Marx’s Labor Theory of Value in the Era of Data Commodification: A Quantum Dialectical Perspective

Marx’s labor theory of value (LTV) emerged in the industrial age, a historical moment when commodities were tangible objects produced in factories through the expenditure of human labor time. In that epoch, the commodity was nothing less than crystallized labor, solidified in the form of material goods. The rhythm of exploitation and accumulation could be observed in the visible contrast between the worker’s exertion on the shop floor and the surplus appropriated by capitalists. Yet, in the contemporary age, the engine of accumulation has migrated from the industrial to the digital domain. Today’s capitalism increasingly turns to the commodification of data—clicks on a screen, online profiles, consumer preferences, genetic codes, medical records, and even the most fleeting behavioral traces of daily life. These fragments of existence are transformed into monetizable assets. The paradox, however, lies in the fact that unlike a machine or a garment produced in a factory, data is not manufactured in the traditional sense. It does not emerge from a deliberate process of production but is rather captured, extracted, and recombined by powerful digital infrastructures. This raises the pressing question: does Marx’s LTV still hold in this new terrain where value seems to emerge from intangible flows rather than material labor?

From the standpoint of Quantum Dialectics, the answer is not to discard or abandon Marx’s insights, but to dialectically negate and sublate them into a higher synthesis. The essence of value remains rooted in human labor, yet its appearance has undergone a qualitative transformation in what may be described as the quantum layer of digital capitalism. Here, new forces of cohesion—monopoly control, platform infrastructures, and intellectual property regimes—organize and stabilize the dispersed fragments of data into commodities. At the same time, countervailing forces of decohesion—open-source networks, user-generated flows, and popular resistance to surveillance—continuously destabilize this process, preventing it from reaching a fixed equilibrium. The commodification of data, therefore, is not a refutation of Marx’s theory but its dialectical unfolding into higher complexity. In this unfolding, the LTV retains its centrality, but now expresses itself in more elusive, layered, and mediated forms. It is precisely within these contradictions of cohesion and decohesion that the dynamics of digital capitalism—and the future of value itself—must be understood.

At the heart of classical Marxism lies the labor theory of value, a principle that sought to uncover the hidden mechanics of capitalist production. According to Marx, the value of a commodity is determined not by its individual uniqueness or the subjective desires it may satisfy, but by the socially necessary labor time required to produce it. In other words, the measure of value is rooted in the average amount of labor that society, under given historical and technological conditions, must expend to bring forth a commodity. This concept stripped away the illusions of market price and revealed the real foundation of exchange in the material expenditure of human energy.

From this foundation flows Marx’s central insight into exploitation: the generation of surplus value. Workers, compelled to sell their labor power in order to survive, produce more than what they receive in wages. A portion of their labor time goes unpaid, appropriated by the capitalist as profit. This unpaid labor is the essence of exploitation, and it is systematically embedded in the structure of the capitalist mode of production. Unlike theories that see profit as the result of ingenuity, thrift, or risk-taking, Marx’s analysis shows it to be the outcome of a structural asymmetry between labor and capital.

In this way, commodities themselves become more than material goods for consumption. They are congealed abstract labor—crystallizations of human activity alienated from the workers who performed it. Each commodity carries within it the silent trace of exploitation, making value not only measurable but also a map of class domination. Through the movement of commodities and money, the hidden exploitation of workers becomes normalized and masked by the appearance of free exchange.

This framework was extraordinarily effective in the industrial age, where commodities were tangible and the link between labor and value was visibly traceable in the factory system. A textile mill, a steel foundry, or a car assembly line made clear how labor was harnessed to generate both use-value and surplus value. Yet, in the twenty-first century, the terrain of capital accumulation has shifted. Value is no longer confined to the factory floor; it extends into the mining of subjective existence itself. Today, clicks, online interactions, personal preferences, and even unconscious behavioral patterns are harvested, processed, and sold as commodities. The critical question that arises is whether Marx’s labor theory of value can still operate as a guiding framework in this new context where capital thrives not merely on physical production, but on the continuous extraction of life’s digital residues.

