Toward a political economy of synthetic data: A data-intensive capitalism that is not a surveillance capitalism?

Surveillance of human subjects is how data-intensive companies obtain much of their data, yet surveillance increasingly meets with social and regulatory resistance. Data-intensive companies are thus seeking other ways to meet their data needs. This article explores one of these: the creation of synthetic data, or data produced artificially as an alternative to real-world data. I show that capital is already heavily invested in synthetic data. I argue that its appeal goes beyond circumventing surveillance to accord with a structural tendency within capitalism toward the autonomization of the circuit of capital. By severing data from human subjectivity, synthetic data contributes to the automation of the production of automation technologies like machine learning. A shift from surveillance to synthesis, I argue, has epistemological, ontological, and political economic consequences for a society increasingly structured around data-intensive capital.

Automated summary

This article explores the use of synthetic data as an alternative to surveillance for data-intensive companies. It argues that synthetic data, which is artificially produced and detached from human subjectivity, aligns with the capitalist trend of autonomization of capital circulation. The creation of synthetic data not only allows companies to bypass surveillance but also contributes to the automation of production in technologies like machine learning. The shift from surveillance to synthesis has significant epistemological, ontological, and political economic implications in a society driven by data-intensive capital.