The Birth Pangs of Intelligent Transformation and Their Resolution — An Analysis Based on Marx’s View of Machinery

Introduction

引 论

In July 2018, at the BRICS Business Forum, General Secretary Xi Jinping pointed out: “Science and technology are the primary productive forces, providing an inexhaustible driving force for the progress of human civilization. Humanity has experienced several leaps in agricultural civilization and industrial civilization, which brought about a great development of social productive forces, but also accompanied by the birth pangs of transformation. Today, the world has once again arrived at such an important historical juncture. In the great tide of a new round of scientific and technological revolution and industrial transformation, clearing away the old and establishing the new will inevitably lead to industrial change, and this process is difficult and painful.” In today’s world, artificial intelligence technology has become a powerful driving force for a new round of scientific and technological revolution and industrial transformation. The process of social intelligent transformation is accelerating, and the accompanying birth pangs of transformation are increasingly evident. Based on this, exploring the generative mechanisms of technological change, analyzing the deep roots of the “birth pangs” triggered by intelligent transformation, and proposing effective paths for their resolution have become important research topics.

2018年7月，习近平总书记在金砖国家工商论坛上的讲话中指出：“科技是第一生产力，为人类文明进步提供了不竭动力。人类曾经历农业文明、工业文明的数次飞跃，带来了社会生产力大发展，同时也伴生着蜕变的阵痛。今天，世界再次来到这样一个重要历史节点。在新一轮科技革命和产业变革大潮中，除旧布新必然导致产业变革，这个过程是艰难痛苦的。”当今世界，人工智能技术成为新一轮科技革命和产业变革的强大动力，社会智能化转型进程加速推进，与之伴生的转型阵痛也日益显现。基于此，探讨技术变迁的生成机制，剖析智能化转型引发“阵痛”的深层根源并提出有效的消解进路，已成为重要的研究课题。

Reviewing previous literature and research, there are three main representative views on the roots of the “birth pangs” caused by science and technology. The first view appeals to technology itself. For example, in the explanatory framework constructed by Daron Acemoglu and Pascual Restrepo, technology is divided into “enabling technologies” and “replacing technologies.” The former refers to technologies that help people complete existing tasks more efficiently, while the latter refers to new technologies that make work and skills redundant. “Enabling technologies” make transformation proceed smoothly and orderly, while “replacing technologies” trigger “birth pangs.” The second view attributes the roots to the individual themselves. This view holds that the reason some people benefit from technological change while others are eliminated is due to differences in intelligence or innate endowments among individuals. Both of the above views, to a certain extent, neglect the historical premise of the combination of technology and people: on the one hand, the “enabling effects” and “replacement effects” exhibited by technology are ultimately determined by specific socio-economic structures, not by technology itself; on the other hand, “the distribution of innate intelligence among different social classes is approximately random,” but inequality in initial resources limits the effectiveness of equal opportunity, suppresses the educational rights of disadvantaged groups, and prevents them from adapting to technological change. Compared with the above two views, the early socialist Owen paid attention to the dual nature of machinery. Owen pointed out that, under reasonable arrangements, “every invention and improvement in machinery will contribute to human labor.” However, “since the widespread installation of expensive machinery, the coercion imposed on human nature has far exceeded what it can generally endure. As a result, great harm has been brought to both individuals and the public.” “Machinery could have been the greatest blessing for humanity, but under the current arrangements, it has become the greatest calamity for humanity.” Owen attempted to solve the “machinery problem” by transforming society. In the “new villages” he envisioned, “people will adopt all measures to encourage the promotion of machinery and promote it forever, but it will not compete with human labor, but will only assist human labor.” Owen had profound insights into the significance of machinery and large-scale industry in the future development of society, but his understanding of the negative aspects of machinery and his solutions remained at the level of moral critique, failing to penetrate into the laws of social and historical operation. Schumpeter, starting from the paradigm of “creative destruction,” believed that the essence of the “birth pangs” phenomenon is a process of socio-economic dynamic competition and self-innovation. However, he failed to realize that the mutual competition and confrontation between old and new modes of production reflect the institutional defects of the macro socio-economic structure itself.

梳理既往的文献和研究，对于科学技术引发的“阵痛”之根源的探讨，主要有三种比较具有代表性的观点。第一种观点诉诸技术本身。例如在达龙·阿西莫格鲁和帕斯夸尔·雷斯特雷波构建的解释性框架中，技术被划分为“使能技术”和“取代技术”，前者指那些能够帮助人们更高效地完成已有任务的技术，后者指那些让工作和技能变得多余的新技术。“使能技术”会使转型平稳有序地进行，“取代技术”则会引发“阵痛”。第二种观点将根源归结于个体本身。这种观点认为，之所以部分人能够从技术变迁中获益而部分人被淘汰，是因为人与人之间在智力或先天禀赋上存在差异。上述两种观点都在一定程度上忽视了技术与人相互结合的历史前提：一方面，技术展现出的“使能效应”和“取代效应”归根结底是由特定社会经济结构所规定的，而非源于技术自身；另一方面，“不同社会阶层之间先天智力的分布近似是随机的”，但初始资源的不平等限制了机会均等的作用效力，抑制了弱势群体的受教育权利，使他们无法适应技术变迁。相较于上述两种观点，早期社会主义者欧文关注到了机器的双面性。欧文指出，在得到合理安排的情况下，“机器的每一种发明和改进都将有助于人类的劳动”。然而“自从普遍设置昂贵的机器设备以来，人性所受的强制已经远远超出了它一般所能忍受的限度。结果就给个人和公众都带来了极大的损害”。“机器本可以成为人类最大的福星，在目前的安排下却成了人类最大的灾祸。”欧文试图通过改造社会来解决“机器问题”。在他设想的“新村”中，“人们将采取一切办法鼓励推广机器，并将其永远推广下去，但它不会和人的劳动竞争，而只会有助于人的劳动”。欧文对机器技术和大工业在未来社会发展中的意义有深刻洞见，但他对机器消极面的认识及其解决之道，仍停留于道德批判层面，未能深入到社会历史运行的规律中去。熊彼特则从“创造性毁灭”范式出发，认为“阵痛”现象的实质是一个社会经济动态竞争和自我创新的过程。但未能意识到新旧两种生产方式相互竞争对抗所反映的是宏观社会经济结构本身存在的制度缺陷。

As early as the period of mechanized transformation, Marx keenly observed the situation where workers’ interests were damaged during the replacement of traditional hand tools by the system of machinery, and conducted an in-depth investigation of the relationship among capital, machinery, and labor. Although contemporary intelligent technology, as a combination of machine intelligence and biological intelligence, differs substantially from the machine technology of the industrial era, which served as an extension of human limbs, the relationship among capital, technology, and labor—the dominant factors behind intelligent transformation and mechanized transformation—shows great similarity. Therefore, we can still first follow Marx’s analytical framework, penetrate the dense fog to capture the core clues of the “birth pangs” induced by the capitalist application of technology, and, combined with new phenomena and new problems of the intelligent era, explore the deep socio-economic roots of the birth pangs of intelligent transformation. On this basis, we further explore possible paths to resolve the birth pangs of intelligent transformation.

早在机械化转型时期，马克思就敏锐地关注到了机器体系取代传统手工器具过程中工人利益受损的情形，并对资本、机器、劳动之间的关系进行了深入考察。尽管当代智能技术作为机器智能和生物智能的结合，与工业时代作为人类肢体延伸的机器技术存在实质性差别，但智能化转型与机械化转型背后的主导因素即资本、技术、劳动之间的关系却有着巨大相似性。因此，我们仍可以首先沿着马克思的分析框架，透过层层迷雾捕捉到技术的资本主义应用诱发的“阵痛”的核心线索，并结合智能时代的新现象、新问题，探讨智能化转型阵痛的深层社会经济根源，在此基础上进一步探讨消解智能化转型阵痛的可能进路。

I. Marx’s Original Diagnosis of the “Machinery Problem” and an Analysis of Its Applicability

一、马克思对“机器问题”的原初诊断及其适用性分析

The roots of “birth pangs” must be sought in the actual socio-historical structure, that is, in the actual mode of combination of technology and people. If the historical premise of the combination of technology and people is neglected, and technology and people themselves are examined in isolation, it is easy to attribute the “birth pangs” phenomenon to natural laws, thereby obscuring the real factors that trigger “birth pangs.” In the era of great socio-economic transformation in which Marx lived, the popularization of machinery was the process of technological change at that time. Marx delved into the movement process of capital, examined the structural relationship among capital, technology, and labor, analyzed the historical premise of the combination of machinery and labor, and scientifically revealed the roots of the “machinery problem.”

