Artificial Intelligence Solutions For Global Health And Disaster Response Challenges And Opportunities

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Artificial Intelligence Solutions for Global Health and Disaster Response: Challenges and Opportunities

Author: Tetyana Chumachenko
language: en
Publisher: Frontiers Media SA
Release Date: 2024-09-02
Artificial intelligence (AI) has shown promise as an effective tool in disaster preparedness and response, providing a unique perspective on some of the most urgent health challenges. Rapid advances in AI technology can potentially revolutionize the way how we respond to emergencies and disasters that affect the world's health, including early warning systems, resource allocation, and real-time decision-making. This Research Topic aims to explore the latest developments in AI and its applications in global health and disaster response, providing a comprehensive overview of the potential and challenges of AI in improving health outcomes in crises. This Research Topic will bring together leading researchers, practitioners, and policymakers in global health and disaster response to share their experiences and insights on how AI can be leveraged to improve response efforts and enhance healthcare delivery.
Artificial Intelligence and Machine Learning for Enhancing Resilience: Concepts, Applications, and Future Directions

As contemporary societies face unprecedented challenges such as mounting mental health issues, environmental crises, and socioeconomic insecurity, the urgency of developing objective, scalable, and dynamic methodologies to study resilience has never been greater. This book arises at the intersection of cutting-edge technology and human insight. It focuses on the possibility for AI and ML to transform resilience assessment, prediction, and interventions across the individual, organizational, and ecological levels. The chapters included in this book represent an organized synthesis of cutting-edge science, pragmatic applications, and prospective potential. With machine learning algorithms to estimate psychological resilience and AI-based models for climate change adaptation and ecosystem management, this book demonstrates the rich innovations that are emerging at the cross-sector of technology and resilience science. Perhaps most importantly, this book does not gloss over the urgent ethical, technical, and regulatory issues that arise when AI is introduced to sensitive topics such as mental health and environmental management. Questions about data privacy, algorithmic bias, model interpretability, and equitable technology deployment are thoroughly investigated, providing lessons learned and suggestions for moving ahead. A significant strength of this work is its global focus. Showcasing work from contributors of various methodologies and regions provides the latest views on new methodologies, strategies for practical implementation, and on what still needs to be invented. This guarantees that the publication engages with the messy socio-cultural and environmental contexts in which these interventions work and that it doesn’t just mirror technological possibilities. For academicians, practitioners, technologists, and policymakers, this book is both a fundamental reference and an outlook resource. It provides: Holistic examination of AI and ML in the context of psychological, organizational, and ecological resilience. In-depth reviews on methodological innovations, such as deep learning, natural language processing, and sensor-based assessments. Unprecedented appraisals of barriers to implementation, with ethical and regulatory considerations. We trust that this book will inspire conversation, fuel innovation, and support a future in which technology supplements, rather than replaces, human ability to adapt, recover, and flourish. We encourage readers to critique the content, to reflect on how AI, ML, and resilience intersect in their particular contexts, and to join us in shaping a future where technological and human resilience evolve together.
Artificial Intelligence

This book presents contextualised and detailed research on Artificial Intelligence (AI) and the Global South. It examines the key challenges of these emerging and least industrialised countries while proffering holistic and comprehensive solutions. The book then explains how AI, as part of these broad interventions, can drive Global South economies to achieve inclusive development and shared prosperity. The book outlines how countries can swiftly prepare to adopt and develop AI across all sectors. It presents novel national, regional, and continental AI adoption, development, and implementation frameworks. Features: Broad non-AI interventions and prescriptions to address Global South challenges A comprehensive but accessible introduction to AI concepts, technology, infrastructure, systems, and innovations such as AlphaFold, ChatGPT-4, and DeepSeek-R1 An overview of AI-related technologies such as quantum computing, battery energy storage systems, 3D printing, nanotechnology, IoT, and blockchain How to prepare emerging economies to unlock the benefits of AI while mitigating the risks Discussion of specific AI applications in 11 critical Global South sectors Details of 11 sector case studies of AI adoption in the Global South and Global North Ten country case studies: Sharing emergent AI experiences in the Global South AI adoption framework: vision, strategy, policy, governance, legislation/regulation, and implementation matrix A framework for democratising and decolonising AI The value proposition for AI research, development, and ownership in the Global South A case for the participation of the Global South in the AI semiconductor industry This book is aimed at policymakers, business leaders, graduate students, academics, researchers, strategic thinkers, and world leaders seeking to understand and leverage the transformative role of AI-based systems in achieving inclusive development, economic transformation, and shared prosperity.