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#Information Support Force, #intelligent warfare, #intellligentization, Chinese Artificial Intelligence, Chinese Military Artificial Intelligence Weaponizatio, Chinese military cognitive warfare, Chinese Military Informatization, 中國解放軍敘事戰爭, 以認知為中心的戰爭：應對複雜戰爭的作戰概念, 認知域戰

AI integrated into Chinese Armed Forces: PLA Strategic Support Force Developed Artificial Intelligence Innovation Capabilities

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人工智慧融入中國軍隊：解放軍戰略支援部隊發展人工智慧創新能力

現代英語：

Artificial Intelligence ( AI ) technology has advanced by leaps and bounds in recent years . All major powers have developed advanced AI capabilities and attempted to effectively integrate AI into their armed forces. Beijing has also released an ambitious plan to make China a global leader in advanced artificial intelligence by 2030. Chinese Communist Party leader Xi Jinping also reiterated at the 20th Party Congress that China should attach equal importance to the development of artificial intelligence and “intelligent warfare.”

Although China’s strategic goals in the field of artificial intelligence are clear, how it will integrate artificial intelligence into the People’s Liberation Army remains opaque. But at least the recently established PLA Strategic Support Force (SSF) provides some clues: the organization has been given an innovative mission and is responsible for integrating multiple “strategic functions.” To effectively understand the Strategic Support Force, we need to explore whether it will have a “game-changing” impact in future conflicts, where mastery of the information domain and effective integration of artificial intelligence may determine victory or defeat.

The PLA’s “Joint Operationality”: Strategic Support Force

The PLA underwent major reforms in 2015, partly motivated by the need to shift the PLA’s force focus from land territorial defense to extended force projection to ensure China’s strategic interests in areas such as space, cyber warfare and the far seas. A key element of these reforms is the creation of the Strategic Support Force, which concentrates tasks in these broad areas.

The Strategic Support Force (SSF) is tasked with integrating many “strategic” functions and capabilities previously dispersed across the PLA, including space, cyber, information, and psychological warfare. Today, the Strategic Support Force consists of two departments covering these functions: the Space Systems Department, which is responsible for all space-related missions; and the Cyber ​​Systems Department, which undertakes the PLA’s broad information warfare activities.

The ultimate goal of the Strategic Support Force is to gain information advantage, achieve decision-making advantage, and thus achieve ultimate victory. Analysts recently concluded that its mission is likely to support the pursuit of information superiority and can be divided into two categories: providing strategic information superiority and support capabilities to the PLA’s top leadership, including counter-space operations and offensive cyber warfare, and providing information support services to theater military commands.

The Strategic Support Force appears to be designed to enhance the PLA’s “jointness,” or its ability to conduct joint operations. Historically, the PLA has faced challenges integrating joint operations due to the difficulty in innovating and implementing new command and control and intelligence, surveillance, and reconnaissance capabilities. Because the information support provided by the Strategic Support Force is likely to include “intelligence, surveillance and reconnaissance to achieve operational and strategic objectives”, some experts believe that the Strategic Support Force plays a key role in improving the overall joint combat effectiveness of the PLA.

The SSF also appears to have several mechanisms in place to develop or acquire technology in order to carry out its mission effectively. While the SSF is not the only agency within the PLA with this function, the SSF is responsible for more AI-related equipment contracts than any other service in the PLA. For example, the Strategic Support Force has made significant investments in artificial intelligence innovation, leveraging citizen partnerships to acquire new technologies such as intelligence, surveillance and reconnaissance, autonomous vehicles, information and electronic warfare, simulation and training, and target identification.

On December 31, 2015, the founding ceremony of the leadership bodies of the People's Liberation Army (PLA) Ground Force, the PLA Rocket Force, and the PLA Strategic Support Force was grandly held at the Bayi Building in Beijing. Xi Jinping awarded military flags to the Army, Rocket Force and Strategic Support Force and delivered a speech. Photo/Xinhua News Agency
On December 31, 2015, the founding ceremony of the leadership bodies of the People’s Liberation Army (PLA) Ground Force, the PLA Rocket Force, and the PLA Strategic Support Force was grandly held at the Bayi Building in Beijing. Xi Jinping awarded military flags to the Army, Rocket Force and Strategic Support Force and delivered a speech. Photo/Xinhua News Agency

PLA Artificial Intelligence Innovation

The U.S. National Security Council pointed out in its 2022 final report that “while artificial intelligence will be widely used in all fields, the large amount of data associated with space, cyber, and information operations makes these application cases particularly suitable for priority integration of AI technology in war simulations, exercises, and experiments.” This is exactly the area where the Strategic Support Force operates.

Many of the Strategic Support Force’s functions involve processing a variety of diverse, large volumes of rapidly changing information flows at speeds exceeding human capacity, making them excellent candidates for the application of artificial intelligence. For example, AI can help create and maintain situational awareness and can be used for prediction by collecting, integrating and analyzing information. AI can also be used to analyze the consequences and planning of potential actions and conduct war simulations.

However, actual command decisions are made by the theater military command or the Joint Chiefs of Staff. At the same time, the development of AI for decision-support applications may be the responsibility of other PLA components, such as the National University of Defense Technology and the Academy of Military Sciences, rather than the Strategic Support Force. Nevertheless, in providing information support to these decision makers, the Strategic Support Force is likely to play an important role in human-machine interface interaction with such artificial intelligence systems, thereby effectively supporting decision making.

At the same time, of the twelve major military applications currently being developed by the PLA, at least five are closely related to the missions of the Strategic Support Force, namely smart satellites, intelligence, surveillance and reconnaissance software, automated cyber attack software, cognitive electronic software, and possible automated vehicles, including:

  1. Space Battle
  2. Cyber ​​Warfare
  3. Electronic warfare
Schematic diagram. The picture shows facial recognition technology demonstrated at the "Security China" held in Beijing, China in 2018. Photo/Associated Press

While many applications of AI within the SSU mission area can be identified today, the most important long-term impacts may be difficult to predict. Furthermore, the AI ​​plans proposed in China’s national white paper are not consistent with actual innovation progress.

In fact, most of China’s major investments in AI appear to be business-related and have little to do with military missions. Some assessments suggest that previous estimates of China’s current AI capabilities may be overstated. This means that it is not possible to immediately see the effective integration of artificial intelligence into the PLA’s mission areas, but the Strategic Support Force does have the mission of gaining information advantages to achieve decision-making advantages and ultimate victory.

As for artificial intelligence, it means that the Strategic Support Force must integrate artificial intelligence applications to make up for the PLA’s weaknesses in ensuring and utilizing information advantages. But this does not mean that the Strategic Support Force will become the focus of the PLA’s overall artificial intelligence innovation.

While many of the SSF’s missions are amenable to AI and there may be synergies between missions for applying AI, it is unclear which applications the SSF will use, whether these synergies are feasible, and whether the SSF has the capability to execute them. There will inevitably be a certain degree of prioritization in innovation for specific AI applications that are differentiated across different tasks.

China is determined to become a global leader in artificial intelligence and apply its technology to military missions to suppress U.S. advantages in the Indo-Pacific region. In many ways, the SSF has the advantages to achieve these goals, including a relaxed policy environment that promotes innovation, the SSF’s clear innovation responsibilities, and senior leadership support for “smartness.” The SSF also builds partnerships with China’s high-tech commercial sector and academia. These efforts are consistent with China’s military-civil fusion agenda, which aims to overcome barriers that prevent the People’s Liberation Army from acquiring resources from the commercial sector.

Schematic diagram. Photo/Associated Press
Schematic diagram. Photo/Associated Press

Obstacles to the Strategic Support Force’s Implementation of the PLA’s Innovation Plan

However, the Strategic Support Force also faces huge obstacles in implementing the People’s Liberation Army’s innovation-driven plan. The SSF and the PLA as a whole will face several challenges in AI applications, including attracting and retaining high-quality high-tech talent and mainland China’s inability to domestically develop and manufacture advanced logic and memory chips that are critical to developing cutting-edge AI—a clear weakness now that the United States has disrupted its supply of high-end semiconductors. In addition, research institutions in the United States and other Western countries are now increasingly cautious about collaborating with Chinese researchers in fields such as artificial intelligence, which have significant military potential.

The PLA’s limited combat experience has led to a lack of relevant “real and empirical” data, which may hinder the development of decision-making support artificial intelligence systems. More importantly, unless the PLA focuses on understandable, trustworthy AI, the use of AI systems with opaque operations, uncertain effective areas, and uncertain failure modes could cause serious damage.

For the national army , although there may be some limitations and uncertainties in the military application of artificial intelligence, with the continuous development and maturity of artificial intelligence technology, its application potential in the military field is still huge. As technology advances, we can expect to see more artificial intelligence systems introduced into military applications to improve operational efficiency and combat effectiveness.

However, to ensure that artificial intelligence technology can be robustly applied to military missions, it is necessary to strengthen technology research and development and testing, ensure the safety and reliability of the system, and rationally plan and manage the use of artificial intelligence technology. Only in this way can we better utilize artificial intelligence technology to enhance the information-based combat effectiveness of our military and achieve stronger and more robust combat capabilities.

現代國語：

近年來人工智能（Artificial Intelligence, AI）技術突飛猛進，所有主要大國都發展先進的AI能力，並試圖將AI有效地融入武裝力量。北京亦發佈雄心勃勃之計畫，要求2030年將中國建設成為全球先進人工智能強國。中共領導人習近平亦於第20次黨代表大會再次強調，中國應於人工智慧領域發展與「智慧戰爭」 並重。

雖然中國大陸於人工智能領域的戰略目標明確，但其如何將人工智能融入解放軍仍然是不透明的。但至少，最近成立的解放軍戰略支援部隊（Strategic Support Force, SSF）提供了一些線索：該組織賦予了創新任務，負責整合多種「戰略功能」。為了有效理解戰略支援部隊，探究它是否將在未來衝突中產生「改變遊戲規則」的影響，其中掌握資訊領域和有效整合人工智能可能決定勝負。

解放軍的「聯合作戰性」：戰略支援部隊

2015年解放軍軍隊進行重大改革，部分動機是將解放軍武力重點從陸地領土防禦轉向延伸武力投射，以確保中國在太空、網絡戰和遠海等領域的戰略利益。這些改革的主要關鍵要素即為成立戰略支援部隊，集中了這些廣泛領域中的任務。

戰略支援部隊（SSF）的任務是整合先前分散在解放軍各部隊的許多「戰略」職能和能力，包括太空、網絡、資訊與心理戰等。如今，戰略支援部隊由兩個部門組成，涵蓋了這些職能：太空系統部門，負責所有與太空有關的任務；網路系統部門，承擔解放軍廣義的資訊戰活動。

戰略支援部隊最終目標是獲得資訊優勢，實現決策優勢，從而取得最終勝利。分析家最近得出結論，其任務很可能是支援追求資訊優勢，並可分為兩類：為解放軍最高層領導提供戰略資訊優勢和支援能力，包括反太空行動和攻擊性網絡戰，以及向戰區軍事指揮部提供資訊支援服務。

戰略支援部隊設計似乎旨在提升解放軍的「聯合作戰性」，或其進行聯合作戰的能力。歷史上，因新的指揮掌控與情報、監視和偵察能力的創新和實施方面實存在困難性，解放軍在整合聯合作戰方面面臨挑戰。因戰略支援部隊提供的資訊支援很可能包含「情報、監視和偵察，以實現作戰和戰略目標」，一些專家認為戰略支援部隊在提高解放軍整體聯合作戰性方面起到了關鍵作用。

為了有效遂行任務，戰略支援部隊似乎還擁有若干機制來開發或取得技術。雖然戰略支援部隊並非解放軍內唯一承擔此功能的機構，戰略支援部隊負責與人工智能相關的裝備合約比解放軍的任何一個服務都要多。例如戰略支援部隊在人工智慧創新方面進行了大量投資，利用公民合作夥伴關係來獲取情報、監視和偵察、自主車輛、資訊與電子戰、模擬與訓練、以及目標識別等新技術。

2015年12月31日，中國人民解放軍陸軍領導機構、中國人民解放軍火箭軍、中國人民解放軍戰略支援部隊成立大會在北京八一大樓隆重舉行。習近平授予陸軍、火箭軍、戰略支援部隊軍旗並致訓詞。 圖／新華社
2015年12月31日，中國人民解放軍陸軍領導機構、中國人民解放軍火箭軍、中國人民解放軍戰略支援部隊成立大會在北京八一大樓隆重舉行。習近平授予陸軍、火箭軍、戰略支援部隊軍旗並致訓詞。 圖／新華社

解放軍人工智慧創新

美國國家安全委員會於2022年最終報告中指出，「雖然人工智能將在所有領域普遍應用，但與空間、網絡和信息作戰領域相關的大數據量，使得這些領域的應用案例特別適合優先整合AI技術應用於戰爭模擬、演習和實驗。」而這正是戰略支援部隊所運營的領域。

戰略支援部隊許多功能涉及處理各種多樣、大量和快速變化之信息流，處理速度超過人類容量，都是應用人工智能的絕佳候選領域。例如，人工智慧可以幫助創建和維持態勢感知，透過收集、整合和分析信息，也可用於預測；另人工智能還可於分析潛在行動的後果與規劃、進行戰爭模擬。

然而實際指揮決策則由戰區軍事指揮部或聯合參謀部負責。同時，用於決策支援應用的人工智慧的開發可能由其他解放軍組成部分，如中國國防科技大學和軍事科學院，並非由戰略支援部隊負責。儘管如此，在為這些決策者提供資訊支援方面，戰略支援部隊很可能在與此類人工智慧係統進行人機界面互動發揮重要作用，並進而有效支援決策制定。

與此同時，解放軍刻正開發的十二個主要軍事應用中，至少五個與戰略支援部隊的任務密切相關，分別是智慧衛星、情報、監視和偵察軟件、自動化網絡攻擊軟件、認知電子軟件以及可能的自動化車輛，包含：

太空戰
對於太空戰，解放軍可能探索應用人工智能，內含用於管理大規模衛星；與在地球觀測資料集分析（處理和目標識別衛星圖像）；認知無線電技術，一種「智慧」無線電技術，旨在藉由自主切換頻道來避免干擾和擁擠，從而使空間通訊更加高效；自主衛星操作，以彌補有限的帶寬和延遲與減輕地面衛星操作員的工作負荷。

網路戰
網路戰，即為網路安全和電子戰都依賴於即時處理大量資料以識別威脅並更新防禦措施。如藉由人工智能引導對敵對網絡的指引，亦可同時支援技術偵察和網絡攻擊。此任務處於戰略支援部隊的職責範圍內，此部隊的創立旨在鞏固解放軍在網路安全和電子戰方面的聯繫。自動化還可以提高網絡防禦的速度和規模，減輕先前解放軍面臨的限制。

電子戰
人工智能亦可協助電子戰，增強電子戰系統的自主性。如人工智能可以識別和分類雷達或通訊系統的信號，檢測和分類幹擾器，提高幹擾信號的到達方向估計，開發高效的抗干擾協議與即時更新防禦措施（認知電子戰）。


示意圖。圖為2018年中國北京舉行的「安全中國」（Security China）上展示的人臉辨識技術。 圖／美聯社

雖然目前可確定戰略支援單位任務範圍內許多人工智能的應用，但最重要的長期影響可能難以預測。此外，中共國家白皮書中提出的人工智慧計劃並非與實際的創新進展一致。

實際上，中共於人工智能大部分重要投資似乎與商業相關，與軍事任務關係不大。一些評估先前關於中國當前人工智能能力的估計可能過於誇大。意謂不可能立即看到人工智能有效整合於解放軍的任務領域，但戰略支援部隊確實賦予提取信息優勢以實現決策優勢和最終勝利的任務。

至於人工智能方面，意謂戰略支援部隊必然整合人工智能應用，以彌補解放軍在確保和利用資訊優勢方面之弱點。但這不意謂戰略支援部隊將成為解放軍整體人工智慧創新的焦點。

儘管戰略支援部隊的許多任務均適用於人工智能，而且在任務之間可能存在應用人工智能的協同效應，但目前尚不清楚戰略支援部隊將使用哪些應用，這些協同效應是否具有可行性，與戰略支援部隊是否有能力執行。對於在不同任務中具有差異的特定人工智慧應用，創新中必然會存在一定程度的優先考慮。

中國決心成為全球人工智慧領域領導者，並將其技術應用於軍事任務，以壓制美國在印太地區的優勢。在許多方面，戰略支援部隊都具備説明實現這些目標的優勢，包括寬鬆的政策環境促進創新、戰略支援部隊明確的創新職責以及高層領導對「智慧化」的支持。戰略支援部隊也與中國的高科技商業部門和學術界建立合作關係。這些努力與中國的軍民融合協議一致，旨在克服妨礙解決中國人民解放軍從商業部門獲取資源屏障。

戰略支援部隊執行解放軍創新計畫的障礙

不過戰略支援部隊在執行中國人民解放軍創新驅動計畫時，亦面臨巨大障礙。戰略支援部隊和解放軍總體上將在人工智能應用面臨一些挑戰，包括吸引和留住高素質高科技人才，與中國大陸無法於國內研發和製造對開發尖端人工智能至關重要的先進邏輯和存儲芯片——這是目前美國已中斷對高端半導體的供應所導致的明顯弱點。此外，美國和其他西方國家的研究機構現在對與具有重大軍事潛力的人工智能等領域的中國研究人員進行合作越來越謹慎。

根據解放軍有限的戰鬥經驗，導致了相關「實踐實證」資料匱乏，可能妨礙發展決策支援人工智慧系統。更重要的是，除非解放軍專注於可理解、值得信賴的人工智能，否則使用具有不透明操作、不確定有效區域和不確定故障模式的人工智能係統可能會造成嚴重損害。

對於國軍而言，儘管人工智能於軍事應用可能存在一些限制和不確定性，但隨著人工智能技術的不斷發展和成熟，其在軍事領域的應用潛力仍然巨大。隨著技術的進步，我們有望看到更多人工智慧係統被引入軍用應用中，提高作戰效率和戰鬥力。

然而，要確保人工智能技術能夠穩健地應用於軍事任務中，需要加強技術研發和測試，確保系統的安全性和可靠性，以及合理規劃和管理人工智能技術的使用。只有這樣，我們才能更好地利用人工智慧技術來提升國軍資訊化戰鬥力，並實現更強大、更穩健的作戰能力。

中國原創軍事資源：https://opinion.udn.com/opinion/story/123525/7360758884

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Uncertainty – Fog of War and the Way to Win in Modern Warfare for China’s Military

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不確定性－戰爭迷霧與中國軍隊在現代戰爭中的勝利之道

現代英語：

Wars in different eras have different characteristics, and the “fog of war” that accompanies them is constantly changing. Often when people feel that they have basically seen the way to win through multi-faceted exploration, the next war presents new uncertainties. Local wars such as the Syrian War and the India-Azerbaijan conflict have demonstrated the multifaceted and complex nature of modern warfare from different perspectives. It can be seen that although traditional firepower warfare is still on the stage, the characteristics of intelligence have already emerged; although the combat type is still an offensive and defensive struggle, the combat guidance, environmental conditions, and specific methods of play have undergone profound changes. Wars are accelerating their evolution towards intelligence. The battlefield space has expanded from land, sea, air, space, electricity, and the Internet to space, polar regions, deep sea, and cognitive confrontations. The game competition has changed from military confrontation to multi-dimensional competitions such as politics, economy, science and technology, and public opinion. The participating forces have developed from the two warring parties to global attention and multi-dimensional intervention. Information intelligence has moved from auxiliary support to comprehensive dominance, full penetration, and full coverage. The combat unit has evolved from scale optimization to small, micro, and sophisticated, and the form is scattered and capable. Intelligence and hybrid have become basic trends. In the face of evolving wars and new uncertainties, we need to be sensitive to change and respond proactively, accumulate momentum and forge ahead in the midst of change, so as to achieve leadership and surpass others and seize the opportunity to win.

Enhance the hybrid nature of war based on the “pan-variability”. War is the continuation of politics and has never been a simple military confrontation. In the era of intelligence, visible struggles and invisible struggles coexist, battlefields with gunpowder smoke and silent battles coexist, and gray areas, hybrid warfare, and marginal conflicts coexist. In the face of fierce and complex competitive game situations, it is necessary to accelerate the construction of a hybrid warfare system with military as the cornerstone. First, enrich strategic options. Closely follow the characteristics of the times, strengthen the exploration of the characteristics and laws of non-military confrontation and the construction of power means, implement relevant preparations, and form comprehensive advantages. Secondly, enhance invisible strength. Attach importance to geopolitical, cultural, psychological and other aspects of research, and form an effective discourse system through think tank exchanges, academic promotion, cultural integration, legal construction, media propaganda and other means to influence the other party’s cognition in a silent way. Thirdly, unite the forces of peace. Take the construction of a united front in the new era as an important means of hybrid confrontation, unite all forces that can be united, and enhance international influence and appeal.

Enhance the flexibility of tactics based on the “smart change” of the battlefield. Looking at recent local wars and conflicts, due to factors such as the regional dimension and the strength of both sides, the traces of traditional warfare are still relatively obvious, but intelligent and unmanned warfare has irreversibly come to the fore. It can be foreseen that comprehensive intelligent warfare is not far away, the extension range of weapons and equipment will be farther and wider, the combat perspectives of the opposing sides will be larger and wider, and the degree of hinge fusion between the physical domain, network domain, and cognitive domain will be deeper. The battlefield with deep “smart change” calls for concepts and tactics that are adapted to it. We should accelerate the promotion of intelligent thinking, intelligent technology, and intelligent network aggregation and empowerment to form a flexible closed link with fast perception, fast decision-making, fast judgment, fast action, and fast feedback, based on “OODA” and the kill chain to beat the slow with the fast and change with change. Relying on intelligent computing power and intelligent algorithms, we design wars in advance, build various models, and innovate tactics and training methods in peacetime. In wartime, we analyze the battle situation in real time, keenly seize opportunities, and make precise decisions and actions. We use “military + technology”, “theory + experiment”, and “algorithm + tactics” to integrate the art of strategy with intelligent technology to achieve a combination of the strange and the orthodox, take the lead in rapid changes, and win by intelligence.

