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AI Audits: Uncovering Risks in ML Systems; With Guest: Shea Brown, PhD
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Manage episode 362311986 series 3461851
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.
Thanks for checking out the MLSecOps Podcast! Get involved with the MLSecOps Community and find more resources at https://community.mlsecops.com.
Additional tools and resources to check out:
Protect AI Guardian: Zero Trust for ML Models
Recon: Automated Red Teaming for GenAI
Protect AI’s ML Security-Focused Open Source Tools
LLM Guard Open Source Security Toolkit for LLM Interactions
Huntr - The World's First AI/Machine Learning Bug Bounty Platform
58 episodes
Fetch error
Hmmm there seems to be a problem fetching this series right now. Last successful fetch was on October 30, 2025 16:55 ()
What now? This series will be checked again in the next day. If you believe it should be working, please verify the publisher's feed link below is valid and includes actual episode links. You can contact support to request the feed be immediately fetched.
Manage episode 362311986 series 3461851
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.
Thanks for checking out the MLSecOps Podcast! Get involved with the MLSecOps Community and find more resources at https://community.mlsecops.com.
Additional tools and resources to check out:
Protect AI Guardian: Zero Trust for ML Models
Recon: Automated Red Teaming for GenAI
Protect AI’s ML Security-Focused Open Source Tools
LLM Guard Open Source Security Toolkit for LLM Interactions
Huntr - The World's First AI/Machine Learning Bug Bounty Platform
58 episodes
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