From Classic Labor to the Labor of the 'General Intellect'

[S. E. Anderson]

From Classic Labor to the Labor of the 'General Intellect'

 

by Te Li

Te Li is an assistant professor at the School of Economics and Management of Yunnan Open University. His research focuses on the mathematization of institutions and political economy.

https://monthlyreview.org

Issue: Vol. 77, No. 11 (April 2026)

Classical Exposition of Marxist Labor Theory

Marxist labor theory serves as the theoretical cornerstone of historical materialism and surplus value theory, permeating Karl Marx’s critical anatomization of the capitalist mode of production. This theoretical system takes labor as its core category and constructs a crucial framework for understanding the laws of human social development by revealing the social-historical, dual, and subjective characteristics of labor. The following classical exposition unfolds across four dimensions: the essential determination of labor, the theory of labor’s dual character, the mechanism of surplus value production, and the goal of human free and comprehensive development.

Marx defined labor as the “metabolism” between humans and nature, emphasizing its dual attributes: on the one hand, it is a naturally necessary activity for producing material means of subsistence; on the other hand, it is an objectifying activity that confirms human essential powers.¹ In the Economic and Philosophic Manuscripts of 1844, Marx pointed out: “The whole character of a species, its species-character, lies in the nature of its life activity.… The species-character of man is precisely free conscious activity.”² This philosophical positioning of labor transcends the narrow perspective of classical political economy that merely views labor as a source of wealth, endowing labor with ontological significance—it is both the essential characteristic that distinguishes humans from animals and the bond that forms social relations.

A key characteristic of the Marxist conception of labor is its distinct historicity and sociality. Labor is not merely the expression of individual behavior but collective activity conducted under social-historical conditions. With the development of productive forces, the forms, nature, and content of labor, as well as its role in social structure, continuously change. In Marx’s theoretical framework, labor is intimately connected with social formations, modes of production, class structures, and comprehensive human development.

The social character of labor determines that it always exists within specific production relations. Marx explicitly opposed abstract discussions of labor, advocating that labor’s actual forms must be examined within concrete social formations. For example, slave labor, serf labor, and wage labor, while sharing the name “labor,” actually present fundamentally different social natures due to differences in the ownership of the means of production. This methodological insight teaches us that isolated labor analysis divorced from production relations will obscure the essence of exploitation.

The theory of labor’s dual character (concrete labor and abstract labor) proposed by Marx in the first volume of Capital represents a major innovation in the history of political economy. Concrete labor creates use value, embodying the material exchange relationship between humans and nature; abstract labor forms the substance of value, reflecting social relations among commodity producers. This distinction completely dismantled the erroneous understanding of classical economists, who conflated labor with general production factors.

In the context of modern digital intelligence, labor’s value creation remains the core of social productive force development. However, with the widespread application of automation, artificial intelligence, and big data, both labor’s value creation and the forms of surplus value exploitation have undergone significant changes. This means that Marx’s value theory needs reexamination in the context of the digital intelligence era to address the challenges and transformations brought by intelligent labor.

Particularly noteworthy is Marx’s emphasis that “all labour is an expenditure of human labour-power, in the physiological sense, and it is in this quality of being equal, or abstract, human labour that it forms the value of commodities.”³ This contains two layers of deep meaning: first, abstract labor is not physical energy expenditure but a unit of measurement for socially necessary labor time; second, the essence of value is reified social relations, not natural attributes. This dialectical thinking laid the theoretical foundation for revealing the secret of surplus value.

Through analysis of the capitalist production process, Marx revealed the distorted state of labor under capital’s domination. In Capital, he divided the working day into necessary labor time and surplus labor time, with the former reproducing labor power value and the latter creating surplus value gratuitously for capitalists. This division leads to two serious consequences: first, workers can only receive compensation equivalent to the value of their labor power, resulting in a regime rooted in relative immiseration; second, labour’s own products become tools for capital valorization that in turn rule over workers, creating a condition in which “dead labour dominates and soaks up living labour.”⁴

The Economic and Philosophic Manuscripts of 1844 more sharply pointed out capitalism’s fourfold alienation of labor: workers’ alienation from their labor products, from themselves, from others, and from nature. The root of this alienated state lies in the externalization of labor caused by private property—labor that should be a means of self-realization becomes merely a means of survival. Marx thus concluded: “Only in community with others has each individual the means of cultivating his gifts in all directions.”⁵

Marxist labor theory ultimately points toward human liberation. The Communist Manifesto solemnly declares: “In place of the old bourgeois society, with its classes and class antagonisms, we shall have an association in which the free development of each is the condition for the free development of all.”⁶ This “free development” is built upon the sublation of capitalist labor alienation: when public ownership of means of production eliminates the basis of exploitation, labor can return to its authentic state—being both a means of livelihood and a means of self-realization.

