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The AI Product Manager's Handbook

You're reading from   The AI Product Manager's Handbook Develop a product that takes advantage of machine learning to solve AI problems

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Product type Paperback
Published in Feb 2023
Publisher Packt
ISBN-13 9781804612934
Length 250 pages
Edition 1st Edition
Languages
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Author (1):
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Irene Bratsis Irene Bratsis
Author Profile Icon Irene Bratsis
Irene Bratsis
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Table of Contents (19) Chapters Close

Preface 1. Part 1 – Lay of the Land – Terms, Infrastructure, Types of AI, and Products Done Well
2. Chapter 1: Understanding the Infrastructure and Tools for Building AI Products FREE CHAPTER 3. Chapter 2: Model Development and Maintenance for AI Products 4. Chapter 3: Machine Learning and Deep Learning Deep Dive 5. Chapter 4: Commercializing AI Products 6. Chapter 5: AI Transformation and Its Impact on Product Management 7. Part 2 – Building an AI-Native Product
8. Chapter 6: Understanding the AI-Native Product 9. Chapter 7: Productizing the ML Service 10. Chapter 8: Customization for Verticals, Customers, and Peer Groups 11. Chapter 9: Macro and Micro AI for Your Product 12. Chapter 10: Benchmarking Performance, Growth Hacking, and Cost 13. Part 3 – Integrating AI into Existing Non-AI Products
14. Chapter 11: The Rising Tide of AI 15. Chapter 12: Trends and Insights across Industry 16. Chapter 13: Evolving Products into AI Products 17. Index 18. Other Books You May Enjoy

Preface

It’s hard to come across anyone that doesn’t have strong opinions and reactions about AI these days. I’ve witnessed my own feelings and conclusions about it ebb and flow as the years have gone on. When I was a student, I felt a tremendous amount of excitement and optimism about where AI, and the fourth industrial revolution that accompanies it, would take us. That was quickly tempered when I started my book club, and I started a monthly practice of reading books about how bias and dependence on AI were compromising our lives in seen and unseen ways. Then, I started moderating events, where I brought together people from virtually every corner of AI and machine learning, who spoke not just on how they’re leveraging this technology in their own work but on their own beliefs about how AI will impact us in the future.

This brings us to one of the greatest debates we find ourselves returning to with every major advancement in technology. Do we dare adopt powerful technology even when we’re aware of the risks? As far as I see it, we don’t have a choice, and the debate is only an illusion we indulge ourselves in. AI is here to stay, and nihilistic fears about it won’t save us from any harm it may cause. Pandora’s box is open, and as we peer into what remains of it, we find that hope springs eternal.

AI is holding up a mirror to our biases and inequalities, and so far, it’s not a flattering reflection. It’s my hope that, with time, we will learn how to adopt AI responsibly in order to minimize its harm and optimize its greatest contributions to our modern civilization. I wanted to write a book about AI product management because it’s the makers of products that bring nebulous ideas into the “real” world. Getting into the details about how to ideate, build, manage and maintain AI products with integrity, to the best of my ability, is the greatest contribution I can make to this field at this present moment. It’s been an honor to write this book.

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