Examining the Environmental Footprint of Artificial Intelligence. Este artículo no está disponible.Examining the Environmental Footprint of Artificial Intelligence

While artificial intelligence is often viewed as a powerful tool for enhancing environmental monitoring, a paradoxical reality is simultaneously unfolding. The development and deployment of AI systems require vast amounts of energy, computing power, water resources, and digital infrastructure, raising important concerns about their environmental footprint. From data center construction and operation to growing demands for electricity, water consumption, and electronic waste disposal, AI technologies themselves can place significant pressures on natural and environmental systems. As these technologies become increasingly embedded across society, it is essential to better understand both their environmental benefits and their hidden ecological costs. This growing tension highlights the need for scholarly research that critically evaluates the true environmental and sustainability implications of artificial intelligence in a rapidly digitalizing world. Examining the Environmental Footprint of Artificial Intelligence provides a critical examination of the environmental consequences of AI technologies, highlighting the opportunities, tradeoffs, and sustainability challenges that accompany the rapid expansion of artificial intelligence across modern society. Bridging scientific research, case studies, and policy analysis, this book provides a balanced, evidence-based exploration of the ecological risks tied to the accelerating demand for AI infrastructure. Covering topics such as critical minerals for AI hardware, the ecological political economy of AI, and technology leadership education, this book is an imperative academic resource for graduate and doctoral students, sustainability professionals, ESG practitioners, technology developers, AI practitioners, data scientists, regulators, environmental policymakers, and more.

Momina Shaheen is an academic and researcher in computer science with over 8 years of experience in teaching and research. She currently serves as a Lecturer in Computing and Programme Leader at the University of Roehampton London. Her work focuses on edge computing, the Internet of Things, federated learning, and cybersecurity, with applications across smart cities, healthcare, finance, and education. Shaheen holds a B.Sc. in Information Technology, an M.Eng. in Software Engineering, and defended her Ph.D. in Computer Science, focusing on improving deep learning performance in federated machine learning. Her academic contributions include over 46 peer-reviewed publications in Q1 journals, multiple book chapters, and editorial work, earning her an h-index of 9 and over 400 citations. She has taught a wide range of undergraduate and postgraduate modules, including algorithms, software development, artificial intelligence, and data visualization. In addition to her teaching, she leads international collaborations and actively contributes to curriculum design, grant writing, and supervision of research projects. She also served as a reviewer for prominent journals such as Nature (under Early Career Reviewer Program), MDPI Electronics, IEEE Access, IET Information Security, Springer Scientific Reports, PLOS ONE, and ACM Transactions, and has chaired international conferences. Shaheen is committed to fostering innovation in computing education, and intelligent systems.