Foreword
Greg Stuart
Preface
Introduction
Part 1: The Fundamentals of Artificial Intelligence
1. Artificial Intelligence Is Not Human Intelligence
2. How AI Fits Patterns
3. How AI Uses Gradient Descent
4. Edge Cases, Compression, and the Limits of Associative Intelligence
5. Precision, Input Control and the Rationale for Decisions
6. Assessing Risk in AI Applications
Part 2: Opportunities, Risks, Countermeasures, and & Critical Questions
7. Case Studies in AI: The AI Revolution and the Sales and Marketing Case Studies
8. Case Studies in AI: Translations, MRIs, Fraud Detection, Autonomous Vehicles, and the Impact of AI on Labor
9. Case Studies in AI: Using AI to Trade in Markets
10. Cases Studies in AI: Bias in Facial Recognition, Hiring and Advertising
11. The Conundrum
Acknowledgements
Endnotes
Index