How AI Interviews Are Changing Candidate Behavior
Many people say the scariest part of job hunting is answering the classic, “Tell me about yourself.” That moment has traditionally been a human‑to‑human interaction, but now some companies are handing it off to their AI interview systems.
Imagine having to deliver that same answer not to a person sitting across from you, but to an AI agent on your laptop, knowing its algorithm may be analyzing every blink, pause, and word choice. A growing number of fresh job seekers are experiencing this, and a new study on the Information Systems Research site shows it’s changing how candidates behave in ways one might not expect.
The study was conducted by Akshat Lakhiwal of the University of Georgia’s Terry College of Business, along with co‑authors Che‑Wei Liu (Arizona State University), Hillol Bala (Indiana University), and Hung‑Yue Suen (National Taiwan Normal University). They surveyed hundreds of online job seekers using behavioral coding of video responses, and comparisons between AI and human evaluators, looking to capture both what candidates say they do and what they actually do on camera.
“If you’re applying for a job at your dream company and your dream company wants to interview you using AI, you really don’t have a lot of choice… but you also don’t know how it works,” says Lakhiwal.
AI DOESN’T CATCH EXAGGERATION
What the researchers found is that when candidates knew their one‑way video interview would be evaluated by AI, they were significantly more likely to exaggerate or embellish their qualifications. These were one‑way interviews where applicants record answers to prompts like “Why should we hire you?”
The uncertainty seems to push people into performance mode. Lakhiwal says candidates throw the kitchen sink at the situation, overselling skills, inflating achievements, and trying to reverse‑engineer what the algorithm might reward. Oddly enough, the AI didn’t penalize them.
The industry‑favored AI agent used in the study rated exaggerators just as highly as candidates who genuinely possessed the qualifications they described.
Human evaluators, however, immediately picked up on the embellishments and rated authentic candidates higher. What this alludes to is that AI may be fast, but it’s not great at detecting when someone is stretching the truth.
In a recent Forbes piece by workplace‑law scholar Michelle Travis, she warns about the biases that come with this. “AI hiring tools are not merely passive mirrors of human social biases, but can actively create new ones from experience.”
TRANSPARENCY MAY BE THE KEY
The researchers also took this another step, and they tested a fix through another experiment. In their experiment, the group of candidates was told not only that AI would review their videos, but how it would do so. They learned the system looked for facial expressions, verbal sentiment, keywords, and rated them on teamwork, job‑related abilities, work style, and personality. That small dose of transparency changed everything.
“Telling applicants more about the process allows them to be more authentic,” shares Lakhiwal. “We’re advocating transparency in terms of someone’s ability to understand the process. I don’t really need to know which model they are using to analyze my video, but as a candidate, what matters is to be able to make sense of the process the same way I understand what it means to be interviewed by a human.”
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