AI Security Podcast Exploring Top AI Security Frameworks
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Jul 11, 2024 The podcast explores various AI security frameworks like Databricks, NIST, and OWASP Top 10, comparing their key components and practical implementation strategies. It discusses the challenges of selecting the right framework, AI risk management, and the importance of governance and collaboration. The episode also touches on using Chat GPT for document analysis, Google AI Studio, and the progression of AI proficiency.
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NIST AI Framework Too Broad
- Caleb thinks NIST AI risk framework tries to be too broad by applying to everyone.
- He suggests separate frameworks for cybersecurity, engineers, and governance/compliance.
Combining NIST and Databricks
- Ashish appreciates Databricks' framework for its separation of model types and shared responsibility model.
- He suggests using NIST as a base and incorporating Databricks' methodology for component analysis.
Actionable AI Security Strategy
- Start by establishing a baseline using OWASP Top 10.
- Build a risk management framework using NIST and consider Databricks' methodology.