Enhance the plasticity of forces based on the “micro-change” of units. One of the important characteristics of modern warfare is that large systems support elite combat, and combat units are becoming increasingly miniaturized, integrated, and modular. We must focus on the combat unit, the end of combat effectiveness, and forge a “sharp knife” and “sharp blade” that is small, fine, micro, and strong to adapt to intelligent warfare. On the one hand, strengthen its ability to integrate into the system and connect all parties, rely on ubiquitous access to information networks, and achieve decentralized combat and energy concentration through flexible matching and rapid reorganization; on the other hand, strengthen its independent decision-making and improvisation capabilities, improve robustness and self-recovery, and be able to survive, respond to emergencies, and fight in extreme situations. It is possible to explore the formation of a “micro-unit” concept force, implement a flexible organization, do not fix the number of personnel, and do not restrict the field. Advanced combat theories, new combat formations, and new weapons and equipment can be tested and verified in advance, so as to explore ways to achieve cloud combat, cloud joint, cloud energy gathering, and self-combination at the end of the strike chain.

Enhance strategic bottom line based on deterrence “evolution”. Deterrence has a long history like war. With the in-depth application of intelligent technology and weapons and equipment, the connotation and extension, force means, form and effect of deterrence are changing. Although traditional nuclear deterrence is still the cornerstone of bottom line, new deterrence capabilities have been quietly formed, requiring higher determination, strength, wisdom, and strategy. Focusing on the role of deterrence in blocking the enemy invisibly in peacetime, controlling the situation at the key in times of crisis, and winning the final victory in wartime, we should focus on strengthening the strong and making up for the weak, opening up new areas, and long-term strategy to maximize the strategic value of deterrence. First, we should give equal importance to conventional and unconventional, accelerate the development of new weapons and new forces, and achieve the predetermined deterrence intention through actual combat training and actual combat deployment, supplemented by the expression and transmission of strategic will. Secondly, we should continue to study new combat concepts and new combat theories, and promote the transformation of theories from “soft” to “hard” through academic exchanges, think tank collisions, and multi-track and multi-layer confrontations, and transform them into real deterrence. Thirdly, accelerate the transformation of science and technology into the military field, increase research efforts in cloud computing, blockchain, quantum technology, etc., and strive to form a potential deterrent to opponents.

現代國語：

郭呈淵 趙中其

不同時代的戰爭有不同的特點，而與之相伴的「戰爭迷霧」也在不斷變幻。往往當人們透過多方探索、感覺已經基本看清其中的勝利之道時，下一場戰爭又呈現出新的不確定性。敘利亞戰爭、亞阿衝突等局部戰爭，從不同側面展示了現代戰爭的多面性、複雜性。可以看到，傳統火力戰雖仍在舞台之中，但智慧化特徵已然顯現；作戰類型雖仍為攻防爭奪，但作戰指導、環境條件、具體打法已深刻變化。戰爭正加速向智慧化演進，戰場空間由陸、海、空、天、電、網向太空、極地、深海、認知等全域對抗拓展，博弈比拼由軍事對決向政治、經濟、科技、輿論等多維較量轉變，參與力量由交戰雙向全球關注、多元介入方向發展，資訊智能由輔助支撐向全面主導、全程貫穿、全域覆蓋邁進，作戰單元由規模集優向小微精尖、形散能聚演化，智能、混合成為基本趨勢。面對嬗變中的戰爭和新的不確定性，需要敏銳知變、積極應變，於變中蓄勢、變中進取，實現領先超越、搶得制勝先機。

基於戰爭「泛變」增強超限混合性。戰爭是政治的延續，從來不是單純的軍事對抗。智能化時代，看得見的爭鬥和看不見的鬥爭並存，有硝煙的戰場和無聲息的爭戰同在，灰色地帶、混合戰爭、邊緣衝突相伴而生。面對激烈複雜的競爭賽局態勢，需要加速建構以軍事為基石的混合戰爭體系。首先，豐富戰略選項。緊貼時代特點，加強非軍事抗衡特點規律探究和力量手段建設，實化相關準備，形成綜合優勢。其次，提升隱形實力。重視做好地緣、文化、心理等面向研究，透過智庫交流、學術推廣、文化交融、法律建構、媒介宣傳等方式，形成有效話語體系，在潤物無聲中影響對方認知。再次，團結和平力量。把建構新時代統一戰線作為混合對抗的重要手段，團結一切可以團結的力量，增強國際影響力和感召力。

基於戰場「智變」增強戰法彈性。縱觀近幾場局部戰爭與衝突，囿於地域維度、雙方實力等因素，傳統作戰痕跡仍較為明顯，但智能化、無人化已不可逆轉地走向前台。可以預見，全面智慧化戰爭並不遙遠，武器裝備的延伸範圍將更遠更廣，對抗雙方的交戰視角將更大更寬，物理域、網絡域、認知域鉸鏈融合程度更深。深度「智變」的戰場，呼喚與之相適應的理念、戰法，應加快推進智能化思維、智能化技術、智能化網絡聚合增能，形成快感知、快決策、快判斷、快行動、快反饋的彈性閉合鏈路，基於「OODA」和殺傷鏈以快打慢、以變制變。依托智能算力、智能演算法，平時超前設計戰爭、建構多種模型、創新戰法訓法，戰時即時研判戰情、敏銳捕捉戰機、精準決策行動，運用“軍事+科技”“理論+試驗” “演算法+打法”，融合謀略藝術與智慧技術，實現奇正結合、搶先快變、以智制勝。

基於單元「微變」增強力量可塑性。大體系支撐精兵作戰是現代戰爭的重要特色之一，作戰單元變得日益微型化、整合化、模組化。要扭住作戰單元這一戰鬥力末端，鍛造適應智慧化戰爭、小而精、微而強的「尖刀」「利刃」。一方面，強化其融入體系、連結各方的能力，依托泛在接取的資訊網絡，透過靈活搭配、快速重組，實現分散作戰、集效聚能；另一方面，強化其自主決策、臨機應變能力，提高魯棒性和自恢復性，在極端情況下能生存、能應急、能作戰。可探索組成「微單元」概念部隊，實行彈性編制，不固定員額、不限制領域，超前試驗論證先進作戰理論、新式作戰編組、新型武器裝備，為實現打擊鏈條末端雲作戰、雲聯合、雲聚能、自組合運用摸索路子。

基於威懾「衍變」增強戰略保底性。威懾與戰爭一樣歷史悠久。隨著智慧化技術和武器裝備的深入運用，威懾的內涵外延、力量手段、形式效果等都在改變。雖然傳統的核威懾仍是保底基石，但新的威懾能力已在悄悄形成，對決心、實力、智慧、謀略等要求更高。著眼發揮威懾平時阻敵於無形、危時控勢於關鍵、戰時決勝於最後的作用，應注重固強補弱、開拓新域、長期經略，實現威懾戰略價值最大化。首先，堅持常規與非常規並重，加速發展新型武器、新質力量，透過實戰化演訓、實戰化部署，輔以謀略意志表達傳遞，達成預定威懾企圖。其次，持續研究新作戰概念、新作戰理論，透過學術交流、智庫碰撞和多軌多層對抗，推動理論由“軟”變“硬”，轉化為現實威懾力。再次，加速科技向軍事領域轉化進程，在雲端運算、區塊鏈、量子科技等方面加強研究力度，努力形成對對手的潛在嚇阻。

中国军网 国防部网

2022年9月16日 星期五

中國原創軍事資源：http://www.81.cn/jfjbmap/content/2022-09/16/content_324164888.htm

#Information Support Force, #intelligent warfare, #intellligentization, #新興戰爭技術, Asymmetric Warfare, China's Informatization - 中國信息化, China's Military Organization - Intelligence, Chinese Artificial Intelligence, Chinese Military Artificial Intelligence Weaponizatio, Chinese Military Characteristics & Development Trends of Cognitive Domain Operations and Warfare, Chinese Military Cognitive Domain Operations, Chinese military cognitive warfare, Chinese Military Future Wars, Chinese Military Informatization, Chinese Military Use of Cognitive Confrontation within the Combat Domain, Chinese Military Views - 中國軍事觀, Cognitive Confrontation, Cognitive Domain Warfare, Dissipative Warfare, Information Support Force, Intelligent Warfare, Multi-Domain Operations, 中國的情報戰, 中國的耗散戰, 中國解放軍敘事戰爭, 中國認知戰和領域作戰, 中國軍事分析:認知域作戰的特徵與發展趨勢, 中國軍事應用與比特幣在未來戰爭中的應用, 中國軍事未來戰爭, 中國軍事特徵及認知域作戰與戰爭發展趨勢, 中國軍事認知域作戰的重點是什麼、重點在哪裡？, 中國軍事認知戰, 中國軍事認知領域作戰, 中國軍民融合計劃, 中國軍用反衛星武器研製, 中國軍隊, 中國軍隊對耗散戰的戰術運用, 中國軍隊瞄準未來戰爭打好五場認知戰, 以認知為中心的戰爭：應對複雜戰爭的作戰概念, 認知域戰, 認知戰

China’s Military Accelerating Integrated Development of Mechanization, Informatization and Intelligentization

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我軍加速機械化、資訊化、智慧化融合發展

中国军网 国防部网

2020年11月25日 星期三

現代英語：

The Fifth Plenary Session of the 19th CPC Central Committee made new and comprehensive arrangements for national defense and military construction, aimed at achieving the goal of the centenary of the founding of the army, and clearly put forward the contemporary requirements and strategic measures for accelerating the integrated development of mechanization, informatization and intelligence. Forging ahead on a new journey, focusing on accelerating the integrated development of mechanization, informatization and intelligence, seizing opportunities, responding to challenges, and taking advantage of the situation are of great significance for accelerating the modernization of national defense and the army and comprehensively improving the ability to prepare for war in the new era.

Recognize the necessity of accelerating the integration of mechanization, informatization and intelligence

Those who follow the trend will win, and those who control the trend will prevail. At present, the new round of scientific and technological revolution is showing a strong trend of intelligent technology leading the way, pushing the world’s new military revolution to develop in depth. The trend of intelligent weapons and equipment is obvious, and the superposition and aggregation effect with mechanization and informatization is prominent. The war form is accelerating from mechanization to informatization, entering the stage of giving birth to intelligent warfare. It is the development and change of the times that has made the acceleration of the integrated development of mechanization, informatization and intelligence become the general trend and powerful driving force for promoting the in-depth development of military transformation, and the inevitable choice to ensure winning the initiative, winning advantages and winning the future.

Comply with the trend of the world’s military revolution. At present, the rapid development of artificial intelligence technology is increasingly having a subversive impact on the field of war and combat. Seizing the strategic commanding heights of artificial intelligence and accelerating the development of artificial intelligence militarization and practical combat have become the strategic frontiers of military competition among major countries in the world. Increasing the intensity of military application of artificial intelligence technology, realizing the deep transformation and comprehensive upgrading of mechanized and informationized combat equipment, embedding artificial intelligence systems into the informationized combat command chain and action chain, and making the combat force organization more modular and integrated through intelligent transformation are the common practices of the world’s military powers in seeking new military advantages. Whether it is possible to accelerate the integrated development of mechanization, informatization and intelligence, especially to fully release the efficiency expansion of intelligence on mechanization and informatization, so that platform operations, system operations and precision operations can obtain higher quality and efficient intelligent support, is undoubtedly a key to whether the strategic initiative of military competition can be firmly grasped.

The need to comprehensively improve the level of modernization. Modernization has a distinct timeliness, and the requirements of the times are the key measure to measure the degree of modernization of a country and an army. Today, we are entering a stage where intelligence is the core driving force of change. The integrated development of mechanization, informatization and intelligence is not only an important symbol of the level of modernization of the country and the army, but also a fundamental measure to promote the modernization of national defense and the army. To accelerate the modernization of military theory, military organizational form, military personnel and weapons and equipment, we need to obtain a powerful engine and support for reform and innovation, transformation and upgrading, quality improvement and efficiency increase from the integrated development of mechanization, informatization and intelligence, and in a certain sense, it plays an important role in determining the direction, mode and path of modernization. Only by accelerating the integrated development of mechanization, informatization and intelligence, and making it run through all aspects of the whole process of promoting modernization, and promoting quality change, efficiency change and power change from a high starting point, can we comprehensively improve the level of national defense and military modernization.

The need to accelerate the transformation of combat effectiveness generation mode. The generation of combat effectiveness, from the combination of people and weapons to the element structure and the way of force release, has its mandatory era orientation and positioning. With the advent of the era of intelligent warfare, unmanned intelligent warfare has become a key factor affecting the direction of the war and even the outcome of the war. Intelligent technology and equipment have become a multiplier of mechanized and informationized combat effectiveness. Accelerating the development of military intelligence has become the strategic focus of improving the combat capability of the system and building new domains and new qualities of combat forces, making the generation and improvement of combat effectiveness increasingly dependent on the level of integrated development of mechanization, informatization and intelligence. Only by incorporating the transformation of combat effectiveness generation mode into the track of integrated development of mechanization, informatization and intelligence, building an intelligent and networked combat command platform, forming a human-machine efficient collaborative combat force use method, and making “smart victory” the core direction of combat theory innovation and combat method transformation, can combat effectiveness construction achieve substantial breakthroughs and overall leaps.

Grasp the requirements of the times to accelerate the integrated development of mechanization, informatization and intelligence

Accelerating the integrated development of mechanization, informatization and intelligence is a new proposition of the times. Grasping its requirements of the times from the perspective of its essential connotation, mode of action and basic laws is an important prerequisite for ensuring that the integrated development has a clear direction, accurate positioning, clear ideas and practical measures.

Grasp the essential connotation of integrated development. Mechanization, informatization and intelligentization are integrated and developed, with mechanization as the foundation, informatization as the leading factor and intelligence as the direction. The so-called integrated development is to form an integrated and unified promotion pattern, build an integrated design, and gather the best and release the energy operation mode, and produce an overall effect of superposition aggregation and quality and efficiency doubling. This deep integrated development is mainly reflected in: taking cognitive integration as the guide, having a scientific understanding of the advantages of firepower, mobility, information power and intellectual value, and establishing the operational concept of comprehensive control, comprehensive integration and comprehensive victory; relying on platform integration, building a combat platform integrating main combat equipment, information network and artificial intelligence, and improving the comprehensive combat capability of full-domain, precise and unmanned; taking system integration as the core, through the embedded transformation of weapon equipment system and information network system by artificial intelligence system, the overall potential of combat force and combat elements is demonstrated with higher quality and level of system integration; with system integration as the support, coordinating the construction of mechanization, informatization and intelligence, coordinating the construction of combat force and support guarantee force, and creating an integrated joint combat system that adapts to the needs of actual combat.

Grasp the role of integrated development. The integrated development of mechanization, informatization and intelligence is a process of showing their strengths, interacting with each other and promoting each other. It is a process of aggregating equipment advantages, information advantages and intelligence advantages. Its role is mainly reflected in: strengthening the leading role of intelligence, focusing on accelerating the development of military intelligence, insisting on using intelligence to drive the leapfrog development of mechanization and informatization, taking intelligence as the core direction of the development of weapons and equipment and information network construction, increasing the research and development of unmanned and autonomous weapons and equipment, and improving the intelligent application, intelligent management and control, and intelligent operation level of information networks, and giving full play to the maximum effect of controlling energy with intelligence, gathering excellence with intelligence, and winning with intelligence; strengthening the leading role of informatization, grasping the information network system as a handle, accelerating the construction of command information systems and information combat systems, using the advantages of information technology to upgrade and transform existing weapons and equipment, and developing precise, intelligent, integrated, and efficient informationized weapons and equipment, and maximizing the adhesion and integration of information networks on combat systems and effectiveness; strengthening the basic role of mechanization, insisting on taking the mechanization of weapons and equipment as the material basis and carrier for the development of intelligence and informatization, strengthening the construction of weapons and equipment systems, and working hard to fill the gaps in the system and make up for the shortcomings and weaknesses, greatly improving the application level of information technology and intelligent technology in weapons and equipment, and enhancing the scientificity, pertinence, and cutting-edge nature of equipment construction and development.

Grasp the basic laws of integrated development. Mechanization, informatization and intelligence are inevitably closely linked, and together they constitute the key support for the generation and improvement of combat effectiveness. The basic laws of integrated development are mainly manifested in: the progressive nature of development and change, which reflects the different historical stages of the evolution of war forms, changes in combat methods, and the development of weapons and equipment in the time sequence; in terms of interaction, the former is the premise and foundation of the latter (for example, mechanization is the foundation and premise of informatization, and informatization is the foundation and premise of intelligence), and the latter is the development trend and higher potential of the former. With the long-term nature of overlapping and coexisting, the former will produce a marginal diminishing effect when it develops to a certain stage, and the latter needs to inject new momentum and vitality into it, but the latter is not a negation or end of the former, but a repositioning and orientation of the former. What needs to be achieved is the “three-in-one” inclusiveness, rather than the “three-choice” mutual exclusion. It has inclusive complementarity. Mechanization focuses on entities, informatization focuses on data, and intelligence focuses on algorithms. The stronger the foundation of the former, the greater the degree of realization of the latter; the stronger the traction of the latter, the faster the upgrading of the former. It has the empowerment of improving quality and efficiency. Weapon platforms need information networks to empower them, and weapon platforms and information networks need artificial intelligence to empower them. This is a process of optimization and upgrading, improving quality and efficiency, and achieving a new leap in combat effectiveness, quality and efficiency.

Tighten the strategic grasp to accelerate the integrated development of mechanization, informatization and intelligence

To accelerate the integrated development of mechanization, informatization and intelligence, we should plan, act and follow the trend, focus on combat effectiveness as the only fundamental standard, continuously promote the modernization of national defense and the armed forces, and realize the party’s goal of building a strong military in the new era.

We should focus on preparing for war. Wars change with the times, and victory changes with the times. We should take accelerating the integrated development of mechanization, informatization and intelligence as an important mission topic to comprehensively improve the ability to prepare for war in the new era. Focus on mission tasks, focus on the new requirements for winning modern wars, conduct in-depth research on the winning mechanism and changes in combat methods brought about by the evolution of war forms, grasp the new characteristics of the informationized and intelligent battlefield, actively explore new tactics for using and responding to intelligent weapons, and improve the informationized and intelligent combat capabilities; focus on transformation and construction, accelerate the transformation of combat effectiveness generation to informatization and intelligence, take military intelligent construction and combat as the main line, accelerate the construction of new domains and new types of combat forces, increase the training of informationized and intelligent talents, and strive to achieve the overall reshaping of combat forces and combat systems; focus on training with war, actively explore new ways of informationized and intelligent training, examine future battlefields and combat opponents from the perspective of “smart war” and “smart victory”, enhance the pertinence of mission topics and emergency response training, use intelligent technology to improve the level of science and technology training, and promote practical training to a higher quality level.

We must focus on deepening reform. Reform is a key move to strengthen the army and win the future. We must accelerate the integrated development of mechanization, informationization, and intelligence as an important focus of deepening national defense and military reform. We must insist on seeking combat effectiveness from reform, focus on the prominent characteristics of the army’s lean, integrated, miniaturized, modular, and multi-functional nature in the intelligent era, design reforms with a forward-looking, innovative, and open mind, establish a smooth and efficient leadership, command, and support mechanism, further integrate force resources, streamline the construction and management mechanism, and optimize the organizational structure. Adapting to the requirements of being able to fight and win battles, we must build a strategic and campaign command system that is integrated in peacetime and wartime, operates normally, specializes in the main business, is lean and efficient, and build a joint combat force system with elite combat forces as the main body, promote the development of the force organization in the direction of enrichment, synthesis, multi-functionality, and flexibility, implement modular organization, building block combination, and task-based joint, build a force with multiple capabilities and broad adaptability, and promote the overall leap in combat effectiveness through system structure optimization and reconstruction.

We should stick to the support point of innovation-driven development. Innovation is the core support for the development of combat effectiveness. We should accelerate the integrated development of mechanization, informatization and intelligence as the focus of implementing the innovation-driven development strategy. We should seek breakthroughs in the innovation of combat theory, closely follow the development trend of military revolution and the recent wars in the world, study the development and application of high-tech, especially intelligent technology and its impact on war, study the new characteristics, new styles and new mechanisms of intelligent warfare, study the winning strategies of intelligent warfare and combat, and accelerate the construction of a combat theory system with the characteristics of our army and in line with the laws of modern warfare. We should seek breakthroughs in scientific and technological innovation, focus on independent innovation and original innovation in national defense science and technology, take the military application of high-tech, especially artificial intelligence technology, as the main direction, accelerate the implementation of major strategic projects in national defense science and technology and weapons and equipment, accelerate the development of strategic, cutting-edge and disruptive technologies, accelerate the upgrading and replacement of weapons and equipment and the development of intelligent weapons and equipment, strive to achieve the transformation from following and running side by side to running side by side and leading, and provide stronger scientific and technological support for the transformation and construction of our army’s combat effectiveness.

