Making AI Work for People : A Framework for Designing and Building Impactful AI-Powered Applications

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  • 電子書籍
  • ポイントキャンペーン

Making AI Work for People : A Framework for Designing and Building Impactful AI-Powered Applications

  • 著者名:Ibrahim, Asmaa
  • 価格 ¥8,143 (本体¥7,403)
  • Wiley(2026/03/02発売)
  • 春分の日の三連休!Kinoppy 電子書籍・電子洋書 全点ポイント30倍キャンペーン(~3/22)
  • ポイント 2,220pt (実際に付与されるポイントはご注文内容確認画面でご確認下さい)
  • 言語:ENG
  • ISBN:9781394392094
  • eISBN:9781394392100

ファイル: /

Description

Design AI applications that inspire trust, solve real problems, and put people first

Making AI Work for People: A Framework for Designing and Building Impactful AI-Powered Applications by Asmaa Ibrahim offers software engineers, product managers, and app designers a comprehensive framework for creating AI-powered applications that truly serve humanity. Ibrahim, Product Lead at Aleph Alpha, experienced ML team leader, AI-driven transformation expert, and leader of the team that created Gemini in Firebase, addresses the critical challenge facing today's tech professionals: how to harness AI's transformative potential while guaranteeing applications remain ethical, accessible, and aligned with human values.

This book explores cutting-edge innovation and provides the PRESS framework for designing human-first solutions that enhance – rather than replace – human capabilities. The PRESS framework is a systematic approach that guarantees AI-powered products are designed with five essential principles in mind: People-first design, Responsible in the core, Explainability and interpretability, Safety via benchmarking, and Sustainability and long-term impact. The author offers real-world case studies, proven development methodologies, and insights from successful AI implementations across the telecom, retail and other sectors, showing you how to navigate the complex landscape of AI integration while remaining laser-focused on user needs, trust, and ethics. The book covers everything from identifying opportunities for AI integration and measuring success with human-centered KPIs to scaling applications from MVP to production-grade systems.

Making AI Work for People also includes:

  • A comprehensive PRESS framework that guides every stage of AI product development from conception to deployment
  • Practical strategies for human-AI collaboration that amplify rather than replace human strengths and capabilities in real-world applications
  • A proven evaluation flywheel to guarantee that AI applications meet real user needs
  • Real-world case studies from telecom and retail demonstrating successful human-first AI implementations
  • Essential guidance for scaling AI applications while managing costs, infrastructure challenges, and long-term maintenance requirements

This book is essential for software engineers integrating AI into product development, product managers leading AI initiatives, and app designers creating human-AI interfaces who want to build applications that inspire trust and deliver genuine value through the PRESS framework. It's also a must-read for executives and managers of technical teams seeking crucial insights into systematic, responsible AI development practices that drive measurable business outcomes.

Table of Contents

About the Author xxi
Acknowledgments xxiii
Introduction xxv

Chapter 1 The Trillion-Dollar Challenge 1

Chapter 2 Understanding AI Economics and Assessing Your Readiness 25

Chapter 3 Identifying AI Opportunities Through the PRESS Lens 47

Chapter 4 Design Your People-First AI Systems 71

Chapter 5 Measuring Success by AI Type 97

Chapter 6 Continuous Evaluation 125

Chapter 7 Data Foundation Through PRESS 145

Chapter 8 Technology Choices at Scale 169

Chapter 9 Serving Optimization 195

Chapter 10 Building AI Literacy 215

Appendix A PRESS Readiness Assessment 237
Appendix B The Collaboration Mode Matrix 247
Appendix C North Star Selection 253
Appendix D Three-Layer Metrics 259
Appendix E Ten-Week Validation Timeline 265
Appendix F Technology Selection Matrix 275
Appendix G Continuous Evaluation Checklist 283
Appendix H Serving Optimization Checklist 289
Appendix I AI Literacy Self-Assessment 293

Glossary 299
Index 313

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