Irmela F. Koch-Bayram, Chris Kaibel, Torsten Biemann, María del Carmen Triana
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: Applicants' experiences with discrimination explain their reactions to algorithms in personnel selection
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.
期刊介绍:
The International Journal of Selection and Assessment publishes original articles related to all aspects of personnel selection, staffing, and assessment in organizations. Using an effective combination of academic research with professional-led best practice, IJSA aims to develop new knowledge and understanding in these important areas of work psychology and contemporary workforce management.