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16min chapter
162: The Power of Explainable AI
Alter Everything
Importance of Explainable AI in Understanding Model Decision-making Process
The chapter explores the significance of explainable AI in understanding how machine learning models make decisions, emphasizing transparency, trust-building, and preventing biases. It highlights real-world examples of misclassifications and stresses the need for industry sectors like healthcare and finance to adopt explainable AI for ethical and legal reasons. Various techniques such as decision trees and SHAP are discussed to achieve model interpretability and uncover bias in AI systems.
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Discover
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Listen to the best highlights from the podcasts you love and dive into the full episode