{"product_id":"ai-for-good-applications-in-sustainability-humanitarian-action-and-health-hardback-9781394235872","title":"AI for Good; Applications in Sustainability, Humanitarian Action, and Health (Hardback) 9781394235872","description":"\u003cfont face=\"Georgia\"\u003e\r\n\u003cp\u003e\u003cfont size=\"6\"\u003eAI for Good\u003c\/font\u003e\u003cbr\u003e\r\n\u003cfont size=\"5\"\u003eApplications in Sustainability, Humanitarian Action, and Health\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\r\n\u003cp\u003e\u003cfont size=\"4\"\u003eJuan M. Lavista Ferres (Author), William B. Weeks (Author), Brad Smith (Foreword by)\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e9781394235872, Wiley\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eHardback, published 9 April 2024\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e432 pages\u003cbr\u003e23.1 x 16.3 x 3.3 cm, 0.658 kg\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\r\n\r\n\u003cp align=\"justify\"\u003e\u003cstrong\u003e\u003cfont size=\"3\"\u003e\u003cp\u003e\u003cb\u003eFOREWORD BY BRAD SMITH, VICE CHAIR AND PRESIDENT OF MICROSOFT\u003cbr\u003e\u003cbr\u003eDiscover how AI leaders and researchers are using AI to transform the world for the better\u003cbr\u003e\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eIn\u003ci\u003e AI for Good: Applications in Sustainability, Humanitarian Action, and Health\u003c\/i\u003e, 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.\u003c\/p\u003e \u003cp\u003eThe authors also provide:\u003c\/p\u003e \u003cul\u003e \u003cli\u003eEasy-to-follow, non-technical explanations of what AI is and how it works\u003c\/li\u003e \u003cli\u003eExamples 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\u003c\/li\u003e \u003cli\u003eReal 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\u003c\/li\u003e \u003cli\u003eA 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\u003c\/li\u003e \u003cli\u003eDiscussions of the future of AI in the realm of social benefit organizations and efforts\u003c\/li\u003e \u003c\/ul\u003e Beyond the work of the authors, contributors, and researchers highlighted in the book, \u003ci\u003eAI For Good \u003c\/i\u003ebegins 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. \u003cp\u003eAn essential guide to impactful social change with artificial intelligence, \u003ci\u003eAI for Good\u003c\/i\u003e 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.\u003c\/p\u003e\u003c\/font\u003e\u003c\/strong\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e\u003cp\u003eForeword xix\u003cbr\u003e \u003ci\u003eBrad Smith, Vice Chair and President of Microsoft\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eIntroduction xxiii\u003cb\u003e\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eWilliam B. Weeks, MD, PhD, MBA\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eA Call to Action xxvi\u003cbr\u003e\u003ci\u003eJuan M. Lavista Ferres\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart I: Primer on Artificial Intelligence and Machine Learning 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 1: What Is Artificial Intelligence and How Can It Be Used for Good? 3\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eWilliam B. Weeks\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eWhat Is Artificial Intelligence? 5\u003c\/p\u003e \u003cp\u003eWhat If Artificial Intelligence Were Used to Improve Societal Good? 6\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 2: Artificial Intelligence: Its Application and Limitations 9\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eJuan M. Lavista Ferres\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eWhy Now? 11\u003c\/p\u003e \u003cp\u003eThe Challenges and Lessons Learned from Using Artificial Intelligence 13\u003c\/p\u003e \u003cp\u003eLarge Language Models 24\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 3: Commonly Used Processes and Terms 33\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eWilliam B. Weeks and Juan M. Lavista Ferres\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eCommon Processes 33\u003c\/p\u003e \u003cp\u003eCommonly Used Measures 35\u003c\/p\u003e \u003cp\u003eThe Structure of the Book 37\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart II: Sustainability 39\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 4: Deep Learning with Geospatial Data 41\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eCaleb Robinson, Anthony Ortiz, Simone Fobi Nsutezo, Amrita Gupta, Girmaw Adebe Tadesse, Akram Zaytar, and Gilles Quentin Hacheme\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eExecutive Summary 41\u003c\/p\u003e \u003cp\u003eWhy Is This Important? 