“It's the most fair thing to do, but it doesn't make any sense”: Perceptions of Mathematical Fairness Notions by Hiring Professionals

We explore the alignment of organizational representatives involved in hiring processes with five different, commonly proposed fairness notions. In a qualitative study with 17 organizational professionals, for each notion, we investigate their perception of understandability, fairness, potential to increase diversity, and practical applicability...

De (On)mogelijkheden van machine learning voor het verminderen van bias en discriminatie bij personeelsbeslissingen

In this article, we describe the implementation of algorithms based on machine learning for personnel selection procedures and how this data-driven approach corresponds to and differentiates from classical psychological assessment. We discuss if, and in what way, bias and discrimination occur when using algorithms based on machine learning...