Connecting brain and heart: artificial intelligence for sustainable development

Diego Chavarro (), Jaime Andrés Perez-Taborda () and Alba Ávila ()
Additional contact information
Diego Chavarro: Colombian Society of Engineering Physics (SCIF)
Jaime Andrés Perez-Taborda: Colombian Society of Engineering Physics (SCIF)
Alba Ávila: Colombian Society of Engineering Physics (SCIF)

Scientometrics, 2022, vol. 127, issue 12, No 12, 7060 pages

Abstract: Abstract A key objective of global policies on Artificial Intelligence (AI) is to foster AI research for sustainable development (SD). In this paper, we analyze the inclusion of SD in AI research indexed by the IEEE Xplore database from 2000 to 2019. We address three critical questions: (1) To what extent is AI research addressing the sustainable development goals (SDGs)? (2) Which subject areas of AI show an emerging interest in SD? And (3) What patterns of collaboration between regions of the world are being stimulated by AI? Our scientometric analysis consists of (1) Identifying the number of AI papers that address SDGs in their titles, abstracts, and keywords. (2) Developing a composite indicator based on the number of documents produced, scientific impact, and inventive impact to distinguish areas with an emerging interest in SD; (3) Exploring co-authorship networks at three levels: region, income group, and country. The overall results show that a small share of papers is explicitly focused on SD. Our composite indicator allowed us to identify an emerging interest in SD from Ultrasonics, Ferroelectrics, and Frequency Control, Education, Consumer Electronics, Electrical Engineering, Electromagnetic Compatibility and Interference. Specifically, on AI subjects, we found emerging interests in Prediction Methods, Computation Theory, Machine Learning, Learning (artificial intelligence), and Biological Neural Networks. Inter-regional and inter-income group collaboration are limited, and network power is concentrated in a few countries. The results could be useful to improve the connection between technical knowledge, strategic planning for S&T investment, and SD policies.

Keywords: Artificial intelligence; Sustainable development; Engineering and society; Research policy; Emerging technologies (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s11192-022-04299-5 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:scient:v:127:y:2022:i:12:d:10.1007_s11192-022-04299-5

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11192

DOI: 10.1007/s11192-022-04299-5

Access Statistics for this article

Scientometrics is currently edited by Wolfgang Glänzel

More articles in Scientometrics from Springer, Akadémiai Kiadó
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().