42\u003c\/p\u003e \u003cp\u003eMethods Used 43\u003c\/p\u003e \u003cp\u003eFindings 44\u003c\/p\u003e \u003cp\u003eDiscussion 46\u003c\/p\u003e \u003cp\u003eWhat We Learned 46\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 5: Nature-Dependent Tourism 48\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eDarren Tanner and Mark Spalding\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eExecutive Summary 48\u003c\/p\u003e \u003cp\u003eWhy Is This Important? 49\u003c\/p\u003e \u003cp\u003eMethods Used 50\u003c\/p\u003e \u003cp\u003eFindings 52\u003c\/p\u003e \u003cp\u003eDiscussion 52\u003c\/p\u003e \u003cp\u003eWhat We Learned 55\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 6: Wildlife Bioacoustics Detection 57\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eZhongqi Miao\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eExecutive Summary 57\u003c\/p\u003e \u003cp\u003eWhy Is This Important? 58\u003c\/p\u003e \u003cp\u003eMethods Used 59\u003c\/p\u003e \u003cp\u003eFindings 61\u003c\/p\u003e \u003cp\u003eDiscussion 64\u003c\/p\u003e \u003cp\u003eWhat We Learned 65\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 7: Using Satellites to Monitor Whales from Space 66\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eCaleb Robinson, Kim Goetz, and Christin Khan\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eExecutive Summary 66\u003c\/p\u003e \u003cp\u003eWhy Is This Important? 67\u003c\/p\u003e \u003cp\u003eMethods Used 67\u003c\/p\u003e \u003cp\u003eFindings 69\u003c\/p\u003e \u003cp\u003eDiscussion 70\u003c\/p\u003e \u003cp\u003eWhat We Learned 71\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 8: Social Networks of Giraffes 73\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eJuan M. Lavista Ferres, Derek Lee, and Monica Bond\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eExecutive Summary 73\u003c\/p\u003e \u003cp\u003eWhy Is This Important? 75\u003c\/p\u003e \u003cp\u003eMethods Used 78\u003c\/p\u003e \u003cp\u003eFindings 79\u003c\/p\u003e \u003cp\u003eDiscussion 84\u003c\/p\u003e \u003cp\u003eWhat We Learned 86\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 9: Data-driven Approaches to Wildlife Conflict Mitigation in the Maasai Mara 88\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eAkram Zaytar, Gilles Hacheme, Girmaw Abebe Tadesse, Caleb Robinson, Rahul Dodhia, and Juan M. Lavista Ferres\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eExecutive Summary 88\u003c\/p\u003e \u003cp\u003eWhy Is This Important? 90\u003c\/p\u003e \u003cp\u003eMethods Used 90\u003c\/p\u003e \u003cp\u003eFindings 92\u003c\/p\u003e \u003cp\u003eDiscussion 94\u003c\/p\u003e \u003cp\u003eWhat We Learned 96\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 10: Mapping Industrial Poultry Operations at Scale 97\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eCaleb Robinson and Daniel Ho\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eExecutive Summary 97\u003c\/p\u003e \u003cp\u003eWhy Is This Important? 98\u003c\/p\u003e \u003cp\u003eMethods Used 98\u003c\/p\u003e \u003cp\u003eFindings 100\u003c\/p\u003e \u003cp\u003eDiscussion 102\u003c\/p\u003e \u003cp\u003eWhat We Learned 104\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 11: Identifying Solar Energy Locations in India 105\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eAnthony Ortiz and Joseph Kiesecker\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eExecutive Summary 105\u003c\/p\u003e \u003cp\u003eWhy Is This Important? 