The Enclosure of Information: Alternative Data, Bossware, and the Societies of Control
Let’s start with a personal anecdote: I currently work as a BI developer for a procurement analytics company whose database comprises about 2% of the global GDP. This means that roughly 2% of all transactions that occur globally — every purchase, every sale — exist within the datasets we maintain and analyze. Recently, my company opened a data analyst position for a new alternative data business. The goal: to aggregate data from multiple clients, anonymize the clients (but notably, not their suppliers), and then sell this dataset to hedge funds. Investors would use this data to place bets on the stock market, leveraging insights into publicly traded suppliers.
During my interview for the position, I asked the interviewer a simple yet pressing question: How is this not insider trading? The response was a telling reflection of the contradictions embedded in modern financial capitalism. They admitted it was a tricky legal territory, but assured me that the key reason this was permissible was that the dataset was available for purchase. Because anyone with sufficient money could access it, the law considered it “public data.” In other words, legal distinctions do not hinge on accessibility in a universal sense but on accessibility within the marketplace. The boundary between legality and illegality, fairness and exploitation, is drawn not by ethical considerations but by the ability to pay.
The absurdity of this distinction reveals itself in stark terms: I, as an employee, already have access to this data. If I were to use it to train a machine learning model to predict the stock prices of publicly traded suppliers, I would go to jail for insider trading. But if a multi-millionaire purchases the very same data, builds the very same model, and executes the very same trades, it is entirely legal. The law does not ban insider trading per se; it simply transforms it into a luxury good. If I wish to turn $1,000 into $2,000 using inside information, I go to jail. If a hedge fund wishes to turn $10 million into $20 million through identical means, it is legal, because they have the ability to pay for the dataset.
This system reflects a fundamental structural injustice at the heart of what can be termed “big data capitalism.” Insider trading laws, in theory, exist to prevent unfair advantages in financial markets. However, in practice, these laws do not eliminate insider advantages; they just regulate access to them. Hedge funds are permitted to engage in practices functionally equivalent to insider trading because the information they use has been commodified. The law operates on a simple principle: information asymmetry is criminal when exercised by the poor, but profitable when exercised by the rich.
This phenomenon ties in perfectly with Marx’s concept of ‘primitive accumulation’. Marx described this process of primitive accumulation as the process wherein common lands were enclosed and made private, forcing peasants into waged labor. In the digital era, a parallel form of enclosure is taking place. Today, financial elites do not simply enclose land or labor; they enclose knowledge itself. They extract data from the productive economy — data that emerges from real transactions, from real exchanges — and sell it to the highest bidder. This data is generated collectively but appropriated privately. Just as the enclosures of the past dispossessed peasants of access to land, the enclosure of data today ensures that predictive insights remain the exclusive domain of financial elites.
Hedge funds do not produce value; they extract it from productive enterprises by exploiting information asymmetries. They do not build, create, or innovate. They merely optimize the machinery of speculation, using proprietary datasets to predict movements in the market before others can react. The result is an epistemic monopoly — an enclosure of economic foresight. Small traders, workers, and entrepreneurs operate in a field where the most valuable information is systematically locked behind financial barriers. The future, in essence, is for sale, but only to those who can afford it.
The logic of data enclosure is not confined to financial markets. It extends into the realm of labor through what has become known as “bossware.” I recently encountered a case that exemplifies the rise of a new, insidious form of workplace surveillance. A relative who works remotely was forced to install a monitoring software on their laptop. This software measured the number of clicks per second, mouse movements, and keystrokes, computing an “activity” metric that determined whether they were working hard enough. If their activity level fell below 50%, they risked disciplinary action or termination. The implication was clear: every moment of inactivity was a threat to job security. To survive, they had to feign productivity even in moments of rest.
Here, we find a striking parallel between the financialization of data and the algorithmic governance of labor. Just as hedge funds monopolize predictive insights to manipulate markets, employers use behavioral data to manipulate workers. Both cases involve the enclosure of information and its transformation into a tool of control. Where hedge funds exploit information asymmetries to accumulate capital, employers exploit surveillance asymmetries to extract as much surplus-value from workers as possible.
To further understand this phenomenon, we must make a difference between a disciplinary society and a society of control. Foucault’s Discipline and Punish analyzed the emergence of disciplinary societies, in which institutions such as prisons, schools, and factories imposed rigid structures of control. Power operated through enclosure — individuals were confined within spaces where their behavior was monitored and corrected.
Deleuze, in contrast, argued that we have moved beyond the disciplinary society into what he called the society of control. Here, power does not operate through confinement but through continuous modulation. Individuals are not merely disciplined within enclosed spaces; they are subjected to real-time adjustments in behavior through networks of surveillance and data analysis. The transition from discipline to control is the transition from fixed institutions to fluid, algorithmic governance. Deleuze would have argued that the rigid and strict codes of the disciplinary societies have been deterritorialized and replaced with the flexible axiomatics of global capitalism. This is not a purely contingent encounter, but a necessary consequence of globalization: both the literal and the metaphorical boundaries and ‘walls’ that separate social contexts are tearing down and being replaced by systems of control detached from a physical location in space. In an analogy with object-oriented-programming, we might say that objects are replaced with classes, or that particulars are replaced with universals: an axiomatic for Deleuze is like a universal empty template that can be ‘filled in’ by multiple specific particulars according to abstract rules.
The case of bossware exemplifies this shift. Workers are not explicitly ordered to work in a certain way; rather, they are nudged, coerced, and manipulated by algorithmic feedback loops. The system does not command; it modulates. The metric of 50% activity is not a fixed rule (a code) but a flexible threshold (an axiomatic) that can be raised or lowered based on real-time data. Deleuze’s insight was prophetic: we are no longer confined by walls but by flows of information that adjust our reality in ways we can neither predict nor resist.
The phenomena of alternative data and bossware can also be understood within the broader framework of what Shoshana Zuboff calls surveillance capitalism and what Yanis Varoufakis terms techno-feudalism.
Zuboff argues that contemporary capitalism has evolved into a system where human behavior itself becomes the primary commodity. Corporations do not merely predict consumer behavior; they shape it. The same logic applies to hedge funds trading on alternative data and employers using bossware. In both cases, predictive insights are not merely passive observations; they become tools of behavioral modification. Financial elites shape market behavior through predictive analytics, while employers shape workers’ behavior through algorithmic surveillance. Both forms of power rest on the extraction and enclosure of behavioral data.
Varoufakis takes this argument further, suggesting that we are witnessing the rise of techno-feudalism — a system in which digital platforms do not simply mediate economic activity but actively control it. Under techno-feudalism, platforms function as digital landlords, extracting rent from users who have no choice but to participate in their ecosystems. The enclosure of alternative data serves the same function as the enclosure of common lands in feudal societies: it concentrates power in the hands of a digital aristocracy.
If the enclosure of land led to peasant revolts, what forms of resistance might emerge against the enclosure of data? The answer is uncertain, but one thing is clear: the commodification of information serves only to reinforce class hierarchies. As financial elites manipulate alternative data for speculative gain and employers use bossware to extract ever more surplus-value, the question we must ask is not merely how to regulate these practices, but how to dismantle the very system that enables them. A society built on the enclosure of knowledge is not a free society. It is a society of control, and it is time to resist.
