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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, #intellligentization, 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 Intelligentization, Chinese Military Use of Cognitive Confrontation within the Combat Domain, Chinese Military Views - 中國軍事觀, Dissipative Warfare, 認知域戰, 認知戰

“Studying the Military, Studying War, Studying Fighting” Chinese Military Special Topic: The Key to Winning Cognitive Warfare

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「學軍事、學戰爭、學打仗」中國軍事專題：打贏認知戰爭的關鍵

現代英語：

Information Network: The Key to Winning the Cognitive War

■Zhai Chan

introduction

In today’s era of information and intelligent integration, information networks, with their advantages of deep reach, wide popularity, and strong interactivity, will play an irreplaceable and important role in cognitive warfare. With the support of information networks, cognitive warfare will be more powerful and more scalable. A deep understanding of the mechanism, laws, basic forms, methods and means of cognitive warfare of the role of information networks will help to timely control the initiative of cognitive warfare and lay the foundation for victory.

The Mechanism and Laws of Information Networks and Cognitive Warfare

The essence of cognitive warfare in the role of information networks is to provide massive amounts of information through core algorithms, create biased cognitive scenarios, and influence the thinking and cognition of people and intelligent machines. This process integrates the operating rules of information networks and the internal mechanisms of thinking and cognition, has strong predictability, and is the underlying structure and key point that must be grasped in information network cognitive warfare.

The stickiness effect based on path dependence. The highly developed information network in today’s society provides a platform that people cannot live without for learning, working, living, entertainment, military construction, combat and military struggle preparation, forming an interconnected path dependence between each other. This platform uses information as the core and the network as the medium. Through invisible stickiness, it connects different groups of people, societies, countries and the military together, connecting the entire world into a closely connected global village. Objectively, it also provides a bridge and a link for conducting cognitive operations, influencing the opponent’s thinking and cognition, and winning cognitive wars. In 2009, US Secretary of State Hillary Clinton delivered an “Internet Freedom” speech, advocating the “Internet Freedom” strategy, attempting to use the channel formed by people’s high dependence on the Internet to influence the thinking and cognition of the people of the opponent country, especially the younger generation, and spread American values.

Interactive influence based on information exchange. Education believes that interactive communication can effectively overcome the cognitive barriers formed by one-way information transmission, reach consensus, form empathy, and strengthen empathy through mutual information exchange, emotional integration, and mutual needs. A big difference between information networks and traditional communication media is that they provide a carrier that can interact and communicate on a large scale, at a fast pace, and with high efficiency. In this carrier, the party with strong information can repeatedly confirm the influence, adjust methods and strategies, and intervene in the thinking and cognition of the other party through the interactive mechanism provided by the carrier, based on the other party’s thought fluctuations, emotional changes, attitude feedback, etc. For a long time, the United States has maintained a “engagement + containment” strategy toward China. One very important consideration is that this kind of engagement can effectively overcome the communication barriers and information gaps formed by simple blockade and confrontation, enhance the interaction between the two governments and peoples, and thus find opportunities to open gaps and influence our ideas and ideologies. Although this strategy takes place in the traditional field, it is inherently consistent with the interactive influence mechanism of information networks based on information exchange.

The seductive influence based on the preset scene. The concealment, virtuality and permeability of the information network allow its controllers to create extremely deceptive, tempting and inflammatory information scenes through water army flooding, information filtering and “fishing in troubled waters” and other technical and strategic means, so that the opponent is deeply trapped in it without knowing it, and instead develops towards the preset process and results. This directional manipulation of the information network can subtly and efficiently influence, infect and shape the opponent’s thinking and cognition, so that the opponent is unconsciously led by the rhythm, and the combat effect is far better than the confrontation. On the eve of the Iraq War, the US media spread false information such as the existence of weapons of mass destruction in Iraq through the Internet and other platforms, accusing the Saddam regime of collusion with al-Qaeda, rampant corruption, and unprovoked harm to the Iraqi people. At the same time, they tried every means to cover up the truth, filter out the anti-war voices of their own people, and strive to create an atmosphere that the Saddam regime is evil and hateful and that the whole of America is united in hatred of the enemy.

The basic form of cognitive warfare in the role of information networks

The laws of war and the mechanism of victory determine the basic form of war. The laws and mechanisms of cognitive warfare based on information networks inherently determine the external forms of this war. The most basic and representative ones include information confusion warfare, misleading thinking warfare, and will-destroying warfare.

Information confusion warfare. It is to infuse the network with a large amount of complex information that combines the real and the fake, which is both true and illusory, so that the enemy’s information network capacity is overloaded, malfunctions, and disordered operations, or causes specific audiences to become “deaf, blind, and insensitive”, have cognitive abilities blocked, and their thinking, cognition, and decision-making judgments are hindered. This form of warfare is often used in the early stages of combat and in opaque battlefields. The party with information advantage can make the enemy fall into a state of panic and bewilderment, resulting in perception failure, loss of thinking, and self-disorder. Bloomberg reported that the Space Force, the sixth branch of the U.S. military that was recently established, plans to purchase 48 jammer systems by 2027, aiming to disrupt satellite signals “in the event of a conflict with a major power.” Many national militaries generally feel that the information they receive is not too little but too much. The massive amount of information coming from all directions has put tremendous pressure on situation perception and analysis and judgment.

Misleading thinking warfare. This is to form a biased information scene by instilling specific information that contains the intentions of the party controlling the information network, misleading, deceiving and influencing the thinking of specific countries, armies and people, causing them to deviate from the correct development track and deviate in a direction that is beneficial to oneself and detrimental to the enemy. It is the highest level and common practice of cognitive attack. This kind of misleading is based on strong external pressure, on specious strategies, and on information mixed with water as a weapon. It targets the opponent’s thinking characteristics and weak links, and implements clear-cut deception, causing the opponent to lose his way in tension and panic, and fall into the “trap” unknowingly. In recent years, while implementing the great power competition strategy, some countries have used cyber trolls to fabricate false situations, create false information, and spread true rumors to fan the flames around our country and encourage some countries that have historical grievances with our country and frictions with our country in reality to seek trouble. The purpose is to induce us to divert our attention, weaken the investment of resources and strength in the main strategic direction, deviate from the track of great power rejuvenation, and seek to reap the benefits of the two fishermen.

Will-destroying war. Futurist Alfred Toffler said that whoever controls the human mind controls the entire world. War is ultimately a confrontation between people. People’s psychological activities largely affect their mental state, which in turn affects their will to fight. Will-destroying war is different from traditional warfare that indirectly affects people’s will through material destruction. It directly affects the psychological activities, mental state and thinking decisions of key figures, thus affecting military morale, fighting will and combat actions. With the development of science and technology and social progress, the intervention in people’s will has entered the stage of “technology + strategy” from the traditional strategy-based intervention. More than a decade ago, scientists developed a “sound beam” weapon that uses an electromagnetic network to emit extremely narrow sound waves from hundreds of meters away, interfering with the enemy’s judgment and even causing mental confusion among strong-willed soldiers. In recent years, studies have shown that artificial speech synthesis technology based on brain wave signals can extract signals from the brain and synthesize speech that humans can directly understand.

Information networks are the main means of cognitive warfare

“Technology + strategy” constitutes the basic means of modern cognitive warfare. As a product of modern scientific and technological development, the information network’s means of effecting cognitive warfare are also mainly reflected in “technology + strategy”. This provides us with a basic entry point for understanding and grasping the ways and scientific paths of information network’s effect on cognitive warfare, thereby winning the war.

Big data construction. As the core component of the information network, data is not only the carrier of information, but also the “new oil” driven by the value of the information network, and the basic ammunition for cognitive warfare. Through massive data, complex information scenarios are constructed for my use, or the opponent’s cognitive confusion, or misleading and deceiving thinking, or destroying beliefs and wills are formed, which constitutes the basic logic of cognitive warfare in the information network. In this logical framework, data is undoubtedly the most basic resource and the most core element. A few years ago, authoritative departments calculated that the world produces about 2.5 exabytes (EB) of data every day, of which only 20% is structured data that can be directly used, and the remaining 80% needs to be analyzed, identified, and screened. These data resources, which are growing exponentially, provide an inexhaustible supply of “data ammunition” for constructing data information scenarios and conducting cognitive warfare.

Intelligent push. In the information network era, intelligent push has become a convenient channel for people to absorb external information, gain identification of thinking, emotional resonance, and influence the thinking and cognition of others. Using advanced technologies such as artificial intelligence to collect, organize, and analyze people’s thinking habits and behavioral preference data to form personalized and customized perception push can produce an “echo wall” of social cognitive trends and an information cocoon that shackles people. At the same time, it is also conducive to empathizing with others, understanding the thinking trends and possible actions of opponents, and taking targeted countermeasures. In our daily lives, we all have the experience of receiving a large amount of similar information after shopping online or searching for certain types of information. This intelligent push method is applied to cognitive operations, which can easily enable the information leader to use information network data to conduct forward-looking analysis and judgment on the decisions and actions that may be made by the command and decision-making level of the combat target, and induce them to make the decision-making actions they hope to see or make corresponding response measures in advance.

Emotional infiltration. Freud said that we are not pure wisdom or pure souls, but a collection of impulses. In the information network space, the concepts that can be widely and quickly disseminated are often not calm, rational, and objective thinking and analysis, but mostly impulsive and irrational emotional mobilization. This is determined by the fast pace of information dissemination and news release. The cognitive need to respond quickly to this information, in turn, leads to the reflexive, impulsive, and emotional response of “fast thinking”, which transforms seemingly isolated social cases into highly coercive and inflammatory psychological hints and behavioral drives, and explosively promotes irrational decision-making and actions. In June 2009, a diplomatic cable disclosed by WikiLeaks described the lavish banquets held by the family of Tunisia’s Ben Ali regime and described the regime as a corrupt and tyrannical “mafia”. This deepened the resentment of the country’s citizens and became an important driving force behind the “Jasmine Revolution” that overthrew the Ben Ali regime.