106\u003c\/p\u003e \u003cp\u003eMethods Used 107\u003c\/p\u003e \u003cp\u003eFindings 109\u003c\/p\u003e \u003cp\u003eDiscussion 110\u003c\/p\u003e \u003cp\u003eWhat We Learned 111\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 12: Mapping Glacial Lakes 113\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eAnthony Ortiz, Kris Sankaran, Finu Shrestha, Tenzing Chogyal Sherpa, and Mir Matin\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eExecutive Summary 113\u003c\/p\u003e \u003cp\u003eWhy Is This Important? 114\u003c\/p\u003e \u003cp\u003eMethods Used 115\u003c\/p\u003e \u003cp\u003eFindings 117\u003c\/p\u003e \u003cp\u003eDiscussion 120\u003c\/p\u003e \u003cp\u003eWhat We Learned 123\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 13: Forecasting and Explaining Degradation of Solar Panels with AI 124\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eFelipe Oviedo and Tonio Buonassisi\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eExecutive Summary 124\u003c\/p\u003e \u003cp\u003eWhy Is This Important? 125\u003c\/p\u003e \u003cp\u003eMethods Used 126\u003c\/p\u003e \u003cp\u003eFindings 128\u003c\/p\u003e \u003cp\u003eDiscussion 131\u003c\/p\u003e \u003cp\u003eWhat We Learned 132\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart III: Humanitarian Action 133\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 14: Post-Disaster Building Damage Assessment 135\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eShahrzad Gholami\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eExecutive Summary 135\u003c\/p\u003e \u003cp\u003eWhy Is This Important? 136\u003c\/p\u003e \u003cp\u003eMethods Used 137\u003c\/p\u003e \u003cp\u003eFindings 140\u003c\/p\u003e \u003cp\u003eDiscussion 143\u003c\/p\u003e \u003cp\u003eWhat We Learned 144\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 15: Dwelling Type Classification 146\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eMd Nasir and Anshu Sharma\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eExecutive Summary 146\u003c\/p\u003e \u003cp\u003eWhy Is This Important? 147\u003c\/p\u003e \u003cp\u003eMethods Used 148\u003c\/p\u003e \u003cp\u003eFindings 149\u003c\/p\u003e \u003cp\u003eDiscussion 151\u003c\/p\u003e \u003cp\u003eWhat We Learned 153\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 16: Damage Assessment Following the 2023 Earthquake in Turkey 155\u003c\/b\u003e\u003cbr\u003e \u003ci\u003eCaleb Robinson, Simone Fobi, and Anthony Ortiz\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eExecutive Summary 155\u003c\/p\u003e \u003cp\u003eWhy Is This Important? 156\u003c\/p\u003e \u003cp\u003eMethods Used 157\u003c\/p\u003e \u003cp\u003eFindings 159\u003c\/p\u003e \u003cp\u003eDiscussion 162\u003c\/p\u003e \u003cp\u003eWhat We Learned 162\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 17: Food Security Analysis 164\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eShahrzad Gholami, Erwin w. Knippenberg, and James Campbell\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eExecutive Summary 164\u003c\/p\u003e \u003cp\u003eWhy Is This Important? 165\u003c\/p\u003e \u003cp\u003eMethods Used 166\u003c\/p\u003e \u003cp\u003eFindings 171\u003c\/p\u003e \u003cp\u003eDiscussion 175\u003c\/p\u003e \u003cp\u003eWhat We Learned 177\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 18: BankNote-Net: Open Dataset for Assistive Universal Currency Recognition 178\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eFelipe Oviedo and Saqib Shaikh\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eExecutive Summary 178\u003c\/p\u003e \u003cp\u003eWhy Is This Important? 179\u003c\/p\u003e \u003cp\u003eMethods Used 180\u003c\/p\u003e \u003cp\u003eFindings 182\u003c\/p\u003e \u003cp\u003eDiscussion 185\u003c\/p\u003e \u003cp\u003eWhat We Learned 186\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 19: Broadband Connectivity 187\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eMayana Pereira, Amit Misra, and Allen Kim\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eExecutive Summary 187\u003c\/p\u003e \u003cp\u003eWhy Is This Important? 