Shea Brown, PhD explores with us the “W’s” and security practices related to AI and algorithm audits.

What is included in an AI audit?

Who is requesting AI audits and, conversely, who isn’t requesting them but should be?

When should organizations request a third party audit of their AI/ML systems and machine learning algorithms?

Why should they do so? What are some organizational risks and potential public harms that could result from not auditing AI/ML systems?

What are some next steps to take if the results of your audit are unsatisfactory or noncompliant?

Shea Brown, PhD; is the Founder and CEO of BABL AI, and a faculty member in the Department of Physics & Astronomy at the University of Iowa.

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Additional tools and resources to check out:
Protect AI Guardian: Zero Trust for ML Models

AI Audits: Uncovering Risks in ML Systems; With Guest: Shea Brown, PhD