(Author’s unit: Joint Operations College of National Defense University)

現代國語：

黨的十九屆五中全會對國防和軍隊建設作出新的全面部署，著眼實現建軍百年奮鬥目標，明確提出加快機械化資訊化智能化融合發展的時代要求和戰略舉措。奮進新征程，聚力加快機械化資訊化智能化融合發展，搶抓機遇，應對挑戰，乘勢而上，對於加速國防和軍隊現代化、全面提高新時代備戰打仗能力具有極其重要的意義。

認清加速機械化資訊化智能化融合發展的時代必然性

順勢者贏，駕馭者勝。目前，新一輪科技革命呈現智慧化技術強勁引領的態勢，推動世界新軍事革命向縱深發展，武器裝備智慧化趨勢明顯、與機械化資訊化的疊加聚合效應凸顯，戰爭形態在加速由機械化向訊息化演變中，進入到催生智慧化戰爭階段。正是時代發展與變革，使加速機械化資訊化智慧化融合發展，成為推動軍事變革深入發展的大勢所趨和強大動力，成為確保贏得主動、贏得優勢、贏得未來的必然選擇。

順應世界軍事革命潮流之需。目前，人工智慧技術正在高速發展，正日益對戰爭和作戰領域產生顛覆性影響。搶佔人工智慧戰略制高點，加速人工智慧軍事化實戰化發展，成為世界主要國家軍事競爭的戰略前線。加大人工智慧技術軍事應用的力度，實現對機械化、資訊化作戰裝備的深度改造、全面升級，把人工智慧系統嵌入資訊化作戰指揮鏈、行動鏈，透過智慧化改造使作戰力量編成更加模組化、一體化，是世界軍事大國謀求新的軍事優勢的通行做法。能否加速機械化資訊化智慧化融合發展，特別是充分釋放智慧化對機械化、資訊化的效能拓展，讓平台作戰、體係作戰、精準作戰獲得更高質高效的智慧化支撐，無疑是能否牢牢把握軍事競爭戰略主動權的一個關鍵。

全面提升現代化建設水準之需。現代化有著鮮明的時代性，時代要求是衡量一個國家、一支軍隊現代化程度的關鍵尺度。當今時代，正進入到以智慧化為核心變革動力的階段，機械化資訊化智能化的融合發展，既是國家和軍隊現代化水平的重要標誌，也是推進國防和軍隊現代化的根本性舉措。加速軍事理論、軍隊組織形態、軍事人員和武器裝備現代化，都需從機械化資訊化智慧化融合發展中，獲得變革創新、轉型升級、提質增效的強力引擎和支撐，並在一定意義上起著決定現代化建設發展方向、發展方式、發展路徑的重要角色。只有加速機械化資訊化智慧化融合發展，使之貫穿到推動現代化建設的全過程各環節，在高起點上推動品質變革、效率變革、動力變革，才能全面提升國防與軍事現代化建設水準。

加快轉變戰鬥力生成模式之需。戰鬥力的生成，從人與武器的結合到要素結構、力量釋放方式，都有其強制性的時代定向、定位。智慧化戰爭時代的到來，無人智慧化作戰成為影響戰局走向乃至戰爭勝負的關鍵要素，智慧化技術裝備成為機械化、資訊化作戰效能的倍增器，加速軍事智慧化發展成為提升體係作戰能力、打造新域新質作戰力量的戰略重心，使戰鬥力的生成與提升愈來愈取決於機械化資訊化智慧化的融合發展水準。只有把轉變戰鬥力生成模式納入機械化資訊化智慧化融合發展的軌道，建構智慧化網路化的作戰指揮平台，形成人機高效協同的作戰力量運用方式，讓「智勝」成為作戰理論創新、作戰方式變革的核心指向，才能使戰鬥力建設取得實質突破、實現整體性躍升。

掌握加速機械化資訊化智慧化融合發展的時代要求

加速機械化資訊化智慧化融合發展是一個全新的時代命題，從本質內涵、作用方式、基本規律上把握其時代要求，是確保融合發展方向明、定位準、思路清、舉措實的重要前提。

掌握融合發展本質內涵。機械化資訊化智能化融合發展，機械化是基礎，資訊化是主導，智能化是方向。所謂融合發展，就是形成融為一體、合而為一的推進格局，建構一體設計、聚優釋能的運作模式，產生疊加聚合、質效倍增的整體效應。這種深度融合發展主要體現在：以認知融合為先導，具有對火力、機動力、資訊力和智力價值優勢的科學認知，確立綜合製權、綜合整合、綜合製勝的作戰理念；以平台融合為依托，建構主戰裝備、資訊網路、人工智慧融為一體的作戰平台，提升全域化、精確化、無人化的綜合作戰能力；以系統融合為內核，透過人工智慧系統對武器裝備系統、資訊網路系統的嵌入式改造，以更高品質和水平的系統整合展現作戰力量、作戰要素的整體勢能；以體系融合為支撐，統籌機械化資訊化智能化建設，統籌作戰力量、支援保障力量建設，打造適應實戰需求的一體化聯合作戰體系。

把握融合發展作用方式。機械化資訊化智能化融合發展，是各展其長、互為作用、相互促進的過程，是聚合裝備優勢、資訊優勢、智能優勢的過程。其作用方式集中體現在：強化智能化的引領作用，聚焦加速軍事智能化發展，堅持以智能化牽引機械化、信息化跨越式發展，把智能化作為武器裝備和信息網絡建設發展的核心指向，加大研發無人化、自主化武器裝備的力度，提升資訊網路的智慧應用、智慧管控、智慧運作水平，發揮以智駕馭能、以智聚優、以智取勝的最大效應；強化資訊化的主導作用，扭住資訊網路體系這個抓手，加快指揮資訊系統、資訊作戰系統建設，運用資訊科技優勢升級改造現有武器裝備，開發精確、智慧、融通、高效的資訊化武器裝備，最大限度地發揮資訊網路對作戰體系與效能的黏合力、整合力；強化機械化的基礎作用，堅持將武器裝備機械化作為智慧化、資訊化發展的物質基礎與載體，加強武器裝備體系建設，在填補體系空白、補齊短板弱項上下功夫，大幅提升武器裝備的資訊科技、智慧技術應用水平，增強裝備建設發展的科學性、針對性、前沿性。

把握融合發展基本法則。機械化資訊化智能化之間有著必然的內在的緊密聯繫，共同構成戰鬥力生成和提升的關鍵支撐。其融合發展的基本法則主要表現在：具有發展變革的遞進性，在展開時序上，反映了戰爭形態演進、作戰方式變革、武器裝備發展的不同歷史階段；在相互作用上，前者是後者的前提和基礎（例如機械化是資訊化的基礎和前提，資訊化是智慧化的基礎和前提），後者是前者的發展趨向和更高位能。具有交疊並存的長期性，前者發展到某一階段會產生邊際遞減效應，需要後者為其註入新動能、新活力，但後者不是對前者的否定和終結，而是對前者的重新定位和定向，所要達成的是「三合一」式的兼容並蓄，而不是「三選一」式的互斥排他。具有相容且蓄的互補性，機械化以實體為重心，資訊化以數據為重心，智能化以演算法為重心，前者的基礎越牢，後者的實現程度就越大；後者的牽引作用越強，前者的升級換代就越快。具有提質增效的賦能性，武器平台需要資訊網路為其賦能，武器平台、資訊網路需要人工智慧為其賦能，這是優化升級、提質增效的過程，是實現戰鬥力品質效能新躍升的過程。

緊扭加快機械化資訊化智慧化融合發展的策略性抓手

加速機械化資訊化智能化融合發展，應因勢而謀、應勢而動、順勢而為，緊緊圍繞以戰鬥力這個唯一的根本標準，不斷推進國防和軍隊現代化建設，實現黨在新時代的強軍目標。

扭住備戰打仗這個聚焦點。戰爭因時而化，勝戰據時而變。要把加速機械化資訊化智能化融合發展，作為全面提升新時代備戰打仗能力的重要使命課題。聚焦使命任務，著眼打贏現代化戰爭的新要求，深入研究戰爭形態演變帶來的致勝機理、作戰方式之變，掌握資訊化智能化戰場的新特點，積極探索運用與應對智慧武器的新戰法，提升資訊化智慧化作戰能力；聚焦轉型建設，加速推進戰鬥力生成向資訊化、智慧化轉型，以軍事智慧化建設與作戰為主線，加速新域新質作戰力量建設，加大資訊化智慧化人才的培養力度，著力實現作戰力量、作戰體系的整體重塑；聚焦以戰領訓，積極探索資訊化智慧化訓練的新路子，從「智戰」「智勝」視角審視未來戰場、作戰對手，增強使命課題、應急應戰訓練的針對性，運用智能技術提昇科技興訓水平，推動實戰化訓練向更高質量水平發展。

扭住深化改革這個著力點。改革是強軍興軍、制勝未來的關鍵一招。要把加速機械化資訊化智慧化融合發展，作為深化國防和軍事改革的重要著力點。堅持向改革要戰力，著眼智慧時代軍隊精幹化、一體化、小型化、模組化、多能化的突出特徵，以前瞻、創新、開放的思路設計改革，建立順暢高效的領導、指揮、保障機制，進一步整合力量資源、理順建管機制、優化編成結構。適應能打仗、打勝仗的要求，建構平戰一體、常態運作、專司主營、精幹高效的戰略戰役指揮體系，建構以精銳作戰力量為主體的聯合作戰力量體系，推動部隊編成向充實、合成、多能、靈活方向發展，實行模組化編組、積木式組合、任務式聯合，打造具備多種能力和廣泛適應性的部隊，透過體系結構優化再造促進戰鬥力整體躍升。

扭住創新驅動這個支撐點。創新是戰鬥力建設發展的核心支撐力。要把加速機械化資訊化智慧化融合發展，作為實施創新驅動發展策略的重心。在作戰理論創新上求突破，密切追蹤軍事革命發展趨勢和近期世界發生的戰爭，研究高新技術特別是智慧化技術發展運用及對戰爭的影響，研究智能化作戰的新特徵、新樣式、新機理，研究智慧化戰爭與作戰的致勝方略，加速建構具有我軍特色、符合現代戰爭規律的作戰理論體系。在科技創新上求突破，聚力國防科技自主創新、原始創新，把高新技術特別是人工智慧技術的軍事應用作為主攻方向，加速實施國防科技與武器裝備重大戰略工程，加速戰略性前沿性顛覆性技術發展，加速武器裝備升級換代和智慧化武器裝備發展，奮力實現由跟跑並跑向並跑領跑的轉變，為我軍戰鬥力轉型建設提供更強勁的科技支撐。

（作者單位：國防大學聯合作戰學院）

中國原創軍事資源：http://www.81.cn/gfbmap/content/2020-11/25/content_276619888.htm

#Information Support Force, #intelligent warfare, #intellligentization, Chinese Artificial Intelligence, Chinese Military Artificial Intelligence Weaponizatio

Artificial Intelligence Will Change Chinese Military Winning Mechanism of Future Wars

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人工智慧將改變中國軍隊未來戰爭制勝機制

現代英語：

2024-05-02 09:xx | Source:  Peopke’s Liberation Army Daily

Artificial intelligence technology is an important support for improving strategic capabilities in emerging fields. In recent years, it has developed rapidly and has been widely used in the military field, constantly giving rise to new asymmetric advantages, and profoundly changing the basic form, combat methods and winning mechanisms of future wars. We should have a deep understanding of artificial intelligence as a revolutionary technological driving force, accurately identify changes, respond scientifically, and actively seek changes, strive to explore ways to win future wars, and gain the initiative in the accelerating intelligent war.

Information Mechanism

Knowing yourself and the enemy will ensure victory in every battle. Quickly and effectively mastering all-round information is the primary prerequisite for winning a war. Artificial intelligence can realize intelligent perception of battlefield situation, intelligent analysis of massive data, and intelligent processing of multiple information, which can form a “transparent” advantage on the battlefield.

Autonomous implementation of battlefield perception. By embedding intelligent modules into the wartime reconnaissance system, various reconnaissance node units can achieve random networking, on-the-spot coordination, and organic integration, and can autonomously capture battlefield information in all directions and dimensions, build a relatively “transparent” digital battlefield environment and combat situation, and then dispel the “fog” of war and present a panoramic view of the combat scene.

Accurately identify massive amounts of data. Relying on intelligent technologies such as precise sensing technology and analytical recognition technology, it accurately interprets, analyzes, compares, and integrates diversified voice, text, pictures, videos, and other data to obtain faster, more complete, more accurate, and deeper battlefield situation results, far exceeding the speed and accuracy of human brain processing.

Efficient response to key information. Based on intelligent technologies such as combat cloud, big data, and the Internet of Things, it is able to quickly discover large quantities of non-standardized, heterogeneous intelligence data, autonomously discover symptoms, identify intentions, analyze trends, find patterns, and respond to commanders’ needs for key information in real time and accurately.

Synchronous sharing of integrated situation. The intelligent control system can optimize and integrate various reconnaissance and surveillance systems distributed in different spaces and frequency domains such as land, sea, air, space, and power grids, and play an important hub role in sharing information and unified cognition, building a situation based on “one picture”, “one network”, and “one chain”, so that all combat units can synchronously share the required information from different spaces, distances, and frequencies in all domains and at all times, and realize intelligent sharing.

Decision-making mechanism

Those who win before the battle have made more calculations. Scientific and accurate decision-making is a prerequisite for winning a war. Artificial intelligence can simulate and deduce dynamic battlefields, quickly make feasible decisions, greatly shorten the operational planning and decision-making cycle, and form a decision-making advantage.

Intelligent strategic situation analysis. The decision-making support system that incorporates artificial intelligence technology has functions such as information collection, query management, data processing, and correlation analysis. It can effectively break through the limitations of human analytical capabilities, maximize the separation of false and true, correlation verification, and link thinking, automatically conduct big data analysis such as enemy situation, our situation, and battlefield environment, and form comparative data on related forces and weapons. It can efficiently assist combat command and help commanders quickly make combat decisions.

Intelligent optimization of combat plans. Relying on the intelligent combat simulation system, according to the pre-input combat missions and strike target information, it automatically generates multiple sets of intuitive plans and programs, comprehensively evaluates their advantages and disadvantages and potential risks, and selects the plan that is most conducive to achieving the commander’s intention for the commander to make the final decision. After receiving the combat missions and target requirements from the superior, each combat unit further screens the battlefield target information in combination with the tasks and requirements of this level, and independently formulates the best plan and program at this level to maximize combat effectiveness.

Intelligent prediction of decision-making effectiveness. The intelligent decision-making support system relies on intelligent technologies such as big data, high-performance computing, and neural network algorithms to give the command and control system more advanced “brain-like” capabilities, allowing it to think more rationally about unexpected situations on the battlefield and quickly come to relatively objective results of the engagement.

Power control mechanism

Power is the right to control based on benefits. Seizing control is the key factor in winning a war. Artificial intelligence can “transplant” part of human intelligence to weapons, making the combination of humans and weapon systems closer and closer. The deep interaction between man and machine has changed the traditional elements of control, endowed it with new connotations, and can help gain new control advantages.

The right to control the domain is expanding to the high frontier. In the future, highly intelligent unmanned systems will be able to carry out a variety of combat missions even under harsh conditions such as high temperature, extreme cold, high pressure, lack of oxygen, toxicity, radiation, and in extreme environments such as extremely high, extremely far, extremely deep, extremely microscopic, extremely dark, and extremely bright. The competition for control of the combat domain and combat space will extend to the high frontier, the far frontier, and the deep frontier.

The right to control information is expanding to multiple means. Traditionally, the right to control information is achieved by attacking the enemy’s reconnaissance and early warning system, destroying its command and control system, and other means to control the acquisition, processing, and distribution of information. However, information warfare dominated by artificial intelligence uses information itself as “ammunition”, and the means to seize the right to control information are more diverse.

The network control power is expanding to distributed. The network information system built based on intelligent technology provides a ubiquitous network “cloud” to aggregate battlefield resources of various terminals and provide services, which can realize modular organization and automated reorganization of combat forces. The traditional purpose of breaking the network and destroying the chain by attacking key nodes will no longer be achieved. It is inevitable to respond to the “decentralized” battlefield with an intelligent distributed attack mode.

The power to control the brain is expanding to new domains. Brain-like technology and simulation technology are gradually militarized, forming new areas of competition and confrontation. The focus has shifted from focusing on confrontation in the physical and information domains to focusing more on influencing and controlling the opponent’s psychology. Technologies such as virtual reality and audio-visual synthesis can be indistinguishable from the real thing. “Core attack” can quietly change the enemy’s command and control system algorithm. “Brain control” can directly control the enemy’s decision-making. By controlling and influencing the enemy’s psychology, thinking, will, etc., the goal of stopping and winning the war can be achieved at the lowest cost.

Mechanism of action

The key to victory in war is to take advantage of the enemy’s unpreparedness and to take actions that the enemy does not expect. Artificial intelligence can improve the intelligence of weapons and equipment, command and control systems, and action decision-making, making the mobile response capability faster and the joint strike capability more accurate, creating a super action advantage.

The speed of action is “instant kill”. The intelligent combat system can see, understand, learn and think, effectively shortening the “OODA” cycle. Once an “opportunity” is found, it will use intelligently controlled hypersonic weapons, kinetic weapons, laser weapons, etc. to quickly “instant kill” the target at a long distance.

Action style is “unmanned”. “Unmanned + intelligent” is the future development direction of weapons and equipment. Low-cost unmanned vehicles, drones, unmanned submarines and other unmanned autonomous equipment, with the support of cluster autonomous decision-making systems, can plan the task division of each unit according to combat objectives, accurately dock with each other, autonomously combine, covertly penetrate, and carry out cluster saturation attacks on the enemy.

“Blurred” action space. In future wars, using interference to carry out soft strikes on the enemy’s intelligent combat systems and intelligent weapons, and using intelligent weapons to delay or influence the enemy’s decision-making and psychology will become the key to victory. Most of these actions are completed unconsciously or silently, presenting a “blurred” state where the enemy and us are invisible, the boundaries between the front and the rear are unclear, and the visible and invisible are difficult to distinguish.

The action deployment is “stealth”. The intelligent command system and weapon equipment have bionic and stealth properties. As long as they are deployed in advance in possible combat areas during peacetime preparations or training exercises, they can be pre-positioned and dormant in preparation for war. Once they are activated in time during wartime, they can launch a sudden attack on the enemy, which will help to quickly seize the initiative in the war.

System Mechanism

Five factors and seven strategies determine victory or defeat. Future wars will be full-domain, full-system, full-element, full-process system confrontations, and a stable and efficient combat system is the basic support for winning the war. As the application of artificial intelligence in the military field continues to expand, the combat system is becoming more and more intelligent, and the full-domain integrated combat system will produce a strong system advantage.

There are more means of “reconnaissance”. Intelligent combat clusters rely on network information systems to connect with various large sensors, electronic warfare systems and other human-machine interaction platforms, use the detection and perception equipment of each combat unit to obtain battlefield data, give full play to the self-organizing characteristics of intelligent groups, strengthen real-time reconnaissance and monitoring support for joint combat systems and back-end intelligence analysis, and achieve full-domain reconnaissance, joint early warning, and coordinated verification, forming a multi-dimensional, full-domain coverage of large-area joint reconnaissance intelligence system.

The scope of “control” is wider. The use of intelligent unmanned combat platforms can break through the logical limits of human thinking, the physiological limits of senses and the physical limits of existence, and replace humans to enter traditional life-forbidden areas such as the deep sea, space, polar regions, and areas with strong radiation, and stay there for a long time to carry out “unconventional warfare”, thereby further expanding the combat space and having the ability to continuously deter opponents in a wider range of fields.

The speed of “fighting” is faster. Supported by the intelligent network information system, the intelligence chain, command chain, and kill chain are seamlessly connected, the speed of information transmission, decision-making speed, and action speed are simultaneously accelerated, and the intelligent combat units can be flexibly organized, autonomously coordinated, and quickly strike. All of these make the time utilization efficiency extremely high and the battlefield response speed extremely fast.

The “evaluation” is more accurate. Using intelligent technologies such as experiential interactive learning and brain-like behavior systems, the intelligent combat evaluation system can independently complete the collection, aggregation, and classification of multi-means action effect evaluation information, accurately perceive battlefield actions based on big data and panoramic images, dynamically identify combat progress and correct defects, predict complex battlefield changes, and make comprehensive plans and respond flexibly.

The “maintenance” is more efficient. The widespread application of intelligent comprehensive support systems represented by equipment maintenance expert systems and intelligent sensing equipment can efficiently respond to the support needs of various domains, intelligently plan support resources, ensure that the “cloud” aggregates various battlefield resources, and effectively improve the comprehensive support capabilities of the networked battlefield.

