A Systematic Mapping of Artificial Intelligence Solutions for Sustainability Challenges in Latin America and the Caribbean



Artificial Intelligence, AI, Machine Learning, ML, Climate Change, Sustainability, Biodiversity, Data Science


The environmental health of Latin America and the Caribbean (LAC) is crucial to the survival of the planet. LAC countries occupy 13% of the Earth’s landmass yet contain 60% of the terrestrial life. The region is particularly brittle as climate change looms on the horizon, and its economic reliance on exploiting natural resources is accelerating its biodiversity loss. Central to these problems is that LAC is the most economically unequal region globally. Thus, it faces unique challenges in promoting sustainable development. This paper explores whether and how Artificial Intelligence (AI) may provide methods to accelerate the changes needed to increase resilience and facilitate adaptation. Starting with a systematic mapping of the research on AI for sustainability in LAC, we present a diagnosis of the current situation structured along the proposed axes of climate change, human vulnerability, and biodiversity. Then, we give some illustrative examples of potential directions for further work with applicability to the region. Due to its often overlooked resources, capabilities, and particularly fragile geolocation, LAC is called to play an oversize role in the planet’s sustainability in the coming decades.


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Author Biographies

Joaquin Salas, Instituto Politécnico Nacional

Joaquin Salas is a professor in the field of Computer Vision at Instituto Politécnico Nacional. Member of the Mexican National Research Sys- tem, his research interests include monitoring nat- ural systems using visual perception and aerial platforms. Salas received a Ph.D. in computer science from ITESM, México. He has been a visiting scholar at MIT, Stanford, Duke, Oregon State, Xerox PARC, the Computer Vision Center, and the ÉNST de Bretagne. He has served as co- chairperson of the Mexican Conference for Pattern Recognition three times. Salas was a Fulbright scholar for the US State Department. He has been invited editor for Elsevier Pattern Recognition and Pattern Recognition Letters. For his services at the Instituto Politécnico Nacional, he received the Lázaro Cárdenas medal from the President of Mexico.

Genevieve Patterson, Climate Change AI

Geneviève Patterson is a freelance researcher. Until July 2022, she was the Head of Applied Research at Visual Supply Company (VSCO), specializing in Computer Vision and Blockchain technologies and is a Core Team Volunteer at Cli- mate Change AI. Previously, she was CTO of the TRASH app (acquired by VSCO). Before working on her start-up, she was a Postdoctoral Researcher at Microsoft Research New England. Her research focuses on human-in-the-loop AI methods. Her interests include AI for climate science, cinematic video understanding, and active learning. She received her Ph.D. from Brown University in 2016. Contact her at genevieve@climatechange.ai.

Flavio de Barros Vidal, University of Brasília

Flavio de Barros Vidal received a B.Sc. in Electrical Engineering from the Federal University of Juiz de Fora (UFJF), Juiz de Fora, Brazil, in 2002. Then, in 2005, he received an M.Sc. in Elec- trical Engineering from the University of Brasilia (UnB), Brasília, Brazil. In 2009, he received a Ph.D. in Electrical Engineering from the Univer- sity of Brasília, Brasília, Brazil. He is currently an Senior professor in the Department of Com- puter Science at the University of Brasilia, Brazil. His current research interests include forensics, biometrics, deep learning, and computer vision. He is the leader of the Biometric and Technologies Group (BiTGroup) and a member of the Image, Signal, and Acoustic research group (LISA), both at the University of Brasília, Brazil. Contact him at fbvidal@unb.br.


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How to Cite

Salas, J., Patterson, G., & de Barros Vidal, F. (2022). A Systematic Mapping of Artificial Intelligence Solutions for Sustainability Challenges in Latin America and the Caribbean. IEEE Latin America Transactions, 20(11), 2312–2329. Retrieved from https://latamt.ieeer9.org/index.php/transactions/article/view/6816