Artificial Intelligence in International Human Resource Management

Abstract

Artificial intelligence is increasingly deployed in human resource management to enhance candidate selection and streamline recruitment processes. However, significant questions remain regarding the reliability and consistency of artificial intelligence-driven interview systems compared to traditional human resource management evaluations. Given the potential for intentional or unintentional bias in AI algorithms, there is a critical need to evaluate whether electronic interview systems produce candidate selections comparable to those of human evaluators when assessing a shared applicant pool.
This research employs a comparative evaluation methodology to assess multiple electronic human resource information systems (HRIS) and their effectiveness in candidate selection. A comparison of the top 10 selections generated by various AI-driven interview platforms with those made by experienced human resource managers was conducted using a standardized pool of candidates. I examine the degree of overlap in candidate rankings and analyze patterns of disparity that may indicate systemic bias or inconsistency in artificial intelligence algorithms.