(Zeng Haiqing’s unit: Henan Provincial Military Region)

現代國語：

人工智慧技術是提升新興領域戰略能力的重要支撐，近年來獲得快速發展並廣泛運用於軍事領域，不斷催生新的非對稱優勢，深刻改變未來戰爭的基本形態、作戰方式和致勝機理。應該深刻認識人工智慧這項革命性技術動力，準確識變、科學應變、主動求變，努力探索制勝未來戰爭之道，在加速來臨的智慧化戰爭中贏得主動。

資訊機理

知彼知己，百戰不殆。快速有效地掌握全方位資訊是戰爭制勝的首要前提。人工智慧可實現戰場態勢智慧感知、大量資料智慧分析、多元資訊智慧處理，能夠形成戰場「透明」優勢。

戰場感知自主實施。將智慧模組嵌入戰時偵察系統，各類偵察節點單元可實現隨機組網、臨機協同、有機整合，能夠全方位、多維度自主捕獲戰場信息，構建相對「透明」的數位化戰場環境和戰態勢，進而撥開戰爭“迷霧”，全景式呈現作戰場景。

海量資料精準識別。依托精準感知技術及分析辨識技術等智慧化科技，精準判讀、分析、比對、融合多元化的語音、文字、圖片、視訊等數據，從而獲取更快、更全、更準、更深的戰場態勢結果，遠超人腦處理的速度和精確度。

關鍵資訊高效響應。基於作戰雲、大數據、物聯網等智慧化技術群，能夠從大批量、非標準化、異構化的情報數據中快速發掘，自主發現徵候、識別意圖、研判趨勢、找到規律，即時精準地響應指揮官對關鍵資訊的需求。

融合態勢同步共享。智慧化控制系統能夠將分佈在陸海空天電網等不同空間、不同頻域的各種偵察監視系統優化整合，並發揮共享信息和統一認知的重要樞紐作用，構建形成基於“一幅圖”“一張網」「一條鏈」的態勢，使各作戰單元全局全頻全時從不同空間、不同距離、不同頻率同步共享所需信息，實現智慧共享。

決策機理

夫未戰而廟算勝者，得算多也。科學準確決策是戰爭制勝的先決條件。人工智慧可進行動態戰場模擬推演，快速給予可行決策，大幅縮短作戰規劃決策週期，能夠形成決策優勢。

戰略形勢智能研判。融入人工智慧技術的決策輔助系統，具備資訊收集、查詢管理、資料處理、關聯分析等功能，可有效突破人類分析能力的限制，最大限度去偽存真、關聯印證、連結思考，自動進行敵情、我情和戰場環境等大數據分析，形成相關兵力、兵器等對比數據，能夠有效率地輔助作戰指揮，幫助指揮家快速定下作戰決心。

作戰方案智能優選。依托智能化作戰模擬系統，根據預先輸入的作戰任務和打擊目標訊息，自動產生多套形象直觀的方案和計劃，綜合評估其優缺點及潛在風險，優選出最有利於實現指揮官意圖的方案，供指揮官作出最後決斷。各作戰單元接到上級作戰任務和目標需求後，結合本級任務和要求，進一步對戰場目標資訊進行甄別篩選，自主制訂本級最優方案和計劃，實現作戰效能最大化。

決策效能智能預測。智慧化輔助決策系統依賴大數據、高效能運算、神經網路演算法等智慧化技術，賦予指揮控制系統更高階的「類腦」能力，可以更理性地思考戰場上出現的意外情況，快速得出相對客觀的交戰結果。

制權機理

勢者，因利而製權也。奪取制權是贏得戰爭制勝優勢的關鍵因素。人工智慧可將人的部分智慧「移植」到武器上，使得人與武器系統結合越來越緊密，人機一體深度互動改變了傳統的製權要素，賦予新的製權內涵，能夠助力獲得新的製權優勢。

制域權向高邊疆拓展。未來高度智慧化的無人系統，即使在高溫、極寒、高壓、缺氧、有毒、輻射等惡劣條件下，在極高、極遠、極深、極微、極黑、極亮等極端環境中，仍可遂行多種作戰任務，作戰領域和作戰空間的製權之爭向高邊疆、遠邊疆、深邊疆延伸。

制資訊權向多手段拓展。傳統的奪取制資訊權，是透過打擊敵偵察預警體系、破壞其指揮控制系統等手段實現對資訊取得、處理、分發等途徑的控制，而人工智慧主導下的資訊作戰則是將資訊本身作為「彈藥”，奪取制資訊權的手段更加多元。

制網權向分散式拓展。基於智慧科技建構的網路資訊體系，提供泛在網路「雲」以聚合各類終端的戰場資源並提供服務，能夠實現作戰力量模組化編組、自動化重組，傳統的透過打擊關鍵節點，達成斷網毀鏈的目的將很難再實現，必然是以智慧化分散式打擊模式來應對「去中心化」的戰場。

制腦權向新維度拓展。類腦技術、模擬技術等逐步軍事化，形成了新的博弈和對抗領域，重心由注重物理域、資訊域對抗向更加註重影響和控制對手心理轉變，虛擬實境、聲像合成等技術能夠以假亂真， 「攻芯戰」能夠悄無聲息地改變敵方指揮控制系統演算法，「控腦戰」能夠直接控制敵方決策，透過控制和影響敵方的心理、思維、意誌等，能夠以最小代價實現止戰、勝戰之目的。

行動機理

兵之情主速，乘人之不及。採取敵方意料不到的行動是戰爭制勝的關鍵要害。人工智慧可提高武器裝備、指控系統、行動決策等方面的智慧化程度，使機動反應能力更快、聯合打擊能力更準，創造出超強的行動優勢。

行動速度「秒殺化」。智慧化作戰系統看得見、聽得懂、能學習、會思考，有效縮短了“OODA”循環週期，一旦發現“有機可乘”，便運用智能化控制的超高聲速武器、動能武器、激光武器等，對目標進行遠距離快速「秒殺」。

行動樣式「無人化」。 「無人+智慧」是未來武器裝備發展方向。低成本的無人車、無人機、無人潛航器等無人自主裝備，在集群自主決策系統支援下，可針對作戰目標規劃各單元的任務分工，無人器之間精準對接、自主組合、隱蔽突防，對敵進行群集飽和攻擊。

行動空間「模糊化」。未來戰爭中，利用乾擾手段對敵方的智慧化作戰系統和智慧武器實施軟打擊，利用智慧武器遲滯或影響敵方人員的決策和心理將成為致勝關鍵。這些行動大都是在不知不覺或無聲無息中完成的，呈現敵我雙方不見人影、前方後方界限不清、有形無形難以辨別的「模糊」狀態。

行動布勢「隱身化」。智慧化指揮系統和武器裝備具有生物仿生和隱身性能。只要在平時備戰或訓練演習時提前佈設在可能交戰地域，潛伏預置、休眠待戰，戰時一旦需要適時激活，對敵實施猝然打擊，有助於快速掌握戰爭主動權。

體系機理

五事七計知勝負。未來戰爭是全領域、全系統、全要素、全流程的體系對抗，穩定且有效率的作戰體係是戰爭制勝的基礎支撐。隨著人工智慧在軍事領域應用不斷拓展，作戰體系智慧化程度越來越高，全域融合的作戰體系將產生強大的體系優勢。

「偵」的手段更多。智慧化作戰集群依托網路資訊體系與各類大型感測器、電子戰系統及其他人機互動平台連接，運用各作戰單元本身偵測感知設備取得戰場數據，發揮智慧群體自組織特性，強化對聯合作戰體系及後端情報分析的即時偵監支持，能夠實現全局偵搜、聯合預警、協同印證，形成多維一體、全域覆蓋的大區域聯合偵察情報體系。

「控」的領域更廣。運用智慧化無人作戰平台，能夠突破人類思維的邏輯極限、感官的生理極限和存在的物理極限，並取代人類進入深海、太空、極地、強輻射地域等傳統的生命禁區，並長時間置身其中實施“非常規作戰”，從而使作戰空間進一步拓展，具備在更廣的領域持續懾拒對手的實力。

「打」的速度更快。在智慧化網路資訊體系支撐下，情報鏈、指揮鏈、殺傷鏈無縫連接，資訊傳輸速度、決策速度與行動速度同步加快，智慧化作戰單元能夠靈活編組、自主協同、快速打擊。這些都使得時間利用效率極高、戰場反應速度極快。

「評」的精準度更準。運用經驗互動學習、類腦行為體係等智慧化科技，智慧化作戰評估系統能夠自主完成多手段行動效果評估資訊的擷取匯聚、分級分類，基於大數據和全景圖精準感知戰場行動，動態識別作戰進程並修正缺陷問題，預判複雜戰場變化，綜合規劃、靈活應對。

「保」的效率更高。以裝備維修專家系統、智慧化感知設備為代表的智慧化綜合保障系統的廣泛應用，能夠高效響應各域保障需求，智慧規劃保障資源，保障「雲」聚合各類戰場資源，有效提升網路化戰場綜合保障能力。

（曾海清 作者單位：河南省軍區）

中國原創軍事資源：http://www.81.cn/szb_223187/szbxq/index.html?paperName=jfjb&paperDate=2024-05-02&paperNumber=03&articleid=93088338

#Information Support Force, #intelligent warfare, #intellligentization, Asymmetric Warfare, Chinese Artificial Intelligence, Chinese Military Artificial Intelligence Weaponizatio

Artificial Intelligence Will Profoundly Change the Face of Warfare for China

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人工智慧將深刻改變中國的戰爭面貌

現代英語：

Defeating dozens of top Go players in a man-machine battle, defeating a retired US Air Force pilot in a simulated air combat… In recent years, artificial intelligence has been like an omnipotent “magician”, creating endless miracles, shocking many people and constantly refreshing people’s imagination.

As a technical science dedicated to simulating, extending and expanding human intelligence, artificial intelligence has long surpassed scientists’ initial imagination and entered a “booming period” of rapid development. It is profoundly changing the way humans produce and live, and promoting the social form to accelerate from digitalization and networking to intelligence. At the same time, the widespread use of artificial intelligence technology in the military field will fundamentally change the winning mechanism and combat methods of modern warfare, give birth to new combat means and combat ideas, and promote the war form to accelerate into the intelligent era.

In intelligent warfare, intelligent equipment, intelligent command, intelligent maintenance, and intelligent combat methods are all conceivable – “fake news” created by artificial intelligence is everywhere in the entire process of war preparation, conduct and conclusion, and it is “false and true”; the role of inanimate intelligent entities and robot fighters in intelligent warfare is prominent, and artificial intelligence combat forces such as “cloud brain”, “digital staff” and “virtual warehouse” used for information support, command and control, effect evaluation and logistics support will play an increasingly important role in future wars. Intelligent machines and intelligent weapons will become the main force on future battlefields; remote and precise Specific, miniaturized, and large-scale unmanned attacks will become the main form of attack. “Man-to-man” warfare will expand to “machine autonomous warfare” warfare; intelligent swarm attrition warfare, cross-domain mobile warfare, and cognitive control warfare will become basic combat types; decentralized deployment of humans and machines, autonomous coordination, and concentrated energy offensive and defensive operations will become the basic principles of cross-domain integration and global operations; the “observation-judgment-decision-action” link will be greatly shortened, the combat rhythm will be faster, the actions will be more precise, and the efficiency will be higher; upgrading and training artificial intelligence systems and various unmanned combat platforms through continuous confrontation exercises will become an important way to enhance combat effectiveness. Intelligence will surpass firepower, mobility, and information power and become the most critical factor in determining the outcome of a war. As a result, the meaning of battlefield control will need to be redefined, new topics will be added to international arms negotiations, and textbooks on intimidation theory will need to be rewritten.

The world’s military powers, represented by the United States, have foreseen the broad application prospects of artificial intelligence technology in the military field. They believe that future wars will be intelligent wars and future arms competitions will be intelligent competitions. They have also laid out a series of research plans in advance, hoping to seize the initiative in the military application of artificial intelligence and strive to open up a “generation gap” with potential opponents. In recent years, NASA, the Department of Defense and various military services have deployed a series of artificial intelligence technology research projects in the military field. The U.S. Department of Defense has also proposed the establishment of a “Joint Artificial Intelligence Center” to jointly promote artificial intelligence projects with the U.S. military and 17 intelligence agencies, and coordinate the planning and construction of an intelligent military system supported by military technology and military applications. Russia also sees artificial intelligence as the commanding heights of future military competition. The Russian military is stepping up the development of humanoid robots that can drive vehicles and build robot troops that can fight side by side with human soldiers. Russian President Vladimir Putin said: “Artificial intelligence is not only the future of Russia, but also the future of all mankind. It contains huge opportunities and threats that are difficult to predict today.” Countries such as the United Kingdom, Japan, Australia, South Korea, and India are also increasingly paying attention to the development and application of artificial intelligence in the military field.

Today, the pace of military application of artificial intelligence may be difficult to stop. Faced with the new situation, we need to firmly grasp the major historical opportunities for the development of artificial intelligence, judge the general trend, take the initiative to plan, grasp the direction, seize the initiative, and effectively safeguard national security. At the same time, from the perspective of the future and destiny of mankind, the international community should establish a mechanism to prevent the excessive military application of artificial intelligence as soon as possible. After all, the power of human beings to create civilization should not become a tool to destroy civilization, and scientific and technological progress should be a blessing for the benefit of mankind, rather than a death knell that threatens human survival and development.

(Author’s unit: Academy of Military Science)

現代國語：

■遊光榮

在人機大戰中擊敗數十名頂級圍棋高手、在模擬空戰中擊敗美國空軍退役飛行員……近年來，人工智能猶如萬能的“魔法師”，創造了層出不窮的奇跡，在驚掉不少人下巴的同時，也不斷刷新著人們的想像。

作為一門致力於模擬、延伸和擴展人的智慧的技術科學，人工智慧早已超越了科學家最初的想像，進入了一個高速發展的“井噴期”，正在深刻改變人類的生產生活方式，推動社會形態從數位化、網絡化向智慧化加速躍升。同時，人工智慧技術在軍事領域的廣泛運用，將從根本上改變現代戰爭制勝機理和作戰方式，催生新的作戰手段和作戰思想，推動戰爭形態加速邁入智能化時代。

在智慧化戰爭中，智慧化裝備、智慧化指揮、智慧化維修、智慧化作戰方式都是可以想像的——人工智慧製造的「虛假新聞」在戰爭準備、進行和結束的全過程中無處不在，而且“以假亂真”；無生命智能體、機器人戰鬥員在智能化戰爭中的作用凸顯，用於信息支援、指揮控制、效果評估、後勤保障的“雲大腦”“數字參謀”“虛擬倉儲”等人工智慧作戰力量將在未來戰爭中發揮越來越重要的作用，智慧機器和智慧武器將成為未來戰場的主力；遠程化、精確化、小型化、大規模無人攻擊將成為主要進攻形式，「人對人」的戰爭將向「機器自主作戰」的戰爭拓展；智慧化的蜂群消耗戰、跨域機動戰、認知控制戰將成為基本作戰類型；人機分散部署、自主協同、集中能量攻防作戰，成為跨域融合、全局作戰的基本準則；「觀察-判斷-決策-行動」連結大大縮短，作戰節奏更加快速、行動更加精準、效率更高；透過持續的對抗演習對人工智慧系統和各類無人化作戰平台的升級訓練，將成為戰鬥力提升的重要方式。智能將超越火力、機動性和資訊力，成為決定戰爭勝負的最關鍵因素。隨之而來的是，戰場控制權的內涵將需要重新界定，國際軍備談判將增加新主題，威懾理論的教科書也將改寫。

以美國為代表的世界軍事強國，預見到人工智慧技術在軍事領域的廣闊應用前景，認為未來的戰爭將是智慧化戰爭、未來的軍備競賽將是智慧化競賽，並已提前佈局了一系列研究計劃，希望搶佔人工智慧軍事化應用先機，力求與潛在對手拉開「代差」。近年來，美國國家航空暨太空總署、國防部和各軍種在軍事領域部署了一系列人工智慧技術研究項目，美國國防部還提出建立“聯合人工智慧中心”，計劃聯合美軍和17家情報機構共同推進人工智慧項目，統籌規劃建設以軍事技術和軍事應用為支撐的智慧軍事體系。俄羅斯也視人工智慧為未來軍事競爭的製高點，俄軍正加緊研發可以駕駛車輛的類人機器人、組建可與人類戰士並肩戰鬥的機器人部隊。俄總統普丁提出：「人工智慧不僅僅是俄羅斯的未來，也是全人類的未來。這包含著巨大的機會和當今難以預測的威脅。」英國、日本、澳洲、韓國、印度等國家也日益重視人工智能在軍事領域的發展與應用。

現今，人工智慧軍事化應用步伐或許難以阻止，面對新形勢，我們需要牢牢掌握人工智慧發展的重大歷史機遇，研判大勢、主動謀劃、把握方向、搶佔先機，有效維護國家安全。與此同時，從人類自身前途命運出發，國際社會應該早日建立防止人工智慧在軍事上過度應用的機制。畢竟，人類創造文明的力量不應該成為毀滅文明的工具，科技進步應該成為造福人類的福音，而不是成為威脅人類生存與發展的喪鐘。

（作者單位：軍事科學院）

中國原創軍事資源：http://www.mod.gov.cn/gfbw/jmsd/4826892.html?big=fan

#Information Support Force, #intelligent warfare, #intellligentization, Chinese Artificial Intelligence, Chinese Military Artificial Intelligence Weaponizatio

Militarization of Artificial Intelligence Competition Accelerating, China Must Adapt to Win

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人工智慧軍事化競爭加速，中國必須適應才能取勝

現代英語：

Adapt to the general trend of technological development and seize the commanding heights of future wars——

Artificial intelligence is a general term for cutting-edge technologies such as big data, automated decision-making, machine learning, image recognition, and space situational awareness. It can liberate the “cognitive burden” of human intelligence and physical energy, and enable technology users to gain the advantages of foresight, preemption, and preemptive decision-making and action. As a “force multiplier” and “the foundation of future battles”, artificial intelligence will fundamentally reshape the future form of war, change the country’s traditional security territory, impact the existing military technology development pattern, reconstruct the future combat system and military force system, and become an important dominant force on the future battlefield.

With the rapid development of technology and the accelerating competition, major countries have launched their own artificial intelligence development plans, and accelerated the reform of organizational mechanisms, scientific and technological research and development, and innovation of tactics and strategies, promoting the military use of artificial intelligence and seizing the commanding heights of future wars.

Accelerate organizational innovation

Promoting technology transformation and application

Unlike traditional technologies, the development and transformation of artificial intelligence has its own characteristics. The institutional setup and operation mode of the traditional national defense system are difficult to adapt to the needs of the rapid development of artificial intelligence. To this end, the armed forces of relevant countries have vigorously carried out organizational system reform and innovation, removed the institutional barriers in the process of artificial intelligence technology development, and accelerated the transformation and application of related technologies.

Emphasis on “connecting the near and the far”. The UK, with the “Defense Data Office” and the “Digital Integration and Defense Artificial Intelligence Center” as the main body, integrates route planning, specification setting, technology governance and asset development, and removes administrative obstacles that restrict the development and application of artificial intelligence technology. The United States, relying on the “Strategic Capabilities Office” and the “Chief Digital and Artificial Intelligence Officer”, uses the Army Futures Command as a pilot to integrate decentralized functions such as theoretical development, technology research and development, and equipment procurement, focusing on strengthening the innovative use of existing platforms in a “potential tapping and efficiency increasing” manner, while buying time for the Defense Advanced Research Projects Agency’s medium- and long-term technological innovation, thereby effectively balancing actual needs and long-term development.

Attach importance to “research-use conversion”. The application of artificial intelligence in the military field will have a profound impact on battlefield combat methods, tactical and combat method selection, etc. Russia has established institutions such as the “Advanced Research Foundation” and the “National Robotics Technology Research and Development Center” to guide the design, research and development and application of artificial intelligence technology in the Russian military to improve the practical conversion rate of scientific research results. The United States has established the “Joint Artificial Intelligence Center” and relied on the “National Mission Plan” and “Service Mission Plan” to coordinate military-civilian collaborative innovation and scientific and technological achievements. The transformation promotes the widespread application of artificial intelligence in the US Department of Defense and various services.

Focus on “military-civilian integration”. Russia has established institutions such as the “Times Science and Technology City” in Anapa and other places, relying on the “Advanced Research Foundation” to fully absorb military and civilian talents, actively build scientific and technological production clusters and research clusters, and effectively expand the two-way exchange mechanism of military and civilian talents. The United States has established institutions such as the “Defense Innovation Experimental Group” in Silicon Valley and other places, relying on the “Defense Innovation Board”, so that the latest achievements in technological innovation and theoretical development in the field of artificial intelligence can directly enter high-level decision-making. France has established innovative defense laboratories, defense innovation offices and other technical research and development institutions in the Ministry of National Defense, aiming to solicit private capital investment and defense project cooperation to improve scientific research efficiency.

Highlight the “integration of science and technology”. The Israel Defense Forces has established a digital transformation system architecture department. According to the specific effects of the organic integration of various systems into various military services, new technologies, new theories, and new concepts are fully demonstrated to determine the corresponding technology research and development priorities and strategic development directions. The United States has enhanced the overall management of defense technology innovation and application by re-establishing positions such as the Deputy Secretary of Defense for Research and Engineering and creating the Chief Digital and Artificial Intelligence Officer. It has also relied on theoretical methods such as red-blue confrontation, simulation and deduction, and net assessment analysis to conduct practical tests on various new ideas, new concepts, and new methods, so as to select various technology research and development focuses and strategic and tactical research directions, and achieve a virtuous interaction between technological development and theoretical innovation.

Project establishment for military needs

Seize the opportunity for future development

In recent years, various military powers have targeted the research and development of cutting-edge artificial intelligence technologies, and have launched extensive projects in the fields of situational awareness, data analysis, intelligence reconnaissance, unmanned combat, etc., with the intention of seizing the initiative in future development.

Situational awareness. In the traditional sense, situational awareness refers to the collection and acquisition of battlefield information through satellites, radars, and electronic reconnaissance. However, under the conditions of “hybrid warfare” where peacetime and wartime are blurred, soldiers and civilians are integrated, internal and external links are linked, and the entire domain is integrated, the role of situational awareness in non-traditional domains such as the human domain, social domain, and cognitive domain has received unprecedented attention. The U.S. “Computable Cultural Understanding” project aims to process multi-source data through natural language processing technology to achieve cross-cultural communication; the “Compass” project aims to extract cases from unstructured data sources, integrate key information, and respond to different types of “gray zone” operations. The French “Scorpion” combat system project aims to use an intelligent information analysis and data sharing platform to enhance the firepower support effectiveness of the French army’s existing front-line mobile combat platforms to ensure the safety of operational personnel.

