aircraft carrier strike groups, and infrastructure such as overseas bases, satellite
communications, logistics, and support equipment” to the PLA Navy.132 The company
compares itself to the U.S. data management company Palantir Technologies.133
Center for Security and Emerging Technology25Decision support systems streamline portions of the military decision-making
process by helping identify courses of action for commanders.134 One of China’s most
well-known military AI companies, StarSee ( 摄星智能 ), specializes in computer vision
and decision support software. In 2020, the company won a commendation from
China’s Central Military Commission for its work on combatting COVID-19.135 Among
other products, StarSee advertises a “Real-time Combat Intelligence Guidance
System” designed to “combine the massive parameter model of a knowledge graph
and the dynamic information of the battlefield in real-time.”13 6 StarSee’s product is
designed to create a common operational picture across different PLA units.137 By
“relying on image, video, and audio language extraction and analysis technology,”
the company claims to be able to identify foreign weapons platforms, “give various
performance parameters of the weapon, and calculate its sustainability, firepower,
maneuverability, command and control capabilities, intelligence capabilities, and oth -
er threat level parameters.”13 8 A product demonstration from June 7 , 2020, appears
to track Chinese aircraft flying near a U.S. Arleigh Burke-class destroyer off the coast
of California.139 Members of the StarSee research team previously worked for Baidu,
Alibaba, Tencent, and Microsoft Research Asia.14 0
FIGURE 7
Real-Time Combat Intelligence System Offered by a PLA Contractor
Source: StarSee and Haixun News.141 StarSee’s “Real-time Combat Intelligence Guidance System”
appears to identify and track U.S. Navy assets near California in June 2020.

Center for Security and Emerging Technology26Weapon target assignment software selects an optimal combination of weap -
ons systems to engage one or more targets, assuming different success rates for
each.142 In addition to AI-based predictive maintenance and logistics software, the
PLA contractor Anwise Global advertises a “SIMBAT Weapon Effectiveness Eval -
uation System,” which can reportedly use “test data from multiple sources such as
simulation, internal and external field tests, and exercises, among others, to evaluate
effectiveness throughout the entire life cycle of weapons and equipment.”14 3 It is not
clear whether the PLA has purchased access to SIMBAT specifically, but PLA units
have awarded Anwise Global other AI contracts, and the PLA regularly publishes
AI-based weapon target assignment research of its own.14 4
Combat tasking , whereby a commander selects a course of action and directs a
unit to complete some activity, represents one of the final steps in the military deci -
sion-making process.14 5 Public procurement data indicates that PLA units and de -
fense SOEs have awarded contracts for AI-based command and control software to
support unit-level decision-making and combat tasking. One such project, awarded
by the China Ship Research and Design Center of the China Shipbuilding Industry
Corporation (CSIC), is for an “intelligent loss management system” to help com -
manding officers operate with fewer personnel after sustaining casualties. In another
case, the PLA Ground Force awarded a contract to 4Paradigm, one of the largest
enterprise AI companies in China, for a “battalion and company command deci -
sion-making model and human-machine teaming software.”14 6 4Paradigm advertises
a wide array of products and services, including software-defined computing plat -
forms and an “automatic decision-making machine learning platform” called Sage
HyperCycle.147 As of January 202 1, the company was cooperating on Very Large Da -
tabase research with Intel and the National University of Singapore.14 8 4Paradigm’s
angel investor, Sequoia Capital, remains its largest outside shareholder.149
Taken collectively, these examples illustrate the kinds of public, AI-based deci -
sion support applications being developed by the Chinese defense industry. While
it is too early to say whether the PLA may attempt to automate other segments of
its C2 infrastructure, it is clear that some units have already begun acquiring COTS
technologies for combat decision support and contingency operations. China’s
private AI sector is also starting to mature, with a few specialized companies like
Anwise Global, DataExa, and StarSee carving out a niche to support different seg -
ments of the PLA’s decision-making process.
AUTOMATED TARGET RECOGNITION
Target recognition and fire control are critical components of modern weapons
systems, but applying AI to these tasks is a fairly new area of research. Although
much of the PLA’s research into AI-based automated target recognition is still
aspirational, some units are purchasing relevant systems and equipment, and 4
Center for Security and Emerging Technology27percent (1 4) of PLA AI contracts in our dataset appear related to ATR. Through -
out 2020, PLA units and defense SOEs awarded contracts for feature extraction
and recognition algorithms, target recognition algorithms for unmanned vehicles,
brain-inspired multi-target fusion, and target detection based on synthetic aper -
ture radar imagery.15 0
Most notably, the Chinese military appears to be following in the footsteps of
the DOD in developing AI-based ATR software for aerial vehicles.151 Today, private
Chinese companies, including Shandong Hie-Tech Co., Ltd. ( 山东航创电子科技有限
公司), advertise AI-based ATR systems for use in UAVs. The company won a con -
tract to supply the PLAN with “UAVs and supporting equipment” in June 2020.152
Research papers from PLA and state-sponsored laboratories also discuss develop -
ing AI-based ATR software. For example, the Shenyang Institute of Automation’s
first target recognition research forum in 2017 focused on using deep learning to
recognize targets in still-frame images, and several SIA researchers have conduct -
ed research along similar lines.15 3 SIA’s Robotic Vision Group ( 机器人视觉组 ) lists a
“UAV airborne visual automated target tracking system” as one of its achievements,
but public information about the system is limited.154
FIGURE 8
AI-Based UAV Target Lock Software Advertised by a PLA Contractor
Source: Shandong Hie-Tech.155
Note: The caption reads "Vehicle Recognition: Moving target frame selection locking and tracking
capability based on AI chip computing power; autonomous recovery of targets temporarily lost
due to cover."

Center for Security and Emerging Technology28The PLA also aspires to use AI-based ATR software in undersea vehicles. In
2020, various PLA units awarded ATR contracts to universities and state-run re -
search institutes that were still in the early stages of developing the technology.15 6
Notable examples include “USV target recognition algorithm and software de -
velopment,” “deep learning-based, automatic detection of targets at sea,” and
a contract to construct a “typical marine target database and target recognition
module based on deep learning.”157 Multiple PLA units and defense SOEs awarded
undersea target recognition contracts to Harbin Engineering University, one of sev -
en universities administered by China’s Ministry of Industry and Information Technol -
ogy.15 8 HEU researchers have developed a series of “Smart Water” ( 智水) AUVs for
underwater ATR and path-planning missions, and are suspected of developing the
HSU-001 large UUV first unveiled in China’s 2019 National Day military parade.15 9
Although AI-enabled ATR research is still in early development, it is maturing
rapidly. Recent research papers by PLA units and defense industry engineers have
used machine learning algorithms such as Single Shot Detector 300 (SSD300) and
“You Only Look Once” (YOLO) to recognize targets with more than 80 percent ac -
curacy.160 While many of these algorithms are trained to recognize stationary targets
in long-distance, overhead images, it remains to be seen whether or how the PLA
may adopt AI-based ATR systems for ground-based weapons systems.
Center for Security and Emerging Technology29eyond the Chinese military’s intended application of AI, it is
important for U.S. policymakers and defense planners to under -
stand the sources of the technology that is being purchased by the
PLA. Based on trends in public PLA contracts, we offer three observations
about the overall structure and efficiency of China’s emerging military AI
industry.
First, among the contract award notices in our dataset, defense SOEs
are both buyers and suppliers of AI-related equipment. Research institutes
and subsidiaries belonging to CASC, AVIC, the Aero Engine Corporation
of China (AECC), and CSIC are included in the PLA’s official procure -
ment records (referred to as “PLA contracts”), and each placed orders for
AI-related equipment in 2020.161 Along with other defense SOEs, these
companies and their subsidiaries also received contracts to supply AI-re -
lated equipment to PLA units and other state-owned research institutions.
This two-way transfer of technology could indicate that SOEs are spe -
cializing in certain subfields of AI development, rather than crowding out
private-sector investment.Supply and Demand
for Intelligent
Equipment in the PLA4
B
Center for Security and Emerging Technology30Second, whereas the organizations responsible for buying AI equipment are
fairly concentrated, the PLA’s AI equipment suppliers are diffuse. Of the 343 public
AI contracts in this study, 33 1 contracts named 273 unique suppliers. Most com -
panies were awarded just one public AI contract, and the single most active pri -
vate-sector supplier, Langfang Rongxiang Electromechanical Equipment Co., Ltd.
(廊坊市荣祥机电设备有限公司 ), was awarded just four contracts during our period of
inquiry.
Moreover, China’s MCF development strategy is improving the PLA’s access
to private-sector advances in AI. Since the 1980s, the Chinese government has
attempted to integrate the technical achievements of the civilian and military indus -
tries to strengthen China’s comprehensive national power. In more recent policy
documents, the CCP has called for deepening MCF and “encouraging the two-
way transfer and transformation of military-civil technology,” as evidenced by the TABLE 2
The PLA’s Top Buyers of AI-Related Equipment, April-November 2020TABLE 2
The PL A’s Top Buyers of AI-Related Equipment, April-November 2020
Institution Institution (Chinese) No. of
Contracts
China Aerospace Science and Technology Corporation (CASC) И֢ਡמॠ܉த֝Ҹ՛ 82
Strategic Support Force И֢ыࡇઆݹӋ۫ऋݙݵୂ஄  65
Ground Force И֢ыࡇઆݹӋஏӋ  58
Navy И֢ыࡇઆݹӋࢁӋ  51
Academy of Military Science s Ӌзॠ؆ஓ 34
Air Force И֢ыࡇઆݹӋॱӋ  10
Aero Engine Corporation of China (AECC) И֢ਡॱՇԈߑத߄֝ஒҸ՛  8
Overall Design Institute of Hubei Aerospace Technology Research
Academy (CASIC 9th Overall Design Department) ࢖Ԙਡߐ܉מू९ஓۈѽગઋ۱
И֢ਡמॠٗத֝আЬۈѽગઋୂ 5
Rocket Force И֢ыࡇઆݹӋࢮওӋ 4
China Ship Research and Design Center И֢参ਥू९ગઋИڶ 3
National Defense University И֢ыࡇઆݹӋ֢அॠ؆םߐ܉؆ 3
People’s Armed Police И֢ы࠶ࡇ੸ઊبୂ஄  3
 INSTITUTION INSTITUTION (CHINESE)NO. OF
CONTR ACTS
Source: CSET corpus of PLA purchasing activity (343 contracts specify purchasing units).
Note: Values for state-owned enterprises such as CASC and AECC include multiple subsidiaries.
Center for Security and Emerging Technology31Internet+ Action Plan (201 5), innovation-driven development strategy (2016), and
New Generation Artificial Intelligence Development Plan (2017).162 CSET research
has highlighted the role of new policy levers in achieving this goal, such as gov -
ernment guidance funds, technology brokers, and a formal Chinese AI Industry
Alliance—of which 24 (9 percent) of the 273 suppliers in this study are members.163
It should come as no surprise that a large number of private companies supply the
PLA with AI-related equipment, and that some of these companies have benefited
from equipment, personnel, information, and capital provided directly or indirectly
by the state.
THE PRIVATIZATION OF INTELLIGENTIZATION
A robust military AI industry is emerging in China, spanning Chinese Academy
of Sciences (CAS) research institutes, military factories, universities, private en -TABLE 3
The PLA’s Top Suppliers of AI-Related Equipment, April-November 2020TABLE 3
The PL A’s Top Suppliers of AI-Related Equipment, April-November 2020
Institution Institution (Chinese) No. of Contracts
China Electronics Technology Group Corporatio n И֢ऄ׿ॠ܉த֝Ҹ՛  4
Langfang City Rongxian g Electrical and Mechanical Equipment Co., Ltd. ڋⵐ١哛䯅ߑऄગ߄וஒҸ՛ 4
Harbin Engineering University տٗࢣض३؆ם 4
Hebei Xintu Technology Co., Ltd. ࡜Ԙޏନॠ߄܉ஒҸ՛  4
Shanghai Jiaotong Universit y Їࢁсପ؆ם 3
Beijing Institute of Technology Ԙч؆םࣲٗ 3
University of Science and Technolog y Beijing Ԙчॠ؆ם܉ 3
Beihang University Ԙчਡॱਡ؆םמ 3
Shenzhen City Kehai Technology Co., Ltd. ࢋⴽ١ИॠࢁҒॠ߄܉ஒҸ՛ 3
Northwestern Polytechnical University ੼ԘٗЏ؆ם 3
Inno Aviation Technology Co., Ltd. ੼֜؍મਡॱॠ߄܉ஒҸ՛  3
 INSTITUTION INSTITUTION (CHINESE)NO. OF
CONTR ACTS
Source: CSET corpus of PLA purchasing activity (331 contracts specify suppliers).
Center for Security and Emerging Technology32terprises, state-owned enterprises, and their subsidiaries. To categorize each AI
equipment supplier in our dataset, we searched for background information on
each company’s “About Us” web page, vacancies they advertised on job posting
websites, and ownership information on Chinese financial service and due dili -
gence platforms. We recorded the date each institution was established and any
indication that it may be a subsidiary of a defense SOE or state-owned holding
company. If a company publicly claimed to be a subsidiary or appeared to be
majority-owned by an SOE, university, or CAS institute, we labeled it as such.
Among the 273 unique PLA suppliers identified in this study, we find that private
Chinese technology companies—not SOEs or their subsidiaries—are the PLA’s most
common suppliers of AI-related equipment. Generally speaking, these are recently
established, high-technology companies for whom intelligent software or sensors
are a dominant focus.164 The PLA awarded 61 percent of the public AI contracts in
our dataset to 166 private enterprises. Of them, two-thirds (108) were founded
since 2010, and more than one-third (63) were founded since 201 5. Most have
fewer than 50 employees and registered capital of less than $1 million.165
FIGURE 9
Private Companies are the PLA’s Primary AI Equipment SuppliersFIGURE 9
Private Companies are the PL A’s Primary AI Equipment Suppliers
60.8%Private Compan y
24.5%SOE Subsidiary8.8%University2.2%CAS Institute
3.7%Other
Source: CSET corpus of PLA procurement activity (273 known AI equipment suppliers).
Center for Security and Emerging Technology33As previously noted, China’s MCF strategy is accelerating the PLA’s access
to, and adoption of, AI. Many of the non-state-owned companies that supply the
PLA with AI equipment are supported directly or indirectly by the state, and some
self-identify as “military-civil fusion enterprises” ( 军民融合企业 ). But even non-state-
owned companies tend to jointly develop products with legacy defense SOEs, or
base their business model around supplying them with software and equipment. The
typical modern, private Chinese military AI company is:
• Founded by STEM graduates from elite universities in coastal provinces;
• Headquartered in a commercialization enclave or innovation park run by a
university or the local CCP Science and Technology Commission;
• Engaged with researchers at defense-affiliated universities and research
laboratories; and
• Sustained by contracts from public security bureaus, PLA units, and major
defense SOEs.
LIMITATIONS OF U.S. EXPORT CONTROLS
U.S. policymakers regularly voice concerns that technology produced in the Unit -
ed States may be exfiltrated and deliberately or inadvertently accelerate Chinese
military modernization. The U.S. government has adopted several policies de -
signed to curtail the Chinese defense industry’s access to equipment, personnel,
information, and capital, especially where AI is concerned.166 Since 1989, the
United States has prohibited arms sales to China, and today the U.S. government
presumes denial for license applications of items relevant to national security (NS
items) to known military end-users in China.167 Additional statutes place restrictions
on specific companies:
• The Entity List (EL) published by the U.S. Department of Commerce’s Bureau
of Industry and Security restricts the ability of U.S. firms to sell or supply
technology or intellectual property to specific institutions abroad, including
some individuals and institutions based in China.168
• The Chinese Military-Industrial Complex Companies List (NS-CMIC List)
published by the Department of the Treasury’s Office of Foreign Assets Con -
trol restricts the ability of U.S. persons to make securities investments or own
stock in certain Chinese military companies, pursuant to Executive Order
1395 9.169
Center for Security and Emerging Technology34• The List of Chinese Military Companies (NDAA Sec. 1 260H List) published
by the Department of Defense is mandated by the FY202 1 National De -
fense Authorization Act, and exists to inform Americans of companies that
may be connected to the Chinese military.170 Subsequent Executive Orders
have extended OFAC investment restrictions to include companies on the
Sec. 1 260H List.171
Although tens of thousands of Chinese companies are licensed to supply the
PLA with equipment, very few are found on any of these three U.S. export control
or sanctions lists. Of the 273 known AI equipment suppliers in our dataset, just 8
percent (22) face specific limitations set by the U.S. Departments of Commerce,
Treasury, or Defense. At times, lapses in due diligence and situational awareness
may permit the Chinese military and defense industry to access U.S. technology
and capital.172
FIGURE 10
Portion of Known PLA AI Equipment Suppliers Named
in U.S. Export Control or Sanctions Lists
NS-CMIC
List (O FAC)FIGURE 10
Portion of Known PLA AI Equipment Suppliers Named in U.S. Expo rt
Control or Sanctions Lists
Entity List (BIS)
NDAA Sec.
1260 List (DOD)
NOT LISTEDInformatization (৴ଉԽ) Intelligentization ஐೳԽ
PARENT IS LISTED LISTED91%
83.5%
91.2%
Source: CSET corpus of PLA procurement activity (273 known AI equipment suppliers).
