Using AI to bridge gaps and mitigate biases in recruiting

Abstract

As acute shortages for data professionals further develop in competitive talent markets, addressing biases and bottlenecks in hiring has become a business imperative. However, most companies continue to rely on judgments and experience when conceptualizing jobs and drafting job advertisements. Drawing on results from analyzing over 15 million jobs and their outcomes, Maryam explains how often-innocuous recruiting decisions have dramatic impacts on hiring outcomes, from the success of a hiring process to the candidate pool composition and the amount of time it takes to hire. She then discusses how using data-driven approaches provide an arbitrage opportunity that has significant impact on both the quality and diversity of candidate pools for data analyst and data scientist roles.