You cannot reliably tell from one answer whether a candidate used AI. A polished response, a pause, or a change in speaking style is not proof. Treat a concern as a reason to ask a neutral, job-related follow-up, then assess the candidate’s understanding and experience using consistent questions and other evidence.
What signs might suggest AI use—and what do they prove?
Possible warning signs can justify checking an answer, but none establishes on its own that AI was used. The Canadian federal Public Service Commission lists cues including a sharp difference in style or detail between answers, generic or irrelevant responses, fake citations, experience claims that conflict with a work history, and descriptions of personal experience in the third person. In prerecorded video, apparent script reading may also raise a question. The Commission explicitly describes these as signs, not proof; its guidance applies to the Canadian federal public service, not every employer or jurisdiction (Public Service Commission of Canada guidance).
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Do not treat a candidate’s accent, eye movement, nervousness, pause, polished vocabulary, or a single change in style as a reliable AI indicator. The reviewed guidance does not establish these behaviors as diagnostic. They can have many explanations unrelated to AI.
Can you tell if someone is using ChatGPT in an interview?
Not with certainty from the answer alone. AI-assisted responses can sound polished and score well on content without making the speaker’s delivery distinguishable. In a preregistered experiment, 245 participants completed asynchronous video interviews under control, verbatim-ChatGPT, or personalized-ChatGPT conditions. The AI groups received higher overall and content scores than the control, while delivery scores did not differ; the AI groups received lower honesty ratings. Those results describe that particular prerecorded-video experiment, not a validated way to detect AI in live remote interviews (Canagasuriam et al., 2025).
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The study authors interpreted the lower honesty ratings as suggesting that some AI use—especially reading responses verbatim—might be identified with some accuracy. That is an interpretation of experimental results, not proof that interviewers can reliably identify AI use in real hiring or across roles.
Other studies have examined different settings, including virtual medical-school admissions interviews and U.S. pre-hire assessments. Their results should not be treated as estimates of how often candidates use AI in live job interviews. A U.S. operational assessment study, for example, measured self-reported GenAI use in assessments, not live interviews; it does not establish a universal interview-use rate (Robie et al., 2026).
What should you ask when an answer sounds AI-generated?
Use a follow-up to check the candidate’s reasoning, personal contribution, and ability to apply knowledge—not to spring a trick question or demand a confession. Ask the same core questions and use the same scoring criteria for candidates applying to the same role.
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- “What part of that work did you personally own?”
- “What trade-off led you to that decision?”
- “Can you walk me through how you reached that result?”
- “If this new constraint applied, what would you change?”
Choose the question that fits the answer and the job. For a claimed project, ask about the candidate’s specific role, decisions, and outcome. For a technical or situational answer, introduce a realistic new constraint and ask how it changes the approach. A useful follow-up gives the candidate a fair chance to show understanding; it is not a test of whether they can improvise under pressure.
How should you verify the candidate’s qualifications?
Evaluate the answer alongside the rest of the hiring evidence instead of making an adverse decision from one interview impression. The Canadian Public Service Commission recommends interviews, reference questions, and scenarios as ways to confirm that qualifications belong to the candidate rather than being AI-generated information. Apply these methods consistently and keep them relevant to the role.
- Compare specific claims with the candidate’s work history and other assessment results.
- Use structured questions and consistent scoring rather than relying on an interviewer’s general impression.
- Where appropriate, ask references about the candidate’s responsibilities and contributions.
- Record the concrete inconsistency or follow-up and the candidate’s response, not assumptions about mannerisms.
Use judgment about what an assessment can establish: a strong response to a new scenario can demonstrate current understanding, while a reference or work-history check can help corroborate a past claim. No single method answers every question about authorship.
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Should you use an AI detector?
Do not use a detector score as decisive evidence that a candidate used AI. The Canadian Public Service Commission warns that detector reliability may be questionable and that false positives can seriously affect candidates. The asynchronous-video study also notes that text detectors were designed for writing, not spoken video answers, and that accurately classifying interview transcripts is uncertain. A transcript detector result is therefore not a dependable shortcut to establishing who produced an answer.
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Decide what the assessment is meant to measure and communicate the rules before candidates take part. If responsible AI use is relevant to the job, it may be more useful to assess that skill directly than to treat every use as misconduct. If the assessment is intended to measure unaided ability, say so clearly.
Specify which tools and stages are covered, including preparation, live interviews, and take-home tasks; whether candidates must disclose AI-generated content; and how suspected rule breaches will be handled. Apply the same standard to everyone. Consider fairness as well: candidates may differ in access to paid tools, equipment, language support, and technical knowledge. These policy recommendations come from Canadian federal public-service guidance and should not be mistaken for universal legal requirements.
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If a possible breach arises, follow the process you announced and the policy that applies in your jurisdiction. The Canadian federal guidance discusses case-by-case reassessment and investigation in its own public-service context; it is not a universal procedure for private employers or other governments. Avoid an automated accusation or adverse decision based only on a detector score.
Does changing the interview format solve the problem?
A virtual medical-school admissions experiment tested a modified multiple mini-interview format that removed isolated preparation time and had an examiner read the prompt aloud. In that study, the ChatGPT group performed worse than both control groups under the modified timing, while there was no statistically significant difference in the standard timing condition. The modified format also appeared to reduce rating consistency. This is a finding from a medical-school admissions setting, not a general recommendation or proven fix for remote job interviews (Virtual MMI study, 2025).
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