Surveillance Capitalism

Surveillance capitalism is a concept that describes a form of capitalism in which data extracted from individuals’ behaviors in digital and physical environments becomes the primary input for economic value creation. The term specifically refers to the use of data collected through social media, search engines, mobile applications, and the Internet of Things (IoT) digital systems for commercial purposes such as predicting, influencing, and directing user behavior.

The concept was most comprehensively developed by social scientist Shoshana Zuboff. Zuboff treats surveillance capitalism as a new economic order and power structure based on the collection of personal data under conditions of unauthorized or asymmetric consent.

Origins and Historical Background of the Concept

Early Digital Capitalism and Data-Based Revenue Models

At the end of the 1990s and the early 2000s, with the widespread adoption of the internet, most digital services began to be offered free of charge. Search engines, email services, and later social networks developed a business model in which users did not pay directly but instead supported services through advertising revenue. In this model, users’ online behaviors—such as search queries, clicks, and browsing habits—became a valuable data source for targeted advertising.

Initially, this data was regarded as auxiliary inputs used to improve the technical functioning of services. Over time, however, the data itself came to be seen as an independent economic asset and a competitive advantage.

Surveillance Capitalism Illustration (Generated by Artificial Intelligence)

Platformization and Data Concentration

From the mid-2000s onward, the digital economy evolved into a structure known as “platformization.” Search engines, social media platforms, mobile operating systems, and app stores became infrastructures that centralized both user interactions and data flows. Companies such as Google, in particular, built massive data reservoirs thanks to their large user bases and continuous data generation.

During this process, data collection was no longer limited to online activities; it expanded into the physical world through location data, mobile app usage, sensor outputs, and later through Internet of Things (IoT) devices. As a result, individuals’ daily lives became continuous sources of data production.

The “Big Other” Article and Conceptualization

Zuboff first systematically introduced the concept of surveillance capitalism in her 2015 article titled Big Other: Surveillance Capitalism and the Prospects of an Information Civilization. In this work, she argues that big data is not merely a technical necessity but the product of a specific accumulation logic shaped by institutional and economic interests.

At the heart of the article is the claim that a new architecture of power and control has emerged through the constant monitoring, recording, and analysis of individual behavior. Zuboff defines this architecture as the “Big Other” and distinguishes it from classical totalitarian surveillance models. The Big Other operates not through a centralized authority but through distributed, algorithmic, and often invisible digital systems.

The operational assumptions of surveillance capitalism are largely based on Hal Varian’s theories of computer-mediated transactions. According to Varian, these transactions enhance economic efficiency through data extraction, the creation of new contractual forms, personalization, and continuous experimentation. Zuboff, however, characterizes this process as a form of contractual absence that eliminates market uncertainty and replaces human autonomy with “automatic obedience.”

The Discovery of Behavioral Surplus

According to Zuboff, the defining feature of surveillance capitalism is the discovery of behavioral surplus as an economic resource. Behavioral surplus refers to data traces collected from users that are not essential for the functioning of a service but are nonetheless extractable from their behavior. Over time, these data have become the primary input for products designed not only to target advertisements but also to predict and steer individuals’ future behaviors.

At this point, surveillance capitalism diverges from classical market capitalism by positioning users not merely as “customers” or “consumers,” but as a resource that continuously generates data from which value is extracted.

Book Study and Historical Depth

In her 2019 book The Age of Surveillance Capitalism, Zuboff expanded the conceptual framework introduced in her 2015 article within a historical narrative. In the book, surveillance capitalism is compared with previous economic epochs such as industrial capitalism and managerial capitalism. The author argues that this new order is not merely the result of technological innovation but is made possible by regulatory gaps, institutional interests, and political passivity.

Theoretical Framework

This system operates according to a distinct “logic of accumulation” that differs from traditional market dynamics.

Behavioral Surplus

Behavioral surplus is the fundamental raw material of surveillance capitalism. It includes users’ clicks, search histories, location movements, social interactions, and sensor outputs. This data is converted into economic value with limited user awareness or consent.

Inference Cycle

Zuboff’s described inference cycle is a four-stage process through which surveillance deepens. First, in the intrusion phase, sensors and applications penetrate users’ private non-digital spaces such as their homes, cars, or bodies. Next, in the habituation phase, users internalize these tools as indispensable parts of their lives and normalize surveillance. As the process continues, the continuous stream of collected data enables adaptation, allowing algorithms to update themselves and enhance predictive capacity. In the final stage, control, the system moves beyond passive observation and actively intervenes to modify user behavior for profit-driven purposes.

Prediction Products

Collected data is transformed into prediction products through big data analytics and machine learning techniques. These products are concrete forecasts such as “Person X has a 90 percent probability of feeling depressed on Friday evening and will be inclined to purchase Product Y.” These predictions are sold to advertisers, insurance companies, or political campaign firms.

Surveillance capitalism is not limited to Google or Facebook; it has spread throughout the entire economy. In this expansion, robotic vacuum cleaners map home layouts and infer income levels from furniture placement, while telematics devices installed in vehicles in the insurance sector monitor driver behavior in real time to determine premiums. Similarly, in health technology, smartwatches analyze pulse and sleep data to predict health conditions and emotional states.

Additionally, in gamification examples such as Pokémon Go, which Zuboff characterizes as a surveillance capitalism experiment, players chasing virtual rewards are in fact directed toward sponsored physical locations, providing a concrete example of remote behavioral manipulation for commercial purposes.

Social and Ethical Impacts

Surveillance capitalism is criticized for transforming privacy from an individual preference or personal domain issue into a structural power relation. According to Shoshana Zuboff, privacy is not entirely eliminated in this process; rather, the power to make decisions about individuals’ lives becomes concentrated in the hands of surveillance actors who possess the capacity to collect and process data.

Moreover, it is argued that algorithmic targeting, personalized content ranking, and micro-targeting practices have fragmented public discourse, weakened a shared information foundation, and negatively affected democratic processes. It is also claimed that data-driven scoring mechanisms may reproduce existing social inequalities in areas such as credit, employment, and insurance, and increase the risk of discrimination against specific groups.

Regulation and Alternative Approaches

Regulatory debates concerning surveillance capitalism focus on protecting personal data, increasing transparency of algorithmic systems, and monitoring the social impacts of digital platforms. Within this framework, data protection legislation, platform accountability, competition law tools, and privacy-enhancing technologies are among the most common policy proposals. Internationally, regulations developed particularly by the European Union stand out as legal efforts to construct a framework against surveillance capitalism.

In Türkiye, these debates are primarily conducted within the framework of the Law on the Protection of Personal Data (KVKK). While the KVKK establishes fundamental principles regarding the processing of personal data, it has limited impact on the data-driven business models of digital platforms, algorithmic decision-making processes, and behavioral steering practices. Therefore, academic and legal assessments argue for a more comprehensive digital governance approach that addresses the structural effects of surveillance capitalism.