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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
- 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
Research Analyst, CSA
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...
Jeffrey Ritter
Michael Roza
Risk, Audit, Control and Compliance Professional at EVC
Eric Tierling
Mark Yanalitis
Candy Alexander
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...
Renata Budko
Hadir Labib
Blue Team Manager
Vani Mittal
Nick Ray
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