現代國語：

來源：解放軍報 作者：翟嬋 責任編輯：劉上靖 2021-11-18 06:49:14
資訊網絡：認知戰制勝要津

■翟 嬋

引 言

在資訊化智慧化融合發展的當今時代，資訊網絡以其觸角深、受眾廣、互動性強等優勢，在認知戰中將發揮無可取代的重要作用。有了資訊網絡的加持，認知戰將如虎添翼、如魚得水。深刻掌握資訊網絡作用認知戰的機理規律、基本形態、方法手段等，有助於及時掌控認知戰主動權，為贏得勝利奠定基礎。

資訊網絡作用認知戰的機理規律

資訊網絡作用認知戰的本質在於透過核心演算法，提供大量訊息，營造傾向性認知場景，影響人和智慧機器的思維認知。這個過程融合資訊網絡運行規律和思維認知內在機理，具有很強的可預知性，是資訊網絡認知戰必須把握的底層架構和關鍵之點。

基於路徑依賴的黏性影響。當今社會高度發達的資訊網絡，提供了一個人們學習、工作、生活、娛樂，軍隊建設、作戰和軍事鬥爭準備須臾離不開的平台，在彼此之間形成一個互聯互通的路徑依賴。這一平台以資訊為核、網絡為媒，透過無形的黏性把不同人群、社會、國家包括軍隊連接在一起，既將整個世界打通成一個緊密聯繫的地球村，客觀上也為開展認知作戰、影響對手思維認知、制勝認知戰爭提供了橋樑和紐帶。 2009年美國國務卿希拉裡曾發表「互聯網自由」演說，鼓吹「互聯網自由」戰略，企圖利用人們對互聯網的高度依賴形成的作用通道，影響對手國民眾特別是青年一代的思維認知，傳播美式價值觀。

基於資訊交換的互動影響。教育學認為，互動交流能有效克服訊息單向傳遞所形成的認知屏障，在彼此訊息交換、情感融通、需求相促中達成共識、形成同理心、強化同理。資訊網絡與傳統交流溝通媒介的一個很大不同，在於提供了一個能大範圍、快節奏、高效率互動交流的載體。在這一載體中，資訊強勢一方能透過載體提供的互動機制，依據另一方的思想波動、情緒變化、態度回饋等，反復確認影響，調整方法策略，幹預另一方的思維認知。長期以來，美國對華保持「接觸+遏制」戰略，一個很重要的考慮就在於這種接觸能有效克服單純封鎖對抗形成的溝通壁壘和信息鴻溝，增強兩國政府和民眾之間的互動，從而尋找機會打開缺口，影響我們的思想觀念和意識形態。這項戰略雖然發生在傳統領域，但與資訊網絡基於資訊交換的互動影響機理內在一致。

基於預設場景的誘導影響。資訊網絡的隱蔽性、虛擬性、滲透性，使其掌控者能通過水軍灌水、資訊過濾、「渾水摸魚」等技術和謀略手段，營造極具欺騙性、誘惑性、煽動性的信息場景，使對手深陷其中而不自知，反而朝著預設的過程和結果發展。這種對資訊網絡的指向性操控，能潛移默化地高效影響、感染和塑造對手的思維認知，使之不知不覺被帶節奏，收到遠比對抗硬槓好得多的作戰效果。伊拉克戰爭前夕，美國媒體透過網路等平台大肆散佈伊拉克存在大規模殺傷性武器等虛假訊息，指責薩達姆政權與基地組織相互勾連、腐敗成風，還無端殘害伊拉克人民，同時又想方設法掩蓋事實真相，過濾本國人民的反戰聲音，極力營造薩達姆政權邪惡可恨、全美上下同仇敵愾的氛圍。

資訊網絡作用認知戰的基本形態

戰爭規律和製勝機理決定戰爭的基本形態。資訊網絡作用認知戰的規律機理內在規定著這種戰爭的外在呈現形態。其中最基本、最具代表性的包括資訊迷茫戰、思維誤導戰和意志毀傷戰。

資訊迷茫戰。就是用海量虛實結合、亦真亦幻的復雜信息灌注網絡，使敵對方信息網絡容量過載、功能失常、運轉失序，或導致特定受眾對象“失聰失明失感”、認知能力擁堵、思維認知和決策判斷受阻。這一戰爭形態常用於作戰初期和不透明戰場，擁有資訊優勢的一方能使敵對方陷入茫然不知所措的恐慌狀態，從而感知失靈、思維失據、自亂陣腳。彭博社稱，美國成立不久的第六大軍種——太空軍，計劃2027年前採購48套幹擾系統，旨在“與大國發生沖突情況下”，幹擾迷茫其衛星信號。不少國家軍隊普遍感到，現在獲取的資訊不是太少了而是太多了，來自四面八方的巨量資訊大量聚集，給態勢感知和分析判斷造成巨大壓力。

思維誤導戰。就是透過灌輸包含資訊網絡掌控方意圖指向的特定訊息，形成傾向性訊息場景，誤導欺騙和影響特定國家、軍隊和人群思維理念，使之偏離正確發展軌道，朝著於己有利、於敵有損的方向偏移，是認知攻擊的最高境界和慣常做法。這種誤導以強大的外部壓力為前提，以似是而非的策略為基礎，以摻雜水分的信息為武器，針對對手思維特點和薄弱環節，實施導向鮮明的誘騙，使對手在緊張慌亂中迷失方向，不知不覺落入「圈套」。這些年來，一些國家在實施大國競爭戰略的同時，通過網絡水軍虛構假情況、製造假信息、散佈真謠言，在我國週邊煽風點火，鼓動一些在歷史上與我國有積怨、現實中有摩擦的國家尋尋覓滋事，目的就是要誘導我們轉移注意力，削弱在主要戰略方向上的資源力量投入，偏離強國復興的軌道，謀取漁翁之利。

意志毀傷戰。未來學家托夫勒說，誰控制了人的心理，誰就控制了整個世界。戰爭說到底是人與人的對抗，人的心理活動很大程度影響人的精神狀態，進而影響作戰意志。意志毀傷戰與傳統作戰透過物質摧毀間接影響人的意志不同，它透過直接影響關鍵人物的心理活動、精神狀態和思維決策，影響軍心士氣、戰鬥意志和作戰行動。隨著科技發展和社會進步，對人的意志的干預，已經由傳統以謀略為主演進到“技術+謀略”階段。早在十多年前就有科學家研製出“聲波集束”武器，通過電磁網絡從數百米外發射極為狹窄的聲波“音柱”，幹擾敵人判斷甚至使意志堅強的軍人精神錯亂。近年來有研究表明，基於腦電波信號的人工語音合成技術可提取大腦中的信號，合成人類能夠直接理解的語音。

資訊網絡作用認知戰的主要手段

「技術+謀略」構成現代認知戰的基本手段。資訊網絡作為現代科技發展的產物，其對認知戰的作用手段也主要體現在「技術+謀略」上。這為我們認識並掌握資訊網絡作用認知戰的方式、科學路徑，從而製勝戰爭提供了基本切入點。

大數據構塑。數據作為資訊網絡的核心構件，不僅是資訊的載體，而且是資訊網絡價值驅動的“新石油”，更是作用認知戰的基本彈藥。透過大量資料構塑為我所用的複雜資訊場景，或對對手進行思維認知迷茫，或給予思維誤導欺騙，或進行信念意志摧毀，構成資訊網絡作用認知戰的基本邏輯。在這個邏輯架構中，數據無疑是最基礎的資源、最核心的元素。遠在幾年前，權威部門就統計，全球每天生產約2.5艾字節（EB）的數據，其中僅20%是可以直接利用的結構化數據，其餘80%則需要進行分析、甄別、篩選。這些幾何級數成長湧現的數據資源，為構塑數據資訊場景、實施認知戰提供了取之不盡用之不竭的「數據彈藥」。

智能化推送。資訊網絡時代，智慧化推播成為人們攝取外在訊息，獲得思考認同、情感共鳴、影響他人思考認知的便利管道。運用人工智慧等先進技術收集、整理、分析人的思維慣性、行為偏好數據，形成擬人化客製化感知推送，能夠產生社會認知趨同的「回音壁」和桎梏人的信息繭房，同時也有利於推己及人、了解對手的思維趨向和可能行動，有針對性地採取應對措施。生活中，我們都有一次或幾次網上購物、搜索某類信息後，大量類同信息推送進來的經歷，這種智能化推送手段應用到認知作戰中，很容易使信息主導方通過信息網絡數據，對作戰對象指揮決策層可能做出的決策、採取的行動等予以前瞻分析研判，誘導其作出希望看到的決策行動或預先作出相應的應對措施。

情緒化浸染。佛洛伊德說，我們不是純粹的智慧、純粹的靈魂，而是一個沖動的集合。在資訊網絡空間，能夠得到廣泛且快速傳播的觀念認知，往往不是冷靜理性客觀的思維分析，多是沖動非理性的情緒情緒動員。這是由資訊傳播、新聞發布「先發製人」的快節奏決定的。對這些資訊作出快速反應的認知需求，反過來又導致「快思維」條件反射性、沖動性、情緒化反應，將看似孤立的社會個案轉化為具有強烈壓迫性、煽動性的心理暗示和行為驅動，暴發性催生非理性決策行動。 2009年6月維基解密披露的一份外交電文中，描繪了突尼斯本·阿里政權家族宴會的奢靡場景，並煞有介事地將該政權形容為腐敗暴政的“黑手黨”，這加深了該國國民怨恨情緒，從而成為引燃推翻本·阿里政權的「茉莉花革命」重要推手。

中國原創軍事資源：http://www.mod.gov.cn/gfbw/jmsd/4899062.html?big=fan

#Information Support Force, #intelligent warfare, #intellligentization, Chinese Military Cognitive Domain Operations, Chinese military cognitive warfare, Chinese Military Informatization, Dissipative Warfare, 中國解放軍敘事戰爭

Studying the Military, Studying War, Studying How to Fight: Chinese Military Combat Deception on the Intelligent Battlefield

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研究軍事、研究戰爭、研究怎麼打仗：中國軍隊在智慧戰場上作戰的欺騙

現代英語：

It is easy to break the “fog” of the battlefield, but it is difficult to break the “obsession” in your heart——

Combat Deception on the Intelligent Battlefield

■ Yuan Yi Zhao Di

introduction

Since ancient times, achieving surprise through combat deception has been an important way to win on the battlefield. Entering the era of intelligence, the in-depth application of artificial intelligence technology has not only clearly dispelled the original war “fog”, but also created a large amount of new war “fog”. If we only rely on improving deception techniques and means, and simply superimposing and strengthening the traditional deception paradigm, it will become increasingly difficult to achieve the deception goal. From “smart deception” to “smart victory”, there is an urgent need for an overall transformation of the objects of deception, means of deception, methods of deception, and focus of deception, so as to form a new deception paradigm that meets the requirements of the intelligent era.

The target of deception has shifted from humans to human-machine hybrid agents

Clausewitz believed that three-quarters of the factors on which war is based are more or less surrounded by the “fog” of uncertainty. Combat deception is essentially the use of uncertainty in war. The more “fog” there is in war, the more room there is for maneuvering. Traditional combat deception is carried out around the opponent’s decision-making level, and people are the only target of deception. However, with the increasingly prominent role of intelligent intelligence analysis and auxiliary decision-making systems in command activities, the use of deception to achieve strategic, campaign, and tactical surprises faces major challenges. How to deceive human-machine hybrid intelligent entities composed of humans and intelligent systems has become an important factor that needs to be considered when planning and implementing deception in the intelligent era. The competition surrounding intelligent deception and anti-deception is becoming increasingly fierce.

There is a world of difference between deceiving people and deceiving intelligent systems. In the past, the “calculations” that deceived people may be exposed when facing the “calculations” of intelligent systems. Intelligent systems can efficiently integrate and process massive amounts of sensor data and Internet open source information, making a qualitative leap in the speed, depth, breadth and accuracy of battlefield situation perception, realizing a profound transformation from “sensing” to “knowing”, from “state” to “momentum”, and playing an important role in dispelling the “fog” of war. For example, on the battlefield, although both sides try to hide the truth and cover up their intentions in various ways, they still cannot escape the “eyes” of the intelligent system: the tracks left by carefully disguised tanks and armored vehicles, after being detected by the enemy’s satellites, drones, etc., will also reveal their specific locations under the analysis of the intelligent system.

