Introduction to Auditing AI Systems

Learn the fundamentals of how to adapt to and comply with AI regulation in this introductory course on auditing AI systems for bias and discrimination.

Introduction

• Welcome to the new world of AI audits

1. New Paradigm of AI Audits

• What is an AI audit?
• How are audits used?
• The state of AI legislation
• Ethics of scoring and classifying humans

2. Why Audit AI Systems?

• AI audit limitations and opportunities
• Development workflows
• AI performance
• Statistical parity

3. Data for AI Audits

• Data for auditing AI
• Sources of bias in data
• Types of bias and data sampling methods

4. Principles for AI Audits

• Why explainability matters
• Levels of transparency
• Responsible AI principles: Compliance
• Preparing for AI regulation

5. Model Audits

• Types of model audits
• Stages of a model audit
• Model audit: Home loans
• Auditing training data
• Audit outcomes: Explainability statements
• Continuous audits

Conclusion

• Generative AI
• Next steps