Impact of AI Literacy on HR Managers' Understanding of Recommender Systems

This research article examines the influence of AI literacy on Human Resource (HR) managers' perceptions and understanding of explainable AI (XAI) elements within recruiting recommender systems. Conducted with 410 HR managers in Germany, the study compares baseline dashboards with versions enhanced by three XAI styles: important features, counterfactuals, and model criteria. The findings indicate that while adding XAI features can improve subjective perceptions of trust and helpfulness among users with moderate to high AI literacy, it does not necessarily enhance their objective understanding. In fact, complex explanations may lead to a decrease in accurate understanding, particularly among those with higher AI literacy. The article emphasizes the need for tailored explanation strategies and targeted literacy training to ensure fair and effective AI adoption in HRM. It also highlights the critical role of AI literacy in interpreting AI outputs and making informed recruitment decisions, underscoring the importance of transparency in AI systems.