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Artificial Intelligence Brings About New Changes in Chinese Military Training

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人工智慧為中國軍事訓練帶來新變化

現代英語：

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

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

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

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

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

現代國語：

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

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

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

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

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

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

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

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

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中國軍方將區分人工智慧在戰爭中的作用和功能

現代英語：

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

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

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

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

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

　　The unreliability of artificial intelligence in prediction and judgment during war

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

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

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

　　Artificial intelligence has limited involvement in military decision-making tasks

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

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

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

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

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

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

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

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

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

現代國語：

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

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

軍事組織決策的戰略脈絡為人工智慧帶來了巨大挑戰

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

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

戰爭中人工智慧在預測與判斷上的不可靠性

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

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

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

人工智慧在軍事決策任務機制中參與受限

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

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

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

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

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

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

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

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

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

原文責任編輯：舒建軍 馬氍鴻

（本文註釋內容略

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

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

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數位化、網路化、智慧化的中國武器化，抓住中國新一代資訊科技的焦點

現代英語：

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

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

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

　　Digitalization: From computerization to dataization

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

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

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

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

　　Networking: From the Internet to Cyber-Physical Systems

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

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

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

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

　　Intelligence: From Expert Systems to Meta-Learning

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

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

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

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

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

現代國語：

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

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

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

數位化：從電腦化到資料化

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

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

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

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

網路化：從網際網路到資訊物理系統

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

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

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

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

智能化：從專家系統到元學習

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

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

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

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

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

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

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

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

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中國的立場文件：規範人工智慧的軍事應用

現代英語：

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

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

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

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

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

To this end, we call for:

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

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

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

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

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

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

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

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

現代國語：

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

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

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

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

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

為此，我們呼籲：

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

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

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

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

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

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

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

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

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

#Information Support Force, #intelligent warfare, #中國的耗散戰, #中國軍事人工智慧武器化, Asymmetric Warfare, China's Informatization - 中國信息化, Chinese Artificial Intelligence, Chinese Military Artificial Intelligence Weaponizatio, Chinese Military Characteristics & Development Trends of Cognitive Domain Operations and Warfare, Chinese Military Cognitive Domain Operations, Chinese military cognitive warfare, Chinese Military Future Wars, Chinese Military Informatization, Chinese Military Views - 中國軍事觀, Information Support Force, Intelligent Warfare, Mosaic Warfare, Multi-Domain Operations, 中國軍事認知戰, 中國軍事認知領域作戰, 中國軍民融合計劃, 中國軍用反衛星武器研製, 中國軍隊對耗散戰的戰術運用, 認知域戰

Chinese Military Analysis on the Strategic Application of Intelligent Warfare

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中國軍事對智慧戰爭戰略應用的分析

現代英語：

An analysis of the use of strategies in intelligent warfare

■Chen Dongheng, Zhong Ya

Reading Tips: “Warfare is the art of deception”. War is a competition of comprehensive strength. Ancient Chinese military strategists have always attached great importance to “strategizing in the tent and winning thousands of miles away”, and all of them regard strategy as the way to victory. War practice shows that as long as war is a confrontation between humans, smart strategies will not withdraw from the battlefield. Today’s battlefield competition is about intelligent skills, and what is fought is smart strategies.

“The best military is to attack the enemy’s strategy, the next best is to attack the enemy’s alliance, the next best is to attack the enemy’s soldiers, and the worst is to attack the city.” Strategy, as a component of combat power and a weapon to win the war, runs through ancient and modern times and transcends national boundaries, and has an important function of influencing and determining the outcome of the war. Although the role of science and technology is more prominent in intelligent warfare, it does not exclude the use of strategy. With the support and guidance of strategy, the combat system is more efficient. In-depth research and mastery of the use of strategy in intelligent warfare will be more conducive to winning the initiative in intelligent warfare.

The status and role of the use of strategy in intelligent warfare

The essence of strategy lies in the intelligent release of power. Scientific strategy application can often defeat the majority with the minority, the big with the small, and the strong with the weak. The battlefield of intelligent warfare presents more transparency, more extended combat space, more diverse means of confrontation, and more complex winning mechanism. This provides a solid material foundation and technical support for the implementation of strategy, and the status and role of strategy are becoming more and more important.

The internal driving force of the army construction and development planning. Demand is the order of the army, and use is the commander of the weapon. How science and technology are innovated, how weapons and equipment are developed, and how the national defense forces are built are often driven by demand and forward-looking planning. For example, in order to make up for the gap between Russia and the United States in terms of overall air defense and anti-missile strength, Russia used “asymmetric” strategies to focus on penetration technology and developed the “Zircon” and “Dagger” hypersonic missiles before the United States. Facts show that the application of strategies mainly focuses on “Tao” and “Fa”. The more reasonable the design and the more scientific the application, the more it can stimulate the motivation, vitality and potential of innovation and creation, and trigger a revolution in science and technology, weapons and equipment, and military construction and combat methods. Only when intelligent warfare, scientific and technological innovation and weapons and equipment development are closely connected with the needs of scientific war strategies can they adhere to the correct direction and be better transformed into actual combat power.

A multiplier of the actual combat effectiveness of the combat system. In the combat power spectrum, strategy, as an important soft power, has the value and significance of providing scientific methodological guidance, appropriate time and opportunity selection and correct path support for the use of military hard power. For example, Iran once used the “dislocation” tactics to launch a large-scale retaliatory air strike against Israel, first using hundreds of cheap drones to attract the consumption of Israel’s expensive air defense system, and then using more advanced high-value ballistic missiles to penetrate, which improved the hit rate to a certain extent. Facts show that when facing an opponent with superior hard power, if the strategy is used properly, it can also achieve miraculous results; and the same hard power may have very different combat effectiveness when using different strategies and tactics. In intelligent warfare, although the “blade” of military hard power is faster, in order to make it more effective, it still needs to rely on more sophisticated strategic “sword skills”.

Dependent variables of hybrid warfare operations. Strategy can not only empower military hard power, but also has a strong direct combat function, and can even defeat the enemy without fighting by “soft killing”. For example, the United States once spent a lot of money to capture the leader of al-Qaeda, Osama bin Laden, but he seemed to have disappeared from the world, and technical means could not determine his exact hiding place. He was finally tracked down by targeting his messenger through strategic use. The United States’ “live broadcast” “Spear of Poseidon” operation attempted to show the strength of the US military by killing Bin Laden to shock the international community. Intelligent warfare is a hybrid warfare, which has entered a new era of global live broadcast, universal participation, and full coverage. More and more countries are adopting strategic methods to enhance their own confidence and strike the opponent’s will to resist, and the strategic “soft kill” combat function is becoming more and more apparent.

Basic mechanism of intelligent warfare strategy application

Intelligent warfare, high-level development of artificial intelligence, rapid iteration, full spectrum penetration, and high-efficiency release, make the application of strategy have more dimensional support and stronger drive, showing a unique operation mechanism.

Cluster operation of strategy application. The application of strategy is based on the underlying logic of war operation and follows the law of evolution of the subject from individual to team and then to system. From a historical perspective, the application of strategy warfare in the cold weapon era relied more on the wisdom and experience accumulation of generals. Natural factors such as geography and weather are the main grasps of strategy operation. The burning of Red Cliff and borrowing arrows from straw boats are vivid footnotes. In the mechanized era, in order to adapt to the increasingly complex composition of military branches and the needs of fast-paced operations, the “General Staff” of senior military institutions dedicated to war planning services came into being. The “General Staff” in the two world wars is a typical representative. In the information age, the use of war strategies mainly relies on the control of information, and information power has become the main support behind strategic planning. In intelligent warfare, the comprehensiveness of technology application, the systematic nature of force planning, and the platform characteristics of game confrontation are more prominent, and the internal requirements are that the subject of strategy implementation should shift to a more powerful systematic platform.

Algorithm-driven strategy application. Strategy is based on strategy. The essence of planning is calculation, calculation of the world situation, calculation of military situation, calculation of development trend, calculation of strength and weakness, calculation of winning advantage… Whether it is calculation by human brain or machine, calculation by generals or calculation by teams, calculation is always the most critical supporting factor. Generally speaking, whoever has stronger computing power, more precise algorithms, and faster calculations can grab the “calculation” machine and win the victory. In the era of intelligent calculation, artificial intelligence participates in strategic decision-making with human-machine hybrid algorithms or machine algorithms, which greatly enhances the efficiency of calculation. It is based on this that major countries have focused on breakthroughs in artificial intelligence to win the future competition. These artificial intelligences, characterized by strong computing power, have great application potential in simulating battlefield situations, simulating war processes, and assisting decision-making and command. Only by guarding against the opponent’s technical aggression, vigorously improving our computing power, and adding the wings of algorithms to traditional strategies can we be invincible in the strategic game confrontation.

Intelligent support for the use of strategies. In intelligent warfare, strategies are based on the rapid development of artificial intelligence and its extensive military applications. It is a two-way “rush” of human strategic wisdom and “technical” wisdom. Now, the generals’ ingenuity and traditional staff work have become increasingly difficult to adapt to the needs of intelligent warfare. Comprehensive intelligent command and decision-making platforms have become an important support for the implementation of strategies. The command and decision-making system of the US military has developed into a large platform that integrates four-layer structural functions, including “intelligence support, information fusion, mission coordination, autonomous decision-making, action deployment, force allocation, situation adjustment, and real-time tracking”, and has become the brain of its “decision-making center warfare”. The Russian Federation Armed Forces Combat Command Center can dispatch and monitor the training and exercises of the entire army in real time, and undertake combat command tasks in low-intensity small-scale conflicts. It can be seen that intelligent support for strategic planning and strategy implementation has gradually taken shape. Intelligent strategic confrontation has put forward higher requirements for the professional integration of strategic subjects, and promoted the deep integration of human biological intelligence and artificial intelligence, which is “human-like intelligence”.

Main ways to use strategies in intelligent warfare

In intelligent warfare, the era background, supporting conditions, and action mechanisms of strategy application have undergone profound changes. The way of implementing strategies must keep pace with the times, strive to combine traditional strategic advantages with new technologies and new forms of warfare, innovate and expand scientific paths to effectively release strategic energy, and strive to plan quickly, plan carefully, and integrate strategy and attack.

