This book emphasizes the importance of incorporating sustainability concepts through the lens of education, research, and advocacy. A core focus is artificial intelligence (AI) and its developing role in relation to education, research, and advocacy to advance sustainable development. By providing a comprehensive perspective, the reader learns that research and education must work together to generate innovation, advocating responsible AI development and deployment. To enable the development of change agents in their fields, the authors emphasize the importance of incorporating sustainability ideas into a variety of educational programs. On the topic of creating purposeful learning environments, AI is examined as the tool to strike a balance between flexible, student-centered approaches and curriculum standards, in consideration of the sustainability impact factor.
This book aims to align with the United Nations Sustainable Development Goal (SDG) No. 4 on quality education. It also examines how research aids in the development of sustainable practices and the discovery of novel solutions. Researchers can contribute to evidence-based decision-making by encouraging interdisciplinary collaboration and interacting with stakeholders. Furthermore, the reader learns that advocacy can be used by both individuals and groups to effect real change through awareness-raising, influencing public opinion, and advocating for legislative changes. The ethical issues, legal frameworks, and the role of advocacy in forming responsible AI practices for capacity building are discussed. Each topic is supported by case studies, best practices, and practical insights, making this book a useful reference for research and practice.
Developed by experts in their respective fields of science, technology, and engineering with experience in education, research, and advocacy, this book would serve scholars with innovative insights for their research. Practitioners may also utilize this book for their professional work to apply the latest advancements and optimal methodologies.
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