Security and Governance Framework for GenAI | Protect GenAI

Unleash the power of Generative AI safely! Discover how Generative AI Security Frameworks, Governance Frameworks, and Guardrails can protect your GenAI projects. Learn proven approaches and access resources (slides) to ensure responsible and secure GenAI development and deployment.


Generative AI, with its immense potential, requires robust security frameworks to mitigate risks. Here's a quick breakdown of key elements:


Generative AI Security Framework: This framework outlines best practices for securing generative AI systems throughout their lifecycle, from data collection to deployment. It addresses concerns like model manipulation, bias, and adversarial attacks. A good example is Google's Secure AI Framework SAIF which focuses on building secure-by-default generative AI.


Governance Framework: This framework establishes policies and procedures for the responsible development and use of generative AI. It ensures compliance with regulations and ethical considerations. Think of it as the rulebook for generative AI projects.


Guardrails: These are specific controls within the governance framework that limit or prevent risky behaviors. Imagine guardrails on a bridge - they provide boundaries to keep generative AI use on track. They might include things like data access restrictions or bias detection algorithms.

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