Center for Security and Emerging Technology35Because most institutions that supply AI-related equipment are new and not sub -
ject to end-use controls, the Chinese military is frequently able to access or acquire
technology from abroad, including from the United States. Some Chinese suppliers
make a business out of sourcing foreign data or components and reselling them to
sanctioned Chinese defense companies or PLA units. Beijing Zhongtian Yonghua
Technology Development Co., Ltd. (Zhongtian Yonghua; 北京中天永华科技发展有
限公司 ), for example, is not currently listed in any U.S. sanctions regime. In August
2020, it was awarded a contract to supply intelligent sensor equipment to CASC,
which the DOD designates as a Chinese military company.173 A Chinese online busi -
ness directory entry for Zhongtian Yonghua says that it is “mainly engaged in the
agency and sales of various imported instruments and meters,” and specifies that it
is primarily a distributor of instrumentation equipment produced by companies in the
United States (Agilent, Fluke Corporation, and Testo Inc.) and Japan (Hioki Corpo -
ration and Kyoritsu Electrical Instruments Works, Ltd.).174 Multiple companies engage
in similar activity, and some examples are included throughout this report.175
Center for Security and Emerging Technology46
Center for Security and Emerging Technology37rocurement data offers a detailed, if incomplete, picture of how
the PLA may use AI in future warfare. By comparing trends in pur -
chasing records to long-standing themes observed in theoretical
writings, research papers, and news reporting, we conclude that the PLA
is interested in using AI to erode the U.S. advantage in undersea warfare
and to jam U.S. sensor and communication networks. These aspirations
are particularly relevant for U.S. policymakers and defense planners as
they respond to mounting Chinese threats to Taiwan and other partners in
the Indo-Pacific.176
ERODING THE U.S. ADVANTAGE IN UNDERSEA
WARFARE
The PLA’s adoption of AI appears focused in part on overcoming its
significant disadvantages in undersea warfare. Ten years ago, the PLAN
had “very limited ASW [anti-submarine warfare] capabilities and [ap -
peared] not to be making major investments to improve them”; and more
recent assessments have concluded that floating mines and active sonar
would likely prove ineffective against U.S. submarine forces operating in
or near the Taiwan Strait.177 To compensate, the PLAN commissioned the
construction of an “Underwater Great Wall” ( 水下长城 ) acoustic sensor
network in 2017 , and has since rapidly expanded its diesel submarine
force.178 Today the PLA appears to be making significant investments in
AI-enabled systems, such as A/UUVs, A/USVs, and undersea ISR sys -
tems, which could challenge U.S. and allied submarine forces in a crisis.
In addition to the contract data presented earlier in this report, research
published in 202 1 by Jiangsu University of Science and Technology
claims that “a full spectrum of unmanned submersibles has been initially What the PLA’s
Buying Habits Say
About Its Battle Plans5
P
Center for Security and Emerging Technology38established in China,” listing nearly a dozen AUV and UUV models of varying
sizes.179 Based on contract data and recent technology demonstrations, we assess
that over the next five to 10 years, the PLAN will likely continue expanding its
network of autonomous surface and undersea vehicles in an attempt to limit U.S.
Navy access to the undersea space between the first and second island chains.18 0
Public A/UUV contracts in our dataset are primarily for small- and medi -
um-sized vehicles used for ISR, but English-language reporting has also shed light
on some of the PLA’s larger vessels, which are proliferating in number and grow -
ing in capability.181 Chinese AUVs have also set navigation records for depth and
distance. In June 2020, the SIA’s Haidou 1 ( 海斗一号 ) AUV successfully dove below
10,000 meters in the Mariana Trench; and in November, SIA’s Sea-Whale 2000
(海鲸2000) AUV finished a 37-day continuous test, crossing 1,250 miles of the
South China Sea.182 Despite the PLA’s apparent progress in testing, however, prior
CSET analysis has shown that “the state of the current technology, the complexity
of antisubmarine warfare, and the sheer scale and physics-based challenges of
undersea sensing and communications all suggest these systems have a long way to
go.”18 3 Given limitations in battery life and the robustness of computer vision sys -
tems, it remains to be seen whether the PLA’s expanding AUV force will materially
change the undersea balance of power.
JAMMING AND BLINDING U.S. INFORMATION SYSTEMS
In conjunction with modernizing equipment, the PLA is developing new concepts
of operations oriented around systems confrontation and systems destruction
warfare , in which “warfare is no longer centered on the annihilation of enemy
forces on the battlefield,” but “won by the belligerent that can disrupt, paralyze,
or destroy the operational capability of the enemy’s operational system.”184 For
example, an electronic warfare textbook published by NUDT emphasizes that
“the U.S. military’s combat command, military deployment, and joint operations
are extremely dependent on battlefield information network systems,” and pre -
scribes that, “once the battlefield communication network is broken . . . the entire
battlefield information network system (C4ISR system) will be severely damaged,
destroyed, or even paralyzed.”185 Approximately 8 percent of public procurement
projects in our dataset (29) are related to information and electronic warfare,
many of which focus on jamming or blinding enemy sensor networks and using
AI for cognitive electronic warfare. Examples of such equipment contracts are
outlined in Table 4.
Center for Security and Emerging Technology39Cyberattacks, data manipulation, and electromagnetic spectrum interference
are key components of the PLA’s systems confrontation strategy. In 2020, several
PLA units and state-backed research institutions awarded contracts for “microwave
reconnaissance jamming drones” and “electromagnetic weapon” payloads that
can be attached to swarms of small UAVs and flown into enemy airspace.18 6 PLA
thinkers also emphasize the need to “disrupt or block the enemy's command and
decision-making to ensure one's own decision-making advantage,” and point to the
U.S. Joint Enterprise Defense Infrastructure (JEDI; now the Joint Warfighting Cloud
Capability) as a likely locus of systems confrontation.187 “In the ‘combat cloud’
system,” write PLA National Defense University professors Zhang Xiaotian and Luo
Fengqi, “information and algorithms are key strategic resources, and the opposing
parties will inevitably engage in information confrontation and algorithmic warfare
in the ‘cloud.’”18 8 TABLE 4
Select AI-Related Electronic Warfare Contracts Awarded by PLA
Units in 2020
Translated Project Name MUCD Probable Afﬁliation within the PLA
Autonomous and controllable transformation of software conﬁguration
management system Unit 63796 PLASSF Xichang Space Launch Center
Optical ﬁber line automatic switching protection devices and optical
ampliﬁer equipment Unit 66389 PLASSF (Central Theater Command)
Information and Communications Brigade
Power ampliﬁer and smart pressurizer Unit 63751 PLASSF Base 26 Tracking and
Communications Ofﬁce
Enclosed space automatic frequency modulation device Unit 63672 PLASSF Northwest Academy of Nuclear
Research
Research on key test technology for microwave reconnaissance jamming
UAV Unit 63871 Huayin Conventional Munitions Test and
Training Base
Environmental noise intelligent collection terminal Unit 63811 PLASSF Wenchang Space Launch Center
Algorithm demonstration software for cooperative sensing of radar
targets; credible detection and dynamic evolution of electromagnetic
environment Unit 93209 PLAAF Research Academy
 TABLE 4
Select AI-Related Electr onic Wa rfare Cont racts Awarded by PLA Units in 2020
TRANSLATED PR OJECT NAME MUCD PROBABLE AFFILIA TION WITHIN THE PL A
Source: CSET corpus of PLA procurement activity (seven EW contracts awarded by identifiable PLA units).
Center for Security and Emerging Technology50
Center for Security and Emerging Technology41espite the PLA’s demonstrable progress in adopting AI, three
points of tension will define its continued push toward intelli -
gentization in the 2020s and beyond. These include the vul -
nerability of C4ISR networks; dependence on foreign computer chips;
and disagreements over the development of lethal autonomous weapon
systems.
BREAKING THE COMBAT CLOUD IT STRIVES TO
EMULATE
The first tension concerns the PLA’s plan to exploit U.S. battle networks
while developing its own. Having watched and learned from the U.S.
experience in Afghanistan, Iraq, Kosovo, and Libya, the PLA is invest -
ing heavily in its own networked C4ISR systems, many of which feature
elements of AI.189 The PLA’s vision for an intelligentized force is based in
large part on U.S. military concepts like network-centric warfare, Mosaic
Warfare, and the notion of a “combat cloud.”190 In particular, PLA think -
ers cite the need to “cloudify” ( 云化) their combat systems to speed up the
observe-orient-decide-act (OODA) feedback loop first coined by U.S. Air
Force Colonel John Boyd.191 By emulating U.S. integration of sensor arrays
and weapons platforms, the PLA aims to develop “‘ubiquitous networks’
(泛在网络 ) that will shorten the distance between perception, judgement,
decision-making, and action,” and brace itself for the quickened tempo of
modern warfare.192 “As the pace of war accelerates,” write PLA science
and technology analysts Shi Chunmin and Tan Xueping, “combat time will
be calculated in seconds.”193 They go on to note that Link 16, the commu -
nications and tactical data transmission system used by the United States,
NATO, and coalition forces, allows a delay of just seven milliseconds.194 Fundamental Tensions
in Chinese Military
Modernization6
D
Center for Security and Emerging Technology42But ubiquitously connecting sensors and shooters has created new vulnerabil -
ities for the United States, which PLA leaders recognize and plan to exploit. U.S.
defense planners often lament that exquisite ISR and communication systems make
for “big, fat, juicy targets,”195 and worry that in a crisis, adversaries will jam, blind,
and hack the networks that bind U.S. assets together.196 As previously outlined, PLA
leaders are forging a new array of operational concepts predicated on “systems
confrontation” and “systems destruction,” which are specifically designed to take
advantage of U.S. vulnerabilities.197 But it is not clear how the PLA plans to make
its own networks resilient to the kinds of exploits it envisions deploying against the
United States. One solution may be to develop edge applications of AI that are
insulated from the rest of the battle network.198 Some edge applications—such as
predictive maintenance systems for satellites or target recognition systems for auton -
omous underwater vehicles—can be found among the PLA’s public AI contracts.199
ENSURING ACCESS TO FOREIGN SEMICONDUCTORS
The second tension concerns the supply of advanced computing products at the
heart of China’s intelligentization strategy. Chinese leaders are acutely aware of
the PLA’s wholesale dependence on AI chips designed by U.S. companies and
produced in Taiwan and South Korea. Although computing hardware was not
the original focus of our procurement analysis, further investigation reveals that
the PLA has awarded myriad contracts for U.S.-designed computer chips useful
for training machine learning systems.200 One paper by researchers from China’s
Ministry of Industry and Information Technology estimates that “more than 90%
of China's high-end chips rely on imports,” including “100% of DRAM memo -
ry, 99% of CPUs, and 93% of MEMS sensors.”201 The Chinese government has
constructed multibillion-dollar guidance funds to promote the country’s domestic
semiconductor manufacturing industry, but these initiatives are rife with corruption,
and it is not yet clear whether they will succeed.202
In the meantime, U.S. policymakers have crafted a variety of export controls
and sanctions designed to limit the Chinese military’s access to leading-edge AI
chips.203 Large Chinese corporations such as Huawei have had to cease production
of some product lines and have seen large shortfalls in revenue as a result of U.S.
sanctions.204 However, this study finds that few of the PLA’s AI equipment suppliers—
just 8 percent of the companies in our dataset—face specific barriers to acquiring
U.S. equipment, information, and capital. PLA units and defense SOEs continue to
procure systems that use leading-edge NVIDIA and Xilinx processors, and some -
times purchase these processors, themselves, through intermediary companies.
Moreover, in 202 1, U.S. companies have cooperated on AI-related research proj -
ects with Chinese businesses that supply the PLA with AI systems and equipment.205
Center for Security and Emerging Technology43The PLA’s continued access to U.S. and other foreign technology is not guaran -
teed. The United States and its allies may yet take additional steps to impede Chi -
nese military access to the data, hardware, and personnel required to build an intel -
ligentized force. If such policies were to create a significant shortage in advanced
semiconductors, and if China continues to struggle with indigenizing segments of its
own chip industry, it would likely slow or impair the PLA’s intelligentization strategy.
But U.S. experts warn that a decision to effectively cut off Chinese military access
to foreign advanced semiconductors could inadvertently fuel China’s homegrown
chipmaking industry, and should not be taken lightly.206
DECIDING THE ROLE OF LETHAL AUTONOMOUS WEAPONS
The third tension concerns the development of LAWS. The Chinese government has
famously shown a Janus face to LAWS, publicly calling for a ban on such weap -
ons while privately carving out a legal defense for their development.207 As in the
United States, different factions within the Chinese military and defense industry
harbor different attitudes toward LAWS.208 A 2020 CSET study found that PLA
officers and defense industry engineers are worried AI may undermine strategic
stability by reducing the capability of Chinese air defenses, increasing the vulner -
ability of Chinese command and control systems, or degrading the PLA’s available
time to respond to an attack.209 Some PLA officers appear legitimately disturbed
by LAWS, and caution against a future characterized by smart weapons. In 202 1,
for example, three PLA researchers responded to reports that a Turkish “Kargu-2”
quadcopter had autonomously attacked a human target in Libya, writing that
fully-autonomous weapon systems present “not only a lack of moral responsibility,
but also a serious challenge to international humanitarian law and international
peace and security.”210 This perspective is not uncommon, and PLA officers often
voice similar concerns in research papers and think pieces.
Others in the PLA are more sanguine about AI’s utility on the battlefield, and be -
lieve that technology will inevitably increase the operational tempo of war such that,
unaided by fully automated systems, humans will be incapable of responding to
imminent attack.211 Liu Peng, a member of China’s Cloud Computing Expert Commit -
tee and professor at the PLA University of Science and Technology, wrote in 2020
that “at present, most intelligent combat decision-making systems are semi-autono -
mous systems with humans in the loop,” but that the PLA should “introduce learning
into the combat decision-making process to achieve mutual error correction, com -
plementarity and efficiency.”212 Defense officials in the United States have advanced
similar arguments.213 Among other issues, the fast pace of technology development,
lack of appetite for safety measures, and general lack of trust between the United
States and China are giving rise to a security dilemma around AI development.214
Center for Security and Emerging Technology44Despite the Chinese government’s stated position against LAWS, it is clear that
developing AI-based target recognition and fire control systems is an objective of
some PLA and government-backed research centers.215 Computer vision is by far
the most active subfield of the PLA’s public AI research portfolio, and the share of
PLA-sponsored research papers dedicated to “military target recognition” ( 军事目
标识别 ) increases each year.216 By itself, AI-based ATR does not constitute a lethal
autonomous weapon system. Yet target recognition remains an integral step in the
detect-to-engage sequence, and AI-based ATR is inseparable from “AI weapon”
(人工智能武器 ) concepts described by the Chinese military.217 In August 2020, The
Paper , a well-circulated state-run media outlet, reported that using AI-based ATR
to “equip a missile with a ‘super-powerful brain’ to achieve precision strikes” is
the “lifelong pursuit” of NUDT’s State Key Laboratory for Automated Target Rec -
ognition ( 自动目标识别国家重点实验室 ).218 ATR research published by the Dalian
Naval Academy is similarly explicit, noting that “AI and computer vision technolo -
gy provides new technical support for shipborne missiles to attack all kinds of sea
and land targets accurately” and, “in the process of target recognition, using deep
learning algorithms is an effective way to improve the accuracy of missiles attacking
targets.”219
Ultimately, trends in procurement records, research publications, and media
reports indicate that the Chinese military and defense industry are developing AI-
based target recognition and fire control systems, which are essential components
of LAWS. Although public information about their research is limited, the NUDT
State Key Laboratory for Automated Target Recognition and the CAS Shenyang
Institute of Automation appear to be key institutions driving LAWS development in
China. Combined with the Chinese government’s extraordinarily narrow definition
of LAWS, this emphasis on AI-enabled ATR research suggests that the PLA may
yet develop weapons capable of autonomously detecting and engaging human
targets.220
Center for Security and Emerging Technology45Conclusion
he share of procurement activity dedicated to AI is one indication
that China’s military aspirations extend beyond peripheral security
concerns. In the 2020s, intelligentization has become the chief
focus of Chinese military modernization, with AI-related systems and
equipment already accounting for 5 percent of public contracts awarded
by the PLA’s five main service branches. This report’s narrow look at pub -
lic procurement records confirms that the PLA awarded AI contracts worth
at least $49 million from April to November 2020, and that it may spend
more than $1.6 billion on AI-related systems and equipment each year.
Investing in AI is part of the PLA’s longstanding mission to become a
“world-class” military that is “equal to, or in some cases superior to, the
United States.”221 PLA leaders frequently compare their own capabilities
to those of the U.S. military, and public writings from 202 1 refer explicitly
to degrading and exploiting U.S. information systems. While much of the
PLA’s focus on systems confrontation and systems destruction appears to
still be in early stages of development, a plurality of its equipment con -
tracts are related to information operations and electromagnetic spectrum
dominance. Within the next five to 10 years, the Chinese military will likely
continue investing in AI to erode the U.S. advantage in undersea warfare;
and will seek opportunities to jam, blind, and hack U.S. military information
systems.
