Explaining Explainable AI

December 16th, 2020

With contributors:

Srividya Sridharan , Mike Gualtieri , Aldila Yunus , Jeremy Vale

Summary

Explainable AI helps leaders who are adopting AI meet regulatory requirements, build trust among business stakeholders, and derive valuable insight from data. Just as there are many flavors of AI technologies, so too are there many types of explainable AI: transparent or interpretable; global or local. Selecting the right approach depends on your use case and audience. Prioritize transparent approaches for high-risk and highly regulated use cases; favor interpretability for lower-risk use cases where accuracy is paramount. Furnish global explanations for regulators and business stakeholders, and provide local explanations for individual customers. To learn more about explainable AI, read this report and schedule an inquiry.

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