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AI Model Risk Management Framework
AI Model Risk Management Framework
Who it's for:
  • AI/ML Engineers and Developers
  • Data Scientists
  • Risk Management Professionals
  • Compliance Officers and Auditors
  • Business Leaders, Executives, and Project Managers
  • Communications and Public Relations Professionals

AI Model Risk Management Framework

Release Date: 07/23/2024

Working Group: AI Safety Initiative

Sophisticated machine learning (ML) models present exciting opportunities in fields such as predictive maintenance and smart supply chain management. While these ML models hold the potential to unlock significant innovation, their increasing use also introduces inherent risks. Unaddressed model risks can lead to substantial financial losses, regulatory issues, and reputational harm. To address these concerns, we need a proactive approach to risk management.

This paper from the CSA AI Technology and Risk Working Group discusses the importance of AI model risk management (MRM). It showcases how model risk management contributes to responsible AI development and deployment and explores the core components of the framework. These components work together to identify and mitigate risks and improve model development through a continuous feedback loop.

Key Takeaways:
  • Benefits of a comprehensive AI risk management framework, including the more responsible use of AI, enhanced transparency, informed decision-making processes, and robust model validation
  • Elements, benefits, and limitations of the four core components: AI model cards, data sheets, risk cards, and scenario planning
  • How to combine the core components into a comprehensive AI risk management framework
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Acknowledgements

Josh Buker
Josh Buker
Research Analyst, CSA

Josh Buker

Research Analyst, CSA

Chris Kirschke
Chris Kirschke
Cloud Portfolio Information Security Officer at Albertsons Companies

Chris Kirschke

Cloud Portfolio Information Security Officer at Albertsons Companies

Security Leader with over 20+ years of experience across Financial Services, Streaming, Retail and IT Services with a heavy focus on Cloud, DevSecOps and Threat Modeling. Advises multiple security startups on Product Strategy, Alliances and Integrations. Sits on multiple Customer Advisory Boards helping to drive security product roadmaps, integrations and feature developments. Avid hockey player, backpacker and wine collector in his spare t...

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Jeffrey Ritter Headshot Missing
Jeffrey Ritter

Jeffrey Ritter

Michael Roza
Michael Roza
Risk, Audit, Control and Compliance Professional at EVC

Michael Roza

Risk, Audit, Control and Compliance Professional at EVC

Since 2012, Michael Roza has been a pivotal member of the Cloud Security Alliance (CSA) family. He has contributed to over 125 projects, as a Lead Author or Author/Contributor and many more as a Reviewer/Editor.

Michael's extensive contributions encompass critical areas including Artificial Intelligence, Zero Trust/Software Defined Perimeter, Internet of Things, Top Threats, Cloud Control Matrix, DevSecOps, and Key Management. His lea...

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Eric Tierling Headshot Missing
Eric Tierling

Eric Tierling

Mark Yanalitis Headshot Missing
Mark Yanalitis

Mark Yanalitis

Candy Alexander Headshot Missing
Candy Alexander

Candy Alexander

MJ Schwenger
MJ Schwenger
vCIO/CISO, RCP

MJ Schwenger

vCIO/CISO, RCP

Maria (MJ) Schwenger is a seasoned Information Security Executive. She leverages her deep expertise across cybersecurity, privacy & compliance, AI/Generative AI, cloud modernization, and software development to spearhead transformative digital journeys. Renowned for her leadership in integrating emerging technologies like AI/GenAI, DevSecOps/SRE, Blockchain, IoT/Edge, and cloud-native optimization, she seamlessly unlocks innovative business...

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Renata Budko Headshot Missing
Renata Budko

Renata Budko

Hadir Labib
Hadir Labib
Blue Team Manager

Hadir Labib

Blue Team Manager

Vani Mittal Headshot Missing
Vani Mittal

Vani Mittal

Nick Ray Headshot Missing
Nick Ray

Nick Ray

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