MIT Researchers Create ‘ExSum’: A Mathematical Framework To Evaluate Explanations Of Machine Learning Models And Quantify How Well People Understand Them

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Machine learning is frequently referred to as a “black box” because the interactions between input and output become increasingly opaque as the model’s complexity grows. People’s understanding of these models is confined to how data is entered and final choices are made, and there is not much clarity in how these models make their predictions. While previous research has been done to determine how accurate the explanations given by these models are, the question of how quickly and reliably individuals …

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