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AI Must Explain Itself

Published:
June 16, 2020

This wide-ranging and accessible article dives into the movement for "Explainable AI", exploring the practical, psychological, and regulatory dimensions of explainability. Explainability is a prerequisite for ML assurance, and counterfactuals are emphasized as core to the next step: auditability.

Money quote: "In the absence of clear auditing requirements, it will be difficult for individuals affected by automated decisions to know if the explanations they receive are in fact accurate or if they’re masking hidden forms of bias."

AI Governance & Assurance