The rise of data as a central commodity of digital capitalism introduces a profound paradox. Unlike material goods, which are bound by scarcity and require costly reproduction, data possesses the peculiar quality of infinite reproducibility. A single dataset, once captured, can be copied, shared, and transmitted across countless servers at virtually no cost. The traditional logic of commodities, where scarcity underpins exchange value, is thus unsettled. Data’s ability to multiply endlessly without depletion undermines the very foundation on which capitalist markets are supposed to rest. To maintain its status as a commodity, capital must artificially impose scarcity—through legal protections, intellectual property rights, and the enclosure of digital infrastructures. This contradiction reveals data’s ambiguous nature: at once abundant and enclosed, open in its essence but privatized in its form.

A second paradox arises from the indeterminacy of labor time embedded in data production. Unlike the industrial worker whose labor is visibly directed toward manufacturing a product, the “producers” of data often have no awareness that they are laboring at all. Users casually posting on social media, patients providing health information during a medical check-up, or employees leaving behind digital traces in the course of their daily work—each of these acts generates raw material for capitalist accumulation. Yet none of them is conventionally recognized as labor, nor is their contribution measured in terms of socially necessary labor time. The invisibility of labor in the digital domain obscures exploitation, rendering value extraction diffuse and disguised as voluntary participation in digital life.

The paradox deepens with platform mediation, where the commodity form of data does not emerge from any isolated act of production but from the aggregation, processing, and monetization of countless dispersed activities. It is not the single click, the lone search, or the individual post that holds value in itself, but the recombination of millions of such fragments into coherent datasets. Algorithms organize and interpret this raw material, converting it into predictive models, targeted advertising systems, or surveillance tools. In this sense, platforms function as the true factories of digital capitalism, not producing material goods but synthesizing the scattered residues of everyday life into commodifiable intelligence.

Thus, while the use-value of data is evident—enabling targeted marketing, surveillance architectures, or predictive analytics—the value-form of data remains obscure. Where exactly is labor congealed in this process? Is it in the hidden, unconscious contributions of users, in the programming and maintenance of algorithms, or in the massive infrastructures that sustain data processing? The contradiction of data commodities lies precisely in this ambiguity: value undeniably emerges, yet its origins are dispersed, concealed, and refracted through the opaque machinery of platform capitalism.

The contradictions of data commodities become clearer when approached through the lens of Quantum Dialectics, which allows us to see value not as a static property but as a dynamic interplay of cohesive and decohesive forces across different layers of reality. From this perspective, the data economy can be understood as a quantum field in which fragments of labor, scattered traces of human activity, and algorithmic processes interact dialectically to generate new forms of value.

To begin with, data may be seen as decohesed fragments of labor. Every click on a website, every search query, every GPS signal emitted by a smartphone is a tiny residue of human activity. Taken in isolation, these signals are meaningless: a click without context reveals nothing, a GPS ping by itself has no intrinsic value. They represent labor in its most dispersed and fragmented state—decohered into micro-signals detached from any immediately recognizable commodity form. In traditional industrial capitalism, labor was congealed visibly in the finished product of the factory. In digital capitalism, however, labor disperses into uncountable digital traces, stripped of context and meaning until capital reassembles them.

Here, capital functions as the cohesive force, intervening to bind together what is otherwise scattered and insignificant. Through vast computational infrastructures, platforms collect, aggregate, and recombine the fragmented residues of human life. The billions of clicks, searches, and behavioral traces are pulled into coherence as structured datasets, consumer profiles, and predictive models. Algorithms and machine learning techniques act as the machinery of cohesion, transforming dispersed fragments into commodities that can be bought and sold. In this sense, the platform becomes the new “factory,” not of material goods but of informational coherence.

What emerges from this process is not value traceable to any single act but an emergent property of aggregation. The commodity form of data does not exist in a solitary click or an isolated transaction. Rather, it crystallizes in the emergent structure produced when countless fragments are gathered, processed, and algorithmically shaped into patterns, correlations, and predictions. Value here is layered and systemic: it arises not from the parts in isolation but from their recombination into wholes that serve capital’s imperatives of control, profit, and surveillance. Just as matter at the quantum level exhibits properties not reducible to its individual particles, so too does data acquire value only in its aggregated, systematized form.

