This is a Brookings Center on Regulation and Markets working paper.
Abstract
The rise of artificial intelligence (AI) has enabled modern society to automate aspects of the organizational hiring process. Yet, prospective job candidates are hesitant to engage with such technologies in their everyday lives unless they perceive algorithms as behaving fairly. Procedural fairness is considered critical in shaping individual attitudes toward algorithms. However, empirical studies examining the role of procedural fairness in AI-enabled hiring are lacking. The present research seeks to bridge this gap by investigating how perceptions of procedural fairness and related fairness dimensions influence job applicants’ perceptions of different hiring algorithms designed to incorporate fairness ideals and their attitudes toward companies using these algorithms. Our findings indicate that people perceive hiring algorithms as procedurally fairest when they adopt a “Fairness through unawareness” approach to mitigating bias. They are also likely to view companies who use this approach more positively and are more motivated to apply for open positions.
Authors
