Green AI

1. Auflage 2027
ISBN: 978-1-041-35737-7
Verlag: Taylor & Francis

Buch, Englisch, 240 Seiten, Format (B × H): 156 mm x 234 mm

Reihe: Data Analytics Applications

As the power and scale of AI systems expand, so too does their environmental footprint. Training large models demands vast computational resources. Data centres consume significant amounts of electricity and water. Supply chains for hardware rely on extractive processes with tangible ecological costs. AI’s environmental implications are no longer peripheral concerns. They are central to the future of both digital innovation and planetary sustainability.

In this context, the emergence of green artificial intelligence represents not a niche subfield but a necessary evolution in how artificial intelligence is conceived, designed, and governed. The future of technological progress cannot be measured solely in terms of model performance, accuracy benchmarks, or market valuation. It must also be measured in terms of environmental impact.

With chapters written by globally recognized experts, Green AI is a forward-looking exploration of how AI can be designed, developed, and deployed with environmental sustainability at its core. It blends technical insight with ethical urgency, outlining both the environmental costs of today’s AI systems, especially in compute and carbon emissions, and practical strategies to reduce those impacts without sacrificing innovation. From energy-efficient algorithms and hardware to lifecycle-wide sustainability frameworks, the book shows how researchers, engineers, and policymakers can balance AI’s transformative potential with ecological responsibility. Real-world case studies, policy analysis, and calls to action make the book a foundational text for anyone interested in making the next wave of AI both powerful and planet friendly.

Zielgruppe

Professional Practice & Development and Professional Reference

Autoren/Hrsg.

Liebowitz, Jay

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Wirtschaftswissenschaften Volkswirtschaftslehre Internationale Wirtschaft Entwicklungsökonomie & Emerging Markets
• Geowissenschaften Umweltwissenschaften Nachhaltigkeit
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining

Inhaltsverzeichnis

1. Rethinking Green AI: Efficiency Meets Responsibility2. Green AI Must Be Human First AI3. Green AI in Smart Cities: Computational Proportionality and Sustainable Urban AI4. Green AI as Organizational Design: Building Durable Systems in an Age of Uncertainty5. The Geoscience–AI Nexus: Earth Sciences, Artificial Intelligence, and the Material Foundations of the Digital Age6. Marketcraft for AI: Designing a Better Market for Memory,Compute, and Intelligence7. Proportional AI: Right-Sized Intelligence for Sustainability8. Sustainable Machine Learning: Energy-Aware Design and Optimization9. Agent-Based Modeling for Sustainable Transitions10. Efficiency at the Source: How Edge Computing Drives Green AI in Advanced11. Green Artificial Intelligence for Sustainable Engineering Systems:A Unified Net-Benefit and Proportionality Framework12. Sustainable Artificial Intelligence in Healthcare: Principles, Applications, and Future Directions

Über Autor(innen)

Dr. Jay Liebowitz is a Special Advisor to the President at Thomas Jefferson University on AI and Analytics initiatives. He recently served as Professor of Business Innovation and Industry Transformation and Director of a new AI-EDGE Center in the Crummer Graduate School of Business at Rollins College. He also served as the inaugural Executive-in-Residence for Public Service at Columbia University’s Data Science Institute. He was previously a Visiting Professor in the Stillman School of Business and the MS-Business Analytics Capstone & Co-Program Director (External Relations) at Seton Hall University. He previously served as the Distinguished Chair of Applied Business and Finance at Harrisburg University of Science and Technology. Before HU, he was the Orkand Endowed Chair of Management and Technology in the Graduate School at the University of Maryland University College (UMUC). He served as a Full Professor in the Carey Business School at Johns Hopkins University. He was ranked one of the top 10 knowledge management researchers/practitioners out of 11,000 worldwide, and was ranked #2 in KM Strategy worldwide according to the January 2010 Journal of Knowledge Management. At Johns Hopkins University, he was the founding Program Director for the Graduate Certificate in Competitive Intelligence and the Capstone Director of the MS-Information and Telecommunications Systems for Business Program, where he engaged over 30 organizations in industry, government, and not-for-profits in capstone projects.