Intelligent technology integration releases energy. That is, make full use of intelligent technology to empower and release energy for strategies. Generally speaking, the effective implementation of strategies is inseparable from accurate information perception, rapid personnel mobilization, and efficient force strikes. The innovative application of artificial intelligence enables people to see farther, hear more closely, know more, and calculate faster, making the army gather and disperse more quickly, move more covertly, and release power more rapidly, which is more conducive to the generation of strategies and the achievement of effectiveness. On the one hand, with the help of the rapidity and autonomy of artificial intelligence, the enemy situation can be quickly grasped through intelligent reconnaissance, the decision-making time can be greatly shortened by using machine algorithms, and the optimal strategy can be selected with the help of simulation deduction; on the other hand, relying on artificial intelligence to release and enhance the efficiency of strategies, modern brain control technology, deep fake technology, information confusion technology, public opinion guidance technology, etc., have greatly expanded the space and means of implementing strategies.

Human-machine complementation releases energy. That is, the strengths and weaknesses of human intelligence and machine intelligence complement each other and enhance efficiency and release energy. The biggest advantage of machine intelligence over human intelligence is that it can fight continuously without being affected by biological factors such as will, emotion, psychology, and physical strength. However, the “meta-intelligence” of human intelligence and its ability to adapt to changes are not possessed by machine intelligence. The two intelligence advantages complement each other and aggregate to form a powerful hybrid intelligence, which strongly supports the use of strategies in war. On the one hand, the “machine brain” safely and efficiently makes up for the shortcomings of the human brain; on the other hand, the human brain responds to special situations on the spot. Facts show that the biggest advantage of human intelligence over machine intelligence is that it can make decisions and deal with different situations on the spot, which just makes up for the shortcomings of machine intelligence. Only by combining the two can we form the optimal solution for intelligent calculation and gather the strongest strategic application.

The platform releases energy as a whole. It is to create a modular intelligent system, an integrated intelligent decision-making command action platform that integrates strategy generation and release. Intelligent warfare, every second counts, improves the time sensitivity of target strikes. The intelligent platform comprehensively uses intelligent computing and command automation technology to efficiently process massive data and complex battlefield situations, creating a “super brain” for commanders. It has significant advantages of good functional connection, high stability, fast operation speed, and high combat efficiency. It is a new quality combat force for strategic planning. Relying on the intelligent command and control system, it can make real-time decisions, form a list of time-sensitive targets, and independently solve the combat units and strike platforms that can be summoned and struck the fastest and best. The hardware and software can accurately strike the targets, and accurate strikes on time-sensitive targets can be achieved in real-time decisions, providing more options for assisting war decision-making and command.

(Author unit: Academy of Military Science)

現代國語：

試析智慧化戰爭的謀略運用

■陳東恆 鐘 婭

閱讀提示　「兵者，詭道也」。戰爭是綜合實力的比拼和競賽。我國古代兵家歷來重視“運籌帷幄之中，決勝千里之外”，無不把謀略視為取勝之道。戰爭實踐表明，只要戰爭是人類的對抗，智慧謀略就不會退出戰場。今天的戰場比拼，打的是智能技能，拼的更是智慧謀略。

「上兵伐謀，其次伐交，其次伐兵，其下攻城。」謀略作為戰鬥力的構件和製勝戰爭的利器，貫穿古今、超越國界，具有影響和決定戰爭勝負的重要功能。智能化戰爭中雖然科技的角色更突顯，但並不排斥謀略的運用，在謀略的支撐和引領推動下，作戰體系反而效率更高。深入研究掌握智慧化戰爭的謀略運用，更有利於贏得智慧化戰爭的主動權。

智慧化戰爭謀略運用的地位作用

謀略的本質在於力量的智慧化釋放。科學的謀略運用常能以少勝多、以小博大、以弱勝強。智慧化戰爭戰場呈現更透明、作戰空間更延展、對抗手段更多樣化、制勝機理更複雜等特點，這為施謀用計提供了堅實物質基礎和技術支撐，謀略的地位作用愈發重要。

軍隊建設發展規劃的內動力。需為軍之令，用為器之帥。科學技術如何創新、武器裝備怎樣發展、國防軍隊怎麼建設，常常由需求牽引、前瞻謀劃。例如，俄羅斯為彌補防空反導整體力量方面與美國的差距，運用「非對稱」謀略在突防技術上發力，先於美國研發出「鋯石」「匕首」高超聲速導彈。事實表明，謀略運用主要著力於“道”和“法”，其設計越合理、運用越科學，越能激發創新創造的動力、活力和潛力，引發科學技術、武器裝備和軍隊建設作戰方式的革命。智慧化戰爭，科技創新和武器裝備開發只有緊密對接科學的戰爭謀略需求，才能堅持正確的方向，更好地轉化為現實的戰鬥力。

作戰體系實戰效能的倍增器。在戰鬥力譜系中，謀略作為重要的軟力量，其存在的價值和意義在於為軍事硬實力運用提供科學的方法論指引、合適的時機場合選擇和正確的路徑支撐。例如，伊朗曾利用「錯置」戰法對以色列發動大規模報復性空襲，先是以數百架廉價無人機吸引消耗以軍昂貴的防空系統，繼而用更先進的高價值彈道導彈突防，一定程度上提高了命中率。事實顯示，面對硬實力佔優的對手，如果謀略運用得當也能收到奇效；而同樣的硬實力運用不同的策略戰法，作戰效能可能大相徑庭。智慧化戰爭，雖然軍事硬實力的「刀鋒」更快，但要使其發揮更大戰鬥效能，還需藉助更高明的謀略「刀法」。

混合戰爭作戰運籌的因變數。謀略不僅能為軍事硬實力賦能，本身還有強大的直接作戰功能，甚至能以「軟殺傷」不戰而屈人之兵。例如，美國曾重金緝拿基地組織頭目本·拉登，但他好像人間蒸發一樣，技術手段無法確定其確切藏身處，最終通過謀略運用盯上其信使才追踪到。而美國「直播」「海神之矛」作戰行動，則企圖透過擊殺賓拉登來展現美軍的強大，以震撼國際社會。智慧化戰爭是混合戰爭，已經進入全球直播、全民參與、全域覆蓋的全新時代，越來越多的國家採取謀略方式增強己方信心、打擊對手抵抗意志，謀略「軟殺傷」的作戰功能越加顯現。

智慧化戰爭謀略運用的基本機理

智慧化戰爭，人工智慧的高階位元發展、快速度迭代、全頻譜滲透、高效能釋放，使謀略運用有了更多維的支撐、更強大的驅動，展現出獨特的運行機理。

謀略運用的集群作業。謀略的運用，既基於戰爭運行的底層邏輯，也遵循施動主體從個體到團隊再到體系的流轉演進規律。從歷史上看，冷兵器時代的謀略戰爭運用，更多靠將帥的智謀和經驗積累，地理、天候等自然因素是謀略運籌的主要抓手，火燒赤壁、草船借箭就是其生動註腳。機械化時代，適應日益復雜的軍兵種構成和快節奏作戰需要，專司戰爭謀劃服務的高級軍事機構“參謀部”便應運而生，兩次世界大戰中“總參謀部”就是其中的典型代表。資訊化時代謀略的戰爭運用，依靠的主要是對資訊的掌控，資訊力成為謀略運籌背後的主要支撐力。智慧化戰爭，技術應用的綜合性、力量運籌的體系性、博弈對抗的平台化特徵更加突出，內在要求謀略的施動主體向功能更強大的體系化平台轉進。

謀略運用的演算法驅動。謀略以謀為關鍵。謀的本質是算，算天下大勢、算軍事態勢、算發展趨勢、算強弱勝勢、算制勝優勢……無論是人腦算還是機器算、將帥算還是團隊算，算始終是最關鍵的支撐要素。一般情況下，誰的算力更強、演算法更精、算計更快，誰就能搶得「算」機、贏得勝算。智能化時代的算，人工智慧以人機混合演算法或機器演算法參與謀略決算，極大增強了算的效率。正是基於此，各主要國家紛紛把贏得未來競爭的成長點聚焦到人工智慧突破上。這些以強算力為特徵的人工智慧，在模擬戰場態勢、模擬戰爭進程、輔助決策指揮上有極大應用潛力。謹防對手技術突襲，大力提高我們的算力，為傳統謀略插上演算法的翅膀，才能在謀略博弈對抗中立於不敗之地。

謀略運用的智慧支撐。智慧化戰爭，謀略基於的是人工智慧迅猛發展及其廣泛軍事應用，是人的謀略之智與「技術」之智的雙向「奔赴」。現在，將帥的神機妙算、傳統的參謀作業，已經越來越難以適應智能化戰爭需要，綜合性的智能化指揮決策平台，成為施謀用計的重要支撐。美軍的指揮決策體系，已經發展成為融「情報保障、資訊融合，任務協調、自主決策，行動展開、力量配屬，態勢調整、實時跟踪」等四層結構功能於一體的大平台，成為其「決策中心戰”的大腦。俄羅斯聯邦武裝力量作戰指揮中心，可即時調度監控全軍訓練演習，並在低強度小規模沖突中擔負作戰指揮任務。可見，智慧支撐謀略運籌、策略實施逐步形成。智慧化謀略對抗，對謀略主體的專業化整合性提出了更高要求，推動人的生物智慧與人工智慧這一「類人智慧」深度融合結合。

智慧化戰爭謀略運用的主要方式

智慧化戰爭，謀略運用的時代背景、支撐條件、作用機理等發生了深刻變化。施謀用計的方式必須與時俱進，努力把傳統謀略優勢與新的技術、新的戰爭形態結合起來，創新拓展有效釋放謀略能量的科學路徑，致力先知快謀、精謀巧打、謀打融合。

智技融合釋能。就是充分利用智慧科技為謀略賦能釋能。通常而言，謀略的有效實施離不開準確的資訊感知、迅捷的人員調動、高效的力量打擊。人工智慧的創新應用，使人看得更遠、聽得更切、知得更多、算得更快，使軍隊集散更迅速、行動更隱蔽、力量釋放更迅猛，更加有利於謀略生成和謀效達成。一方面，借助人工智慧的快速性、自主性，透過智慧偵察迅速掌握敵情，運用機器演算法極大縮短決策時間，借助模擬推演優選謀略方案；另一方面，依靠人工智慧為謀略釋放增效，現代控腦技術、深度偽造技術、資訊迷茫技術、輿論引導技術等，極大拓展了施謀用計的空間與手段。

