This session will help to unpack how classic tools (structured interviews, cognitive ability tests, and personality inventories) compare with newer AI-driven measurement (resume models, video/voice analysis, automated scoring, and algorithmic decisioning). 

We’ll weigh pros like standardization, speed, and scale against cons like hidden bias, weak validation, and “black box” decision paths - then go deeper on what matters most in practice: fairness, reliability/validity, and legal defensibility (job-relatedness, consistency, documentation, auditability, and candidate accommodations). The goal is a pragmatic playbook for choosing - or safely combining - approaches without sacrificing compliance, trust, or quality.