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Article Summary

Article Summary of:

Derisking AI: Risk management in AI development

Originally published:
Nov 20, 2020

In this follow-up in a series on AI challenges, McKinsey thought leaders lay out an approach that enterprises should pursue with their AI/ML projects in much the same way as they do with all their initiatives: risk management by design. Organizations should plan for risk concurrently while developing projects, as well as ensure a consistent practice across teams and projects. Understanding risk when it comes to AI/ML systems requires some unique considerations, liabilities, and domain knowledge to ensure that they are consistent with the company's values, risk profile, and compliance needs. They emphasize the importance of "standards, testing, and controls...embedded into various stages of the analytics model’s life cycle, from development to deployment and use".

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