人機互補釋能。就是人體智能與機器智能長短互補、增效釋能。機器智能與人體智能相比的最大優勢在於，能不受意志、情緒、心理、體力等生物因素的影響連續作戰。而人體智能的「元智能」及其隨機應變的能力則為機器智能所不具備。兩種智能優勢互補聚合形成強大的混合智能，強力支撐謀略的戰爭運用。一方面，「機腦」安全高效補人腦不足；另一方面，人腦臨機應對處置特殊情況。事實表明，人體智慧相比機器智慧的最大優勢在於面對不同情況能臨機決策處置，這恰好彌補了機器智慧的不足。只有把兩者結合起來，才能形成智慧運算最優解，聚成謀略運用最強能。

平台一體釋能。就是打造模塊化的智慧系統，整合謀略生成、釋放的一體化智慧決策指揮行動平台。智慧化戰爭，分秒必爭，提高了目標打擊時敏感性。智慧化平台綜合運用智慧化計算和指揮自動化技術，高效處理海量數據及復雜戰場態勢，為指揮員打造“超強大腦”，具有功能銜接好、穩定程度高、運行速度快、作戰效率高的顯著優勢，是謀略運籌的新質作戰力量。依托智能化指揮控制系統能夠實時決斷，形成時敏目標清單，自主解算能夠最快召喚、最優打擊的作戰單元、打擊平台，軟硬一體對目標進行精確打擊，在實時決斷中實現對時敏目標的精確打擊，為輔助戰爭決策指揮提供了更多選項。

（作者單位：軍事科學院）

中國原創軍事資源：https://www.81.cn/ll_208543/16345416888.html

#Information Support Force, #intelligent warfare, #新興戰爭技術, Asymmetric Warfare, China's Informatization - 中國信息化, Chinese Military Artificial Intelligence Weaponizatio, Chinese Military Characteristics & Development Trends of Cognitive Domain Operations and Warfare, Chinese Military Use of Cognitive Confrontation within the Combat Domain, Chinese Military Views - 中國軍事觀, Cognitive Confrontation, Cognitive Domain Warfare, Dissipative Warfare, Information Support Force, Intelligent Warfare, 中國軍隊對耗散戰的戰術運用, 以認知為中心的戰爭：應對複雜戰爭的作戰概念, 認知戰

Chinese Intelligent Warfare Cannot be Successful Without Human Element

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中國智慧戰爭離不開人的因素

2019年10月17日 17:00 來源：解放軍報 作者：徐莉

現代英語：

An important task in studying intelligent warfare is to accurately position humans in intelligent warfare.

　　No matter how high the “kite” of intelligent weapons and equipment flies, it can only be controlled by humans and autonomously by machines. Humans must have a strong enough kite string and hold it tightly at all times.

　　”Synchronous development of man and machine” should be regarded as a basic principle for the development of military intelligence. Intelligence should integrate both “things” and “people”.

　　At present, the research on intelligent warfare is in the ascendant. Some people believe that intelligent warfare will be unmanned as the core form of expression, and unmanned equipment such as drones, unmanned submarines, and robot soldiers will become the protagonists of war. The form of war will also develop from the co-starring of “human-machine collaborative warfare” to the one-man show of “machine vs. machine war”. People seem to have become bystanders in intelligent warfare, with the meaning and trend of “intelligent warfare makes people go away”. What is the status and role of people, who have always been the main body of war, in intelligent warfare? This is the first problem that should be solved in the study of intelligent warfare.

　　The Marxist view of war holds that weapons are an important factor in war, but not the decisive factor. The decisive factor is people, not weapons. Although people no longer directly control weapons in advanced intelligent warfare, the following factors still determine that people are the main body of war and the key to winning.

　　First, war is the continuation of politics. The launching of war and the control of the war process must be decided by people according to political needs. The game outside the battlefield has a decisive influence on the progress of the war. For example, the results of diplomatic negotiations, the focus of international public opinion, and the support of the domestic people all depend on the decisions of politicians and military strategists, which cannot be replaced by any intelligent machines.

　　Secondly, war planning and command can only be implemented by commanders at all levels. Military command is both a science and an art, but it is more of an art. Any successful battle or campaign in the world is the result of commanders breaking routines and stereotypes and using troops creatively. The history of our army’s growth and development has repeatedly proved that correct military strategic guidance and flexible strategies and tactics are the magic weapon for our army to defeat the strong with the weak and defeat the many with the few, which enables our army to move from victory to victory. It is also something that intelligent machines cannot imitate or create. For example, in the battle, the comparative analysis of enemy and our combat forces, the real-time control of the combat situation, the real-time evaluation of the overall damage effect, the combat psychological analysis of enemy commanders, and the prediction of the next combat action, etc., intelligent machines can only provide auxiliary decision-making information and suggestions. Commanders at all levels must make decisions, make combat decisions, and issue combat orders.

　　Third, the level of intelligence of weapons and equipment ultimately depends on humans. Artificial intelligence originates from human intelligence. One of the major factors restricting the development of intelligence is that the scientific understanding of human intelligence is still superficial, and the understanding of the cognition, memory, thinking, decision-making and action mechanism of the human brain is still insufficient. The “Wuzhen Index: Global Artificial Intelligence Development Report 2016” pointed out that over the years, the proportion of biological research in the four sub-fields of artificial intelligence, machine learning, natural language processing, computer vision, and robotics, has been the lowest. Due to the lack of attention to the basic and decisive influence of brain science on artificial intelligence, the current artificial intelligence can only stay at the stage of superficial understanding and primary imitation of brain functions. Once there is a major breakthrough in the understanding of human intelligence, artificial intelligence will also be reborn and enter a leapfrog development stage.

　　Fourth, only humans can control intelligent weapons and equipment and combat platforms. Although the final intelligent weapons can be operated without human on-site control, when to put intelligent weapons and equipment into battle, when to change the direction of attack, how to control the rhythm of the war, when to withdraw from the battle, etc., can only be decided by humans in the end. This is the basic principle that must be grasped when designing intelligent weapons and equipment, that is, one of Asimov’s three laws of robotics: robots must obey human orders. Once intelligent weapons and equipment are out of human control, it will be a disaster for the entire human race, not just the enemy. This also determines that no matter how high the “kite” of intelligent weapons and equipment flies, it can only be controlled by humans and autonomous control functions of machines. The autonomous function of machines can only be effective within the scope limited by humans. Humans must have a strong enough kite line and hold it tightly at all times.

　　Fifth, only humans can crack and control the enemy’s intelligent weapons and equipment. The development of military history has proved that any weapon and equipment has its “Achilles’ heel” and will eventually be defeated. There has never been and will never be perfect and impeccable weapons and equipment in history, and intelligent weapons and equipment are no exception. The magic weapon to defeat the enemy is humans with infinite wisdom. For example, drones seem advanced, but they can be interfered, trapped or controlled by radio waves of a specific frequency. The same is true for other intelligent weapons and equipment, and finding and studying methods, technologies, and equipment to crack, control, and destroy intelligent weapons and equipment is where human wisdom comes into play.

　　Therefore, “synchronous development of man and machine” should be taken as a basic principle for the development of military intelligence. Intelligence should be applied to both “objects” and “people”. As soldiers in the era of intelligent warfare, they must master the working principles and weak links of intelligent weapons and equipment, be familiar with and master the “thinking mode” and “conventional actions” of intelligent weapons and equipment, as well as the abnormal “abnormal thinking” and abnormal “extraordinary actions” that may appear, and understand their technical and tactical indicators and performance. Especially in the stage of man-machine collaborative operations, soldiers are required not only to be able to coordinate actions with machines, but also to communicate with machines without obstacles in cognitive ability and intelligence. This not only relies on intelligent knowledge reserves, but also relies on the “brain reading” and “brain strengthening” of intelligent equipment. Scientific research shows that the normal human brain usage rate is only 3%-5%, which shows that there is still a huge room for improvement and release of human intelligence. When studying intelligent warfare, we should also study how to improve human intelligence.

　　In the face of intelligent warfare, we should prepare for the future, establish intelligent troops suitable for intelligent warfare as soon as possible, study the way to defeat the enemy in intelligent warfare, and establish and improve the theory of intelligent warfare; repair, maintain and improve intelligent weapons and equipment; study the methods, techniques and equipment to decipher the control keys of enemy weapons and equipment; study effective means to attack the enemy’s intelligent weapons and equipment, rewrite their combat rules and targets, and make them turn against us in the face of battle, or use high-energy lasers and high-power microwaves to directly destroy the enemy’s communication networks and weapons and equipment, demonstrating the way to win in intelligent warfare.

　　In short, in intelligent warfare, people are still the main body of war and the decisive factor in the outcome of war. An important task in studying intelligent warfare is to find the correct position of people in intelligent warfare. Otherwise, it is easy to fall into the idealistic quagmire of “seeing things but not people”, “only weapons” and “only technology”.

