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AI Resilience: A Revolutionary Benchmarking Model for AI Safety
AI Resilience: A Revolutionary Benchmarking Model for AI Safety
Who it's for:
  • C-Suite
  • Cloud security and AI professionals
  • Compliance managers

AI Resilience: A Revolutionary Benchmarking Model for AI Safety

The rapid evolution of Artificial Intelligence (AI) promises unprecedented advances. However, as AI systems become increasingly sophisticated, they also pose escalating risks. Past incidents, from biased algorithms in healthcare to malfunctioning autonomous vehicles, starkly highlight the consequences of AI failures. Current regulatory frameworks often struggle to keep pace with the speed of technological innovation, leaving businesses vulnerable to both reputational and operational damage. 

This publication from the CSA AI Governance & Compliance Working Group addresses the urgent need for a more holistic perspective on AI governance and compliance, empowering decision makers to establish AI governance frameworks that ensure ethical AI development, deployment, and use. The publication explores the foundations of AI, examines issues and case studies across critical industries, and provides practical guidance for responsible implementation. It concludes with a novel benchmarking approach that compares the (r)evolution of AI with biology and introduces a thought-provoking concept of diversity to enhance the safety of AI technology.

Key Takeaways: 
  • The difference between governance and compliance 
  • The history and current landscape of AI technologies 
  • The landscape of AI training methods 
  • Major challenges with real-life AI applications
  • AI regulations and challenges in different industries
  • How to rate AI quality by using a benchmarking model inspired by evolution

The other two publications in this series discuss core AI security responsibilities and the AI regulatory environment. By outlining recommendations across these key areas of security and compliance in 3 targeted publications, this series guides enterprises to fulfill their obligations for responsible and secure AI development and deployment.
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