In Critique of the Gotha Programme, Marx envisioned the higher phase of communist society implementing “from each according to his ability, to each according to his needs,” where labor would no longer be subject to external coercion and would truly become “life’s prime want.” However, he emphasized that achieving this ideal state requires a long historical process, and the current task is to break capital’s control over labor through socialist revolution and rebuild workers’ subjective status.

Marxist labor theory not only criticizes the oppressive nature of capitalist labor relations but also proposes the theory of labor liberation in socialist society. Marx clearly stated in the Communist Manifesto that the ultimate goal of socialist revolution is to eliminate class differences and achieve worker liberation: “The emancipation of the proletariat must be the work of the entire human race.”⁷ He believed that socialist society should eliminate private ownership of means of production, enabling workers to determine collectively the production and distribution methods enabling common enjoyment of social wealth. The socialist society Marx envisioned is one that realizes free and comprehensive human development. In this society, labor is no longer identified with individual alienation, no longer a mere activity for survival, but a means for comprehensive individual development. Labor in socialist society is free, meaningful, and capable of serving comprehensive human progress.

Marxist labor theory penetrates the fog of economic phenomena with profound dialectics, both affirming the great power of labor in creating civilization and ruthlessly exposing labor alienation under the capitalist system. This theory remains our intellectual weapon for analyzing contradictions in labor relations in the digital economy era, uncovering how the pursuit of labor liberation provides direction for human development in the age of general intellect.

The Digital Intelligence Wave Reshaping Labor’s Essential Determination

With the deep integration of digital technology and intelligent technology (hereinafter referred to as “digital intelligence”), human society’s production paradigm is undergoing revolutionary transformation. This transformation not only changes the physical forms of labor tools and objects of labor but more profoundly shakes the essential determination of labor revealed by Marxist labor theory. Labor is no longer simply the “material exchange between humans and nature” but has evolved into a complex system containing data elements, algorithmic mediation, and intelligent collaboration. This reconstruction both expands the theoretical boundaries of labor and brings new demands for theoretical interpretation. The following multidimensional analysis examines the reshaping effects of digital intelligence on labor’s essential determination.

Classical labor theory centers on human workers, emphasizing their core position in value creation. However, in the digital intelligence era, robotic arms on industrial production lines can autonomously complete precision assembly, unmanned vehicles in logistics warehouses can dynamically optimize routes, and even some creative work has begun to involve generative AI. Such scenarios indicate that the main force of direct material production has gradually evolved into human-machine collaborative systems. The traditional relationship of “living labor dominating dead labor” has been broken, replaced by new labor relations where workers and intelligent machines are mutually constituted subjects. This transformation compels us to reexamine the connotation of labor’s subjectivity: when machines possess learning capabilities and can actively adapt to environments, human workers’ roles increasingly shift toward supervisors, coordinators, and innovative decision-makers—along with machine trainers and other supportive operatives.

Under the digital intelligence wave, workers’ roles have undergone profound changes. First, workers’ jobs are no longer mainly those of operatives and physical laborers but increasingly shift toward technical support, data analysis, and innovative work. With the rise of artificial intelligence, traditional workers may face the risk of being replaced by machines, especially those engaged in repetitive, standardized work may lose employment opportunities. A World Economic Forum report predicted in 2020 that by 2025 more than 85 million jobs worldwide would disappear due to automation, while 97 million new positions would be created, most of which would require digital skills and innovative capabilities.⁸

The digital intelligence wave has, to some extent, intensified capital’s exploitative relationship with labor. With the application of artificial intelligence and automation technology, enterprises can replace human labor with machines, reducing production costs and increasing profits. However, this also leads to workers’ declining status in work, particularly low-skilled workers facing unemployment or wage decline. According to an International Labour Organization report, the digitalization wave may further expand global wage gaps, with low-skilled workers’ incomes decreasing while high-skilled workers’ incomes may increase more significantly.⁹

In the digital intelligence economy, massive data becomes a key production factor, constituting a special object of labor. Data collectors’ daily operations involve transforming the physical world into digital signals, while algorithm engineers’ training process essentially involves mining and refining data patterns. Unlike traditional raw materials, data possesses characteristics of non-consumption, replicability, and marginal costs approaching zero, fundamentally changing how labor objects are processed—from transforming material entities to processing information symbols. More importantly, data itself carries social relational attributes, with its collection, circulation, and use processes deeply embedded in the logic of capital and social power structures, endowing labor objects with unprecedented social complexity.

