sustainability
Article
Ordering Artificial Intelligence Based Recommendations
to Tackle the SDGs with a Decision-Making Model Based
on Surveys
Sergio Alonso
1,
* , Rosana Montes
1
, Daniel Molina
2
, Iván Palomares
1,3
, Eugenio Martínez-Cámara
2
,
Manuel Chiachio
4
, Juan Chiachio
4
, Francisco J. Melero
1
, Pablo García-Moral
5
, Bárbara Fernández
6
,
Cristina Moral
6
, Rosario Marchena
6
, Javier Pérez de Vargas
7
and Francisco Herrera
2,7
Citation: Alonso, S.; Montes, R.;
Molina, D.; Palomares, I.;
Martínez-Cámara, E.; Chiachio, M.;
Chiachio, J.; Melero, F.J.; García-
Moral, P.; Fernández, B.; et al.
Ordering Artificial Intelligence Based
Recommendations to Tackle the SDGs
with a Decision-Making Model Based
on Surveys. Sustainability 2021, 13,
6038. https://doi.org/10.3390/
su13116038
Academic Editors: Álvaro Herrero,
Carlos Cambra, Carlos Alonso de
Armiño, Pawel Ksieniewicz and
Paolo Gastaldo
Received: 21 April 2021
Accepted: 21 May 2021
Published: 27 May 2021
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Attribution (CC BY) license (https://
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4.0/).
1
Department of Software Engineering, Andalusian Research Institute in Data Science and Computational
Intelligence (DaSCI), University of Granada, 18071 Granada, Spain; rosana@ugr.es (R.M.);
ivanpc@ugr.es (I.P.); fjmelero@ugr.es (F.J.M.)
2
Department of Computer Science and Artificial Intelligence, Andalusian Research Institute in Data Science
and Computational Intelligence (DaSCI), University of Granada, 18071 Granada, Spain;
dmolina@decsai.ugr.es (D.M.); emcamara@decsai.ugr.es (E.M.-C.); herrera@decsai.ugr.es (F.H.)
3
Department of Computer Science and Information Engineering, National Cheng Kung University,
Tainan 70101, Taiwan
4
Department of Structural Mechanics and Hydraulic Engineering, Andalusian Research Institute in Data
Science and Computational Intelligence (DaSCI), University of Granada, 18071 Granada, Spain;
mchiachio@ugr.es (M.C.); jchiachio@ugr.es (J.C.)
5
Faculty of Arts, University of Granada, 18071 Granada, Spain; pablogarciamoral@gmail.com
6
Ferrovial S.A., C/ Principe de Vergara 135, 28002 Madrid, Spain; barbara.fernandez@ferrovial.com (B.F.);
cmoral@ferrovial.com (C.M.); rmarchena@ci3.es (R.M.)
7
Royal Academy of Engineering of Spain (RAES), 28005 Madrid, Spain; jpvargas@raing.es
* Correspondence: zerjioi@ugr.es
Abstract: The United Nations Agenda 2030 established 17 Sustainable Development Goals (SDGs)
as a guideline to guarantee a sustainable worldwide development. Recent advances in artificial
intelligence and other digital technologies have already changed several areas of modern society,
and they could be very useful to reach these sustainable goals. In this paper we propose a novel
decision making model based on surveys that ranks recommendations on the use of different artificial
intelligence and related technologies to achieve the SDGs. According to the surveys, our decision
making method is able to determine which of these technologies are worth investing in to lead new
research to successfully tackle with sustainability challenges.
Keywords: Sustainable Development Goals; artificial intelligence; emerging digital technologies;
decision making
1. Introduction
The Sustainability Development Goals (SDGs) were adopted by the United Nations
as a blueprint to achieve a global development for a more sustainable future for all peo-
ple, reducing the poverty, protecting the environment, and producing global peace and
prosperity [1].
Artificial intelligence (AI) and other digital technologies, such as big data, virtual and
augmented reality, blockchain, etc. are strongly impacting in our lives [2,3], producing a
continuous transformation in the so-called Fourth Industrial Revolution [4], and changing
many fields in our daily life due to its versatility. Thus, AI can be foreseen to have a similar
impact to tackle these SDGs [5,6].
In a recent work [5], after a comprehensive literature review, the role that AI and
digital technologies could play in the different SDGs was presented, and it provides several
recommendations on how these technologies can help to achieve each of the SDGs. Due
Sustainability 2021, 13, 6038. https://doi.org/10.3390/su13116038 https://www.mdpi.com/journal/sustainability