“阵痛”的根源需要从现实的社会历史结构中寻找，即从技术和人结合的实际方式中寻找。如果忽视了技术和人相互结合的历史前提，仅仅对技术、人本身进行孤立的考察，就容易将“阵痛”现象归结为自然规律，从而遮蔽引发“阵痛”的真实因素。在马克思所处的经济社会大转型时代，机器的普及历程就是当时技术变迁的过程。马克思深入到资本的运动过程中，对资本、技术、劳动间的结构性关系进行考察，剖析了机器与劳动相互结合的历史前提，科学揭示了“机器问题”产生的根源。

First, machinery in itself is a progressive force in social history. In his youth, Marx already recognized that industry and machinery are manifestations of human essential forces. “The history of industry and the established objective existence of industry are an open book of the essential forces of man.” In *Capital* and its manuscripts, Marx further constructed a logical chain between the degree of technological development and the height of human civilization development. In Marx’s view, machinery performs the special function of means of labor, extending the “natural limbs” of humans, enabling people to have a stronger ability to transform nature. In the production process, the progressiveness of machinery is reflected in the improvement of production efficiency: machinery “incorporates great natural forces and natural science into the production process” and “acts as freely as natural forces,” enabling society to obtain a large quantity of labor products with less labor. It can be seen that Marx associated technological progress with human natural instincts, establishing a positive evaluation of technology.

首先，机器就其本身而言是社会历史的进步力量。青年时期的马克思就已认识到工业、机器是人的本质力量的体现。“工业的历史和工业的已经生成的对象性的存在，是一本打开了的关于人的本质力量的书。”在《资本论》及其手稿中，马克思进一步构建起技术发展程度和人类文明发展高度之间的逻辑链条。在马克思看来，机器发挥着劳动资料的特殊功能，延长了人“自然的肢体”，使人拥有更强的改造自然的能力。在生产过程中，机器的进步性体现在对生产效率的提升上：机器“把巨大的自然力和自然科学并入生产过程”，并“像自然力那样无偿地发生作用”，使得社会付出较少的劳动就能获得大量的劳动产品。可见，马克思将技术进步与人的自然本能相关联，确立了对技术的肯定性评价。

Second, the intervention of capital in the labor process transformed the social nature of machinery. Machinery in itself, in the labor process, is a technological condition for production to proceed. But the intervention of capital caused machinery to acquire the capital form of fixed capital, to be possessed by capital and become a tool for exploiting labor. On the one hand, machinery is in no sense the means of production of an individual worker. Machinery, by virtue of its absolute advantage in production efficiency, eliminated traditional and inefficient modes of production. But at the same time, the expensive production equipment of machine industry, its “feverish production speed,” “enormous scale of production,” and continuous production process meant that only capital could afford the high reserves required for production, and capital established monopolistic control over the means of production. On the other hand, “a person who has no property other than his own labor power must, in any social and cultural state, become a slave to others who have become the owners of the material conditions of labor.” Under the circumstances where machine-based large-scale industry became the universal mode of production and machinery itself was monopolized by capital, workers could only flow into the market in the form of commodities, ultimately be purchased by capitalists, and provide surplus value. On this basis, machinery became dead labor opposed to living labor, transformed from a means of liberating labor into a tool for capital exploitation.

其次，资本介入劳动过程使机器的社会性质发生了转变。机器就其自身而言，在劳动过程中是生产得以进行的工艺条件。但资本的介入使机器取得了固定资本的资本形式，被资本占有并成为剥削劳动的工具。一方面，机器在任何意义上都不会是单个人的生产资料。机器凭借其生产效率上的绝对优势淘汰了传统而低效的生产方式，但与此同时，机器工业昂贵的生产设备、“狂热的生产速度”、“巨大的生产规模”和连续的生产过程，使得只有资本才能支付起生产所需要的高额准备金，资本确立了对生产资料的垄断控制。另一方面，“一个除自己的劳动力以外没有任何其他财产的人，在任何社会的和文化的状态中，都不得不为另一些已经成了劳动的物质条件的所有者的人做奴隶”。在机器大工业成为社会普遍的生产方式而机器本身又被资本所垄断的情况下，劳动者只得以商品形式流入市场，最终被资本家购买并提供剩余价值。在此基础上，机器变成了同活劳动相对立的死劳动，由解放劳动的手段变成了资本剥削的工具。

Finally, machinery as fixed capital assumes the dominant position in the production process, while the worker is degraded to an appendage of the machine, and the formal subsumption of labour under capital is transformed into real subsumption. Compared with traditional human labour, machinery possesses enormous advantages in strength, efficiency and quality control. In order to maximise labour efficiency and extract extra surplus value, the capitalist typically organises production according to the physical properties of the machine, and the machine becomes the new core of production. “In the system of machinery, large-scale industry has a completely objective organic body of production, which appears before the worker as a ready-made material condition of production.” From this point on, the relationship between the machine and the worker is completely inverted: it is no longer the labour process that adapts to the worker, but the worker who must adapt to the labour process. Capital gains control over the labour process; the worker can only act on a certain link in production without grasping the whole picture of production, and the machine becomes the technical means by which capital squeezes surplus labour from the worker.

最后，作为固定资本的机器取得了生产过程中的主体地位，劳动者降格为机器的附庸，劳动对资本由形式从属转化为实际从属。相较于传统人力，机器在力量、效率、品控上有着巨大优势。资本家为了最大程度提升劳动效率、获取超额剩余价值，通常以机器的物理属性为原则组织生产，机器成为新的生产核心。“在机器体系中，大工业具有完全客观的生产有机体，这个有机体作为现成的物质生产条件出现在工人面前。”自此，机器与工人的关系被彻底颠倒，不再是劳动过程适用于工人，而是工人不得不适应劳动过程。资本取得了劳动过程的控制权，工人只能起作用于生产的某个环节而无法掌控生产的全貌，机器成为资本榨取工人剩余劳动的技术手段。

Marx’s investigation and analysis of the relationship among capital, machinery and labour distinguishes between the machine itself and the capital form of the machine, thereby also transcending Hegel’s view of machinery, which completely regards the machine as a product of objectified labour and neglects the nature of the machine itself. While affirming the technological progressiveness of machinery, Marx identifies the capital factor behind the alienation of labour and reveals the transformation of the nature of machine technology under the conditions of capital. The question that needs further discussion is whether Marx’s diagnosis of the machine problem in the era of machine technology is applicable to the analysis of problems in the era of intelligent transformation. In other words, do the heterogeneity between intelligent systems and the system of machinery, and the differences between intelligent transformation and mechanised transformation, cause Marx’s theory to encounter limitations today?

