Navigating Discrimination in Hiring

This chapter examines the complexities of measuring discrimination in hiring practices, emphasizing the difference between truth-seeking data and oversimplified narratives. It discusses the limitations of diversity training and suggests that a data-driven approach is essential to identify and address biases effectively. The conversation also highlights the potential of machine learning algorithms in enhancing hiring practices by focusing on merit and predicting applicant performance.