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 in the Sales and Marketing
8 - Case Studies in AI: Translations, MRIs, Fraud Detection, Autonomous Vehicles, and 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
Notes
Index
