AI for good: applications in sustainability, humanitarian action, and health / edited by Juan M. Lavista Ferres, PhD, MS, William B. Weeks, MD, PhD, MBA; foreword by Brad Smith.
Material type:
TextLanguage: English Publisher: Hoboken, New Jersey: Wiley, 2024Copyright date: ©2024Description: xxix, 399 pages : illustrations, charts ; 23 cmContent type: - text
- still image
- unmediated
- volume
- 1394235879
- 9781394235872
| Item type | Home library | Collection | Shelving location | Call number | Materials specified | Status | Date due | Barcode | Item holds | |
|---|---|---|---|---|---|---|---|---|---|---|
Adult Book
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Dr. James Carlson Library | NonFiction | New | 006.3 A288 | Checked out | 05/28/2024 | 33111011129406 | |||
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Adult Book
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Main Library | NonFiction | New | 006.3 A288 | Available | 33111011345762 |
Enhanced descriptions from Syndetics:
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.
Includes index.
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 tacking intractable social problems with the power of artificial intelligence (AI). In the book, you'll learn about how climate change, illness and disease, and challenges to fundamental human rights are all being fought using replicable methods and reusable AI code.
Foreword / Brad Smith -- Introduction / William B. Weeks -- A call to action / Juan M. Lavista Ferres -- Chapter 1 What Is Artificial Intelligence and How Can It Be Used for Good? / William B. Weeks -- Chapter 2 Artificial Intelligence: Its Application and Limitations / Juan M. Lavista Ferres -- Chapter 3 Commonly Used Processes and Terms / William B. Weeks and Juan M. Lavista Ferres -- Chapter 4 Deep Learning with Geospatial Data / Caleb Robinson, Anthony Ortiz, Simone Fobi Nsutezo, Amrita Gupta, Girmaw Adebe Tadesse, Akram Zaytar, and Gilles Quentin Hacheme -- Chapter 5 Nature-Dependent Tourism / Darren Tanner and Mark Spalding -- Chapter 6 Wildlife Bioacoustics Detection / Zhongqi Miao -- Chapter 7 Using Satellites to Monitor Whales from Space / Caleb Robinson, Kim Goetz, and Christin Khan -- Chapter 8 Social Networks of Giraffes / Juan M. Lavista Ferres, Derek Lee, and Monica Bond -- Chapter 9 Data-driven Approaches to Wildlife Conflict Mitigation in the Maasai Mara / Akram Zaytar, Gilles Hacheme, Girmaw Abebe Tadesse, Caleb Robinson, Rahul Dodhia, and Juan M. Lavista Ferres -- Chapter 10 Mapping Industrial Poultry Operations at Scale / Caleb Robinson and Daniel Ho -- Chapter 11 Identifying Solar Energy Locations in India / Anthony Ortiz and Joseph Kiesecker -- Chapter 12 Mapping Glacial Lakes / Anthony Ortiz, Kris Sankaran, Finu Shrestha, Tenzing Chogyal Sherpa, and Mir Matin -- Chapter 13 Forecasting and Explaining Degradation of Solar Panels with AI / Felipe Oviedo and Tonio Buonassisi -- Chapter 14 Post-Disaster Building Damage Assessment / Shahrzad Gholami -- Chapter 15 Dwelling Type Classification / Md Nasir and Anshu Sharma -- Chapter 16 Damage Assessment Following the 2023 Earthquake in Turkey / Caleb Robinson, Simone Fobi, and Anthony Ortiz -- Chapter 17 Food Security Analysis / Shahrzad Gholami, Erwin W. Knippenberg, and James Campbell -- Chapter 18 BankNote-Net: Open Dataset for Assistive Universal Currency Recognition / Felipe Oviedo and Saqib Shaikh -- Chapter 19 Broadband Connectivity / Mayana Pereira, Amit Misra, and Allen Kim -- Chapter 20 Monitoring the Syrian War with Natural Language Processing / Rahul Dodhia and Michael Scholtens -- Chapter 21 The Proliferation of Misinformation Online / Will Fein, Mayana Pereira, Jane Wang, Kevin Greene, Lucas Meyer, Rahul Dodhia, and Jacob Shapiro -- Chapter 22 Unlocking the Potential of AI with Open Data / Anthony Cintron Roman and Kevin Xu -- Chapter 23 Detecting Middle Ear Disease / Yixi Xu and Al-Rahim Habib -- Chapter 24 Detecting Leprosy in Vulnerable Populations / Yixi Xu and Ann Aerts -- Chapter 25 Automated Segmentation of Prostate Cancer Metastases / Yixi Xu -- Chapter 26 Screening Premature Infants for Retinopathy of Prematurity in Low-Resource Settings / Anthony Ortiz, Juan M. Lavista Ferres, Guillermo Monteoliva, and Maria Ana Martinez-Castellanos -- Chapter 27 Long-Term Effects of COVID-19 / Meghana Kshirsagar and Sumit Mukherjee -- Chapter 28 Using Artificial Intelligence to Inform Pancreatic Cyst Management / Juan M. Lavista Ferres, Felipe Oviedo, William B. Weeks, Elliot Fishman, and Anne Marie Lennon -- Chapter 29 NLP-Supported Chatbot for Cigarette Smoking Cessation / Jonathan B. Bricker, Brie Sullivan, Marci Strong, Anusua Trivedi, Thomas Roca, James Jacoby, Margarita Santiago-Torres, and Juan M. Lavista Ferres -- Chapter 30 Mapping Population Movement Using Satellite Imagery / Tammy Glazer, Gilles Hacheme, Amy Michaels, and Christopher J.L. Murray -- Chapter 31 The Promise of AI and Generative Pre-Trained Transformer Models in Medicine / William B. Weeks.