Archives for AI explainability
AI-based companies usually turn to the black box and avoid critical analysis of the results obtained from their models.
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“AI models do not need to be interpretable to be useful.” Nigam Shah, Stanford Interpretability in machine learning goes back to the 1990s when it was neither referred to as “interpretability” nor “explainability”. Interpretable and explainable machine learning techniques emerged from the need to design intelligible machine learning systems and understand and explain predictions made…
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