Data analysis. Relying on artificial intelligence technology to improve intelligent data collection, identification analysis and decision-making support capabilities can transform information advantages into cognitive and action advantages. Russia’s “Battle Command Information System” aims to use artificial intelligence and big data technology to analyze the battlefield environment and provide commanders with a variety of action plans. The UK’s “THEIA Project” and France’s “The Forge” digital decision support engine are both aimed at enhancing information processing capabilities in command and control, intelligence collection, etc., and improving commanders’ ability to control complex battlefields and command effectiveness.

Intelligence reconnaissance field. Compared with traditional intelligence reconnaissance, the use of artificial intelligence algorithms to collect and process intelligence has the advantages of fast information acquisition, wide content sources, and high processing efficiency. The Japanese Self-Defense Forces’ satellite intelligent monitoring system is designed to identify and track foreign ships that may “infringe” its territorial waters near key waters. The U.S. military’s “Causal Exploration of Complex Combat Environments” project aims to use artificial intelligence and machine learning tools to process multi-source information and assist commanders in understanding the cultural motivations, root causes of events, and relationships between various factors behind the war; the “Marvin” project uses machine learning algorithms, face recognition technology, etc. to screen and arrange various suspicious targets from full-motion videos, providing technical support for counter-terrorism and other operations.

Unmanned combat field. In some technologically advanced countries, the unmanned combat system is becoming more mature and the spectrum of equipment types is becoming more complete. The Israeli military’s M-RCV unmanned combat vehicle can perform a variety of tasks such as unmanned reconnaissance, firepower strikes, and the transportation and recovery of drones under all-terrain and all-time conditions. The Russian military’s “Sentinel-R” drone system, which has the ability to detect, track, and strike military targets in real time, also has certain anti-reconnaissance and anti-interference capabilities, and has been tested on the battlefield. The U.S. military’s “Future Tactical Unmanned Aerial Vehicle System” project aims to comprehensively improve the U.S. Army’s ability to perform reconnaissance and surveillance, auxiliary aiming, battle damage assessment, and communication relay missions.

Adapting to future battlefield changes

Constantly exploring new tactics

In order to adapt to the tremendous changes in the battlefield environment in the intelligent era, relevant countries have explored a series of new tactics by improving the efficiency of artificial intelligence’s participation in key military decisions and operations.

Algorithmic warfare, that is, relying on big data and artificial intelligence technology, gives full play to the powerful potential of combat networks, human-machine collaboration, and autonomous and semi-autonomous weapons, so that the “observation-adjustment-decision-action” cycle of the side is always ahead of the opponent, thereby destroying the enemy’s combat plan and achieving preemptive strike. In December 2015, the Russian army relied on unmanned reconnaissance and intelligent command information systems to guide ground unmanned combat platforms to cooperate with Syrian government forces, and quickly eliminated 77 militants within the target range at the cost of 4 minor injuries. In 2021, the US Air Force conducted a test flight of the first intelligent drone “Air Borg”, marking the US military’s algorithmic warfare further moving towards actual combat.

Unmanned warfare is guided by low-cost attrition warfare with saturated quantity attacks and system offensive and defensive operations, and strives to achieve all-round situation tracking, dynamic deterrence and tactical suppression of the enemy’s defense system through human-machine collaboration and group combat modes. In May 2021, the Israeli army used artificial intelligence-assisted drone swarms in the conflict with the Hamas armed group, which played an important role in determining the enemy’s position, destroying enemy targets, and monitoring enemy dynamics. In October 2021 and July 2022, the US military launched drone targeted air strikes in northwestern Syria, killing Abdul Hamid Matar, a senior leader of al-Qaeda, and Aguer, the leader of the extremist organization “Islamic State”, respectively.

Distributed warfare, relying on the unlimited command and control capabilities of artificial intelligence and new electronic warfare means, uses special forces and other shallow-footprint, low-signature, fast-paced forces to form small groups of multi-group mobile formations, infiltrating the combat area in a multi-directional and multi-domain manner, continuously breaking the enemy’s system weaknesses and chain dependence, and increasing the difficulty of its firepower saturation attack. In this process, “people are in command and machines are in control”. In recent years, the US military has successively launched a number of “distributed combat” scientific research projects such as “Golden Tribe” and “Elastic Network Distributed Mosaic Communication”.

Fusion warfare relies on network quantum communications and other means to build an anti-interference, high-speed “combat cloud” to eliminate technical barriers to data link intercommunication, interconnection and interoperability among military services and achieve deep integration of combat forces. In 2021, the joint common basic platform developed by the US Joint Artificial Intelligence Center officially has initial operational capabilities, which will help the US military break down data barriers and significantly improve data sharing capabilities. During the NATO “Spring Storm” exercise held in Estonia in 2021, the British Army used artificial intelligence technology to conduct intelligent analysis and automated processing of battlefield information from various services, improving the integration between services and enhancing the effectiveness of joint command and control.

(Author’s unit: National University of Defense Technology)

現代國語：

適應科技發展大趨勢，搶佔未來戰爭制高點——

人工智慧是大數據、自動化決策、機器學習、圖像識別與空間態勢感知等前沿技術群的統稱，可解放人類智能體能的“認知負擔”，使技術使用者獲得先知、先佔、先發製人的決策行動優勢。作為“力量倍增器”和“未來戰鬥的基礎”，人工智慧將從根本上重塑未來戰爭形態、改變國家傳統安全疆域、衝擊現有軍事技術發展格局、重建未來作戰體系和軍事力量體系，成為未來戰場的重要主導力量。

隨著科技的快速發展和競爭的不斷提速，主要國家紛紛推出自己的人工智慧發展規劃，並加速推動組織機制變革、科技研發和戰術戰法創新，推動人工智慧軍事運用，搶佔未來戰爭制高點。

加速組織形態創新

推進技術轉換應用

有別於傳統的技術，人工智慧的研發和轉化有自身的特點，傳統國防體系的機構設置和運作方式，很難適應人工智慧快速發展的需求。為此，相關國家軍隊大力進行組織體制改革與創新，破除人工智慧技術研發過程中的體制障礙，加速推廣相關技術的轉換與應用。

強調「遠近銜接」。英國以「國防資料辦公室」與「數位整合與國防人工智慧中心」為主體，將路線規劃、規範設定、技術治理與資產開發等能效聚攏整合，破除限制人工智慧技術發展應用的行政阻礙。美國以“戰略能力辦公室”和“首席數位和人工智慧官”為依托，以陸軍未來司令部為試點，將理論開發、技術研發、裝備採辦等分散職能整合到一起，重點以“挖潛增效”方式加強現有平台的創新運用，同時為國防高級研究計畫局的中長期技術創新爭取時間，從而有效兼顧現實需求與長遠發展。

重視「研用轉換」。人工智慧在軍事領域的運用，將對戰場戰斗方式、戰術戰法選擇等方面產生深刻影響。俄羅斯透過組成「先期研究基金會」和「國家機器人技術研發中心」等機構，指導俄軍人工智慧技術的設計、研發與應用工作，以提高科學研究成果的實用轉換率。美國透過設立“聯合人工智慧中心”，依托“國家任務計畫”和“軍種任務計畫”，著力統籌軍地協同創新和科技成果轉化，促進人工智慧在美國國防部和諸軍種的廣泛應用。

注重「軍民一體」。俄羅斯在阿納帕等地設立“時代科技城”等機構，依托“高級研究基金會”，充分吸收軍地人才，積極構建科技生產集群和研究集群，有效拓展軍地人才雙向交流機制。美國透過在矽谷等地設立“國防創新試驗小組”等機構，依托“國防創新委員會”，使人工智慧領域的技術創新與理論發展最新成果可以直接進入高層決策。法國在國防部建立創新防務實驗室、防務創新處等技術研發機構，旨在徵集民間資本投資與國防專案合作，提昇科研能效。

突顯「理技結合」。以色列國防軍設立數位轉型體​​系架構部，依據各類系統有機融入各軍兵種的具體效果，對新技術、新理論、新概念進行充分論證，以確定相應技術研發重點與戰略發展方向。美國透過重設國防部研究與工程副部長、創建首席數位與人工智慧長等職位，提升國防技術創新與應用的統管力度，並依托紅藍對抗、模擬推演、淨評估分析等理論方法，對各類新觀念、新觀念、新方法進行實務檢驗，以選定各類技術研發焦點與策略戰術攻關方向，實現技術發展與理論創新的良性互動。

針對軍事需求立項

搶佔未來發展先機

近年來，各軍事強國瞄準人工智慧前線技術研發，在態勢感知、資料分析、情報偵察、無人作戰等領域廣泛立項，意圖搶佔未來發展先機。

態勢感知領域。傳統意義的態勢感知是指依托衛星、雷達和電子偵察等手段收集和取得戰場資訊。然而，在平戰模糊、兵民一體、內外連動、全域融合的「混合戰爭」條件下，人類域、社會域、認知域等非傳統領域態勢感知的作用受到前所未有的重視。美國「可計算文化理解」項目，旨在透過自然語言處理技術處理多源數據，實現跨文化交流；「指南針」項目，旨在從非結構化數據源中提取案例，整合關鍵訊息，應對不同類型的「灰色地帶」行動。法國「蠍子」戰鬥系統項目，旨在運用智慧化資訊分析與資料共享平台，提升法軍現有前線移動作戰平台的火力支援效力，以保障行動人員安全。

數據分析領域。依託人工智慧技術提高智慧化資料蒐集、識別分析和輔助決策能力，可將資訊優勢轉化為認知和行動優勢。俄羅斯“戰鬥指揮資訊系統”，旨在藉助人工智慧與大數據技術分析戰場環境，為指揮官提供多類行動預案。英國「THEIA計畫」和法國的「The Forge」數位決策支援引擎，都旨在增強指揮控制、情報蒐集等方面的資訊處理能力，提高指揮官駕馭複雜戰場的能力和指揮效能。

情報偵察領域。相較於傳統情報偵察，利用人工智慧演算法蒐集處理情報，具備獲取資訊快、內容來源廣、處理效率高等優勢。日本自衛隊衛星智慧監控系統，旨在識別、追蹤重點水域附近可能「侵犯」其領海的外國船隻。美軍「複雜作戰環境因果探索」項目，旨在利用人工智慧和機器學習工具處理多源訊息，輔助指揮官理解戰爭背後的文化動因、事件根源和各因素關係；「馬文」項目則透過運用機器學習演算法、人臉辨識技術等，從全動態影片中篩選排列出各類可疑目標，為反恐等行動提供技術支撐。

無人作戰領域。一些技術先進的國家，無人作戰體係日臻成熟、裝備種類譜係日趨完善。以軍M-RCV型無人戰車，可在全地形、全時段條件下，執行無人偵察、火力打擊、運載及回收無人機等多樣化任務。具備察打一體能力的俄軍「前哨-R」無人機系統，可即時偵測、追蹤、打擊軍事目標，也具備一定反偵察和抗干擾能力，已在戰場上經過檢驗。美軍「未來戰術無人機系統」項目，旨在全面提升美陸軍執行偵察監視、輔助瞄準、戰損評估、通訊中繼等作戰任務的效能。

適應未來戰場轉變

不斷探索全新戰法

為適應智慧化時代戰場環境的巨大變化，相關國家透過提升人工智慧在各關鍵軍事決策與行動的參與能效，探索出一系列全新戰法。

演算法戰，即以大數據和人工智慧技術為依托，充分發揮作戰網路、人機協作以及自主和半自主武器的強大潛能，使己方「觀察-調整-決策-行動」的循環週期始終領先對手，進而破壞敵作戰計劃，實現先發制人。 2015年12月，俄軍依托無人偵察與智慧化指揮資訊系統，引導地面無人作戰平台與敘利亞政府軍配合，以4人輕傷代價，迅速消滅了目標範圍內的77名武裝分子。 2021年，美空軍進行了首架智慧無人機「空中博格人」的試飛，標誌著美軍演算法戰進一步向實戰化邁進。

無人戰，以飽和數量攻擊、體系攻防作戰的低成本消耗戰為指導，力求透過人機協同、群體作戰模式，實現對敵防禦體系全方位的態勢追蹤、動態威懾和戰術壓制。 2021年5月，以軍在同哈馬斯武裝組織的衝突中使用人工智慧輔助的無人機蜂群，在確定敵人位置、摧毀敵方目標、監視敵方動態等方面發揮了重要作用。 2021年10月和2022年7月，美軍在敘利亞西北部發起無人機定點空襲，分別擊斃「基地」組織高階領導人阿卜杜勒·哈米德·馬塔爾和極端組織「伊斯蘭國」領導人阿蓋爾。

分佈戰，以人工智慧無限指揮控制能力及全新電子戰手段為依托，利用特種部隊等淺腳印、低特徵、快節奏的兵力，形成小股多群機動編隊，以多向多域方式分散滲入作戰區域，持續破擊敵體系短板和鍊式依賴，增加其火力飽和攻擊的難度。在這個過程中，實現「人在指揮、機器在控制」。近年來，美軍相繼啟動「金色部落」「彈性網路分散式馬賽克通訊」等多個「分散式作戰」科學研究立項。

融合戰，依托網路量子通訊等手段，建構抗干擾、高速率的“作戰雲”，以消除軍兵種數據鏈互通、互聯和互操作技術障礙，實現作戰力量的深度融合。 2021年，美聯合人工智慧中心研發的聯合通用基礎平台正式具備初始操作能力，將協助美軍打破資料壁壘，大幅提升資料共享能力。 2021年在愛沙尼亞舉行的北約「春季風暴」演習期間，英軍運用人工智慧技術，對各軍種戰場資訊進行智慧分析與自動化處理，提升了軍種間的融合度，增強了聯合指揮控制效能。

（作者單位：國防科技大學）

中國原創軍事資源：http://www.81.cn/jfjbmap/content/2022-09/01/content_323888.htm

#Information Support Force, #intelligent warfare, #intellligentization, Chinese Artificial Intelligence, Chinese Military Artificial Intelligence Weaponizatio, Chinese Military Characteristics & Development Trends of Cognitive Domain Operations and Warfare

Artificial Intelligence Brings About New Changes in Chinese Military Training

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人工智慧為中國軍事訓練帶來新變化

現代英語：

The widespread application of artificial intelligence in the military has triggered changes in the field of military training, which is reflected in specific training activities, that is, it has given rise to new changes in training elements. This is particularly evident in the fact that intelligent equipment systems have become important training targets, intelligent combat theories have begun to enter training content, and intelligent technology has been deeply integrated into training methods and training support.

The training object has changed from “human-only” to “human-machine hybrid”. The object of traditional military training is a single person. Both the trainer and the trainee are human. Humans are the only object of military training activities. Artificial intelligence technology is embedded or integrated into weapons and equipment, making weapons and equipment that previously required human control have machine intelligence and a certain degree of autonomy. Intelligent robots that can autonomously perform combat missions have appeared in large numbers on modern battlefields, making intelligent unmanned systems and manned systems “close comrades-in-arms”. Mixed operations of “unmanned forces” and “manned forces” will become a new formation pattern. These weapons and equipment with machine intelligence are different from traditional manned weapons and equipment. At their core, they are artificial intelligence algorithms embedded or integrated with learning capabilities. They need to be trained through repeated training in actual combat or battlefield environments that are close to actual combat, so as to accumulate experience and improve performance, and then gradually enhance the actual combat capability of the equipment to fight autonomously. Therefore, weapons and equipment with machine intelligence also need to form and improve their combat capabilities through continuous training and become new trainees. At the same time, training systems with machine intelligence can also become training platforms for military personnel to acquire combat skills or the right-hand man of military training organizers, playing the role of trainers. It can be seen that, with the empowerment of artificial intelligence, weapons and equipment and related systems are gradually becoming the same training targets as military personnel. The targets of military training are no longer just military personnel, but also include weapons and equipment or systems with a certain level of autonomy, presenting a new scene of people training machines, machines training people, and human-machine hybrid training.

The content of training has expanded from “enhancing physical fitness and skills” to “enhancing intelligence and integration”. Training content is the core element of military training and is constantly changing with the development of technical forms and situations and tasks. The content of traditional military training is mainly to enhance the combat fitness, skills and command capabilities of military personnel. The widespread application of artificial intelligence in the military field has made battlefield winning weapons and equipment and systems more and more intelligent, breaking through the limits of human cognition of traditional time and space, reconstructing the relationship between humans and weapons and equipment, incubating new command and control methods, and giving rise to the continuous emergence of new combat methods and the evolution of war forms. Human-machine integration has become a prominent feature of intelligent warfare, and “controlling the brain and seizing intelligence” is the key to winning intelligent warfare. Therefore, military training in the intelligent era will compress traditional military training content and strengthen perception and cognition, human-machine collaboration, intelligent decision-making and command, etc. The training for people is mainly to understand and master the basic principles, thinking concepts, operating skills, and command art of intelligent warfare; the training for intelligent equipment and systems is mainly to improve learning ability, autonomy, collaboration, and the ability to integrate with human intelligence. The main training content system includes thinking training content focusing on intelligent cognition and human-computer interaction, intelligent skill training content focusing on intelligent equipment operation and human-computer interaction, intelligent command training content focusing on giving full play to the advantages of intelligent information systems such as autonomous analysis, auxiliary decision-making, and accurate evaluation, and intelligent coordination training content focusing on autonomous coordination of unmanned intelligent platforms and human-computer collaborative actions. In order to improve the combat reliability of intelligent weapons and equipment and enhance the intelligent system’s understanding of combat intent, the “deep learning” training content of intelligent autonomous weapons and equipment emphasizes enhancing the intelligence of humans and machines, and strengthening the collaborative training of humans and machines, so as to achieve a perfect integration of man and machine.

The training method has moved from “human-dominated” to “human-led”. The way people produce determines the way they fight and the way they train. Traditional military training methods, lacking the support of artificial intelligence technology, are mainly determined based on factors such as the ability characteristics of trainers and the ability foundation of trainees. The organizational form is limited, the implementation procedures are rigid, and the methods and means are single. At present, the intelligence of war is forcing the intelligence of military training. With the help of artificial intelligence technology, military training planning will move from artificial intelligence planning to system intelligence planning. With the assistance of cloud computing, new algorithms, big data analysis and other technologies, the intelligent training system can autonomously generate training plans with requirements on training content, conditions, standards and other aspects according to the training objectives, efficiently assist training planning and improve the quality and efficiency of training planning; training management will leap from artificial extensive type to intelligent and precise type, and the intelligent training system can overcome the traditional training There are problems in management such as incomplete elements, incomplete processes, untimely feedback, and inaccurate guidance. By automatically collecting training data of all elements and the whole process, using artificial intelligence technology to conduct in-depth analysis of training data, analyzing and evaluating the training effectiveness of trainees, generating real-time training evaluation reports, accurately feedback on problems in training, and proposing personalized improvement suggestions, the training method has been transformed from the previous single “human-dominated” type to the “human-host-assisted” “human-dominated” type.

The training environment has extended from “relying on reality” to “virtual and real integration”. Organizing training in a training environment based on real equipment and real scenes is the main mode of traditional military training. This training mode has problems such as high requirements for training venues, large consumption of materials and equipment, great difficulty in training support, long training preparation time, and difficulty in grasping training safety, which makes a certain gap between training and actual combat. Training like fighting is the development direction of military training, and artificial intelligence technology provides conditions for realizing this development direction. The combination of virtual and real can create a more “real” weapon operation experience and battlefield environment, conduct virtual war experiments, realistically simulate combat processes, accurately evaluate combat concepts, and thus narrow the gap between training and actual combat, so that the odds of victory can be established in the laboratory first. Intelligent simulation training systems can be used to repeat, reproduce and create scenes, environments and conditions of classic battles and difficult training courses, and set up difficult and dangerous situations to test and train troops. In individual soldier training, artificial intelligence and technologies such as augmented reality, virtual reality, and simulation are used to provide a “virtual-reality integration” platform and environmental support for the officers and soldiers’ combat skills, physiological functions, and psychological effectiveness training. Officers and soldiers can see, hear, and “touch” the “real” weapons and equipment and battlefield environment; in unit training, a “real” battlefield environment can be set up, a “homogeneous” combat time domain can be created, and a simulated blue army with “both form and spirit” can be built, effectively improving the quality and effectiveness of confrontational training with actual soldiers and equipment, enhancing the training effect of “being in the situation and feeling the same”, and achieving the training goal of “based on reality, with the help of virtuality, and transcending reality”.