马克思对资本、机器、劳动之间关系的考察分析，区分了机器本身与机器的资本形式，由此也超越了黑格尔完全将机器视为物化劳动的产物而忽视机器本身性质的机器观。马克思在肯定机器技术进步性的同时，找到了劳动异化背后的资本因素，揭示了机器技术在资本条件下的性质转变。接下来需要进一步讨论的问题是，马克思在机器技术时代对机器问题的诊断，是否适用于分析智能化时代的问题？换言之，智能系统和机器体系的异质性，以及智能化转型和机械化转型的差异，是否使马克思的理论在今天遭遇局限？

First, the heterogeneity between “intelligent systems” and the “system of machinery” does not fundamentally affect Marx’s analytical framework. Marx’s core diagnosis of the machine problem lies in the machine’s acquisition of the capital form of fixed capital. On the surface, some new characteristics of “intelligent systems” may cause this theory to encounter limitations: on the one hand, compared with “machinery,” which is an extension of the human limbs and organs, artificial intelligence places greater emphasis on simulating the human brain’s thought processes, that is, using computers to accomplish tasks that previously required human intelligence, enabling machine intelligence to rival and surpass biological intelligence. Some scholars, represented by Stephen Hawking, believe that the “thinking” and “self-improvement” abilities exhibited by artificial intelligence may cause it to break free from the role of a “tool” and replace humans as the “subject of civilisation.” If so, artificial intelligence would break free from its identity as a “means of labour” and would no longer have the opportunity to be capitalised. On the other hand, as a non-physical tool, “intelligent systems” possess some unique attributes different from traditional “systems of machinery.” For example, once an intelligent system is developed, it can be replicated infinitely, allowing an enterprise to purchase it once and apply it to production scenarios of any scale; during application, “intelligent systems” do not wear out their use value with production like machinery; furthermore, as a “virtual product,” the operation of “intelligent systems” can transcend the limitations of time and space. These characteristics seem to strip away the material basis for capital to appropriate them.

第一，“智能系统”与“机器体系”间的异质性不对马克思的分析框架造成根本影响。马克思对机器问题的核心诊断在于机器取得固定资本的资本形式。表面上，“智能系统”的一些新特质可能使这一理论遭遇局限：一方面，相较于作为人的四肢器官延伸的“机器”，人工智能更强调对于人脑思维过程的模拟，即利用计算机完成一些以往需要借助人的智力才能胜任的工作，使机器智能媲美并超越生物智能。以霍金为代表的一些学者认为，人工智能展现出的这种“思维”和“自我完善”的能力可能会使其脱离“工具”角色，取代人类成为“文明主体”。倘若如此，人工智能将脱离“劳动资料”身份，不再拥有资本化的契机。另一方面，“智能系统”作为一种非实物工具，具备一些与传统“机器体系”不同的独特属性。例如，智能系统一旦开发完成，便可以无限复制，这使得企业只需一次性购买，便能将其应用于任意规模的生产场景；在应用过程中，“智能系统”也不会像机器一样随着生产的进行而损耗自身的使用价值；此外，作为“虚拟产品”，“智能系统”的运行能够突破时间和空间的限制。这些特质似乎抽离了资本对其占有的物质基础。

However, “intelligent systems” and the “system of machinery” also share key similarities in the following three aspects, so that the heterogeneity between them does not fundamentally affect “intelligent systems” acquiring the “capital form”: first, intelligent technology, like all kinds of technology including machinery, has materiality. Intelligent technology does not arise out of nothing in the minds of individuals but is linked to the existing level of development of productive forces; it is created by humans in active practical activities based on their own needs. Bowens has criticised some scholars for regarding technology as “the will of God” or “the product of biological organs,” making technology seem “elusive.” In fact, technology, as a social existence, is an objective object that can be understood. The emergence and development of intelligent technology follow regular patterns. Second, the “thinking” ability of artificial intelligence cannot make it the subject of civilisation. The essence of artificial intelligence “thinking” is that, under the guidance of human instructions, the “intelligent system” retrieves and analyses massive amounts of data and generates corresponding content accordingly. This shows that artificial intelligence, unlike humans, does not possess self-awareness. In other words, intelligent technology cannot think from its own subjectivity and therefore cannot fundamentally shake the dominant position of humans. Third, although “intelligent systems” can be “infinitely replicated” once produced, their preliminary design, research and development and other links are still constrained by objective conditions such as funding and hardware; moreover, the rapid iteration of intelligent technology will also render old “intelligent systems” obsolete, requiring users to continuously purchase and replace new “intelligent systems.”

但是，“智能系统”和“机器体系”也在以下三个层面具有关键相似性，这使得二者间的异质性不对“智能系统”取得“资本形式”造成根本影响：一是智能技术同包括机器在内的各类技术一样，具有物质性。智能技术并非是个别人的头脑凭空产生的，而是与既有的生产力发展水平相联系，是人类基于自身需求，在能动的实践活动中创造的。鲍恩曾批评一些学者把技术视为“上帝的旨意”或“生物器官的产物”，使技术仿佛“不可捉摸”。事实上，技术作为社会存在，是可以认识的客观对象。智能技术的产生、发展都是有规律可循的。二是人工智能的“思维”能力并不能使之成为文明的主体。人工智能“思维”的实质是在人类指令的引导下，通过“智能系统”对海量数据进行检索与分析，并据此生成相应的内容。这表明人工智能不像人一样具备自我感知。换言之，智能技术无法从自身的主体性出发进行思考，因而无法从根本上撼动人的主体地位。三是“智能系统”虽然一经产出就可“无限复制”，但其前期的设计、研发等环节依旧受到资金、硬件等客观条件的制约；而智能技术的迅速迭代也会使旧的“智能系统”过时，使用者需不断购买并更换新的“智能系统”。

Second, compared with the heterogeneity between technological subjects, the process of “intelligent transformation” and the process of “mechanised transformation” exhibit obvious consistency. In terms of the scale and extent of transformation, “artificial intelligence,” like “machine technology,” “electrical technology” and “information technology,” is a general-purpose technology capable of triggering paradigm revolutions. The so-called general-purpose technology refers to those disruptive foundational technologies that can ultimately be transformed into the overall production conditions of society and affect all fields of social production. This indicates that “intelligent transformation” and “mechanised transformation” may have similar scale and extent. In terms of the internal mechanism of transformation, both “intelligent transformation” and “mechanised transformation” are changes in the mode of production driven by technological progress, which is directly reflected in changes in the labour process. Some scholars, when studying Marx’s theory of the labour process, believe that only direct labour can create value, but this makes it difficult to explain the problem of capital exploitation in the intelligent era, the increase in the intensity of certain types of labour, the intensification of economic inequality, and even more so the source of enterprise profits in “unmanned factories” in the intelligent era. In the machine era, the main form of the labour process was the worker directly acting on the object of labour through the means of labour (machinery). The intelligent era extends this process. Specifically, the intelligent and automated mode of production allows workers to be absent from the site of material product production, instead pre-objectifying and condensing their own living labour into intelligent technology, indirectly acting on the object of labour. It can be seen that the change in the mode of production triggered by “intelligent transformation” does not pose a challenge to the foundation of value creation.

第二，相较于技术主体间的异质性，“智能化转型”过程与“机械化转型”过程具有明显的一致性。从转型的规模和程度上看，“人工智能”和“机器技术”“电力技术”“信息技术”一样，都是能够引发范式革命的通用型技术。所谓通用型技术，是指那些最终能够转化为社会整体生产条件的、对社会生产各个领域均产生影响的颠覆性基础技术。这表明“智能化转型”和“机械化转型”可能拥有相似的规模和程度。从转型的内在机理看，“智能化转型”和“机械化转型”都是技术进步推动下的生产方式变革，这直接体现在劳动过程的变化上。有学者在研究马克思的劳动过程理论时，认为只有直接劳动才能创造价值,但这样一来，就难以解释智能时代的资本剥削问题和某些劳动的强度提升、经济不平等的加剧等现象，更无法解释智能时代“无人工厂”的企业利润来源。在机器时代，劳动过程的主要形式是劳动者通过劳动资料（机器）直接作用于劳动对象。智能时代则将这一过程延长了。具体而言，智能化、自动化的生产方式使劳动者可以不在物质产品的生产现场，而是预先将自身的活劳动物化凝结于智能技术之中，间接作用于劳动对象。可见，“智能化转型”引发的生产方式变革并不会对价值创造的基础形成挑战。

In summary, based on an analysis of the empirical facts of the development of large-scale machine industry, Marx made a scientific and reasonable diagnosis of the machine problem. Although there are differences between “intelligent systems” and the “system of machinery,” and between “intelligent transformation” and “mechanised transformation,” focusing on the core links, these differences will not fundamentally shake Marx’s analytical framework and overall conclusions regarding technology, labour and capital.