On the contrary, it is very easy to deceive intelligent systems with methods that target them, but it may not be able to deceive people. A foreign research team found that by changing a few key pixels in a picture of a cat, the intelligent system can identify the cat as a dog, while the human eye will not make any recognition errors due to this change. Similar incidents are common. Some studies have pointed out that sticking a piece of paper with a special pattern on a person’s forehead can deceive the strongest facial recognition system, and this method is highly portable and can deceive other facial recognition algorithms with a slight change.

It can be seen that deceiving people and deceiving intelligent systems are two different “deception methods”. After the deep application of artificial intelligence in the field of intelligence analysis and auxiliary decision-making, from the formulation of strategic deception plans to the design of battlefield camouflage patterns, how to deceive both the human brain and the computer and keep the human-machine hybrid intelligent body “in the dark” will be an important issue that needs to be focused on and solved in order to win the initiative in war.

The fraudulent methods have shifted from being mainly human-based to a combination of human and machine.

The organization and implementation of traditional combat deception is mainly manual, especially large-scale strategic deception, which requires a lot of manpower, material and financial resources. For example, in World War II, the Allies formulated a series of deception plans to ensure the success of the Normandy landing: setting up a fake radio network and a simulated landing fleet, and imagining that the US 1st Army Group with 50 divisions and 1 million people was actively preparing to cross the channel and land in the direction of Calais; using the air force to bomb Calais and Normandy, but the former was bombed more than 1 times more than the latter, etc. The application of artificial intelligence in deception can fundamentally change this situation. With humans as the main guide and intelligent means as the auxiliary, it can quickly generate massive amounts of false information, confusing the real with the fake, and create a thicker war “fog” for the opponent.

The use of intelligent means can improve the quality of deception. On the one hand, intelligent decision-making aids can be used to formulate deception plans, optimize the design of deception forces, deception deployment, deception processes, etc., to achieve systematic deception with the best overall effect; on the other hand, intelligent intelligence analysis systems can be used to pre-test the deception effect, “using one’s own spear to attack one’s own shield”, find out the loopholes and contradictions in the plan, and then improve the deception plan to make it logically self-consistent and seamless.

The use of intelligent means can expand the scale of deception. The increasingly mature deep fake technology can synthesize realistic fake pictures, handwriting, audio, video, etc. in large quantities, and has broad application prospects in strategic, campaign, and tactical deception. For example, in strategic campaign deception, corresponding technical means can be used to confuse opponents by forging fake radio stations and fake commanders, and even to fake an active command post in a certain battle direction; in tactical deception, battlefield camouflage can be used to attach special patterns to high-value equipment to make the opponent’s intelligent system recognize it incorrectly.

The use of intelligent means can reduce the cost of deception. With the support of technologies such as virtual reality and deep fakes, unexpected deception effects can often be achieved with the help of synthetic optics, acoustics and other means, and they are low-cost and low-investment, which is more cost-effective than traditional strategic deception methods. For example, setting up false targets such as bait unmanned combat platforms, using electronic feints and electronic camouflage to send false signals can effectively restrain the opponent’s power, produce high returns at low cost, and thus gain the upper hand.

The use of intelligent means can optimize the accuracy of deception. Traditional combat deception is usually stereotyped, with prominent characteristics of broadcast, extensive, and generalized. For this reason, in the era of intelligence, we should focus on collecting data on opponent decision makers in peacetime and use big data for precise analysis to “know the enemy” more deeply and specifically. On this basis, deep fake technology can be used in wartime to customize the content of deception, realizing precise deception from targeting groups to targeting individuals.

The method of deception has shifted from mainly deceiving to mainly confusing and seducing.

“Playing cards” and “playing chess” are two game modes with completely different battlefield transparency. In the “playing cards” mode, both sides only know the cards that the opponent has played, but do not know the cards in the opponent’s hand, let alone what cards the opponent will play next; while in the “playing chess” mode, the deployment of both sides’ forces on the chessboard is completely transparent, but the opponent’s intentions and the next move are unknown. It is not difficult to see that from cold weapon wars, hot weapon wars, mechanized wars, informationized wars, and then to intelligent wars, the form of war confrontation is increasingly changing from the “playing cards” mode to the “playing chess” mode.

In a war of “playing cards”, blind deception is very useful. Through strict disguise and strict confidentiality, the opponent’s channels of information can be blocked as much as possible, making it impossible for the opponent to detect one’s own intentions and actions, thereby achieving surprise. In the past, when the means of obtaining information were limited and information on the battlefield situation was scarce, there were many examples of wars that used “hiding the truth” and “showing falsehood” to achieve surprise. However, at present, with the help of advanced reconnaissance technology, full-dimensional and full-spectrum reconnaissance has been realized, and the battlefield is becoming more and more transparent. Complete concealment without any revealing features is difficult to achieve. Once the concealment state is switched to the action state, the probability of being discovered by the opponent will be greatly increased. Blind deception can only become an auxiliary deception method.

In the war of “chess”, the following two deception methods are usually used: one is confusing deception, that is, using intelligent means to send a large amount of true and false mixed and difficult to identify information, increasing the ambiguity of information and the difficulty of analysis, making it difficult for the opponent to judge or misjudge. The second is inducement deception, that is, by sending high-definition misleading information, the opponent is led into a preset trap. The combination of these two methods and the cooperation of blinding deception together constitute a hybrid deception that is difficult for the opponent to guard against.

The focus of deception shifts from human perception to human cognition

As the main subject of war, people are important variables that influence the war situation, which implies uncertainty and uncontrollability. From the perspective of psychology, cognitive neurology and other aspects, the “black box” of the mind still cannot be revealed. Deception by deception targets people’s eyes and ears, taking advantage of human sensory weaknesses, while deception by deception and temptation directly targets people’s minds, taking advantage of human weaknesses.

From past cases, even with the most advanced intelligence surveillance and reconnaissance technology and the most intelligent analysis methods, it is impossible to make up for and overcome human weaknesses. In many cases, it is not that the intelligence department failed to recognize the opponent’s deception, but that the decision-makers are unwilling to believe the facts. On the eve of the Soviet-German War in World War II, although more and more evidence showed that Germany was planning to invade the Soviet Union, the Soviet decision-makers believed that the war would not come for the time being. Therefore, when the war broke out, the Soviet army was not well prepared for the response, and the initial defensive actions were very passive.

War practice shows that in the era of intelligence, even if the opponent has obvious military technology advantages and can achieve one-way transparency on the battlefield through advanced intelligence surveillance and reconnaissance technology, the enemy can still take advantage of the cognitive weaknesses of the opponent’s decision-making layer to implement counter-intuitive deception and cover up the true intentions and actions. This also shows that the focus and center of deception in the era of intelligence should not be entirely on how to deliberately cover up the traces of military actions, but should focus more on targeting the opponent’s decision-making layer and inducing it to make decisions and actions that the enemy wants to see.

(Author’s unit: Institute of War Studies, Academy of Military Science)

現代國語：

資料來源：中國軍網-解放軍報 作者：袁 藝 趙 頔 責任編輯：尚曉敏 出版：2024-08-13 07:01:28

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●破戰場「迷霧」易，破心中「執念」難——

智能化戰場上的戰鬥欺騙

■袁 藝 趙 頔

引 言

自古以來，透過作戰欺騙達成突然性，是戰場制勝的重要途徑。進入智慧化時代，人工智慧技術的深度應用，在清晰撥開原有戰爭「迷霧」的同時，又製造出大量新的戰爭「迷霧」。如果只依賴改進欺騙技術和手段，在傳統欺騙範式上做簡單的疊加強化，就想達成欺騙目標的難度越來越大。由“智騙”到“智勝”，迫切需要欺騙對象、欺騙手段、欺騙方式、欺騙重心等各個方面的整體轉變，形成適應智能化時代要求的新型欺騙範式。

欺騙對象由人轉向人機混合智能體

克勞塞維茨認為，戰爭所依據的四分之三的因素或多或少被不確定性的「迷霧」包圍著。作戰欺騙本質上就是對戰爭中不確定性的利用，戰爭「迷霧」越多，施計用謀的空間就越大。傳統作戰欺騙都是圍繞著對方決策層而展開的，人是欺騙的唯一對象。但隨著智慧情報分析與輔助決策系統在指揮活動中的地位作用日益凸顯，以欺騙達成戰略、戰役、戰術突然性面臨重大挑戰。如何欺騙人與智慧系統共同組成的人機混合智能體，成為智能化時代籌劃實施欺騙需要考慮的重要因素，圍繞智能欺騙與反欺騙的較量日趨激烈。

欺騙人與欺騙智慧系統有著天壤之別，以往欺騙人的「算計」在面對智慧系統的「計算」時可能會被識破。智慧型系統可高效融合處理海量的傳感器數據和互聯網開源信息，使得戰場態勢感知的速度、深度、廣度和精度產生質的飛躍，實現由“感”到“知”、由“態”到“勢”的深刻轉變，在撥開戰爭「迷霧」方面發揮重要作用。例如，戰場上盡管交戰雙方都試圖用各種方法隱藏真相、掩蓋企圖，但仍逃不出智能係統的「慧眼」：精心偽裝的坦克、裝甲車等留下的車轍痕跡，被對方衛星、無人機等偵照後，在智慧型系統的分析下也會暴露出具體位置。

相反，針對智慧型系統的欺騙方式欺騙智慧系統非常容易，但可能又欺騙不了人。國外研究團隊發現，只要改變一隻貓的圖片中的少數幾個關鍵像素，就可以使智慧系統將貓識別為狗，而人眼則完全不會因這種變化而出現識別錯誤。類似的事件屢見不鮮，有研究指出，在人類前額上貼一張有特殊圖案的紙片，就能夠騙過最強的人臉識別系統，且這一方法具有很強的可移植性，稍加改變就可以欺騙其他的人臉識別演算法。

由此可見，欺騙人與欺騙智慧系統是兩種不同的「騙法」。人工智慧深度應用於情報分析與輔助決策領域後，大到戰略欺騙方案的製定，小到戰場迷彩圖案的設計，如何既騙過人腦又騙過電腦，把人機混合智能體「蒙在鼓裡”，將會是贏得戰爭主動權需要重點關注並加以解決的重要課題。

欺騙手段由人工為主轉向人機結合

傳統作戰欺騙的組織實施以人工為主，尤其是大規模的戰略欺騙，需要投入大量的人力物力財力。例如，二戰時盟軍為確保諾曼底登陸成功，制定了一系列疑兵計畫：建立假的無線電網和模擬登陸艦隊，虛構有50個師100萬人的美第1集團軍群，正在積極準備橫渡海峽向加萊方向登陸；使用空軍對加萊和諾曼底進行轟炸，但前者遭到的轟炸比後者多1倍以上等等。人工智慧運用於欺騙可從根本上改變這一局面，以人為主導輔以智能手段，可快速生成海量虛假信息，以假亂真，給對手製造更加濃厚的戰爭“迷霧”。