現代國語：

人工智慧在軍事領域的廣泛應用，引發了軍事訓練領域的變革，反映在具體訓練活動中，就是催生了訓練要素的新變化。這突顯在智慧化裝備系統成為重要的訓練對象，智慧化作戰理論開始進入訓練內容，智慧化技術深度融入訓練方法與訓練保障。

訓練對象由「人為唯一」轉變為「人機混合」。傳統軍訓的對像是單一的人，組訓者和受訓者都是人，人是軍訓活動的唯一對象。人工智慧技術嵌入或融入武器裝備中，使得以往需要人操控的武器裝備有了機器智能，具備了一定自主性。能夠自主遂行作戰任務的智慧機器人大量出現在現代戰場，使得智能無人系統與有人系統成為“親密戰友”，“無人部隊”與“有人部隊”混編作戰將成為新的編組樣式。這些具有機器智慧的武器裝備不同於傳統有人操控的武器裝備，其核心是嵌入或融入了學習能力的人工智慧演算法，需要在實戰或近似實戰的戰場環境中，通過多次反復的訓練獲取數據來對演算法進行訓練，從而實現經驗累積、性能提升，進而逐步增強裝備自主作戰的實戰能力。因此，具有機器智慧的武器裝備也需要透過不斷訓練來形成和提高作戰能力，成為新的受訓者。與此同時，具有機器智慧的訓練系統還能夠成為軍事人員獲取作戰技能的訓練平台或軍事訓練組訓者的得力助手，扮演組訓者的角色。由此可見，在人工智慧的賦能下，武器裝備及相關係統逐步成為與軍事人員同樣的訓練對象，軍事訓練的對像不再是單一的軍事人員，也包括具有一定自主化程度的武器裝備或系統，呈現人訓機、機訓者、人機混合訓練的新景象。

訓練內容由「增體強技」向「增智強融」拓展。訓練內容是軍事訓練的核心要素，隨著技術形態和形勢任務的發展而不斷變化。傳統軍事訓練的內容主要是為了增強軍事人員的戰鬥體能、技能和指揮能力。人工智慧在軍事領域的廣泛應用，使得戰場制勝的武器裝備和系統越來越具有智慧化的特徵，突破了人類對傳統時空認知的極限，重構了人與武器裝備的關系，孵化了全新的指揮控制方式，催生了新型作戰方式不斷湧現和戰爭形態的嬗變。人機融合成為智慧化戰爭的顯著特徵，「制腦奪智」是製勝智能化戰爭的關鍵。因此，智能化時代的軍事訓練將壓縮傳統軍事訓練內容，加強感知認知、人機協同、智慧決策指揮等內容。針對人的訓練主要是理解和掌握智能化作戰的基本原理、思維理念、操作技能、指揮藝術等；對於智能化裝備和系統的訓練主要是學習能力、自主能力、協同能力以及與人類智能共融的能力。主要訓練內容體系包括以智慧化認知、人機互動為重點的思維訓練內容，以智慧化裝備操作、人機互動為重點的智慧化技能訓練內容，以發揮智慧資訊系統自主分析、輔助決策、精確評估等優勢為重點的智慧化指揮訓練內容，以無人智慧化平台自主協同、人機協同行動等為重點的智慧化協同訓練內容，為提高智慧化武器裝備作戰可靠性、增強智慧化系統對作戰意圖理解力的智慧自主武器裝備「深度學習」訓練內容，突顯增強人和機的智慧、強化人與機的協同訓練，從而達到人機一體的完美融合。

訓練方法由「人為主宰」向「人為主導」邁進。人的生產方式決定了作戰方式，也決定了訓練方式。傳統軍事訓練的方法由於缺乏人工智慧技術支撐，主要是根據組訓人員的能力特點和受訓人員的能力基礎等因素來確定，組織形式受限，實施程序固化，方法手段單一。當前，戰爭的智慧化倒逼軍事訓練的智慧化。在人工智慧技術的助力下，軍事訓練籌劃將由人工集智籌劃向系統智能籌劃邁進，智能化訓練系統在雲計算、新型演算法、大數據分析等技術的輔助下，能夠根據訓練目標自主生成關於訓練的內容、條件、標準等方面指標要求的訓練方案，高效輔助訓練籌劃，提高訓練籌劃的質效；訓練管理由人為粗放型向智能精確型跨越，智能化訓練系統能夠克服傳統訓練管理存在要素不全面、流程不完整、回饋不及時、指導不精確等問題，透過自動採集全要素、全過程訓練數據，利用人工智慧技術對訓練數據進行深度分析，對受訓者的訓練成效進行分析評估，產生即時性訓練評估報告，精準回饋訓練中存在的問題，提出個性化的改進建議，使訓練方法由以往單一的「人為主宰」式向「人主機輔」的「人為主導」式邁進。

訓練環境由「依托現實」延伸至「虛實一體」。依托實裝實景的訓練環境組織訓練是傳統軍事訓練的主要模式。這種訓練模式存在對訓練場地要求高、物資器材消耗大、訓練保障難度大、訓練準備耗時長、訓練安全難把握等問題，使訓練與實戰之間存在一定的差距。像作戰一樣訓練是軍事訓練的發展指向，人工智慧技術為實現這一發展指向提供了條件。利用虛實結合的方式能夠創設更「真實」的武器操作體驗和戰場環境，能夠進行虛擬戰爭實驗，逼真演繹作戰進程，準確評估作戰構想，從而縮小訓練與實戰之間的差異，讓勝算先在實驗室裡奠定。可利用智慧化模擬訓練系統，重復、再現和創設經典戰例、重難點訓練課目的場景、環境及各項條件，設置難局危局險局摔打錘煉部隊。單兵訓練中，運用人工智慧以及增強現實、虛擬現實、模擬模擬等技術，為官兵的戰鬥技能、生理機能、心理效能等訓練提供「虛實融合」的平台與環境支撐，官兵可看到、聽到、「觸摸」到「真實」的武器裝備和戰場環境；部（分）隊訓練中，可以設置「真實」的戰場環境、創造「同質」的作戰時域、打造「神形兼具」的模擬藍軍，有效提升實兵實裝對抗性訓練的質效，增強「身臨其境、感同身受」的訓練效果，達成「基於現實、借助虛擬、超越現實」的訓練目標。

中國原創軍事資源：http://www.81.cn/szb_223187/szbxq/index.html?

#Information Support Force, #intelligent warfare, #intellligentization, Chinese Artificial Intelligence, Chinese Military Artificial Intelligence Weaponizatio

Chinese Military to Distinguish Role and Function of Artificial Intelligence in War

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中國軍方將區分人工智慧在戰爭中的作用和功能

現代英語：

This article reviews the article “Foresight and Judgment: Why Artificial Intelligence Enhances the Importance of Humans in Future Wars” published in the journal “International Security”. It explores the contextual challenges faced by artificial intelligence in the process of war strategic decision-making, as well as the difficulty and uncontrollability of artificial intelligence’s participation in prediction and judgment in a war environment. It analyzes the common decision-making process and characteristics of artificial intelligence in military decision-making, and points out the important role played by human factors.

In recent years, artificial intelligence has developed rapidly and has been widely used in many fields such as business, logistics, communications, transportation, education, communication, translation, etc. The military field also attaches great importance to it. A large number of studies and practices have shown that artificial intelligence can generally replace human work in many positions. Therefore, using artificial intelligence to carry out military operations and dominate all actions in future wars has become the goal of artificial intelligence in the military field. Future wars are essentially wars of artificial intelligence. Avi Goldfarb and Jon R. Lindsay pointed out in the article “Prediction and Judgment: Why Artificial Intelligence Increases the Importance of Humans in War” that in future wars, artificial intelligence cannot replace humans. Artificial intelligence has not weakened the role of humans, but has increased the importance of humans in war. The author believes that artificial intelligence supported by pure machines cannot solve the problems in current and future wars, mainly due to data quality issues and the difficulty of judgment. Coupled with the opponent’s cover-up, deception and interference, the role of artificial intelligence supported by pure machines in future wars will be greatly reduced. The two authors mainly discussed four main aspects: strategic context, artificial intelligence in war, the performance of artificial intelligence in military decision-making, and discussion and reflection on the strategic significance of military artificial intelligence. They discussed that artificial intelligence still cannot replace pure artificial intelligence in current and future wars. On the contrary, the role of humans will still be important in future wars. The analysis process and main points are as follows. In order to facilitate direct evaluation of relevant views, we also gave corresponding comments after the views of all parties.

　　The strategic context of military organizational decision-making poses a huge challenge to artificial intelligence

　　The author points out that the decision-making of military organizations will be affected by many factors. Generally speaking, it may manifest as follows: (1) Political context: The political context is mainly manifested in the strategic environment, facility conditions and psychological preferences; (2) Technical context: The rapid advancement of machine learning can complete more accurate, complex, convenient and larger-scale forecasts including image recognition and navigation; (3) Decision-making process: This process mainly involves the objective facts of goals, values, and environment and the reasoning extracted from them, that is, a process of judgment, data and prediction; (4) Division of labor between man and machine: The application of artificial intelligence is a function of data quality and judgment difficulty. The quality of data and the clarity or difficulty of judgment determine the relative advantages of man and machine in decision-making.

　　It should be said that the author has grasped the main macro-contextual factors that artificial intelligence faces in the process of participating in military decision-making, taking on specific military roles, completing various military tasks, and realizing strategic and campaign intentions. Political context is often the most difficult condition for artificial intelligence to grasp. International politics and domestic politics, especially the instability of international diplomatic relations, the sudden changes in international politics, the stability and mutation of domestic politics, the unpredictability of changes in international geography and natural environment, and the psychological changes of international and domestic personnel are difficult for artificial intelligence to grasp. In terms of technology, although artificial intelligence has developed rapidly, it cannot be separated from its high dependence on data, which makes technological development equivalent to the basic fact in physics, that is, no matter how fast an object moves, it cannot exceed the speed of light. The decision-making process is the most important aspect of artificial intelligence participating in military decision-making and affecting future wars, and it is also the most complex process of military command under the background of war. However, at present, no army of any country or commander of any army can say so confidently that artificial intelligence can make all aspects of decision-making as rational as humans. In the face of huge amounts of data, the biggest advantage of artificial intelligence is computing. However, the prerequisite for humans is that some data does not need to be calculated and conclusions can be drawn by intuition. Moreover, decision-making and command often reflect the commander’s higher wisdom and art. The context of human-machine division of labor actually makes us more aware that more data will be used in war decisions in the future. Humans can hand over the decision-making power of certain matters to artificial intelligence, and necessary decisions must still be made by humans. The actual stage of human-machine division of labor is the harmonious division of labor and human-machine collaboration, especially the emphasis on rationality, humanity, morality and ethics of war by humans.

　　The unreliability of artificial intelligence in prediction and judgment during war

　　(1) Uncontrollable data in the strategic environment inevitably affects predictions: This may be reflected in the data itself and in the acquisition and use of data. The more prominent manifestations in data are: data falsification, data restriction, data control, data invalidity, and inability to analyze. The main manifestations in the source of data and data analysis are: there are many data sources and it is difficult to predict; data analysis is limited by technology; the scope of data continues to expand with the development of the network, diluting effective data; network systems and software are susceptible to interference from multiple parties; hackers and multiple parties harassment; conflicts among multiple technologies.

　　(2) Military management judgment cannot be separated from human participation: Artificial intelligence faces many challenges in the process of participating in military management. First, military management judgment is a highly subjective issue. Second, the use of machine learning to complete this calculation process is also inevitably affected by human judgment. Third, the function used by AI has clear goals, and all relevant parties are guided by common goals to reach a consensus and exert the leadership and command of the troops. The command of the army often faces different military services, branches, and units. Their respective skills, tactics, capabilities, and cognition will be different. When artificial intelligence is used to solve these collective action problems, huge disputes are inevitable, which often makes the problem worse.

　　In this section, the author points out two fatal weaknesses that artificial intelligence must face in participating in military command, and at least cannot be solved at present: one is that the reliability of data is difficult to guarantee, and the other is the problem of human participation. Regarding the reliability of data, in the course of war, there are often a lot of data that are difficult to distinguish between true and false. In addition to the controllability of data, as an opponent or a third party, they may intentionally control certain aspects of data, and the data provided may also be arranged with special content and logical relationships. It is even possible to intentionally distort the data and provide irrational scattered data, making the data analysis results irrelevant and unable to draw effective conclusions, thus losing the ability to judge. Humans will not solve the problem that human participation is necessary in the judgment process of artificial intelligence for a long time in the future. The current artificial intelligence is designed by humans. Although it can be trained and optimized through a large amount of data, humans do not allow artificial intelligence to break away from the regulations and constraints of humans in advance. Artificial intelligence is completely determined by its own design, optimization and upgrade. Considering that the military decision-making process is full of variables, it is impossible to completely hand over a military decision-making process to artificial intelligence. What artificial intelligence can accomplish is to automatically transmit data and analyze large quantities of data and provide results. If general management decisions can be handed over to artificial intelligence, then the real key decisions still need to be made manually. In fact, considering the decision-making of military management, especially the more complex, challenging and controlled decision-making and process in the war environment, artificial intelligence still has a long way to go to perfectly reflect the personal decision-making charm and intention of the commander, and to fully realize the collective integrated action of the army and the personalized command of diversified military services. Under human war conditions, each combatant, especially the end and senior commander of the combatant, has many variables in the execution of the war. For example, changes in wind, rain, ice and snow, rivers, lakes and seas, fighting will, road conditions, transportation capacity, production operation, material supply, etc. often lead to emergencies. Therefore, the actual battlefield often has more variables than design. In the many judgments of military management and battlefield decision-making, even under the conditions of future intelligent combat, human participation will still be dominant.

　　Artificial intelligence has limited involvement in military decision-making tasks

　　The article points out that artificial intelligence embodies four decision-making processes in the military decision-making task mechanism, and also embodies four corresponding decision-making characteristics, which are mainly manifested as follows.

　　Automated decision-making process: The best example of AI performance is “automated decision-making”. First, it can reduce the work of administrative agencies. Second, AI helps to improve the efficiency and scale of routine activities. Finally, AI helps to optimize logistics supply chains. But even in these tasks, the intervention of human judgment is the basis and scale of automated decision-making.

　　Manual decision-making process: AI cannot perform tasks characterized by limited, biased data and ambiguous, controversial judgments, which must be completed by human decision-making. For military strategy and command tasks, the “fog” in the environment and the “friction” in the organization all require human “ingenuity” to solve. Whenever the “fog” and “friction” are the greatest and human “genius” is most needed, the role of AI becomes weak.

　　Decision-making automation process: Premature automation mainly refers to the intervention of AI when the conditions are not mature. Relying on AI is particularly dangerous when the data quality is low, but the machine has a clear goal and is authorized to act. The risk is greatest when the killing action is authorized. In addition, the data may be biased, and the machine may not understand human behavior well. The risks of premature automation are extreme in the military field (for example, friendly fire and civilian casualties). AI weapons may inadvertently target innocent civilians or friendly forces, or provoke hostile retaliation. As a result, AI often kills without regard for the consequences.

　　Human-machine cooperation process: Human-machine cooperation refers to the need for the joint cooperation of humans and machines in the processing of large amounts of information. In fact, many judgment tasks are difficult, and human intervention is necessary to obtain high-quality data. In practice, intelligence analysts have an instinct to deal with deceptive targets and ambiguous data, and it is difficult for artificial intelligence to learn this instinct-based ability. Applying artificial intelligence to the judgment of such problems is a difficult and challenging practice. However, in human-machine cooperation, artificial intelligence is more about solving complex and large data and analyzing complex problems under human guidance. However, whether it is high-quality data analysis or the final decision, the dominant force is still people.

　　The above lists the role of artificial intelligence in four different decision-making modes in the current military decision-making mechanism. Although the author did not say it explicitly, we can feel that these four processes either require human participation or the role of artificial intelligence is limited; in this overall process, artificial intelligence is also showing a weakening trend. These four processes can be reinterpreted as: artificial intelligence dominates the automatic decision-making process, artificial intelligence decision-making is limited in the manual decision-making process, decision-making is prematurely automated in the decision-making automation process, and human experience is difficult to replace in the human-machine cooperation process. In the first process, it is obvious that artificial intelligence can demonstrate its advantages in routine routine work, big data repetitive tasks, and programmed procedural activities. However, even in such activities, the scale and basis of human judgment are still the key to the realization of artificial intelligence. In the second process, it is mainly those cases where the data is small, the attitude is strong, the subjectivity is prominent, and the judgment is very easy to be ambiguous. Due to insufficient data, machine learning is difficult to complete, and each case may have specific changes, and it is impossible to form an overall judgment scale. In such a situation, artificial intelligence is often difficult to act. Humans’ unique values, worldviews, outlooks on life, moral emotions, personal spiritual realms, and personal work experiences often lead to very reasonable judgments on decisions like this, which is difficult for artificial intelligence to accomplish for the time being. Although there are still many experiments in this area, the ability of humans to comprehensively call on personal comprehensive knowledge, emotions, and value judgments in decision-making is significantly better than that of artificial intelligence. In the third process, the decision-making automation process has the advantages of huge data volume, fast data processing response, real-time data analysis results, and a reader-friendly interface. Therefore, for many problems, people are particularly inclined to collect relevant data from the beginning and use artificial intelligence to conduct data learning and analysis. However, since the data may have just begun to appear, or the data is easy to be manipulated or arranged, the actual data obtained is often only the front end of the actual data. Therefore, whether it is deep learning with artificial intelligence or data analysis with artificial intelligence, there will be premature automated analysis, and the trained artificial intelligence or the results of the analysis cannot fully identify the issues of concern. In fact, when we conduct research on any problem, it is difficult to guarantee that the data we obtain in a certain aspect represents all the data of the problem we are concerned about. Although the external data looks huge, this data may only be extremely biased or extremely local, extremely early or even immature data about the relevant things. The artificial intelligence based on this, whether it is training or calculation, the result is premature calculation, prematurely representing all the problem data information. And artificial intelligence itself, due to its high dependence on data, is difficult to escape the pre-determination of the data itself. Therefore, in the context of war, if the data of artificial intelligence is often interfered with, destroyed, deceived, manipulated and designed by relevant parties, then the decision-making judgments made by artificial intelligence are often unreliable, even very dangerous or tragic. Therefore, the outcome of leaving the war completely to artificial intelligence must be terrible: either the war has unlimited intensity, or there will be inhumane killings. After all, it is difficult for artificial intelligence to make rational value judgments and humane emotional decisions. In the fourth process, the author highly emphasizes that in human-machine cooperation, human judgment can produce a high level of judgment in deceptive, slightly different, ambiguous, unclear data and diversified data. This is an instinct generated by professional experience. Although artificial intelligence can obtain some amazing conclusions in the study of big data, such analysis standards and strategies can never escape human design and are constantly adjusted under human intervention. Of course, we must also point out that artificial intelligence’s values, moral sense, humanity and emotions cannot surpass humans in any way. Although it can have super knowledge content, logic and computing power, at present and for a long time in the future, considering the auxiliary data processing status of artificial intelligence in human-machine cooperation, even if artificial intelligence reaches human sensitivity, complexity, sharpness, consciousness and intuition, we will still give the complex and important final decision-making power to humans themselves.

　　In response to the above situation, the author discussed and reflected on the role of artificial intelligence in war and came to the following conclusions: First, the artificial intelligence data and judgments used by military organizations rely on human intervention; second, opponents in war have the motivation to complicate the data and judgments that artificial intelligence relies on; third, it is too early for artificial intelligence machines to replace human soldiers; finally, the unintended consequences and controversies brought about by artificial intelligence-driven wars are becoming increasingly prominent. For this reason, the author emphasizes that it is too early to assume that artificial intelligence will replace humans in war or any other competitive activities. Whether from the environment and conditions of the war itself, the process of war decision-making, the deep learning and computing of artificial intelligence in war, and the performance of artificial intelligence in the execution of military tasks, there is every reason to believe that even in future wars dominated by artificial intelligence, the role of humans will become increasingly important.

　　Here, the author puts forward a view that is very different from the current mainstream view: military artificial intelligence will not replace human dominance in war, but will instead highlight the prominent position and role of artificial intelligence in future wars. The author’s view should be worthy of deep thinking by artificial intelligence researchers, especially military artificial intelligence researchers. The author analyzes from many aspects why artificial intelligence cannot be independent of humans, act alone, and take on major tasks in future wars: the diverse context of war brings insurmountable challenges to artificial intelligence; the prediction and judgment of artificial intelligence in war cannot be reliable; artificial intelligence has limited ability to participate in military decision-making and cannot completely replace human participation and decision-making. In particular, it emphasizes the difficulty of grasping war itself, the unpredictability of multiple factors, the elusiveness and deliberate design and deception of all parties involved, the complexity, variability, deception, uncontrollability and difficulty in ensuring the authenticity of the war data obtained, and the vulnerability of artificial intelligence in prediction and judgment: the problems solved by artificial intelligence, the basis for solving them, the process of solving them, the procedures for solving them and the models for solving them are all affected by human factors, as well as the limited ability of artificial intelligence to participate in military decision-making. These three aspects show that artificial intelligence still faces many challenges in war and give us important inspiration: it is too early for artificial intelligence to dominate the future battlefield and become a truly independent warrior and war commander in future wars. Only humans are the masters and rulers of war. Due to the high degree of dominance of humans in the design of artificial intelligence, we hope that the day when artificial intelligence dominates war will never come. As humans, we expect that when artificial intelligence is galloping on the track of war, the developers of artificial intelligence should also always take ethical emotions and international law, the law of war and humanitarianism as the bottom line. This is the basic guarantee for peaceful development, harmonious development and harmonious development on the earth, and the pursuit of beauty, peace and happiness.

　　At present, we are paying close attention to the rapid development of artificial intelligence. In particular, the development of ChatGPT, which can handle all kinds of challenges in daily chatting, knowledge search, question answering, problem solving, programming, business management, project planning, language translation, paper writing, and literary creation, has indeed sounded the alarm for many positions that undertake deep mental work. However, no matter how artificial intelligence develops, no matter how subversive artificial intelligence like ChatGPT develops in the military field, humans are the leaders of artificial intelligence and the masters of war, and only humans can ensure the humanity, legitimacy, and effectiveness of war. I hope that the development of artificial intelligence can eliminate war.

