Nvidia's Ross Says AI Hiring Favors Matching Résumés by 23%-60%
Updated
Updated · Business Insider · May 19
Nvidia's Ross Says AI Hiring Favors Matching Résumés by 23%-60%
2 articles · Updated · Business Insider · May 19
Jonathan Ross said AI screening systems may prefer résumés generated by the same large language model they use, arguing applicants may need multiple AI-tailored versions to improve their odds.
A late-2025 academic paper he cited tested more than 2,200 résumés across 24 occupations and found same-model submissions were 23% to 60% more likely to be shortlisted than comparable human-written ones.
Ross told the Sohn Investment Conference that job seekers should try versions built with tools such as Claude and ChatGPT if they can identify which model a recruiter is using.
The comments land as AI hiring spreads: a 2025 Resume.org survey of nearly 1,400 U.S. workers found 57% of companies used AI in hiring, 79% of those used it to review résumés, and 74% allowed automated rejection without human review.
That expansion is intensifying concerns about bias and false negatives in recruiting, with some applicants reporting near-instant rejections they suspect were triggered by automated screening.
As AI judges other AIs in hiring, are human qualifications becoming irrelevant?
Your résumé might be rejected for using the 'wrong' AI. How can applicants beat the system?
The New Bias in AI Recruitment: Self-Preferencing, Ethical Risks, and What Job Seekers and Employers Must Know
Overview
This report explores a new form of bias in AI-driven hiring, where AI models tend to favor resumes and content generated by other AI systems—a phenomenon called AI self-preferencing. As AI tools become more common in early hiring stages, job seekers who use AI to craft and optimize their resumes may gain an advantage over those who write by hand. This shift highlights the need to look beyond traditional biases like gender or race and consider how AI evaluating AI-generated text can impact fairness and meritocracy in recruitment. Understanding and adapting to these technologies is now crucial for both candidates and employers.