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Neural networks have proven themselves very capable of performing tasks that have eluded researchers for years. When you find out that no one really knows why neural networks behave the way they do, it only adds to their mystique.

The fields of eXplainable AI (XAI) and Fairness, Accountability, and Transparency in Machine Learning (FAT/ML) aim to provide insight into how neural networks comes to the conclusions that they do.

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