总之，马克思基于对机器大工业发展的经验事实的分析，对机器问题做出了科学合理的诊断。尽管“智能系统”和“机器体系”、“智能化转型”和“机械化转型”间存在差异，但着眼于核心环节，这些差异并不会从根本上动摇马克思技术、劳动、资本的分析框架与整体结论。

II. The Roots and Forms of the Pains of Intelligent Transformation

二、智能化转型阵痛的根源和形式

What is the essence of “pains”? Are they normal fluctuations in industrial upgrading or abnormal conditions in economic operation? Before proposing paths to resolve the pains of intelligent transformation, it is necessary for us to analyse the roots of these “pains” and their specific manifestations in the labour process. Generally speaking, various “pains” triggered by technological change and industrial upgrading are a natural phenomenon. However, if “pains” are entirely understood as normal phenomena of technological and industrial change, it may overlook concomitant problems in the transformation process, such as increased work intensity for some workers, insufficient employment, and uneven distribution of technological dividends. These problems have deep-seated social roots and require revealing their internal mechanisms through a dialectical examination of capital, technology and labour.

“阵痛”的本质是什么？是产业升级的正常波动还是经济运行的异常情形？在提出消解智能化转型阵痛的路径之前，我们有必要对“阵痛”产生的根源及其在劳动过程中的具体表现形式加以分析。一般来说，技术变迁和产业升级引发各种“阵痛”是一个自然的现象，但如果把“阵痛”全然理解为技术和产业变革的正常现象，则可能忽略转型过程中某些劳动者工作强度提高、就业不充分、技术红利分配不均等伴生问题。这些问题有其深层次的社会根源，需要通过对资本、技术、劳动的辩证考察来揭示其内在机理。

(I) Uncovering the Roots: Intelligent Technology Serves as a Tool for Capital to Discipline Labour

（一）根源解蔽：智能技术充当了资本规训劳动的工具

The deep-seated root of the pains of intelligent transformation lies in the fact that intelligent technology has acquired the capital form and serves as a tool for capital to control labour. Under conditions where technology is controlled by capital, the more developed the tool, the more prominent capital’s discipline over labour becomes.

智能化转型阵痛的深层根源在于智能技术取得了资本形式，充当了资本控制劳动的工具。在技术受资本控制的条件下，工具愈是发达，资本对劳动的规训就愈是突出。

On the one hand, through the monopolization of “data” and “computing power,” capital makes intelligent technology serve its own interests, thereby triggering a series of “pain” phenomena. Data, as the raw form of information, provides the necessary training material for intelligent models. Capital’s monopoly on data is mainly achieved by controlling data sources or establishing data collection platforms. For example, large manufacturing enterprises, relying on their original scale advantages, collect data during the production process, while large capital companies collect massive amounts of data by building information platforms; capital companies that gain a first-mover advantage in data collection can use this advantage to expand their user base or enhance production efficiency, thereby collecting more data resources for debugging and improving existing intelligent models. As data resources accumulate and market influence expands, these companies can join forces to participate in the formulation of data standards, thereby influencing the way data is used and shared across society and establishing capital’s “data hegemony.” Computing power refers to the ability of a computing system to process data and execute calculations. The more complex the deep learning models required by artificial intelligence, the higher the demand for computing power, and the more expensive the design and manufacture of processors become, making it difficult for individuals to bear the acquisition cost. In short, under conditions where data and computing power are monopolized by capital, even highly skilled workers cannot master the entire production process; they must also produce with the support of data and computing power, that is, with the permission of capital. As capital controls the key links in the development and application of intelligent technology, intelligent technology completes its transformation into the nature of fixed capital. Thus, capital can gratuitously occupy a large number of products produced by the new technology, accumulate even greater material wealth, and reproduce the conditions for forming new monopolies.

一方面，资本通过对“数据”和“算力”的垄断，使智能技术服务于资本的利益，进而引发系列“阵痛”现象。数据即信息的原始形式，为智能模型提供了必要的训练材料。资本对数据的垄断主要是通过控制数据源或建立数据收集平台来实现的。例如，大型制造业企业基于原有规模优势在生产过程中采集数据，大型资本公司则通过建立信息化平台收集海量数据；在数据收集上获得先发优势的资本公司可以凭借这一优势扩大用户基础或提升生产效能，进而收集更多的数据资源，用于原有智能模型的调试和改进。随着数据资源的积累和市场影响力的扩大，这些公司可以联合起来参与数据标准的制定，从而影响整个社会的数据使用和共享方式，建立起资本的“数据霸权”。算力指计算系统处理数据和执行计算的能力。人工智能所需的深度学习模型越复杂，对算力的要求就越高，处理器的设计和制造就越昂贵，个人很难承担其购置成本。总之，在数据和算力被资本垄断的情况下，即使是高技能劳动者也无法掌握整个生产过程，也需要在数据和算力的支持下，即在资本的允许下才能进行生产。伴随着资本控制了智能技术发展应用的关键环节，智能技术完成了向固定资本的性质转变。由此，资本得以无偿占据新技术产出的大量产品，积累起更加高额的物质财富，并再生产出形成新垄断的条件。

On the other hand, although artificial intelligence cannot replace humans as the subject of civilization, humans may lose themselves in the process of using intelligent devices. While being infiltrated and controlled by the power of capital, intelligent technology has also become a powerful means for capital to discipline people. In the sphere of production, the design and operation of intelligent tools appear on the surface to be “creative” mental labor, but the organization of the labor process must still follow the programmatic principles of intelligent devices. Some mental workers, while using intelligent technology to assist decision-making, gradually lose their ability to think independently, forming a dependence on intelligent technology. Beyond the sphere of production, the discipline of the labor force by intelligent technology also extends into the sphere of life. If machinery sucked the physical strength of workers, then capital platforms such as short videos and online shopping make laborers engage in unpaid data production while draining their mental energy. Marcuse once pointed out that in advanced capitalist industrial society, “technological progress extends to the entire system of domination and coordination, creating forms of life (and power) that seem to reconcile the forces opposing this system and to defeat and reject all protests raised in the name of escaping toil and domination and achieving freedom as a historical prospect.” Habermas also pointed out that “science and technology have today not only become the primary productive force but also the basis for the legitimacy of domination.” In today’s rapid development of intelligent technology, capital, by using intelligent technology to control labor, has formed various concrete manifestations of the pains of intelligent transformation.

另一方面，人工智能虽不能取代人类成为文明主体，人类却可能在运用智能设备的过程中迷失自身。智能技术在被资本力量渗透和控制的同时，也成为了资本对人进行规训的有力手段。在生产领域，智能工具的设计和操作表面上是有“创造性”的脑力劳动，但劳动过程的组织依旧要遵从智能设备的程式原则。部分脑力劳动者在运用智能技术辅助决策的同时，也逐渐丧失了独立思考的能力，形成了对智能技术的依赖。在生产领域之外，智能技术对劳动力的规训也延伸到生活领域。如果说机器设备吮吸了工人的体力，那么短视频、网络购物等资本平台则使劳动者无偿进行数据生产的同时，透支了人的精神力。马尔库塞曾指出，在发达资本主义工业社会，“技术的进步扩展到整个统治和协调制度，创造出种种生活（和权力）形式，这些生活形式似乎调和着反对这一制度的各种势力，并击败和拒斥以摆脱劳役和统治，获得自由的历史前景的名义而提出的所有抗议”。哈贝马斯也指出，“科学与技术，今天不仅成了第一位的生产力，而且也成了统治的合法性的基础”。在智能技术快速发展的今天，资本借助智能技术对劳动的控制，形成了智能化转型阵痛的各种具体样态。

(II) Concrete Representation: The Capitalist Application of Intelligent Technology and Its Manifestations

（二）具体再现：智能技术的资本主义应用及其表征

When intelligent technology acquires the social form of “capital” and demonstrates advantages over labor power, the capitalist application of intelligent technology is born. The so-called “capitalist application of intelligent technology” refers to intelligent technology serving capital’s need to extract surplus value, transforming from a means of liberating labor into a tool for exploiting labor. When analyzing the “capitalist application of machinery” and its logic, Marx pointed out: “The contradictions and antagonisms inseparable from the capitalist application of machinery do not exist, because they arise not from the machinery itself, but from its capitalist application! For machinery in itself shortens the working day, while its capitalist application lengthens it; machinery in itself lightens labor, while its capitalist application intensifies it; machinery in itself is a victory of man over the forces of nature, while its capitalist application subjects man to the forces of nature; machinery in itself increases the wealth of the producer, while its capitalist application turns the producer into a pauper in need of relief.” We can extend Marx’s line of thought and further analyze the “pain” phenomena brought about by the capitalist application of intelligent technology from various specific links in the production process.