Contrary to conventional wisdom about bloating in the Chinese de -
fense industry, we find that the PLA has made significant progress engaging
the private Chinese technology sector to acquire AI systems and intelligent
equipment.222 Most of the PLA’s AI equipment suppliers today are not lega -T
Center for Security and Emerging Technology46cy defense SOEs, but small, private companies that specialize in software develop -
ment, data management, and IoT device design.223 Some Chinese AI companies in
our study self-identify as “military-civil fusion enterprises,” and benefit from equip -
ment, personnel, information, or capital provided by the state. Others are private
technology companies that have welcomed the PLA as a customer.
The PLA’s progress toward intelligentization will become increasingly important
for the United States in the 2020s as tensions between the two countries continue to
rise. In its attempts to harness AI for military advantage, the PLA will face important
questions, for example, about decoupling supply chains and developing lethal au -
tonomous weapons. It remains to be seen whether the Chinese military will succeed
in becoming a fully intelligentized and world-class military force, but one thing is
certain: AI is no longer just an emerging technology. Rather than speculate about its
far-future implications, defense planners and policymakers would do well to heed
the words of science fiction writer William Gibson: “The future is already here—it's
just not evenly distributed.”224
Center for Security and Emerging Technology47Appendix I: Classifying “Intelligent” Equipment Contracts
Tenders in CSET’s PLA procurement dataset include four variables. The authors manually ex -
tracted another three fields where information was available, and subjectively coded two other
fields based on each tender’s Name and Content. All nine variables considered in this study
are listed below.
Name. Each of the 66,207 tenders in our dataset has a name that offers some information
about the purchase. Of them, 45,868 are “public” ( 公开) and include more detailed informa -
tion fields, listed below.
Public Unit. Each public tender also mentions an agency or department for which the tender is
being filed, typically a large branch of an organization, such as “Strategic Support Force.”
Information Type. Public tenders in our dataset included requirements, inquiries, bid solici -
tations, and notices of contract awards, annulments, and modifications, among other types of
information. Of the 45,868 public tenders in our dataset, 1 8,354 were contract award notices.
Content. Each public tender listed additional, detailed information in the body of the an -
nouncement text. The 343 AI-related contracts in our dataset variously included three kinds of
information:
End user: The PLA unit or state-owned defense company that intended to use the technology,
specified in 232 cases.
Supplier: The company or research institution that successfully won the contract to supply the
equipment, specified in 33 1 cases.
Contract value: The total value of the contract, specified in 205 cases.
AI Relevance. After using fourteen keywords to identify 523 “intelligent” equipment contracts,
the authors manually examined project names and descriptions to verify that each was actual -
ly related to AI.225 For the purpose of this paper, the authors included off-the-shelf UAVs and
intelligence-related subsystems, intelligent or automatic weather monitoring, and intelligent
power distribution as “AI-related,” but excluded UAV molds used for manufacturing, wing
parts, and “intelligent” or “automatic” systems with no clear connection to AI, such as “intelli -
gent welding systems” and “automatic drilling equipment.” 1 80 contracts were excluded from
analysis, leaving 343 AI-related contracts.
Application. The authors then manually categorized each of the 343 AI contracts into one of
seven different applications: (1) Intelligent and Autonomous Vehicles; (2) Intelligence, Sur -
Center for Security and Emerging Technology48veillance, and Reconnaissance; (3) Predictive Maintenance and Logistics; (4) Information and
Electronic Warfare; (5) Simulation and Training; (6) Command and Control; and (7) Automated
Target Recognition. Tenders that did not fit in any of these seven categories were marked “Other.”
Categorizing each contract was necessarily a subjective, iterative process. To make the labels
more robust, the authors used the Elicit AI research assistant to check their manual coding.226
Elicit uses language models to code data. For each contract, Elicit used the manual labels for
some of the other contracts as training data, then labeled each “intelligent equipment” contract
in the dataset. Initially, Elicit agreed with author coding in 50 percent of cases. After one author
reviewed the disagreements, recoded some of the data, and reran Elicit, agreement increased to
62 percent. For remaining disagreements, author judgment superseded that of Elicit. Table 5 lists
10 examples of how the authors coded “intelligent” equipment contracts.
Center for Security and Emerging Technology49TABLE 5
Examples of Coded “Intelligent” Equipment Contracts
Tender Name (Chinese) Tender Name (English) Counts as AI? Application(s)
Ȕ>>ы޴ٗਈӁځֺऀް֫ગઋՃҼ୰һ
ߐ܉ۅ஬ࡌӣߤȕԥ▲࢛ߛҸॐ"XX design and artiﬁcial intelligence typical application
scenarios demand analysis of key general use
technologies" sole source announcemen t Yes Other
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ਈ֘ߑыࢮ֨ߐ܉ওӋΗΗঝٗ३ځऀू
९ȕாऩיԣ "Research on military applications of AI technology for
rockets - intelligent robotics technology in rocket
military XX class engineering applied research project"
outsourcing Yes Autonomous Vehicles
(Munitions)
Ȕ֫ځݼ୍ߐ܉ڏू९ȕȔׂй֪஭ۨࡦ
ҦԽڟࣲѽҍچࢋڨ঑ࡣू९ȕா߆ԇঝ
தИ۸ԕ୊૆ாऩTwo service-type pooled and packaged procurement
projects on "research on effect ﬁeld reconstruction
technology," and "research on projectile penetration
depth algorithms based on the principles of seismic
wave imaging" Yes Autonomous Vehicles
(Munitions)
Ȕ޴ਈԣࣲהԆବԪԆٗչःٵ׺Ֆ ࡹ
ડȕ߶ܥৈߧҸճз "Intelligent co-processor accelerator card processing
and Shenwei [CPU and operating system] platform
testing" tender announcement Yes Other
Ȕਡמ੸޴וਈ㌿ࠒ঩৏Ҽ୰ߐ܉ू९ȕ
છ߶ৈߧҸॐ Announcement of bid evaluation results for the "study
of key technology for an aerospace equipment
intelligent inspection system" Yes Predictive
Maintenance and
Logistics
Ȕ㌿ਡڟЊޗыߑѢऱ঩৏ڐՇȕיԣ୊
૆ாऩИ߶Ҹճ "Cruise missile and UAV simulation system
development" outsourcing procurement bid
announcement Yes Simulation and
Training
ாऩޗыٵߑՖӣ঩৏ॼжۅળӮ୊
૆И߶ҸճAnnouncement of the winner of the Project 1903 UAV
platform subsystems competitive negotiation
procurement tender Yes Autonomous Vehicles
(Air)
ࢆࡈࣆ૶Ѻݹ݌߯ࡑ௄ࡣސࡹ
ू९Њ௠ચИ߶Ҹճ Announcement of the winning bid for 2020 -6356 low-
emission gas turbine prediction methods research and
validation No N/A
૱୿ԡਘԈԗ֕Мગו୊૆  Procurement of Workshop 23: semi-automated blasting
equipment No N/A
Q<иߢ঒ؘ௠ू९ٵՖਘԈԗ஍ً঩
৏ாऩИ߶ҘଣыҸॐ Announcement of ﬁnalists for the 500kV diode
experimental research platform automated subsystems
project tender No N/A
 TABLE 5
Examples of Coded “Intelligent” Equipment Contr acts
TENDER NAME (CHINESE) TENDER NAME (ENGLISH) COUNT S AS AI? APPLIC ATION(S)
Source: CSET corpus of PLA procurement activity, with input from Elicit.
Center for Security and Emerging Technology50
Center for Security and Emerging Technology51Appendix II: AI-Related Purchases by Service Branch
Relative to defense SOEs or military academies, contract data indicates that the PLA’s five ser -
vice branches are extraordinarily active in adopting AI. The Strategic Support Force, Ground
Force, Navy, Air Force, and Rocket Force were responsible for awarding just 20 percent
(3,726) of the public contracts in our dataset, but 55 percent (1 88) of those related to AI. That
said, AI-related equipment contracts constitute just 5 percent of all the equipment contracts
awarded by PLA service branches in our April–November 2020 dataset.
TABLE 6
Number of Equipment Contracts Awarded by PLA Service Branches,
April-November 2020
The PLA’s five main service branches are most focused on using AI to improve navigation and
data management in autonomous vehicles; to improve the speed and scale of intelligence col -
lection and dissemination; and to enhance logistics through predictive maintenance. However,
each of the services tend to focus on different applications of AI. For example, relative to other
branches, the PLASSF is most interested in purchasing AI technology that can be used in infor -
mation and electronic warfare, whereas the Ground Force tends to purchase more AI solutions
for predictive maintenance and logistics. Each of the PLA’s service branches are focused on
using AI in intelligent and autonomous vehicles and for predictive maintenance, but ISR and
information and electronic warfare are also common applications.PLA Service Branch Total Number of Equipment
Contracts Number of AI-Related
Equipment Contracts Portion of Public Contracts
Related to AI
Strategic Support Force 1,674 65 3.9%
Ground Force 682 58 8.5%
Navy 1,102 51 4.6%
Air Force 199 10 5.0%
Rocket Forc e 69 4 5.8%
Total 3,726 188 5.0%
 TABLE 6
Number of Equipment Contr acts A warded by PLA Service Br anches,
April-November 2020
PLA SER VICE BR ANCHTOTAL NUMBER OF
EQUIPMENT C ONTR ACTSNUMBER OF AI-REL ATED
EQUIPMENT C ONTR ACTSPORTION OF PUBLIC
CONTR ACTS RELATED TO AI
Source: CSET corpus of PLA procurement activity.
Center for Security and Emerging Technology52PLA STRATEGIC SUPPORT FORCE (PLASSF)
As the service branch responsible for space, cyber, and information warfare, the PLA Strategic
Support Force is the most active in procuring AI-related technologies and applications. Of the
PLASSF’s 65 public AI-related contracts, most were related to intelligence, surveillance, and
reconnaissance (ISR); information warfare, and autonomous vehicles.
FIGURE 11
Number of AI Equipment Contracts Awarded by PLA Service Branches,
April-November 2020
Air Fo rceNavyGround ForceStrategic
Suppor t Force
NUMBER OF AI EQUIPMEN T CONTRACT SFIGURE 11
Number of AI Equipment Contr acts A warded by
PLA Service Br anches, April-November 2020
Rocket Fo rce
Autonomous Vehicle s Intelligence, Surveillance, and Reconnaissanc e
Predictive Maintenanc e01 02 03 04 05 06 07 0
Information and Electr onic Warfare
Simulation and Training Target Recognition Command and Cont rol
Other
Public procurement records indicate that the PLASSF is focused on using AI for intelligence and
data fusion, especially for applications such as weather monitoring, earth imagery, and battle
damage assessment. One of its most expensive public contracts in 2020, valued at $1. 1 mil -
lion, was for an automatic high-altitude image detection system provided by Nanjing Britronics
Machinery Co., Ltd. ( 南京大桥机器有限公司 ). The company produces more than 60 types of
weather radar and satellite imaging equipment, including an “intelligent high-altitude image
detection system” capable of measuring meteorological phenomena between 36 and 200
kilometers above ground.227 In July 2020, PLASSF Unit 63672 also bought a UAV-borne “frag -Source: CSET corpus of PLA procurement activity (188 contracts awarded by service branches).Air Fo rceNavyGround ForceStrategic
Suppor t Force
NUMBER OF AI EQUIPMEN T CONTRACT SFIGURE 11
Number of AI Equipment Contr acts A warded by
PLA Service Br anches, April-November 2020
Rocket Fo rce
Autonomous Vehicle s Intelligence, Surveillance, and Reconnaissanc e
Predictive Maintenanc e01 02 03 04 05 06 07 0
Information and Electr onic Warfare
Simulation and Training Target Recognition Command and Cont rol
Other
Center for Security and Emerging Technology53ment distribution measurement system” from Xi'an Kuaizhou Measurement and Control Technol -
ogy Co., Ltd. ( 西安快舟测控技术有限公司 ), an application particularly useful in battle damage
assessment.228 The General Staff Department’s Survey and Mapping Research Institute in Xi’an
(Unit 61 540) was another significant purchaser of AI-enabled ISR equipment within the PLASSF,
awarding various contracts for intelligentized forecast correction systems, high-precision posi -
tioning algorithms, and high-resolution ocean and climate modeling software.229
The PLASSF envisions using AI for information and electronic warfare, in applications ranging
from multilingual natural language processing to public opinion monitoring, cyber threat in -
telligence, and adaptive radar jamming. For example, the PLASSF’s Engineering Information
University awarded various contracts for an AI-based “internet public opinion monitoring and
clustering system,” “intelligent network traffic analysis system,” and a “cyber threat intelligence
early warning platform” throughout 2020. Previous research suggests that PLASSF Base 3 1 1
(Unit 617 16) carried out social media manipulation ahead of Taiwan’s 201 8 local elections.230
One of the PLASSF’s repeat contractors, EverSec, advertises services for petabyte-scale data
storage and processing, AI-based open source data mining, and internet blocking and cen -
sorship protocols.231 In addition, multiple PLASSF units have awarded contracts for AI-based
fiber optical line protection switches, network amplifiers, and automated frequency modulation
systems used in cognitive electronic warfare.232
The PLASSF is also awarding contracts for autonomous vehicles, both individual platforms for
logistics and sustainment and swarms with potential combat applications. Public reporting indi -
cates that the PLASSF has been experimenting with using UAVs to resupply troops from Lhasa,
Tibet, for operations near the Line of Actual Control with India.223 The service’s procurement
records indicate that it has purchased several UAVs and intelligentized simulation systems from
Lyncon Tech ( 西安羚控电子科技有限公司 ), a leading provider of Chinese drone swarm technolo -
gy, specifically for use in or near Lhasa. In June 2020, the PLASSF’s Equipment Command and
Technology Academy (Unit 63628) awarded a $630,000 contract to AOSSCI Technology for
a UAV simulation and training center.
PLA GROUND FORCE (PLAGF)
After the PLASSF, the Ground Force has displayed the most interest in adopting AI, and award -
ed 58 of the public AI-related contracts in our dataset. Previous studies show that academic AI
research sponsored by the PLAGF tends to focus on improving unmanned or robotic systems’
ability to navigate difficult terrain, and this priority is also reflected in the service’s public pro -
curement records.234 Of the 58 AI contracts the PLAGF awarded in 2020, the plurality were
related to autonomous vehicles, predictive maintenance, and electronic warfare.
The PLAGF is most focused on using AI in autonomous aerial and ground vehicles. Valued at
$890,000, its single most expensive public AI contract involved developing a UAV swarm, to
be fulfilled by CASC Shenzhou Flight Vehicle Co., Ltd. ( 航天神舟飞行器有限公司 ). The company
Center for Security and Emerging Technology54holds several patents related to swarm technology and UAV-based applications of the Beidou
satellite constellation.235 Other PLAGF contracts were related to ultra-short-range control link
modules and non-line-of-sight transceivers for unmanned and autonomous UAVs. The PLAGF is
also leveraging AI for ground vehicles, and in June 2020 awarded a contract to Beijing Laser
Bofeng Information Technology Co., Ltd. ( 北京雷神博峰信息技术有限责任公司 ), “a major sup -
plier of vehicle-mounted Beidou information terminals and intelligent control systems for petrol
vehicles,” to develop an autonomous tanker truck.236 The company specializes in autonomous
“IoT vehicles” for logistics and transportation.237
Predictive maintenance is another clear priority for the PLAGF. Throughout 2020, it awarded
contracts for “intelligent supply chain” networks, ammunition shell quality detection software,
and equipment failure and maintenance prediction systems. Among these, its most expensive
project was a $275,000 contract for a “self-organized network intelligent packaging system”
for bullets. The contractor, Chongqing Jialing Special Equipment Co. ( 重庆嘉陵特种装备有限
公司), is a wholly owned subsidiary of the defense SOE China North Industries Corporation
(NORINCO).238
To a lesser degree, the PLAGF is also leveraging AI for electronic warfare. In September 2020,
PLAGF Unit 6387 1 awarded Xi'an Ruiweishen Electronic Technology Co., Ltd. ( 西安睿维申电子
科技有限公司 ) a $160,000 contract to develop a “microwave reconnaissance jamming drone.”
In 201 3, the company had won a national Torch Program award for a high-performance dig -
ital signal processing platform.239 The PLAGF awarded a similar contract to TIYOA Aviation (
河北天遥航空设备科技有限公司 ) to develop “electromagnetic weapon” payloads aboard small
UAVs. The company specializes in intelligent control systems, video surveillance, and small
drone applications.240
PLA NAVY (PLAN)
The Navy is just behind the Ground Force as the PLA’s third-most active branch in adopting AI,
and awarded 5 1 of the public AI-related contracts in our dataset. Most contracts were relat -
ed to autonomous vehicles, ISR, and other applications not neatly captured in our taxonomy.
Naval Aviation University ( 海军航空大学 ) was the PLAN unit most active in awarding AI con -
tracts, accounting for nearly one third (1 5) of those in our dataset. Valued at $1.3 million, the
PLAN’s most expensive public AI contract involved retrofitting unmanned aerial vehicles with
multi-tasking pods, to be filled by AECC Guizhou Liyang Aviation Power Co., Ltd. ( 中国航发贵
州黎阳航空动力有限公司 ). Several other PLAN contracts were related to sea floor mapping and
AUV development.
