In a nutshell AI resume screening tools showed strong racial and gender bias, with White-associated names preferred in 85.1% of tests and Black male names favored in 0% of comparisons against White males. Bias increased when resumes were shorter, suggesting that when there’s less information, demographic signals like names carry even more weight. Removing names isn’t enough to fix the problem, as subtle clues—like word choice or school name—can still reveal identity, allowing AI systems to continue filtering out diverse candidates. ================================================================= SEATTLE — Every day, millions of Americans send their resumes into what feels like a digital black hole,...