Worker surveillance is the monitoring of employees through cameras, sensors, software logs, wearables, or AI systems. In safety settings it may be justified to detect hazards, but it becomes a cyber-security and privacy risk when collection is broader than needed, poorly explained, or difficult to stop. If an organization cannot say exactly what is being observed, who can access it, and how long data is kept, the system is too expansive for a legitimate safety purpose.
In real environments, worker-surveillance tools often sit inside connected dashboards and alert systems, which makes them part of the attack surface. An attacker who steals credentials, alters sensor feeds, or changes alert logic can create false confidence or hide unsafe behavior. Defenders reduce this risk with data minimization, role-based access, strong logging, retention limits, and human review of automated alerts. The key control is proportionality: monitoring should support protection, not become a covert profiling system.