Call for Chapters: AI and Ecological Change for Sustainable Development

Editors

Jabulani Garwi, University of the Free State, South Africa
Reason Masengu, Middle East College, Oman

Call for Chapters

Proposals Submission Deadline: December 8, 2024
Full Chapters Due: February 9, 2025
Submission Date: February 9, 2025

Introduction

The world is undergoing profound ecological shifts due to climate change, biodiversity loss, and unsustainable resource exploitation. Against this backdrop, technological innovation, particularly Artificial Intelligence (AI), has emerged as a critical tool, offering data-driven solutions to some of the most pressing environmental challenges of our time. This book, AI and Ecological Change for Sustainable Development, explores the powerful nexus of AI and ecological change, illustrating how predictive modeling and machine learning can enhance sustainable practices, mitigate ecological degradation, and foster resilient development pathways—particularly within the Global South, where environmental, social, and economic contexts require tailored approaches. The Global South presents a uniquely rich setting for AI applications in sustainable development, with its abundant natural resources, diverse ecosystems, and communities increasingly affected by ecological transformations. Yet, the region also faces considerable obstacles, including limited infrastructure, social disparities, and economic constraints, which must be carefully navigated to ensure AI contributes inclusively to sustainability. This volume brings together interdisciplinary perspectives to examine how AI can enable localised, equitable responses to environmental challenges while enhancing socio-economic resilience. We invite scholars, practitioners, and policymakers to contribute insights into the ways AI technologies—from machine learning and sensor networks to advanced data analytics—can support sustainable development. This includes examining socio-political and ethical considerations that accompany AI's ecological applications, recognising that the integration of AI is not purely technical but intersects with governance, community needs, and global sustainability goals. Through contributions from fields such as environmental science, engineering, sustainable agriculture, policy studies, and development studies, this book aims to deliver a comprehensive overview of AI’s impact on ecological change. By presenting both theoretical and practical insights, we hope to inspire actionable approaches that advance sustainable development, where AI meets ecology for a more resilient and sustainable world.

Objective

This book seeks to advance the field of sustainable development by critically examining the transformative potential of AI in addressing ecological challenges in the Global South. It explores how AI technologies, such as machine learning, predictive analytics, and data-driven decision-making, can not only mitigate ecological degradation but also foster resilient socio-economic systems by promoting sustainable practices. By bridging the gap between theoretical insights and practical applications, this volume presents a comprehensive view of AI’s capacity to support unique environmental, social, and economic needs within this region. In contrast to the existing literature, which predominantly focuses on AI applications in technologically advanced regions, this book fills a vital gap by addressing the specific challenges, constraints, and opportunities facing the Global South—a region often overlooked in mainstream AI and sustainability discussions. Through a collection of interdisciplinary perspectives that includes case studies, empirical research, and conceptual frameworks, the book provides contextually relevant insights that reveal how AI can empower resilience and equity within resource-constrained settings experiencing severe impacts from ecological shifts. Ultimately, this volume serves as a resource for researchers, practitioners, and policymakers seeking to implement AI strategies for sustainable development, offering actionable insights to inform policy, guide ethical technological deployment, and inspire globally inclusive approaches to AI-driven ecological interventions. By addressing these objectives, the book aims to deepen academic understanding and contribute to a globally inclusive discourse on AI’s role in shaping a sustainable future, ensuring that AI-driven ecological initiatives reflect the unique challenges and opportunities within the Global South.

Target Audience

This book is designed for a multidisciplinary audience, including researchers, practitioners, policymakers, and graduate students, who are focused on the intersections of AI, ecological change, and sustainable development. Academics and researchers across fields such as environmental science, data science, engineering, and sustainable development will benefit from the book’s in-depth analysis of AI applications tailored to the unique socio-economic and environmental contexts of the Global South. For policymakers and government officials, particularly those involved in environmental governance and technology policy, the book offers actionable insights into integrating AI within national and regional sustainability frameworks, addressing the distinct challenges and opportunities present in emerging economies. Practitioners and professionals within technology, agriculture, environmental management, and related sectors will find practical case studies and frameworks that highlight effective, data-driven approaches to leveraging AI for sustainable development. Additionally, graduate students and emerging scholars will gain a valuable foundation and exposure to cutting-edge research and methodologies, equipping them to advance both theoretical understanding and practical applications in the field. Overall, this book will attract a readership committed to understanding and applying AI’s potential for sustainable and equitable ecological solutions, providing insights to foster transformative change in diverse global settings.

