What it asks for. High-risk AI systems must be designed so that natural persons can effectively oversee them during use, with the aim of preventing or minimising risks to health, safety and fundamental rights. Oversight measures are either built into the system by the provider or identified by the provider for the deployer to implement.
In practice. The people assigned to oversight must be able to understand the system's capabilities and limitations, monitor its operation, remain aware of automation bias, interpret the output correctly, decide not to use it or override or reverse its output, and stop it safely, for example with a stop button. For remote biometric identification, the article generally requires that a result be separately verified by at least two competent people before action is taken. Evidence includes oversight procedures, override records, training for reviewers and interface designs that show confidence or explanation information.
Common gaps. Oversight is often nominal: reviewers approve outputs in bulk without the time, information or authority to challenge them, and override decisions are not logged.