現代國語：

研究智能化戰爭的一項重要任務，就是找準智能化戰爭中人的定位。

不論智慧化武器裝備這個「風箏」飛多高，永遠只能是人類控制與機器自主控制功能並存，人類必須擁有足夠結實的風箏線並時刻牢牢抓住它。

應把「人機同步發展」當作軍事智慧化發展的一個基本原則，智慧化既要化「物」也要化「人」。

當前，對智慧化戰爭的研究方興未艾。一些觀點認為，智慧化戰爭將以無人化為核心表現形式，無人機、無人潛航器、機器人士兵等無人裝備將成為戰爭主角，戰爭形態也將從「人機協同作戰」的聯袂主演，最後發展到「機器對機器大戰」的獨角戲。人似乎成了智慧化戰爭的旁觀者，大有「智慧化戰爭讓人走開」的意味和態勢。曾經一直是戰爭主體的人，在智能化戰爭中的地位和角色究竟是什麼，這是研究智能化戰爭應當首先解決的問題。

馬克思主義戰爭觀認為，武器是戰爭的重要因素，但不是決定的因素，決定的因素是人而不是武器。雖然在高階階段的智慧化戰爭中，人不再直接操控武器，但以下因素仍決定了人是戰爭的主體和關鍵的致勝力量。

首先，戰爭是政治的延續，戰爭的發動、戰爭進程的掌控，必須由人視政治需求作出決定。戰場以外的博弈對戰爭進程有著決定性的影響，如外交談判的結果、國際輿論的焦點、國內民眾支持度等，均取決於政治家、軍事家的決策，是任何智能化的機器都無法替代的。

其次，戰爭規劃和指揮只能由各級指揮官來實施。軍事指揮既是科學，也是藝術，但更體現為藝術。世界上任何一場取得勝利的戰鬥、戰役，都是指揮者打破常規和定式，創造性用兵的結果。我軍成長壯大的歷史也一再證明，正確的軍事戰略指導、機動靈活的戰略戰術，是以弱克強、以少勝多，使我軍不斷從勝利走向勝利的製勝法寶，也是智能化機器所無法模仿和創造的。例如，戰中對敵我作戰力量的比較分析、作戰態勢的即時掌控、整體毀傷效果的即時評估、敵軍指揮作戰心理分析，以及對下一步作戰行動的預判等等，智慧化機器只能提供輔助決策資訊和建議案，必須由各級指揮官親自決策、下定作戰決心，並下達作戰命令。

第三，武器裝備智慧化程度高低最終取決於人類。人工智慧源自人類智能，目前製約智能化發展的一大因素，就是對人類智能的科學認識尚膚淺，對人類大腦的認知、記憶、思維、決策和行動機理等的認識還很不夠。 《烏鎮指數：全球人工智慧發展報告2016》指出，歷年來人工智慧的機器學習、自然語言處理、電腦視覺、機器人四類細分領域涉及生物學研究的比例均最低。由於不重視腦科學對人工智慧基礎和決定性的影響，直接導致當前人工智慧只能停留在對大腦功能膚淺認識和初級模仿階段，一旦對人類智慧的認識有了重大突破，人工智慧也必將脫胎換骨，進入跨越式發展階段。

第四，控制智慧化武器裝備和作戰平台的只能是人。雖然最終的智慧化武器可以沒有人類現場操控，但智慧化武器裝備何時投入戰鬥、何時轉換進攻方向、如何把控戰爭節奏、何時撤出戰鬥等等，最終只能由人來決定，這是智慧化武器裝備設計時必須掌握的基本原則，即阿西莫夫機器人三定律之一：機器人必須服從人類的命令。一旦智能化的武器裝備脫離了人的控制，那將是整個人類而不僅僅是敵人的災難，這也決定了不論智能化武器裝備這個“風箏”飛多高，永遠只能是人類控制與機器自主控制功能並存，機器自主功能只能在人類限定的範圍內有效，人類必須擁有足夠堅固的風箏線並時刻牢牢抓住它。

第五，破解、控制敵人智慧化武器裝備的只能是人。軍事歷史發展證明，任何武器裝備都有其“阿喀琉斯之踵”，最終都會被擊敗。歷史上從來沒有、未來也不會出現完美無缺、無懈可擊的武器裝備，智慧化武器裝備也不例外，而克敵制勝的法寶就是擁有無窮智慧的人類。例如，無人機看似先進，但完全可以被特定頻率的電波幹擾、誘捕或控制。其他智慧化武器裝備也是如此，而尋找並研究破解、控制、擊毀智慧化武器裝備的方法、技術、裝備，則是人類聰明才智的用武之地。

因此，應把「人機同步發展」作為軍事智能化發展的一個基本原則，智能化既要化「物」也要化「人」。作為智能化戰爭時代的軍人，必須掌握智能化武器裝備的工作原理和薄弱環節，熟悉並掌握智能化武器裝備的“思維方式”和“常規動作”，以及可能出現的非常態的“異常思維”和變態的“超常動作”，了解其技戰術指標及性能，特別是人機協同作戰階段，不僅要求軍人能夠與機器協調行動，而且在認知能力和智力上能夠和機器無障礙交流，這不僅要依靠智能化的知識儲備，也要依賴智慧化裝備的「讀腦」「強腦術」。科學研究表明，正常人大腦使用率只有3%——5%，這說明，人類智慧仍有巨大的提升和釋放空間。研究智能化戰爭，也應同步研究如何提升人類智慧。

面對智慧化戰爭，我們應當未雨綢繆，儘早建立與智能化戰爭相適應的智能化部隊，研究智能化戰爭的克敵制勝之道，建立完善智能化戰爭理論；維修、保養、改進智能化武器裝備；研究破解敵方武器裝備操控密鑰的方法、技術、裝備；研究攻擊敵軍智能化武器裝備的有效手段，改寫其作戰規則和作戰對象，使其臨陣倒戈，或是利用高能量激光、高功率微波直接擊毀敵通信網絡和武器裝備，彰顯智慧化戰爭的致勝之道。

總之，智慧化戰爭中人仍是戰爭的主體，是戰爭勝負的決定性因素。研究智能化戰爭的一項重要任務就是找準智能化戰爭中人的定位。否則，就容易陷入「見物不見人」「唯武器論」「唯技術論」的唯心主義泥沼。

中國原創軍事資源：http://www.qstheory.cn/defense/2019-10/17/c_112511776588.htm

#Information Support Force, Asymmetric Warfare, China's Informatization - 中國信息化, China's Military Organization - Intelligence, Chinese Artificial Intelligence, Chinese Military Artificial Intelligence Weaponizatio, Chinese Military Characteristics & Development Trends of Cognitive Domain Operations and Warfare, Chinese military cognitive warfare, Chinese Military Future Wars, Chinese Military Informatization, Dissipative Warfare, 中國解放軍敘事戰爭, 中國軍隊對耗散戰的戰術運用, 以認知為中心的戰爭：應對複雜戰爭的作戰概念, 認知戰

Chinese Military Center of Gravity for Winning Intelligent Warfare

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中國打贏智慧戰爭的軍事重心

中國軍網 國防部網 // 2020年12月31日 星期四

現代英語：

The winning mechanism of war refers to the main factors for winning a war, the way they play a role, and the internal mechanisms, laws and principles of their mutual connection and interaction. With the advent of the intelligent era, the increasingly widespread application of artificial intelligence in the military field has promoted the transformation of the war form to intelligent warfare, and the winning mechanism of war has also changed accordingly.

Having data advantage is the basis for success

In the era of intelligence, the core foundation of many “disruptive technologies” is data, and war will also be “no data, no war”. In intelligent warfare, both sides will fight a “data war” around understanding data, relying on data, competing for data, and using data. Whoever owns the “data right” will have the initiative in the war. Fighting for data, mastering data, analyzing data, and applying data in war are the keys to winning intelligent warfare.

Data resources are combat effectiveness. In intelligent warfare, data comes first before troops move. Whoever controls the data controls the resources to win the war, and controls the initiative and the chips for victory. The ability to understand and use data is an important indicator for measuring combat capability and directly affects the outcome of the war. Obtaining data, analyzing data, and using data are not only the yardsticks for measuring the combat capability of troops, but also the new engine for improving the combat effectiveness of troops. Data is the most direct record of the objective world. It appears in the form of numbers and is raw data, such as the performance parameters of weapons and equipment, the size of troops, the number of guarantees, target parameters, etc. These data can be processed to become the information and intelligence needed for combat. In the information age led by data, data has become the blood of intelligent warfare.

Big data has given rise to a data-based battlefield. To some extent, whoever controls the data resources controls the “winning space” of the war. Data has changed the logical cognition of war. In the past, people inferred the whole from the individual and inferred the inevitability from the small probability events, but now they deduce individual characteristics from the high probability and find the internal laws of specific things from the correlation. Only by understanding the relevant data can we grasp the overall situation, only by gathering similar data can we grasp the trend, and only by integrating all-source data can we understand the connection. All of this is attributed to the control of the data-based battlefield.

Big data changes the way of fighting. As the most important strategic resource, how to distinguish the authenticity and quality of data, how to fight and counter-fight, deceive and counter-deceive, attack and counter-attack around massive data, has become a key issue in winning intelligent wars. When data becomes the focus of war, it will inevitably lead to competition and gaming around data, thereby promoting changes in the style of fighting. At present, the competition for data collection is intensifying, and major countries have launched research on national defense big data projects to provide more intelligence with practical value for military decision-making. The “asymmetry” of data forms the “asymmetry” of algorithms, and then achieves the “asymmetry” of tactics.

Data has given rise to intelligent equipment systems. Data technology has upgraded combat platforms to highly intelligent and autonomous systems. Data has enabled command and control systems, air combat platforms, precision-guided munitions, etc. to complete the transition from informatization to intelligence. For example, modern “swarm technology” is the application of artificial intelligence supported by big data. Data has become a “telescope”, “microscope” and “perspective lens” for analyzing wars. To win intelligent wars, one must have a data mind, data awareness and data thinking.

Mastering algorithm advantages is the key to success

One of the characteristics of intelligent warfare is that all battle plans, campaign plans and war plans need to be generated by computers, and its essence is algorithm-generated tactics. Having an algorithm advantage means having an intelligent advantage, which can achieve a high degree of unity of information advantage, cognitive advantage, decision-making advantage and action advantage.

Algorithm advantage dominates information advantage. Algorithm is a systematic method to describe the strategic mechanism for solving problems, and is the key and prerequisite for improving intelligence advantage. Algorithm technology mainly includes deep learning, supercomputing, brain-like intelligence and other technologies. The use of intelligent sensing and networking technology can widely and quickly deploy various types of intelligent perception nodes, and can implement active collaborative detection for tasks, thereby building a transparent and visible digital combat environment. Judging from the current development trend, the advantage of war algorithms dominates information advantage, which contains great potential to rewrite the rules of the modern war game. This pair of “invisible hands” will shape the new landscape of future intelligent warfare.

Algorithmic advantage dominates cognitive advantage. In intelligent warfare, big data can quickly convert massive amounts of data into useful intelligence after being processed by high-performance and efficient algorithms, thereby gaining cognitive advantage. Algorithms, as the “brain” of artificial intelligence, have become the key to intelligently sensing the battlefield and using it for decision-making, command, and coordination. The party with algorithmic advantage can dispel the “battlefield fog” and “information fog” caused by the failure to process data in a timely manner, making cognition more profound and thus seizing the initiative in the war. In the future, whoever has algorithmic advantage will have stronger cognitive ability, faster learning speed, and better quality results.

