Journal Article
Published 2026
Mapping the potential and limitations of using generative AI technologies to address socio-economic challenges in LMICs
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Dr. Amelia Taylor
Co-author
Computer Science & Information Systems (CSIS)
30 total publications
Amelia Taylor is a lecturer in Artificial Intelligence at the Malawi University of Business and Applied Sciences, former the University of Malawi, the Polytechnic. She teaches Artificial Intelligence, Computational Intelligence and programming module...
UN Sustainable Development Goals
Global Impact
Research Fields & Tags
Primary Author
Rachel Adams
Co-Authors
Dr. Amelia Taylor
Abstract
Drawing on the experiences and lessons learned from researchers based in low- and middle-income countries (LMICs) that leverage generative artificial intelligence (GenAI) technologies to address socio-economic challenges, we showcase the considerable potential to use GenAI to accelerate the progress towards achieving some of the Sustainable Development Goals, as well as considerable obstacles for creating locally adapted AI tools for fair development in LMICs. An expanded evidence base on GenAI in resource-limited settings is crucial for policymakers to understand opportunities and risks, while rights-based safeguards against AI harms can be strengthened by the lived experiences of local projects.
Year of Publication
2026
External Digital Object URL
Access Publisher / External Source
Journal Name
Nature Computational Science
Volume
6
Issue
1
Page Numbers
441–449
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