
Premium
Opening Credits
1/1/2025
Introduction: The Trust Gap
1/1/2025
Chapter 1: The High Stakes of AI Failure
1/1/2025
Chapter 2: Deconstructing Bias It’s in the Data, Not the Code
1/1/2025
Chapter 3: Why AI Hallucinates and Confidently Lies
1/1/2025
Chapter 4: The Bias Audit Framework
1/1/2025
Chapter 5: De-biasing Data with Synthetic Oversampling
1/1/2025
Chapter 6: Algorithmic Fairness Implementing Fairlearn and IBM AIF360
1/1/2025
Chapter 7: Grounding AI with Retrieval-Augmented Generation (RAG)
1/1/2025
Chapter 8: Prompt Engineering for Truthfulness
1/1/2025
Chapter 9: The Red-Teaming Lab—Stress-Testing for Hallucinations
1/1/2025
Chapter 10: The AI Integrity Dashboard
1/1/2025
Chapter 11: The Human-in-the-Loop Framework
1/1/2025
Chapter 12: The Ethics and Compliance Blueprint
1/1/2025
About the author
1/1/2025
Ending Credits
1/1/2025