当智能技术获得“资本”的社会形式并展现出相较于劳动力的优势时，智能技术的资本主义应用就诞生了。所谓“智能技术的资本主义应用”，是指智能技术服务于资本榨取剩余价值的需要，从解放劳动的手段变为剥削劳动的工具。马克思在分析“机器的资本主义应用”及其逻辑时曾指出：“同机器的资本主义应用不可分离的矛盾和对抗是不存在的，因为这些矛盾和对抗不是从机器本身产生的，而是从机器的资本主义应用产生的！因为机器就其本身来说缩短劳动时间，而它的资本主义应用延长工作日；因为机器本身减轻劳动，而它的资本主义应用提高劳动强度；因为机器本身是人对自然力的胜利，而它的资本主义应用使人受自然力奴役；因为机器本身增加生产者的财富，而它的资本主义应用使生产者变成需要救济的贫民。”我们可以延伸马克思的思路，进一步从生产劳动的各个环节具体分析智能技术的资本主义应用带来的“阵痛”现象。

During the period of labor preparation, the capitalist application of intelligent technology leads to the “displacement” of workers. “Technological unemployment” specifically refers to unemployment caused by the substitution of technology for human labor in the production process, and is one of the most intuitive phenomena of “pain.” During the period of intelligent transformation, workers’ previously livelihood-dependent skills are replaced by intelligent devices; they are expelled from the original production process while being unable to immediately integrate into a new one. Academia often attributes this situation to the nature of intelligent technology itself or the natural endowments of workers. But the root cause behind it lies in the capitalist application of technology. When analyzing the general law of capitalist accumulation in *Capital*, Marx pointed out: “It is the absolute interest of every capitalist to extract a given quantity of labor from fewer workers rather than from more workers at the same or even lower cost.” At the same time, because capital degrades workers into appendages of technology, making them “engage in the same simple operation for life.” Today, with the intellectualization and automation of production, a smaller amount of labor can drive a large quantity of means of production, causing the number of low-skilled positions to shrink continuously. At the same time, the constant innovation of machine languages and operating systems renders workers’ previous skills obsolete. Low-skilled workers, due to intellectual limitations, find it difficult to quickly adapt to new technical requirements. Capital needs workers to engage in more advanced complex labor; however, these low-skilled workers find it very difficult to quickly adapt and integrate into new production positions.

在劳动准备时期，智能技术的资本主义应用导致了工人的“游离”。“技术性失业”特指生产过程中采用技术替代人力导致的失业，是“阵痛”最直观的现象之一。在智能化转型时期，劳动者先前赖以为生的技能被智能设备取代，在被排挤出原有生产过程的同时又无法马上融入新的生产过程。通常学界会将这种状况的产生归因于智能技术本身或劳动者的自然禀赋。但其背后的根本原因在于技术的资本主义应用。马克思在《资本论》中分析资本主义积累的一般规律时指出，“每一个资本家的绝对利益在于，从较少的工人身上而不是用同样低廉或甚至更为低廉的花费从较多工人身上榨取一定量的劳动”。与此同时，由于资本将劳动者降格为技术的附庸，使他们“终生从事同一种简单操作”。在今天，伴随着生产的智能化和自动化，较少量的劳动便可推动大量的生产资料，使得低技能岗位数量不断缩减。同时，机器语言、操作系统的不断革新使工人原先的技能过时。低技能工人由于智识的限制，难以迅速适应新的技术要求。资本需要工人从事更高级的复杂劳动，然而，这些低技能工人很难快速适应并融入新的生产岗位。

During the period of labor execution, the capitalist application of intelligent technology covertly increases labor intensity. When analyzing the issue of machinery, Marx pointed out: “On the basis of capitalist production, the purpose of using machinery is by no means to lighten or shorten the daily toil of the worker.” Automation in the intelligent age superficially liberates workers from intense physical labor, or allows them to participate in the production process merely as “supervisors.” However, if intelligent technology is used for the purpose of capital valorization, then only enterprises at the forefront of innovation can continuously obtain surplus value. To stand out in fierce competition, the intensity of labor for highly skilled workers is collectively intensified. Furthermore, intelligent technology also invisibly strengthens the hidden exploitation of other laborers. On the one hand, intelligent technology blurs the absolute boundary between work and life, imperceptibly extending workers’ working hours. On the other hand, under intelligent technology, workers form new lifestyles; while using intelligent systems in life scenarios, they continuously provide personal information to platforms, unknowingly engaging in a large amount of unpaid labor in data production and intelligent model training.

在劳动进行时期，智能技术的资本主义应用隐蔽地提升了劳动强度。马克思在分析机器问题时指出，“在资本主义生产的基础上，使用机器的目的，决不是为了减轻或缩短工人每天的辛劳”。智能时代的自动化表面上使劳动者从紧张的体力劳动中解放出来，或仅仅以“监督者”的身份参与生产过程。然而，如果智能技术被用于资本增殖的目的，那么只有处于创新最前沿的企业才能持续获得剩余价值。为了在激烈的竞争中脱颖而出，高技能劳动者的劳动紧张程度被集体强化。此外，智能技术也在无形中加强了对其他劳工的隐性剥削。一方面，智能技术模糊了工作和生活之间的绝对界限，无形之中延长了劳动者的工作时间。另一方面，智能技术之下劳动者形成了新的生活模式，劳动者在生活情景中运用智能系统的同时不断地向平台提供个人信息，在不知不觉中进行了大量数据生产和智能模型训练方面的无酬劳动。

In the period of distribution of products, the capitalist application of intelligent technology has contributed to the intensification of inequality. In theory, technological development generally raises social labor productivity and creates more material wealth than before. But the capitalist application of technology concentrates the increased wealth in the hands of a few, causing a short-term intensification of inequality. As Marx pointed out, “all the progress of civilization … all the growth of the productive forces of labor itself — such as the results of science, invention, the division and combination of labor, improved means of communication, the creation of the world market, machinery, etc. — do not enrich the worker but rather enrich capital.” [14]14 This is a paraphrase of Marx’s argument in the *Grundrisse*; the exact wording is adapted from the Chinese translation of Marx’s texts. And the development and application of artificial intelligence technology will further widen the gap between capital and labor, while at the same time producing differentiation among workers themselves, so that the income level of professional talent engaged in technological research and development and of highly skilled tech workers rises relatively, while the income level of low-skilled workers falls relatively. For low-skilled workers on the production front line in particular, intelligent technology replaces them with automated systems, leading to unemployment and impoverishment.