現代國語：

摘要：本文評論了《國際安全》期刊上發表的《預見與判斷：為什麼人工智慧增強了人在未來戰爭中的重要性》一文，探討了人工智慧在戰爭戰略決策過程中所面臨的脈絡挑戰問題，以及戰爭環境下人工智慧參與預測與判斷的難度與不可控性，分析了軍事決策中人工智慧常見的決策過程及其特點，指出其中人工因素所扮演的重要角色。

近年來，人工智慧發展迅猛，被廣泛應用於商業、物流、通訊、交通、教育、傳播、翻譯等眾多領域，軍事領域也對其高度重視。大量研究和實踐表明，人工智慧大體可以取代人類在眾多崗位上的工作，因此，用人工智慧進行軍事行動並主導未來戰爭中的所有行動成為人工智慧在軍事領域的目標。未來戰爭，實質是人工智慧的戰爭。高德法伯與喬恩R.林賽在《預見與判斷：為什麼人工智慧增強了人在未來戰爭中的重要性》（Prediction and Judgment: Why Artificial Intelligence Increases the Importance of Humans in War）一文中指出，未來戰爭中，人工智慧不可能取代人類，人工智慧不但沒有弱化人類的作用，相反也增強了人類在戰爭中的重要性。作者認為，純粹機器支援下的人工智慧解決不了當下和未來戰爭中的問題，主要是數據的品質問題以及判斷的困難性，加上對手的掩蓋、欺騙和乾擾，純粹機器支持下的人工智慧在未來戰爭中的作用將大打折扣。兩位作者主要從戰略脈絡、戰爭中的人工智慧、人工智慧在軍事決策中的表現以及軍事人工智慧戰略意義的討論與反思四個主要方面論述了人工智慧在當下及未來戰爭中依然無法取代純人工，相反，人類的角色在未來戰爭中依舊重要。其分析過程和主要觀點如下所示。為了便於對相關觀點直接做出評價，我們也一併在各方觀點之後給出了相應的評論。

軍事組織決策的戰略脈絡為人工智慧帶來了巨大挑戰

作者指出，軍事組織的決策會受到多方面的影響，整體說來，可能會表現為如下情況：（1）政治脈絡：政治脈絡主要表現為戰略環境與設施條件與心理偏好；（2）技術脈絡：機器學習的快速推進可以完成包括影像辨識、導航等在內的更精準、複雜、便捷以及更大數量上的預報；（3）決策過程：本過程主要涉及目標、價值、環境的客觀事實以及由此抽取的推理，也就是一個判斷、數據以及預測的過程；（4）人機分工：人工智慧的運用都是數據品質和判斷困難性所形成的函數，數據的品質高低、判斷的明確或困難決定了人機在決策上的相對優勢。

應該說，作者此處抓住了當前人工智慧參與軍事決策、擔任軍事具體角色、完成各種軍事任務、實現戰略戰役意圖過程中面臨的主要宏觀語境因素。政治脈絡往往是人工智慧最難掌握的條件，國際政治與國內政治，特別是國際間外交關係不穩定、國際政治的風雲突變、國內政治的穩定與突變性、國際地理和自然環境變化的不可預測性、國際與國內人員的心理變化等，是人工智慧難以掌握的。在技​​術方面，儘管人工智慧快速發展，但是，其無法脫離對資料的高度依賴性，這使得技術發展等同於物理學中的基本事實，即物體的移動速度再快也無法超越光速限制。決策過程，是人工智慧參與軍事決策影響未來戰爭的最重要的方面，也是戰爭背景下軍事指揮最為複雜的過程。但是，目前還沒有哪一個國家的軍隊、哪一個軍隊的指揮官能夠如此自信地說，人工智慧可以將決策的所有環節做到像人一樣有獨特的理性。面對龐大的數據，人工智慧的最大優勢是計算，但是，人類的先決條件是，有些數據不需要計算，憑直覺便能得出結論，更何況決策指揮往往體現指揮員更為高超的智慧與藝術。人機分工的脈絡其實讓我們愈發體認到，未來將有更多數據運用到戰爭決策中，人類可以將某些事務的決策權交給人工智慧，必要的決策仍要由人類來做。人機分工實際走向的階段，是人機的和諧分工與人機協同，特別是人類對戰爭的理性、人性、道德與倫理的重視。

戰爭中人工智慧在預測與判斷上的不可靠性

（1）戰略環境的不可控制資料難免影響預測：這可能表現在資料本身以及資料的取得與使用。資料方面較突出的表現為：資料造假、資料受限、資料受控、資料無效、無法分析等。在資料的源頭和資料分析中的主要表現為：資料來源眾多，難以預料；資料分析受技術限制；資料範圍隨網路發展不斷擴大，稀釋有效資料；網路系統和軟體易受多方幹擾；駭客以及多方的襲擾；多種技巧的衝突。

（2）軍事管理的判斷無法脫離人工參與：人工智慧在參與軍事管理過程中面臨眾多考驗。第一，軍事管理的判斷是個主觀性極強的問題。第二，運用機器學習來完成這個計算過程也不得不受人為判斷影響。第三， AI所使用的函數目標明確，各相關方為共同目標所牽引達成一致，發揮部隊領導指揮力。軍隊的指揮往往要面臨不同軍兵種、分支機構、單位人員，各自的技戰術、能力以及認知等都會有差異，讓人工智慧來解決這些集體行動問題時，難免會出現巨大的爭議，往往會使得問題變得更糟。

在這部分，作者指出了人工智慧參與軍事指揮中不可不面對，而且至少當下無法解決的兩個致命弱點：一個是數據的可靠性難以保證，一個是人工參與問題。關於數據的可靠性，在戰爭過程中，數據往往存在大量真假難辨的情況。再加上數據的受控性，作為對手一方以及第三方，可能有意控制某方面的數據，提供的數據也做了特殊內容以及邏輯關係的安排，甚至還有可能將數據做有意歪曲以及提供無理性的分散數據，使得數據分析結果毫無關聯性，也無法得出有效結論，從而喪失判斷能力。人類在未來很長一段時間內不會解決人工智慧判斷過程中必須有人工參與此問題。當下的人工智慧都是由人類設計出來的，儘管可以透過大量資料進行訓練以及優化，但是，當下人類還不允許人工智慧脫離人類事先的規定和約束，完全由人工智慧來決定自身的設計與優化和升級。考慮到軍事決策過程充滿了變數，不可能將一個軍事決策過程完全交給人工智慧來完成。人工智慧能夠完成的，就是自動化的傳遞數據以及大量的數據分析並提供結果。如果說一般的管理決策可以交給人工智慧來完成，那麼真正的關鍵決策，還是要交給人工來實現。實際上，考慮到軍事管理的決策，特別是戰爭環境下更為複雜、更具有挑戰性、更為受控的決策與過程，人工智慧要想完美體現指揮官的個人決策魅力和意圖，要想完全實現軍隊集體一體化行動以及多樣化軍兵種的個人化指揮，還有很長的路要走。人類戰爭條件下，每一個參戰方，特別是作戰者末端和高級指揮方對戰爭的執行有著很多的變量，比如，風雨冰雪、江河湖海、戰鬥意志、道路狀況、運輸能力、生產運行、材料補給等方面的變化往往會導致突發狀況。因此，實際的戰場往往變數大於設計。在軍事管理與戰場決策的眾多判斷中，即便是在未來智慧化作戰條件下，人工的參與將依舊處於主導地位。

人工智慧在軍事決策任務機制中參與受限

文章指出，人工智慧在軍事決策任務機制中體現了四種決策過程，也體現了相應的四種決策特點，其主要表現如下。

自動決策過程：人工智慧效能的最佳案例就是「自動決策」。首先，它可以減少行政機構的工作。其次，人工智慧有助於提高常規活動的效率和規模。最後，人工智慧有利於優化物流供應鏈。但即便是在這些任務中，人的判斷的介入才是自動決策提供決策的依據和判斷的尺度。

人工決策過程：人工智慧無法執行以有限、有偏見的數據和模棱兩可、有爭議的判斷為特徵的任務，這必須要人工決策來完成。對於軍事戰略和指揮任務來說，環境中的「迷霧」、組織中的「摩擦」等都需要人類的「聰明才智」來解決。每當「迷霧」和「摩擦」最大，最需要人類「天才」的時候，人工智慧的作用就變得弱小了。

決策自動化過程：過早的自動化主要是指在條件不成熟的情況下進行人工智慧的介入。在資料品質低但機器有明確目標並獲得授權採取行動的情況下，依賴人工智慧尤其危險。當授權採取殺戮行動時，風險最大。另外，數據也可能有偏差，而且機器也不能很好地理解人類的行為。過早自動化的風險在軍事領域是極端的（例如，誤傷和平民傷亡）。人工智慧武器可能無意中以無辜平民或友軍為目標，或引發敵對報復。因此，AI 往往會不顧及後果地殺人。

人機合作過程：人機合作指的是在大量資訊處理中需要人工和機器的共同協作。實際上，在許多判斷任務中困難重重，要獲得高品質的數據必須介入人工。在實踐中，情報分析人員處理欺騙性目標和模糊資料有著一種本能，人工智慧難以學到這種基於本能的能力。將人工智慧應用到這類問題的判斷中是一項困難和挑戰性極大的實踐。但是，人工智慧在人機合作中更多的還是在人工指導下解決複雜、龐大的數據以及分析複雜問題。不過，無論是高品質的數據分析，還是最後的決策，主導力量仍然是人。

以上羅列了當前人工智慧在參與軍事決策機制過程中，四種不同決策模式情況下人工智慧所扮演的角色。儘管作者沒有明說，但是我們能夠感覺到，這四個過程要不是需要人工的參與，就是人工智慧的作用受限；在這個整體過程中，人工智慧還隱約呈現出弱化的趨勢。這四個過程可以重新解讀為：自動決策過程中人工智慧占主導地位，人工決策過程中人工智慧決策受限，決策自動化過程中決策過早自動化以及人機合作過程中人工經驗難以取代。在第一個過程中，顯然人工智慧能夠體現自身在常規慣例性工作、大數據重複性任務、程式化程序性活動中的優勢，但是，即便是在這類活動中，人的判斷尺度和依據依舊是人工智慧得以實現的關鍵。在第二個過程中，主要是那些數據偏小、態度性強、主觀性突出、判斷極易出現模棱兩可情況，由於數據量不足，機器學習難以完成，而且每一個個案可能都有具體變化，無法形成總體的判斷尺度，在這樣的情況下，人工智慧往往難以作為。人類獨有的價值觀、世界觀、人生觀、道德情感、個人精神境界以及個人工作經驗，往往會對類似這樣的決策做出非常合理的判斷，這個是人工智慧一時難以完成的，儘管這方面的實驗依舊很多，但是人類決策中綜合調用個人綜合知識以及情感與價值判斷的能力明顯優於人工智慧。在第三個過程中，決策自動化過程由於具有資料量龐大、處理資料反應快、分析資料結果即時化、讀者介面親近友善等優勢，因此，對於許多問題來說，人們特別傾向於一開始就將相關數據集合起來，並利用人工智慧進行數據學習和分析，但由於數據可能剛開始呈現，或者數據易被操控或者安排，實際獲得數據往往只是實際數據的前端部分，因此，無論是用人工智能進行深度學習還是用人工智慧進行資料的分析，都會出現過早自動化分析的情況，所訓練的人工智慧或說分析的結果都無法全面標識所關心的問題。而實際上，我們在進行任何問題研究時，很難保證我們獲取的某個方面的數據代表了所關心問題的全部數據，儘管外部數據看上去很龐大，但是這個數據很可能只是有關事物的極為偏態或極為局部、極為初期乃至不成熟的資料。在此基礎上的人工智慧，無論是訓練和計算，其結果都是過早計算，過早代表了問題資料資訊的全部。而人工智慧自身，由於對於資料的高度依賴性，很難逃離資料本身的先設決定。因此，在戰爭背景下，如果人工智慧的數據經常受到有關方面的干擾、破壞、欺騙、操控與設計，那麼，人工智慧得出的決策判斷往往是不可信賴，甚至是非常危險或可悲的。因此，完全把戰爭交給人工智慧的結局肯定是可怕的：要么是戰爭出現了無限制的烈度，要么出現慘無人道的殺戮，畢竟人工智慧很難做到人類理性的價值判斷以及人道情感決策。在第四個過程中，作者高度強調了人機合作中，人工的判斷能夠在欺騙性、微小差別、模棱兩可、模糊不清的數據以及多樣化數據中產生一種高水平的判斷，這是一種職業經驗產生的本能；儘管人工智慧能在大數據的學習中獲取某些讓人驚嘆的結論，但是這樣的分析標準和策略，始終逃脫不過人工的設計，也始終在人工的干預下不斷調整。當然，我們也要指出的是，人工智慧的價值觀、道德感、人性和情感，無論如何是超越不了人類的，儘管其可以具備超強的知識含量、邏輯性和計算能力，但是在目前和未來相當長一段時間，考慮到人工智慧在人機合作中的輔助處理資料地位，即便人工智慧達到人類的敏感、複雜、敏銳、自覺與直覺，我們仍會將複雜而重要的最後決策權交給人類本身。

針對以上情況，作者對人工智慧在戰爭中的作用做了一番討論和反思，得出如下結論：首先，軍事組織使用的人工智慧數據和判斷都依賴人工的干預；其次，戰爭中的對手有動機使人工智慧依賴的數據和判斷複雜化；再一次，現在人工智慧機器取代人類戰士所帶來的優勢還為時過早；最後，人工智慧所驅動的戰爭帶來的不可意想的後果和爭議日益突出。為此，作者強調，現在就認為人工智慧將在戰爭或任何其他競爭活動中取代人類還為時過早。無論從戰爭本身的環境和條件，戰爭決策的過程，戰爭的人工智慧深度學習與運算，以及人工智慧參與軍事任務執行的表現來看，有充分的理由相信，即便是未來在由人工智慧主導的戰爭中，人類的角色也會愈加重要。

此處，作者提出了與當下主流觀點很是相左的觀點：軍事人工智慧不會在戰爭中取代人類的主導，相反還會凸顯人工在未來戰爭中的突出地位與作用。作者的觀點應該值得人工智慧研究者，特別是軍事人工智慧研究者的深度思考。作者從多方面分析了人工智慧無法做到在未來戰爭中獨當一面、獨立人類、獨行其道、獨當大任：戰爭的多樣化語境為人工智慧帶來不可逾越的挑戰；戰爭中人工智慧的預測與判斷無法做到可靠；人工智慧在軍事決策中參與能力有限、無法完全取代人類的參與和決策。特別是強調了戰爭本身的難以捉摸性、多方因素的不可預測性、各參與者的難以捉摸和刻意設計與欺騙性，所獲得的戰爭數據的複雜性、多變性、欺騙性、不可控制性、難以確保真實性，人工智慧在預測和判斷中的脆弱性：人工智慧所解決的問題、解決的依據、解決問題的過程、解決的程序以及解決的模型都受人工因素的影響，以及人工智慧在軍事決策中參與能力的受限三大面向，向人們展示了戰爭中人工智慧還面臨諸多挑戰，給了我們重要的啟示：人工智慧要主宰未來戰場，成為未來戰爭中真正獨立於人類之外的戰士和戰爭指揮者，還為時過早。唯有人類才是戰爭的主人和主宰者。由於人類對人工智慧設計的高度主宰性，我們希望人工智慧主宰戰爭這一天永遠不會到來。當人類的我們期望人工智慧在戰爭的賽道上疾馳時，人工智慧的開發者也要把倫理情感和國際法、戰爭法、人道主義始終作為底線，這是在地球上和平發展、和諧發展、和諧發展，追求美好、追求和平、追求幸福的基本保證。

當前，我們對人工智慧的快速發展高度關注。特別是ChatGPT的發展，它在日常聊天、知識搜尋、問題回應、難題解題、編寫程式、經營管理、專案規劃、語言翻譯、論文撰寫、文學創作等方面能夠接受百般刁難，確實已向承擔深度腦力工作的眾多崗位拉響了警報。但是，無論人工智慧如何發展，無論類似ChatGPT這樣具有顛覆性的人工智慧在軍事領域怎樣發展，人類才是人工智慧的主導者和戰爭中的主宰者，也只有人類才能確保戰爭的人道性、合法性和有效性。但願人工智慧的發展能夠消滅戰爭。

原文責任編輯：舒建軍 馬氍鴻

（本文註釋內容略

中國原創軍事資源：https://www.cssn.cn/dkzgxp/zgxp_gjshkxzzzwb/gjshkxzz202301/202308/t20230807_5677376.shtml

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Chinese Weaponization of Digitalization, Networking, Intelligence, Grasping the Focus New Chinese Generation of Information Technology

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數位化、網路化、智慧化的中國武器化，抓住中國新一代資訊科技的焦點

現代英語：

Digitalization, networking, and intelligence are the prominent features of the new round of scientific and technological revolution, and are also the core of the new generation of information technology. Digitalization lays the foundation for social informatization, and its development trend is the comprehensive dataization of society. Dataization emphasizes the collection, aggregation, analysis and application of data. Networking provides a physical carrier for information dissemination, and its development trend is the widespread adoption of information-physical systems (CPS). Information-physical systems will not only give birth to new industries, but will even reshape the existing industrial layout. Intelligence reflects the level and level of information application, and its development trend is the new generation of artificial intelligence. At present, the upsurge of the new generation of artificial intelligence has arrived.

　　In his important speech at the 2018 General Assembly of Academicians of the Chinese Academy of Sciences and the Chinese Academy of Engineering, Comrade Xi Jinping pointed out: “The world is entering a period of economic development dominated by the information industry. We must seize the opportunity of the integrated development of digitalization, networking, and intelligence, and use informatization and intelligence as leverage to cultivate new momentum.” This important statement is an accurate grasp of the dominant role and development trend of information technology in today’s world, and an important deployment for using information technology to promote national innovation and development.

　　Human society, the physical world, and information space constitute the three elements of today’s world. The connection and interaction between these three worlds determine the characteristics and degree of social informatization. The basic way to perceive human society and the physical world is digitization, the basic way to connect human society and the physical world (through information space) is networking, and the way information space acts on the physical world and human society is intelligence. Digitalization, networking, and intelligence are the prominent features of the new round of scientific and technological revolution, and are also the focus of the new generation of information technology. Digitalization lays the foundation for social informatization, and its development trend is the comprehensive dataization of society; networking provides a physical carrier for information dissemination, and its development trend is the widespread adoption of information-physical systems (CPS); intelligence reflects the level and level of information application, and its development trend is the new generation of artificial intelligence.

　　Digitalization: From computerization to dataization

　　Digitalization refers to the technical approach of storing, transmitting, processing, handling and applying information carriers (text, pictures, images, signals, etc.) in digital coding form (usually binary). Digitalization itself refers to the way of representing and processing information, but in essence it emphasizes the computerization and automation of information application. In addition to digitalization, dataization (data is an information carrier in coded form, and all data is digital) emphasizes the collection, aggregation, analysis and application of data, and strengthens the production factors and productivity functions of data. Digitalization is developing from computerization to dataization, which is one of the most important trends in the current social informatization.

　　The core connotation of dataization is the deep understanding and deep use of big data generated by the integration of information technology revolution and economic and social activities. Big data is a fragmentary record of social economy, real world, management decision-making, etc., containing fragmented information. With the breakthrough of analytical technology and computing technology, it is possible to interpret this fragmented information, which makes big data a new high-tech, a new scientific research paradigm, and a new way of decision-making. Big data has profoundly changed the way people think and live and work, bringing unprecedented opportunities to management innovation, industrial development, scientific discovery and other fields.

　　The value generation of big data has its inherent laws (obeying the big data principle). Only by deeply understanding and mastering these laws can we improve the awareness and ability to consciously and scientifically use big data (big data thinking). The value of big data is mainly realized through big data technology. Big data technology is an extension and development of statistical methods, computer technology, and artificial intelligence technology. It is a developing technology. The current hot directions include: blockchain technology, interoperability technology, storage and management technology of integrated storage and computing, big data operating system, big data programming language and execution environment, big data foundation and core algorithm, big data machine learning technology, big data intelligent technology, visualization and human-computer interaction analysis technology, authenticity judgment and security technology, etc. The development of big data technology depends on the solution of some major basic problems, including: the statistical basis and computational theoretical basis of big data, the hardware and software basis and computational methods of big data computing, and the authenticity judgment of big data inference.

　　Implementing the national big data strategy is an important way to promote the digital revolution. Since my country proposed the implementation of the national big data strategy in 2015, the pattern of rapid development of big data in my country has been initially formed, but there are also some problems that need to be solved: data openness and sharing are lagging, and the dividends of data resources have not been fully released; the profit model of enterprises is unstable, and the integrity of the industrial chain is insufficient; core technologies have not yet made major breakthroughs, and the technical level of related applications is not high; there are still loopholes in security management and privacy protection, and the construction of relevant systems is still not perfect; etc. At present, effective measures should be taken to solve the bottleneck problems that restrict the development of big data in my country.

　　Networking: From the Internet to Cyber-Physical Systems

　　As an information-based public infrastructure, the Internet has become the main way for people to obtain, exchange and consume information. However, the Internet only focuses on the interconnection between people and the resulting interconnection between services.

　　The Internet of Things is a natural extension and expansion of the Internet. It connects various objects to the Internet through information technology, helping people obtain relevant information about the objects they need. The Internet of Things uses information collection equipment such as radio frequency identification, sensors, infrared sensors, video surveillance, global positioning systems, laser scanners, etc., and connects objects to the Internet through wireless sensor networks and wireless communication networks, so as to achieve real-time information exchange and communication between objects and between people and objects, so as to achieve the purpose of intelligent identification, positioning, tracking, monitoring and management. The Internet realizes the interconnection between people and services, while the Internet of Things realizes the cross-connection between people, objects and services. The core technologies of the Internet of Things include: sensor technology, wireless transmission technology, massive data analysis and processing technology, upper-level business solutions, security technology, etc. The development of the Internet of Things will go through a relatively long period, but it may take the lead in achieving breakthroughs in applications in specific fields. Internet of Vehicles, Industrial Internet, unmanned systems, smart homes, etc. are all areas where the Internet of Things is currently showing its prowess.

