The bright side of AI in hiring: Collaborating with algorithms supports ethical decision-making

Abstract

In this study, we use principal-agent theory and attribution theory to examine how AI’s support during ethical violations in the hiring process influences decision-making and how it can be explained by the perception of who is responsible for that violation. In three between-subject experiments, we exposed managers to vignettes describing an AI or human norm violation during the hiring process. The results show a bright side of AI arising from the finding that managers might be more ethical when sharing HR tasks with algorithms than with other people in organizations because working with AI limits assigning responsibility to other humans. It also exposes nuances between responsibility attribution and human behavior with AI in the hiring context.

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