Juan M. Lavista Ferres, William B. Weeks

AI for Good (eBook, PDF)

Applications in Sustainability, Humanitarian Action, and Health

• Format: PDF

Produktbeschreibung

FOREWORD BY BRAD SMITH, VICE CHAIR AND PRESIDENT OF MICROSOFT

Discover how AI leaders and researchers are using AI to transform the world for the better


In AI for Good: Applications in Sustainability, Humanitarian Action, and Health, a team of veteran Microsoft AI researchers delivers an insightful and fascinating discussion of how one of the world's most recognizable software companies is tackling intractable social problems with the power of artificial intelligence (AI). In the book, you'll see real in-the-field examples of researchers using AI with replicable methods and reusable AI code to inspire your own uses.

The authors also provide:

• Easy-to-follow, non-technical explanations of what AI is and how it works
• Examples of the use of AI for scientists working on mitigating climate change, showing how AI can better analyze data without human bias, remedy pattern recognition deficits, and make use of satellite and other data on a scale never seen before so policy makers can make informed decisions
• Real applications of AI in humanitarian action, whether in speeding disaster relief with more accurate data for first responders or in helping address populations that have experienced adversity with examples of how analytics is being used to promote inclusivity
• A deep focus on AI in healthcare where it is improving provider productivity and patient experience, reducing per-capita healthcare costs, and increasing care access, equity, and outcomes
• Discussions of the future of AI in the realm of social benefit organizations and efforts

Beyond the work of the authors, contributors, and researchers highlighted in the book, AI For Good begins with a foreword from Microsoft Vice Chair and President Brad Smith. There, Smith details the Microsoft rationale behind the creation of and continued investment in the AI for Good Lab. The vision is one of hope with AI saving lives in disasters, improving health care globally, and Microsoft's mission to make sure AI's benefits are available to all.

An essential guide to impactful social change with artificial intelligence, AI for Good is a must-read resource for technical and non-technical professionals interested in AI's social potential, as well as policymakers, regulators, NGO professionals, and non-profit volunteers.

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Produktdetails

• Verlag: For Dummies
• Seitenzahl: 432
• Erscheinungstermin: 23. Januar 2024
• Englisch
• ISBN-13: 9781394235896
• Artikelnr.: 69861374

Autorenporträt

JUAN M. LAVISTA FERRES, PHD, MS, is the Microsoft Chief Data Scientist and the Director of the AI for Good Lab at Microsoft.

WILLIAM B. WEEKS, MD, PHD, MBA, is the Director of AI for Health at Microsoft.

Inhaltsangabe

Foreword xix
Brad Smith, Vice Chair and President of Microsoft

Introduction xxiii
William B. Weeks, MD, PhD, MBA

A Call to Action xxvi
Juan M. Lavista Ferres

Part I: Primer on Artificial Intelligence and Machine Learning 1

Chapter 1: What Is Artificial Intelligence and How Can It Be Used for Good? 3
William B. Weeks

What Is Artificial Intelligence? 5

What If Artificial Intelligence Were Used to Improve Societal Good? 6

Chapter 2: Artificial Intelligence: Its Application and Limitations 9
Juan M. Lavista Ferres

Why Now? 11

The Challenges and Lessons Learned from Using Artificial Intelligence 13

Large Language Models 24

Chapter 3: Commonly Used Processes and Terms 33
William B. Weeks and Juan M. Lavista Ferres

Common Processes 33

Commonly Used Measures 35

The Structure of the Book 37

Part II: Sustainability 39

Chapter 4: Deep Learning with Geospatial Data 41
Caleb Robinson, Anthony Ortiz, Simone Fobi Nsutezo, Amrita Gupta, Girmaw Adebe Tadesse, Akram Zaytar, and Gilles Quentin Hacheme

Executive Summary 41

Why Is This Important? 42

Methods Used 43

Findings 44

Discussion 46

What We Learned 46

Chapter 5: Nature-Dependent Tourism 48
Darren Tanner and Mark Spalding

Executive Summary 48

Why Is This Important? 49

Methods Used 50

Findings 52

Discussion 52

What We Learned 55

Chapter 6: Wildlife Bioacoustics Detection 57
Zhongqi Miao

Executive Summary 57

Why Is This Important? 58

Methods Used 59

Findings 61

Discussion 64

What We Learned 65

Chapter 7: Using Satellites to Monitor Whales from Space 66
Caleb Robinson, Kim Goetz, and Christin Khan

Executive Summary 66

Why Is This Important? 67

Methods Used 67

Findings 69

Discussion 70

What We Learned 71

Chapter 8: Social Networks of Giraffes 73
Juan M. Lavista Ferres, Derek Lee, and Monica Bond

Executive Summary 73

Why Is This Important? 75

Methods Used 78

Findings 79

Discussion 84

What We Learned 86

Chapter 9: Data-driven Approaches to Wildlife Conflict Mitigation in the Maasai Mara 88
Akram Zaytar, Gilles Hacheme, Girmaw Abebe Tadesse, Caleb Robinson, Rahul Dodhia, and Juan M. Lavista Ferres

Executive Summary 88

Why Is This Important? 90

Methods Used 90

Findings 92

Discussion 94

What We Learned 96

Chapter 10: Mapping Industrial Poultry Operations at Scale 97
Caleb Robinson and Daniel Ho

Executive Summary 97

Why Is This Important? 98

Methods Used 98

Findings 100

Discussion 102

What We Learned 104

Chapter 11: Identifying Solar Energy Locations in India 105
Anthony Ortiz and Joseph Kiesecker

Executive Summary 105

Why Is This Important? 106

Methods Used 107

Findings 109

Discussion 110

What We Learned 111

Chapter 12: Mapping Glacial Lakes 113
Anthony Ortiz, Kris Sankaran, Finu Shrestha, Tenzing Chogyal Sherpa, and Mir Matin

Executive Summary 113

Why Is This Important? 114

Methods Used 115

Findings 117

Discussion 120

What We Learned 123

Chapter 13: Forecasting and Explaining Degradation of Solar Panels with AI 124
Felipe Oviedo and Tonio Buona