Artificial Intelligence—Reducing the Carbon Footprint?

Ekaterina I. Shumskaia
Additional contact information
Ekaterina I. Shumskaia: Moscow State Institute of International Relations (MGIMO University)

A chapter in Industry 4.0, 2022, pp 359-365 from Springer

Abstract: Abstract The article is devoted to the question of the impact of artificial intelligence and machine learning technologies on climate change. The work contains an analysis of technological capabilities and an assessment of their impact on the economy. Since the previous industrial revolutions have led to many modern environmental problems, including climate change, further technology adoption requires not only achieving productivity gains, but also meeting the requirements of environmental initiatives, including reducing carbon dioxide emissions into the atmosphere. The possibilities for widespread use of artificial intelligence are unique, in particular, a number of new solutions to the problems of climate change are emerging. This article describes examples of using the AI in the production and electricity. Attention is also drawn to some of the challenges that arise in the development of AI models: the Jevons’ paradox, the growth in demand for resources and electricity for computers. The highlighted notes must be taken into account when developing breakthrough technologies and further climate solutions.

Keywords: Artificial intelligence; Machine learning; Carbon footprint; Renewable energy sources; Climate change; Technological impact; O31; O33; O44 (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-79496-5_33

Ordering information: This item can be ordered from
http://www.springer.com/9783030794965

DOI: 10.1007/978-3-030-79496-5_33

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().