運用智慧手段可提升欺騙品質。一方面，可運用智慧輔助決策手段訂定欺騙計畫，優化設計欺騙力量、欺騙部署、欺騙流程等，實現全局效果最佳的體系化欺騙；另一方面，可運用智慧情報分析系統預先檢驗欺騙效果， “以己之矛攻己之盾”，找出計劃中的漏洞和矛盾點，進而完善欺騙計劃，使其邏輯自洽、嚴絲合縫。

運用智慧手段可擴大欺騙規模。日益成熟的深度偽造技術，可大量合成逼真的虛假圖片、筆跡、音頻、視頻等，在戰略、戰役、戰術欺騙中有著廣泛的應用前景。例如，在戰略戰役欺騙方面，可透過相應技術手段，偽造假電台、假指揮員等迷惑對手，甚至能夠在某一戰役方向偽造一個活躍的指揮所；在戰術欺騙方面，可通過戰場偽裝，給高價值裝備貼上特製圖案，使對手的智慧系統識別出錯。

運用智慧手段可降低欺騙成本。在虛擬現實、深度偽造等技術的支持下，借助合成光學、聲學等手段往往也能達到意想不到的欺騙效果，並且兼具低成本、小投入的特點，相比傳統戰略欺騙方式具有高效費比優勢。如設置誘餌無人作戰平台等假目標，運用電子佯動、電子偽裝等施放假信號，都能夠有效牽制對手力量，以低成本產出高回報，從而贏得制勝先機。

運用智慧手段可優化欺騙精度。傳統作戰欺騙通常千篇一律，廣播式、粗放式、概略化特點比較突出。為此，智能化時代，平時就應注重廣泛收集對手決策者數據，並運用大數據進行精確分析，以更加深刻更加具體地「知彼」。在此基礎上，戰時就可運用深度偽造技術個性化客製化欺騙內容，實現由針對群體到瞄準個體的精準欺騙。

欺騙方式由以蒙蔽為主轉向以迷惑、誘導為主

「打牌」和「下棋」是戰場透明度截然不同的兩種賽局模式。 「打牌」模式中，雙方都只知道對手已出的牌，但不知道對手手中的牌，更不知道下一步對手會出什麼牌；而「下棋」模式中，棋盤上雙方兵力部署完全透明，但不知道對手企圖和下一步棋怎麼走。不難看出，從冷兵器戰爭、熱兵器戰爭、機械化戰爭到資訊化戰爭，再到智慧化戰爭，戰爭對抗形式日益由「打牌」模式轉變為「下棋」模式。

在「打牌」模式的戰爭中，蒙蔽式欺騙非常管用，可通過嚴密偽裝和嚴格保密，盡可能地封鎖對手的獲情渠道，使其無法察覺己方企圖和行動，進而達成突然性。在過去資訊獲取手段有限、戰場態勢資訊匱乏的年代，主用「隱真」輔以「示假」達成突然性的戰例很多。但當前，憑借先進偵察技術，已經實現了全維全譜偵察，戰場透明化程度越來越高，無任何暴露特徵的完全隱蔽已難以實現，而一旦由隱蔽狀態轉入行動狀態，更會大大增加被對手發現的機率，蒙蔽式欺騙只能成為輔助欺騙手段。

在「下棋」模式的戰爭中，通常採用以下兩種欺騙方式：一是迷惑式欺騙，即藉助智能手段，發出大量真假混雜、難以辨認的信息，增大信息模糊度和分析難度，使對手難以判斷或判斷失誤。二是誘導式欺騙，即透過發出高清晰誤導訊息，將對手引入預設陷阱。兩種方式結合再加上蒙蔽式欺騙的配合，共同構成了對手難以防範的混合式欺騙。

欺騙重心由人的感知轉向人的認知

作為戰爭的主體，人是左右戰局的重要變量，蘊含著不確定性和不可控性。從心理學、認知神經學等層面來看，心智的「黑箱」仍然無法揭開。蒙蔽式欺騙針對的是人的耳目，利用的是人類感官弱點，而迷惑式和誘導式欺騙直指人的心智，利用的是人性弱點。

從以往案例來看，即使擁有最先進的情報監視偵察技術和最聰明化的分析手段，也無法彌補和克服人性弱點。很多情況下，不是情報部門沒有辨識出對手的欺騙，而是決策層不願意相信事實。在第二次世界大戰蘇德戰爭前夕，盡管當時越來越多的證據表明，德國正計劃入侵蘇聯，但蘇聯決策層認為戰爭暫時不會來臨，所以當戰爭爆發時，沒有做好應對準備的蘇軍，前期的防禦行動非常被動。

戰爭實踐表明，進入智能化時代，即使對手擁有明顯的軍事技術優勢，能夠通過先進的情報監視偵察技術達成戰場單向透明，但己方仍可利用對手決策層的認知弱點，實施反直覺欺騙，掩蓋真實意圖和行動。這也表明，智能化時代欺騙的發力點和重心，不應全部放在如何刻意掩蓋軍事行動痕跡上，而應更加註重針對對手決策層，誘導其作出己方希望看到的決策行動。

（作者單位：軍事科學院戰爭研究院）

中國原創軍事資源：http://www.81.cn/ll_208543/16330870.html

#Information Support Force, #intelligent warfare, #intellligentization, Chinese Military Future Wars, 中國解放軍敘事戰爭, 認知戰

Chinese Military Building a Solid Data Foundation for Victory in the Intelligent Battlefield

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中國軍隊為智慧戰場勝利建構堅實數據基礎

現代英語：

Build a solid data foundation for victory in the intelligent battlefield

——A brief analysis of military data management in future wars

■Bai Xiaoying Li Xiaosong

Military data is an important engine for promoting changes in the quality, efficiency and power of military construction. With the development of technology, the way data is generated and used is constantly changing, which poses new challenges to the concepts and methods of military data. To win the future information-based and intelligent war, it is necessary to establish a new military data governance ecosystem, focus on strengthening data integration and data empowerment, and enhance data management capabilities throughout the life cycle, support capabilities for scenario-based analysis and intelligent applications, and safe and controllable supervision capabilities.

Recognize the objective necessity of military data governance

As a basic resource, data is being integrated into military operations, military training, strategic management, equipment construction, and logistics support at an accelerated pace. Military data governance activities are based on data quality, aim to release data value, and ensure data security, and are becoming increasingly important in the construction of military informationization and intelligence.

Objective requirements for improving data quality. Whether it is military construction management or military combat command, it is necessary to process and analyze a large amount of data with various types, different standards, and complex relationships from different channels, different time and space, and different fields. The large amount of data accumulated at different stages of military construction often has problems such as incomplete systems, inaccurate content, untimely updates, and ineffective alignment of multiple source data, which can easily lead to insufficient decision-making basis and even misleading decisions. Improving the availability, completeness, correctness, consistency, timeliness and other credible attributes of military data, and supporting military modeling and analysis based on high-quality data can provide support for the realization of scientific decision-making based on data.

The practical need to release the value of data. Traditional military information systems are mostly used to support a single department or a single business need. Data is created and stored along with the business system. Data between different systems is difficult to be compatible and effectively associated, and business collaboration processes based on data flow have not been established between different departments. With the continuous iteration of the system, a large amount of high-value data cannot be reused and may become “stagnant water”. However, business development requires a large amount of historical data resources from different periods. Repeated construction is bound to cause a large waste of manpower, financial resources and time. Data governance promotes the cross-level, cross-domain, cross-system, cross-departmental and cross-business circulation of data by establishing data standards, optimizing business processes, and improving management mechanisms, continuously improving the ability of comprehensive data perception and deep cognition, and maximizing the release of data value.

Necessary measures to ensure data security. The high sensitivity of military data determines the high security requirements of governance. Due to threats such as data leakage, data destruction, and data abuse, data owners and users often have various concerns about sharing data, resulting in many problems such as invisible, unavailable, and dare not use data. Data security governance runs through the entire life cycle of data generation, circulation, application, evolution, and destruction, meets the trust requirements of data rights authorization, shared circulation, audit traceability, and builds a management and technical system for security assurance.

Face up to the role and value of military data governance

Military data governance can effectively improve data quality, ensure data security, promote data sharing, and play an enabling role in assisting military construction and management decision-making and improving the effectiveness of military scientific research and innovation.

Empower future combat operations. In future wars, combat advantages are highly dependent on data advantages. The ever-changing battlefield environment requires real-time aggregation of data from land, sea, air, space, electricity, and network combat domains to gain decision-making advantages. In an open, collaborative, dynamic, and evolving data ecosystem, high-quality data governance can effectively ensure the quality and security of data throughout its life cycle. Building a modern data connection and sharing architecture can horizontally connect data covering various forces in joint operations, and vertically aggregate data covering command and control, battlefield environment, combat readiness intelligence, etc., to form a data pool that supports multi-domain operations and provide real-time, multi-source data assurance for multi-domain operations. Data governance targets a large amount of raw data, efficiently removes the coarse and retains the fine, removes the false and retains the true, and extracts high-value information, so that commanders can grasp the accurate and dynamic battlefield situation in real time in future operations, and use this as a basis to accurately judge the enemy’s situation and our situation, make scientific decisions and deployments, accurately control combat actions, and ensure the accuracy and efficiency of multi-domain combat activities. According to changes in the battlefield situation and different types of authorization, commanders can flexibly and quickly obtain and call data that meets combat applications, providing more powerful data support and better service supply for multi-domain operations.

Support the modernization of military governance. In the era of intelligence, through the digital collection, standardized processing, and networked connection of military governance elements, the physical world is highly digitized, and the physical world is reshaped by digital mapping, realizing the full connection of physical domains, information domains, etc. With the help of data governance, an integrated military governance information network platform that is cross-military, cross-domain, and cross-system can be systematically built, effectively integrating multiple governance paths such as leadership, coordination, guidance, and interaction, and driving the transformation of fragmented management to holistic governance. The deep integration of military data governance work with business work such as military strategic management, equipment construction, training support, and military scientific research can provide high-quality data for planning, resource allocation, and management evaluation, and promote the improvement of the quality and efficiency of the military governance system. Through data governance, effective integration and deep fusion of data across systems and departments can be achieved, which can effectively break through the time, space and field limitations of the traditional management system and improve modern military governance capabilities.

Promote the development of military intelligence. In modern warfare, both sides try to take various means to obtain, analyze and use battlefield data. Data has become the basic support for the overall operation of the combat system based on the information system. Under the conditions of informatization and intelligence, the combat system operates based on data, combat decisions are generated based on data, and combat actions are guided by data. Having data advantages is the prerequisite for the system to win. Especially in recent years, with the rapid development of general artificial intelligence such as ChatGPT and Sora and the huge effectiveness they have shown in the military field, related technologies need high-quality data to “feed”. Data quality often directly determines the “intelligence” of intelligent algorithm models, and even affects the level of military intelligence construction. Strengthening military data governance can efficiently discover and agilely associate related information, extract and integrate multi-domain knowledge, maintain the integrity, consistency, and freshness of information in the process of dynamic evolution, and provide highly credible, highly reliable, and high-value data supply for artificial intelligence training, ensuring that it is not “misled”, enhancing its reliability and explainability, and thereby improving the ability of artificial intelligence to serve complex battlefield situation perception and accurate analysis and decision-making.

