Latest / Hiring & Firing with Fexingo: Recruitment, Performance, and Workforce Decisions
The Hiring Algorithm That Learned Bias From Human Data
In this episode, Lucas and Luna examine how algorithmic hiring tools inherit and amplify human bias using the example of Amazon's abandoned resume-screening AI. They walk through the specific feedback loop: historical hiring data taught the algorithm to penalize resumes containing the word 'women's,' degrade candidates from all-women's colleges, and favor verbs more common on men's resumes. The hosts discuss why this happened despite engineering teams having no explicit gender filter, and what it means for companies rushing to deploy AI in hiring today. They also…
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