Time-based wage systems were capitalism’s iconic invention for controlling labor time, and in the digital intelligence era, algorithms have achieved microscopic, refined management of labor processes. Delivery riders’ routes are calculated in real time by systems, ride-hailing drivers’ service hours are precisely tracked, and livestream hosts’ speaking rhythms are governed by traffic algorithms. This algorithm-dominated labor process control presents dual characteristics: superficially improving resource allocation efficiency while actually pushing Taylorist scientific management to its extreme. This leads to a fragmenting of labor time and makes labor intensity less scrutable. Workers seemingly gain the freedom of flexible employment but actually fall into efficiency traps set by algorithms, with the boundaries between necessary labor time and surplus labor time becoming increasingly blurred due to continuous online work states.

Applications in smartphone app stores, content creation on short video platforms, product recommendation lists on e-commerce platforms: these typical digital intelligence era labor products possess significant virtual characteristics. They occupy no physical space, yet achieve massive value realization through the attention economy. This value capture mechanism highlights contemporary labor’s specific contradictions: on the one hand, virtual products’ use value highly depends on users’ subjective experience; on the other hand, their exchange value strictly follows market laws. When the number of likes determines content creators’ revenue share, labor value measurement standards have actually completed a perilous leap from labor time to user attention.

Digital intelligence technology has broken traditional labor’s spatiotemporal constraints, giving rise to new forms such as flexible employment, remote work, and the gig economy. The COVID-19 pandemic further accelerated this trend, transforming remote work from an exceptional situation to a routine choice.¹⁰

In the temporal dimension, digital labor exhibits “24/7” characteristics. Platform workers can take orders at any time, content creators have no fixed working hours, and programmers frequently need to respond to sudden system failures. The traditional concept of “working day” becomes blurred, with boundaries between work time and rest time increasingly dissolved. This change both provides workers with temporal flexibility and brings problems of uncontrollable work intensity.¹¹

In the spatial dimension, workplaces are no longer limited to physical spaces like factories and offices. Cloud computing technology enables office work anywhere with Internet connectivity, while virtual reality technology further expands possibilities for remote collaboration. Global talent mobility and collaboration become possible, with transnational project teams achieving seamless integration through digital platforms.¹²

This spatiotemporal reconstruction poses new requirements for labor management and rights protection. Traditional labor law issues, such as defining work hours, calculating overtime pay, and ensuring occupational safety, become more complex in digital environments. Simultaneously, it provides technical conditions for achieving more humanized and personalized labor arrangements.

Digital intelligence has not negated Marxist labor theory’s basic framework but rather confirms its powerful and unique explanatory capacity. Just as the factory system emerging in the steam engine era did not overturn surplus value theory, algorithmic governance in the artificial intelligence era similarly needs analysis within the framework of labor’s dual character. The key lies in grasping the dialectical relationship between change and continuity: what changes is only labor’s specific manifestation forms and technological carriers; what remains constant is the basic fact of labor as the basis of the reproduction of the social. Currently, there is an urgent need to develop Marxist labor value theory in relation to digital intelligence practices, particularly theoretical innovation in areas such as data property rights definition, algorithmic ethics regulation, and the protection of digital labor rights.

New Contradictions Created by Digital Labor and Socialist Solutions

One of the most prominent contradictions in the digital intelligence era is the conflict between the monopolistic positions formed by large tech companies through their technological advantages and the widespread need for workers’ rights protection. This monopoly differs from traditional resource monopolies; it is based on control over digital resources such as data, algorithms, and platforms, possessing greater concealment and penetration.¹³

The rise of platform economies has enabled a few large tech enterprises to control massive user data and advanced algorithmic technologies, forming de facto “digital oligarchs.” Taking the United States as an example, tech giants like Google, Amazon, Apple, and Meta possess overwhelming advantages in their respective fields. They not only control key nodes of information circulation but also determine the income and work opportunities of millions of platform workers through algorithms.¹⁴ This technological monopoly places workers in extremely disadvantageous positions in the digital economy: unilateral platform rule-making, algorithmic black box operations, severely skewed income distribution, and an absence of work guarantees are becoming increasingly serious problems.¹⁵ Although antimonopoly regulation has been continuously strengthened in various countries, structural contradictions in platform economies persist. Workers in new business forms such as food delivery and ride-hailing drivers face difficulties in labor relation recognition, absence of social security, and challenges in workplace injury rights protection.