Intelligence, surveillance, and reconnaissance is another major focus of the PLAN’s AI pro -
curement. Several contracts mention fusing automatic identification system (AIS) ship position -
ing data to improve situational awareness for submarine and surface fleets. For example, in
June and July 2020, the PLAN Submarine Academy ( 海军潜艇学院 ) purchased bulk AIS ship
Center for Security and Emerging Technology55tracking data from Elane Inc. ( 亿海蓝（北京）数据技术股份公司 ) and tasked the company with
bulk AIS processing.241 Elane runs shipfinder.com , a global shipping database with “millions
of global shipping and related users.”242 The company advertises “real-time monitoring of all
satellite AIS ship positions worldwide,” updated every five minutes, using a constellation of
108 Orbcomm satellites.243 Although Orbcomm is a U.S. satellite company, Elane’s AIS service
is marketed for Chinese users only. Other PLAN units have struck similar contracts to purchase
AIS data from Yantai Huadong Electron Technology Co., Ltd. (Huadong Elec-Tech; 烟台华东电
子软件技术有限公司 ) and the China Transport Telecommunications & Information Center (CTTIC)
Information Technology National Engineering Laboratory.244
The PLAN’s other AI contracts involve building libraries of undersea sonar signatures and using
deep learning to stitch them together. In July 2020, the PLAN’s Naval Aviation University
awarded Harbin Engineering University with a contract for an “automatic sea-based target de -
tection” system based on “deep learning image recognition.” Several researchers at HEU have
pioneered an AI-based “seabed image mosaic system,” hold relevant patents, and regularly
conduct research on the topic.245
PLA AIR FORCE (PLAAF)
With just ten public AI contracts, the Air Force appears much less interested in AI procurement,
relative to the Ground Force or Navy. Its AI purchases are mostly related to autonomous vehi -
cles, predictive maintenance, and electronic warfare.
Most public AI research papers sponsored by the PLAAF are related to autonomous flight, a
trend that extends to its procurement records.246 Several contracts were related to intelligent
flight decision control ( 智能驾驶决策控制 ), technology primarily developed by Northwestern
Polytechnical University and research institutes subordinate to CASC. One of the primary com -
panies involved in supplying autonomous UAVs to the PLAAF is ChunYi UAV ( 北京淳一航空科技
有限公司 ), a Beijing-based provider of autonomous aerial and surface-sea vehicles.247 In Sep -
tember 2020, the PLA Air Force paid to lease and operate some of ChunYi UAV’s autonomous
aerial vehicles. The company’s website specifies that its products are useful for “counterterror -
ism and aerial dogfight weapons testing and training.”248
Some of the PLAAF’s more expensive AI contracts are related to predictive maintenance for
communication networks. In April 2020, for example, China Eracom Contracting and Engi -
neering Co., Ltd. ( 中时讯通信建设有限公司 ), a fiber-optic cable company, won a contract for an
“intelligent operation and maintenance management system.” That month, the PLAAF awarded
a similar contract to China Iconic Technology Co, Ltd. ( 中徽建技术有限公司 ), a twice-removed
subsidiary of China Telecom, for an intelligent phone network system.
Finally, like the PLAGF, the PLAAF is also interested in using AI for electronic warfare and elec -
tromagnetic spectrum dominance. In October 2020, the PLAAF’s Air Defense Early Warning
Equipment Department (Unit 93209) awarded China Civil Aviation University a contract for
Center for Security and Emerging Technology56“trusted radar target detection” and “research into the dynamic evolution of the electromagnetic
environment,” using algorithms to enhance battlefield situational awareness and plot the loca -
tions of friendly radar units.
PLA ROCKET FORCE (PLARF)
The Rocket Force is the least active service branch with respect to public AI procurement, award -
ing just four contracts from April to November 2020. The PLARF contracts included using AI to
forecast maintenance and support resource consumption; as well as to develop intelligent robot -
ics; a “smart communications warehouse”; and an autonomous, tethered UAV platform.
The PLARF awarded its largest AI contract to China Electronics Technology Corporation (CETC)
for an autonomous, tethered UAV platform, to be supplied to the 61 3 Brigade in Shangrao
City.249 Tethered drones are particularly useful for emergency response and communication, as
an autonomous UAV can be towed alongside a ground vehicle or watercraft without the need
for constant supervision or recharging.250 CETC’s 54th Research Institute produces lines of four-
and six-rotor tethered UAVs,251 while the 7th and 23rd Research Institutes hold patents on UAV
mooring cables.252 Other Chinese companies have developed tethered UAVs for emergency
communications, such as the DG-X10 and DG-M20.253
Center for Security and Emerging Technology57Endnotes
1. “GPT-3 Powers the Next Generation of Apps,” OpenAI, March 25, 202 1, https://openai.com/blog/gpt-3-
apps/ .
2. Thomas Mahnken, “Secrecy & Stratagem: Understanding Chinese Strategic Culture,” Lowy Institute, 201 1,
https://archive.lowyinstitute.org/sites/default/files/pubfiles/Mahnken%2C\_Secrecy\_and\_stratagem\_1.pdf .
3. Lonnie Henley, “PLA Operational Concepts and Centers of Gravity in a Taiwan Conflict,” testimony before
the U.S.-China Economic and Security Review Commission, Hearing on Cross-Strait Deterrence, February
1 8, 202 1, https://www.uscc.gov/sites/default/files/202 1-02/Lonnie\_Henley\_Testimony.pdf ; and Oriana
Skylar Mastro, “The Taiwan Temptation: Why Beijing Might Resort to Force,” Foreign Affairs , July 202 1,
https://www.foreignaffairs.com/articles/china/202 1-06-03/china-taiwan-war-temptation .
4. The PLA considers “intelligentized” warfare to be a style of warfare characterized by “ubiquitous networks,”
in which “‘human-on-human’ warfare will be replaced by ‘machine-on-human’ or ‘machine-on-machine
warfare.” Yang Wenzhe, “How to Win Intelligentized Warfare by Analyzing What are Changed and What
are Unchanged” [在变与不变中探寻智能 化战争制胜之道 ], PLA Daily , October 22, 2019, translated by the U.S.
Army Foreign Military Studies Office, http://www.8 1.cn/jfjbmap/content/2019-10/22/content\_2458 10.htm .
5. Translation by Joel Martinsen of Liu Cixin’s Ball Lightning (New York: Tor Books, 201 8): 1 50.
6. Jiayang Fan, “Liu Cixin’s War of the Worlds,” The New Yorker, June 24, 2019, https://www.newyorker.com/
magazine/2019/06/24/liu-cixins-war-of-the-worlds .
7. Derek Grossman, "Envisioning a 'World-Class' PLA: Implications for the United States and the Indo-Pacific,"
RAND Corporation, July 1, 2019, https://www.rand.org/content/dam/rand/pubs/testimonies/CT500/
CT5 1 4/RAND\_CT5 1 4.pdf .
8. Shana Lynch, “Andrew Ng: Why AI Is the New Electricity,” Stanford Business, March 1 1, 2017 , https://www.
gsb.stanford.edu/insights/andrew-ng-why-ai-new-electricity .
9. Forrest E. Morgan, Benjamin Boudreaux, Andrew J. Lohn, Mark Ashby, Christian Curriden, Kelly Klima, and
Derek Grossman, “Military Applications of Artificial Intelligence: Ethical Concerns in an Uncertain World,”
RAND Corporation, 2020: 77 , https://www.rand.org/pubs/research\_reports/RR3 1 39-1.html .
10. For landmark analyses of AI in the PLA, see Gregory C. Allen, “Understanding China's AI Strategy: Clues
to Chinese Strategic Thinking on Artificial Intelligence and National Security,” Center for a New American
Security, February 6, 2019, https://www.cnas.org/publications/reports/understanding-chinas-ai-strategy ;
Elsa B. Kania, “‘AI weapons’ in China’s military innovation,” Brookings Institution, April 2020, https://www.
brookings.edu/research/ai-weapons-in-chinas-military-innovation/ ; and Marcus Clay, “New Concept
Weapons: China Explores New Mechanisms to Win War,” China Brief 2 1, no. 8 (April 23, 202 1): 26–33,
https://jamestown.org/program/new-concept-weapons-china-explores-new-mechanisms-to-win-war/ .
A “program of record” is a “a directed, funded effort that provides a new, improved, or continuing materiel,
weapon, or information system or service capability in response to an approved need.” See “Finding the
Right Transition Path,” U.S. Department of Defense Office of Small Business Programs, 2017 , https://business.
defense.gov/Portals/57/Documents/BPII-MPTW17%20slides/Tuesday/Yarmie\_Finding%20The%20
Right%20Transition%20Path.pdf?ver=2017-09-1 1-1 4325 1-370/ .
11 . For the official budget and analysis, see Matthew P. Funaiole and Brian Hart, “Understanding China’s 202 1
Defense Budget,” Center for Strategic and International Studies, March 5, 202 1, https://www.csis.org/
analysis/understanding-chinas-202 1-defense-budget . By comparison, the most updated third-party estimate
puts Chinese military spending at $252 billion. See “World military spending rises to almost $2 trillion in
2020,” Stockholm International Peace Research Institute, April 26, 202 1, https://www.sipri.org/media/
press-release/202 1/world-military-spending-rises-almost-2-trillion-2020 .
Center for Security and Emerging Technology581 2. China Power Team, "What Does China Really Spend on its Military?" Center for Strategic and International
Studies, December 28, 201 5 (Updated May 27 , 202 1), https://chinapower.csis.org/military-spending/ .
13 . In the United States, the 202 1 DOD budget request includes $243 billion for equipment acquisition: $1 37
billion for procurement and $107 billion for research, development, test, and evaluation. Combined, they
amount to approximately 34 percent of the U.S. defense budget. See “Long-Term Implications of the 202 1
Future Years Defense Program,” Congressional Budget Office, September 2020, https://www.cbo.gov/
publication/56554 .
1 4. “Military and Security Developments Involving the People’s Republic of China,” U.S. Department of Defense,
2020: 1 38, https://media.defense.gov/2020/Sep/01/2002488689/-1/-1/1/2020-DOD-CHINA-
MILITARY-POWER-REPORT-FINAL.PDF .
15. Cortez A. Cooper III, “PLA Military Modernization: Drivers, Force Restructuring, and Implications,” RAND
Corporation, February 1 5, 201 8: 10, https://www.rand.org/content/dam/rand/pubs/testimonies/
CT400/CT488/RAND\_CT488.pdf .
16. “The Ministry of National Defense confirmed for the first time that the PLA has basically achieved
mechanization” [ 国防部首次证实：解放军已经基本实现机械化 ], NetEase News, November 27 , 2020, https://
perma.cc/Q79Y-GCC4 .
17. M. Taylor Fravel, “China’s New Military Strategy: “Winning Informationized Local Wars,” China Brief
1 5, no. 1 3 (July 2, 201 5): 3–7 , https://jamestown.org/program/chinas-new-military-strategy-winning-
informationized-local-wars .
1 8. Edmund J. Burke, Kristen Gunness, Cortez A. Cooper III, Mark Cozad, “People's Liberation Army
Operational Concepts,” RAND Corporation, 2020, https://www.rand.org/content/dam/rand/pubs/
research\_reports/RRA300/RRA394-1/RAND\_RRA394-1.pdf .
19. Dean Cheng, “Chinese Party Sets Bold Military Goal: ‘Mechanized & Informationized’ By 2027 ,” Heritage
Foundation, November 24, 2020, https://www.heritage.org/asia/commentary/chinese-party-sets-bold-
military-goal-mechanized-informationized-2027 .
20. Zichen Wang, ‘Once-in-a-generation change in PLA guidelines: intelligentization added, mechanization
declared ‘basically accomplished,’” Pekingnology, December 8, 2020, https://pekingnology.
substack.com/p/once-in-a-generation-change-in-pla ; P.K. Mallick, “Defining China’s Intelligentized
Warfare and Role of Artificial Intelligence,” Vivekanada International Foundation, 202 1, https://
indianstrategicknowledgeonline.com/web/Defining%20China%20Intelligentized%20Warfare%20
and%20Role%20of%20Artificial%20Intelligence.pdf .
21. Yang Wenzhe, “How to Win Intelligentized Warfare by Analyzing what are Changed and What are
Unchanged.”
22. Original CSET translation by Ben Murphy, “Outline of the People’s Republic of China 1 4th Five-Year Plan for
National Economic and Social Development and Long-Range Objectives for 2035” [ 中华人民共和国国民经
济和社会发展第十四个五年规划和 2035 年远景目标纲要 ], Xinhua, May 1 3, 202 1, https://cset.georgetown.edu/
publication/china-1 4th-five-year-plan/ .
23. Cheng, “Chinese Party Sets Bold Military Goal: ‘Mechanized & Informationized’ By 2027.”
24. While the word “intelligentization” is not in the PLA’s 201 3 Science of Military Strategy , the document does
refer to “intelligent weaponry,” warfare becoming “long-range, rapid, precise and intelligent,” and other
uses clearly associated with “intelligentization.” See “Science of Military Strategy (201 3),” translation by
China Aerospace Studies Institute, published February 8, 202 1, https://www.airuniversity.af.edu/CASI/In-
Their-Own-Words/Article-Display/Article/2485204/plas-science-of-military-strategy-201 3/ .
25. James Mulvenon, “China’s ‘Goldwater-Nichols’? The Long-Awaited PLA Reorganization Has Finally
Arrived,” China Leadership Monitor 49 (Winter 2016): 1–6, https://www.hoover.org/sites/default/files/
research/docs/clm49jm.pdf ; John Costello and Joe McReynolds, China’s Strategic Support Force: A Force
for a New Era (Washington, DC: National Defense University Press, 201 8): https://ndupress.ndu.edu/
Media/News/Article/165 1760/chinas-strategic-support-force-a-force-for-a-new-era/ .
26. Emily S. Weinstein, Testimony before the U.S.-China Economic and Security Review Commission on “U.S.
Investment in China’s Capital Markets and Military-Industrial Complex,” March 19, 202 1, https://www.
Center for Security and Emerging Technology59uscc.gov/files/001763 ; Emily de La Bruyère and Nathan Picarsic, “Defusing Military-Civil Fusion: The
Need to Identify and Respond to Chinese Military Companies,” Foundation for Defense of Democracies,
May 27 , 202 1, https://www.fdd.org/analysis/202 1/05/26/defusing-military-civil-fusion/ .
27. Tai Ming Cheung, Fortifying China: The Struggle to Build a Modern Defense Economy (Ithaca: Cornell
University Press, 201 3): https://www.amazon.com/Fortifying-China-Struggle-Defense-Economy/
dp/0801 4792 1 5 ; Yoram Evron, “China’s Military-Civil Fusion and Military Procurement,” National Bureau
of Asian Research, January 28, 202 1, https://www.nbr.org/publication/chinas-military-civil-fusion-and-
military-procurement/ ; James C. Mulvenon and Richard H. Yang, “The People’s Liberation Army in the
Information Age,” RAND Corporation, 1999, https://www.rand.org/pubs/conf\_proceedings/CF1 45.html .
28. 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 (DIUx), January 201 8, https://admin.govexec.com/media/diux\_
chinatechnologytransferstudy\_jan\_201 8\_(1).pdf ; and Cheung, Fortifying China .
29. These include requirements ( 需求), inquiries ( 询价), and bid solicitations ( 公开招标 ).
30. Tim Schmidt, “Guidelines for Competitive Bidding,” ProcureWare, August 27 , 201 4, https://www.
procureware.com/guidelines-competitive-bidding/ .
31. These include winning bid announcements ( 中标公告 ) and single-source procurement awards ( 单一来源公示
or 单一来源公告 ).
32. Confidential ( 秘密) and secret ( 机密) projects correspond to different security levels, similar to the information
classification system in the United States. Note that the use of these phrases for classified material differs from
their standard meaning in Chinese. See “State Secrets” [ 国家秘密 ], China Law Wiki, accessed September 27 ,
202 1, https://perma.cc/CN5H-K3LZ .
33. For a full list of China’s 1 1 largest defense SOEs, see “Table 2. China’s State-Owned Defense Companies,”
in Ryan Fedasiuk and Emily Weinstein, “Universities and the Chinese Defense Technology Workforce,”
Center for Security and Emerging Technology, December 2020, https://cset.georgetown.edu/publication/
universities-and-the-chinese-defense-technology-workforce/ .
34. See the official definition in “Summary of the 201 8 Department of Defense Artificial Intelligence Strategy,”
https://media.defense.gov/2019/Feb/1 2/2002088963/-1/-1/1/SUMMARY-OF-DOD-AI-
STRATEGY.PDF ; and analysis by Greg Allen, “Understanding AI Technology,” U.S. Department of Defense
Joint AI Center, April 2020, https://www.ai.mil/docs/Understanding%20AI%20Technology.pdf .
35. As demonstrated in this study, China’s AI equipment suppliers are not shy about showcasing their products
and services. In some cases, we were able to validate information in CSET’s corpus of PLA procurement
records by examining press releases published contemporaneously by contract awardees.
36. Elicit is a research assistant developed by the applied research lab Ought, which makes use of the GPT-3
language transformer developed by OpenAI. See “Elicit: The AI Research Assistant,” https://elicit.org ;
and Jungwon Byun and Andreas Stuhlmüller, “Automating reasoning about the future at Ought,” Ought,
November 9, 2020, https://ought.org/updates/2020-1 1-09-forecasting .
