i10x.ai Unveils Bias in AI-Driven Job Application Evaluations

In this episode of Global Economic Press, Alex Brady discusses a groundbreaking study conducted by i10x.ai that reveals significant biases in artificial intelligence-driven job application evaluations. The study highlights how artificial intelligence systems can unfairly screen job applications based on which model wrote the resume, leading to discrepancies in hire recommendations. This finding is crucial for both job seekers and employers who rely on artificial intelligence systems for recruitment, as it underscores the need for more equitable and unbiased evaluation processes. The study analyzed 1,576 data points across 100 candidate profiles using four leading artificial intelligence systems: GPT-5.4, Claude Sonnet 4.6, Gemini 3 Pro, and Grok 4.3. It found that Claude Sonnet 4.6 was the strictest evaluator, showing a significant self-bias by hiring only 42% of GPT-written resumes compared to 84% of its own. Meanwhile, Gemini-written resumes scored the highest across all evaluators, with an average hire rate of 94.5%. These biases in automated applicant tracking systems can prevent resumes from reaching human recruiters, making it an urgent issue to address. For more information on the study and to access a free resume screening tool, visit i10x.ai.