Rethinking Artificial Intelligence: Algorithmic Bias and Ethical Issues| How Process Experts Enable and Constrain Fairness in AI-Driven Hiring

Ignacio Fernandez Cruz


Organizations risk losing their competitive edge as they struggle to find and hire qualified talent. Hiring personnel turn to artificial intelligence (AI) tools to help acquire talent, increase efficiency, and reduce costs. Yet despite the best intentions for integrating fair and evidence-based systems, exacerbated levels of bias may occur from using these tools. Drawing from scholarship on process expertise and emerging practices of AI use at work, I provide a case study of 42 high-volume recruiters and uncover how hiring personnel enact and justify unsystematic sourcing practices within the confines of their held expertise, organizational demands, and technology choices. I explain how AI-based hiring decisions in organizations are context dependent and blend the capabilities of algorithmic-powered tools with choices and judgments made by process experts. I conclude by offering theoretical and practical considerations for expertise, hiring, and the integration of algorithms at work.


hiring algorithms, process expertise, fairness, organizational communication

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