Socialist systems provide the institutional foundation for resolving this contradiction. First, adhering to an ownership structure with public ownership as the main body can fundamentally prevent excessive concentration of means of production in the hands of a few capitalists. In the digital economy field, participation by state-owned enterprises and collective economies can form effective checks against private monopolies. Second, strengthening government macroeconomic regulation functions through antimonopoly enforcement, data property rights definition, and platform responsibility, while standardization maintains fair market competition. Third, establishing and improving labor protection systems adapted to new business form characteristics ensures platform workers enjoy basic labor rights and social security.

Another prominent contradiction in intelligent labor is the fundamental opposition between algorithmic systems’ deep intervention in labor processes and human needs for subjectivity and dignity. This contradiction is particularly evident in platform economies, where algorithms not only determine workers’ work content and pace, but penetrate deeply into workers’ behavioral patterns and thinking modes, forming new types of “algorithmic discipline.”

In the food delivery industry, algorithmic systems precisely calculate delivery time and routes for each order, implementing real-time monitoring and dynamic adjustment of drivers. This “algorithmic management,” while improving delivery efficiency, also transforms workers into tools for algorithm execution, seriously damaging their autonomy and creativity.¹⁶ Similar situations appear in ride-hailing, express delivery, domestic services, and other industries. More seriously, some algorithmic systems conduct “credit ratings” based on workers’ historical performance, affecting their future work opportunities and forming digitized hierarchical systems.¹⁷

This algorithmic control is essentially a new form of capital’s domination over labor. As Marx analyzed, the goal of capitalist production processes is to pursue surplus value maximization, with workers being merely means to achieve this goal. In the digital intelligence era, algorithms become new tools for capital to control labor, with precision and coverage far exceeding traditional management methods.

Socialism’s fundamental goal of achieving comprehensive human development provides a critical orientation for resolving algorithmic control contradictions. First, establishing a “people-centered” technological development concept requires that algorithmic design and application must serve human development needs, not the reverse. Second, establishing algorithmic transparency and explainability systems protects workers’ right to know and supervise, preventing algorithmic black box operations. Third, improving mechanisms for worker participation in platform governance through trade union organizations and collective bargaining gives workers a voice in algorithmic rule-making.¹⁸

Digital intelligence technology has created enormous social wealth, but the distribution of these “digital dividends” is extremely unbalanced, forming new wealth gaps. This imbalance manifests not only between enterprises and workers but also among different types of workers, regions, and age groups.

Globally, digital economy development has enabled a few tech giants to accumulate unprecedented wealth. Statistics show that the total market capitalization of the world’s top ten tech companies exceeds many countries’ GDP. These companies have relatively few employees, meaning there is extremely high value appropriated per unit of labor.¹⁹ In stark contrast, large numbers of traditional industry workers face the problems of obsolete skills, declining incomes, and employment instability. This “digital divide” not only exacerbates social inequality but also threatens social stability.

Socialism’s essential requirement of achieving common prosperity provides fundamental guidance for solving unequal digital dividend distribution, according to the following principles. First, development achievements that are shared by the people through redistributive measures such as tax regulation and transfer payments help to narrow income gaps. Second, increasing investment in digital infrastructure construction in underdeveloped areas and promoting digital rural construction enable more people to enjoy digital economy development dividends. Third, improving vocational education and skills training systems helps traditional industry workers adapt to digital transformation, preventing large-scale structural unemployment.²⁰

The digital intelligence era has witnessed new forms of labor alienation that both continue traditional alienation and exhibit digitization-specific manifestations. This new alienation constitutes a profound contradiction with socialism’s ideal of pursuing comprehensive human development.

Alienation in digital labor first manifests as workers’ alienation from labor products. In the data economy, users’ every click, browse, and purchase becomes platform data assets, but users themselves cannot share the value created by this data. This “free labor” completely separates workers from their labor results. Second, workers’ alienation from labor processes is enhanced, as algorithmic control makes labor highly standardized and mechanized, with workers losing control over work pace and methods. Third, the alienation of human relationships increases, since digital platforms, while connecting masses of users, also lead to reduced face-to-face communication and fragmented social relations.

More seriously, digital technology may exacerbate human alienation from nature. Although the digital economy is frequently characterized as a “green economy,” problems such as data center energy consumption and electronic product manufacturing and disposal are increasingly prominent. Artificial intelligence training and operation require enormous electricity consumption and intensifying environmental burdens.²¹

Socialist systems, by prioritizing comprehensive human development as their central objective, provide institutional guarantees for overcoming new forms of labor alienation. First, through public ownership and distribution according to labor systems, socialism ensures that workers can share the fruits of their labor creation, rebuilding the inherent connection between workers and labor products. Second, it advocates human-centered technological development concepts, making technological progress serve human development needs rather than subjugating humans to technology. Third, it constructs new social relations in the digital age, promoting comprehensive human interaction and collaboration through digital means and achieving organic unity between individual development and social development.

