Technology and Policy
Model interpretability refers to the extent to which a human can understand the reasoning behind the predictions made by a machine learning model. It is crucial for fostering trust and transparency in algorithmic decision-making processes, especially when these models are used in sensitive areas like healthcare, finance, and law enforcement.
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