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July 2021 Francesca Buratti – SACT China Subject Matter Expert NOT CLASSIFIED China Newsletter n.5– July 2021 Francesca Buratti – SACT China Subject Matter Expert What is published in NATO SACT China Newsletters and Reports do not constitute the official position or policy of NATO or member governments. SACT publications on China seek to inform the community of interest and promote understanding of China's military and strategy. The views expressed by the author(s) are their own. In this newsletter: Giving Precision Munitions ‘Eyes’ and a ‘Brain’: The State of PLA Research on Military Target Recognition, The Jamestown Foundation; Becoming Strong: The New Chinese Foreign Policy, Foreign Affairs; The U.S. Military Nuclear Nightmare: China Is Building 119 ICBM Silos (Or Not?), 1945 (Security Journal); What China Wants from North Korea, The National Interest; The China-Pakistan Partnership Continues to Deepen, The Diplomat; What Xi Jinping’s Major Speech Means For Taiwan, Council on Foreign Relations; Another strong year for China’s defence companies, Institute for Strategic Studies. Giving Precision Munitions ‘Eyes’ and a ‘Brain’: The State of PLA Research on Military Target Recognition, The Jamestown Foundation, July 2 The People’s Republic of China (PRC) has identified artificial intelligence (AI) as an economic and security developmental priority. The State Council’s National AI Development Plan, released in July of 2017, calls AI “the new focus of world competition” and the 14th Five Year Plan, adopted in March 2021, promotes the “deep integration of internet, big data and artificial intelligence in industries”. Since the early 2000s, PLA doctrine has focused on enabling “informationized” warfare, a model of network-centric operations derived from the U.S. military. One of the most active fields of PLA AI research is applying machine learning to computer vision—teaching computers how to interpret the visual world. PLA officers and academic researchers alike are bullish on deep learning’s value for military applications. According to researchers at the PLA Army Academy of Armored Forces, deep learning offers advantages over traditional machine learning because it avoids the need for manual extraction of target features in the training dataset, an onerous chore when accurate programs demand tens of thousands of image sample. Image recognition for military applications requires a higher degree of accuracy for target detection than civilian applications of image processing, but early research is promising. While the deep learning tests described in the literature can correctly identify military equipment more than 85 percent of the time, PLA authors stress the need for further development to improve accuracy. PLA research on deep learning applications for image recognition broadly fall into two categories: object detection and classification. Object recognition algorithms can detect things that exist in an image but cannot properly classify them without the aid of another trained neural network. PLA researchers must design their own sets of training data to develop object classifiers and correctly categorize objects like tanks and fighter aircraft in both live video and still imagery. Finally, some PLA researchers are attempting to classify objects by “threat.” Another NOT CLASSIFIED Page 1 of 9 issue is the PLA’s reliance on outside sources for image recognition algorithms. Moreover, the challenges reported in gathering sufficient samples for image classification underscore the need to consider how military systems imagery in the public domain will assist the PLA. While the PLA will undoubtedly train neural networks off its own classified imagery, commercial satellite and UAV imagery will likely assist this effort, no matter whether it is first acquired by the PRC’s military or private sector. Algorithms can become accurate by training off civilian imagery, then be turned over to the PLA for further development. The state of public access literature suggests that significant obstacles remain before the PLA will be capable of using AI as a guidance system for PGMs. But the direction of research is disturbing given that tests already indicate a high degree of accuracy, which is enough to aid imagery analysts and ensure continued PLA attempts at weaponization. In the near future, an emerging threat is the PLA’s potential to field “fire and forget” PGMs that can independently assess targets, especially if linked with the ability to loiter until targets become available. This type of stand-off munition would enhance the PLA’s already formidable combat capabilities in the Western Pacific. Key Points: This article examines writings by PLA-affiliated authors and private sector researchers leveraging open-source research—much of which is developed in the U.S.