This entire process is underpinned by the contradiction of enclosure versus openness, a contradiction at the heart of digital capitalism. On one side, data is inherently non-rival—it can be infinitely copied, shared, and circulated without depletion. On the other side, capital must impose artificial enclosures to transform it into a commodity: patents, intellectual property rights, platform monopolies, and paywalls act as mechanisms of cohesion that restrict access and preserve scarcity. This tension between openness and enclosure is the very manifestation of the cohesion–decohesion dynamic in the data economy. It ensures that while data flows are constantly proliferating and escaping control, capital simultaneously tightens its grip to monetize them.

From a quantum dialectical perspective, then, data is not simply an immaterial good but a battlefield where dispersed human activity is continuously pulled into coherence by capital, generating emergent value under conditions of contradiction. Digital capitalism thrives precisely because of this unstable equilibrium, an equilibrium that both enables profit and sows the seeds of its eventual transformation.

If Marx’s principle that value is rooted in labor is to be preserved in the digital age, it must be dialectically extended to account for the new forms of labor that underlie data commodification. In industrial capitalism, labor was concentrated and visible in the factory, the mine, or the field. In digital capitalism, however, labor disperses across multiple quantum layers of activity—some overt and measurable, others hidden and barely recognizable as labor at all. The challenge, then, is to map these forms of labor and reveal how they are woven into the production of value in the data economy.

The most obvious layer is direct labor, carried out by those who design, sustain, and regulate digital infrastructures. Programmers writing code, data scientists developing algorithms, content moderators filtering toxic material, and gig workers tagging images or transcribing audio all provide indispensable contributions to the functioning of platforms. Their labor is closer to the classical industrial model: it is conscious, contractual, and often waged, even if under conditions of precarity and overexploitation. Without this visible workforce, the data economy could not function, for the “immaterial” flows of information rely on material acts of maintenance, correction, and continuous improvement.

A second, less visible layer consists of indirect labor, carried out not in workplaces but in the ordinary rhythms of daily life. Users generating content on social media, patients handing over genetic or health data, consumers leaving behind trails of online searches or purchase histories—all are contributing to the accumulation of data capital. This has been described by theorists like Christian Fuchs as prosumer labor: a hybrid form in which people simultaneously produce and consume, unaware that their everyday digital participation generates raw material for commodification. Unlike the factory worker, these “workers” are unpaid and unrecognized, yet their contributions are essential to the extraction of surplus value in the digital sphere. The casual click, the routine swipe, and the unconscious data trail become, once aggregated, the lifeblood of platform accumulation.

A third and novel dimension is algorithmic labor. Machine learning systems appear autonomous, generating translations, recommendations, or predictive analytics with no human intervention. Yet this autonomy is only apparent. Behind every algorithm stand immense quantities of human-labeled data, painstakingly curated, annotated, and corrected by armies of workers. These invisible labors ensure that algorithms “learn” correctly and continue to function. Moreover, the maintenance of algorithmic systems—debugging, retraining, and refining—is itself an ongoing process of human labor. Thus, even the most advanced forms of artificial intelligence remain parasitic on vast reservoirs of human activity, both past and present.

Taken together, these layers illustrate that value still originates in labor, but it is now dispersed, hidden, and reassembled across the quantum layers of digital capitalism. The commodification of data does not abolish labor; instead, it mystifies it. What appears as an immaterial and spontaneous flow of information is in fact structured by the invisible expenditure of human effort at multiple levels. Labor has not disappeared—it has been displaced, fragmented, and concealed behind the surface appearance of seamless digital exchange. The task of critique, then, is to bring these obscured labors back into visibility, thereby reasserting Marx’s insight that exploitation remains the true motor of capitalist accumulation, even in the age of data.