Algorithm advantage dominates decision-making advantage. With its high-speed and precise calculation, the algorithm can replace people’s hard thinking and repeated exploration, thereby accelerating knowledge iteration. With the support of massive data and supercomputing capabilities, the judgment and prediction results of artificial intelligence will be more accurate. By constructing combat model rules through algorithms, commanders can be assisted in making rapid decisions in multi-level planning and ad hoc handling of strategies, campaigns, tactics, etc. through actuarial, detailed, deep and expert reasoning. With the development of disruptive technologies such as big data, cloud computing, and quantum computing and their application in the military field, the future combat decision-making cycle will become near real-time. In intelligent warfare, the party that masters super algorithms can quickly propose flexible and diverse combat plans and countermeasures in response to changes in combat opponents, constantly disrupting the opponent’s established intentions and deployments, and thus seize the dominance of the war.

Algorithmic advantage leads to operational advantage. In the era of intelligent warfare, algorithms determine tactics, and algorithmic advantage leads to war advantage. Supported by superior algorithms, the reaction speed of artificial intelligence is thousands of times that of humans. “Algorithmic warfare” foreshadows the transformation of future wars. Whoever can seize the commanding heights of intelligent algorithms can seize the initiative and win before the battle. On the intelligent battlefield, algorithms are far more important than artillery shells. War algorithms have become the key factor in winning intelligent warfare and are the strategic commanding heights that future intelligent armies must seize. Intelligent warfare calculations are ubiquitous. The party that has the algorithmic advantage can quickly and accurately predict the battlefield situation, innovate combat methods, and achieve the advantage of “winning before the battle.”

Multi-domain integration is the key to success

Multi-domain integration is based on the cloud-based combat system. With the support of the cloud-based battlefield situation, various combat personnel, equipment, facilities, and environmental elements have expanded the battlefield space from the traditional three-dimensional space to the polar regions, deep sea, space, and cyberspace, and even to multi-dimensional domains such as cognitive domain and information domain. Multi-domain integration has formed a giant, complex, and adaptive confrontation system. The integration of “cloud gathering” and “network gathering” has become a new mechanism for intelligent combat.

Cross-domain integration and integrated energy release. Under the conditions of intelligent warfare, the emergence of a large number of new long-range combat platforms and intelligent new concept weapons has made the future combat landscape present the characteristics of air-ground-sea-sky integration, global instant strikes, and cross-domain strategic deterrence and control. Supported by the cross-domain, distributed, and networked “cloud killing” collaborative combat system, through the cross-domain aggregation of multiple combat capabilities, cross-domain interoperability of combat command, cross-domain sharing of combat information, cross-domain movement of combat weapons, cross-domain response of combat actions, and cross-domain complementarity of combat functions are achieved. Cross-domain integration is the close coordination of main domain control and cross-domain support to implement cross-domain collaborative support. Integrated energy release is the transition of joint operations from integrated joint operations to cross-domain joint operations, realizing the cross-domain aggregation and overall energy release of multiple combat capabilities.

Human-machine integration, using speed to defeat slowness. If weapons are an extension of the human body, intelligence is an extension of the human brain. In the era of intelligent warfare, there will be a mode of giving human intelligence to machines to implement combat. People will further withdraw from the front-line confrontation and combat, and the combination of people and weapons will appear in a new form. Unmanned combat weapons and human intelligence are deeply integrated into an organic symbiosis, perfectly combining human creativity, thinking and the precision and speed of machines. Therefore, in future intelligent warfare, the mode of engagement will gradually change from the mutual killing of “human-machine integration” to the unmanned system cluster confrontation of “human-machine integration”. Relying on the intelligent combat system, commanders adaptively adjust and select the mode of action according to changes in the battlefield environment. Unmanned combat develops from single-platform remote control combat to multi-platform cluster autonomy, forming a simple command chain of “commander-combat cluster”, highlighting the rapid, flexible and autonomous characteristics of human-machine collaboration.

Brain-intelligence fusion and efficient control. The combat system of intelligent warfare will be characterized by a highly intelligent “human + network + machine”. The intelligent command and control system will operate in a collaborative manner of “human brain + intelligent system”. The intelligent system will assist or even partially replace the role of humans in command and control. The intelligent command and control system will have relatively strong autonomous command and control capabilities, and can relatively independently obtain information, judge situations, make decisions, and deal with situations. Relying on the battlefield situation awareness system, with the help of big data, cloud computing, artificial intelligence, and modeling and simulation technology, it is possible to accurately analyze and judge massive battlefield information, realize the transformation of combat command from “human experience-centered” to “data and model-centered” intelligent decision-making methods, and make combat planning more scientific and efficient. In the future, the super self-evolution and strategic decision-making capabilities of deep neural networks will realize the combat cycle of “human out of the loop”.

Integration of intelligence and mind, attacking the mind and winning the will. With the development of artificial intelligence technology, the boundaries between the biologicalization and humanization of intelligent weapons will be blurred in the future, and the control of people themselves will become the focus. “Attacking the mind and winning the will” is still the highest combat purpose of intelligent warfare. “Cognitive control warfare” based on the control of human brain and consciousness cognition may evolve into an important combat style. With human cognitive thinking as the target, various means are used to stimulate, influence and control the cognitive system to achieve the effect of disrupting the enemy’s command and decision-making system, inducing the enemy’s combat power, and disintegrating the enemy’s morale. For example, based on brain reading and brain control technology, using mental guidance and control means, the strategic intentions, combat intentions, and combat methods of the enemy commander can be grasped in real time, and even directly act on the brain of the enemy personnel, or the consciousness of the party can be “injected” in the form of EEG coding to interfere with or control their consciousness, thinking and psychology, and finally seize the “right to control intelligence” and achieve deep control over combat personnel. With the large-scale application of intelligent combat platforms on the battlefield, information systems assisting humans will gradually transform into intelligent systems partially replacing humans. The focus of the power struggle will shift from “information rights” to “intelligence rights”, and using elite troops to gain control of key domains will become the dominant approach.

現代國語：

戰爭制勝機理，指贏得戰爭勝利的主要因素、發揮作用的方式及其相互聯繫、相互作用的內在機制、規律和原理。隨著智慧時代的到來，人工智慧在軍事領域越來越廣泛的應用，推動戰爭形態轉向智慧戰爭，戰爭制勝機制也隨之改變。

擁有數據優勢是致勝基礎

在智慧化時代，眾多「顛覆性科技」的核心根基就是數據，戰爭也將是「無數據不戰爭」。在智慧化戰爭中，雙方圍繞著認識數據、依靠數據、爭奪數據和運用數據開打“數據戰”，誰擁有“數據權”，誰就掌握了戰爭的主動權。爭奪數據、掌握數據、分析數據，並將數據運用於戰爭之中，是智慧化戰爭的勝利之要。

數據資源就是戰鬥力。在智慧化戰爭中，兵馬未動，資料先行。誰掌握了數據誰就掌握了取得戰爭勝利的資源，也就掌控了戰爭的主動和勝利的籌碼。認識和運用數據的能力，是衡量作戰能力的重要指標，直接影響戰爭的勝負。取得數據、分析數據和運用數據既是衡量部隊作戰能力的標尺，也是提升部隊戰鬥力的新引擎。數據是客觀世界最直接的記載，以數字的形式出現，是原始資料，如武器裝備的性能參數、兵力規模、保障數量、目標參量等，這些數據經過處理能夠成為作戰所需的資訊和情報。在數據引領的資訊時代，數據已成為智慧化戰爭的血液。

大數據催生數據化戰場。某種程度上講誰把控了資料資源，就把握了戰爭的「勝利空間」。數據改變了對戰爭的邏輯認知，過去是從個別推論整體、從小機率事件中推理必然性，而現在是從大概率中推導個別特徵、從相關性中找出具體事物的內在規律。只有洞察相關數據才能掌握全局，只有聚集同類數據才能掌握趨勢，只有融合全源數據才能洞悉關聯。而這一切都歸於對資料化戰場的把控。

大數據改變作戰樣式。數據作為最重要的戰略資源，如何辨別數據的真假優劣，如何圍繞海量數據開展爭奪與反爭奪、欺騙與反欺騙、攻擊與反攻擊，成為打贏智能化戰爭的關鍵問題。當數據成為戰爭爭奪的焦點，必然帶來圍繞數據的競賽和博弈，從而推動作戰樣式改變。目前，資料收集之爭愈演愈烈，大國紛紛進行國防大數據計畫研究，以便為軍事決策提供更多具有實際價值的情報。以資料的“非對稱”，形成演算法的“非對稱”，進而實現戰法的“非對稱”。

數據催生智慧化裝備系統。數據技術使作戰平台升級為高度智慧化和自主化的系統，數據使指揮控制系統、空中作戰平台、精確導引彈藥等完成由資訊化向智慧化過渡。例如，現代「蜂群技術」就是大數據支撐下的人工智慧運用。數據已經成為解析戰爭的“望遠鏡”“顯微鏡”“透鏡”，打贏智能化戰爭必須具備數據頭腦、數據意識、數據思維。

掌握演算法優勢是致勝關鍵

智慧化戰爭的特徵之一就是一切戰鬥計畫、戰役計畫和戰爭計畫都需轉向電腦生成上來，其本質就是演算法生成戰法。擁有演算法優勢就擁有智慧化優勢，就可以實現資訊優勢、認知優勢、決策優勢和行動優勢的高度統一。

演算法優勢主導資訊優勢。演算法是用系統化的方法描述解決問題的策略機制，是提高智慧優勢的關鍵和前提。演算法技術主要包括深度學習、超級運算、類腦智慧等技術。採用智慧感測與網路技術，可廣泛快速部署各類智慧感知節點，可面向任務實施主動協同探測，進而建構透明可見的數位化作戰環境。從當前的發展趨勢來看，戰爭演算法優勢主導資訊優勢，蘊含著改寫現代戰爭遊戲規則的巨大潛力，這雙「無形之手」將塑造未來智慧化戰爭新圖景。

演算法優勢主導認知優勢。在智慧化戰爭中，大數據經過高效能、高效率的演算法處理後，能夠將大量資料快速轉換為有用的情報，從而獲得認知優勢。演算法作為人工智慧的“大腦”，成為智慧感知戰場並由此用於決策、指揮和協同的關鍵。佔有演算法優勢的一方，能驅散因資料得不到及時處理而產生的“戰場迷霧”和“資訊迷霧”，使得認知更為深刻，從而奪取戰爭主動權。未來誰擁有演算法優勢，誰的認知能力就強，學習速度就快，品質效果就優。

