AI in Recruitment: How Machine Learning Shapes Candidate Behavior and Selection Outcomes

Researchers from the Rotterdam School of Management at Erasmus University have discovered that the use of artificial intelligence (AI) by companies during the hiring process can influence candidate behavior, leading to biased selection outcomes.

This study aggregates findings from 12 experiments involving over 13,000 participants. The results indicated that job seekers tend to modify their behavior to «appeal» to AI, significantly emphasizing their analytical abilities while downplaying emotional traits.

«The conclusion that individuals strategically highlight specific skills or attributes suggests that candidates present a distorted image of their true selves,» noted Anne-Katrin Klesse, an assistant professor of marketing management.

The authors validated their findings through modeling hiring processes and documenting how applicants portrayed themselves to AI systems as well as human evaluators.

«If your organization employs AI for hiring, promotions, or assessments, it’s crucial to understand that these tools do more than alter the process; they can also influence who secures a job,» Klesse stated.

She recommends that organizations take the following measures to prevent unintentional bias and distorted self-presentation by candidates:

— Ensure transparency: Disclose the use of AI and the criteria for its assessments.
— Conduct AI system audits: Regularly evaluate AI assessment systems for behavioral biases that may restrict the talent pool and introduce unintended biases into the selection process.
— Train hiring teams: Educate recruiters and managers about the possibility that candidates may alter their behavior when they know they are being assessed by AI.

Earlier research from Duke University indicated that while generative AI tools can enhance productivity, they may also negatively impact professional reputations. Findings showed that employees using tools like ChatGPT, Claude, or Gemini at work faced unfavorable judgments regarding their competence and motivation from colleagues and supervisors.