Book

Description

The Algorithmic Hiring Trap explores the hidden risks of AI-powered recruitment and the biases that can emerge when algorithms learn from historical hiring data.   From resume screening and automated interviews to candidate ranking and assessment, this book examines how AI can reproduce discrimination through data, proxy variables, and system design.   Drawing on documented cases involving Amazon, HireVue, iTutorGroup, and Workday, it explores gender, racial, age, disability, and socioeconomic bias—while also examining transparency, privacy, human oversight, fairness, and regulation.   As AI becomes increasingly involved in deciding who gets seen, interviewed, and hired, one question remains: When an algorithm makes the decision, who is responsible for the outcome?