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Artificial intelligence and sustainability

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Artificial intelligence and sustainabilityby Mohamed Ahmed Alloghani.
作者:	Alloghani, Mohamed Ahmed.
出版者:	Cham :Springer Nature Switzerland :2024.
面頁冊數:	xx, 212 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Artificial intelligenceEnvironmental aspects.
電子資源:	https://doi.org/10.1007/978-3-031-45214-7
ISBN:	9783031452147$q(electronic bk.)

Artificial intelligence and sustainability
Alloghani, Mohamed Ahmed.

Artificial intelligence and sustainability[electronic resource] /by Mohamed Ahmed Alloghani. - Cham :Springer Nature Switzerland :2024. - xx, 212 p. :ill. (some col.), digital ;24 cm. - Signals and communication technology,1860-4870. - Signals and communication technology..

Introduction -- Introduction to AI and Sustainability -- Challenges surrounding AI software development -- Strategies for building efficient AI systems -- Ethical considerations in AI development -- AI and Energy -- AI and Climate Change -- AI and Natural Resource Management -- AI and Sustainable Agriculture -- AI and Sustainable Transport -- AI and Sustainable Cities -- AI and Sustainable Business -- Methods for ensuring data privacy and security in AI software -- Case studies -- Future directions for sustainable AI software development -- Conclusion.

This book gives readers the tools to craft AI systems that don't just thrive today, but endure sustainably into the future. Whether a trailblazer or an aspiring innovator, this book enables readers to resonate with the ambitions of software developers, data scientists, and AI practitioners. The author covers the latest techniques and best practices for energy efficiency, reducing carbon footprints, and ensuring fair and ethical AI. The book also addresses important issues such as AI governance, managing risks, and ensuring transparency. Topics covered include understanding the relationship between AI and sustainable development, strategies for building efficient AI systems, and ethical considerations in AI development, among others. The author includes case studies of companies and organizations that have successfully implemented sustainable AI software development practices. Therefore, this book will be of interest to AI practitioners, academics, researchers, and lecturers in computer science, artificial intelligence, machine learning and data sciences.

ISBN: 9783031452147$q(electronic bk.)

Standard No.: 10.1007/978-3-031-45214-7doiSubjects--Topical Terms:

921961
Artificial intelligence
--Environmental aspects.

LC Class. No.: Q335

Dewey Class. No.: 006.3

Artificial intelligence and sustainability
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505 0 $a Introduction -- Introduction to AI and Sustainability -- Challenges surrounding AI software development -- Strategies for building efficient AI systems -- Ethical considerations in AI development -- AI and Energy -- AI and Climate Change -- AI and Natural Resource Management -- AI and Sustainable Agriculture -- AI and Sustainable Transport -- AI and Sustainable Cities -- AI and Sustainable Business -- Methods for ensuring data privacy and security in AI software -- Case studies -- Future directions for sustainable AI software development -- Conclusion.
520 $a This book gives readers the tools to craft AI systems that don't just thrive today, but endure sustainably into the future. Whether a trailblazer or an aspiring innovator, this book enables readers to resonate with the ambitions of software developers, data scientists, and AI practitioners. The author covers the latest techniques and best practices for energy efficiency, reducing carbon footprints, and ensuring fair and ethical AI. The book also addresses important issues such as AI governance, managing risks, and ensuring transparency. Topics covered include understanding the relationship between AI and sustainable development, strategies for building efficient AI systems, and ethical considerations in AI development, among others. The author includes case studies of companies and organizations that have successfully implemented sustainable AI software development practices. Therefore, this book will be of interest to AI practitioners, academics, researchers, and lecturers in computer science, artificial intelligence, machine learning and data sciences.
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