How does AI detect cheating in video interviews?

AI cheating detection in video interviews works through trust scores: the system flags AI-assisted cheating by analyzing response patterns, screen activity, and authenticity signals during the interview.

Candidate cheating with AI is the defining hiring problem of 2026. Tools that write answers in real time are free and widely available. The interview has to assume assistance is possible and detect it, not hope it does not happen.

What gets detected

RightMatch trust scores look for signals that a response was not the candidate's own work:

Copy/paste behavior during written or spoken responses
AI-generated answers, including AI-generated or cloned interview audio
Resume duplication across applicants and identities
Location spoofing, such as IP location mismatching the claimed location
Camera-replay attacks and deepfake artifacts in the video feed
Identity verification mismatches

Each signal contributes to a trust score on the candidate's report card. Recruiters see the score alongside the interview transcript and evidence.

What it does not do

Trust scores do not use biometric surveillance. They do not auto-reject candidates. A flagged interview goes to human review. The recruiter makes the final call, with the evidence in front of them.

Why this matters now

The old defense was proctoring: lock the browser, watch the webcam. That model broke when AI assistance moved into separate devices and real-time audio. Detection has to happen in the interview itself, analyzing how the candidate responds, not just where they look.