John Wiley & Sons AI for Good Cover FOREWORD BY BRAD SMITH, VICE CHAIR AND PRESIDENT OF MICROSOFT Discover how AI leaders and researche.. Product #: 978-1-394-23587-2 Regular price: $25.14 $25.14 Auf Lager

AI for Good

Applications in Sustainability, Humanitarian Action, and Health

Lavista Ferres, Juan M. / Weeks, William B.


1. Auflage April 2024
432 Seiten, Hardcover

ISBN: 978-1-394-23587-2
John Wiley & Sons

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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.

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 Buonassisi

Executive Summary 124

Why Is This Important? 125

Methods Used 126

Findings 128

Discussion 131

What We Learned 132

Part III: Humanitarian Action 133

Chapter 14: Post-Disaster Building Damage Assessment 135
Shahrzad Gholami

Executive Summary 135

Why Is This Important? 136

Methods Used 137

Findings 140

Discussion 143

What We Learned 144

Chapter 15: Dwelling Type Classification 146
Md Nasir and Anshu Sharma

Executive Summary 146

Why Is This Important? 147

Methods Used 148

Findings 149

Discussion 151

What We Learned 153

Chapter 16: Damage Assessment Following the 2023 Earthquake in Turkey 155
Caleb Robinson, Simone Fobi, and Anthony Ortiz

Executive Summary 155

Why Is This Important? 156

Methods Used 157

Findings 159

Discussion 162

What We Learned 162

Chapter 17: Food Security Analysis 164
Shahrzad Gholami, Erwin w. Knippenberg, and James Campbell

Executive Summary 164

Why Is This Important? 165

Methods Used 166

Findings 171

Discussion 175

What We Learned 177

Chapter 18: BankNote-Net: Open Dataset for Assistive Universal Currency Recognition 178
Felipe Oviedo and Saqib Shaikh

Executive Summary 178

Why Is This Important? 179

Methods Used 180

Findings 182

Discussion 185

What We Learned 186

Chapter 19: Broadband Connectivity 187
Mayana Pereira, Amit Misra, and Allen Kim

Executive Summary 187

Why Is This Important? 188

Methods Used 189

Findings 190

Discussion 192

What We Learned 193

Chapter 20: Monitoring the Syrian War with Natural Language Processing 194
Rahul Dodhia and Michael Scholtens

Executive Summary 194

Why Is This Important? 195

Methods Used 197

Findings 198

Discussion 200

What We Learned 200

Chapter 21: The Proliferation of Misinformation Online 202
Will Fein, Mayana Pereira, Jane Wang, Kevin Greene, Lucas Meyer, Rahul Dodhia, and Jacob Shapiro

Executive Summary 202

Why Is This Important? 203

Methods Used 204

Findings 208

Discussion 210

What We Learned 211

Chapter 22: Unlocking the Potential of AI with Open Data 213
Anthony Cintron Roman and Kevin Xu

Executive Summary 213

Why Is This Important? 214

Methods Used 215

Findings 216

Discussion 219

What We Learned 220

Part IV: Health 222

Chapter 23: Detecting Middle Ear Disease 225
Yixi Xu and Al-Rahim Habib

Executive Summary 225

Why Is This Important? 226

Methods Used 227

Findings 230

Discussion 232

What We Learned 233

Chapter 24: Detecting Leprosy in Vulnerable Populations 235
Yixi Xu and Ann Aerts

Executive Summary 235

Why Is This Important? 236

Methods Used 237

Findings 238

Discussion 239

What We Learned 240

Chapter 25: Automated Segmentation of Prostate Cancer Metastases 241
Yixi Xu

Executive Summary 241

Why Is This Important? 242

Methods Used 243

Findings 245

Discussion 249

What We Learned 250

Chapter 26: Screening Premature Infants for Retinopathy of Prematurity in Low-Resource Settings 252
Anthony Ortiz, Juan M. Lavista Ferres, Guillermo Monteoliva, and Maria Ana Martinez-Castellanos

Executive Summary 252

Why Is This Important? 253

Methods Used 255

Findings 259

Discussion 260

What We Learned 262

Chapter 27: Long-Term Effects of COVID-19 264
Meghana Kshirsagar and Sumit Mukherjee

Executive Summary 264

Why Is This Important? 265

Methods Used 267

Findings 269

Discussion 274

What We Learned 275

Chapter 28: Using Artificial Intelligence to Inform Pancreatic Cyst Management 277
Juan M. Lavista Ferres, Felipe Oviedo, William B. Weeks, Elliot Fishman, and Anne Marie Lennon

Executive Summary 277

Why Is This Important? 278

Methods Used 279

Findings 281

Discussion 283

What We Learned 285

Chapter 29: NLP-Supported Chatbot for Cigarette Smoking Cessation 287
Jonathan B. Bricker, Brie Sullivan, Marci Strong, Anusua Trivedi, Thomas Roca, James Jacoby, Margarita Santiago-Torres, and Juan M. Lavista Ferres

Executive Summary 287

Why Is This Important? 289

Methods Used 291

Findings 294

Discussion 299

What We Learned 301

Chapter 30: Mapping Population Movement Using Satellite Imagery 303
Tammy Glazer, Gilles Hacheme, Amy Michaels, and Christopher J.L. Murray

Executive Summary 303

Why Is This Important? 304

Methods Used 306

Findings 312

Discussion 315

What We Learned 317

Chapter 31: The Promise of AI and Generative Pre-Trained Transformer Models in Medicine 318
William B. Weeks

What Are GPT Models and What Do They Do? 318

GPT Models in Medicine 319

Conclusion 327

Part V: Summary, Looking Forward, And Additional Resources 329

Epilogue: Getting Good at AI for Good 331
The AI for Good Lab

Communication 332

Data 333

Modeling 335

Impact 337

Conclusion 340

Key Takeaways 340

AI and Satellites: Critical Tools to Help Us with Planetary Emergencies 342
Will Marshall and Andrew Zolli

Amazing Things in the Amazon 344

Quick Help Saving Lives in Disaster Response 346

Additional Resources 348
Lucia Ronchi Darre

Endnotes 351

Acknowledgments 353

About the Editors 358

About the Authors 361

Microsoft's AI for Good Lab 361

Collaborators 369

Index 382
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.

J. M. Lavista Ferres, Microsoft; W. B. Weeks, Microsoft