: Applicants' experiences with discrimination explain their reactions to algorithms in personnel selection |
| |
Authors: | Irmela F. Koch-Bayram Chris Kaibel Torsten Biemann María del Carmen Triana |
| |
Affiliation: | 1. Department of Management, University of Mannheim, Mannheim, Germany;2. Owen Graduate School of Management, Organization Studies Area, Vanderbilt University, Nashville, Tennessee, USA |
| |
Abstract: | Algorithms might prevent prejudices and increase objectivity in personnel selection decisions, but they have also been accused of being biased. We question whether algorithm-based decision-making or providing justifying information about the decision-maker (here: to prevent biases and prejudices and to make more objective decisions) helps organizations to attract a diverse workforce. In two experimental studies in which participants go through a digital interview, we find support for the overall negative effects of algorithms on fairness perceptions and organizational attractiveness. However, applicants with discrimination experiences tend to view algorithm-based decisions more positively than applicants without such experiences. We do not find evidence that providing justifying information affects applicants—regardless of whether they have experienced discrimination or not. |
| |
Keywords: | diversity and inclusion fairness organizational justice selection |
|
|