37. To minimize false negatives, we processed several iterations of keywords, first using explicit phrases like
“artificial intelligence” and “machine learning,” and eventually adding broader terms like “robot” and
“learning” to our search.
38. Data from 2020 indicates that the purchasing power of the Chinese RMB is more than four times that of
the U.S. dollar. See data from the OECD, “Purchasing power parities (PPP),” accessed September 202 1,
https://data.oecd.org/conversion/purchasing-power-parities-ppp.htm . However, “PPP estimates do not
account for specific cost differences of many military-related items,” warn Matthew P. Funaiole and Brian
Hart, “Understanding China’s 202 1 Defense Budget.”
39. In the United States, Major Defense Acquisition Programs (MDAPs) and Major Automated Information
Systems (MAISes) are acquisition programs expected to exceed certain lifetime procurement costs ($2.79
billion and $520 million, respectively), and are subject to enhanced oversight and scrutiny. It is not clear
whether the PLA has adopted similar definitions or procedures in its procurement system. See “Acquisition
Process: Major Defense Acquisition Program (MDAP),” AcqNotes, updated June 2 1, 202 1, https://
acqnotes.com/acqnote/acquisitions/major-defense-acquisition-program .
Center for Security and Emerging Technology6040. In 2017 , the last year data was available, the PLA spent 41 percent of its budget on equipment, amounting
to $64 billion. The PLA’s official public budget has since grown substantially, from $1 54 billion in 2017 to
$209 billion in 202 1. Assuming the share of funding for equipment has remained the same, it is likely that the
PLA will have spent approximately $86 billion on equipment in 202 1. See baseline statistics in China Power
Team, “What Does China Really Spend on Its Military?”
41. The 205 AI contracts in our dataset with known monetary values combined to a total of 3.5 billion RMB
($49 million USD), with the average contract amounting to 1.6 million RMB ($230,000 USD). On net, AI-
related contracts accounted for 1.9 percent of contract award notices in our dataset. If at least 1.9 percent
of the PLA’s total estimated $86 billion equipment spending went to AI-related projects, then it would have
spent at least $1.6 billion on the technology in 2020.
42. Ashwin Acharya and Zachary Arnold, “Chinese Public AI R&D Spending: Provisional Findings,” Center for
Security and Emerging Technology, December 2019, https://cset.georgetown.edu/publication/chinese-
public-ai-rd-spending-provisional-findings/ .
43. Autonomy is counted as distinct from AI in most analyses of U.S. military AI spending, but we incorporate
keywords related to both fields in this analysis of the PLA. See Chad Peltier, “Put Your Money Where Your
Strategy Is,” War on the Rocks, March 23, 2020, https://warontherocks.com/2020/03/put-your-money-
where-your-strategy-is-using-machine-learning-to-analyze-the-pentagon-budget/ ; and Margarita Konaev,
Husanjot Chahal, Ryan Fedasiuk, Tina Huang, and Ilya Rahkovsky, “U.S. Military Investments in Autonomy
and AI: A Budgetary Assessment,” Center for Security and Emerging Technology, October 2020, https://
cset.georgetown.edu/publication/u-s-military-investments-in-autonomy-and-ai-a-budgetary-assessment/ .
44. Elsa B. Kania, “Battlefield Singularity: Artificial Intelligence, Military Revolution, and China’s
Future Military Power,” Center for a New American Security, November 2017: 1 1, https://s3.us-
east-1.amazonaws.com/files.cnas.org/documents/Battlefield-Singularity-November-2017.
pdf?mtime=2017 1 1 29235805&focal=none .
45. Prior CSET research has evaluated the PLA’s interest in autonomous or unmanned aerial, surface, undersea,
or ground vehicles; intelligent munitions; intelligent satellites; intelligence, surveillance, and reconnaissance
(ISR) software; automated cybersecurity software; automated cyberattack software; decision support
software; automated missile launch software; and software used in cognitive electronic warfare. See Ryan
Fedasiuk, “Chinese Perspectives on AI and Future Military Capabilities,” Center for Security and Emerging
Technology, August 2020, https://cset.georgetown.edu/publication/chinese-perspectives-on-ai-and-
future-military-capabilities/ .
46. “Autonomy Communities of Interest,” Defense Innovation Marketplace, accessed March 202 1, https://
defenseinnovationmarketplace.dtic.mil/communities-of-interest/autonomy/ .
47. Liu Peishan, “Overview of China’s Logistics Drone Industry in 2020” [2020 年中国物流无人机行业概览 ],
LeadLio, April 2020, https://perma.cc/5W6X-6SLA ; and “About Us” [ 关于我们 ], the Drone Network,
accessed March 202 1, https://perma.cc/K4PR-KE2J .
48. Information available upon request.
49. Elsa Kania, “The PLA’s Unmanned Aerial Systems: New Capabilities for a ‘New Era’ of Chinese Military
Power,” China Aerospace Studies Institute, August 201 8: 20, https://www.airuniversity.af.edu/Portals/10/
CASI/Books/PLAs\_Unmanned\_Aerial\_Systems.pdf .
50. Rick Joe, “China’s Growing High-End Military Drone Force,” The Diplomat, November 27 , 2019, https://
thediplomat.com/2019/1 1/chinas-growing-high-end-military-drone-force/ .
51. “Marine Information Technology Equipment Center” [ 海洋信息技术装备中心 ], Shenyang Institute of
Automation, accessed May 202 1, https://perma.cc/YS6L-T28K .
52. Information available upon request.
53. Joseph Trevithick, “China Is Hard At Work Developing Swarms Of Small Drones With Big Military
Applications,” The Drive, January 16, 201 8; https://www.thedrive.com/the-war-zone/17698/chinas-
is-hard-at-work-developing-swarms-of-small-drones-on-multiple-levels ; Liu Xuanzun, “China unveils first
practical drone swarm tech, ‘to be used in amphibious landing missions,’” Global Times, October 1 8, 2020,
https://www.globaltimes.cn/content/1 203857.shtml ; Jeffrey Lin and Peter W. Singer, “China is making
1,000-UAV drone swarms now,” Popular Science, July 1 3, 202 1, https://www.popsci.com/china-drone-
swarms/ .
Center for Security and Emerging Technology6154. The first reported use of a drone swarm in combat took place in May 202 1, when Israeli Defense Forces used
a swarm in Gaza during a conflict with Hamas. See Zachary Kallenborn, “Israel’s Drone Swarm Over Gaza
Should Worry Everyone,” Defense One, July 7 , 202 1, https://www.defenseone.com/ideas/202 1/07/
israels-drone-swarm-over-gaza-should-worry-everyone/1 83 1 56/ . The PLA appears to be exploring similar
capabilities. In “‘AI weapons’ in China’s military innovation,” Elsa Kania warns that the PLA “has fielded a
growing number of robotic and unmanned systems, as well as advanced missiles with precision guidance,
some of which may possess at least limited degrees of autonomy.” PLA officers in 202 1 have also clarified
that “UAV group operations have moved from conceptual research to battlefield practice.” See Ding Zaiyong,
Yang Xiaoling, and Hao Weichuan, “Military Forum ｜Group warfare, interpreting a new picture of the
unmanned battlefield” [ 军事论坛｜群式作战，演绎无人战场新图景 ], PLA Daily, May 20, 202 1, https://perma.
cc/QE5D-HP4K .
55. For example, in November 2020, CASC’s 503 Research Institute purchased an AI-based radar coincidence
imaging system from Nanjing Leiying Electronic Technology Co., Ltd. ( 南京理工雷鹰电子科技有限公司 ).
56. PLA theoretical writing has also emphasized the role of UAV swarms in combat operations: “They can also be
used for targeted killing.” See “Drone ‘swarms’ will change the rules of the battlefield” [ 无人机 “蜂群”或改变战
场规则 ], Army Bridge Network, March 6, 2017 , https://perma.cc/UF6T-5XLN .
57. “UAV Dispatching System” [ 无人机调度系统 ], the Drone Network, March 17 , 202 1, https://perma.cc/
F4C7-JM27 ; and “LoRa SWARMLINK Portable Cluster Unmanned System Dedicated Gateway” [ 若联
SWARMLINK 便携式集群 无人系统专用网关 ], the Drone Network, September 25, 2017 , https://perma.cc/
YSS2-FT5U .
58. “About Inno” [ 关于因诺 ], Inno Aviation Technology Company, accessed June 9, 202 1, https://perma.cc/
WT87-MWZB ; “Some Thoughts on UAV Swarm Combat” [ 无人机蜂群作战的几点思考 ], PLA Unit 661 33, July
2019, https://perma.cc/P7N9-4RYW ; and “Intelligent decision-making and planning” [ 智能决策与规划 ],
Zhejiang University Institute of UAV Systems and Control, accessed June 23, 202 1, https://perma.cc/S597-
8FAK .
59. An extraordinarily detailed report from researchers at Beihang University discusses U.S. swarm capabilities
and how the Chinese military could defeat them: Wang Xiangke, Liu Zhihong, Cong Yirui, Li Jie, and Chen Hao,
“Overview and future development of small fixed-wing UAV clusters” [ 小型固定翼无人机集群综述和未来发展 ],
Acta Aeronautica Sinica 41, no. 4 (2020): 023732, https://perma.cc/E3PG-GHZJ .
60. For an example of a ship intelligent integration platform, see Pang Yu, Zhao Fan-qi, and Wu Jun, “Research
and Design of Intelligent Integrated Platform for Smart Ships” [ 智能船舶集成平台的研究与设计 ], MARIC Science
and Technology Forum 5, no. 1 82 (2019): https://perma.cc/RFN5-N927 .
61. Xi'an Tianhe Haiphong Intelligent Technology Co., Ltd. ( 西安天和海防智能科技有限公司 ) won the 2020 National
Underwater Robot (Zhanjiang) Competition in May 2020: “Underwater Robot Competition: Xi'an Tianhe
Haiphong Intelligent Technology Co., Ltd.-Introduction to Smart Ocean Team” [ 水下机器人大赛：西安天和海防
智能科技有限公司 -智慧海洋队简介 ], Phoenix New Media, May 16, 2020, https://perma.cc/NT79-NWKN.
Also see “expendable mobile ASW training target”: https://perma.cc/SZ8R-7YEH .
62. “Underwater Robot Competition” by Phoenix New Media calls Tianhe Defense “the first domestic scientific
research team to realize the industrialization of underwater unmanned autonomous vehicles.” Tianhe Defense
also advertises a “shadowless underwater unmanned reconnaissance solution” ( 无影水下无人侦察解决系统 )
designed to detect submarines: “Xi'an Tianhe Defense is ready to help 2017 China Ocean Economy Expo”
[西安天和防务蓄势待发 助力 2017 中国海洋经济博览会 ], Sohu post, November 29, 2017 , https://perma.
cc/2SVV-B4FM .
63. “Autonomous Underwater Vehicle” [ 自主水下航行器 ], HiSoUR, accessed June 1 5, 202 1, https://perma.cc/
UWN3-99U5 .
64. “Hanhai Lanfan Zhifan AUV-ZF-01 Underwater Drone” [ 瀚海蓝帆 智帆 AUV-ZF-01 水下无人机 ], the Drone
Network, accessed June 26, 202 1, https://perma.cc/E8XE-32UJ .
65. “KHI Pipeline Inspection AUV” [KHI 管道检测 AUV], the Drone Network, June 8, 2019, https://perma.cc/
VU5P-95TA .
66. “Underwater Robot Competition,” Phoenix New Media.
Center for Security and Emerging Technology6267. Hunan Gaozhi Technology Co., Ltd. is listed as a “military-civilian high-tech enterprise jointly supported
by the Hunan Provincial Department of Science and Technology and the National University of Defense
Technology,” and received $1 10,000 from the province’s MCF fund in 201 8: “Projects to be supported by
the special fund for the development of military-civilian integration industry in Hunan Province” [ 湖南省军民
融合产业发展专项资金拟支持项目 ], Hunan Software Industry Association, March 6, 201 8, https://perma.cc/
A5XV-ZKDP .
68. See examples of cameras, “GZ-1C8837HXG-LR/FA/VE/I50,” https://perma.cc/4FZQ-39KH ; “GZ-
1C7837HXG-FA/VE/I20,” https://perma.cc/Y686-WBQ4 ; servers, “GZ-3804D-FA,” https://perma.
cc/SD76-8LN5 ; and patents, “Invention of the integrated guidance assembly disclosed” [ 发明一体化制导组
合体公开 ], https://perma.cc/VX9R-MTLN; all accessed June 1 4, 202 1.
69. Information available upon request.
70. Elsa Kania, “Chinese Military Innovation in Artificial Intelligence,” Testimony before the U.S.-China
Economic and Security Review Commission, Hearing on Trade, Technology, and Military-Civil Fusion, June
7 , 2019, https://www.uscc.gov/sites/default/files/June%207%20Hearing\_Panel%201\_Elsa%20Kania\_
Chinese%20Military%20Innovation%20in%20Artificial%20Intelligence\_0.pdf .
71. Song Yuangang and Shao Longfei, “Military Big Data: An Accelerator of Military Intelligence Revolution” [
軍事大數據︰軍事智能變革的加速器 ], PLA Daily , September 6, 2019, https://perma.cc/3SK8-38F9 .
72. In “Challenges to Security in Space,” the U.S. Defense Intelligence Agency concludes that, “Since observing
the U.S. military’s performance during the 1991 Gulf War, the PLA embarked on an effort to modernize
weapon systems and update doctrine to place the focus on using and countering adversary information-
enabled warfare,” https://www.dia.mil/Portals/27/Documents/News/Military%20Power%20
Publications/Space\_Threat\_V1 4\_0201 19\_sm.pdf .
73. Information available upon request.
7 4. Zhang Yinan, “The development of domestic database and the practice of Uxsino software” [ 国产数据库发展
与优炫软件实践 ], presentation by Uxsino, accessed June 1 4, 202 1, https://perma.cc/7ZF5-VBER .
75. Zhang Yinan, “The development of domestic database and the practice of Uxsino software.”
76. Qin Yuan, “The Development and Application of Remote Sensing Micro-Satellite,” Shenzhen Aerospace
Dongfanghong HIT Satellite Ltd. presentation before the United Nations, September 201 8, https://perma.
cc/5JBS-9PXM .
77. “Holographically Perceive the Ocean and Discover the Value of Data” [ 全息感知海洋，发现数据价值 ], Startest
Marine, accessed June 1 4, 202 1, https://perma.cc/MPF8-DACG .
78. “GeoSide1 400 High Resolution Side-Scanning Sonar” [GeoSide1 400 高分辨率侧扫声呐 ], Startest Marine,
accessed June 1 4, 202 1, https://perma.cc/F4FX-NB93 .
79. “The 4th Committee Meeting of the 10th Professional Committee of Marine Surveying and Mapping of the
Chinese Society of Surveying and Mapping and the 32nd Comprehensive Academic Symposium on Marine
Surveying and Mapping Ended Successfully in Kunming” [ 中国测绘学会第十届海洋测绘专业委员会第四次全体委
员会议暨第三十二届海洋测绘综合性学术研讨会在昆明圆满落幕 ], Startest Marine, November 30, 2020, https://
perma.cc/DFV9-QKCV ; and “GeoSide1 400 High Resolution Side-Scanning Sonar.”
80. “Surveying and Mapping Data Management and Release Platform” [ 测绘数据管理与发布平台 ], Startest
Marine, accessed June 1 4, 202 1, https://perma.cc/X4YC-H3LF .
81. “Surveying and Mapping Data Management and Release Platform.”
82. William Hannas and Huey-Meei Chang, “China’s STI Operations: Monitoring Foreign Science and
Technology Through Open Sources,” Center for Security and Emerging Technology, January 202 1, https://
cset.georgetown.edu/publication/chinas-sti-operations/ ; and Larry M. Wortzel, “The Chinese People’s
Liberation Army and Information Warfare,” U.S. Army War College Strategic Studies Institute, March 201 4:
1 8, https://publications.armywarcollege.edu/pubs/2263.pdf .
83. “GL-AI Speech Recognition System 001” [GL-AI 语音识别 001], Glaucus-Tech, accessed July 1, 202 1,
https://perma.cc/KQ7K-P732 . By comparison, Google Translate can process Chinese with 80-95
percent accuracy: Nicole Wetsman, “Google Translate still isn’t good enough for medical instructions,” The
Verge, March 9, 202 1, https://www.theverge.com/202 1/3/9/223 19225/google-translate-medical-
instructions-unreliable .
Center for Security and Emerging Technology6384. Glacus-Tech’s image recognition system specifically runs on NVIDIA processors. An NVIDIA-branded Jetson
TX2 is visible on its product description page: “GL-AI Image Recognition System 001” [GL-AI 图像识 别001],
Glacus-Tech, accessed July 1, 202 1, https://perma.cc/5VBR-PCHD ; see information about the P40 at
“NVIDIA Tesla P40 GPU Accelerator,” NVIDIA, accessed July 1, 202 1, https://www.nvidia.com/content/
dam/en-zz/Solutions/design-visualization/documents/nvidia-p40-datasheet.pdf .
