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.

Foreword xix
Brad Smith, Vice Chair and President of Microsoft Introduction xxiiiWilliam 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? 3William 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 9Juan 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 33William 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 41Caleb 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 48Darren 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 57Zhongqi 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 66Caleb 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 73Juan 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 88Akram 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 97Caleb 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 105Anthony 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 113Anthony 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 124Felipe 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 135Shahrzad 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 146Md 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 164Shahrzad 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 178Felipe 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 187Mayana 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 194Rahul 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 202Will 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 213Anthony 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 225Yixi 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 235Yixi 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 241Yixi 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 252Anthony 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 264Meghana 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 277Juan 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 287Jonathan 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 303Tammy 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 318William 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