Bias Detection and Mitigation in AI: A Framework for fair and inclusive Machine Learning Models

As AI becomes increasingly integrated into sectors like healthcare, finance, and recruitment, concerns around algorithmic bias, fairness, and data privacy are rising. This study addresses these ethical issues by introducing the Bias Detection Dashboard—a Python-based tool built with Pandas, Seaborn, Matplotlib, Fairlearn, and Streamlit. The dashboard helps users identify data imbalances, compute fairness metrics like disparate impact, and detect sensitive attributes before model training. A case study in HR recruitment shows how it flagged gender bias and guided corrective steps. The research also introduces the Ethical AI Triangle—bias, fairness, and privacy—as key pillars that must be balanced. It calls for ethical practices across the AI lifecycle, diversity in teams, and transparent systems to build responsible, trustworthy AI.