Forbes October 4, 2024
Vinay Kumar Sankarapu is the CEO and Founder of Arya.ai, AI cloud for safe & responsible AI.
In my previous article, I discussed the importance of AI explainability and the different categories of AI explainability, explainable predictions, explainable algorithms and interpretable explanations.
In this article, I’ll explore the current methods used in explainable AI (XAI) and explainability outcomes and also share insights on how organizations can build explainability templates.
Several techniques, such as Shap, LIME, partial dependence plot, individual condition expectations plots (ICE), etc., have been developed for explainable AI (XAI) to provide interpretations of models’ decisions. They can be categorized into, as I explained in my last article, global explainability, local explainability and cohort explainability.
Let’s take a look...
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