演算法優勢主導決策優勢。演算法以其高速、精確的計算，能夠取代人的苦思冥想和反覆探索，加速知識迭代。在海量數據和超算能力支援下，人工智慧的判斷和預測結果將更加準確。透過演算法建構作戰模型規則，以精算、細算、深算和專家推理方式，可輔助指揮官在戰略、戰役、戰術等多層規劃規劃和臨機處置中實現快速決策。隨著大數據、雲端運算、量子運算等顛覆性技術的發展及其在軍事領域的應用，未來作戰決策週期將變成近實時。在智慧化戰爭中，掌握超強演算法的一方能夠針對作戰對手變化，快速提出靈活多樣的作戰方案與應對之策，不斷打亂對手既定企圖與部署，從而奪取戰爭主導權。

演算法優勢主導行動優勢。在智慧化戰爭時代，演算法決定戰法，演算法優勢主導戰爭優勢。在優勢演算法的支撐下，人工智慧的反應速度是人類的千百倍。 「演算法戰」預示著未來戰爭的變革，誰能搶佔智慧演算法制高點，誰就能搶得先機，未戰先勝。在智慧化戰場上，演算法遠比砲彈重要，戰爭演算法成為致勝智能化戰爭的關鍵因素，是未來智慧型軍隊必須搶佔的戰略高點。智慧化戰爭運算無所不在，掌握演算法優勢的一方，能夠快速且準確預測戰場態勢，創新作戰方法，達成「未戰而先勝」之利。

搞好多域融合是製勝樞紐

多域融合是以作戰體系的雲態化為基礎，各類作戰人員、裝備、設施、環境要素在雲態化的戰場態勢支撐下，戰場空間從傳統的三維空間，向極地、深海、太空和網電空間，乃至認知域、資訊域等多維域拓展，多域融合形成巨型複雜自適應對抗體系，「雲聚」融合「網聚」成為智慧化作戰新機理。

跨域融合、整合釋能。在智慧化戰爭條件下，多種新型遠戰平台、智慧化新概念武器的大量湧現，使未來作戰面貌呈現出空地海天一體、全球即時性打擊、跨域戰略懾控等特徵。以跨領域、分散式、網路化的「雲殺傷」協同作戰系統為支撐，透過多種作戰能力跨域聚合，實現作戰指揮跨域貫通，作戰資訊跨域共享，作戰兵器跨域穿行，作戰行動跨域回應，作戰功能跨域互補。跨域融合是主域主控與跨域支援的緊密配合，實施跨域協同支援。整合釋能是聯合作戰由一體化聯合作戰過渡到跨域聯合作戰，實現多種作戰能力的跨域聚合、整體釋能。

人機融合、以快製慢。如果說武器是人身體延伸的話，智慧則是人腦的延伸。智能化戰爭時代，將出現把人的智慧賦予機器進而實施作戰的模式，人將更進一步退出一線對抗作戰，人與武器結合方式將以嶄新形態出現。無人作戰武器與人類智慧深度融合為有機共生體，把人的創造性、思想性和機器的精準性、快速性完美結合。因此，在未來智慧化戰爭中，交戰方式將由「人機結合」的相互殺傷逐漸轉向「人機融合」的無人系統集群對抗。依托智能化作戰系統，指揮員針對戰場環境變化自適應調整選擇行動方式，無人作戰由單平台遙控作戰向多平台集群自主方向發展，形成「指揮官—作戰集群」的簡易指揮鏈，彰顯人機協同的快速靈活自主特徵。

腦智融合、高效控制。智慧化戰爭的作戰體系將表現為高度智慧化的“人+網路+機器”，智慧化指揮控制系統將以“人腦+智慧系統”的協作方式運行，智慧系統將輔助甚至部分替代人在指揮控制中的作用。智慧化指揮控制系統將具備較強的自主指揮、自主控制能力，可相對獨立自主地獲取資訊、判斷態勢、做出決策、處置狀況。依托戰場態勢感知系統，借助大數據、雲端運算、人工智慧和建模模擬技術，能夠對海量戰場資訊進行精準分析研判，實現作戰指揮由「以人的經驗為中心」向「以數據和模型為中心」的智慧化決策方式轉變，作戰規劃更加科學有效率。未來深度神經網路的超強自我進化和戰略決策能力，將實現「人在迴路外」的作戰循環。

智心融合，攻心奪志。隨著人工智慧技術的發展，未來智慧化武器的生物化和人的武器化將界線模糊，針對人本身的控制將成為焦點，「攻心奪志」仍是智慧化戰爭最高作戰目的，基於以人腦和意識認知實施控制為目標的「認知控制戰」可能演化為重要作戰樣式。以人的認知思維為目標，運用多種手段對認知體系施加刺激、影響與控制，達成擾亂敵指揮決策系統、誘導敵作戰力量、瓦解敵軍心士氣的效果。如基於讀腦、腦控技術，運用心智導控手段，即時掌握對方指揮官戰略意圖、作戰企圖、作戰方法等，甚至直接作用於對方人員大腦，或將己方意識以腦電編碼形式“注入” ，幹擾或控制其意識、思維和心理，最終奪取“制智權”，實現對作戰人員的深度控制。隨著智慧化作戰平台大量應用於戰場，資訊系統輔助人類將逐漸轉向智慧系統部分取代人類。制權爭奪的重心將由“資訊權”轉向“智能權”，以精兵點殺謀取關鍵維域控制權將成為主導方式。

中國原創軍事資源：https://www.81.cn/jfjbmap/content/2020-12/31/content_279888.htm

#Information Support Force, #中國的耗散戰, Asymmetric Warfare, China Cyber Dilemma in the 21st Century, China National Cyber Security Strategy, China's Informatization - 中國信息化, China's Military Organization - Intelligence, Chinese Artificial Intelligence, Chinese Military Artificial Intelligence Weaponizatio, Chinese Military Characteristics & Development Trends of Cognitive Domain Operations and Warfare, Chinese Military Cognitive Domain Operations, Chinese military cognitive warfare, Chinese Military Future Wars, Chinese Military Informatization, Chinese Military Use of Cognitive Confrontation within the Combat Domain, Chinese Military Views - 中國軍事觀, Dissipative Warfare, 中國解放軍敘事戰爭, 中國軍隊對耗散戰的戰術運用, 認知域戰, 認知戰

These Chinese Civilian AI “Black Technologies” Will Significantly Advance the People’s Liberation Army in “counterattacking” the US Military

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這些中國民用人工智慧「黑科技」將大幅推動解放軍「反攻」美軍

現代英語：

At the World Internet Conference held in Wuzhen in recent years, many leaders of technology companies talked most about artificial intelligence, and the “Light of the Internet Expo” at previous conferences has become a “big show” for various artificial intelligence. In particular, this year, many well-known Chinese Internet companies have shown off their own “black technology”, which is impressive. China’s rapid progress in the field of artificial intelligence has amazed the world. Reuters commented that China is expected to be on par with the United States in five years and become the world’s leading artificial intelligence innovation center. Like the United States, China has clearly made artificial intelligence a priority in both economy and military.

    The report, written by Elsa Kania of the Center for a New American Security, asserts that future competition between China and the United States in the field of artificial intelligence “may change the future balance of economic and military power.” Earlier this year, an undisclosed Pentagon document exaggerated that Chinese companies are circumventing official supervision by purchasing shares in American companies to obtain sensitive American artificial intelligence technologies with potential military uses. Andrew Ng, a well-known scientist in the field of machine learning, said that if the United States wants to stay ahead, it must focus on developing its own artificial intelligence. China is by no means a slouch in the field of artificial intelligence that only relies on foreign technology. Foreign media commented that while the West is still discussing and keeping a close eye on its own technology, China’s innovative progress has begun to rewrite the world’s artificial intelligence technology landscape. The next question is whether China is willing to play with the West.

    The discussion that artificial intelligence will change the rules of war is no longer news. The Brookings Institution website once published an article suggesting that the US military bet on six major technologies, and artificial intelligence technology is one of them. Today, artificial intelligence has made breakthroughs in assisting combat personnel in decision-making and connecting combat personnel with intelligent combat systems, and has been widely used in simulated combat training. Today, a large number of unmanned equipment with intelligent features have entered the arsenals of major countries. Among them, the most widely used US military has nearly 10,000 unmanned aerial systems and more than 12,000 unmanned ground systems, which have become an indispensable and important part of US military operations.

    In a simulated confrontation in June 2016, an artificial intelligence system developed by American researchers defeated two retired fighter pilots in a simulated air battle. In this simulated air battle, the blue team consisting of two fighter jets was equipped with a stronger weapon system, but the red team of the artificial intelligence system defeated the enemy aircraft through evasive maneuvers. After the game, the pilots thought that the program was very good at controlling the situation and was surprisingly responsive. It seemed to be able to predict human intentions and quickly fight back when the opponent changed flight movements or launched missiles. This incident has attracted widespread attention, and the prospect that artificial intelligence will completely replace human soldiers on the battlefield in the future seems to have been further confirmed.

    Throughout human history, most epoch-making technologies have emerged from the military and wars. Humans are more likely to burst out with inspiration at the moment of life and death, and have greater motivation to promote technological progress. In the field of artificial intelligence, the boundaries between the civilian and military use of many technologies are not obvious. Today, the world’s technology giants also have more talents and financial resources than most countries, and the broad application prospects make them more motivated to invest in research and development. The future trend of artificial intelligence technology is expected to be led by these technology giants. This is why in the field of artificial intelligence, the “military-civilian integration” of major countries has become more in-depth, and even the US military has “widely issued invitations to heroes.”

