Objectivity is an essential feature of the selection process in hiring. While human decision-making tends to lack consistent objectivity, AI-based systems provide the opportunity to make selection processes more objective and fairer by mitigating human biases that could cause discrimination. In this work, Professor Mirbabaie investigates the AI-based system’s impact on humans’ hiring decisions and how an Explainable AI (XAI) approach could moderate this relationship. Based on an online experiment with 194 participants, the findings suggest that AI-based systems can reduce discrimination against older and female candidates. However, they simultaneously appear to cause fewer selections of foreign-race candidates. Contrary to expectations, the explanations for these effects differed for the same XAI approach depending on the context. This work is published in the journal Electronic Markets.
Hofeditz, L., Clausen, S., Rieß, A., Mirbabaie, M., & Stieglitz, S. Applying XAI to an AI-based system for candidate management to mitigate bias and discrimination in hiring.