Introduction

Artificial intelligence (AI) is a strategic technology leading a new wave of technological revolution and industrial transformation, profoundly changing human production and lifestyle. General Secretary Xi Jinping pointed out that the current technological revolution and industrial transformation led by AI is in full swing. Driven by new theories and technologies such as mobile internet, big data, supercomputing, sensor networks, and brain science, AI exhibits new characteristics such as deep learning, cross-domain integration, human-machine collaboration, collective intelligence openness, and autonomous control, significantly impacting economic development, social progress, and global governance. While AI propels leaps in productivity, it also complicates discussions around labor forms and value creation processes, presenting new challenges to labor value theory that require scientific responses.

New Challenges to Labor Value Theory

As a foundational theory of Marxist political economy, labor value theory is a scientific creation formed by Marx based on the negation of classical political economy. Its main content includes theories about the duality of commodities, the determination of value, the development of value forms, and the fundamental contradictions of commodity economies. The core idea is that value is the crystallization of undifferentiated human labor embedded in commodities, and living labor is the sole source of commodity value. For a long time, there have been numerous debates in academia regarding labor value theory. With the rapid development and widespread application of AI, the debates have intensified.

The Fundamental Nature of AI

Unlike traditional industrial machines, AI machines, devices, and systems exhibit characteristics similar to human intelligence, attracting widespread attention. The famous “Turing Test” aims to demonstrate that if a machine can imitate human conversation to the point of being indistinguishable, its intelligence should be seriously considered. The emergence of generative AI indicates that large-scale neural network models trained on deep learning algorithms can generate text, images, sounds, videos, and code, showcasing astonishing “thinking abilities” in the content generation process. This technological advancement is rapidly pushing AI towards multimodal and embodied development. Some studies suggest that AI can achieve human-like output in specific tasks, primarily by learning from vast amounts of data and simulating human thought processes to generate content based on probabilistic predictions. As technology advances, AI’s behavior increasingly resembles human intelligence. A profound theoretical question arises: when machine systems approach human cognitive levels, is it possible for self-awareness or independent value orientations to emerge? This question touches on the philosophical boundaries of AI as a “human-like subject.” From the perspective of labor value theory, what element attributes does AI possess in the production system? Is it human or object? Is it “human-like” or “human”?

The Subject of Intelligent Labor

In 1984, the world’s first fully automated factory was established in Tsukuba Science City, Japan, bringing “unmanned factories” into the public eye. In recent years, with the accelerated development and widespread application of AI technology, “dark factories” have rapidly emerged. This intelligent production model relies on intelligent robots, automated equipment, and digital systems to achieve full-process production, operating in a “dark” state without workers present. In this context, AI exhibits a significant substitution effect on human labor. Moreover, AI’s tireless and uncomplaining nature can circumvent the physiological limitations, moral condemnation, and legal sanctions faced by workers engaged in long hours, high-risk, and intense labor, thus possessing the advantages of a “perfect worker.” Therefore, the “new labor” that Marx referred to, which emerged from the industrial revolution, will become a thing of the past; intelligent labor will become the new labor, pushing humans out of direct production processes in some industries and relegating them to roles in supervision, maintenance, and system optimization. The absence of human laborers in direct production and the presence of AI, along with the “re-emergence” of humans in research and maintenance, together create a complex labor landscape. This necessitates an answer to the question of who the true subject of intelligent labor is. Is the analysis of workers as labor subjects still valid?

The Source of Value Creation

According to Marx’s labor value theory, living labor is the sole source of value creation, and the value of a commodity is proportional to the amount of labor that produced it. In intelligent production systems, while AI significantly substitutes human labor, it also drives substantial growth in social wealth and productivity levels. Some Western scholars argue that Marx’s era could not foresee a continuous production process that “does not require direct human labor intervention.” When highly automated “unmanned factories” can produce goods at nearly zero marginal costs, the source of value creation shifts from human labor to machines and algorithms themselves. Is this indeed the case? If the answer is no, then where does the value of products and services from “unmanned factories” come from? In other words, does the classic proposition of labor value theory that “labor is the sole source of commodity value” still hold? This requires new answers.

The Explanatory Power of Labor Value Theory in AI Applications

“From the perspective of the 500-year history of world socialism, we are still in the historical era indicated by Marxism.” As an important content of the basic principles of Marxism, labor value theory has not lost its theoretical explanatory power due to changes in the times; rather, its applicability has expanded, further proving its scientific nature and explanatory power. As General Secretary Xi Jinping pointed out, “Some say that Marxist political economy is outdated, that ‘Capital’ is outdated. This assertion is arbitrary.”

AI as Objectified Knowledge Power

In real life, the development and application of AI manifest in various fields and aspects. From the perspective of social reproduction, AI also exists in a diverse manner.

1. AI as a Product: Marx pointed out in his analysis of the labor process that “labor combines with labor objects. The labor object is objectified, while the object is processed. What was previously expressed in dynamic form by the laborer now manifests as a static attribute in the product.” No machine is created by nature; machines are products of human society. As an objectified product of human essential power, machines are crystallizations of past human labor, knowledge, and wisdom. In this regard, AI is fundamentally similar to the spinning machine and steam engine; it is a product created collaboratively by scientists, engineers, and programmers, embodying a certain amount of value.

