Efficiency Versus Fairness : A Qualitative Study exploring recruiters' driving motivations and potential ethical risks in AI recruitment

Sammanfattning

Artificial intelligence systems and the ethical implications are a growing theme in the recruitment industry, in order to remain competitive in evolving labor markets. The purpose of this research was to explore recruiters' perceptions connected to the use of AI systems in recruitment processes. Specifically, the study explored the driving motivations for recruiters to begin utilizing AI systems and how to deal with potential ethical issues, such as algorithmic bias and “black box” occurrences. The theoretical framework was based on UTAUT2 and Explainable AI (XAI), and a qualitative methodology was followed. The data was collected through seven respondents to capture the empirical viewpoint of how to navigate the tension between efficiency and fairness. The findings indicate that while AI reduces the administrative burden and recruitment time, the recruiters have a hard time justifying the AI system's decisions and lack of transparency. Furthermore, the findings can help the development towards a robust human oversight and ensure compliance with ethical issues and with the legal framework, the EU AI Act.