Explainable AI (XAI) refers to the ability of an artificial intelligence system to explain its reasoning and decision-making processes in a way that is understandable to humans. XAI is important because many AI systems, such as deep learning models, can be difficult for humans to interpret, leading to a lack of trust and transparency. XAI methods include techniques such as visualization, natural language explanations, and model introspection, which allow humans to understand how the AI arrived at its conclusions. XAI has many potential applications in areas such as healthcare, finance, and law, where transparency and accountability are important.
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