The new contradictions created by intelligent labor exhibit complexity and profundity, reflecting both contradictions between technological progress and institutional lag and conflicts between capital logic and humanistic values. Socialist systems, with their unique institutional advantages and value pursuits, can provide fundamental solutions for resolving these contradictions. However, this requires advancing practical exploration based on theoretical innovation, and continuously perfecting socialist institutional systems to adapt them to the requirements of the digital intelligence era.

Pathways for the Contemporary Development of Socialist Labor Theory

Facing the profound transformation of labor forms in the digital intelligence era and the new contradictions brought by intelligent labor, socialist labor theory must undergo contemporary development while adhering to basic principles. This development is not a simple revision of classical theory but rather a creative interpretation and practical expansion of Marxist labor theory under new historical conditions. The contemporary development of socialist labor theory requires coordinated advancement across three levels: theoretical construction, institutional innovation, and practical exploration, constructing a new labor theoretical system that both embodies socialist essential requirements and adapts to digital intelligence era characteristics. This development pathway relates not only to the improvement of theoretical systems but also to the full realization of the superiority of the socialist system and effective protection of people’s fundamental interests.

The contemporary development of socialist labor theory first requires innovative reconstruction of conceptual systems and analytical frameworks at the theoretical construction level. This process needs to construct a theoretical system that accurately reflects the essence of contemporary labor relations by inheriting the scientific core of Marxist labor theory while combining new characteristics of the digital intelligence era.

In terms of conceptual system reconstruction, traditional labor concepts need expansion and deepening. First is the expansion of the labor subject concept, from purely human workers to “human-machine collaborative labor subjects,” recognizing the quasi-subject status of machine-learning systems under specific conditions while clarifying human dominance in labor processes. Second is the digital transformation of labor object concepts, incorporating intangible elements such as data, algorithms, and virtual assets into the category of labor objects, establishing labor object classification systems adapted to digital economy characteristics.²² Third is the computational transformation of labor process concepts, highlighting new features such as algorithmic participation, human-machine interaction, and data-driven processes, forming conceptual frameworks that reflect the essence of labor processes in the digital intelligence era.

In terms of analytical framework innovation, multidimensional and multilevel analytical systems must be constructed. Vertically, this requires establishing analytical chains from micro-individual labor to macro-social labor, covering individual workers’ skill adaptation, enterprise-level organizational transformation, industry-level structural adjustment, and social-level institutional innovation. Horizontally, it necessitates constructing comprehensive analytical frameworks covering economic, political, cultural, social, and ecological dimensions to grasp fully the complexity and diversity of labor relations in the digital intelligence era.

Particularly important is innovative development of value creation theory. While adhering to basic principles of labor value theory, deep analysis of the mechanisms by which new elements such as data factors, algorithmic systems, and network effects function in value creation is needed to construct value creation theory adapted to digital economy characteristics. Simultaneously, attention must be given to expropriation of unpaid labor in non-market labor forms such as open-source software development, knowledge sharing, and community service.²³

Theoretical innovation must combine with institutional innovation to truly realize the contemporary development of socialist labor theory. The core of institutional innovation is establishing labor security mechanisms and governance systems adapted to digital intelligence era requirements, providing institutional support for worker rights protection and harmonious social development.

In terms of labor relations adjustment mechanisms, labor relation recognition standards and management systems adapted to new employment forms need to be established. Addressing the difficulty of labor relation recognition in platform economies, exploring “quasi-employment relationship” concepts can provide legal protection for new labor relations between traditional employment relationships and complete freelancing. Simultaneously, collective bargaining mechanisms must be improved, supporting platform workers’ participation in platform rule-making through organizations such as trade unions to protect their legitimate rights.

Unified social security systems covering all workers must also be constructed. The focus should be establishing social insurance systems for flexible employment personnel and solving social security problems for groups such as platform workers and freelancers. Instituting “digital worker security funds,” jointly funded by platform enterprises, government, and workers, can provide basic security for workers in these new forms of labor.

In addition, digital rights protection mechanisms, data property rights systems and digital worker rights protection systems must be put into place. Clarifying personal data property ownership and creating data value sharing mechanisms enables data producers to share in data commercialization benefits. Simultaneously, there must be algorithmic transparency systems, requiring algorithmic systems involving worker rights to disclose basic logic and decision-making bases to workers, protecting their right to know and supervise these systems.

