AI models handling hiring shun human-written applications

""The findings, detailed in a preprint paper titled "AI Self-preferencing in Algorithmic Hiring: Empirical Evidence and Insights," further amplify persistent concerns about AI bias. Authors Jiannan Xu, a PhD candidate at the University of Maryland, Gujie Li, assistant professor at the National University of Singapore, and Jane Yi Jiang, assistant professor at Ohio State University, found that "LLMs consistently prefer resumes generated by themselves over those written by humans or produced by alternative models, even when content quality is controlled.""

""So those who use OpenAI's GPT-4o, for example, to help draft their resume and cover letter have better odds of getting called back when GPT-4o is assessing their qualifications. "Our findings suggest that when AI models are used to evaluate resumes, they tend to prefer content that resembles their own output," Jane Yi Jiang, one of the paper's co-authors, told The Register in an email. "This doesn't necessarily mean the systems are 'discriminating' in a legal or intentional sense,"

A resume submission experiment analyzed 2,245 human-written resumes alongside material generated by multiple large language models, including GPT-4o, GPT-4o-mini, GPT-4-turbo, LLaMA 3.3-70B, Mistral-7B, Qwen 2.5-72B, and DeepSeek-V3. Models demonstrated a consistent preference for resumes generated by the same model assessing them, with LLM-vs-Human bias strongest. Applicants who used the same model to draft resumes and cover letters experienced higher callback rates when that model evaluated applications. Findings indicate model self-preferencing persists even when content quality is controlled and raise fairness concerns about AI-driven hiring decisions.

Read at Theregister