2. AI as Labor Material: Marx noted that after the production process incorporates capital, labor materials undergo various forms of transformation, with the final form being machines or, more precisely, automated machine systems. In intelligent production systems, AI machines represent a further developed form of automation, still fundamentally labor materials, albeit in a changed form. They are “human-created organs of the human brain,” representing “objectified knowledge power.”

3. AI as Fixed Capital: In the social reproduction process, AI remains a production material driven by human living labor, possessing higher production efficiency. From a capital perspective, it also plays a crucial role in capital accumulation as fixed capital. Regarding the impact of technological progress on fixed capital, Marx pointed out long ago that “the development of fixed capital indicates how much general social knowledge has become direct productive force, thus transforming the conditions of the social life process according to this intelligence.”

AI Cannot Replace Human Labor’s Subject Position

AI represents an enhancement of human productive capacity. The ability to manufacture and use tools distinguishes humans from animals and reflects humanity’s ability to overcome physiological limitations. From the perspective of human development history, the evolution from artificial physical capabilities to artificial intelligence signifies a continuous process of overcoming physiological limitations through technological advancement, thereby achieving human liberation. The invention of machines like steam engines allows humans to utilize powerful machine power to replace their limited physical strength. Currently, the human-like intelligence exhibited by generative AI partially achieves the replacement of limited mental capacity. The development process reflects the continuous enhancement of human productive capacity and the ongoing development of human liberation.

On one hand, AI lacks subjectivity in labor. In application, AI has not changed the human-made attributes and human factors in the production and research process, and it cannot completely detach from human autonomous production and free growth. All of AI’s “actions” stem from preset objective functions and training data, rather than from its own survival needs or social motivations. For instance, generative AI operates based on mathematical statistics and pattern matching, remaining within the realm of “weak AI.” Language models can extract complex statistical patterns from vast amounts of data, achieving high-quality text generation and semantic coherence through deep learning algorithms and large-scale training. However, its operational mechanism fundamentally relies on probabilistic modeling and cannot perform abstract reasoning in a human sense, let alone engage in self-awareness activities. The so-called self-iteration and self-upgrading are merely parameter optimization processes within the framework and objectives preset by algorithm engineers, heavily dependent on the quality and scale of data, with the evolutionary direction always defined and controlled by humans, which determines AI’s essential nature as a human tool.

On the other hand, this reflects the expansion of the concept of “overall workers” in the AI era. Marx’s analysis in “Capital” indicates that as production processes evolve, the concept of “overall workers” continuously expands. In the AI era, as social production’s division of labor and collaboration further develop, the concept of “overall workers” inevitably expands beyond the traditional factory walls. Essentially, “unmanned factories” are not truly unmanned; they are merely one part of the entire production process, with numerous researchers, annotators, and maintenance personnel behind them engaged in algorithm training, data annotation, and hardware maintenance. The workers who previously monitored and debugged machines have now transformed into those organizing, analyzing data, and issuing data commands to machines; they are the true subjects of intelligent labor.

AI is Not a Source of Value

AI machines not only directly participate in commodity production but also create the illusion of AI leading commodity production and creating value. In reality, AI machines are products of objectified labor; they “produce nothing as value” and cannot become sources of value. Throughout the production process, AI lacks complete autonomy and cannot completely detach from human labor, nor can it create value without human living labor. Regarding generative AI, regardless of how novel or creative its outputs appear, they are merely probabilistic deductions and result outputs based on existing program designs and algorithm models, and this computational process lacks social attributes. It must activate and realize value transfer through human living labor, inputting instructions, setting objectives, and intervening in processes. The value creation in AI production systems originates from the living labor of humans engaged in intelligent production, stemming from the intelligent labor of “overall workers.” Why does it seem that human living labor decreases while the value of products produced by some AI companies does not diminish but rather increases? The reasons can be summarized as follows:

1. Value Created by Intelligent Laborers: “Labor exists as activity, not as an object; it exists as the living source of value, not as value itself.” In intelligent production systems, value originates from the active labor of individuals operating, maintaining, and managing AI machines. For generative AI, living labor primarily includes the complex intellectual labor of computer scientists, data engineers, and algorithm engineers continuously optimizing models, as well as the mechanical and fragmented work of “digital laborers” engaged in data collection, annotation, image segmentation, semantic cleaning, and content review, which condenses vast amounts of undifferentiated human labor into underlying data. These two forms of living labor together constitute the true source of value for AI products.

2. Value Transfer of Constant Capital: The value transferred to new products includes portions from production materials and the consumption of AI machines. A large number of researchers contribute substantial labor to the development of new model architectures, algorithm iterations, and the deployment and maintenance of computing systems, which condenses value into AI machines. As labor materials, AI machines will “transfer their value to the products produced by their services, just like any other component of constant capital.” The value added during production will never exceed the value lost due to wear and tear. This consumption includes both tangible wear caused by usage and idleness, as well as intangible wear due to technological iterations.