In skills training and employment services, it is important to set up lifelong learning systems and intelligent employment service platforms. Establishing skills training systems with joint participation by government, enterprises, and social organizations helps workers adapt to technological transformation requirements. Using artificial intelligence technology to provide precise employment services achieves intelligent and personalized job matching.

The contemporary development of socialist labor theory ultimately requires testing and improvement through practical exploration. Diversified practical exploration needs to be carried out in different fields and at distinct levels, accumulating experience and forming replicable and promotable development models.

At the enterprise level, it is necessary to encourage state-owned enterprises and private enterprises to explore humanized intelligent management models. Promoting management approaches combining “algorithms + human intervention” leverages algorithmic systems’ efficiency while maintaining humanistic care and flexibility. Supporting enterprises in establishing mechanisms for worker participation in digital governance, such as establishing “algorithmic committees” and conducting “algorithmic audits,” gives workers greater voice in technological applications.

In platform governance, there must be the implementation of collaborative governance mechanisms with multi-subject participation. Government would play regulatory and guiding roles, platform enterprises would assume primary responsibilities, worker organizations would represent group interests, and professional institutions would provide technical support, forming overall governance synergy.

In regional development, coordinated development between digitally developed and underdeveloped regions is crucial. In international cooperation, there must be active participation in constructing a global digital governance system that promotes a fair and reasonable international digital economic order.

The three levels of socialist labor theory’s contemporary development are not isolated but constitute an organic whole of mutual connection and promotion. Systematic consideration of relationships among theoretical construction, institutional innovation, and practical exploration is needed to construct systematic development strategies.

In temporal arrangements, it is crucial to handle the relationships between inheritance and innovation well. It is necessary to proceed by both adhering unwaveringly to basic principles of Marxist labor theory and conducting theoretical innovation according to characteristics of the era; both learning from and borrowing advanced foreign experiences and exploring development paths suited to national conditions based on actual circumstances.

In key tasks, the question is combining problem orientation with goal orientation. Concentrating efforts on prominent contradictions and problems in digital intelligence era labor relations while focusing on long-term goals of achieving comprehensive human development and common social progress, systematically planning development pathways, is essential.

In advancement mechanisms, leveraging the superiority of the socialist system is vital. This includes strengthening Party leadership, utilizing government’s coordinating role, mobilizing enthusiasm from all sectors, and forming powerful synergy for advancing labor theory’s contemporary development. Simultaneously, it is necessary to respect a practical pioneering spirit, encouraging grassroots exploration and innovation, to learn from and provide successful experiences.

The contemporary development of socialist labor theory is a long-term historical process requiring continuous exploration and improvement in practice. Only by adhering to the combination of theory and practice, unity of inheritance and innovation, and coordination between actual conditions and world trends can we construct a new theoretical system of labor that both embodies the essential requirements of socialism and adapts to the characteristics of the digital intelligence era, providing scientific guidance for achieving high-quality development and enhancing people’s lives.

The Vision of a Civilization of “General Intellect Labor”: Toward the Realm of Freedom

In Capital, Marx depicted the historical process of human society moving from the “realm of necessity” to the “realm of freedom,” emphasizing that “the true realm of freedom” can only flourish when built upon the foundation of the “realm of necessity.”²⁴ In the digital intelligence era, the development of intelligent technology provides unprecedented material and technical conditions for realizing this great ideal. Through the guidance and regulation of socialist systems, implementation of the general intellect promises to construct a new civilizational vision that both fully liberates productive forces and comprehensively develops human capabilities, truly realizing Marx’s envisioned ideal society where “the free development of each is the condition for the free development of all.”

The widespread application of intelligent technologies such as artificial intelligence, robotics, and automation systems could completely liberate humanity from the shackles of physical labor. In “intelligent” factories, robots undertake the vast majority of production tasks while human workers primarily engage in creative design, quality monitoring, system optimization, and other creative work. In service industries, intelligent systems handle standardized service demands while humans focus on personalized service and emotional communication. This division of labor is not simple human-machine substitution but optimized allocation through human-machine collaboration.

More importantly, the development of machine learning will dramatically reduce socially necessary labor time. As Marx prophesied, when “social productive force development becomes so rapid” that “direct labor time becomes increasingly less,” humanity will possess more free time for comprehensive development.²⁵ In such conditions, standard working hours may be shortened to twenty to thirty hours per week or even less, enabling people to have sufficient time for learning, creative activities, entertainment, and social activities, achieving true balance between work and life.²⁶

The core characteristic of a civilization organized around what Marx called “the general intellect” is the transformation of labor content in creative, knowledge-based, and emotional directions.²⁷ When machines undertake most standardized and programmed work, human labor will mainly concentrate in areas machines cannot replace: innovation and creation, complex decision-making, emotional communication, and value judgment. This transformation makes labor truly become the objectification of human essential powers, achieving a fundamental transformation from “means of livelihood” to “life’s need.”

