EconPapers    
Economics at your fingertips  
 

Artificial intelligence: Catalyst or barrier on the path to sustainability?

Alexander Kopka and Nils Grashof

Technological Forecasting and Social Change, 2022, vol. 175, issue C

Abstract: Artificial intelligence (AI) is often seen as a key technology for future economic growth. However, the concrete socio-economic effects have not yet been clearly researched. This is especially true for sustainability issues, which have so far been neglected in the discussion about the impact of AI despite its immense importance. Consequently, this paper focuses on the impact of AI on the regional energy system, which is considered to play a crucial role in addressing the societal challenge of climate change. Apart from the direct influence of AI on the regional energy consumption in Germany, regional differences are also investigated. For the corresponding empirical analysis, various datasets are combined and analysed in a panel-regression at the regional NUTS-3 level (Nomenclature des unités territoriales statistiques). Evidence is found that the energy decreasing/increasing effect of AI highly depends on the regional circumstances, the technological as well as industrial portfolio. Thus, a shotgun approach on subsidizing AI is not advisable when focussing on sustainability.

Keywords: Artificial intelligence; Transition; Energy consumption; Sustainability; Regional circumstances (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (12)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0040162521007496
Full text for ScienceDirect subscribers only

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:eee:tefoso:v:175:y:2022:i:c:s0040162521007496

DOI: 10.1016/j.techfore.2021.121318

Access Statistics for this article

Technological Forecasting and Social Change is currently edited by Fred Phillips

More articles in Technological Forecasting and Social Change from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-03-19
Handle: RePEc:eee:tefoso:v:175:y:2022:i:c:s0040162521007496