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This blog post provides an in-depth analysis of Explainable AI (XAI), a crucial advancement in artificial intelligence that aims to make AI systems transparent and understandable. Explainable AI refers to a set of processes and methods that enable users to forecast and comprehend the results produced by advanced machine learning algorithms. It can be used to give information about an AI model, its potential impacts, and biases. Despite extensive research, the exact definition of Explainable AI is not yet consolidated. This blog post will offer a detailed insight into the usability, effectiveness, and working of Explainable AI.