In the classical industrial age, the extraction of surplus value was most visible at the point of production. Workers on the factory floor produced more than what was returned to them in wages, and this excess—appropriated by the capitalist—was the source of profit. The dynamics of exploitation could be traced directly from labor time to surplus value, making the relationship between labor and capital relatively transparent, even if mystified by the circulation of commodities in the market.

In the data-driven economy, however, surplus extraction assumes a more elusive form. Platforms no longer rely solely on the exploitation of waged labor but instead harvest what Shoshana Zuboff has termed surplus behavioral value. By monitoring, predicting, and ultimately shaping user conduct, platforms transform the minutiae of everyday life into a reservoir of monetizable insights. The sale of targeted advertising, the manipulation of consumption habits, and the predictive modeling of social behaviors all exemplify how surplus is extracted not merely from production but from the appropriation of human behavior itself. In this way, life becomes labor, and subjectivity itself is drawn into the circuits of capital.

This process culminates in what may be described as data rent—a distinctive form of appropriation unique to digital capitalism. Unlike industrial capitalists, who profited from the direct exploitation of labor in production, today’s platform monopolies—Google, Meta, Amazon, and others—profit by controlling access to digital infrastructures. They enclose the digital commons, impose tolls on participation, and demand tribute from all who wish to navigate their ecosystems. The profits they secure are not derived only from the surplus labor of employees or prosumers, but from their strategic position as gatekeepers of informational flows. Data rent, therefore, represents a higher-order appropriation, dependent on the monopolization of infrastructure itself.

From a quantum dialectical perspective, data rent can be understood as the cohesive crystallization of dispersed surplus fragments into monopolistic power. The scattered residues of labor—user data, algorithmic inputs, and behavioral traces—are decohered across billions of individuals. Platforms act as the cohesive force, pulling these fragments together into a structured system that enables extraction on a planetary scale. Rent is thus the emergent form of cohesion, a structural lock-in that allows platforms to capture value across multiple layers of digital life.

Here lies the continuity with Marx’s analysis. Surplus value remains the motor of capitalism, the hidden lever driving accumulation and inequality. What has changed is not the principle but the appearance form. The site of exploitation has shifted: no longer confined to the factory floor, it now resides in the server farm, the data center, and the algorithmic

The world of data capitalism is sustained not by seamless harmony but by a set of profound and unresolved contradictions. These contradictions mirror the tensions Marx identified in industrial capitalism but ubbnfold in new forms at the digital quantum layer of accumulation. They are not mere anomalies but the very forces that drive the evolution of this system, revealing both its power and its instability.

The first contradiction lies in the distinction between productive and unproductive labor. At first glance, user activity—scrolling through feeds, clicking on links, or uploading photos—seems unproductive, mere leisure rather than labor. Yet once these scattered actions are captured, aggregated, and processed by platforms, they are transformed into raw material for profit generation. Dialectically, user data is both unproductive in its isolated form and productive once subsumed under capital’s machinery of recombination. This ambiguity exemplifies the mystification of labor in digital capitalism: value is created, but the locus of production is obscured.

A second contradiction emerges in the tension between private appropriation and collective production. The production of data is inherently collective, generated by billions of users across the globe in the course of their everyday lives. Yet the value extracted from this collective activity is privately appropriated by a handful of monopolistic corporations. The wealth of the many becomes the property of the few, not through direct exploitation in a shared workplace but through the asymmetry of ownership over digital infrastructures. This contradiction exposes the parasitic nature of platform capital: its profits rest on enclosing what humanity produces collectively.

A third contradiction arises in the struggle between openness and enclosure. By nature, data is non-rival: it can be copied infinitely without depletion, shared without loss, and circulated without scarcity. This quality should make data an abundant commons. Yet capitalism thrives on scarcity, and to preserve its profitability, it imposes artificial enclosures through patents, intellectual property rights, platform monopolies, and restrictive architectures. The non-rival character of data constantly undermines these enclosures, while capital invents new barriers to preserve exclusivity. This ceaseless tug-of-war is the cohesion–decohesion dynamic of digital capitalism itself.