Exploring the implementation path of military data governance

Data governance takes data as its object, and needs to sort out the rights and responsibilities of all parties involved in data circulation, forming a data circulation model of benign interaction, co-construction, sharing and co-governance among multiple participants, so as to maximize the release of value. To build a military data governance system, we need to start from the resource system, institutional system, technical system and other aspects.

Build a resource system. Military data business scenarios are diverse, state structures are multi-dimensional, and classification is complex. In order to make data “visible” and “well used”, data resource construction needs to start from the supply side, identify false information, efficiently discover and agilely associate related information, extract and integrate multi-domain knowledge, maintain data integrity in the dynamic evolution process, and form a high-quality data pool. According to different dimensions, a hierarchical and classified military data resource system can be constructed to form a data space with unified identification, multi-dimensional annotation, compliance and security, clear hierarchy, and reasonable structure. According to the requirements of data resource classification and classification, effectively control data usage rights, avoid confusion in data usage management, and realize data discoverability, accessibility, understandability, trustworthiness, and interoperability based on a unified data resource framework.

Improve the institutional system. In the economic and social fields, the data governance framework defines the consensus on the exercise of decision-making power and division of responsibilities for data-related matters, that is, who can take what actions based on what information, at what time and under what circumstances, using what methods. Military data governance needs to be combined with the characteristics of the military field, military activity processes and application scenarios, clarify the laws and regulations on the cross-domain flow of data between different management agencies, security jurisdictions, and physical networks, clarify the authority, responsibilities and collaboration models of different actors in providing and using data, establish rules and regulations covering activities such as data collection, integration and sharing, service application, and security management, promote data construction to be standardized, scientific, and institutionalized, collect, process and apply data in accordance with regulations, standards, authority, and scenarios, and ensure that all stakeholders work in a coordinated manner.

Upgrade the technical system. Facing future wars, it is necessary to build a more adaptable and efficient security technology system that is more adaptable to the release of data value, and to ensure the implementation and implementation of the governance system through technical means. Based on operational data foundations, metadata, data exchange and other standards and specifications, build technologies and tools such as data collection and access, organizational management, shared exchange, and secure operation and control to support the full life cycle management of data. Through technical means such as access control, content protection, operation authorization, traceability and evidence, and regulatory auditing, ensure that data sharing and application meet reasonable, legal, and compliant requirements. For example, based on the digital object system, realize “identity card-style” data management to ensure “one number and one source”; based on the distributed trust management system, realize secure data sharing and controllable traceability.

現代國語：

築牢制勝智慧化戰場的數據基礎

——淺析未來戰爭軍事數據治理

■白曉穎 李曉松

引言

軍事數據是推動軍隊建設品質變革、效率變革、動力變革的重要引擎。隨著技術發展，數據產生和利用的方式不斷嬗變，對軍事數據的概念、方法等都提出新的挑戰。打贏未來資訊化智慧化戰爭，需要建立新的軍事數據治理生態，著力加強數據整合和數據賦能，提升數據全生命週期管理能力、場景化分析和智慧化應用的支撐能力、安全可控的監管能力。

認清軍事數據治理的客觀必需

數據作為基礎性資源，正加速融入軍隊作戰運用、軍事訓練、戰略管理、裝備建設和後勤保障等各環節。軍事數據治理活動以數據品質為基礎，以釋放數據價值為目標，以數據安全為保障，在軍隊資訊化智慧化建設中越來越重要。

提升數據品質的客觀要求。無論是軍隊建設管理，還是軍事作戰指揮，都需要處理和分析來自不同渠道、不同時空、不同領域的大量類型多樣、標準不一、關聯復雜的數據。軍隊建設不同階段累積的大量數據往往存在體係不完整、內容不准確、更新不及時、多種來源數據未有效對齊等問題，容易導致決策依據不充分，甚至誤導決策。提高軍事數據的可用性、完整性、正確性、一致性、時效性等可信屬性，支援基於高品質數據的軍事建模和分析，才能為實現基於數據的科學決策提供支撐。

釋放數據價值的現實需求。傳統的軍隊資訊系統多用於支撐單一部門或單一業務需求，數據伴隨著業務系統創建、存儲，不同系統之間數據難以兼容和有效關聯，不同部門之間未建立基於數據流轉的業務協同流程。隨著系統不斷迭代，大量高價值的數據無法再利用，可能成為「一潭死水」；而業務發展又需要不同時期的大量歷史數據資源，重復建設勢必造成人力、財力和時間的大量浪費。數據治理透過建立數據標準、優化業務流程、完善管理機制，推動數據跨層級、跨領域、跨系統、跨部門、跨業務流通，不斷提升數據全面感知、深度認知的能力，最大限度地釋放數據價值。

確保數據安全的必要舉措。軍事數據的高敏感性決定了治理的高安全性要求。由於存在數據洩露、數據破壞、數據濫用等威脅，數據的所有者和用戶對共享數據往往存在各種顧忌，導致數據不可見、不可用、不敢用等諸多問題。資料安全治理貫穿資料產生、流轉、應用、演化、銷毀的全生命週期，滿足資料確權授權、共享流通、審計溯源等可信任要求，建構了安全保障的管理與技術體系。

正視軍事數據治理的作用價值

軍事數據治理能有效提升數據品質，保障數據安全，促進數據共享，為輔助軍隊建設管理決策、提升軍事研究創新效益發揮賦能作用。

賦能未來作戰運用。未來戰爭，作戰優勢高度依賴數據優勢。瞬息萬變的戰場環境，需要即時匯聚陸、海、空、天、電、網等作戰域的數據，從而獲得決策優勢。在開放、協同、動態、演化的數據生態系統中，高品質數據治理能有效保證數據全生命週期品質與安全。建構現代化的數據引接和共享架構，能夠橫向引接涵蓋聯合作戰各種力量數據，縱向匯聚覆蓋指揮控制、戰場環境、戰備情報等數據，形成支撐多域作戰的數據池，為多域作戰提供實時、多源數據保障。數據治理針對大量匯聚的原始數據，高效去粗取精、去偽存真，萃取高價值信息，使指揮員能夠在未來作戰中實時掌握精確、動態的戰場態勢，並以此為依據準確判斷敵情我情，科學決策部署，精確控製作戰行動，確保多域作戰活動的精確有效率。指揮員根據戰場態勢變化，依據不同類型授權，靈活柔性、快速動態獲取和調用滿足作戰應用的數據，為多域作戰提供更有力的數據支撐和更優質的服務供給。

支撐軍事治理現代化。智能化時代，透過軍事治理要素的數位化採集、標準化處理、網絡化連接，將物理世界高度數據化，以數字形態映射重塑物理世界，實現物理域、資訊域等全領域貫通。藉由資料治理，可以系統化建構跨軍地、跨領域、跨系統的一體化軍事治理資訊網絡平台，有效整合領導、協調、引導、互動等多種治理路徑，驅動碎片化管理向整體性治理轉變。軍事數據治理工作與軍隊戰略管理、裝備建設、訓練保障、軍事科研等業務工作的深度結合，可為規劃計劃、資源調配和管理評估等提供高質量數據，促進軍事治理體系的提質增效。透過數據治理，可以實現數據跨系統、跨部門的有效整合和深度融合，能有效突破傳統管理體系的時間、空間、領域限制，並提升現代軍事治理能力。

助推軍事智能化發展。現代戰爭，作戰雙方力圖採取各種手段獲取、分析和運用戰場數據，數據已成為基於資訊系統的作戰體系整體運行的基本支撐。在資訊化智慧化條件下作戰，作戰體系基於數據運行，作戰決策基於數據產生，作戰行動基於數據牽引，擁有數據優勢是體系聚優制勝的前提。特別是近年來隨著ChatGPT、Sora等通用人工智慧的迅猛發展以及在軍事領域展現出來的巨大效用，相關技術需要高品質的數據來「餵養」。數據品質往往直接決定了智慧演算法模型的「智慧」程度，甚至影響軍事智慧化建設的程度。加強軍事數據治理，可以高效發現、敏捷關聯相關信息，提取並融合多域知識，在動態演化的過程中保持信息的完整性、一致性、鮮活性，為人工智能訓練提供高可信、高可靠、高價值的數據供給，確保其不被“誤導”，增強其可靠性和可解釋性，進而提升人工智能服務復雜戰場態勢感知、精準研判決策的能力。

探索軍事數據治理的實現路徑

數據治理以數據為對象，需理順各方參與者在數據流通各環節的權責關系，形成多方參與者良性互動、共建共享共治的數據流通模式，最大限度地釋放價值。建構軍事資料治理體系，需從資源體系、制度體系、技術體係等方面著手。

構建資源體系。軍事數據業務場景多樣、狀態結構多維、密級分類復雜，為了數據“看得見”“用得好”，數據資源建設需從供給側出發，甄別虛假信息，高效發現、敏捷關聯相關信息，提取並融合多域知識，在動態演化過程中保持資料完整性，形成高品質資料池。可依據不同維度，建構分級分類的軍事資料資源體系，形成統一標識、多維標註、合規安全、層次分明、結構合理的資料空間。依照資料資源分級分類要求，有效控制資料使用權限，避免資料使用管理混亂，實現基於統一資料資源架構的資料可發現、可取得、可理解、可信賴和可互通。

完善製度體系。在經濟社會領域，數據治理框架定義了行使數據相關事務決策權和職責分工的共識，即誰能根據什麼信息，在什麼時間和情況下，用什麼方法，採取什麼行動。軍事數據治理需要結合軍事領域特點、軍事活動流程和應用場景，明確數據在不同的管理機構、安全管轄區域、物理網絡之間跨域流轉的法律法規，明確不同行為主體提供和使用數據的權限、職責與協作模式，建立覆蓋資料收集、整合共享、服務應用、安全管理等活動的規章制度，促進資料建設走向規範化、科學化、制度化，依規、依標、依權限、依場景，採集、處理和應用數據，確保各利益相關者工作協調一致。

升級技術體系。面向未來戰爭，需構築與數據價值釋放更適應、更有效率的安全技術體系，並通過技術手段確保治理制度貫徹執行、落實生效。基於可操作的資料基礎、元資料、資料交換等標準規範，建構資料擷取存取、組織管理、共享交換、安全運控等技術與工具，支援資料的全生命週期管理。透過存取控制、內容保護、操作授權、溯源循證、監管審計等技術手段，確保資料共享與應用滿足合理、合法、合規要求。例如，基於數字對象體系，實現數據「身份證式」管理，確保「一數一源」；基於分散式信任管理體系，實現數據安全共享和可控追溯。

中國原創軍事資源：http://www.mod.gov.cn/gfbw/jmsd/16339063.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

#Information Support Force, #intellligentization, #中國太空軍, #中國的耗散戰, #中國軍事人工智慧武器化, #新興戰爭技術, Chinese Military Future Wars, 中國解放軍敘事戰爭, 認知域戰

Aspects of Chinese intelligent warfare: Artificial intelligence will change the winning mechanism of future Chinese wars

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中國智慧化戰爭看點：人工智慧將改變未來中國戰爭制勝機制

現代英語：

Artificial intelligence technology is an important support for improving strategic capabilities in emerging fields. It has developed rapidly in recent years and is widely used in the military field. It continues to generate new asymmetric advantages and profoundly changes the basic shape, combat methods and winning mechanisms of future wars. We should have a deep understanding of the revolutionary technological power of artificial intelligence, accurately identify changes, respond scientifically, and proactively seek changes, and strive to explore ways to win future wars, and win the initiative in the accelerating intelligent wars.

information mechanism

If you know your enemy and yourself, you can fight a hundred battles without danger. 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, and can form a “transparent” advantage on the battlefield.

