Demystifying AI Audits: A Practical Guide to Compliance
Complex machine learning (ML) models are often referred to as “black boxes” and even the data scientists that trained the models may not be able to explain the underlying algorithmic decisions. While this lack of visibility is a reality, it doesn’t mean that the entire AI and ML lifecycle is unknowable and unauditable. In fact, AI and ML can and should be part of a comprehensive compliance program. In this presentation, we’ll explore where and how InfoSec, compliance, and audit professionals can assess AI models as well as the risk posed by AI through third parties. We will explain the differences between assessing DevOps and MLOps and show where process inventory, policy management, MLBoMs (machine learning bill of materials), and supply chain safety can be applied to provide visibility and audibility to an ML-aware audit program.
- Diana Kelley CISO Protect AI
- Diana Kelley CISO Protect AI