Should workers be paid for the data they produce at work?

When you clock in at your company using an app, when your tasks are logged to calculate your productivity, or when an algorithm determines your next shift or delivery route, you are generating data. This data is not just used to control and organize your work but is also transformed into economic value. Many companies optimize processes, make strategic decisions, or develop new products thanks to this information that you, as an employee, have produced. But this contribution goes beyond the tasks for which you were hired. So, should you be compensated for this data in addition to your regular salary? 

The question of data ownership and monetization in the workplace has been the focus of much of the work of María Luz Rodríguez Fernández, Professor of Labor Law and Social Security at the University of Castilla-La Mancha. She recently participated in the launch event of DigitalWORK, a research project led by Anna Ginès, professor at Esade Law School and director of the Institute of Labor Studies. The project is aimed at studying and promoting a fair, equitable, and transparent digitalization of work. 

Informational capitalism: data as a source of wealth

In the era of “informational capitalism”, data is no longer just another tool for companies. The production system is increasingly based on capturing and analyzing data to create value. While some call data “the new raw material,” other experts offer a more nuanced view, seeing it as “the new capital” of corporations. In any case, Rodríguez emphasizes that “data by itself tells us nothing; what matters for the production process is the information that can be extracted from that data.” 

In addition to producing data as consumers, we also produce it in the workplace, often under constant monitoring

Platform work, born in this new paradigm, is no longer its sole representative. Today, more than 50% of large companies admit to using data and algorithms to organize work, according to Rodríguez. We are already familiar with the idea that digital economy consumers generate data — for example, on social media, where we get free access in exchange for becoming a product for advertising. However, we also produce data at work, often under constant monitoring. 

“Why is it that something that is apparently ours doesn’t—at least partially—benefit the ‘producers’ of that data?”, Rodríguez asks. Although there are few evaluations and it’s hard to estimate, some studies place the value generated by companies from these data at 197.7 billion dollars in the US in 2022 — a figure that has been steadily rising. 

Who owns the data?

Determining who owns the data is no easy task. To begin with, not all data is the same. Some data — such as genetic or biometric data — are closely linked to personal identity, raising serious ethical and legal questions. Others stem from our behavior and are easier to capture and exploit without our conscious control, and it’s not even clear that they belong to us individually. 

Data are social facts; it’s not easy to attribute them to a single owner

Most data are not valuable in themselves but in their aggregation and processing. “They are social facts,” as Rodríguez says, rather than individual ones. For example, who owns a conversation between two people, or an interaction with an entire collective system? Who owns the data if it only makes sense when combined with thousands of other data points? These questions have led some authors to argue that data do not belong to anyone but are a common good. 

Capital, labor, or intellectual property?

These difficulties in defining the nature of data are also present in the production system. In her research, Rodríguez has identified two main theories: one that views data as company “capital” and another that considers it as workers’ “labor.” In the first case, redistribution of the generated value could come through taxes on companies; in the second, data production would have to be recognized as work and remunerated as such. 

However, Rodríguez is skeptical about this latter view. Turning constant data generation into work would reinforce the logic of precarity that already accompanies much of the digital economy. “What kind of labor market would we be building, based on millions of people producing data in precarious, invisible, informal, and unprotected jobs?” she asks. Moreover, normalizing it as just another job would incentivize even greater surveillance of life, especially among vulnerable people who might see generating and selling their data as their only source of income. 

Consent to share personal data often occurs in an asymmetric relationship

Another option, also problematic, is to recognize an intellectual property right over the data. This perspective shifts the dilemma of its exploitation to the issue of consent. But how many times a day do we agree to share information online without reading the terms and conditions? Even more so, how valid can consent be in an employment relationship, where there is a power imbalance between employer and worker? We might end up consenting to the exploitation of our data just to keep our jobs. 

Moreover, Rodríguez warns that recognizing this right to individual ownership and compensation means accepting and legitimizing constant monitoring, supervision, and data capture. We would lose the opportunity to collectively question which data are truly necessary to capture and which are not. By itself, the ownership system could lead to the commodification of a significant part of our lives, with all the ethical dilemmas that entails. 

From property rights to collective bargaining

Despite its limitations, Rodríguez starts from a critical acceptance of data as intellectual property to propose her solution. “Even if we can’t decide exactly whose data it is, we need to locate its origin,” she points out. Taken in isolation, a piece of data might not mean much, but without that initial data, the entire value creation process would not exist. And in the workplace, its origin is the workers. 

Therefore, she proposes a third path: recognizing the economic value of the data generated in the workplace and distributing its benefits through collective bargaining. This mechanism would allow data ownership to be compensated without necessarily accepting constant monitoring and surveillance. 

Collective bargaining not only distributes the benefits of data but also helps define its governance

For her, collective bargaining is also a democratizing tool, not only to redistribute the benefits generated by exploiting the data but also to help define its governance — which data, how, and when it’s collected. Additionally, it would address many of the problems raised, from the difficulty of determining individual value to the power imbalance that often exists between workers and companies. 

Is it feasible? Currently, employment contracts allow data to be captured to monitor work performance but do not mention capturing data for pure economic exploitation. However, nothing prevents this from being addressed. Compensation to employees would not be based on salary logic — since data would not be compensated as work but as the intellectual property of the worker — so the method would resemble an economic royalty. 

Rodríguez concluded her presentation forcefully: “Data is captured without limits and used without limits in the value chain to obtain economic benefits and improve production. At the same time, millions of workers donate their data in exchange for nothing. The time has come to monetize that data, or in other words, to distribute the productivity generated by workers’ data.” 

The challenges of digital work

This debate raises a fundamental question about the future of work in the digital economy: How can we ensure that technology does not deepen inequalities but contributes to greater distributive justice? Recognizing the value of data in the workplace and deciding on it through collective mechanisms would not only compensate those who generate it but also strengthen citizens’ rights in an increasingly digital society.