MEDICAL STUDENT INVESTIGATES AI'S ROLE IN JOB REJECTION

The unnamed medical student couldn't secure a single job interview despite applying widely. Frustrated by the silence, he decided to investigate whether applicant tracking systems (ATS)—AI software that filters resumes before humans see them—were responsible for his rejection. Using Python, he built tools to analyze how algorithms screen candidates. His investigation examined whether technical barriers in ATS software systematically blocked qualified applicants. The effort highlights growing concerns about AI's role in hiring. Automated resume screening has become standard across industries, yet the systems often lack transparency. Candidates rarely know if they're rejected by algorithms or hiring managers. The student's project underscores a broader issue: job seekers have minimal visibility into how AI evaluates their qualifications. His findings add to mounting pressure on employers to disclose and audit hiring algorithms for bias and fairness.