Connecting brain and heart: artificial intelligence for sustainable development

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.