In the civilization of general intellect labor, where the knowledge economy dominates, knowledge-intensive labor such as scientific research, technological innovation, artistic creation, and education and training will become primary forms of labor. Workers are no longer mechanical “cogs” executing instructions, but knowledge workers with independent thinking capabilities and an innovative spirit. Simultaneously, as basic material needs are satisfied, people’s demands for spiritual and cultural products will increasingly grow, with the value of emotional labor such as cultural creativity, psychological counseling, and social service receiving full recognition.

This civilization of the general intellect and the collective worker will thoroughly transform traditional employment relations, constructing more equal, democratic, and cooperative new labor relations. Under conditions of socialized means of production and general-intellect labor processes, traditional capitalist-worker antagonistic relations will be replaced by cooperative relations among workers. Workers are no longer passive “human resources,” but cooperative partners actively participating in enterprise decision-making and management.

Digital platform development provides technical support for realizing labor relation democratization. Decentralized Autonomous Organizations established through blockchain technology can achieve workers’ direct participation and democratic decision-making. Smart contract technology ensures transparent and fair benefit distribution, enabling workers to receive corresponding returns based on contributions. This new type of labor relation embodies socialism’s essential requirement of “workers being masters,” laying foundations for achieving genuine economic democracy.

The civilization of the general intellect creates unprecedented conditions for comprehensive individual development. Productivity improvements and working time reductions brought by technological progress enable individuals to develop talents in multiple fields, no longer strictly limited by the traditional division of labor. One person can simultaneously be a scientific researcher, artistic creator, social service provider, and other multiple identities, truly realizing Marx’s envisioned free life of “hunting in the morning, fishing in the afternoon, engaging in animal husbandry in the evening, and engaging in criticism after dinner.”²⁸

Lifelong learning becomes a basic characteristic of the general intellect civilization. Facing rapidly changing technological environments, workers need to continuously update knowledge and skills; this learning is not passive adaptation but active self-development. Artificial intelligence technology provides personalized learning programs; virtual reality technology creates immersive learning environments, making learning processes more efficient and pleasant. Boundaries between education and labor, learning and practice, increasingly blur, forming a social atmosphere of universal learning and lifelong development.

The civilization of the general intellect requires a fundamental transformation of social relations from competition to cooperation. Under conditions of extremely abundant material wealth, survival competition pressure greatly diminishes, with people more willing to achieve common development through cooperation. New cooperative models such as open-source software development, knowledge sharing platforms, and collaborative innovation networks have already demonstrated strong vitality, indicating enormous potential for future social cooperation.

Globalized digital networks provide technical foundations for constructing a community with as a shared future for humanity. Through the Internet, people from different countries and cultural backgrounds can engage in real-time collaboration, jointly solving major challenges facing humanity. Global issues such as climate change governance, disease prevention and control, and poverty elimination require collective human effort. Intelligent technology provides powerful tools for such global cooperation.

The road toward a general-intellect labor civilization will not be smooth and requires overcoming numerous challenges such as technological monopoly, digital divides, and algorithmic biases. Socialist systems, with their unique advantages, provide realistic pathways for realizing this ideal. Public ownership ensures intelligent technology serves all people; planned regulation prevents disorderly technological development, and democratic participation protects workers’ rights.

Conclusion

In the digital intelligence era, the essence of labor is undergoing profound transformation. The widespread application of artificial intelligence, automation technology, and big data has reshaped labor relations and transcended the traditional Marxist labor theory concept of “labor as the process of material exchange between humans and nature.” As labor gradually integrates into new production models of data, algorithms, and intelligent collaboration, traditional mechanisms of labor value creation and exploitation face new challenges and interpretative needs.

Nevertheless, the core principles of Marxist labor theory remain important theoretical weapons for analyzing labor relations in the digital economy era. Under capitalist systems, the basic structure of labor exploitation still exists, though its forms have changed. Technological progress has not eliminated inequality in labor, especially when a few large tech companies form monopolies through controlling data and algorithms, making worker rights protection issues increasingly serious. Therefore, socialist systems provide effective institutional foundations capable of addressing these new contradictions and ensuring the protection of worker rights in the digital intelligence era.

Socialist labor theory provides theoretical support for resolving these contradictions. Through adhering to ownership structures with public ownership as the main modality, strengthening government macroeconomic regulation functions, and innovating labor protection systems, it can effectively prevent the wealth and opportunity inequality brought by technological progress. Under the guidance of a socialist system, digital intelligence technology may transform into a driving force for liberating productive forces and promoting comprehensive human development, rather than intensifying exploitation and inequality.

