Five critical questions to explain Explainable AI - Deepstash

Explainable AI is a critical element of the broader discipline of responsible AI. Responsible AI encompasses ethics, regulations, and governance across a range of risks and issues related to AI inc...

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Five critical questions to explain Explainable AI

towardsdatascience.com

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Explainable AI is a critical element of the broader discipline of responsible AI. Responsible AI encompasses ethics, regulations, and governance across a range of risks and issues related to AI inc...

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The audience for the explanation or whom to explain should be the first question to answer. Understanding the motivation of the audience, what action or decision the audience is planning to make, t...

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End users require an explanation of the decision or action recommended made by the AI system in order to carry out the recommendation.

Business users require an explanation to ensure corpora...

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Explanations may be generated before the model is built, also called ex-ante or the model is trained and tested first and then the explanation may be generated, also called post-hoc.

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Visual or graphical explanations, tabular data-driven explanation, natural language descriptions or voice explanations are some of the existing modes of explanation.

A salesperson might be co...

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There are six broad approaches as it relates to post-hoc explainability.

  • Feature relevance: These approaches to explainability focus on the inner functioning of the model and highlight t...

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There are six broad approaches as it relates to post-hoc explainability.

  • Feature relevance: These approaches to explainability focus on the inner functioning of the model and highlight t...

STASHED IN:

3

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