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AI ethics, black box models, explainable ai, fairness in AI, feature attribution, future technology, human-centered design, interpretable machine learning, LIME, model explainability, model transparency, regulatory compliance, SHAP, trust in AI, XAI

Explainable AI and Interpretable Machine Learning: Illuminating the Black Box of AI

As machine learning models become ever more pervasive—guiding medical diagnoses, influencing credit decisions, determining content recommendations, and even aiding law enforcement—the question of explainability has taken center stage. Many advanced AI models, especially deep neural networks, operate like intricate “black boxes,” producing predictions with astonishing accuracy but offering little insight into why they made those…
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