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

• Published in: New media & society Vol. 26; no. 6; pp. 3290 - 3306
• Main Author: Steinhoff, James
• Format: Journal Article
• Language: English
• Published: London, England SAGE Publications 01.06.2024
• Subjects: automation; critical data studies; simulation; synthetic data; generative models; capitalism; surveillance; big data; machine learning; Artificial intelligence
• ISSN: 1461-4448; 1461-7315
• DOI: 10.1177/14614448221099217

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.