AI Systems That Automatically Reject Your Job Application

Episode 23 of AI Ethics with Fexingo explores the hidden world of applicant tracking systems (ATS) that automatically reject 75% of résumés before a human ever sees them. Lucas and Luna dive into how these AI filters, trained on historical hiring data from companies like Amazon and Unilever, can encode subtle biases against women, older workers, and non-traditional career paths. We break down the case of Amazon's 2015 automated hiring tool that penalized résumés containing the word 'women's' and discuss why today's ATS software still struggles with gaps in employment, unconventional job titles, and even font choices. The episode also covers emerging regulation like New York City's Local Law 144, which mandates bias audits for automated hiring systems, and the practical steps job seekers can take to 'beat the bot.' Throughout, the hosts balance skepticism of pure automation with recognition that well-designed AI can widen talent pools. The conversation closes with a reflection on fairness and human dignity in the job market. #ApplicantTrackingSystem #ATS #HiringBias #ResumeFiltering #AutomatedHiring #Amazon #Unilever #LocalLaw144 #NYCBiasAudit #JobSearch #AIEthics #BiasInAI #EmploymentDiscrimination #Technology #FexingoBusiness #BusinessPodcast #AlgorithmicFairness #ResponsibleAI Keep every episode free: buymeacoffee.com/fexingo