Abstract
Explainable AI (XAI) refers to the development of artificial intelligence models and algorithms that can be understood and explained by humans. The goal of XAI is to create AI systems that not only produce accurate results but also provide insights into their decision-making process. In recent years, the use of machine learning and other AI technologies has become increasingly prevalent in a variety of fields, including healthcare, finance, and transportation. However, many AI models are often regarded as "black boxes," meaning that the internal workings of the model are not transparent, and it is difficult for humans to understand how the model arrived at a particular decision.
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