User data collected beyond what is needed for service improvement, sold for prediction and influence
Behavioral surplus is a term coined by Shoshana Zuboff in her book "The Age of Surveillance Capitalism" (2019) to describe the data that technology companies collect from users beyond what is necessary to improve their products and services. This surplus data — capturing patterns of behavior, social connections, emotional states, physical movements, and psychological vulnerabilities — is fed into machine learning systems that produce predictions about future behavior, which are then sold to advertisers and other buyers.
Google pioneered the extraction of behavioral surplus when it discovered that the data generated by users' search queries could be used not just to improve search results but to predict what ads users would click on — and that these predictions were enormously valuable. Facebook, Amazon, and other platforms followed, building business models that depend on extracting maximum behavioral data from users while providing minimal transparency about how that data is used.
The concept of behavioral surplus connects corporate surveillance to government surveillance. The infrastructure built by technology companies to extract and analyze user behavior is precisely the infrastructure that intelligence agencies tap through programs like PRISM. The commercial incentive to collect as much data as possible about every user creates a surveillance apparatus that serves both corporate profits and government intelligence — a convergence of interests that neither entity has incentive to limit.