—to improve China’s automatic military target recognition capabilities. Sources were drawn from the Chinese National Knowledge Infrastructure (CNKI). As such, it is a valuable resource for getting know how on China’s “whole of government” approach to Artificial Intelligence (AI), which has important ramifications for the People’s Liberation Army (PLA). It is in NATO’s interest to understand how China’s “military-civil fusion” strategy is intended to facilitate transfers of technology and expertise between the commercial and military sectors, including in the field of AI. Moreover, it is stressed that the AI’s use in the military is far different in China than in the United States. The PLA appears to adopt an approach of rapidly “failing forward” in attempts to exploit AI regardless of its maturity, in part motivated by a perception that the U.S. military still retains a large technological lead over it. Further, the conclusion of the analysis is particularly worth mentioning. According to the authors, the PLA sees significant military applications for AI and is actively developing “intelligentized” weapons designed to detect and attack U.S. aircraft, ships, and armored vehicles. It is especially interesting for NATO, to note that while the article focuses on the PLA’s development of computer vision, Chinese researchers are also employing deep learning in adjacent fields such as in-flight course correction for cruise missiles. Further, the PLA’s progress in adapting deep learning for image recognition is an example of the need for U.S. policymakers and developers alike to consider how open-source technology can be utilized by opponents. Quoting the expert: “reliance upon open architecture is a fundamental tenet of the American innovation ecosystem and should not be restricted to compete with the PRC. Rather, the defense community should see this as an advantage. Knowledge of which algorithms the PLA will rely upon allows the United States to determine possible weaknesses, exploit opportunities for data poisoning, and train against these algorithms in exercises.” Becoming Strong: The New Chinese Foreign Policy, Foreign Affairs, July/August 2021 The article reviews the new Chinese foreign policy, whose main traits will likely emerge in the aftermath of the pandemic. The author points out a paradigm shift underway in Beijing: China believes that its rise to great-power status entitles it to a new role in world affairs—one that cannot be reconciled with unquestioned U.S. dominance. Biden’s attempts at isolating China diplomatically are seen a serious threat from President Xi who is working on multiple fronts to make the country less vulnerable to U.S. aggression and pressure. Beijing’s newfound confidence does not mean it will challenge Washington in every single domain. China rejects U.S. leadership on some issues, but as a developing country, it will limit competition to areas in which it feels it has an advantage, such as the fight against NOT CLASSIFIED Page 2 of 9 COVID-19, poverty reduction, trade, international infrastructure and development, digital payment systems, and 5G technologies, among others. Beijing still hopes it can confine tensions with Washington to the economic realm and avoid an escalation to military clashes. Yet the risk of a conflict over Taiwan, especially, is growing. This is not to suggest that cooperation with Washington is out of the question. Beijing has expressed its willingness to play an active role in reforming global governance regimes, in aiding the global economy’s post-pandemic recovery, and in tackling transnational challenges in concert with Washington. Across the board, however, a post-pandemic China will make its voice heard with greater determination than before and will push back forcefully against any attempts to contain it. The article argues that the China-US competition will be played out on novel battlegrounds, chief among them cyberspace. As the digital sphere takes over more and more of people’s lives, cybersecurity will become more important than territorial security. Meanwhile, international cooperation will increasingly take the form of issue- specific coalitions instead of truly international (or even regional) institutions. China and the United States will build rival teams, with other countries deciding which to join on a case-by-case basis, depending on which arrangement best serves their national interests. Most governments will welcome this trend, having already adopted hedging strategies to avoid picking sides between the two powers. The limits of China’s global reach are also outlined. Despite being a major power, China also thinks of itself as a developing country. This dual identity will color all aspects of China’s post-pandemic foreign policy. As a developing country, China still lacks the resources required of a true world leader, with globe-spanning responsibilities, especially in the military realm. As a great power, however, it will not follow the United States’ lead, and on some issues, competition with Washington will be inevitable: on the one hand, China is anxious not to frame relations with the West as a new Cold War; on the other hand, China will try to shape an ideological environment favorable to its rise, pushing back against the notion that Western political values have universal appeal and validity. China’s economic policies are shifting, too, impelled both by the pandemic, which revealed the vulnerability of global supply chains, and by U.S.
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