Mass surveillance did not arrive as an attack against the open internet. Instead, it emerged as the careless outcome of a business model that treated personal data as the cheapest raw material in the digital economy. As the largest technology companies realized they could monetize not only what people do but who they are, what they fear, and how they can be influenced, the line between “personalization” and surveillance began to dissolve, setting the stage for broader surveillance practices.
From convenience to tracking
The first turning point came when “free” services became the main way to access the internet. Search, email, social networking, and cloud storage cost nothing, but users pay invisibly as their behavioral data flows into corporate data centers. Every click, like, location ping, and purchase became what Shoshana Zuboff later called “behavioral surplus”, defined as data collected beyond what was needed to provide the service and used to predict and influence behavior.
The mobile era intensified this. Smartphones act as constant sensors, recording detailed location, contact, and app usage data. Developers integrated third-party analytics and ad SDKs, letting a few platforms monitor activity across many apps and sites. Web tracking grew into cross-device, real-time profiling, reconstructing daily routines with precision.
Surveillance as a business model
At scale, this data system created surveillance capitalism: human experience became material for extraction, analysis, and profit. The more data gathered, the better platforms can target ads and fine-tune engagement. This feedback loop lets cloud platforms not only predict but shape behavior by controlling digital spaces. The more users felt understood, the more they shared.
Big tech’s AI investments deepened this model as modern machine learning demands more data. Promises of improved recommendations and automated moderation justified intensive collection across devices and spaces. As algorithms advanced, they enabled new predictive products, each of which increased the incentive for more granular data.
Public space under digital watch
Unfortunately, mass surveillance is no longer limited to browser windows and news feeds. Cameras, sensors, and biometric systems now turn public spaces into sources of behavioral surplus. Computer vision and facial recognition allow computers to identify individuals in crowds, track their movements across locations, and match those movements with online profiles and communication patterns. This shift occurred as storage prices fell and cloud platforms enabled real-time analysis of video and sensor data, removing financial and technical barriers to large-scale surveillance.
Authoritarian regimes show this starkly. In China, dense surveillance, AI, and data platforms enable authorities to monitor, track, and link physical presence to online activity. The global tech firms leading commercial digital markets also provide cloud analytics, social monitoring, and biometric tools powering state surveillance. The boundary between corporate tools and state capabilities blurs when governments adopt systems built for ads or platform safety.
The state–corporate surveillance loop
Unfortunately, the mass surveillance with commercial components highlights the symbiotic relationship between big tech and governments. On the one hand, public agencies rely on large platforms for communication, identity verification, and critical infrastructure. On the other hand, law enforcement and intelligence services gain access to troves of data collected under the banner of user convenience through legal processes, back-channel arrangements, or commercial contracts. Where traditional surveillance required targeted warrants and resource‑intensive operations, today’s data flows enable authorities to search, filter, and mine historical records on millions of people with a few queries.
Spyware scandals show the most invasive side. Tools like Pegasus turn smartphones into surveillance devices, activating microphones and cameras and secretly extracting data. Though often justified as anti-terror tools, such software often targets journalists and critics. The same optimized mobile platforms now make covert spying easy, exposing personal and professional lives to intruders.
Systemic risk and shrinking autonomy
This convergence of commercial and government surveillance creates systemic digital risk beyond individual privacy breaches. Societies become dependent on centralized, opaque infrastructure, making them vulnerable to widespread impact from breaches, misuse, or policy shifts in a few key companies.
The human cost is subtler yet widespread. Constant monitoring breeds self-censorship, stifling free exploration of ideas and identities. Philosopher Carissa Véliz suggests that privacy is more than personal. Instead, it is the foundation of dignity. Normalized surveillance shifts the default from “unobserved” to “tracked,” often without real consent.
Reclaiming agency in a surveilled world
Reversing these dynamics will not happen through individual app settings alone, as the scale and integration of modern surveillance demand structural solutions. We must minimize data collection, limit integration, and require monopolies to be interoperable with less-invasive alternatives. Although governments and regulators have begun pushing back through privacy laws and competition cases, these efforts must recognize that public institutions remain major consumers of the very infrastructure they aim to restrain. This internal conflict complicates reform.
Enterprises and citizens must prioritize surveillance risk. Critically assess reliance on single vendors, demand transparency, and align technology choices with democratic values. Surveillance grew from the alignment of technical possibilities, commercial incentives, and political inaction; resisting it requires deliberate strategy, regulation, and civic action.
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