Advancing the frontiers of AI and recruitment technology.

Human oversight has long been positioned as the critical safeguard against AI discrimination in hiring. New research from the University of Washington reveals a troubling reality: when humans collaborate with biased AI systems, they overwhelmingly adopt—rather than counteract—the machine's prejudices. We examine the implications for AI-assisted recruitment and what organizations must do differently.

Large Language Models can replicate and amplify societal biases, particularly in high-stakes domains like hiring. We detail our comprehensive approach to detecting, preventing, and monitoring bias in recruitment AI—from pre-training data curation to continuous evaluation metrics—and introduce our specialized bias benchmark for hiring systems.