As AI systems increasingly drive decisions in sensitive domains, ensuring robust authorization and access control is critical to safeguard data integrity, privacy, and compliance. This session explores the evolving challenges of securing AI systems and the best practices to mitigate risks.
We will delve into the principles of access control tailored for AI pipelines, and implementing fine-grained access policies for datasets, models, and APIs.
The discussion will also highlight cutting-edge trends such as zero-trust architectures for AI, AI-specific compliance requirements, and the ethical considerations of access governance. Real-world case studies will illustrate common pitfalls and innovative solutions, empowering participants to design secure and scalable AI systems that align with organizational objectives and regulatory standards.