Recommended Topics

The book will cover, but is not limited to, the following areas: • Theoretical Foundations of AI in Ecological Contexts -An overview of the theoretical frameworks underpinning AI technologies and their application to ecological challenges. • AI and Climate Change Mitigation -Examining how AI can be leveraged to model, predict, and mitigate the effects of climate change in the Global South. • AI-Driven Environmental Monitoring Systems: Case studies of AI applications in monitoring and assessing environmental changes, such as deforestation and pollution. • AI for Biodiversity Conservation- Investigating how AI can be used to protect endangered species and their habitats through predictive analytics and habitat monitoring. • Optimising Water Resource Management with AI- Exploring AI solutions for improving water management, predicting water shortages, and enhancing conservation efforts in water-scarce regions. • AI in Sustainable Agriculture-Analysis of AI technologies employed to promote sustainable farming practices, enhance crop yields, and manage agricultural resources efficiently. • AI for Disaster Risk Reduction and Response- Evaluating AI’s role in predicting, managing, and responding to natural disasters such as floods, droughts, and hurricanes. • Ethical Considerations in AI for Ecological Change-Discussing the ethical implications of deploying AI in environmental contexts, including issues of data privacy and equity. • AI and Renewable Energy Integration-Exploring how AI can optimise the integration and management of renewable energy sources like solar and wind power in the Global South. • AI-Enhanced Urban Planning for Sustainable Cities-Assessing how AI can support sustainable urban development and smart city initiatives to address urban ecological challenges. • AI in Health and Environmental Sustainability-Investigating the intersection of AI, public health, and environmental sustainability, including how AI can predict and manage health impacts related to environmental factors. • Policy Frameworks for AI in Ecological Management- Providing insights into the policy considerations necessary for the effective and ethical deployment of AI technologies in ecological settings. • AI and Indigenous Knowledge Systems- Examining how AI can integrate with traditional ecological knowledge and practices of Indigenous communities in the Global South. • Economic Impacts of AI on Ecological Sustainability- Analyzing the economic benefits and challenges associated with the implementation of AI technologies for ecological sustainability. • Case Studies of Successful AI-Driven Ecological Initiatives-Highlighting real-world examples of AI applications that have significantly contributed to ecological preservation and sustainable development. • Challenges and Limitations of AI in Ecological Applications- Identifying and addressing the technical, logistical, and contextual challenges faced when applying AI to environmental issues. • AI and Sustainable Supply Chain Management- Exploring how AI can enhance sustainability within supply chains, focusing on reducing environmental impacts and promoting responsible sourcing. • AI for Community Engagement and Environmental Awareness-Evaluating how AI can be used to engage communities and raise awareness about environmental issues and sustainable practices. • Integrating AI with Existing Ecological Models and Tools- Discussing strategies for integrating AI technologies with traditional ecological models and tools to enhance their effectiveness. • Future Directions and Emerging Trends in AI for Ecological Change- Providing an overview of emerging trends, future research directions, and potential advancements in AI applications for ecological transformation.

Submission Procedure

Researchers and practitioners are invited to submit on or before December 8, 2024, a chapter proposal of 1,000 to 2,000 words clearly explaining the mission and concerns of his or her proposed chapter. Authors will be notified by December 22, 2024 about the status of their proposals and sent chapter guidelines.Full chapters of a minimum of 10,000 words (word count includes references and related readings) are expected to be submitted by February 9, 2025, and all interested authors must consult the guidelines for manuscript submissions at https://www.igi-global.com/publish/contributor-resources/before-you-write/ prior to submission. All submitted chapters will be reviewed on a double-anonymized review basis. Contributors may also be requested to serve as reviewers for this project.

Note: There are no submission or acceptance fees for manuscripts submitted to this book publication, AI and Ecological Change for Sustainable Development. All manuscripts are accepted based on a double-anonymized peer review editorial process.

All proposals should be submitted through the eEditorial Discovery^® online submission manager.

Publisher

This book is scheduled to be published by IGI Global (formerly Idea Group Inc.), an international academic publisher of the "Information Science Reference" (formerly Idea Group Reference), "Medical Information Science Reference," "Business Science Reference," and "Engineering Science Reference" imprints. IGI Global specializes in publishing reference books, scholarly journals, and electronic databases featuring academic research on a variety of innovative topic areas including, but not limited to, education, social science, medicine and healthcare, business and management, information science and technology, engineering, public administration, library and information science, media and communication studies, and environmental science. For additional information regarding the publisher, please visit https://www.igi-global.com. This publication is anticipated to be released in 2025.

Important Dates

December 8, 2024: Proposal Submission Deadline
December 22, 2024: Notification of Acceptance
February 9, 2025: Full Chapter Submission
March 16, 2025: Review Results Returned
April 13, 2025: Final Acceptance Notification
April 20, 2025: Final Chapter Submission

Inquiries

Jabulani Garwi University of the Free State jabulanig400@gmail.com Reason Masengu Middle East College masengumasengu@yahoo.com

Classifications

Business and Management; Computer Science and Information Technology; Education; Life Sciences; Library and Information Science; Media and Communications; Security and Forensics; Government and Law; Social Sciences and Humanities; Physical Sciences and Engineering

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