Explainable Ai

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Explainable artificial intelligence XAI refers to a collection of procedures and techniques that enable machine learning algorithms to produce output and results that are understandable and

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Usually it is essential to understand the reasoning behind an AI model s decision making Thus the need for eXplainable AI XAI methods for improving trust in AI models has arisen XAI has

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Explainable artificial intelligence XAI is a set of processes and methods that allows human users to comprehend and trust the results and output created by machine learning

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This book is designed to guide readers through the fundamental concepts of Explainable AI XAI progressing to advanced techniques and exploring future research opportunities

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We review concepts related to the explainability of AI methods XAI We comprehensive analyze the XAI literature organized in two taxonomies We identify future research directions of the

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Explainable artificial intelligence XAI has emerged as a crucial field for understanding and interpreting the decisions of complex machine learning models particularly deep neural networks

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We have conducted an intensive survey on technologies and techniques used in making AI explainable Finally we identified new trends in achieving explainable AI In particular we

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Explainable artificial intelligence XAI aims to provide a suite of machine learning techniques that enable human users to understand appropriately trust and produce more explainable models

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To be trustworthy AI should be amongst others transparent accountable and ethical and explainable AI can play an important role in meeting these specific requirements