Apply a Machine Learning Model to Mitigate Bias in the Future AI-based Recruitment

In the contemporary landscape of Human Resources, the integration of artificial intelligence presents both opportunities and challenges, especially in the field of recruitment encompassing all stages of the process, from candidate sourcing to final selection. However, this integration is not without its challenges. Biased data, originating from historical data or societal prejudices, can present a significant obstacle, potentially perpetuating discriminatory practices. The study "Apply a Machine Learning Model to Mitigate Bias in the Future AI-based Recruitment" aims to comprehensively analyze existing biases from both human and artificial intelligence perspectives within the recruitment process. In its framework, answers to the research questions are sought: what are the existing biases in the recruitment process, both explicit and implicit, and how can biases in the recruitment process be effectively mitigated or eliminated through modeling techniques in future AI-based recruitments systems. Through a data-driven approach and the development of machine learning models, will be discover what kind of biases exist in the selection process and how to mitigate them.