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Mitigating Bias in AI Model Using EXplainable AI in Terms of Hiring Process in The Industry by dika.webmaster is a document available to read on EtoBox.

This study addresses the ethical concerns of bias in AI recruitment processes by proposing an Explainable Artificial Intelligence (XAI) approach that enhances transparency and accountability in hiring models. Utilizing SHapley Additive exPlanations (SHAP), the research identifies and mitigates biases related to gender, nationality, and other features, resulting in improved classification accuracy and fairness metrics. The findings advocate for the integration of XAI techniques in recruitment to ensure equit

Author

dika.webmaster

Language

EN