　　The Internet of Things mainly solves the problem of people’s perception of the physical world, while to solve the problem of manipulating physical objects, it is necessary to further develop the cyber-physical system (CPS). The cyber-physical system is a multi-dimensional complex system that integrates computing, networking and physical environment. It realizes real-time perception, dynamic control and information services of large engineering systems through the organic integration and deep collaboration of 3C (Computer, Communication, Control) technologies. Through the human-computer interaction interface, the cyber-physical system realizes the interaction between the computing process and the physical process, and uses the networked space to control a physical entity in a remote, reliable, real-time, secure and collaborative manner. In essence, the cyber-physical system is a network with control attributes.

　　Unlike public infrastructure that provides information interaction and application, the focus of the development of cyber-physical systems is on the research and development of networked physical equipment systems that deeply integrate perception, computing, communication and control capabilities. From an industrial perspective, cyber-physical systems cover a range of applications from smart home networks to industrial control systems and even intelligent transportation systems, which are national and even world-class applications. More importantly, this coverage is not just about simply connecting existing devices together, but will give rise to a large number of devices with computing, communication, control, collaboration and autonomous capabilities. The next generation of industry will be built on cyber-physical systems. With the development and popularization of cyber-physical system technology, physical devices that use computers and networks to achieve functional expansion will be ubiquitous, and will promote the upgrading of industrial products and technologies, greatly improving the competitiveness of major industrial fields such as automobiles, aerospace, national defense, industrial automation, health and medical equipment, and major infrastructure. Cyber-physical systems will not only give birth to new industries, but will even reshape the existing industrial layout.

　　Intelligence: From Expert Systems to Meta-Learning

　　Intelligence reflects the quality attributes of information products. When we say that an information product is intelligent, we usually mean that the product can accomplish things that only intelligent people can accomplish, or has reached a level that only humans can achieve. Intelligence generally includes perception, memory and thinking, learning and adaptive, behavioral decision-making, etc. Therefore, intelligence can also be generally defined as: enabling an object to have sensitive and accurate perception functions, correct thinking and judgment functions, adaptive learning functions, and effective execution functions.

　　Intelligence is the eternal pursuit of the development of information technology, and the main way to achieve this pursuit is to develop artificial intelligence technology. In the more than 60 years since the birth of artificial intelligence technology, although it has experienced three ups and two downs, it has still made great achievements. From 1959 to 1976, it was a stage based on artificial representation of knowledge and symbol processing, which produced expert systems with important application value in some fields; from 1976 to 2007, it was a stage based on statistical learning and knowledge self-representation, which produced various neural network systems; in recent years, research based on environmental adaptation, self-game, self-evolution, and self-learning is forming a new stage of artificial intelligence development – meta-learning or methodological learning stage, which constitutes a new generation of artificial intelligence. The new generation of artificial intelligence mainly includes big data intelligence, group intelligence, cross-media intelligence, human-machine hybrid enhanced intelligence, and brain-like intelligence.

　　Deep learning is an outstanding representative of the new generation of artificial intelligence technology. Due to its performance that surpasses that of humans in many fields such as face recognition, machine translation, and chess competitions, deep learning has almost become synonymous with artificial intelligence today. However, deep learning has major challenges in terms of topological design, effect prediction, and mechanism explanation. There is no solid mathematical theory to support the solution of these three major problems. Solving these problems is the main focus of future research on deep learning. In addition, deep learning is a typical big data intelligence, and its applicability is based on the existence of a large number of training samples. Small sample learning will be the development trend of deep learning.

　　Meta-learning is expected to become the next breakthrough in the development of artificial intelligence. Recently developed meta-learning methods such as learning to learn, learning to teach, learning to optimize, learning to search, and learning to reason, as well as the outstanding performance of “AlphaGo Zero” in Go, have demonstrated the attractive prospects of such new technologies. However, meta-learning research is only just beginning, and its development still faces a series of challenges.

　　The new generation of artificial intelligence is already here, and the foreseeable development trend is based on big data, centered on model and algorithm innovation, and supported by powerful computing power. The breakthrough of the new generation of artificial intelligence technology depends on the comprehensive development of other types of information technology, as well as the substantial progress and development of brain science and cognitive science. (Xu Zongben, academician of the Chinese Academy of Sciences and professor of Xi’an Jiaotong University)

現代國語：

數位化、網路化、智慧化是新一輪科技革命的突出特徵，也是新一代資訊科技的核心。數位化為社會資訊化奠定基礎，其發展趨勢是社會的全面數據化。資料化強調對資料的收集、聚合、分析與應用。網路化為資訊傳播提供實體載體，其發展趨勢是資訊物理系統（CPS）的廣泛採用。資訊物理系統不僅會催生出新的工業，甚至會重塑現有產業佈局。智慧化體現資訊應用的層次與水平，其發展趨勢為新一代人工智慧。目前，新一代人工智慧的熱潮已經來臨。

習近平同志在2018年兩院院士大會上的重要演講指出：「世界正進入以資訊產業為主導的經濟發展時期。我們要把握數位化、網路化、智慧化融合發展的契機，以資訊化、智慧化為槓桿培育新動能。

人類社會、物理世界、資訊空間構成了當今世界的三元。這三元世界之間的關聯與交互，決定了社會資訊化的特徵與程度。感知人類社會和物理世界的基本方式是數位化，連結人類社會與物理世界（透過資訊空間）的基本方式是網路化，資訊空間作用於物理世界與人類社會的方式是智慧化。數位化、網路化、智慧化是新一輪科技革命的突出特徵，也是新一代資訊科技的聚焦點。數位化為社會資訊化奠定基礎，其發展趨勢是社會的全面資料化；網路化為資訊傳播提供物理載體，其發展趨勢是資訊物理系統（CPS）的廣泛採用；智慧化體現資訊應用的層次與水平，其發展趨勢是新一代人工智慧。

數位化：從電腦化到資料化

數位化是指將資訊載體（文字、圖片、影像、訊號等）以數位編碼形式（通常是二進位）進行儲存、傳輸、加工、處理和應用的技術途徑。數位化本身指的是資訊表示方式與處理方式，但本質上強調的是資訊應用的電腦化和自動化。資料化（資料是以編碼形式存在的資訊載體，所有資料都是數位化的）除包括數位化外，更強調對資料的收集、聚合、分析與應用，強化資料的生產要素與生產力功能。數位化正從電腦化朝向資料化發展，這是當前社會資訊化最重要的趨勢之一。

資料化的核心內涵是對資訊科技革命與經濟社會活動交融生成的大數據的深刻認識與深層利用。大數據是社會經濟、現實世界、管理決策等的片段記錄，蘊含著片段化資訊。隨著分析技術與運算技術的突破，解讀這些片段化資訊成為可能，這使得大數據成為一項新的高新技術、一類新的科學研究範式、一種新的決策方式。大數據深刻改變了人類的思考方式和生產生活方式，為管理創新、產業發展、科學發現等多個領域帶來前所未有的機會。

大數據的價值生成有其內在規律（服從大數據原理）。只有深刻認識並掌握這些規律，才能提高自覺運用、科學運用大數據的意識與能力（大數據思維）。大數據的價值主要透過大數據技術來實現。大數據技術是統計學方法、電腦技術、人工智慧技術的延伸與發展，是正在發展中的技術，目前的熱點方向包括：區塊鏈技術、互通技術、存算一體化儲存與管理技術、大數據作業系統、大數據程式語言與執行環境、大數據基礎與核心演算法、大數據機器學習技術、大數據智慧技術、視覺化與人機互動分析技術、真偽判定與安全技術等。大數據技術的發展依賴一些重大基礎問題的解決，這些重大基礎問題包括：大數據的統計基礎與計算理論基礎、大數據計算的軟硬體基礎與計算方法、大數據推斷的真偽性判定等。

實施國家大數據戰略是推動資料化革命的重要途徑。自2015年我國提出實施國家大數據戰略以來，我國大數據快速發展的格局已初步形成，但也存在一些亟待解決的問題：數據開放共享滯後，數據資源紅利仍未得到充分釋放；企業贏利模式不穩定，產業鏈完整性不足；核心技術尚未取得重大突破，相關應用的技術水準不高；安全管理與隱私保護還存在漏洞，相關制度建設仍不夠完善；等等。目前，應採取有效措施解決制約我國大數據發展的瓶頸問題。

網路化：從網際網路到資訊物理系統

作為資訊化的公共基礎設施，網路已成為人們獲取資訊、交換資訊、消費資訊的主要方式。但是，網路關注的只是人與人之間的互聯互通以及由此帶來的服務與服務的互聯。

物聯網是互聯網的自然延伸和拓展，它透過資訊科技將各種物體與網路相連，幫助人們獲取所需物體的相關資訊。物聯網透過使用射頻識別、感測器、紅外線感應器、視訊監控、全球定位系統、雷射掃描器等資訊擷取設備，透過無線感測網路、無線通訊網路把物體與網路連接起來，實現物與物、人與物之間的即時資訊交換和通信，以達到智慧化識別、定位、追蹤、監控和管理的目的。互聯網實現了人與人、服務與服務之間的互聯， 而物聯網實現了人、物、服務之間的交叉互聯。物聯網的核心技術包括：感測器技術、無線傳輸技術、大量資料分析處理技術、上層業務解決方案、安全技術等。物聯網的發展將經歷相對漫長的時期，但可能會在特定領域的應用中率先取得突破，車聯網、工業互聯網、無人系統、智慧家庭等都是當前物聯網大顯身手的領域。

物聯網主要解決人對物理世界的感知問題，而要解決對物理對象的操控問題則必須進一步發展資訊物理系統（CPS）。資訊物理系統是一個綜合運算、網路和物理環境的多維複雜系統，它透過3C（Computer、Communication、Control）技術的有機融合與深度協作，實現對大型工程系統的即時感知、動態控制和資訊服務。透過人機交互接口，資訊物理系統實現計算進程與實體進程的交互，利用網路化空間以遠端、可靠、即時、安全、協作的方式操控一個實體實體。從本質上來說，資訊物理系統是一個具有控制屬性的網路。

不同於提供資訊互動與應用的公用基礎設施，資訊物理系統發展的聚焦點在於研發深度融合感知、運算、通訊與控制能力的網路化實體設備系統。從產業角度來看，資訊物理系統的涵蓋範圍小到智慧家庭網路、大到工業控制系統乃至智慧交通系統等國家級甚至世界級的應用。更重要的是，這種涵蓋並不僅僅是將現有的設備簡單地連在一起，而是會催生出眾多具有計算、通訊、控制、協同和自治性能的設備，下一代工業將建立在在資訊物理系統之上。隨著資訊物理系統技術的發展和普及，使用電腦和網路實現功能擴展的實體設備將無所不在，並推動工業產品和技術的升級換代，大大提高汽車、航空航太、國防、工業自動化、健康醫療設備、重大基礎設施等主要工業領域的競爭力。資訊物理系統不僅會催生出新的工業，甚至會重塑現有產業佈局。

智能化：從專家系統到元學習

智能化反映資訊產品的品質屬性。我們說一個資訊產品是智慧的，通常是指這個產品能完成有智慧的人才能完成的事情，或是已經達到人類才能達到的程度。智能一般包括知覺能力、記憶與思考能力、學習與適應力、行為決策能力等。所以，智能化通常也可定義為：使對象具備靈敏準確的感知功能、正確的思考與判斷功能、自適應的學習功能、行之有效的執行功能等。

智能化是資訊科技發展的永恆追求，實現這項追求的主要途徑是發展人工智慧技術。人工智慧技術誕生60多年來，雖歷經三起兩落，但還是取得了巨大成就。 1959—1976年是基於人工表示知識和符號處理的階段，產生了在一些領域具有重要應用價值的專家系統；1976—2007年是基於統計學習和知識自表示的階段，產生了各種各樣的神經網路系統；近幾年開始的基於環境自適應、自博弈、自進化、自學習的研究，正在形成一個人工智慧發展的新階段——元學習或方法論學習階段，這構成新一代人工智慧。新一代人工智慧主要包括大數據智慧、群體智慧、跨媒體智慧、人機混合增強智慧和類腦智慧等。

深度學習是新一代人工智慧技術的卓越代表。由於在人臉辨識、機器翻譯、棋類競賽等眾多領域超越人類的表現，深度學習在今天幾乎已成為人工智慧的代名詞。然而，深度學習拓樸設計難、效果預期難、機理解釋難是重大挑戰，還沒有一套堅實的數學理論來支持解決這三大難題。解決這些難題是深度學習未來研究的主要關注點。此外，深度學習是典型的大數據智能，它的可應用性是以存在大量訓練樣本為基礎的。小樣本學習將是深度學習的發展趨勢。

元學習有望成為人工智慧發展的下一個突破口。學會學習、學會教學、學會優化、學會搜尋、學會推理等新近發展的元學習方法以及「AlphaGo Zero」在圍棋方面的出色表現，展現了這類新技術的誘人前景。然而，元學習研究僅是開始，其發展還面臨一系列挑戰。

新一代人工智慧的熱潮已經來臨，可以預見的發展趨勢是以大數據為基礎、以模型與演算法創新為核心、以強大的運算能力為支撐。新一代人工智慧技術的突破依賴其他各類資訊技術的綜合發展，也依賴腦科學與認知科學的實質進步與發展。 （中國科學院院士、西安交通大學教授 徐宗本）

中國原創軍事資源：https://www.cac.gov.cn/2019-03/01/c_1124178478.htm

#Information Support Force, #intelligent warfare, #intellligentization, #中國太空軍, #中國的耗散戰, #中國軍事人工智慧武器化, China's Informatization - 中國信息化, Chinese Artificial Intelligence, Chinese Military Artificial Intelligence Weaponizatio, Chinese Military Future Wars, Chinese Military Views - 中國軍事觀, 中國軍隊對耗散戰的戰術運用, 認知域戰

China’s Position Paper : Regulating Military Applications of Artificial Intelligence

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中國的立場文件：規範人工智慧的軍事應用

現代英語：

The rapid development and widespread application of artificial intelligence technology are profoundly changing human production and lifestyles, bringing huge opportunities to the world while also bringing unpredictable security challenges. It is particularly noteworthy that the military application of artificial intelligence technology may have far-reaching impacts and potential risks in terms of strategic security, governance rules, and moral ethics.

AI security governance is a common issue facing mankind. With the widespread application of AI technology in various fields, all parties are generally concerned about the risks of AI military applications and even weaponization.

Against the backdrop of diverse challenges facing world peace and development, all countries should uphold a common, comprehensive, cooperative and sustainable global security concept and, through dialogue and cooperation, seek consensus on how to regulate the military applications of AI and build an effective governance mechanism to prevent the military applications of AI from causing significant damage or even disasters to humanity.

Strengthening the regulation of the military application of artificial intelligence and preventing and controlling the risks that may arise will help enhance mutual trust among countries, maintain global strategic stability, prevent an arms race, alleviate humanitarian concerns, and help build an inclusive and constructive security partnership and practice the concept of building a community with a shared future for mankind in the field of artificial intelligence.

We welcome all parties including governments, international organizations, technology companies, research institutes and universities, non-governmental organizations and individual citizens to work together to promote the safe governance of artificial intelligence based on the principle of extensive consultation, joint construction and sharing.

To this end, we call for:

– In terms of strategic security, all countries, especially major powers, should develop and use artificial intelligence technology in the military field with a prudent and responsible attitude, not seek absolute military advantage, and prevent exacerbating strategic misjudgments, undermining strategic mutual trust, triggering escalation of conflicts, and damaging global strategic balance and stability.

– In terms of military policy, while developing advanced weapons and equipment and improving legitimate national defense capabilities, countries should bear in mind that the military application of artificial intelligence should not become a tool for waging war and pursuing hegemony, and oppose the use of the advantages of artificial intelligence technology to endanger the sovereignty and territorial security of other countries.

– In terms of legal ethics, countries should develop, deploy and use relevant weapon systems in accordance with the common values ​​of mankind, adhere to the people-oriented principle, uphold the principle of “intelligence for good”, and abide by national or regional ethical and moral standards. Countries should ensure that new weapons and their means of warfare comply with international humanitarian law and other applicable international law, strive to reduce collateral casualties, reduce human and property losses, and avoid the misuse of relevant weapon systems and the resulting indiscriminate killing and injury.

– In terms of technical security, countries should continuously improve the security, reliability and controllability of AI technology, enhance the security assessment and control capabilities of AI technology, ensure that relevant weapon systems are always under human control, and ensure that humans can terminate their operation at any time. The security of AI data must be guaranteed, and the militarized use of AI data should be restricted.

– In terms of R&D operations, countries should strengthen self-discipline in AI R&D activities, and implement necessary human-machine interactions throughout the weapon life cycle based on comprehensive consideration of the combat environment and weapon characteristics. Countries should always insist that humans are the ultimate responsible party, establish an AI accountability mechanism, and provide necessary training for operators.

– In terms of risk management, countries should strengthen supervision of the military application of artificial intelligence, especially implement hierarchical and classified management to avoid the use of immature technologies that may have serious negative consequences. Countries should strengthen the research and judgment of the potential risks of artificial intelligence, including taking necessary measures to reduce the risk of proliferation of military applications of artificial intelligence.

——In rule-making, countries should adhere to the principles of multilateralism, openness and inclusiveness. In order to track technological development trends and prevent potential security risks, countries should conduct policy dialogues, strengthen exchanges with international organizations, technology companies, technology communities, non-governmental organizations and other entities, enhance understanding and cooperation, and strive to jointly regulate the military application of artificial intelligence and establish an international mechanism with universal participation, and promote the formation of an artificial intelligence governance framework and standard specifications with broad consensus.

– In international cooperation, developed countries should help developing countries improve their governance level. Taking into account the dual-use nature of artificial intelligence technology, while strengthening supervision and governance, they should avoid drawing lines based on ideology and generalizing the concept of national security, eliminate artificially created technological barriers, and ensure that all countries fully enjoy the right to technological development and peaceful use.

現代國語：

人工智慧技術的快速發展及其廣泛應用，正深刻改變人類生產和生活方式，為世界帶來巨大機會的同時，也帶來難以預測的安全挑戰。特別值得關注的是，人工智慧技術的軍事應用，在戰略安全、治理規則、道德倫理等方面可能產生深遠影響和潛在風險。

人工智慧安全治理是人類面臨的共同課題。隨著人工智慧技術在各領域的廣泛應用，各方普遍對人工智慧軍事應用甚至武器化風險感到擔憂。

在世界和平與發展面臨多元挑戰的背景下，各國應秉持共同、綜合、合作、永續的全球安全觀，透過對話與合作，就如何規範人工智慧軍事應用尋求共識，建構有效的治理機制，避免人工智慧軍事應用為人類帶來重大損害甚至災難。

加強對人工智慧軍事應用的規範，預防和管控可能引發的風險，有利於增進國家間互信、維護全球戰略穩定、防止軍備競賽、緩解人道主義關切，有助於打造包容性和建設性的安全夥伴關係，在人工智慧領域實踐建構人類命運共同體理念。

我們歡迎各國政府、國際組織、技術企業、科研院校、民間機構和公民個人等各主體秉持共商共建共享的理念，協力共同促進人工智慧安全治理。

為此，我們呼籲：

——戰略安全上，各國尤其是大國應本著慎重負責的態度在軍事領域研發和使用人工智慧技術，不謀求絕對軍事優勢，防止加劇戰略誤判、破壞戰略互信、引發衝突升級、損害全球戰略平衡與穩定。

——在軍事政策上，各國在發展先進武器裝備、提高正當國防能力的同時，應銘記人工智慧的軍事應用不應成為發動戰爭和追求霸權的工具，反對利用人工智慧技術優勢危害他國主權和領土安全的行為。

——法律倫理上，各國研發、部署和使用相關武器系統應遵循人類共同價值觀，堅持以人為本，秉持「智能向善」的原則，遵守國家或地區倫理道德準則。各國應確保新武器及其作戰手段符合國際人道法和其他適用的國際法，努力減少附帶傷亡、降低人員財產損失，避免相關武器系統的誤用惡用，以及由此引發的濫殺。

——在技術安全上，各國應不斷提昇人工智慧技術的安全性、可靠性和可控性，增強對人工智慧技術的安全評估和管控能力，確保相關武器系統永遠處於人類控制之下，保障人類可隨時中止其運作。人工智慧資料的安全必須得到保證，應限制人工智慧資料的軍事化使用。

——研發作業上，各國應加強對人工智慧研發活動的自我約束，在綜合考慮作戰環境和武器特性的基礎上，在武器全生命週期實施必要的人機互動。各國應時常堅持人類是最終責任主體，建立人工智慧問責機制，對操作人員進行必要的訓練。

——風險管控上，各國應加強對人工智慧軍事應用的監管，特別是實施分級、分類管理，避免使用可能產生嚴重負面後果的不成熟技術。各國應加強對人工智慧潛在風險的研判，包括採取必要措施，降低人工智慧軍事應用的擴散風險。

——規則制定上，各國應堅持多邊主義、開放包容的原則。為追蹤科技發展趨勢，防範潛在安全風險，各國應進行政策對話，加強與國際組織、科技企業、技術社群、民間機構等各主體交流，增進理解與協作，致力於共同規範人工智慧軍事應用並建立普遍參與的國際機制，推動形成具有廣泛共識的人工智慧治理框架和標準規範。

——國際合作上，已開發國家應協助發展中國家提升治理水平，考慮到人工智慧技術的軍民兩用性質，在加強監管和治理的同時，避免採取以意識形態劃線、泛化國家安全概念的做法，消除人為製造的科技壁壘，確保各國充分享有技術發展與和平利用的權利。

中國原創軍事資源：https://www.mfa.gov.cn/web/wjb_673085/zzjg_673183/jks_674633/zclc_674645/rgzn/202206/t20220614_10702838.shtml