DOES ARTIFICIAL INTELLIGENCE LEAD TO GENDER BIAS IN RECRUITMENT? A SYSTEMATIC REVIEW WITH THE PRISMA MODEL

Abstract

One of the most prominent indicators of the Fourth Industrial Revolution, artificial intelligence (AI), has begun to profoundly impact both work and social life. In the realm of employment, it has led to a fundamental paradigm shift in work practices and employment structures. Integrated into workflows across various sectors, AI has started to be used effectively in the field of human resources. In particular, its integration into recruitment processes has been observed to enhance efficiency and productivity in human resources by reducing both cost and time. Representing the third wave of recruitment, AI-based hiring systems also have the potential to generate gender bias. To examine this phenomenon, a systematic literature review was conducted based on the PRISMA methodology. Accordingly, 37 experimental studies investigating AI-based recruitment processes (such as sourcing, screening, interviewing, and selection) were included in the study. In approximately 68% of the reviewed studies, AI was found to cause gender bias at some stage of the recruitment process. This finding indicates that early-stage AI tools continue to perpetuate gender-based biases. Furthermore, the study explores the underlying causes of gender bias in AI systems and offers various recommendations to mitigate such bias in recruitment processes.