188\u003c\/p\u003e \u003cp\u003eMethods Used 189\u003c\/p\u003e \u003cp\u003eFindings 190\u003c\/p\u003e \u003cp\u003eDiscussion 192\u003c\/p\u003e \u003cp\u003eWhat We Learned 193\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 20: Monitoring the Syrian War with Natural Language Processing 194\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eRahul Dodhia and Michael Scholtens\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eExecutive Summary 194\u003c\/p\u003e \u003cp\u003eWhy Is This Important? 195\u003c\/p\u003e \u003cp\u003eMethods Used 197\u003c\/p\u003e \u003cp\u003eFindings 198\u003c\/p\u003e \u003cp\u003eDiscussion 200\u003c\/p\u003e \u003cp\u003eWhat We Learned 200\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 21: The Proliferation of Misinformation Online 202\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eWill Fein, Mayana Pereira, Jane Wang, Kevin Greene, Lucas Meyer, Rahul Dodhia, and Jacob Shapiro\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eExecutive Summary 202\u003c\/p\u003e \u003cp\u003eWhy Is This Important? 203\u003c\/p\u003e \u003cp\u003eMethods Used 204\u003c\/p\u003e \u003cp\u003eFindings 208\u003c\/p\u003e \u003cp\u003eDiscussion 210\u003c\/p\u003e \u003cp\u003eWhat We Learned 211\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 22: Unlocking the Potential of AI with Open Data 213\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eAnthony Cintron Roman and Kevin Xu\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eExecutive Summary 213\u003c\/p\u003e \u003cp\u003eWhy Is This Important? 214\u003c\/p\u003e \u003cp\u003eMethods Used 215\u003c\/p\u003e \u003cp\u003eFindings 216\u003c\/p\u003e \u003cp\u003eDiscussion 219\u003c\/p\u003e \u003cp\u003eWhat We Learned 220\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart IV: Health 222\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 23: Detecting Middle Ear Disease 225\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eYixi Xu and Al-Rahim Habib\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eExecutive Summary 225\u003c\/p\u003e \u003cp\u003eWhy Is This Important? 226\u003c\/p\u003e \u003cp\u003eMethods Used 227\u003c\/p\u003e \u003cp\u003eFindings 230\u003c\/p\u003e \u003cp\u003eDiscussion 232\u003c\/p\u003e \u003cp\u003eWhat We Learned 233\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 24: Detecting Leprosy in Vulnerable Populations 235\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eYixi Xu and Ann Aerts\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eExecutive Summary 235\u003c\/p\u003e \u003cp\u003eWhy Is This Important? 236\u003c\/p\u003e \u003cp\u003eMethods Used 237\u003c\/p\u003e \u003cp\u003eFindings 238\u003c\/p\u003e \u003cp\u003eDiscussion 239\u003c\/p\u003e \u003cp\u003eWhat We Learned 240\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 25: Automated Segmentation of Prostate Cancer Metastases 241\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eYixi Xu\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eExecutive Summary 241\u003c\/p\u003e \u003cp\u003eWhy Is This Important? 242\u003c\/p\u003e \u003cp\u003eMethods Used 243\u003c\/p\u003e \u003cp\u003eFindings 245\u003c\/p\u003e \u003cp\u003eDiscussion 249\u003c\/p\u003e \u003cp\u003eWhat We Learned 250\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 26: Screening Premature Infants for Retinopathy of Prematurity in Low-Resource Settings 252\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eAnthony Ortiz, Juan M. Lavista Ferres, Guillermo Monteoliva, and Maria Ana Martinez-Castellanos\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eExecutive Summary 252\u003c\/p\u003e \u003cp\u003eWhy Is This Important? 253\u003c\/p\u003e \u003cp\u003eMethods Used 255\u003c\/p\u003e \u003cp\u003eFindings 259\u003c\/p\u003e \u003cp\u003eDiscussion 260\u003c\/p\u003e \u003cp\u003eWhat We Learned 262\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 27: Long-Term Effects of COVID-19 264\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eMeghana Kshirsagar and Sumit Mukherjee\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eExecutive Summary 264\u003c\/p\u003e \u003cp\u003eWhy Is This Important? 