    For example, at this year’s Internet Conference, Chinese companies displayed a variety of artificial intelligence products and technologies, which have broad application prospects in both civilian and military fields and can be called “black technology”. Intelligent drones and unmanned vehicles, these intelligent equipment can accurately deliver express deliveries to customers based on the target location. If applied to the battlefield, it will make front-line supply and evacuation of wounded soldiers more accurate and convenient. In addition, there are artificial intelligence-assisted treatment products, which integrate artificial intelligence technologies such as image recognition and deep learning with medicine to assist doctors in early screening and diagnosis of patients. If this technology is applied to the battlefield, it will greatly improve the work efficiency and treatment speed of medical soldiers. There is also lip reading recognition technology, which can achieve the effect of voice recognition by recognizing lip reading, and can easily carry out complex communication even on a noisy battlefield. In October this year, the PLA Air Force Logistics Department signed the “Military-Civilian Integration Strategic Cooperation Agreement” with executives of five leading logistics companies. Regarding the use of drones specifically mentioned by the Air Force, relevant companies also introduced the development and planning of large logistics drones. Artificial intelligence has a high priority in China’s military-civilian integration, which will enable the PLA to make full use of technological advances in the commercial field to enhance its military capabilities.

    Intelligent machines represented by drones have demonstrated their power on the battlefield or in simulated confrontations. The U.S. Department of Defense report believes that intelligent swarm systems will occupy an important position in future wars. Intelligent swarm attack refers to a swarm system composed of intelligent robots or drones, in which each component of the system independently selects targets, attack forms and formation forms. Compared with manned systems, it has incomparable advantages in coordination, intelligence, cost and speed. The Pentagon called on talented people from the private sector to join the military’s “drone swarm” development, hoping to speed up progress. In June 2017, China’s 119 fixed-wing drones achieved formation flight, setting a record in number. Although it is still far from achieving high-level intelligent formation operations, the U.S. think tank “Project 2049 Institute” admits that China’s drone formation technology is more advanced than that of the U.S. military.

    In future wars, the balance of victory between the two warring parties may completely tilt towards the side with a higher degree of intelligence, and the possibility of the technological laggards continuing to rely on the development of asymmetric combat power to bridge the gap in combat power is gradually decreasing. When the two sides are on the same battlefield, while the officers and soldiers of the side with weaker technical capabilities are busy attacking, retreating, and transferring, the other side with stronger technical capabilities uses unmanned intelligent equipment for all-weather, high-precision intelligent reconnaissance and strikes. Perhaps trapped by ethical issues, the final decision is still made by humans, but the experience of these controllers in the control room thousands of miles away is like playing an online game. The flesh and blood on the battlefield will be exposed, and the opponent’s life will be wiped out with every mouse click or voice command of the enemy. The psychological competition between the strong and weak warring personnel will be completely unbalanced.

    As Russian President Vladimir Putin said, “Whoever becomes the leader in the field of artificial intelligence will be the leader of the future world.” Artificial intelligence has become the “high ground” of the next military competition, and China is already in a leading position in the field of artificial intelligence. The People’s Liberation Army has the opportunity to actively shape the future war model through military innovation. Reuters commented that artificial intelligence will promote the modernization of the Chinese military and may pose a strategic challenge to the US military. (Dong Lei)

現代國語：

近些年在烏鎮舉行的世界互聯網大會上，眾多科技公司領軍人物談及最多的就是人工智能，而歷屆大會的“互聯網之光博覽會”更成為各類人工智能“大秀場”，尤其今年多家知名網路公司紛紛曬出自家“黑科技”，令人印象深刻。中國在人工智慧領域的快速進步令世界驚嘆，路透社就評論稱，中國5年內有望比肩美國，成為全球首要的人工智慧創新中心。與美國一樣，中國在經濟和軍事上都明確地將人工智慧當作重點。

由新美國安全中心的埃爾莎·卡尼亞撰寫的報告斷言，未來中美兩國在人工智慧領域的競爭「可能會改變未來的經濟和軍事力量對比」。今年早些時候，五角大廈一份未公開文件渲染說，中國企業正透過購買美國公司的股權來繞過官方監管，以取得有潛在軍事用途的美國人工智慧敏感技術。機器學習領域知名科學家吳恩達稱，美國要保持領先就必須把注意力放在發展自己的人工智慧上，中國在人工智慧領域絕非一個只是依賴外來科技的懈怠者。外媒評論稱，當西方還在探討看緊自己的技術的時候，中國的創新進步已開始改寫世界人工智慧技術的版圖，接下來的問題是中國還願不願意帶著西方一起玩。

關於人工智慧將改變戰爭規則的論述早就不是新聞，美國布魯金斯學會網站曾刊文建議美軍在6大技術上押下賭注，人工智慧技術就位列其中。而今人工智慧在輔助作戰人員決策，以及作戰人員與智慧化作戰系統對接方面已經獲得突破，而在模擬實戰化訓練等方面更是得到大規模應用。如今大量具有智慧特徵的無人裝備進入了各大國的武器庫。其中應用最廣泛的美軍已擁有近萬個空中無人系統，地面無人系統更是超過1.2萬個，其已成為美軍行動不可或缺的重要組成部分。

在2016年6月的一次模擬對抗中，美國研究人員開發的人工智慧系統在模擬空戰中大勝2名退役的戰鬥機飛行員。在這次模擬空戰中，由2架戰鬥機組成的藍隊裝備更強的武器系統，但人工智慧系統的紅隊透過閃避動作擊敗了敵機。比賽結束後，飛行員認為這款程式非常善於掌控態勢，反應也靈敏得出奇，似乎能預測人類意圖，並在對手改變飛行動作或發射飛彈時迅速回擊。這事件曾引起廣泛關注，未來戰場人工智慧將全面取代人類士兵的前景似乎得到了進一步佐證。

縱觀人類歷史，大多數劃時代的技術都是興起於軍隊發端於戰爭，人類在生死存亡之際更能迸發出靈感，也擁有更大的推動技術進步的動力。而在人工智慧領域，許多技術的民用與軍用界限並不明顯，如今全球的科技巨頭們也擁有超越多數國家的人才和財力，而廣闊的應用前景則令他們在研發投入上更有動力，未來的人工智慧科技潮流有望被這些科技巨頭所引領。這也是為何在人工智慧領域，各大國的「軍民融合」都更為深入，連美軍也「廣發英雄帖」。

例如在今年的網路大會上，中國企業展示的多款人工智慧產品及技術，在民用及軍用領域都有廣闊的應用前景，堪稱「黑科技」。智慧無人機與無人車，這些智慧裝備可以依據目標位置，精準地把快遞送達顧客手中，如果應用於戰場將令前線補給及後撤傷員等行動變得更加精準便捷。另外還有人工智慧輔助治療產品，透過影像辨識、深度學習等人工智慧技術與醫學融合，進而達到輔助醫師對病患的早期篩檢與診斷，這項技術如果應用於戰場，將大大提升醫療兵的工作效率和救治速度。還有唇語辨識技術，透過辨識唇語就可以達到原本需要聲音辨識的效果，即使是在吵雜的戰場上也可輕鬆進行複雜交流。今年10月解放軍空軍後勤部與5家物流領域領導企業主管簽署了《軍民融合戰略合作協議》，而對於空軍方面特別提到的無人機運用，相關企業也介紹了大型物流無人機的研發和規劃。人工智慧在中國軍民融合中的優先順序很高，這將讓解放軍得以充分利用商業領域的技術進步來增強軍事能力。

以無人機為代表的智慧機器已經在戰場或模擬對抗中展現出威力。美國國防部報告認為，智慧化蜂群系統將在未來戰爭中佔據重要地位。智慧化蜂群攻擊是指智慧機器人或無人機組成的蜂群系統，系統各組成部分自主選擇目標、攻擊形式和編隊形式。相比有人系統，在協調性、智慧性、成本以及速度等方面擁有無可比擬的優勢。五角大廈號召來自民間的才俊加入到軍方的「無人機蜂群」開發中，希望能加快進度。 2017年6月，中國119架固定翼無人機實現編隊飛行，創造了數量紀錄，儘管距離實現高階的智慧化編隊作戰仍較遠，但是美國智庫「2049計畫研究所」坦言中國的無人機編隊技術較之美軍更為先進。

在未來戰爭中，交戰雙方的勝利天平或將徹底偏向智能化程度更高的一方，科技落伍者繼續靠發展不對稱戰力來彌合戰力差距的可能性正逐漸變小。當雙方置身於同一戰場，技術能力較弱一方的官兵在進攻、撤退、轉移，疲於奔命時，技術能力強的另一方則是無人智能裝備全天候、高精度的智能偵察、打擊。或許受困於倫理問題，最終的決策仍由人來完成，但其待在千里之外的控制室，這些控制人員的體驗就像是玩網路遊戲。戰場上的血肉之軀將無所遁形，對手的生命在敵人的每一次滑鼠點擊或是語音命令中灰飛煙滅，強弱雙方交戰人員的心理比拼將完全失衡。

正如俄總統普丁所說，「誰成為人工智慧領域的領導者，誰就是未來世界的領導者」。人工智慧已成為下一個軍事競爭的“制高點”，而中國在人工智慧領域已處於領先位置，解放軍有機會透過軍事創新主動塑造未來戰爭模式，路透社則評論認為，人工智慧將推動中國軍隊的現代化並可能對美軍形成戰略挑戰。 （董磊）

中國原創軍事資源：http://m.news.cn/mil/2017-12/20/c_1297707888.htm

#Information Support Force, #中國軍事人工智慧武器化, Asymmetric Warfare, China's Informatization - 中國信息化, China's Military Organization - Intelligence, Chinese Artificial Intelligence, Chinese Military Artificial Intelligence Weaponizatio, 中國軍隊對耗散戰的戰術運用

Chinese Military Weaponization of Artificial Intelligence

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中國軍事人工智慧武器化

現代英語：

In April this year, the Center for Strategic and Budgetary Assessments of the United States released a “roadmap” for the development of the platform forces of the future ground forces of the US military. The “roadmap” points out that in the future, human-machine teamwork warfare of ground forces will become the main combat style of future ground forces under the influence of robots, artificial intelligence and augmented technology. We still don’t know when unmanned forces will completely replace manned forces. But what is certain is that the mode of man-machine combination is profoundly affecting the future combat methods, changing the current combat force composition to a large extent, and may become the protagonist in future wars.

Please pay attention to the report of the Liberation Army Daily today:

Artificial intelligence technology will promote the organic integration of unmanned combat platforms and manned combat systems.

How far are we from being the protagonists of the human-machine ensemble?

■Zhou Xiaocheng, Gao Dongming, Yuan Yi

In April this year, the Center for Strategic and Budgetary Assessments of the United States released a “roadmap” for the development of the U.S. military’s future ground force platform forces. The “roadmap” points out that in the future, human-machine teamwork warfare of ground forces will become the main combat style of future ground forces under the influence of robots, artificial intelligence and augmented technology.

