TY - JOUR
T1 - The crucial role of artificial intelligence in addressing climate change
AU - Andrade-Arenas, Laberiano
AU - Celis, Domingo Hernández
AU - Yactayo-Arias, César
N1 - Publisher Copyright:
© 2025, Institute of Advanced Engineering and Science. All rights reserved.
PY - 2025/2
Y1 - 2025/2
N2 - Addressing climate change is one of the fundamental priorities at a global level, given its significant impact on both the environment and society. This systematic literature review explores the role of artificial intelligence (AI) in addressing climate change. It identified applications, contributions to predicting extreme events, techniques used, ethical challenges, and associated biases. The rapid systematic literature review (RSL) was conducted using databases such as Scopus, Dimensions, directory of open access journals (DOAJ), and IEEE Xplore. The preferred reporting items for systematic reviews and meta-analyses (PRISMA) statement was used to ensure the completeness and transparency of the analysis. 40 articles were selected that were published between 2018 and 2023 and addressed AI in climate change. The findings show that AI is being used to predict and mitigate extreme climate events, estimate the greenhouse effect, and predict temperatures. In addition, innovative techniques such as hybrid machine learning models, convolutional neural networks, artificial neural networks, support vector machines, and logistic regression. In conclusion, AI offers a promising approach to addressing climate change, with transformative potential in predicting and mitigating its effects. However, continuous ethical considerations are required to guarantee its conscientious and efficient utilization.
AB - Addressing climate change is one of the fundamental priorities at a global level, given its significant impact on both the environment and society. This systematic literature review explores the role of artificial intelligence (AI) in addressing climate change. It identified applications, contributions to predicting extreme events, techniques used, ethical challenges, and associated biases. The rapid systematic literature review (RSL) was conducted using databases such as Scopus, Dimensions, directory of open access journals (DOAJ), and IEEE Xplore. The preferred reporting items for systematic reviews and meta-analyses (PRISMA) statement was used to ensure the completeness and transparency of the analysis. 40 articles were selected that were published between 2018 and 2023 and addressed AI in climate change. The findings show that AI is being used to predict and mitigate extreme climate events, estimate the greenhouse effect, and predict temperatures. In addition, innovative techniques such as hybrid machine learning models, convolutional neural networks, artificial neural networks, support vector machines, and logistic regression. In conclusion, AI offers a promising approach to addressing climate change, with transformative potential in predicting and mitigating its effects. However, continuous ethical considerations are required to guarantee its conscientious and efficient utilization.
KW - Artificial intelligence
KW - Climate change
KW - Climate events
KW - Environment
KW - Machine learning
UR - http://www.scopus.com/inward/record.url?scp=85211139894&partnerID=8YFLogxK
U2 - 10.11591/ijai.v14.i1.pp1-11
DO - 10.11591/ijai.v14.i1.pp1-11
M3 - Original Article
AN - SCOPUS:85211139894
SN - 2089-4872
VL - 14
SP - 1
EP - 11
JO - IAES International Journal of Artificial Intelligence
JF - IAES International Journal of Artificial Intelligence
IS - 1
ER -