Ethical Considerations in Applying Machine Learning to HR Practices: Balancing Efficiency with Fairness

This research paper is aimed at investigating the feasibility of implementing Machine Learning in Human Resource Management (HRM) system from the organizational viewpoint in reference to the effectiveness and fairness of the model designated for predicting turnover rates among employees. From the Kaggle HR Analytics dataset, we achieved our goal by employing the Random Forest algorithm to analyze selected factors related to attrition. These works demonstrated that while growing machine learning delivers higher forecasting, it diminishes ethical factors like algorithmic bias. These implications highlight the importance of equality in the treatment of different demographic groups to expand on the concept of the ethical usage of AI in HRM. This research provides some practical suggestions for organizations that want to use AI for managing human resources and at the same time, being ethical.