85. Comments by Neal Higgins, Jason Wang, and Rachael Martin, “The Cutting Edge of AI & Intelligence,”
Cipher Brief, July 1 2, 202 1, https://www.thecipherbrief.com/column\_article/cutting-edge-of-ai-
intelligence .
86. Fedasiuk, “Chinese Perspectives on AI and Future Military Capabilities,” 19–20.
87. For example, see “Structural Damage Detection and Intelligent Diagnosis” [ 结构损伤检测与智能诊断 ], Weixin
posts from October 29, 2020, https://perma.cc/HGB2-DUMW; and November 22, 2020, https://
perma.cc/KP6P-XR3V .
88. Information available upon request.
89. “Industry Solutions,” Anwise Global Technology, accessed June 1 4, 202 1, https://perma.cc/K7FE-53Y2 ;
and “About Us,” Anwise Global Technology, accessed June 1 4, 202 1, https://perma.cc/J79E-Y5NJ .
90. For example, see the following products advertised by Anwise Global Technology, accessed June 1 4, 202 1,
“PCB Solder Joint Fatigue Calculation and Test Verification Solution” [PCB 焊点疲劳计算及试验验证解决方案 ],
https://perma.cc/EJV9-XH7B ; “Construction of Virtual Prototype Warehouse of Aeronautical Weapons”
[飞航武器虚拟样机库建设 ], https://perma.cc/3BBJ-M7LM ; and “Simulation Performance Verification V&V
Tool” [ 仿真性能验证 V&V工具], https://perma.cc/UQ2T-G7YZ .
91. “Counter-UAV System” [ 反无人机系统 ], Wego, accessed June 1 5, 202 1, https://perma.cc/D5PS-Q826 ;
“About Us” [ 关于我们 ], Sucheon Technologies, accessed June 22, 202 1, https://perma.cc/RX2U-KL4V ;
and “Predictive maintenance service provider ‘Sucheon Technologies’ completed nearly 100 million yuan in
Series B financing” [ 预测性维护服务商「硕橙科技」完成近亿元 B轮融资 ], September 24, 2020, https://www.
chinaventure.com.cn/news/108-20200924-358 173.html .
92. “Virtual test platform V-LAB” [ 虚拟试验平台 V-LAB], Anwise Global Technology, accessed June 1 4, 202 1,
https://perma.cc/8QGQ-NBX8 and https://perma.cc/J6CZ-B6FV .
93. Brett Daniel, “What Is Automatic Test Equipment (ATE)?,” Trenton Systems, February 1 1, 202 1, https://www.
trentonsystems.com/blog/automatic-test-equipment-overview .
94. Shi Chunmin and Tan Xueping, “Digital Warfare Requires Data Thinking” [ 数字化战争需要数据化思维 ], China
National Defense Magazine , November 22, 201 8, https://perma.cc/C3TZ-P9JB .
95. Information available upon request.
96. “Joint Publication 3-1 3: Information Operations,” U.S. Army Training and Doctrine Command, November
20, 201 4, https://www.jcs.mil/Portals/36/Documents/Doctrine/pubs/jp3\_1 3.pdf ; for additional
explanation, see Clay Wilson, “Information Operations, Electronic Warfare, and Cyberwar: Capabilities
and Related Policy Issues,” Congressional Research Service, March 20, 2007 , https://fas.org/sgp/crs/
natsec/RL3 1787.pdf .
97. Elsa Kania, “The PLA’s Latest Strategic Thinking on the Three Warfares,” China Brief 16, no. 1 3 (August 22,
2016): 10–1 4, https://jamestown.org/program/the-plas-latest-strategic-thinking-on-the-three-warfares/ .
98. Ryan Fedasiuk, “A Different Kind of Army: The Militarization of China’s Internet Trolls,” China Brief 2 1, no.
7 (April 1 2, 202 1): 8–1 8, https://jamestown.org/program/a-different-kind-of-army-the-militarization-of-
chinas-internet-trolls/ ; and Zhang Wei, Tang Xiaoyan, and Chen Xi, “A Brief Analysis of the Development
Trend of Public Opinion Warfare in Modern Wars” [ 简析现代战争中舆论战的发展走向 ], PLA Daily , accessed
July 1, 202 1, https://perma.cc/5X6J-KSBN .
99. Ben Buchanan, Andrew Lohn, Micah Musser, and Katerina Sedova, “Truth, Lies, and Automation: How
Language Models Could Change Disinformation,” Center for Security and Emerging Technology, May
202 1, https://cset.georgetown.edu/publication/truth-lies-and-automation/ .
100. The PLA unit primarily responsible for psychological operations and public opinion manipulation is Base
3 1 1 (Unit 617 16), which falls under the jurisdiction of the Strategic Support Force’s Network Systems
Center for Security and Emerging Technology64Department. In recent years, Base 3 1 1 has conducted social media manipulation and influence operations
against Taiwan, and its affiliated researchers have written about the significance of AI in automating social
media analysis and propaganda campaigns. Despite being a focal point for information operations, Base
3 1 1 is not mentioned in any of the public procurement notices in our dataset—likely because of its secrecy.
See Elsa Kania, “The Role of PLA Base 3 1 1 in Political Warfare against Taiwan,” Global Taiwan Brief 2,
no. 7 (February 1 5, 2017): https://globaltaiwan.org/2017/02/1 5-gtb-2-7/ ; and Nathan Beauchamp-
Mustafaga and Jessica Drun, “Exploring Chinese Military Thinking on Social Media Manipulation Against
Taiwan,” China Brief 2 1, no. 7 (April 1 2, 202 1): 25–35, https://jamestown.org/program/exploring-
chinese-military-thinking-on-social-media-manipulation-against-taiwan/ .
101. “Online Behavior Management Equipment” [ 网上行为管理设备 ], Zhengzhou Meicheng Electronic Technology
Co., accessed July 1, 202 1, https://perma.cc/ES5U-ESL3 .
102. See online behavior management systems advertised by Ruijie Networks: “RG-UAC 6000-E20M,” https://
perma.cc/Y55R-7C5Q ; and “RG-UAC6000,” https://perma.cc/3QGG-KTYK . More information is
available at “RG-UAC 6000 Series: Unified Online Behavior Management and Audit” [RG-UAC6000 系列
统一上网行为管理与审计 ], https://perma.cc/RA6L-Q4Z3 ; all accessed July 1, 202 1.
103. “Naval Workers College in the Self-Media Age: How to Deal with Public Opinion in Colleges and
Universities” [ 自媒体时代海军职工大学如何应对高校舆情 ], KnowleSys, accessed July 1, 202 1, https://perma.
cc/69XX-9F7L .
104. Fedasiuk, “A Different Kind of Army.”
105. “How Artificial Intelligence Affects Public Opinion War” [ 人工智能如何影响舆论战 ], PLA Daily, March 2, 202 1,
https://perma.cc/64AK-JRMS .
106. The specific technical method is called minimum variance distortionless response (MVDR) beamforming;
for example, see Wang Qingye and Liu Haitao, “Phased Array Adaptive Cancellation Technology
Countermeasure Research” [ 相控阵自适应对消技术对抗研究 ], Ship Electronics Engineering 39, no. 1 2 (2019):
77-82, https://perma.cc/L9GL-69QL .
107. For example, see Wang, Wang, Chen, and Cao, “A Cognitive Radar Signal Correlated Clutter Sensing
Method.”
108. Ji Weijie, Zhou Weiping, and Liu Tingjun, “Analysis on the Development Characteristics of Modern Electronic
Warfare” [ 现代电子战发展特点浅析 ], Optoelectronics 10, no. 3 (September 2020): 60–65, https://perma.
cc/AR54-ZKK7 ; also see Marcus Clay, “To Rule the Invisible Battlefield: The Electromagnetic Spectrum and
Chinese Military Power,” War on the Rocks, January 22, 202 1, https://warontherocks.com/202 1/01/to-
rule-the-invisible-battlefield-the-electromagnetic-spectrum-and-chinese-military-power/ .
109. “Since the 1950s, the PLA has simultaneously used a True Unit Designator (TUD/ 部队番号 ) system, where units
are identified by their actual number, and a Military Cover Unit Designator (MUCD/ 䜘䱏) system to protect
the identity of its units [...] The PLA assigns MUCDs to ‘units’ ( 部队代号 ), which are defined as corps-, division-,
brigade-, and regiment-level operational and support organizations.” For more information, see Kevin
Pollpeter and Kenneth W. Allen, “The PLA As Organization v2.0,” Defense Group Incorporated, 32–33,
https://apps.dtic.mil/sti/pdfs/AD10827 42.pdf .
1 10. Cui Jifeng and Hu Fuzeng, “Research on Adaptive Active Jamming Strategy Based on Pattern Recognition” [
基于模式识别的自适应有源干扰策略研究 ], Ship Electronics Engineering 38, no. 10 (October 201 8): 104–108,
https://perma.cc/XA3R-NPNX; Wang Long, Wang Lijia, Chen Lei, Cao Xinglong, “A Cognitive Radar
Signal Correlated Clutter Sensing Method” [ 一种认知雷达信号相关杂波感知方法 ], Ship Electronics Engineering
7 (2020): 85-92, https://perma.cc/3884-YZ6K ; and Ji, Zhou, and Liu,“Analysis on the Development
Characteristics of Modern Electronic Warfare.”
111 . Ben Buchanan, John Bansemer, Dakota Cary, Jack Lucas, and Micah Musser, “Automating Cyber Attacks:
Hype and Reality,” Center for Security and Emerging Technology, November 2020, https://cset.
georgetown.edu/publication/automating-cyber-attacks/ .
1 1 2. Dakota Cary, “Academics, AI, and APTs: How Six Advanced Persistent Threat-Connected Chinese
Universities are Advancing AI Research,” Center for Security and Emerging Technology, March 202 1,
https://cset.georgetown.edu/publication/academics-ai-and-apts/ .
113 . For one example, see “Portable Intelligent Terminal Inspection System” [ 便携式智能终端检测系统 ], Skywo
Technology, accessed June 1 4, 202 1, https://perma.cc/7KD3-KZW8 .
Center for Security and Emerging Technology651 1 4. EverSec website home page, accessed July 2, 202 1, https://perma.cc/EBK7-UCZP .
115 . “CISA Launches New Joint Cyber Defense Collaborative,” U.S. Cybersecurity and Infrastructure Security
Agency, August 5, 202 1, https://www.cisa.gov/news/202 1/08/05/cisa-launches-new-joint-cyber-
defense-collaborative .
1 16. EverSec website home page.
117 . “Core Technical Capabilities” [ 核心技术能力 ], EverSec, accessed July 2, 202 1, https://perma.cc/D46Y-JV8R .
1 1 8. “EVERSEC,” Sequoia Capital, accessed October 202 1, https://perma.cc/VSV5-RU8V and https://perma.
cc/GD4E-67GN .
119 . Derek Solen, “Initial Fighter Pilot Training in the PLA Air Force,” China Aerospace Studies Institute, February
202 1, https://www.airuniversity.af.edu/Portals/10/CASI/documents/Research/PLAAF/202 1-02-16%20
Initial%20Fighter%20Pilot%20Training.pdf?ver=CWRhXQPS7sgn1voTIxrdOw%3d%3d ; Mark Cozad, “PLA
Joint Training and Implications for Future Expeditionary Capabilities,” RAND Corporation, 2016, https://
www.rand.org/pubs/testimonies/CT45 1.html ; and Ben Lowsen, “Chinese PLA Training: A Window on
Military Culture,” The Diplomat, April 1 3, 2016, https://thediplomat.com/2016/04/chinese-pla-training-a-
window-on-military-culture/ .
1 20. “AlphaWar Wargame Deduction: ‘The Art of AI Command in Virtual Gunpowder and Decisive Wisdom’”
[AlphaWar 兵棋推演：虚拟硝烟中的 AI指挥艺术与决胜智慧 ], DataExa, March 1 3, 2020, https://perma.cc/9PPF-
Q9GL .
121. Dean Cheng, “The People’s Liberation Army on Wargaming,” War on the Rocks, February 17 , 201 5, https://
warontherocks.com/201 5/02/the-peoples-liberation-army-on-wargaming/ .
1 22. “In the ‘Intelligence+’ Era, How Artificial Intelligence Will Disrupt Future War” [" 智能+"时代，人工智能如何颠覆
未来战争 ], Xinhua, January 2, 201 8, http://www.xinhuanet.com/mil/201 8-01/02/c\_1 29780425.htm .
123 . “War Game in Taiwan Strait 2019” [ 兵棋推演台海 2019], China Institute of Command and Control, July 3,
2019, https://perma.cc/Z97J-UZDG.
1 24. Information available upon request.
125 . “Experimental Center Construction” [ 实验中心建设 ], eDong AI, https://perma.cc/QQR5-7AKJ ; and “VR/
AR/MR Software Development” [VR/AR/MR 软件研发 ], eDong AI, https://perma.cc/WRK2-J2ND ; both
accessed July 9, 202 1.
1 26. AOSSCI product listings on the Drone Network, accessed June 1 4, 202 1, https://perma.cc/2KLU-5UAA ; for
more information, see “X-Chimera UAV+LiDAR system solves your problems perfectly!,” AOSSCI Facebook
post, June 2 1, 2020, https://www.facebook.com/aossci/videos/7 16602538909533 ; and “X-Matrix: An
integrated flight simulation platform developed by AOSSCI independently!,” AOSSCI, accessed June 1 4,
202 1, https://perma.cc/C97F-SLDD .
127. Liu Xuanzun, “PLA deploys AI in mock warplane battles, 'trains both pilots and AIs,’” Global Times , June 1 4,
202 1, https://www.globaltimes.cn/page/202 106/1 2261 3 1.shtml .
1 28. “AlphaWar Wargame Deduction.”
129. Elsa Kania, “Minds at War: China’s Pursuit of Military Advantage through Cognitive Science and
Biotechnology,” Prism 8, no. 3 (January 2020): 83-101, https://ndupress.ndu.edu/Portals/68/Documents/
prism/prism\_8-3/prism\_8-3\_Kania\_82-101.pdf .
1 30. “DataExa "Tianyan" Series Opening: ‘Combat Simulation Deduction System’ for Future Warfare” [ 渊亭“天衍”
系列开篇：面向未来战争的「作战仿真推演系统」 ], DataExa Sohu post, November 5, 2020, https://perma.cc/
Z4A9-426U .
131. “DataExa’s self-developed distributed graph database passed the product evaluation of China Academy
of Information and Communications Technology” [ 渊亭自研分布式图数据库通过中国信通院产品评测 ], Motian
Wheel, July 1 3, 2020, https://perma.cc/X59T-Z2FT .
1 32. “DataExa-Sati Knowledge Graph” [DataExa-Sati 知识图谱 ], https://perma.cc/J6PS-KZKA ; also see
“Tianyan·Combat Simulation Deduction Platform” [ 天衍·作战仿真推演平台 ], https://perma.cc/B27A-UXBF ;
and “Tianji·Weapon and Equipment Atlas Platform” [ 天机·武器装备图谱平台 ], https://perma.cc/52QS-47PR ;
all accessed July 7 , 202 1.
133 . “Apparatus and Application of Knowledge Graph (1): Real-time visualization engine for millions of
knowledge graphs” [ 知识图谱的器与用（一）：百万级知识图谱实时可视化引擎 ], DataExa Sohu post, April 1 2,
2020, https://perma.cc/459Q-25VB .
Center for Security and Emerging Technology661 34. Gary M. Klein and Alan P. Hastings, “Decision-Support Planning and Tools: Planning to Support Decision-
Making,” U.S. Army Ft. Benning, 2016, https://www.benning.army.mil/armor/eARMOR/content/
issues/2016/APR\_JUN/2Klein-Hastings16.pdf .
135 . “About StarSee” [ 关于摄星 ], StarSee, accessed August 2, 202 1, https://perma.cc/8UNK-MBME .
1 36. “StarSee completed a new round of tens of millions of financing, and simultaneously launched the ‘Millions
of Annual Salary Talents Program’” [ 摄星智能完成新一轮数千万融资，同步启动 “百万年薪英才计划 ”], Qianlong,
October 1 4, 2020, https://perma.cc/3RNK-NNM6 .
137. The U.S. military defines a common operational picture (COP) as “a single identical display of relevant
information shared by more than one command that facilitates collaborative planning and assists all echelons
to achieve situational awareness.” See “Joint Publication 3-0: Joint Operations,” U.S. Department of Defense,
updated October 22, 201 8, https://www.jcs.mil/Portals/36/Documents/Doctrine/pubs/jp3\_0ch1.pdf .
1 38. “The first domestically-made military algorithm platform, 8 categories and 30 defense-specific models,
StarSee opens its internal ‘StarSee’ platform for the first time” [ 首个国产军事算法平台， 8类30个防务专用模型，
摄星智能首次开放内部「星智」平台 ], Heart of the Machine Sohu post, July 1 3, 2020, https://perma.cc/76TP-
C7 4X .
139. Image uploaded by Xaixun News, accessed July 8, 202 1, https://perma.cc/XS4G-ZSB2 .
1 40. “The first domestically-made military algorithm platform…”
141. “Heavy! --StarSee Releases Ten Trends of Military Intelligence in 202 1” [ 重磅！—摄星智能发布 2 0 21 年军事智能
十大趋势 ], Technology News, https://perma.cc/AEC7-X4N3 .