Finally, there is the contradiction between automation and labor dependence. The ideology of artificial intelligence presents a vision of autonomy, where machines supposedly free humanity from the drudgery of labor. Yet beneath this appearance lies a vast hidden infrastructure of human work: annotators labeling data, moderators policing content, engineers refining algorithms, and gig workers maintaining the “seams” of automation. AI systems remain profoundly dependent on continuous human input, revealing that even the most advanced technologies of automation are inseparable from exploitation. The more capital seeks to eliminate labor, the more it becomes dependent on new, often invisible forms of it.

Taken together, these contradictions are not marginal tensions but quantum dialectical forces that propel digital capitalism forward while simultaneously destabilizing it. Each contradiction embodies the interplay of cohesion and decohesion, integration and rupture, that defines the digital age. And as with every historical stage of capitalism, these contradictions point not toward equilibrium but toward crisis and transformation—toward the possibility of new social forms that could transcend the exploitative logic of commodified data.

From the standpoint of Quantum Dialectics, the commodification of data must be understood not as the final resting place of capitalist value but as a transitional phase in the evolution of social relations. At present, the forces of cohesion—platform monopolies, intellectual property regimes, and digital enclosures—strive to stabilize accumulation by locking human life into systems of surveillance and rent extraction. Yet these cohesive forces are continually undermined by countervailing movements of decohesion: open-source initiatives that resist privatization, digital commons projects that reclaim knowledge as collective wealth, emerging data unions that demand ownership and compensation for user contributions, and widespread resistance to the totalizing gaze of surveillance capital. Out of this tension, a higher synthesis begins to take shape. It points toward the possibility of a new regime of value, one no longer organized around the private commodification of data but around its collective control as a social commons. In such a system, data would cease to function as an instrument of exploitation and instead serve as a foundation for cooperative knowledge, democratic planning, and shared human flourishing. The revolutionary potential of the present moment, therefore, lies in transforming the very ontology of value—moving from the alienated capture of digital life to the conscious socialization of the quantum layer of existence. This would not merely reform digital capitalism but inaugurate a new stage in the historical dialectic, where humanity collectively reclaims the power embedded in its own digital traces.

Marx’s labor theory of value, when reinterpreted through the lens of Quantum Dialectics, reveals itself to be not an outdated relic of the industrial age but a framework that is more relevant than ever in the era of data commodification. Far from existing outside the domain of labor, data is in fact a new expression of labor’s dispersion and reconfiguration. Each fragment of digital life—clicks, movements, interactions, traces of thought—represents labor in its decohered form: scattered, unconscious, and seemingly immaterial. Capital, acting as a cohesive force, gathers these dispersed fragments, recombines them through platforms and algorithms, and crystallizes them into commodities that can be monetized. Thus, data is not the negation of Marx’s principle but its dialectical extension: labor persists as the hidden substance of value, though refracted through more complex, layered, and mystified forms.

The contradictions inherent in this process mirror the very motor of historical change. On one side lies the tendency toward openness, reflecting the boundless, non-rival nature of data as something that can be infinitely shared and reproduced. On the other side stands enclosure, the attempt by capital to impose artificial scarcity through monopolies, patents, and restrictive infrastructures. Likewise, while the production of data is inherently collective, generated by billions of interconnected individuals across the globe, its appropriation remains private, concentrated in the hands of a few corporations that dominate digital infrastructures. These tensions are not accidental frictions; they are the dialectical forces that propel digital capitalism forward, while simultaneously generating the conditions for its possible transcendence.

The task of our time, therefore, is to expand our understanding of value beyond its narrow economic definition and recognize it as a quantum dialectical process of cohesion and decohesion. Value is not a static quantity but an emergent property of dynamic contradictions—an interplay of forces that binds and disperses labor, stabilizes and destabilizes accumulation, encloses and liberates human creativity. To grasp value in this way is to see beyond its current capitalist form, where data is alienated and commodified, toward its potential as a foundation for new social arrangements. Here lies the promise of collective emancipation: by reclaiming control over the quantum layer of digital life, humanity can transform value from a mechanism of exploitation into a source of shared empowerment, opening the path toward a higher synthesis in which the fruits of collective labor are collectively owned.