在产品分配时期，智能技术的资本主义应用促成了不平等的加剧。理论上，技术的发展普遍提升了社会劳动生产率，创造出比以前更多的物质财富。但技术的资本主义应用却使增长的财富向少数人手中集中，引起了短时期内不平等的加剧。如马克思指出的，“文明的一切进步……劳动本身的生产力的一切增长，如科学、发明、劳动的分工和结合、交通工具的改善、世界市场的开辟、机器等等所产生的结果，都不会使工人致富，而只会使资本致富”。而人工智能技术的开发应用，更会进一步扩大资本和劳动之间的差距，同时在劳动者之间产生分化，使得从事技术研发的专业型人才和高技能科技劳工的收入水平相对提高，而低技能工人的收入水平则相对下降。尤其对于生产一线的低技能工人而言，智能技术使他们被自动化系统替代而导致失业和穷困。

III. The Path to Resolving the Pains of Intelligent Transformation

三、智能化转型阵痛的消解进路

On the basis of an in-depth investigation of the structural relationship among capital, technology and labor, Marx clarified the qualitative transformation of machine technology under the conditions of capital, revealed the internal mechanism of the “machine question,” and provided us with a theoretical reference for analyzing the roots of the pains of intelligent transformation, as well as a basic line of thought for resolving them. The problem of the pains of intelligent transformation exists widely across the globe today, and China likewise faces the risks and challenges brought by the wave of digital-intelligent transformation. [15]15 “Digital-intelligent transformation” (数智化转型) refers to the combined process of digitalization and the application of artificial intelligence. The key to resolving the pains of intelligent transformation lies in properly balancing the relationship among capital, technology and labor; on the basis of correctly understanding and grasping the characteristics of capital and the laws of its behavior, properly handling the issue of fairness and development; paying attention to the protection of the rights and interests of emerging workers, and cultivating new-type workers with autonomy and creativity; and exploring the way of human-machine coexistence, to build a new type of civilized society in which humans and machines coexist harmoniously.

马克思在深入考察了资本、技术、劳动间的结构性关系的基础上，阐明了机器技术在资本条件下的性质转变，揭示了“机器问题”的内在机理，为我们分析智能化转型阵痛的根源提供了理论参照，也为我们提供了消解智能化转型阵痛的基本思路。智能化转型阵痛问题在当今全球范围内广泛存在，中国也同样面临着数智化浪潮带来的风险与挑战。消解智能化转型阵痛的关键在于平衡好资本、技术、劳动间的关系，在正确认识和把握资本特性及其行为规律的基础上，妥善处理公平与发展的问题；注重新兴劳动者权益保障，培育具有自主性与创造性的新型劳动者；探索人机相处之道，构建一个人机和谐的新型文明社会。

(1) Correctly Understand and Grasp the Characteristics of Capital and the Laws of Its Behavior

（一）正确认识和把握资本的特性和行为规律

The existence of capital has its historical rationality, and its behavior also has a dual character. Marx pointed out that “although capital is narrow in its nature, it strives to develop the productive forces comprehensively, and thus becomes the premise of a new mode of production.” Under the conditions of the socialist market economy, various forms of capital also exist. How to understand and treat capital in a socialist society is a new课题. [16]16 The Chinese term 课题 (kè tí) means “subject” or “task” in the sense of a research question or practical problem to be addressed. In his speech at the Central Economic Work Conference in December 2021, General Secretary Xi Jinping pointed out: “Since it is a socialist market economy, various forms of capital will inevitably arise. Although the capital of capitalist society and the capital of socialist society are certainly very different, capital always pursues profit … We need to explore how, under the conditions of the socialist market economy, to bring into play the positive role of capital while effectively controlling its negative role.” This raises the issue of regulating the behavior of capital, to promote its advantages and avoid its disadvantages.

资本的存在有其历史合理性，其行为也有双面性。马克思指出，“尽管按照资本的本性来说，它本身是狭隘的，但它力求全面地发展生产力，这样就成为新的生产方式的前提”。在社会主义市场经济条件下，也存在各种形态的资本。如何认识和对待社会主义社会的资本，是一个新的课题。2021年12月，习近平总书记在中央经济工作会议上的讲话中指出：“既然是社会主义市场经济，就必然会产生各种形态的资本。资本主义社会的资本和社会主义社会的资本固然有很多不同，但资本都是要追逐利润的……我们要探索如何在社会主义市场经济条件下发挥资本的积极作用，同时有效控制资本的消极作用。”这就提出了规范资本行为，趋利避害的问题。

As a factor of production, capital has the function of optimizing resource allocation and promoting technological progress, but it also has the problem of hindering technological progress. On the one hand, in the process of intelligent transformation, capital can efficiently allocate social resources to the most promising technological projects, accelerate the technological research and development of basic industries, and provide impetus for the development of intelligent technology. Capital can also play a role in promoting the transformation of intelligent technological achievements and their popularization in society. But on the other hand, the profit-seeking nature of capital may also become an obstacle to intelligent technological progress. In the embryonic stage of intelligent technology, when the labor expended on developing and applying intelligent systems is less than the labor replaced by intelligent technology, using the new technology is cost-effective for society. But for capital, the new technology will be used only when there is a difference between the value of the intelligent system and the value of the labor power it replaces. Schumpeter once pointed out that “the economically optimal and the technically perfect do not necessarily have to diverge, yet they often do, not only because of ignorance and laziness, but because technically inferior methods may still be the most suitable for given economic conditions.” [17]17 This is a paraphrase of Joseph Schumpeter’s argument in *Capitalism, Socialism and Democracy*. In the period when technology has reached a certain scale, the monopoly of technology by large capital platforms can also hinder technological progress. The upgrading and optimization of intelligent tools depend on the expansion of trainable data sets, the improvement of computing power, and the enhancement of algorithms. Out of a desire to protect competitive advantage, large platform companies under the control of capital may control data and close off code. As platforms form “data silos,” it becomes difficult to use data effectively; while closed code blocks external access and use, it also hinders the dissemination of knowledge and technological cooperation. In the short term, these monopolistic practices may benefit individual capital, but in the long term they will suppress the innovative potential and market vitality of intelligent models, leading to waste of resources and a decline in efficiency.

资本作为生产要素，具有优化资源配置、促进技术进步的功能，也有阻碍技术进步的问题。一方面，在智能化转型的过程中，资本可以高效地将社会资源配置到最具潜力的技术项目上，加速基础产业的技术研发，为智能技术的发展提供动力。资本也能发挥推动智能技术成果转化和社会普及方面的作用。但另一方面，资本的逐利特性也可能成为智能技术进步的阻碍。在智能技术萌芽期，当研发与应用智能系统所费的劳动要少于智能技术所代替的劳动时，对社会而言使用新技术便是合算的。但对资本而言，只有在智能系统的价值和它所代替的劳动力的价值之间存在差额的情况下，新技术才会被使用。熊彼特曾指出，“经济上的最佳和技术上的完善二者不一定要背道而驰，然而却常常是背道而驰的，这不仅是由于愚昧和懒惰，而且由于在技术上低劣的方法可能仍然最适合于给定的经济条件”。在技术形成一定规模的时期，大型资本平台对技术的垄断也会阻碍技术进步。智能工具的升级优化有赖于可训练数据集的扩张、算力的提升和算法的增强。出于对竞争优势的保护，资本控制下的大型平台公司就可能会控制数据并封闭代码。随着平台形成一个个“数据孤岛”，数据很难获得有效利用；代码封闭在阻挡外界访问和使用的同时，也阻碍了知识传播和技术合作。这些垄断行为短期内可能会使个别资本获益，但从长期来说将抑制智能模型的创新潜力和市场活力，导致资源浪费和效率衰减。

In the wave of intelligent transformation, in response to the phenomenon of capital monopolizing data and computing power resources, the United Nations High-Level Advisory Body on Artificial Intelligence, in its final report *Governing AI for Humanity* released in September 2024, proposed lowering the threshold for AI development through the sharing of computing power resources. The report also advocated promoting data exchange and data integration among various social organizational structures, to prevent intelligent technology from being completely controlled by a small group. For China, the government can take the lead in building a unified public computing platform and public digital platform, encouraging data cooperation among enterprises, government and research institutions, improving the accessibility of data and computing power resources, and creating a shared, collaborative and sustainable intelligent industrial ecosystem. To promote the healthy development of AI technology and industry, China has successively issued policy documents such as the *New Generation Artificial Intelligence Development Plan* (2017), the *Guiding Opinions on Accelerating Scenario Innovation to Promote High-Quality Development of the Economy through High-Level Application of Artificial Intelligence* (2022), and the *National AI Industry Comprehensive Standardization System Construction Guide (2024 Edition)*. In December 2024, the Central Economic Work Conference further proposed “carrying out the ‘AI+’ action to cultivate future industries,” enabling the AI industry to empower the development of new quality productive forces. To better leverage the functional role of the capital market, the *Opinions of the State Council on Strengthening Supervision, Preventing Risks, and Promoting the High-Quality Development of the Capital Market* (2024) proposed building a safe, standardized, transparent, open, vibrant and resilient capital market, and promoting the high-quality development of the capital market.

