Table of Contents
- A Primer on Explainable and Ethical AI
- Algorithms Gone Wild - Bias's Greatest Hits
- Opening the Algorithmic Blackbox
- Operationalizing Model Monitoring
- Model Governance - Audit, and Compliance Standards & Recommendations
- Enterprise Starter Kit for Fairness, Accountability and Transparency
- Interpretability Toolkits and Fairness Measures – AWS, GCP, Azure, and AIF 360
- Fairness in AI System with Microsoft FairLearn
- Fairness Assessment and Bias Mitigation with FairLearn and Responsible AI Toolbox
- Foundational Models and Azure OpenAI

