AUTHOR=Kubiak Emeric , Efremova Maria I. , Baron Simon , Frasca Keely J. 

TITLE=Gender equity in hiring: examining the effectiveness of a personality-based algorithm

JOURNAL=Frontiers in Psychology

VOLUME=Volume 14 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2023.1219865

DOI=10.3389/fpsyg.2023.1219865

ISSN=1664-1078

ABSTRACT=Gender biases in hiring decisions remain an issue in the workplace. Also, current gender balancing techniques are scientifically poorly supported and lead to undesirable results, sometimes even contributing to activating stereotypes. While hiring algorithms could bring a solution, they are still often regarded as tools amplifying human prejudices. In this sense, talent specialists tend to prefer recommendations from experts, while candidates question the fairness of such tools, in particular, due to a lack of information and control over the standardised assessment. However, there is evidence that building algorithms based on data that is more gender-blind, like personality -which has been shown to be mostly similar between genders, and is also predictive of performance, could help in reducing gender biases in hiring. The goal of this study was, therefore, to test the adverse impact of a personality-based algorithm across a large array of occupations. Across a sample of 208 predictive models built for 18 employers, which were tested on a global sample of 273,293 potential candidates for each role, mean weighted impact ratios of .91 (Female-Male) and .90 (Male-Female) were observed. We found similar results when analysing impact ratios for 21 different job categories. Our results suggest that personality-based algorithms could help organisations screen candidates in the early stages of the selection process while mitigating the risks of gender discrimination.