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A Multi-Stage Framework for Bias Detection and Mitigation in AI-Driven Recruitment Systems
The use of machine learning in recruitment has raised growing concerns about fairness, as automated hiring systems can generate unequal outcomes across demographic groups. These disparities are influenced not only by imbalanced data but also by the behavior of learning algorithms, making bias a multidimensional challenge that cannot be effectively… Read full abstract & cite →
Bias detection
bias mitigation
AI in recruitment
algorithmic fairness
explainable AI
fairness metrics
machine learning
responsible AI