在智能化转型浪潮中，针对资本垄断数据、算力资源的现象，联合国人工智能高级咨询机构在2024年9月发布的《为人类治理人工智能》（Governing AI for Humanity）的最终报告中提出，应通过共享算力资源以降低人工智能开发的门槛。报告还倡导推动社会各组织结构间的数据交换与数据集成，以避免智能技术被少数群体完全掌控。对于我国而言，可以由政府牵头搭建统一的公共算力平台和公共数字平台，鼓励企业、政府以及研究机构之间开展数据合作，提升数据、算力资源的可及性，营造一个共享、协作和可持续发展的智能产业生态。为推动人工智能技术和产业健康发展，我国先后出台了《新一代人工智能发展规划》（2017年）、《关于加快场景创新以人工智能高水平应用促进经济高质量发展的指导意见》（2022年）、《国家人工智能产业综合标准化体系建设指南（2024版）》等政策文件。2024年12月，中央经济工作会议进一步提出“开展‘人工智能+’行动，培育未来产业”，使人工智能产业赋能新质生产力发展。为更好发挥资本市场功能作用，《国务院关于加强监管防范风险推动资本市场高质量发展的若干意见》（2024年）提出打造安全、规范、透明、开放、有活力、有韧性的资本市场，推动资本市场高质量发展。

(2) Pay Attention to the Protection of the Rights and Interests of Emerging Workers and Cultivate New-Type Workers

（二）注重新兴劳动者权益保障和培育新型劳动者

In his speech at the 14th collective study session of the Political Bureau of the CPC Central Committee on May 27, 2024, General Secretary Xi Jinping pointed out that the impact of trends such as the new round of technological revolution and industrial revolution, and the digital transformation of the economy, on employment is deepening, and the structural employment contradiction of “jobs going unfilled” and “people going unemployed” is becoming increasingly prominent. [18]18 The phrase “jobs going unfilled” (有活没人干) and “people going unemployed” (有人没活干) is a standard Chinese formulation for structural mismatch in the labor market. Specifically, the economic digital-intelligent transformation is promoting the transformation and upgrading of traditional industries, while also giving rise to new industries and new jobs. At the same time, the application of digital and automation technologies has increased the demand for highly qualified, highly skilled workers, while some low-skilled positions face the risk of being replaced. To solve the problem of “people going unemployed,” we must start by cracking the problem of “jobs going unfilled.” This requires not only cultivating emerging workers who meet the needs of digital-intelligent transformation through technical education, but also, more importantly, relying on a good innovation environment and an inclusive social mechanism to cultivate new-type workers. New-type workers are not only workers with the ability to use digital-intelligent technology, but also comprehensively developed workers with autonomy and creativity. As the main form of the current labor force, a large number of emerging workers still engage in partial work, both relying on technology and being constrained by it. Therefore, it is necessary to improve the institutional mechanisms for protecting the rights and interests of workers, and to promote the transformation of emerging workers into new-type workers.

2024年5月27日，习近平总书记在中共中央政治局第十四次集体学习时的讲话中指出，新一轮科技革命和产业革命发展，经济数字化转型等趋势对就业的影响逐步加深，“有活没人干”和“有人没活干”的结构性就业矛盾不断凸显。具体而言，经济数字化、智能化转型促使传统产业转型升级，也催生出新的行业和新的就业岗位。与此同时，数字化、自动化技术的应用，提高了对高素质、高技能劳动者的需求，一些低技能岗位面临被取代的风险。要解决“有人没活干”的问题，就要从破解“有活没人干”入手。这不仅需要通过技术教育培养符合数智化需求的新兴劳动者，更要依托良好的创新环境与包容性的社会机制，培育新型劳动者。新型劳动者既是具有数智技术运用能力的劳动者，更是具备自主性与创造性的全面发展的劳动者。作为现阶段劳动力的主要形态，大量新兴劳动者仍从事局部工作，既依赖技术又受制于技术，因此需要完善劳动者权益保障等方面的体制机制，并推动新兴劳动者向新型劳动者转型。

General Secretary Xi Jinping has repeatedly stressed that labor is the source of wealth and that employment is the most basic aspect of people’s livelihoods. “We must uphold social fairness and justice, remove obstacles that hinder workers from participating in development and sharing in the fruits of development, and strive to enable workers to achieve decent work and all-round development.” In the process of developing new technologies and new industries, promoting technology sharing is particularly crucial for safeguarding workers’ rights and interests. Within production organizations, inequality in digital technology manifests as an asymmetry of power between labor and capital; externally, it manifests as inequality in technology diffusion and the “digital divide.” Addressing these problems first requires making every effort to advance the accessibility of public data, so that the fruits of intelligent technology benefit a broader range of social groups. To this end, the Third Plenary Session of the 20th Central Committee of the CPC proposed to “build and operate national data infrastructure and promote data sharing.” [19]19 The Third Plenary Session of the 20th Central Committee of the CPC, held in July 2024, focused on further deepening reform and advancing Chinese-path modernization. In addition, the rise of online platforms and outsourcing has posed new challenges to the identification of labor relations and the protection of workers’ rights and interests. The “platform economy” and “outsourcing economy” are important components of the digital economy and are highly aligned with the development trends of intelligent technology. Therefore, it is necessary to provide reasonable regulation and guidance for these new economic forms, especially by supplementing and following up with relevant laws and regulations, so that the rights and interests of workers engaged in emerging industries can be fully protected.

习近平总书记多次强调，劳动是财富的源泉，就业是最基本的民生。“要坚持社会公平正义，排除阻碍劳动者参与发展、分享发展成果的障碍，努力让劳动者实现体面劳动、全面发展。”在发展新技术、新产业的过程中，促进技术共享对保障劳动者权益尤为关键。数字技术的不平等在生产组织内部体现为劳资权力的不对等，在外部体现为技术扩散不平等与“数字鸿沟”。解决这些问题首先需要着力推进公共数据的可及性，使智能技术成果惠及更广泛的社会群体。为此，党的二十届三中全会提出要“建设和运营国家数据基础设施，促进数据共享”。此外，在线平台和外包形式的兴起对劳动关系的认定与劳动者的权益保障提出了新课题。“平台经济”“外包经济”是数字经济的重要组成部分，并与智能技术的发展趋势高度契合。因此，需要对这些新兴经济形式进行合理规范引导，尤其是要补充跟进相关法律法规，使从事新兴产业的劳动者权益能够得到充分保障。

It should be pointed out that, in the face of the “pains” brought by intelligent transformation, one should avoid the view that sets labor in opposition to technology. Marx pointed out the complex relationship among natural science, industrial progress, and the situation of workers: “Natural science, however, has invaded and transformed human life practically through industry, and prepared human emancipation, although it had immediately to complete the dehumanization of man.” [20]20 Karl Marx, *Economic and Philosophic Manuscripts of 1844*, in *Marx & Engels Collected Works*, Vol. 3 (Moscow: Progress Publishers, 1975), p. 305. In the face of intelligent technology, anticipating risks from a scientific perspective can keep them within a controllable range for healthy development, so that scientific and technological progress and the all-round development of workers advance together.

