- Companies are adopting AI job interview systems to handle incoming applicants.
- LLMs allow the interviewer to incorporate follow-up questions based on the subject’s response.
- Critics say the opaque models raise serious concerns about bias, particularly where there is no documentation about how a decision is made.
When Floria Tan applied for an internship at China’s food delivery giant Meituan, her first video interview was not with a human being.
The interviewer certainly looked real enough. It was a woman, about Tan’s age, with a friendly smile — but her voice and manner were stitled and distinctly robotic. The interviewer gave a brief introduction about Meituan and asked a series of canned questions like, “What was a challenge you came across in the past?” After each answer, the interviewer would summarize what was said and offer a follow-up question.
The interviewer was an AI avatar, working from a list of pre-determined questions but using a large language model to generate authentic-sounding responses on the fly. But Tan told Rest of World it felt more like taking a written exam than having a conversation. “I didn’t take it as a real human,” she said. “I just looked at the camera and talked.”
Once seen as a curiosity, AI job interviews have grown in popularity as startups look to build businesses on top of the surprising capabilities shown by platforms like OpenAI. The industry is still small, and the jobs affected are often large-scale roles where companies need to sift through thousands of applicants at once. But as companies scramble for ways to integrate AI into their business, experiences like that of Tan are set to become commonplace.
“They don’t get angry or have a bad mood…it doesn’t matter what skin color you have, where you’re from, or what your accent is.”
The idea of using large language models to further automate the hiring process has already caught fire in the U.S. corporate world. A 2023 survey of 1,000 human-resources workers by the U.S. firm ResumeBuilder found that 10% of companies were already using AI in the hiring process, and another 30% planned to start the following year. The research firm Gartner listed natural-language chatbots as one of 2023’s key innovations for the recruiting industry, designating the technology as experimental but promising.
The practice now appears to be catching on in China and India. Alongside Tan’s experience, applicants at firms like Siemens, China Mobile, and Estee Lauder have recently reported AI-powered interviews in China, according to social media posts. (None of the three companies responded to a request for comment.) MoSeeker, a Chinese AI recruitment system provider, performs hundreds of thousands of automated interviews each year, and lists multinationals including Disney and Mars among its clients. Platforms like Talently.ai, Instahyre and Intervue are among a number of Indian companies using AI in the hiring process.
There are a variety of ways to automate the hiring process. The first step is simply to standardize the list of questions asked in the initial interview, a measure often adopted as an effort to fight cultural biases. Once the questions are standardized, there’s only minimal benefit to human presence. Companies often transition from in-person interviews to remote Zoom calls, then to a pre-recorded video of a human, and finally to a fully computer-generated avatar. A Harvard Business School article described this range of options as “the depersonalization spectrum.”
The rise of generative AI platforms like OpenAI and Anthropic allows companies to automate the process even further, adding responsive follow-up questions through the platforms’ natural language systems. Talently.ai is one such service, converting interview answers into text and using prompt engineering to generate a response. Founder Qasim Salam told Rest of World his company can save clients as much as 80% of the work hours necessary to fill a role.
Salam is confident that AI interviewers are less biased than humans. “They don’t get angry or have a bad mood when they’re conducting these interviews and disregard a candidate because of that,” he said. “It doesn’t matter what skin color you have, where you’re from, or what your accent is … So it purely assesses candidates on merit.”
“The more data we give it, the more potential there is for bias.”
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