3. Redistribution of Profits: Marx’s analysis in “Capital” indicates that enterprises that adopt advanced technologies and improve labor productivity will gain excess profits. It is evident that during certain periods, a few AI technology companies, leveraging their advantages in data, algorithms, and computing power, achieve labor productivity significantly higher than the industry average, thus creating technological barriers, obtaining market dominance, and securing excess profits. This essentially represents a redistribution of profits among capital.

Growth Points of Labor Value Theory in the AI Era

Compared to the time when Marx established labor value theory, significant changes have occurred in today’s era. “For Marxist political economy to remain vital, it must keep pace with the times.” We must seriously pay attention to and study the theoretical growth points regarding changes in labor forms and value creation spaces, enriching and developing Marxist labor value theory in a timely manner.

Attention to Major Changes in Labor Forms

As a unique conscious and purposeful social practice activity, labor is the material exchange process through which humans regulate their relationship with nature by expending their physical and mental efforts. Currently, the rapid development and widespread application of AI have given rise to intelligent labor, a new form of human labor. Compared to the presence, repetitiveness, and specificity of labor forms in the mechanical industrial era, intelligent labor exhibits significant characteristics of absence, creativity, and abstraction, achieving an iterative upgrade in human labor forms. Marx noted that “to engage in productive labor, it is no longer necessary to do it personally; it is sufficient to become an organ of the overall worker and fulfill a certain function.” With the development of intelligent labor, the concepts of production workers and production labor have further expanded.

In intelligent production systems, humans and AI form a complementary and collaborative relationship, with AI taking on repetitive, high-intensity, high-precision, and high-risk procedural tasks, while humans focus on creative labor. Data has become an important production factor, leading many to engage in “digital labor,” where production exhibits characteristics of non-material forms. The production and circulation of data have spawned a series of new industry branches, including complete supply chains dedicated to data collection, annotation, cleaning, classification, storage, analysis, and contextual application. Data can be infinitely replicated and artificially deleted, unlike traditional use values that possess specific and limited usefulness, making “digital labor” difficult to quantify by time. We must carefully study the new definitions of productive labor brought about by “digital labor”; examine the new characteristics of intelligent labor; and re-evaluate the distinctions between mental and physical labor, the conversion of complex and simple labor, and the transformation of private and social labor, providing new interpretations for labor quantity calculations. For the political economy with Chinese characteristics, the focus should be on researching how to promote the integrated development of the digital economy and the real economy, leveraging digital technology’s amplifying, overlapping, and multiplying effects on economic development.

Attention to the Expansion of Value Creation Spaces

In intelligent production systems, production activities exhibit important characteristics of fragmented labor time, virtualized labor management, and flexible labor locations. Intelligent labor extends from factory floors to digital platforms and social networks, greatly expanding the space for value creation. Some foreign scholars have proposed the concept of “platform capitalism,” indicating that public network platforms serve as new platforms for value creation, where value primarily derives from the extraction and capitalization of user behavior data, rather than being limited to traditional compensated wage labor. Users’ actions on digital platforms, such as attention, clicks, browsing, and comments, are recorded and utilized by platforms to optimize algorithms and customize more precise product services. In this regard, the global “digital laborers,” including workers producing hardware, software developers, data processors, and users generating data through online clicks, collectively create value in various forms. Among them, users of major online platforms often provide “digital labor” that is unpaid, passive, and not covered by traditional value theories, complicating the recognition of value sources. Therefore, it is essential to expand the categories of “labor,” “value creation,” and “laborers” to accommodate new phenomena in the AI era and deepen the understanding of new characteristics and spaces in value creation.

Attention to New Characteristics of Labor Process Control

Labor value theory not only profoundly reveals the basic principles of commodity value formation but also lays the theoretical foundation for uncovering the sources of surplus value. Under the widespread application of AI, labor process control no longer primarily relies on the management supervision of foremen or tangible production discipline constraints; instead, it mainly relies on systems governed by data and algorithms, exhibiting greater concealment, internalization, and real-time characteristics. Research on gig economy platforms in both domestic and international academia indicates that AI algorithms have achieved unprecedented precision in controlling labor processes through task assignment, pricing, supervision, and rating, creating a so-called production landscape where labor is supposedly unexploited. In reality, “digital labor,” unconstrained by labor time and space, can harm workers’ physical and mental health, while continuously optimized algorithms may alienate labor into “physically tortured and mentally devastated” negative activities. Engels once said that as human labor capacity continues to grow, “science increasingly makes natural forces subject to human control. This immeasurable productive capacity, once consciously applied for the benefit of the masses, will quickly reduce human labor to a minimum.” To realize Engels’ vision, the key lies in shifting the purpose of technological development from “value proliferation” to “human liberation.” In this regard, the contemporary mission of labor value theory is to reveal the roots of technological alienation under capital logic and provide theoretical support for technology benefiting the masses.