1 42. For example, see Zhang Mingyang and Chen Chen, "Joint task management of sensor and weapon based on
distributed management system," Proceedings of the 36th Chinese Control Conference (CCC) (2017): 3002-
3007. https://ieeexplore.ieee.org/document/65 1 2 1 47 .
1 43. “SIMBAT Weapon Effectiveness Evaluation System” [SIMBAT 武器效能评估系统 ], Anwise Global Technology,
accessed June 1 4, 202 1, https://perma.cc/PP4F-A83J .
1 44. For example, see Wang Lichao, Qiao Yongjun, and Li Yongsheng, “Optimization Algorithm for Weapon
Target Assignment Based on CE-CAPSO” [ 基于CE-CAPSO 武器目标分配优化算法 ], Fire Control and Command
and Control 1 1 (2020): https://perma.cc/43F9-8U43 .
1 45. “1 5-06 MDMP Lessons and Best Practices Handbook,” U.S. Army Combined Arms Center, March 1 2, 201 5,
https://usacac.army.mil/organizations/mccoe/call/publication/1 5-06 .
1 46. Information available upon request.
147. “4Paradigm Sage HyperCycle” [ 自动决策类机器学习平台 ], 4Paradigm, accessed July 2, 202 1, https://perma.
cc/9ANV-MG6S .
1 48. “The joint research results of Intel and 4Paradigm were selected into the VLDB International Conference to fully
optimize the performance of the online prediction system for trillion-dimensional features” [ 英特尔、第四范式
联合研究成果入选国际顶会 VLDB 全面优化万亿维特征在线预估系统性能 ], 4Paradigm, January 7 , 202 1, https://
perma.cc/83UM-E8T5 .
149. “A-Round Portfolio Feature Story: 4Paradigm,” Sequoia Capital, accessed September 202 1, https://perma.
cc/A7TJ-Y5T8; and Jane Zhang, “Chinese AI unicorn 4Paradigm raises another US$230 million, bringing
valuation to US$2 billion,” South China Morning Post, April 2, 2020, https://www.scmp.com/tech/start-
ups/article/3078082/chinese-ai-unicorn-4paradigm-raises-another-us230-million-bringing .
1 50. Information available upon request.
151. In 201 8, the DOD established one of its most well-known AI projects, Project Maven, specifically to identify
targets in drone video footage.
1 52. Information available upon request.
1 53. “The first ‘Target Recognition and Artificial Intelligence Summit Forum’ was held in Shenyang” [ 首届"目标识
别与人工智能高峰论坛 "在沈召开 ], Shenyang Institute of Automation, November 16, 2017 , https://perma.cc/
Z7W9-FHYS ; and Liu Tianci, Shi Zelin, and Liu Yunpeng, “Geometric deep learning method for intelligent
target recognition” [ 面向智能目标识别的几何深度学习方法 ], Proceedings of the National Postdoctoral Forum on
Robotics and Intelligent Manufacturing (June 27-29, 201 8): 1–39, https://perma.cc/SY5W-NAJP .
1 54. “Research Results” [ 研究成果 ], Shenyang Institute of Automation Computer Vision Group, accessed June 1 5,
202 1, https://perma.cc/BLT9-YZHP .
Center for Security and Emerging Technology671 55. Shandong Hie-Tech Co., Ltd. [ 山东航创电子科技有限公司 ], accessed June 1 5, 202 1, https://perma.cc/4TAW-
66TF .
1 56. Information available upon request.
157. CSIC and Naval Aviation University awarded these contracts to Huazhong University of Science and
Technology and Harbin Engineering University, respectively.
1 58. Relevant research papers include “Research on underwater target recognition method based on deep
learning” [ 基于深度学习的水下目标识别方法研究 ], https://perma.cc/9TBQ-NJGU ; Li Chen, Huang
Zhaoqiong, Xu Ji, Guo Xinyi, Gong Zaixiao, and Yan Yonghong, “Multi-channel underwater target
recognition using deep learning” [ 使用深度学习的多通道水下目标识别 ], https://perma.cc/JP8L-CKKS ; and
Ma Meizhen, “Study on Underwater Target Recognition Technique,” https://perma.cc/4R7V-T4VD , all
accessed July 7 , 202 1.
1 59. “Autonomous underwater robot, a system with a high degree of artificial intelligence” [ 自治水下机器人，一
种具有高度人工智能的系统 原文網址 ], KK News, October 26, 2017 , https://kknews.cc/zh-my/science/
nvzax92.html .
160. Alex Barker, “Giving Precision Munitions ‘Eyes’ and a ‘Brain,’” China Brief 2 1, no. 1 3 (July 2, 202 1): 28–34,
https://jamestown.org/program/giving-precision-munitions-eyes-and-a-brain-the-state-of-pla-research-
on-military-target-recognition/ .
161. China Shipbuilding Industry Corporation (CSIC; 中国船舶重工集团有限公司 ; 中船重工 ) merged with China
State Shipbuilding Corporation Limited (CSSC; 中国船舶工业集团有限公司 ; 中船集团 ) in November 2019.
The resulting company is known as 中国船舶集团有限公司 (中船集团 ) in Chinese and retains the English name
China State Shipbuilding Corporation Limited (CSSC). “History” [ 历史沿革 ], China State Shipbuilding
Corporation Limited, accessed July 1 3, 202 1, https://perma.cc/7RSV-4EJ9 .
162. Original CSET translation by Ben Murphy, “Outline of the National Innovation-Driven Development
Strategy” [ 中共中央 国务院印发《国家创新驱动发展战略纲要》 ], Xinhua, May 19, 2016, https://cset.
georgetown.edu/publication/outline-of-the-national-innovation-driven-development-strategy/ .
163. Ngor Luong, Zachary Arnold, and Ben Murphy, “Understanding Chinese Government Guidance Funds
An Analysis of Chinese-Language Sources,” Center for Security and Emerging Technology, March 202 1,
https://cset.georgetown.edu/publication/understanding-chinese-government-guidance-funds/ ; Ryan
Fedasiuk, Emily Weinstein, and Anna Puglisi, “China’s Foreign Technology Wish List,” Center for Security and
Emerging Technology, May 202 1, https://cset.georgetown.edu/publication/chinas-foreign-technology-
wish-list/ ; and Luong and Arnold, “China’s Artificial Intelligence Industry Alliance: Understanding China’s AI
Strategy Through Industry Alliances,” Center for Security and Emerging Technology, May 202 1, https://cset.
georgetown.edu/publication/chinas-artificial-intelligence-industry-alliance/ .
164. By contrast, most subsidiaries of state-owned enterprises and military factories were privatized in the 1990s
and early 2000s, and tend to specialize in heavy industry.
165. Sophie Mao, “What Does Registered Capital Mean?” China Law Help , June 1, 2019, https://perma.cc/
UNW6-ERTA .
166. Ian F. Fergusson and Karen M. Sutter, “U.S. Export Control Reforms and China: Issues for Congress,”
Congressional Research Service, January 1 5, 202 1, https://fas.org/sgp/crs/natsec/IF1 1627.pdf .
167. Andrew Caridas, Richard W. Oehler, and Ann M. Nagele, “BIS Tightens Controls on Exports of National
Security-Controlled Items,” Perkins Coie, April 30, 2020, https://www.perkinscoie.com/en/news-insights/
bis-tightens-controls-on-exports-of-national-security-controlled-items.html .
168. “Supplement No. 4 to Part 7 44 of the Export Administration Regulations,” also known as the “Entity List,”
U.S. Department of Commerce Bureau of Industry and Security, last updated June 202 1, https://www.bis.
doc.gov/index.php/policy-guidance/lists-of-parties-of-concern/entity-list .
169. “Non-SDN Chinese Military-Industrial Complex Companies List (NS-CMIC List),” U.S. Department of the
Treasury, June 16, 202 1, https://home.treasury.gov/policy-issues/financial-sanctions/consolidated-
sanctions-list/ns-cmic-list .
170. Jordan Brunner and Emily Weinstein, “Chinese Military-Civil Fusion and Section 1 260H: Congress
Incorporates Defense Contributors,” Lawfare, May 4, 202 1, https://www.lawfareblog.com/chinese-
military-civil-fusion-and-section-1 260h-congress-incorporates-defense-contributors .
Center for Security and Emerging Technology68171. Lindsay B. Meyer, Ashley W. Craig, Elizabeth K. Lowe, Wes S. Sudduth, and Ashley T. Luong, “Investment Ban
on Communist Chinese Military Companies Continues to Evolve,” Venable LLP, May 2 1, 202 1, https://www.
venable.com/insights/publications/202 1/05/investment-ban-on-communist-chinese-military .
172. For example, see commentary by Jason Arterburn on Hileed Solutions, July 9, 202 1, https://twitter.com/
jasonarterburn/status/1 41 3576595646910469?s=20 ; and legal trouble caused by a misspelling of Luokung
Technology, “Luokung Announces NASDAQ Withdrawal of Delisting Notice and Confirmation that Trading in
Luokung Ordinary Shares Will Continue Until May 8, 202 1,” Yahoo Lifestyle, March 1 1, 202 1, https://www.
yahoo.com/lifestyle/luokung-announces-nasdaq-withdrawal-delisting-1 33000794.html .
173. It is not clear which specific CASC research institute may have received sensor equipment from Beijing
Zhongtian Yonghua Technology Development Co., Ltd.
17 4. Beijing Zhongtian Yonghua Technology Development Co., Ltd. [ 北京中天永华科技发展有限公司 ], accessed June
24, 202 1, https://perma.cc/6THP-4XRV .
175. For examples of PLA contractors appearing to access U.S.-origin equipment or data, see Glaucus-Tech’s use
of NVIDIA GPUs (page 19), 4Paradigm’s research partnership with Intel (page 26), and Elane Inc.’s use of
Orbcomm satellite data (page 52).
176. Margarita Konaev, Husanjot Chahal, Ryan Fedasiuk, Tina Huang, and Ilya Rahkovsky, “U.S. Military
Investments in Autonomy and AI: A Strategic Assessment,” Center for Security and Emerging Technology,
October 2020, https://cset.georgetown.edu/publication/u-s-military-investments-in-autonomy-and-ai-a-
strategic-assessment/ .
177. Lyle J. Goldstein, “Watch Your Six: China Has a New Plan to Attack from Below,” The National Interest ,
May 1 8, 202 1, https://nationalinterest.org/blog/reboot/watch-your-six-china-has-new-plan-attack-
below-1 855 1 3 ; Goldstein, “Beijing Confronts Long-Standing Weakness in Anti-Submarine Warfare,” China
Brief 1 1, no. 1 4 (July 29, 201 1): 1 4-17 , https://jamestown.org/program/beijing-confronts-long-standing-
weakness-in-anti-submarine-warfare/ ; Owen R. Cote Jr., “Assessing the Undersea Balance Between the U.S.
and China,” U.S. Naval Institute, 201 1, h ttps://www.usni.org/sites/default/files/inline-files/Undersea%20
Balance%20WP1 1-1.pdf ; and Eric Heginbotham et al, “The U.S.-China Military Scorecard,” RAND
Corporation, 2017 , https://www.rand.org/content/dam/rand/pubs/research\_reports/RR300/RR392/
RAND\_RR392.pdf .
178. H.I. Sutton, “Good Wind ears: China’s Underwater Great Wall,” Covert Shores, May 28, 201 8, http://www.
hisutton.com/Cn\_Underwater\_Great\_Wall.html ; Lyle J. Goldstein, “China Is Building a "Undersea Great
Wall" To Take on America in a War,” The National Interest , October 27 , 2019, https://nationalinterest.org/
blog/buzz/china-building-undersea-great-wall-take-america-war-90601 ; and Henry Holst, “Essay: China’s
Submarine Solution for the Taiwan Strait,” July 8, 201 5, https://news.usni.org/201 5/07/08/essay-chinas-
submarine-solution-for-the-taiwan-strait .
179. Ben Kerong and Wang Bin, “Thinking on the Intelligentization of Marine Equipment and Intelligent Equipment”
[海洋装备智能化与智能化装备思考 ], Journal of Jiangsu University of Science and Technology 35, no. 2 (April
202 1): https://perma.cc/4J7T-MWD6 .
1 80. For an explanation of the “island chain” security concept, see Wilson Vorndick, “China’s Reach Has Grown:
So Should the Island Chains,” CSIS Asia Maritime Transparency Initiative, October 22, 201 8, https://amti.
csis.org/chinas-reach-grown-island-chains/ ; and Derek Grossman, “America Is Betting Big on the Second
Island Chain,” The Diplomat, September 5, 2020, https://thediplomat.com/2020/09/america-is-betting-
big-on-the-second-island-chain/ .
181. Ryan Fedasiuk, “Leviathan Wakes: China’s Growing Fleet of Autonomous Undersea Vehicles,” Center for
International Maritime Security, August 17 , 202 1, https://cimsec.org/leviathan-wakes-chinas-growing-fleet-
of-autonomous-undersea-vehicles/ .
1 82. “Haidou 1 Deep Sea Diving Record” [“ 海斗一号 ”万米深潜记 ], Xinhua, June 10, 2020, https://perma.cc/7RST-
RXSL ; and reporting by Liaoning Daily rehosted by Shenyang Institute of Automation, August 28, 2020,
https://perma.cc/E5ZZ-PXX4 ; and Yan Huang, Jianan Qiao, Jiancheng Yu, Zhenyu Wang, Zongbo Xie, and
Kai Liu, “Sea-Whale 2000: A Long-range Hybrid Autonomous Underwater Vehicle for Ocean Observation,”
OCEANS 2019 - Marseille conference proceeding, 17-20 June 2019, https://ieeexplore.ieee.org/
document/8867050 ; and “China's autonomous underwater monitoring system completes sea trial,” Xinhua,
November 22, 2020, https://perma.cc/5SKD-F3M2 .
Center for Security and Emerging Technology691 83. Konaev, Chahal, Fedasiuk, Huang, and Rahkovsky, “U.S. Military Investments in Autonomy and AI: A Strategic
Assessment.”
1 84. Jeffrey Engstrom, “Systems Confrontation and System Destruction Warfare: How the Chinese People's
Liberation Army Seeks to Wage Modern Warfare,” RAND Corporation, 201 8, https://www.rand.org/pubs/
research\_reports/RR1708.html .
185. Yang Xiaoniu, Communications Electronic Warfare: The Battlefield Network Killer of Information Warfare
[通信电子战 —信息化战争的战场网络杀手 ] (Beijing: Electronics Industry Publishing House, 201 1): 1 34. Available
online from National University of Defense Technology, accessed June 17 , 202 1, https://perma.cc/8QLJ-
8RFQ .
1 86. Information available upon request.
187. Wang Xiaobo and Zhi Tao, “‘Turbocharge’ the Joint Combat System” [ 为联合作战体系 “涡轮增压 ”], PLA Daily,
May 1 4, 2020, https://perma.cc/YM6H-NG5L .
1 88. Zhang Xiaotian and Luo Fengqi, “‘Combat Cloud’ Promotes Systems Confrontation onto the ‘Cloud’ Side”
[“战争云 ”推动体系对抗进入 “云”端], PLA Daily , January 9, 2020, https://archive.vn/j2TNL .
189. Boulanin and Verbruggen, “Mapping the Development of Autonomy in Weapon Systems,” 16.
190. Dahm, “Chinese Debates on the Military Utility of Artificial Intelligence.” For an explanation of Mosaic
Warfare, see Benjamin Jensen and John Paschkewitz, “Mosaic Warfare: Small and Scalable are Beautiful,”
War on the Rocks, December 23, 2019, https://warontherocks.com/2019/1 2/mosaic-warfare-small-and-
scalable-are-beautiful/ .
191. Xue and Yang, “Where is the fulcrum of intelligent warfare?”
192. Dahm, “Chinese Debates on the Military Utility of Artificial Intelligence.”
193. Shi and Tan, “Digital Warfare Requires Data Thinking.”
194. Shi and Tan, “Digital Warfare Requires Data Thinking.”
195. Sandra Erwin, “STRATCOM chief Hyten: ‘I will not support buying big satellites that make juicy targets,’”
Space News, November 19, 2017 , https://spacenews.com/stratcom-chief-hyten-i-will-not-support-buying-
big-satellites-that-make-juicy-targets/ .
196. Sydney J. Freedberg Jr., “Can’t Stop The Signal: Army Strips Down Network To Survive Major War,” Breaking
Defense, March 26, 201 8, https://breakingdefense.com/201 8/03/cant-stop-the-signal-army-strips-down-
network-to-survive-major-war/ .
197. Kevin McCauley, PLA System of Systems Operations: Enabling Joint Operations (Washington, DC: Jamestown
Foundation, 2017): https://jamestown.org/wp-content/uploads/2017/01/System-of-Systems-Enabling-
Joint-Operations.pdf?x35627 .
198. For example, see analysis by Justin Reed, Adam Routh, and Joe Mariani, “Information at the edge: A space
architecture for a future battle network,” Deloitte, November 16, 2020, https://www2.deloitte.com/us/en/
insights/industry/public-sector/future-space-weapons-space-architecture.html .