265\u003c\/p\u003e \u003cp\u003eMethods Used 267\u003c\/p\u003e \u003cp\u003eFindings 269\u003c\/p\u003e \u003cp\u003eDiscussion 274\u003c\/p\u003e \u003cp\u003eWhat We Learned 275\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 28: Using Artificial Intelligence to Inform Pancreatic Cyst Management 277\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eJuan M. Lavista Ferres, Felipe Oviedo, William B. Weeks, Elliot Fishman, and Anne Marie Lennon\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eExecutive Summary 277\u003c\/p\u003e \u003cp\u003eWhy Is This Important? 278\u003c\/p\u003e \u003cp\u003eMethods Used 279\u003c\/p\u003e \u003cp\u003eFindings 281\u003c\/p\u003e \u003cp\u003eDiscussion 283\u003c\/p\u003e \u003cp\u003eWhat We Learned 285\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 29: NLP-Supported Chatbot for Cigarette Smoking Cessation 287\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eJonathan B. Bricker, Brie Sullivan, Marci Strong, Anusua Trivedi, Thomas Roca, James Jacoby, Margarita Santiago-Torres, and Juan M. Lavista Ferres\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eExecutive Summary 287\u003c\/p\u003e \u003cp\u003eWhy Is This Important? 289\u003c\/p\u003e \u003cp\u003eMethods Used 291\u003c\/p\u003e \u003cp\u003eFindings 294\u003c\/p\u003e \u003cp\u003eDiscussion 299\u003c\/p\u003e \u003cp\u003eWhat We Learned 301\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 30: Mapping Population Movement Using Satellite Imagery 303\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eTammy Glazer, Gilles Hacheme, Amy Michaels, and Christopher J.L. Murray\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eExecutive Summary 303\u003c\/p\u003e \u003cp\u003eWhy Is This Important? 304\u003c\/p\u003e \u003cp\u003eMethods Used 306\u003c\/p\u003e \u003cp\u003eFindings 312\u003c\/p\u003e \u003cp\u003eDiscussion 315\u003c\/p\u003e \u003cp\u003eWhat We Learned 317\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 31: The Promise of AI and Generative Pre-Trained Transformer Models in Medicine 318\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eWilliam B. Weeks\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eWhat Are GPT Models and What Do They Do? 318\u003c\/p\u003e \u003cp\u003eGPT Models in Medicine 319\u003c\/p\u003e \u003cp\u003eConclusion 327\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart V: Summary, Looking Forward, And Additional Resources 329\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eEpilogue: Getting Good at AI for Good 331\u003cbr\u003e \u003ci\u003eThe AI for Good Lab\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eCommunication 332\u003c\/p\u003e \u003cp\u003eData 333\u003c\/p\u003e \u003cp\u003eModeling 335\u003c\/p\u003e \u003cp\u003eImpact 337\u003c\/p\u003e \u003cp\u003eConclusion 340\u003c\/p\u003e \u003cp\u003eKey Takeaways 340\u003c\/p\u003e \u003cp\u003eAI and Satellites: Critical Tools to Help Us with Planetary Emergencies 342\u003cbr\u003e \u003ci\u003eWill Marshall and Andrew Zolli\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eAmazing Things in the Amazon 344\u003c\/p\u003e \u003cp\u003eQuick Help Saving Lives in Disaster Response 346\u003c\/p\u003e \u003cp\u003eAdditional Resources 348\u003cbr\u003e \u003ci\u003eLucia Ronchi Darre\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eEndnotes 351\u003c\/p\u003e \u003cp\u003eAcknowledgments 353\u003c\/p\u003e \u003cp\u003eAbout the Editors 358\u003c\/p\u003e \u003cp\u003eAbout the Authors 361\u003c\/p\u003e \u003cp\u003eMicrosoft’s AI for Good Lab 361\u003c\/p\u003e \u003cp\u003eCollaborators 369\u003c\/p\u003e \u003cp\u003eIndex 382\u003c\/p\u003e\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eSubject Areas: Computer science [\u003ca title=\"See our other books on Computer science\" href=\"https:\/\/freshlyprintedbooks.co.uk\/search?q=%22Computer%20science%20%5BUY%5D%22\"\u003eUY\u003c\/a\u003e]\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\u003c\/font\u003e","brand":"Wiley","offers":[{"title":"Brand New","offer_id":52173700595992,"sku":"9781394235872","price":17.37,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0730\/2037\/5320\/files\/9781394235872.jpg?v=1781167486","url":"https:\/\/freshlyprintedbooks.co.uk\/products\/ai-for-good-applications-in-sustainability-humanitarian-action-and-health-hardback-9781394235872","provider":"Freshly Printed Books","version":"1.0","type":"link"}