需要指出的是，面对智能化转型带来的“阵痛”，应避免将劳动与技术对立起来的观点。马克思指出了自然科学、工业进步和劳动者处境之间的复杂关系：“自然科学却通过工业日益在实践上进入人的生活，改造人的生活，并为人的解放作准备，尽管它不得不直接地使非人化充分发展。”面对智能技术，从科学的角度预知风险，可以使之保持在可控的范围内健康发展，使科技进步和劳动者的全面发展共同推进。

(III) Building a New Type of Civilized Society with Human-Machine Harmony

（三）构建人机和谐的新型文明社会

“Looking at the history of world civilization, humanity has successively experienced the agricultural revolution, the industrial revolution, and the information revolution. Each industrial and technological revolution has had a huge and profound impact on human production and life.” The development of artificial intelligence has opened a new era of technological revolution and new industrial revolution, “greatly expanding the scope of time, space, and human cognition; humanity is entering a new era of the intelligent interconnection of all things, a ternary fusion of ‘human, machine, and things.’” In a 2018 congratulatory letter to the inaugural World Artificial Intelligence Conference, General Secretary Xi Jinping pointed out that artificial intelligence is profoundly changing people’s modes of production and life, and is also raising new issues in law, security, employment, ethics, and government governance. Faced with the deep embedding of artificial intelligence and the new business forms and applications it generates into human production and life, the fundamental question we need to consider is how to build a civilized society with human-machine harmony.

“纵观世界文明史，人类先后经历了农业革命、工业革命、信息革命。每一次产业技术革命，都给人类生产生活带来巨大而深刻的影响。”人工智能的发展开启了新技术革命和新产业革命的新时代，“大大拓展了时间、空间和人们认知范围，人类正在进入一个‘人机物’三元融合的万物智能互联时代”。 2018年习近平总书记在致首届世界人工智能大会的贺信中指出，人工智能正在深刻改变人们的生产生活方式，也在法律、安全、就业、道德伦理和政府治理等方面提出了新课题。面对人工智能及其产生的新业态、新应用对人类生产生活的深度嵌入，我们需要思考的根本性问题是，如何构建一个人机和谐的文明社会。

First, build a new type of human-machine relationship that is people-centered and characterized by human-machine harmony. The relationship between humans and intelligent technology is one of mutual coordination and mutually beneficial coexistence. On the one hand, artificial intelligence is created by humans and is an extension of human intelligence. Without the progress of human intellect, there would be no development of artificial intelligence. On the other hand, “benefiting humanity is the most powerful driving force for scientific and technological innovation.” Scientific and technological innovation enhances human capabilities. The development of artificial intelligence injects new momentum into economic and social development, bringing about increases in social productive forces and labor productivity, enhanced public service capacity, and an improved quality of life for people. Humanity needs to actively welcome the arrival of the intelligent era, embrace intelligent change positively, while at the same time paying attention to the safety governance of artificial intelligence, exploring ways for human-machine harmonious coexistence, and working together to promote economic development and social progress.

首先，构建以人为本、人机和谐的新型人机关系。人类与智能技术之间是一种相互协调、互利共存的关系。一方面，人工智能是由人类创造的，是人类智慧的延伸。没有人类智识的进步就没有人工智能的发展。另一方面，“造福人类是科技创新最强大的动力”。科技创新增强了人类能力。人工智能的发展为经济社会发展注入了新动能，带来了社会生产力和劳动生产率的提高、公共服务能力的增强和人的生活品质的提升。人类需要主动迎接智能时代的到来，积极拥抱智能变革，同时重视人工智能安全治理，探索人机和谐相处之道，携手促进经济发展与社会进步。

Second, balance intelligent technology with ethics and morality, and promote “intelligence for good.” General Secretary Xi Jinping pointed out, “Technology can be a sharp tool for development, but it can also become a source of risk. We must prospectively assess the rule conflicts, social risks, and ethical challenges brought by technological development, and improve relevant laws and regulations, ethical review rules, and regulatory frameworks.” To address the ethical challenges and moral risks brought by the development of artificial intelligence, we should adhere to the people-centered concept, embed ethical rules within intelligent technology, and invest funds and technology to train intelligent models so that, while achieving their goals, they also establish an understanding of human ethical rules. When intelligent technology is applied to fields involving ethical categories such as healthcare, justice, and education, the supervision and review of intelligent systems should be strengthened, making every effort to avoid “algorithmic bias” caused by human prejudice, and ensuring the transparency and fairness of their decision-making processes. In addition, with the popularization of the open-source model, where anyone can modify or delete source code, it is necessary to adopt technical means to supervise open-source software to prevent malicious tampering or misuse of the software code. In this regard, China has issued documents such as the *Governance Principles for a New Generation of Artificial Intelligence – Developing Responsible Artificial Intelligence* (2019), *China’s Position Paper on Strengthening Ethical Governance of Artificial Intelligence* (2022), *Global AI Governance Initiative* (2023), and *Shanghai Declaration on Global AI Governance* (2024). The Third Plenary Session of the 20th Central Committee proposed to “improve the development and management mechanisms for generative artificial intelligence” and “establish an artificial intelligence safety supervision system,” guiding the positive development of artificial intelligence through the improvement of the governance system. In short, to address the uncertainties brought by the transformation of artificial intelligence technology, it is necessary to strengthen the construction of governance rules, technical standards, monitoring mechanisms, etc., establish safety and ethical norms for artificial intelligence, and ensure that the development of artificial intelligence is safe, reliable, controllable, and fair, in line with the fundamental interests and value standards of humanity.

其次，平衡智能技术与伦理道德，促进“智能向善”。习近平总书记指出，“科技是发展的利器，也可能成为风险的源头。要前瞻研判科技发展带来的规则冲突、社会风险、伦理挑战，完善相关法律法规、伦理审查规则及监管框架”。应对人工智能发展带来的伦理挑战和道德风险，应坚持以人为本的理念，为智能技术内置伦理规则，投入资金、技术对智能模型进行训练，使智能模型在实现目标的同时也建立起对人类伦理规则的理解；当智能技术应用于医疗、司法、教育等涉及伦理范畴的工作时，应重点加强对智能系统的监管和审查，努力避免人类偏见导致的“算法偏见”，确保其决策过程的透明公正。此外，伴随着开源模式的普及，在任何人都有可能对源代码进行修改、删减的情况下，有必要采取技术手段对开源软件加以监管，防止软件代码被恶意篡改、利用。对此，我国发布了《新一代人工智能治理原则——发展负责任的人工智能》（2019年）、《中国关于加强人工智能伦理治理的立场文件》（2022年）、《全球人工智能治理倡议》（2023年）、《人工智能全球治理上海宣言》（2024年）等文件。党的二十届三中全会提出“完善生成式人工智能发展和管理机制”，“建立人工智能安全监管制度”，以治理体系的完善引导人工智能正向发展。总之，应对人工智能技术变革带来的不确定性，要加强治理规则、技术标准、监测机制等方面的建设，建立人工智能的安全与伦理规范，确保人工智能发展安全、可靠、可控和公平，符合人类的根本利益和价值标准。

Finally, to build a new type of civilized society with human-machine harmony, it is necessary to fully leverage the institutional advantages of socialism with Chinese characteristics, adhere to putting the people first, and prevent “technological alienation.” Break free from the limitations of thinking, transform the binary oppositional thinking of human versus machine into a holistic thinking of human-machine harmonious coexistence, and achieve the organic unity of enhancing people’s well-being and developing intelligent technology. Adhere to reform and innovation, accelerate the formation of new relations of production compatible with the development of new quality productive forces, and achieve positive interaction among capital, technology, and labor. Adhere to the concept of a community with a shared future for mankind, “strengthen international governance and cooperation on artificial intelligence, ensure that artificial intelligence is for good and benefits all of humanity,” and contribute Chinese wisdom and Chinese solutions to building a safe, prosperous, and just civilized world of human-machine harmony. (Author affiliation: Peking University)

最后，构建人机和谐的新型文明社会，要充分发挥中国特色社会主义制度优势，坚持人民至上，防止“技术异化”。摆脱思维局限，将人机二元对立思维转化为人机和谐共生的整体性思维，实现人民福祉增进和智能技术发展的有机统一。坚持改革创新，加快形成同发展新质生产力相适应的新型生产关系，实现资本、技术、劳动间的良性互动。坚持人类命运共同体理念，“加强人工智能国际治理和合作，确保人工智能向善、造福全人类”，为构建安全、繁荣、公正的人机和谐的文明世界贡献中国智慧和中国方案。（作者单位：北京大学）

Online editor: Paul

网络编辑：保罗