AI Sourcing: Promise, Bias, and the Human-in-the-Loop

Why Brilliant Hires Still Become Bad Teams

Five standout hires can still underperform if roles are muddy, handoffs break down, and no one knows who gets to decide. This episode digs into the real ingredients of strong teams: shared purpose, clear decision rights, trust, psychological safety, and accountability.

AI Sourcing: Promise, Bias, and the Human-in-the-Loop

This episode explores how AI sourcing can uncover passive candidates and expand talent pools beyond keyword searches. It also digs into the risks of automated bias, ranking gravity, and why transparent, auditable human oversight is essential.

AI Hiring: Speed, Bias, and Who Gets Through the Door

This episode explores how AI is reshaping recruitment, from résumé screening and ranking to ad delivery and automated decision-making. It also examines the risks of proxy-based hiring, hidden bias, and why trustworthy systems need transparency, accountability, and room for contestation.

AI in Hiring: Speed, Trust, and the Real Edge

We unpack how AI has become standard infrastructure in recruiting, reshaping the funnel from sourcing to scheduling to candidate communication. The conversation also explores where automation helps most, where human judgment still matters, and why structured process design now matters more than ever.

Why Résumés and Gut Feel Mislead Hiring

Claire Monroe and Edwin Carrington unpack why experience, pedigree, and instinct often predict performance far less than managers assume, and how newer research has refined—but not overturned—the case for structured, job-relevant hiring methods. They also explain why work samples, structured interviews, and observable skills produce stronger, fairer decisions than unstructured conversations or résumé polish.