We still don’t know when unmanned forces will completely replace manned forces. But what is certain is that the human-machine combination model is profoundly affecting the future combat methods, changing the current combat force composition to a great extent, and may become the protagonist in future wars.

The realization of human-machine teaming has benefited greatly from the rapid development of military artificial intelligence technology. At present, military artificial intelligence technology has become an important driving force for the development of human-machine teaming, promoting its comprehensive application in military fields such as command decision-making, organization and deployment, equipment operation, combat support, military training, and rear support. Human-machine teaming based on military artificial intelligence technology will effectively promote a significant increase in the combat effectiveness of the army, give birth to a new war style, and change the internal mechanism of winning the war.

In the field of information perception and processing, the armies of the United States, Russia and other countries have been equipped with digital individual systems with intelligent information perception and processing capabilities, which help soldiers to accurately grasp complex battlefield situations in real time and quickly and efficiently deal with various problems arising on the battlefield. At the same time, the deployment and application of a series of intelligent unmanned reconnaissance equipment has greatly improved battlefield transparency and greatly shortened the time for information acquisition and processing.

In terms of unmanned combat platform construction, intelligent unmanned combat equipment, mainly intelligent unmanned vehicles, drones and unmanned submarines, has gradually emerged in military applications. Various auxiliary decision-making systems developed based on artificial intelligence technology can build a powerful grid network information system, enhance the ability of intelligence analysis, command and decision-making, and thus greatly improve the command and decision-making efficiency of human-machine combinations.

Human-machine combination usually consists of manned forces and unmanned forces. Among them, manned forces are the command center, and unmanned forces accept the command and control of manned forces and perform combat missions according to the command and control of manned forces. The three basic forms of human-machine combination can be summarized as human-robot combination, human-AI combination and personnel enhancement. The three forms will greatly improve the deployability, lethality and sustainability of future military forces.

Human-robot teaming refers to a partnership between humans and robots, which aims to improve the ability of humans to interact with various types of robot formations to perform specific tasks. In 2017, the U.S. Air Force demonstrated a manned and unmanned aircraft formation in the “Have-Airstriker II” exercise, with unmanned wingmen autonomously performing ground attack missions. Autonomously controlled unmanned wingmen are able to make value judgments based on changes in the battlefield environment, act according to new action plans, and successfully achieve the expected results. In the same year, the French Dassault Aviation Company successfully achieved a flight of hundreds of kilometers between the “Neuron” drone and the “Rafale” fighter, accumulating technical experience for the research and development of unmanned wingmen.

The combination of human and AI is mainly manifested in the weaponization of humans and the humanization of weapons, which are applied in strategic analysis, combat planning and command decision-making. This requires specialized analysis and research related to but different from the combination of human and robot. Last year, Facebook announced its entry into the field of non-invasive brain-computer interface research. The Advanced Research Projects Agency of the U.S. Department of Defense also announced funding for several research institutions to carry out neuroengineering system design projects to develop brain-computer interfaces that can be implanted in the human brain to achieve high-speed communication between humans and machines.

Personnel augmentation aims to enhance the existing combat capabilities of combat personnel by using mechanical, wearable and implantable external forces. For example, the currently developed equipment such as modular and expandable individual protective equipment, enhanced combat helmets, individual exoskeletons and wearable data recorders highlight the concept of people-oriented and achieve the goals of enhancing personnel protection capabilities, improving battlefield perception capabilities and enhancing individual combat effectiveness.

In the future, human-machine combination will change the traditional combat mode, give birth to new combat forces, blur the boundary between war and non-war, and have a profound impact on future wars. Its development trend is mainly concentrated in three aspects:

First, it is developing towards comprehensive multi-mission combat capabilities. With the needs of future operations, human-machine teaming is developing towards comprehensive, multi-mission capabilities such as reconnaissance and strike, command and control, and combat support. Multi-mission requirements will make human-machine teaming a key node in future operations. Improving comprehensive multi-mission combat capabilities is an inevitable trend in the development of human-machine teaming.

The second is to develop in the direction of distributed networking, cross-domain clustering and collaborative operations. Human-machine collaborative combat technology will become a research focus. Relying on artificial intelligence, data fusion and data management and other related technical support, unmanned combat nodes and manned combat nodes will be distributedly networked to achieve cluster combat of human-machine combination, form wide-area combat capabilities, and achieve the purpose of collaborative combat.

The third is to develop in the direction of system, intelligence and module. The system construction is constantly strengthened, and the system combat capability of human-machine combination is improved according to different battlefield environments and combat requirements, the intelligence level of system combat is improved, the autonomy and interaction ability of unmanned forces in performing tasks are improved, and combat tasks that manned forces are unable to perform are completed.

現代國語：

來源：中國軍網綜合 作者：周小程 高冬明 袁 藝 責任編輯：焦國慶 2018-09-21 03:35

今年4月，美國戰略與預算評估中心發布了美軍未來地面部隊平台力量發展的「路線圖」。該「路線圖」指出，未來地面部隊人機組合作戰將在機器人、人工智慧和增強技術的影響下，成為未來地面部隊的主要作戰樣式。無人力量何時會完全取代有人力量，目前我們還不得而知。但可以肯定的是，人機組合的模式正在深刻影響未來作戰方式，在很大程度上改變當前的作戰力量編成，或將成為未來戰爭中的主角。

請關註今日《解放軍報》的報導——

人工智慧技術將推動無人作戰平台與有人作戰系統有機融合——

人機組合唱主角離我們還有多遠

■周小程 高冬明 袁 藝

今年4月，美國戰略與預算評估中心發布了美軍未來地面部隊平台力量發展的「路線圖」。該「路線圖」指出，未來地面部隊人機組合作戰將在機器人、人工智慧和增強技術的影響下，成為未來地面部隊的主要作戰樣式。

無人力量何時會完全取代有人力量，目前我們還不得而知。但可以肯定的是，人機組合的模式正在深刻影響未來作戰方式，在很大程度上改變當前的作戰力量編成，或將成為未來戰爭中的主角。

人機組合的實現在很大程度上得益於軍用人工智慧技術的快速發展。當前，軍用人工智慧技術已成為人機組合力量發展的重要推手，推動其在指揮決策、編成部署、裝備運用、作戰支援、軍事訓練、後裝保障等軍事領域全面應用。基於軍用人工智慧技術的人機組合將有力促進軍隊戰鬥力大幅提升，催生新的戰爭樣式，改變戰爭制勝的內在機理。

在資訊感知與處理領域，美、俄等國的軍隊已裝備了具有智能化信息感知與處理能力的數字化單兵系統，為士兵實時準確地掌握復雜戰場情況，快速高效地處置戰場上出現的各種問題提供了幫助。同時，一系列智慧化無人偵察裝備的部署應用，大大提高了戰場透明度，使資訊取得和處理的時間大大縮短。

在無人作戰平台建設方面，以智慧化無人車、無人機和無人潛航器為主體的智慧化無人作戰裝備逐漸在軍事應用中嶄露頭角。基於人工智慧技術開發的各種輔助決策系統可建立功能強大的柵格化網路資訊體系，增強情報分析、指揮決策的能力，從而大幅提高人機組合的指揮與決策效能。

人機組合通常由有人力量與無人力量構成。其中，有人力量是指揮中樞，無人力量接受有人力量的指揮和控制，根據有人力量的指揮控制執行作戰任務。人機組合的三種基本形式可以概括為人-機器人組合、人-AI組合和人員增強，三種形式將極大地提高未來軍事力量的可部署性、殺傷性和可持續性。

人-機器人組合是指人與機器人之間的合作夥伴關系，旨在提高執行特定任務的人與各型機器人編隊互動的能力。 2017年，美國空軍在「海弗-空襲者Ⅱ」演習中，展示了有人機和無人機編隊，無人僚機自主執行對地攻擊的任務。自主控制的無人僚機能夠根據戰場環境變化做出價值判斷，以新的行動方案開展行動，並成功實現預期結果。同年，法國達梭飛機製造公司成功實現了「神經元」無人機與「陣風」戰鬥機的數百千米飛行，為無人僚機的研究發展積累了技術經驗。

人-AI的組合主要表現為人的武器化和武器的人化，應用於戰略分析、作戰規劃和指揮決策等方面，這需要開展與人-機器人組合相關卻又與之不同的專門分析研究。去年，「臉書」宣布進軍非侵入性的腦機介面研究領域。美國國防部高級研究計劃局也宣布資助多家研究機構，開展神經工程系統設計項目，開發可植入人腦的腦機接口，實現人機間高速通訊。

人員增強旨在利用機械的、可穿戴和可植入的外部力量來增強作戰人員現有的作戰能力。例如目前開發的注入模塊化拓展的單兵防護裝備、增強型戰鬥頭盔、單兵外骨骼和可穿戴數據記錄儀等設備，突出了以人為本的理念，達到了增強人員防護能力、提高戰場感知能力和提升單兵戰鬥力的目標。

未來，人機組合將改變傳統的作戰模式，催生新型作戰力量，模糊戰爭與非戰爭界限，對未來戰爭產生深遠影響。其發展趨勢主要集中在三個方面：

一是向綜合多任務作戰能力方向發展。隨著未來作戰的需要，人機組合正向具備偵察打擊、指揮控制、作戰支援等綜合型、多任務能力方向發展。多任務需求，將使人機組合成為未來作戰的關鍵節點。提升綜合多任務作戰能力是人機組合發展的必然趨勢。

二是向分散式組網、跨域集群和協同作戰方向發展。人機協同作戰技術將成為研究重點，依託人工智慧、數據融合與數據管理等相關技術支撐，由無人作戰節點、有人作戰節點進行分散式組網，實現人機組合的集群作戰，形成廣域的作戰能力，達到協同作戰的目的。

第三是向體系、智能、模塊方向發展。體系化建設不斷加強，針對不同的戰場環境和作戰需求，提高人機組合的體係作戰能力，提升體係作戰的智能化水平，提高無人力量執行任務時的自主性和交互能力，完成有人力量無法勝任的作戰任務。

中國原創軍事資源：http://www.mod.gov.cn/gfbw/tp_214132/jskj/4827888.html