Short answer: Viewed unconventionally, digital surveillance can be read as a social mirror—revealing and shaping power relations, norms, and identities rather than just collecting data. It performs classification and persuasion, not only observation.

Key terms

• Surveillance — systematic collection and analysis of people’s behavior or data.
• Panopticon — a metaphor for power through possible observation (Foucault).
• Sociotechnical — systems that combine social practices and technology.
• Algorithmic governance — rules enforced or suggested by automated systems.

How it works

• Sensors, logs, and platforms collect signals (clicks, location, biometrics).
• Algorithms categorize and predict behavior, producing profiles.
• Institutions act on profiles (targeting, exclusion, reward), shaping futures.
• Social norms shift as people anticipate and adapt to monitoring.
• Visibility becomes a resource: some groups are hyper-visible; others erased.

Simple example

• A city’s CCTV + facial recognition not only deters crime but redirects policing toward certain neighborhoods, reinforcing social hierarchies.

Pitfalls or nuances

• Data ≠ truth: classifications embed biases.
• Power asymmetry: those who design systems decide categories.
• Resistance and evasion change system effects.

Next questions to explore

• Who benefits from specific surveillance categories?
• How can design redistribute power or enable accountability?

Further reading / references

• Discipline and Punish — Michel Foucault (background on panopticon).
• “The Rise of Big Data Policing” — NYU Law Review search query (try: “Big Data Policing NYU Law Review Katrin Nowotny” if link unavailable).