Deploying AI responsibly is not the hard part — proving it to leadership, to auditors and to your customers is. Learn to deliberately try to break an AI system, then to build the evidence that says it is trustworthy enough to use.
Overview
Syllabus
Module 1
- Foundations: What Is AI Red Teaming, and Where Does It Fit in AI Assurance?
- What red teaming is and is not
- Where it sits in the AI assurance lifecycle
- The range of assurance activities
- The guidance the course draws on
- Who is involved
Module 2
- Planning and Scoping a Red-Team Engagement
- The engagement lifecycle
- Scoping to risk classification
- Setting red-team objectives
- Rules of engagement
- Team composition and deconfliction
Module 3
- Adversarial Testing Techniques for Machine Learning and Generative AI
- Matching technique to attack surface
- Manual versus automated and tool-assisted red teaming
- Generative AI probing techniques
- A preview of testing agentic and tool-using systems
- Telling red-team findings apart from ordinary bugs