199. For examples of edge-deployed AI systems referenced in this study, see adaptive electronic warfare modules
for UAVs (page 1 5), satellite-based computer vision systems (page 17), predictive maintenance systems for
satellites and underwater vehicles (page 20), and multi-tasking pods for UAV-based surveillance (page 52).
200. Forthcoming CSET research will discuss the PLA’s AI hardware acquisition in greater detail: Ryan Fedasiuk,
Karson Elmgren, Ellen Lu, and William Hunt, “One in the Chamber: Managing the Chinese Military’s Access to
AI Chips,” forthcoming .
201. Song Liang and Ren Haifeng, “As New Technology Catches on Fire, the Microchip Industry Gradually Thaws”
[新技术引燃星星之火 ,芯片产业生态坚冰渐融 ], Industrial Innovation, September 20, 201 8, http://www.cycxyjzzs.
com/201 8/364.html .
202. Ngor Luong, Zachary Arnold, and Ben Murphy, “Understanding Chinese Government Guidance Funds: An
Analysis of Chinese-Language Sources,” Center for Security and Emerging Technology, March 202 1, https://
cset.georgetown.edu/wp-content/uploads/CSET-Understanding-Chinese-Government-Guidance-Funds .
pdf; James A. Lewis, “Learning the Superior Techniques of the Barbarians: China’s Pursuit of Semiconductor
Independence,” Center for Strategic and International Studies, January 2019, https://csis-website-prod.
s3.amazonaws.com/s3fs-public/publication/1901 1 5\_Lewis\_Semiconductor\_v6.pdf ; and Jordan Schneider,
“Billion Dollar Heist: How Scammers Rode China's Chip Boom to Riches,” ChinaTalk, March 30, 202 1,
https://chinatalk.substack.com/p/billion-dollar-heist-how-scammers .
Center for Security and Emerging Technology70203. Saif M. Khan, “U.S. Semiconductor Exports to China: Current Policies and Trends,” CSET, October 2020,
https://cset.georgetown.edu/publication/u-s-semiconductor-exports-to-china-current-policies-and-trends/ ;
and Khan, “Securing Semiconductor Supply Chains,” CSET, January 202 1, https://cset.georgetown.edu/
publication/securing-semiconductor-supply-chains/ .
204. Dan Strumpf, “China’s Huawei Reports 38% Revenue Drop as U.S. Sanctions Bite,” Wall Street Journal,
August 6, 202 1, https://www.wsj.com/articles/chinas-huawei-reports-38-revenue-drop-as-u-s-sanctions-
bite-1 1628237938 ; and Eamon Barrett, “The U.S. wanted to starve Huawei of chips. It’s working,” Fortune,
August 10, 2020, https://fortune.com/2020/08/10/us-huawei-ban-chips-starve-run-out-smarphones-
richard-yu/ .
205. For example, see Intel’s research partnership with, and Sequoia Capital’s investment in, 4Paradigm (page 26).
206. Lorand Laskai, “Why Blacklisting Huawei Could Backfire: The History of Chinese Indigenous Innovation,”
Foreign Affairs, June 19, 2019, https://www.foreignaffairs.com/articles/china/2019-06-19/why-
blacklisting-huawei-could-backfire ; Terry Daly and Jordan Schneider, “Will China Retaliate Against U.S.
Chip Sanctions?,” Lawfare, July 16, 202 1, https://www.lawfareblog.com/will-china-retaliate-against-us-
chip-sanctions ; and Saif Khan and Carrick Flynn, “Maintaining China’s Dependence on Democracies for
Advanced Computer Chips,” April 2020, https://www.brookings.edu/wp-content/uploads/2020/04/
FP\_20200427\_computer\_chips\_khan\_flynn.pdf .
207. Elsa Kania, “China’s Strategic Ambiguity and Shifting Approach to Lethal Autonomous Weapons Systems,”
Lawfare, April 17 , 201 8, https://www.lawfareblog.com/chinas-strategic-ambiguity-and-shifting-approach-
lethal-autonomous-weapons-systems .
208. Catherine Aiken, Rebecca Kagan, and Michael Page, “‘Cool Projects’ or ‘Expanding the Efficiency of the
Murderous American War Machine?’ AI Professionals’ Views on Working With the Department of Defense,”
Center for Security and Emerging Technology, November 2020, https://cset.georgetown.edu/publication/
cool-projects-or-expanding-the-efficiency-of-the-murderous-american-war-machine /.
209. Fedasiuk, “Chinese Perspectives on AI and Future Military Capabilities.”
2 10. Shi Hanjuan, Zhang Huijun, and Gao Qinglong, “A Turkish military drone launched an autonomous attack on
the target without receiving any instructions: ‘Kargu-2’ sounded the alarm for humans” [ 一架土耳其军用无人机
在没有接收到任何指令情况下，对目标发动自主攻击 —“卡古-2”给人类拉响警报 ], PLA Daily, June 17 , 202 1, https://
perma.cc/2D3Q-XH94 .
211 . Even outside the PLA, experts generally believe that AI will increase the operational tempo of war. See
Margarita Konaev, “With AI, We’ll See Faster Fights, but Longer Wars,” War on the Rocks, October 29, 2019,
https://warontherocks.com/2019/10/with-ai-well-see-faster-fights-but-longer-wars/ .
212 . Liu Peng, “Clarify the human-machine relationship in intelligent combat decision-making” [ 厘清智能作战决策中
的人机关系 ], PLA Daily, December 1 5, 2020, https://perma.cc/P7GK-T3A9 .
213 . Will Roper, “There's No Turning Back on AI in the Military,” Wired, October 24, 2020, https://www.wired.
com/story/opinion-theres-no-turning-back-on-ai-in-the-military/ .
2 1 4. Paul Scharre, “Debunking the AI Arms Race Theory,” Texas National Security Review 4, no. 3 (Summer 202 1):
https://tnsr.org/202 1/06/debunking-the-ai-arms-race-theory/ .
215 . In its most basic form, an ATR system attempts to match a target’s signature to that stored in a target
identification library. A worldwide survey of weapons systems from the Stockholm International Peace
Research Institute clarifies that most modern ATR applications do not feature deliberative autonomy or machine
learning, but rely on pre-programmed “expert systems” that have existed in some fashion since the 1970s. See
Vincent Boulanin and Maaike Verbruggen, “Mapping the Development of Autonomy in Weapon Systems,”
Stockholm International Peace Research Institute, November 2017: 24, https://www.sipri.org/sites/default/
files/2017-1 1/siprireport\_mapping\_the\_development\_of\_autonomy\_in\_weapon\_systems\_1 1 17\_1.pdf .
2 16. Murdick, Chou, Fedasiuk, and Weinstein, “The Public AI Research Portfolio of China’s Security Forces”; and
Barker, “Giving Precision Munitions ‘Eyes’ and a ‘Brain.’”
217. For more on the detect-to-engage sequence, see “Naval Weapons Systems,” Federation of American
Scientists, https://fas.org/man/dod-101/navy/docs/fun/part01.htm ; for Chinese conceptions of “AI
weapons,” see Elsa Kania, “‘AI weapons’ in China’s military innovation.”
2 1 8. “Let guided weapons ‘learn to think,’ China's automated target recognition research has made new progress”
[让制导武器 “学会思考 ”，中国自动目标识别研究取得新进展 ], The Paper, August 1, 2020, https://perma.
cc/2K3U-2KPW .
Center for Security and Emerging Technology71219. Zhiying Liu, Chunsi Xie, Jinjun Li, and Yu Sang, “Application of Cascade R-CNN and YOLOv3 in Missile Target
Recognition,” Journal of Image and Signal Processing 9, no. 2 (2020): 102-1 10, https://perma.cc/6JAG-
BPX7 .
220. Kania, “China’s Strategic Ambiguity and Shifting Approach to Lethal Autonomous Weapons Systems.”
221. See analysis by M. Taylor Fravel, “China’s ‘World-Class Military’ Ambitions: Origins and Implications,”
The Washington Quarterly 43, no. 1 (2020): 85-99, https://www.tandfonline.com/doi/
abs/10. 1080/0163660X.2020. 1735850?journalCode=rwaq20 ; and “Military and Security Developments
Involving the People’s Republic of China,” pg. i.
222. According to Yoram Evron, “the government has not fostered the necessary conditions for large-scale civilian
participation in military procurement.” See “China’s Military-Civil Fusion and Military Procurement.”
223. Here, too, Liu Cixin’s words bridge science fiction and reality, when he writes that “Any civilian technology can
be put to military use. Likewise, any military technology can benefit the public. As a matter of fact, practically
all of the major scientific achievements of the past century, in aerospace, nuclear weaponry, computers,
and so on, were the product of cooperation between scientists and soldiers following different paths.” See
conversation between Dr. Chen and Gao Bo in Ball Lightning , 257.
224. “The Future Has Arrived — It’s Just Not Evenly Distributed Yet,” Quote Investigator, January 24, 202 1, https://
quoteinvestigator.com/201 2/01/24/future-has-arrived/ .
225. We searched for potential false negatives by enlisting the help of the Elicit AI research assistant. After feeding
Elicit our 523 labeled intelligent equipment contracts as training data—and without specifying the fourteen
keywords used to arrive at those contracts—we asked it to review 1,000 rows of the original dataset. We then
manually confirmed that the few extra contracts “caught” by Elicit were not actually related to AI.
226. “Elicit: The AI Research Assistant”; and Byun and Stuhlmüller, “Automating reasoning about the future at
Ought.”
227. “Company Profile” [ 公司简介 ], Britronics, accessed June 1 1, 202 1, https://perma.cc/27C8-RRFR ; and
“Intelligent high-altitude image detection system” [ 智能高空气象探测系统 ], Britronics, January 1, 201 8, https://
perma.cc/7Q3B-XKBP .
228. See example fragment distribution measurement research by T. Bamford, K. Esmaeili, and A. P. Schoellig, “A
real-time analysis of rock fragmentation using UAV technology,” arXiv. 1607.04243 [cs.RO], 2016, https://
arxiv.org/ftp/arxiv/papers/1607/1607.04243.pdf .
229. Pollpeter and Allen, “The PLA As Organization v2.0,” 1 45.
230. Mustafaga and Drun, “Exploring Chinese Military Thinking on Social Media Manipulation Against Taiwan.”
231. “Core Technical Capabilities,” EverSec.
232. “What is cognitive electronic warfare?,” BAE Systems, accessed July 202 1, https://www.baesystems.com/
en-us/definition/what-is-cognitive-electronic-warfare ; and John Keller, “Air Force asks industry for artificial
intelligence (AI) cognitive electronic warfare (EW) for F-1 5 jets,” Military & Aerospace Electronics, March 1 5,
202 1, https://www.militaryaerospace.com/computers/article/1 4199230/electronic-warfare-ew-cognitive-
artificial-intelligence-ai .
233. Eli Tirk and Kieran Green, “Sustaining China’s Sovereignty Claims: The PLA’s Embrace of Unmanned Logistics,”
China Brief 2 1, no. 10 (May 2 1, 202 1): 17-22, https://jamestown.org/program/sustaining-chinas-
sovereignty-claims-the-plas-embrace-of-unmanned-logistics/ ; Liu Zhen, “China-India border dispute: PLA
looks to private innovators to give troops the edge,” South China Morning Post, November 3, 2020, https://
www.scmp.com/news/china/military/article/3 108302/chinas-military-looks-beyond-traditional-suppliers-
private ; and Rajeswari Pillai Rajagopalan and Pulkit Mohan, “PLA joint exercises in Tibet: Implications for
India,” Observer Research Foundation, February 26, 2020, https://www.orfonline.org/research/pla-joint-
exercises-in-tibet-implications-for-india-61735/ .
234. Murdick, Chou, Fedasiuk, and Weinstein, “The Public AI Research Portfolio of China’s Security Forces.”
235. For example, see patents related to UAV swarms, “Autonomous special situation handling method for
small fixed-wing unmanned aerial vehicle cluster” [ 一种小型固定翼无人机集群自主特情处置方法 ], Patent No.
CN1 10941 287A, announced March 3 1, 2020, https://perma.cc/67T7-LCVG ; and Beidou processing,
“Method for testing performance and Align data precision of Beidou board card of unmanned aerial vehicle”
[一种无人机北斗板卡性能及 Align 数据精度的测试方法 ], Patent No. CN1 1 1025342A, announced April 17 , 2020,
https://perma.cc/9RMF-MPGL .
Center for Security and Emerging Technology72236. “Company Profile” [ 企业简介 ], Beijing Laser Bofeng Information Technology Co., Ltd., accessed June 10,
202 1, http://www.bjbofeng.com/about.php .
237. “Big Data and Internet of Vehicles” [ 大数据与车联网 ], Beijing Laser Bofeng Information Technology Co.,
Ltd., May 4, 2017 , https://perma.cc/WL3D-CQ82 .
238. “Public issuance of 202 1 short-term corporate bonds (first tranche) to professional investors” [ 面向专业投
资者公开发行 2 0 21 年短期公司 债券（第一期） ], Prospectus Summary published by China North Industries
Corporation, accessed May 28, 202 1, https://perma.cc/87MA-G7HW .
239. Initiated in 1988, the Torch Program is a major Chinese government fund for technology startups. “List of
projects approved by the National Torch Program in 201 3” [201 3 年度国家火炬计划立项项目清单 ], Ministry
of Science and Technology, accessed May 202 1, https://perma.cc/6WX5-GWJC .
240. “A new generation of integrated platform for unorganized management and control” [ 新一代无组织管控一
体化平台 ], TIYOA Aviation, accessed June 7 , 202 1, https://perma.cc/WMY4-3BWG .
241. For an explanation of how Chinese military units and security bureaus task private companies with work,
see Zach Dorfman, “Tech Giants are Giving China a Vital Edge in Espionage,” Foreign Policy, December
23, 2020, https://foreignpolicy.com/2020/1 2/23/china-tech-giants-process-stolen-data-spy-
agencies/ .
242. “About Us” [ 关于], Elane Inc, accessed June 10, 202 1, https://perma.cc/Q3TE-Y2V2; and shipfinder.
com, https://web.archive.org/web/202 106102033 1 8/https://www.shipfinder.com/ .
243. “Ship Information Network Satellite AIS Data Service” [ 船讯网卫星 AIS数据服务 ], Elane Inc, accessed June
10, 202 1, https://perma.cc/SQ22-82UH .
244. “Business Introduction” [ 业务介绍 ], https://perma.cc/66K2-VD8J ; and “ShipTracker” [ 船舶跟踪系统 ],
https://perma.cc/64HS-WCD3 ; both published by Yantai Huadong Electron Technology Co., Ltd., and
accessed June 10, 202 1.
245. For examples, see Zhao Yuxin and Zhao Ting, “Survey of the intelligent seabed sediment classification
technology based on sonar images” [ 海底声呐图像智能底质分类技术研究综述 ], CAAI Transactions on
Intelligent Systems 1 5, no. 3 (2020): 587-600, https://perma.cc/R35F-4RFJ ; and Ye Xiufen, Wang
Xingmei, Zhang Zhehui, and Fang Chao, “Sonar image adaptive segmentation method based on
hierarchical mrf” [ 基于分层 mrf的声呐图像自适应分割方法] , Patent No. CN101 286229A, 2008, https://
perma.cc/64CP-ZY8B .
246. See Murdick, Chou, Fedasiuk, and Weinstein, “The Public AI Research Portfolio of China’s Security Forces,”
and Kania, “The PLA’s Unmanned Aerial Systems.”
247. “About Us” [ 关于我们 ], Beijing Chunyi Aviation Technology Co., Ltd., accessed June 9, 202 1, https://
perma.cc/Z6DV-VEVN ; see some of its products: “Six-rotor CY-X6 UAV” [ 六旋翼 CY-X6 无人机 ], Beijing
Chunyi Aviation Technology Co., Ltd., accessed June 9, 202 1, https://perma.cc/RR6N-CDSG .
248. “About Us” [ 关于我们 ], Beijing Chunyi Aviation Technology Co., Ltd., accessed June 9, 202 1, https://
perma.cc/Z6DV-VEVN .
249. Worth nearly $400,000, the contract was awarded by Unit 967 1 3, which operates DF-1 5B short-range
ballistic missiles: https://www.globalsecurity.org/wmd/world/china/plarf-orbat.htm .
250. “What Are The Benefits Of Tethered Drones?,” Elistair, December 22, 2020, https://elistair.com/tethered-
drones-benefits .
251. “54th institute successfully developed four-rotor, six-rotor and tethered drones” [54 所成功研制出四旋翼、六
旋翼和系留无人机 ], Radio Communication Technology 4 (201 8): 383, https://perma.cc/8HAZ-ARJR .
252. For example, see “Multi-rotor unmanned aerial vehicle mooring system” [ 多旋翼无人飞行器系留系统 ], Patent
No. CN103 1 44779B, announced 201 2, https://patents.google.com/patent/CN103 1 44779B/zh ; and
research by Lin Chen and Zhao Ming, “Development of Light Duty Retractable UAV Mooring Rope” [ 无人
机用轻型反复收放系留缆绳的研制 ], Abstract, Fiber Optic Cables and Their Applications 6 (2020): https://
perma.cc/KV9K-ZCZK .
253. “DG-X10 tethered drone” [DG-X10 系留无人机 ], Dagong Technology, accessed June 202 1, https://perma.
cc/CW5Q-HNRZ .
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