Ethics of scoring and classifying humans

Welcome to the new world of AI audits

What is an AI audit?

How are audits used?

The state of AI legislation

AI audit limitations and opportunities

Development workflows

AI performance

Statistical parity

Data for auditing AI

Sources of bias in data

Types of bias and data sampling methods

Why explainability matters

Levels of transparency

Responsible AI principles: Compliance

Preparing for AI regulation

Types of model audits

Stages of a model audit

Model audit: Home loans

Auditing training data

Audit outcomes: Explainability statements

Continuous audits

Generative AI

Next steps