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.
"Sinopsis" puede pertenecer a otra edición de este libro.
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.
"Sobre este título" puede pertenecer a otra edición de este libro.
Librería: PBShop.store UK, Fairford, GLOS, Reino Unido
HRD. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Nº de ref. del artículo: L1-9798337384900
Cantidad disponible: Más de 20 disponibles
Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de America
HRD. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Nº de ref. del artículo: L1-9798337384900
Cantidad disponible: Más de 20 disponibles
Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de America
Hardcover. Condición: new. Hardcover. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9798337384900
Cantidad disponible: 1 disponibles
Librería: California Books, Miami, FL, Estados Unidos de America
Condición: New. Nº de ref. del artículo: I-9798337384900
Cantidad disponible: Más de 20 disponibles
Librería: CitiRetail, Stevenage, Reino Unido
Hardcover. Condición: new. Hardcover. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Nº de ref. del artículo: 9798337384900
Cantidad disponible: 1 disponibles
Librería: Rarewaves.com USA, London, LONDO, Reino Unido
Hardback. Condición: New. Nº de ref. del artículo: LU-9798337384900
Cantidad disponible: Más de 20 disponibles
Librería: Rarewaves.com UK, London, Reino Unido
Hardback. Condición: New. Nº de ref. del artículo: LU-9798337384900
Cantidad disponible: Más de 20 disponibles
Librería: AussieBookSeller, Truganina, VIC, Australia
Hardcover. Condición: new. Hardcover. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Nº de ref. del artículo: 9798337384900
Cantidad disponible: 1 disponibles
Librería: AHA-BUCH GmbH, Einbeck, Alemania
Buch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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. Nº de ref. del artículo: 9798337384900
Cantidad disponible: 2 disponibles