Abstract
<jats:p>This chapter examines how AI-based recruitment systems can produce algorithmic discrimination against job candidates. While these systems are widely used to improve efficiency in screening and selection processes, they may reproduce historical biases and disadvantage groups such as women, ethnic minorities, older individuals, and candidates with health conditions. The study is based on a qualitative content analysis of approximately 40 documents published between 2016 and 2025. The findings show that discrimination emerges from the interaction of multiple technical and social factors rather than a single source. Accordingly, the chapter develops a six-factor framework and offers policy recommendations to improve fairness, transparency, and accountability in AI-based recruitment systems.</jats:p>