Autonomous implementation of battlefield awareness. By embedding intelligent modules into wartime reconnaissance systems, various types of reconnaissance node units can achieve random networking, on-the-fly collaboration, and organic integration. They can independently capture battlefield information in all directions and dimensions, and build a relatively “transparent” digital battlefield environment and combat situation. It then clears the “fog” of war and presents combat scenes in a panoramic manner.

Accurate identification of massive data. Relying on intelligent technologies such as precise sensing technology and analysis and recognition technology, it can accurately interpret, analyze, compare and integrate diversified voice, text, pictures, videos and other data to obtain a faster, more complete, more accurate and deeper battlefield situation. The result is far faster and more accurate than human brain processing.

Respond efficiently to key information. Based on intelligent technology groups such as combat cloud, big data, and the Internet of Things, it can quickly excavate large quantities of non-standardized and heterogeneous intelligence data, independently discover symptoms, identify intentions, study trends, find patterns, and respond accurately in real time. Commander’s need for critical information.

Synchronize and share the integration 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 and space power grids, and play an important hub role in sharing information and unified cognition, building a system based on “one picture” and “one picture”. The “open network” and “one chain” situation enables all combat units to synchronously share the required information from different spaces, distances, and frequencies in all areas, all frequencies, and all the time, realizing wisdom sharing.

Decision-making mechanism

If the husband has not fought yet and the temple is considered the winner, he must be considered the winner. Scientific and accurate decision-making is a prerequisite for winning a war. Artificial intelligence can conduct dynamic battlefield simulations, quickly make feasible decisions, significantly shorten the operational planning and decision-making cycle, and form a decision-making advantage.

Intelligent analysis and judgment of strategic situations. The decision-making assistance system integrated with 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 analysis capabilities, maximize the elimination of falsehoods and preserve truths, correlation verification, and link thinking, and automatically conduct analysis of the enemy’s situation, our situation, and our situation. Big data analysis such as battlefield environment can form comparative data on relevant troops, weapons, etc., which can effectively assist combat command and help commanders quickly make combat decisions.

Intelligent selection of combat plans. Relying on the intelligent combat simulation system, based on the pre-entered combat missions and target information, multiple sets of intuitive plans and plans are automatically generated, comprehensively evaluate their advantages, disadvantages and potential risks, and select the plan that is most conducive to realizing the commander’s intention. for the commander to make the final decision. After receiving combat missions and target requirements from superiors, each combat unit further screens and screens battlefield target information based on the tasks and requirements at this level, and independently formulates the optimal solutions and plans at this level to maximize combat effectiveness.

Intelligent prediction of decision-making effectiveness. The intelligent auxiliary decision-making 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. It can think more rationally about unexpected situations on the battlefield and quickly draw relative conclusions. Objective results of the engagement.

power control mechanism

Powerful people control power because of profit. Seizing power is a key factor in gaining a winning edge in war. Artificial intelligence can “transplant” part of human intelligence into weapons, making the integration of humans and weapon systems closer and closer. In-depth human-machine integration has changed the traditional elements of power control and given new power control connotations, which can help to obtain new technologies. control advantage.

Territorial power expanded to high frontiers. In the future, highly intelligent unmanned systems will operate in extreme environments such as extreme heights, extreme distances, extreme depths, extremely low temperatures, extreme darkness, and extreme brightness, even under harsh conditions such as high temperature, extreme cold, high pressure, hypoxia, poison, and radiation. , a variety of combat missions can still be carried out, and the battle for control of the combat field and combat space extends to high frontiers, far frontiers, and deep frontiers.

Expand the right to control information to multiple means. The traditional way of seizing and controlling information power is to control the acquisition, processing, and distribution of information by attacking the enemy’s reconnaissance and early warning system and destroying its command and control system. However, information operations led by artificial intelligence use information itself as “ammunition”. ”, the means to seize the right to control information are more diverse.

Network control rights are expanded to distributed areas. The network information system built based on intelligent technology provides a ubiquitous network “cloud” to aggregate battlefield resources of various terminals and provide services. It can realize modular grouping and automatic reorganization of combat forces. Traditionally, it can achieve network outage and destruction by attacking key nodes. The purpose of the chain will be difficult to achieve, and the “decentralized” battlefield must be dealt with in an intelligent distributed attack mode.

Brain power expands to new dimensions. The gradual militarization of brain-inspired technology and simulation technology has formed a new field of games and confrontations. The focus has shifted from focusing on confrontation in the physical and information domains to more emphasis on influencing and controlling the opponent’s psychology. Technologies such as virtual reality and audio-visual synthesis can confuse fakes with real ones. “Core attack warfare” can quietly change the enemy’s command and control system algorithm, and “brain control warfare” can directly control the enemy’s decision-making. By controlling and influencing the enemy’s psychology, thinking, will, etc., it can achieve control at the minimum cost. The purpose of war and victory.

Mechanism of action

The passion of soldiers is the key to speed, taking advantage of others’ disadvantages. Taking actions that the enemy does not expect is the key to winning a war. Artificial intelligence can improve the intelligence of weapons and equipment, command and control systems, and operational decision-making, making maneuver response capabilities faster and joint strike capabilities more accurate, creating a super operational advantage.

The speed of action is “instantaneous”. The intelligent combat system can see, hear, learn, and think, effectively shortening the “OODA” cycle. Once an “opportunity is found,” it will use intelligently controlled hypersonic weapons, kinetic energy weapons, and lasers. Weapons, etc., can quickly “kill” targets from a long distance.

The action style is “unmanned”. “Unmanned + intelligence” is the future development direction of weapons and equipment. Low-cost unmanned autonomous equipment such as unmanned vehicles, drones, and unmanned underwater vehicles, with the support of the cluster autonomous decision-making system, can plan the task division of each unit according to the combat objectives, and accurately dock and autonomously combine the unmanned aerial vehicles. , covert penetration, and carry out cluster saturation attacks on the enemy.

The space for action “blurs”. In future wars, using interference means to carry out soft attacks on the enemy’s intelligent combat systems and smart weapons, and using smart weapons to delay or affect the decision-making and psychology of enemy personnel will become the key to victory. Most of these actions were completed unknowingly or silently, presenting a “blurred” state in which neither the enemy nor ourselves were visible, the boundaries between the front and the rear were unclear, and the visible and invisible were difficult to distinguish.

The operational layout is “invisible”. Intelligent command systems and weapons and equipment have bionic and stealth properties. As long as they are deployed in possible combat areas in advance during peacetime preparations or training exercises, they are lurking in advance, dormant and ready for battle. Once needed in wartime, they can be activated in a timely manner to launch a sudden attack on the enemy, which will help to quickly grasp the initiative in the war.

System mechanism

Five things and seven strategies to know the outcome. Future wars will be systematic confrontations in all fields, systems, elements, and processes. 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 a fully integrated combat system will produce powerful system advantages.

There are more means of “detection”. The intelligent combat cluster relies on the network information system to connect with various large-scale sensors, electronic warfare systems and other human-machine interaction platforms. It uses each combat unit’s own detection and sensing equipment to obtain battlefield data, leverages the self-organizing characteristics of the intelligent group, and strengthens joint operations. The real-time reconnaissance and surveillance support of the system and back-end intelligence analysis can realize full-area reconnaissance and search, joint early warning, and collaborative verification, forming a multi-dimensional integrated, full-area coverage large-area joint reconnaissance intelligence system.

The field of “control” is wider. The use of intelligent unmanned combat platforms can break through the logical limits of human thinking, the physiological limits of the senses, and the physical limits of existence, and replace humans into traditional restricted areas of life such as the deep sea, space, polar regions, and areas with strong radiation, and stay there for a long time. Implement “unconventional operations” to further expand the combat space and have the ability to continue to deter opponents in a wider area.

“Hit” is faster. With the support of the intelligent network information system, the intelligence chain, command chain, and kill chain are seamlessly connected. Information transmission speed, decision-making speed, and action speed are simultaneously accelerated. Intelligent combat units can be flexibly organized, autonomously coordinated, and struck quickly. All these make time utilization extremely efficient and battlefield reaction speed extremely fast.

The accuracy of “evaluation” is more accurate. Using intelligent technologies such as experiential interactive learning and brain-like behavioral systems, the intelligent combat assessment system can independently collect, aggregate and classify multi-means action effect assessment information, accurately perceive battlefield actions based on big data and panoramic views, and dynamically identify Combat process and correct deficiencies, predict complex battlefield changes, comprehensively plan and respond flexibly.

“Guarantee” 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 support needs in various domains, intelligently plan support resources, ensure that the “cloud” aggregates various battlefield resources, and effectively enhances the networked battlefield Comprehensive support capabilities.

(Author’s unit: Henan Provincial Military Region)

現代國語：

人工智慧技術是提升新興領域策略能力的重要支持。近年來發展迅速，在軍事領域廣泛應用。它不斷生成新的不對稱優勢，深刻改變未來戰爭的基本形態、作戰方式和勝利機制。我們應該深刻認識人工智慧革命性技術力量，準確辨識變化、科學應對、主動求變，努力探索打贏未來戰爭的辦法，在加速推進的智慧化戰爭中奪取主動權。

資訊機制

知己知彼，百戰不殆。迅速有效地掌握全方位資訊是贏得戰爭的首要前提。人工智慧可以實現戰場態勢的智慧感知、大量數據的智慧分析、多種資訊的智慧處理，可以在戰場上形成「透明」優勢。

自主實施戰場感知。透過在戰時偵察系統中嵌入智慧模組，使各類偵察節點單元實現隨機組網、動態協同、有機融合。它們能夠自主獲取全方位、多維度的戰場訊息，建構相對「透明」的數位化戰場環境和作戰態勢。它撥開戰爭的“迷霧”，全景式地呈現戰鬥場景。

海量資料精準識別。依托精準感知技術、分析辨識技術等智慧技術，對多樣化的語音、文字、圖片、視訊等數據進行精準解讀、分析、比較與整合，獲得更快、更全、更準、更深層的戰場態勢。其結果比人腦處理的速度更快、更準確。

有效響應關鍵訊息。基於作戰雲、大數據、物聯網等智慧技術群，快速挖掘大量非標準化、異質情報數據，自主發現症狀、辨識意圖、研究趨勢、尋找模式、精準應對即時。指揮官需要關鍵資訊。

