AI Bots in the Interview Process
Imagine this. You’re invited to a virtual interview. You log on, the interviewer appears on screen, and begins asking questions. But something seems off. The questions are standardized and seem scripted. The exchange feels impersonal. You are unable to read body language. The cadence of the interviewer’s voice is odd. The interview itself seems highly structured and time-boxed. You may not be interviewing with a person at all; instead, you might find yourself on the other side of the screen from an AI bot.
The integration of artificial intelligence (AI) in recruitment has revolutionized hiring processes, offering efficiency, cost savings, and the ability to handle high volumes of applications. A recent article in Time magazine indicates that the use of AI in the interviewing process is on the rise. Some people find this to be an efficient way to screen candidates. However, the majority find it impersonal, and even worse, insulting.
Although AI technology offers undeniable advantages for employers, its impact on candidates is far more nuanced and often negative. The use of AI bots in interviewing can undermine the candidate experience in several ways, including reducing human connection, creating perceptions of unfairness, limiting opportunities for genuine expression, and contributing to candidate anxiety and mistrust.
One of the most significant drawbacks of AI interviewing is the erosion of human connection. Job interviews are two-way conversations that provide candidates with an opportunity to assess the company culture, engage with potential colleagues, and gain insight into whether the role aligns with their aspirations. When applicants invest time and effort in preparing for an interview, only to interact with a preprogrammed algorithm, they often perceive the process as cold and impersonal, which can diminish their enthusiasm for the role and the organization. In other words, relying on AI bots for screening makes a bad impression on candidates.
AI systems rely heavily on algorithms trained with historical data, which may perpetuate existing biases in hiring practices. For instance, if the training data reflects biased hiring decisions from the past, the AI may replicate or even amplify those biases by unfairly favoring certain demographics over others. This erodes trust in the hiring process and damages employer brands.
Traditional interviews enable applicants to gauge the room, adjust their tone, and refine their responses based on feedback from the interviewer. AI bots, on the other hand, rely on rigid scripts, keyword detection, or facial recognition metrics, and, most importantly, do not capture nuance.
Companies that leverage AI in their hiring practices must be completely transparent with candidates, especially when it comes to the archival and use of the personal data collected by the AI bots. Most people don’t know how these systems work or how their answers will be evaluated. Such obfuscation may be unintentional, but the consequences may be dire. When hiring companies are not forthcoming about their hiring practices, it can lead applicants to draw their own conclusions, resulting in suspicion, distrust, and uncertainty, which will limit the ability to attract top talent.
Hiring is a human process. People hire other people, not a set of skills or competencies. An AI bot is unable to assess soft skills, such as nonverbal communication, teamwork, influence, and most importantly, self-awareness. Candidates want to feel seen, heard, and evaluated as individuals, not data points. Companies that value inanimate efficiency over the human touch risk alienating skilled applicants, reinforcing bias, and damaging their reputation as an employer of choice.