Although digital intelligence technology is bringing an unprecedented transformation in labor relations, socialism’s goal of pursuing free and comprehensive human development remains the fundamental pathway for resolving current labor contradictions. It is necessary to promote the development of socialist labor theory in our time based on theoretical innovation and practical exploration, ensuring that technological progress ultimately serves the common welfare of all workers.

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Notes

1. ↩ Karl Marx, Capital: A Critique of Political Economy, vol. 1 (London: Penguin, 1976), 283.
2. ↩ Karl Marx, Economic and Philosophic Manuscripts of 1844 (Moscow: Progress Publishers, 1959), 75.
3. ↩ Marx, Capital, vol. 1, 137.
4. ↩ Marx, Capital, vol. 1, 548.
5. ↩ Karl Marx and Friedrich Engels, The German Ideology, ed. C. J. Arthur (New York: International Publishers, 1970), 83.
6. ↩ Karl Marx and Friedrich Engels, The Communist Manifesto (London: Penguin, 2002), 244.
7. ↩ Marx and Engels, The Communist Manifesto, 245.
8. ↩ World Economic Forum, The Future of Jobs Report 2020 (Geneva: World Economic Forum, 2020).
9. ↩ International Labour Organization, World Employment and Social Outlook: Trends 2019 (Geneva: ILO, 2019).
10. ↩ Richard Baldwin, The Globotics Upheaval: Globalization, Robotics, and the Future of Work (Oxford: Oxford University Press, 2019).
11. ↩ Janine Berg et al., Digital Labour Platforms and the Future of Work: Towards Decent Work in the Online World (Geneva: International Labour Office, 2018).
12. ↩ Nicholas Bloom, James Liang, John Roberts, and Zhichun Jenny Ying, “Does Working from Home Work? Evidence from a Chinese Experiment,” Quarterly Journal of Economics 130, no. 1 (2015): 165–218.
13. ↩ K. Sabeel Rahman and Kathleen Thelen, “The Rise of the Platform Business Model and the Transformation of Twenty-First-Century Capitalism,” Politics & Society 47, no. 2 (2019): 177–204.
14. ↩ Geoffrey G. Parker, Marshall W. Van Alstyne, and Sangeet Paul Choudary, Platform Revolution: How Networked Markets Are Transforming the Economy and How to Make Them Work for You (New York: W. W. Norton & Company, 2016).
15. ↩ Alex Rosenblat and Luke Stark, “Algorithmic Labor and Information Asymmetries: A Case Study of Uber’s Drivers,” International Journal of Communication 10 (2016): 3758–84.
16. ↩ Katherine C. Kellogg, Melissa A. Valentine, and Angèle Christin, “Algorithms at Work: The New Contested Terrain of Control,” Academy of Management Annals 14, no. 1 (2020): 366–410.
17. ↩ A. Gandini, “Labour Process Theory and the Gig Economy,” Human Relations 72, no. 6 (2019): 1039–56.
18. ↩ Kurt Vandaele, Will Trade Unions Survive in the Platform Economy?: Emerging Patterns of Platform Workers’ Collective Voice and Representation in Europe (Brussels: ETUI Working Paper, 2018).
19. ↩ “The World’s Largest Public Companies 2023,” Forbes Media, 2023.
20. ↩ Christian Fuchs, Digital Labour and Karl Marx (New York: Routledge, 2014).
21. ↩ Emma Strubell, Ananya Ganesh, and Andrew McCallum, “Energy and Policy Considerations for Deep Learning in NLP,” Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics (2019): 3645–50.
22. ↩ Erik Brynjolfsson and Tom Mitchell, “What Can Machine Learning Do?: Workforce Implications,” Science 358, no. 6370 (2017): 1530–34.
23. ↩ Yochai Benkler, The Wealth of Networks: How Social Production Transforms Markets and Freedom (New Haven: Yale University Press, 2006).
24. ↩ Karl Marx, Capital, vol. 3 (London: Penguin, 1981), 959.
25. ↩ Karl Marx, Grundrisse: Foundations of the Critique of Political Economy (New York: Penguin, 1993), 706.
26. ↩ Erik Brynjolfsson and Andrew McAfee, The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies (New York: W. W. Norton & Company, 2014).
27. ↩ Marx, Grundrisse, 706.
28. ↩ Marx and Engels, The German Ideology, 53.

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s. e. anderson
author of The Black Holocaust for Beginners
"If WORK was good for you, the rich would leave none for the poor." (Haiti)
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