Interview Proctoring
Last updated: June 30, 2026
Quick definition
Interview proctoring is the monitoring of environmental conditions during a remote interview session to detect signals of unauthorized assistance, identity substitution, or other integrity concerns that a human reviewer may wish to investigate.
How it works
A proctoring layer runs alongside the interview session and captures signals such as: whether multiple faces are detected in the camera frame, unusual background noise patterns, screen-sharing or overlay activity, or anomalous response latency that may indicate real-time coaching. These signals are not used to automatically disqualify candidates; they are surfaced to the human reviewer as contextual flags alongside the rubric scorecard and transcript. The final integrity judgment rests with the human.
What interview proctoring does not do
Modern interview proctoring is not a polygraph and is not designed to detect deception in answers. It monitors environment and identity signals, not the truthfulness of the candidate's stated experience. Rubric scoring evaluates the quality and specificity of behavioral evidence, which is a separate measure from proctoring.
Proctoring and fairness
Proctoring carries a risk of disparate impact if signals are not interpreted carefully. Candidates in noisy households, with variable internet, or in environments where family members are present may trigger flags that have nothing to do with integrity. Best-practice proctoring systems surface contextual signals rather than making automated disqualification decisions, and require a human to review each flag in context.
EU AI Act and proctoring
Under the EU AI Act, AI systems used in hiring contexts that make consequential decisions are classified as high-risk. Proctoring systems used in candidate assessment fall within this scope. Deployers must maintain a mechanism for candidates to request a human review of any decision influenced by AI proctoring output.