AI is increasingly used to make important decisions in our lives like predicting the onset of a disease, the suitability of a job candidate, the likelihood of a criminal to reoffend, or the next president of the United States. In such cases, having AI model outcomes that are explainable, or interpretable, is often just as important as having model outcomes that are accurate. In this episode, Xyonix Data Scientists engage in a robust discussion where we explore model interpretability and discuss why you should care.

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