同步分享整合情況。智慧控制系統能夠優化整合陸、海、空、天電網等分佈在不同空間、不同頻域的各種偵察監視系統，發揮資訊共享、統一認知的重要樞紐作用，建構基於智慧感知的體系。一張圖」與「一張圖」。 「開網」「一條鏈」的局面，使各作戰單元能夠全地域、全頻率、全時間，同步分享不同空間、不同距離、不同頻率的所需信息，實現智慧共享。

決策機制

如果丈夫還沒有戰鬥，而寺廟被認為是勝利者，那麼他必須被視為勝利者。科學準確的決策是贏得戰爭的前提。人工智慧可以進行動態戰場模擬，快速做出可行決策，大幅縮短作戰規劃和決策週期，形成決策優勢。

智能分析判斷戰略情勢。融入人工智慧技術的決策輔助系統具有資訊收集、查詢管理、資料處理、關聯分析等功能。能有效突破人的分析能力限制，最大限度實現去偽存真、關聯驗證、連結思考，自動進行敵情、我情、我勢分析。戰場環境等大數據分析可以形成相關兵力、武器裝備等比較數據，可以有效輔助作戰指揮，幫助指揮官快速做出作戰決策。

智慧選擇作戰計畫。依托智能作戰模擬系統，根據預先輸入的作戰任務和目標訊息，自動產生多套直觀的作戰方案和計劃，綜合評估其優勢、劣勢及潛在風險，選取最有利於實現了指揮官的意圖。由指揮官作出最終決定。各作戰單元接到上級作戰任務和目標要求後，依據本級任務和要求，對戰場目標資訊進行進一步甄別篩選，自主制定本級最優解決方案和預案，最大限度提高戰鬥力。

智慧預測決策的有效性。智慧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技術，賦予指揮控制系統更先進的「類大腦」能力。能夠更理性地思考戰場上的突發狀況，並迅速得出相關結論。參與的客觀成果。

權力控制機制

有權勢的人因為利益而控制權力。奪取政權是戰爭中取得勝利的關鍵因素。人工智慧可以將人類部分智慧「移植」到武器中，使得人與武器系統的結合越來越緊密。人機深度融合改變了傳統的動力控制要素，賦予了動力控制新的內涵，有助於獲得新的技術。控制優勢。

領土權力擴展到高地邊境。未來高度智慧的無人系統將在極高、極遠、極深、極低溫、極暗、極亮等極端環境下，甚至在高溫、極寒、高壓、缺氧、中毒和輻射。 ，多種作戰任務仍可實施，戰場和作戰空間控制權的爭奪向高邊、遠邊、深邊延伸。

將資訊控制權拓展到多種手段。奪取和控制資訊權的傳統方式是透過攻擊敵方偵察預警系統、摧毀敵方指揮控制系統來控制資訊的取得、處理和發布。然而，人工智慧主導的資訊作戰，是以資訊本身作為「彈藥」的。 ”，奪取資訊控制權的手段更加多樣化。

網路控制權擴展至分散式區域。基於智慧技術建構的網路資訊體系，提供無所不在的網路“雲”，聚合各類終端的戰場資源並提供服務。可實現作戰力量模組化編組和自動重組。傳統上它透過攻擊關鍵節點來實現網路中斷和破壞。鏈上的目的將很難實現，必須以智慧分散式的攻擊方式來應對「去中心化」的戰場。

腦力拓展至新的維度。類腦技術、模擬技術逐漸軍事化，形成了新的博弈與對抗領域。從注重身體和資訊領域的對抗，轉向更加重視影響和控制對手的心理。虛擬實境、視聽合成等技術可以使真假混淆。 「核心攻擊戰」可以悄悄改變敵人的指揮控制系統演算法，「腦控戰」則可以直接控制敵人的決策。透過控制和影響敵人的心理、思維、意誌等，以最小的代價來實現控制。戰爭的目的和勝利。

作用機制

士兵的熱情是速度的關鍵，利用別人的劣勢。採取敵方意想不到的行動是贏得戰爭的關鍵。人工智慧可以提升武器裝備、指揮控制系統、作戰決策的智慧化，讓機動反應能力更快速、聯合打擊能力更精準，打造超級作戰優勢。

作用速度是「瞬時的」。智慧作戰系統能夠看、聽、學、想，有效縮短「OODA」週期。一旦“發現機會”，它就會使用智慧控制的高超音速武器、動能武器和雷射。武器等，可以從遠距離快速「殺死」目標。

行動方式為「無人化」。 「無人化+智能化」是未來武器裝備的發展方向。無人駕駛汽車、無人機、無人潛航器等低成本無人自主裝備，在集群自主決策系統支援下，可依作戰目標規劃各單元任務分工，精準對接、自主組合無人駕駛飛行器。 、隱蔽滲透，對敵方實施集群飽和攻擊。

行動空間「模糊」。未來戰爭中，利用乾擾手段對敵方智慧作戰系統和智慧武器實施軟攻擊，利用智慧武器延緩或影響敵方人員的決策和心理，將成為勝利的關鍵。這些動作大多是在不知不覺中或默默無聞地完成的，呈現出一種「模糊」的狀態，雙方都沒有意識到。無論是敵人還是自己，都是看不見的，前方與後方的界線不清，看得見與看不見的難以區分。

作戰佈局「隱形」。智慧指揮系統和武器裝備具有仿生、隱身性能。只要在平時準備或訓練演習中，提前部署到可能的作戰區域，就是提前潛伏，蟄伏，隨時準備戰鬥。一旦戰爭需要，可以及時投入使用，對敵人發動突襲，有利於迅速掌握戰爭主動權。

系統機制

五件事和七種策略可知結果。未來戰爭將是各領域、各體系、各要素、各過程的系統對抗。穩定、有效率的作戰體係是打贏戰爭的基礎支撐。隨著人工智慧在軍事領域應用範圍不斷拓展，作戰體系智慧化程度越來越高，全面整合的作戰體系將產生強大的體系優勢。

「檢測」的手段還有很多。智慧作戰集群依托網路資訊體系，連結各類大型感測器、電子戰系統及其他的人機互動平台。它利用各作戰單元本身的探測感測設備取得戰場數據，發揮智慧群體自組織特點，加強聯合作戰。透過系統性的即時偵察監視保障和後端情報分析，可實現全域偵察搜尋、聯合預警、協同核查，形成多維度一體化、全域覆蓋的大區域聯合偵察情報系統。

「控制」的領域更加廣泛。利用智慧無人作戰平台，可以突破人類思維的邏輯極限、感官的生理極限、生存的物理極限，取代人類進入深海、太空、極地等傳統生命禁區。實施“非常規作戰”，進一步拓展作戰空間，具備在更廣闊區域持續威懾對手的能力。

「打」得更快。在智慧化網路資訊系統支援下，情報鏈、指揮鏈、殺傷鏈無縫銜接。訊息傳遞速度、決策速度、行動速度同步加快。智慧作戰部隊能夠靈活組織、自主協同、快速出擊。這些使得時間利用率極高，戰場反應速度極快。

「評價」的準確性更加準確。智慧作戰評估系統利用體驗式互動學習、類腦行為系統等智慧技術，自主採集、聚合、分類多手段行動效果評估信息，基於大數據和全景視圖精準感知戰場行動，動態識別戰場態勢，實現戰場態勢感知與決策支撐。

「保」更有效率。以裝備維修專家系統、智慧感知裝備為代表的智慧化綜合保障系統的廣泛應用，能有效率地回應各領域保障需求，智慧規劃保障資源，確保「雲端」聚合各類戰場資源，有效提升保障水準。化戰場綜合保障能力。

（作者單位：河南省軍區）

中國原創軍事資源：

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Comprehensive Review of Chinese Military Intelligent Warfare: Intelligent Combat Command

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中國軍事智慧戰爭全面回顧：智慧作戰指揮

現代英語：

Liu Kui, Qin Fangfei

Tips

● Modern artificial intelligence is essentially like a “brain in a vat”. If it is allowed to carry out combat command, it will always face the problem of subjectivity loss, that is, “self” loss. This makes artificial intelligence have natural and fundamental defects. It must be based on human subjectivity and improve the effectiveness and level of combat command through human-machine hybrid.

● In intelligent combat command, the commander is mainly responsible for planning what to do and how to do it, while the intelligent model is responsible for planning how to do it specifically.

“Brain in a vat” is a famous scientific hypothesis. It means that if a person’s brain is taken out and placed in a nutrient solution, the nerve endings are connected to a computer, and the computer simulates various sensory signals. At this time, can the “brain in a vat” realize that “I am a brain in a vat”? The answer is no, because as a closed system, when a person lacks real interactive experience with the outside world, he cannot jump out of himself, observe himself from outside himself, and form self-awareness. Modern artificial intelligence is essentially like a “brain in a vat”. If it is allowed to implement combat command, it will always face the problem of subject loss, that is, “self” loss. This makes artificial intelligence have natural and fundamental defects, and it must be based on human subjectivity and improve the effectiveness and level of combat command through human-machine hybrid.

Based on “free choice”, build a “man-planned” command model

On the battlefield, the commander can choose which target to attack, and can choose to attack from the front, from the flank, from the back, or from the air; he can isolate but not attack, surround but not attack, talk but not attack… This is human autonomy, and he can freely choose what to do and how to do it. But machines can’t do that. The combat plans they give can only be the plans implied in the intelligent model. As far as the specific plan given each time is concerned, it is also the most likely plan in the sense of probability statistics. This makes the plans generated by artificial intelligence tend to be “templated”, which is equivalent to a “replica machine”. It gives similar answers to the same questions and similar combat plans for the same combat scenarios.

Compared with artificial intelligence, different commanders design completely different combat plans for the same combat scenario; the same commander designs different combat plans when facing similar combat scenarios at different times. “Attack when the enemy is unprepared and take them by surprise”, the most effective plan may seem to be the most dangerous and impossible plan. For commanders, facing combat scenarios, there are infinite possibilities in an instant, while for artificial intelligence, there is only the best-looking certainty in an instant, lacking creativity and strategy, and it is easy for the opponent to predict it. Therefore, in intelligent combat command, based on human autonomy, the commander is responsible for planning and calculation, innovating tactics and tactics, and designing basic strategies, and the machine is responsible for converting basic strategies into executable and operational combat plans, forming a “man-planned” command mode. More importantly, autonomy is the unique mark of human existence as human being. This power of free decision-making cannot and is not allowed to be transferred to machines, making people become vassals of machines.

Based on “self-criticism”, build a command model of “people against machine”

Human growth and progress are usually based on the real self, focus on the ideal self, and criticize the historical self in a negation-negation style. Artificial intelligence has no “self” and has lost its self-critical ability. This makes it only able to solve problems within the original cognitive framework. The combat ideas, combat principles, and tactics of the model are given when the training is completed. If you want to update and improve your knowledge and ideas, you must continuously train the model from the outside. Mapped to a specific combat scenario, the intelligent model can only provide the commander with a pre-given problem solution. It is impossible to dynamically adjust and update it continuously during a battle.

