Ethics In HR machine learning: striking a balance between efficiency and fairness

As organisations continue to incorporate machine learning (ML) in the enhancement of Human Resource Management (HRM), the issue of trade-off between efficiency and fairness arises. The current research explores the ways to utilize the fairness-aware modern techniques in ML, including XGBoost, to accurately detect the employee turnover while enhancing fairness and transparency. The introduced fairness constraints and explainable AI tools provide additional guarantees that employees from different groups will be treated equally. The study shows that the integration of AI in HR processes improves the decision-making process without compromising the ethical aspect and serves as an example of responsible implementation and optimization of HR processes in the context of contemporary industry demands.