People with a self-critical spirit can jump out of the command decision-making thinking process and review, evaluate, and criticize the command decision. In the continuous self-criticism, the combat plan is constantly adjusted, and even the original plan is overturned to form a new plan. In the command organization group, other commanders may also express different opinions on the combat plan. The commander adjusts and improves the original plan on the basis of fully absorbing these opinions, and realizes the dynamic evolution of the combat plan. Therefore, combat command is essentially a dynamic process of continuous forward exploration, not a static process given in advance by the combat plan. When the machine generates a combat plan, the commander cannot accept it blindly without thinking, but should act as an “opponent” or “fault finder”, reflect on and criticize the combat plan, and raise objections. Based on the human’s objections, the machine assists the commander to continuously adjust and optimize the combat plan, forming a command mode of “human opposing and machine correcting”.

Based on “self-awareness and initiative”, we build a command model of “people lead and machines follow”

Comrade Mao Zedong once said that what we call “conscious initiative” is the characteristic that distinguishes humans from objects. Any complex practical activity to transform the world starts with a rough and abstract idea. To transform abstract concepts into concrete actions, it is necessary to overcome various risks and challenges, give full play to conscious initiative, and take the initiative to set goals, make suggestions, and think of ways. Artificial intelligence without conscious initiative, when people ask it questions, it only gives the answers implied in the model, without caring whether the answer can be used, targeted, or practical. In other words, when an abstract and empty question is raised, it gives an abstract and empty answer. This is also why the current popular large model unified operation mode is “people ask questions and machines answer”, rather than “machines ask questions”.

Relying on conscious initiative, even the most abstract and empty problems can be transformed step by step into specific action plans and specific action practices. Therefore, in intelligent combat command, the commander is mainly responsible for planning what to do and what ideas to follow, while the intelligent model is responsible for planning how to do it specifically. If the combat mission is too abstract and general, the commander should first break down the problem into details, and then the intelligent model should solve the detailed problem. Under the guidance of the commander, the problem is gradually solved in stages and fields, and the combat goal is finally achieved, forming a command mode of “people lead and machines follow”. It’s like writing a paper. First you make an outline and then you start writing. People are responsible for making the outline, and the specific writing is done by the machine. If the first-level outline is not specific enough, people can break it down into a second-level or even a third-level outline.

Based on “self-responsibility”, build a command model of “human decision-making and machine calculation”

Modern advanced ship-borne air defense and anti-missile systems usually have four operational modes: manual, semi-automatic, standard automatic, and special automatic. Once the special automatic mode is activated, the system will no longer require human authorization to launch missiles. However, this mode is rarely activated in actual combat or training. The reason is that humans, as the responsible subject, must be responsible for all their actions, while the behavior of machines is the absence of the responsible subject. When it comes to holding people accountable for major mistakes, machines cannot be held accountable. Therefore, life-and-death matters must not be decided by a machine without autonomous responsibility. Moreover, modern artificial intelligence is a “black box”. The intelligent behavior it exhibits is inexplicable, and the reasons for right and wrong are unknown, making it impossible for people to easily hand over important decision-making power to machines.

Because AI lacks “autonomous responsibility”, all problems in its eyes are “domesticated problems”, that is, the consequences of such problems have nothing to do with the respondent, and the success or failure of the problem solving is irrelevant to the respondent. Corresponding to this are “wild problems”, that is, the consequences of such problems are closely related to the respondent, and the respondent must be involved. Therefore, in the eyes of AI without self, there are no “wild problems”, all are “domesticated problems”, and it stays out of any problem. Therefore, in intelligent combat command, machines cannot replace commanders in making judgments and decisions. It can provide commanders with key knowledge, identify battlefield targets, organize battlefield intelligence, analyze battlefield conditions, predict battlefield situations, and even form combat plans, formulate combat plans, and draft combat orders. However, the plans, plans, and orders it gives can only be used as drafts and references. As for whether to adopt them and to what extent, it is up to the commander to decide. In short, both parties make decisions together, with artificial intelligence responsible for prediction and humans responsible for judgment, forming a command mode of “human decision-making and machine calculation”.

現代國語：

從「缸中之腦」看智慧化作戰指揮

■劉 奎 秦芳菲

要點提示

●現代人工智慧，本質上就如同“缸中之腦”，如果讓它實施作戰指揮，始終會面臨主體缺失即“自我”缺失的問題。這使得人工智慧存在天然的、根本的缺陷，必須基於人的主體性，透過人機混合來提升作戰指揮效能和水平

●智能化作戰指揮中，指揮員主要負責規劃做什麼、依什麼思路做，智能模型則負責規劃具體怎麼做

「缸中之腦」是一項著名科學假設。意思是，假如人的大腦被取出放在營養液中，神經末梢接上計算機，由計算機模擬出各種感知信號。這時候，「缸中之腦」能不能意識到「我是缸中之腦」？答案是不能，因為人作為一個封閉的系統，當與外界缺乏真實的互動體驗時，人是無法跳出自身、從自身之外觀察自身並形成自我意識的。而現代人工智慧，本質上就如同“缸中之腦”，如果讓它實施作戰指揮，始終會面臨主體缺失即“自我”缺失的問題。這使得人工智慧存在天然的、根本的缺陷，必須基於人的主體性，透過人機混合來提升作戰指揮效能和水準。

基於“自由選擇”，建構“人謀機劃”的指揮模式

戰場上，指揮員可以選擇打哪一個目標，可以選擇從正面打、從翼側打、從背後打、從空中打；可以隔而不打、圍而不打、談而不打……這就是人的自主性，可以自由選擇做什麼、怎麼做。但機器不行，它給出的作戰方案，只能是智慧模型中蘊含的方案。就每次給出的特定方案而言，也是機率統計意義上可能性最大的方案。這使得人工智慧生成的方案呈現“模板化”傾向，相當於一個“復刻機”，同樣的問題，它給出的是相似的回答，同樣的作戰場景，它給出的就是相似的作戰方案。

與人工智慧相比，同樣的作戰場景，不同的指揮員設計的作戰方案完全不同；同一指揮員在不同的時間面對相似的作戰場景，設計的作戰方案也不相同。 “攻其無備，出其不意”，最有效的方案很可能看上去是最危險、最不可能的方案。對於指揮員，面對作戰場景，一瞬間有無限可能，而對於人工智慧，一瞬間卻只有看上去最好的確定，缺乏創意、缺少謀略，很容易為對方所預料。所以，在智慧化作戰指揮中，要基於人的自主性，由指揮員負責籌謀算計、創新戰法打法、設計基本策略，由機器負責將基本策略轉化為可執行可操作的作戰方案，形成「人謀機劃」的指揮模式。更重要的是，自主性是人作為人而存在的獨特標志，這種自由作決定的權力不可能也不允許讓渡給機器，使人淪為機器的附庸。

基於“自我批判”，建構“人反機正”的指揮模式

人類的成長進步，通常是立足現實自我，著眼理想自我，對歷史自我進行否定之否定式的批判。人工智慧沒有“自我”，同時也喪失了自我批判能力。這使得它只能停留在原有認知框架內解決問題，模型擁有的作戰思想、作戰原則、戰法打法，是在訓練完成時所給予的。如果想獲得知識和想法的更新提升，就必須從外部對模型進行持續訓練。映射到特定作戰場景，智慧模型給指揮員提供的只能是事先給定的問題解決方案，要想在一次作戰中不斷地動態調整更新是做不到的。

具有自我批判精神的人類，可以跳脫指揮決策思考過程，對指揮決策進行審視、評價、批判。在持續地自我批判中不斷對作戰方案進行調整，甚至推翻原有方案，形成新的方案。在指揮機構群體中，其他指揮人員也可能對作戰方案提出不同意見，指揮員在充分吸納這些意見的基礎上，調整改進原有方案，實現作戰方案的動態進化。所以，作戰指揮本質上是一個不斷向前探索的動態過程，不是作戰方案事先給定的靜態過程。當機器生成作戰方案時，指揮員不能不加思考地盲目接受，而應充當“反對者”“找茬人”，對作戰方案展開反思批判，提出反對意見，機器根據人的反對意見，輔助指揮員不斷調整、優化作戰方案，形成「人反機正」的指揮模式。

基於“自覺能動”，建立“人引機隨”的指揮模式

毛澤東同志說過，我們名之曰“自覺的能動性”，是人之所以區別於物的特點。任何一項改造世界的複雜實踐活動，都是從粗糙的、抽象的想法開始的，要將抽象觀念轉化為具體行動，需要克服各種風險和挑戰，充分發揮自覺能動性，主動定目標、出主意、想辦法。沒有自覺能動性的人工智慧，人們向它提出問題，它給出的只是模型中蘊含的答案，而不會管這個答案能不能用、有沒有針對性、可不可以實際操作，即提出抽象、空洞的問題，它給出的就是抽象、空洞的回答。這也是為什麼時下流行的大模型統一的運行模式是“人問機答”，而不是“機器提出問題”。

依賴自覺能動性，再抽象、空洞的問題都能由人一步一步轉化為具體的行動方案、具體的行動實踐。因此，在智慧化作戰指揮中，指揮員主要負責規劃做什麼、依什麼思路做，智慧模型則負責規劃具體怎麼做。若作戰任務太過抽象籠統，應先由指揮員對問題進行分解細化，再由智慧模型對細化後的問題進行解算。在指揮引導下，分階段、分領域逐步解決問題，最終達成作戰目標，形成「人引機隨」的指揮模式。這就像寫一篇論文，先列出提綱，再進行寫作，列提綱由人負責，具體寫作由機器完成，如果感覺一級綱目不夠具體，可由人細化為二級乃至三級綱目。

基於“自主負責”，建立“人斷機算”的指揮模式

現代先進的艦載防空反導系統，通常有手動、半自動、標準自動、特殊自動四種作戰模式，一旦啟用特殊自動模式，系統發射導彈將不再需要人的授權幹預。但該模式無論在實戰還是在訓練中都很少啟用。究其原因，人作為責任主體要對自己的所有行為負責，而機器行為背後卻是責任主體的缺失，當要為重大失誤追責時，機器是無法負責的。所以，生死攸關的大事決不能讓一個沒有自主責任的機器決定。況且，現代人工智慧是一個“黑箱”，它所展現的智能行為具有不可解釋性，對與錯的原因無從知曉，讓人無法輕易將重大決定權完全交給機器。

由於人工智慧缺乏“自主責任”，會使它眼中的問題全是“馴化問題”，也就是該類問題產生的後果與回答者沒有關系，問題解決的成功也罷、失敗也罷，對回答者來說無所謂。與之相應的是“野生問題”，也就是該類問題產生的後果與回答者息息相關，回答者必須置身其中。所以，在缺失自我的人工智慧眼中沒有“野生問題”，都是“馴化問題”，它對任何問題都置身事外。因此，在智慧化作戰指揮中，機器不能取代指揮員做出判斷和決策。它可以為指揮員提供關鍵知識、識別戰場目標、整編戰場情報、分析戰場情況、預測戰場態勢，甚至可以形成作戰方案、制定作戰計劃、擬製作戰命令，但它給出的方案計劃命令，只能作為草稿和參考，至於採不採用、在多大程度上採用，還得指揮員說了算。簡單來說，就是雙方共同做出決策，人工智慧負責預測，人負責判斷，形成「人斷機算」的指揮模式。

中國原創軍事資源：http://www.81.cn/yw_208727/16361814.html

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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