A bibliometric analysis of AI research related to climate change and health in Africa reveals a significant gap between global and African research focuses. While global research leans towards complex predictive models for planetary health, African research concentrates on localized, reactive solutions for immediate infectious disease management. This disparity is attributed to substantial structural barriers in Africa, including limited computational resources, data fragmentation, and energy instability, which impede the scaling of advanced AI applications. The study advocates for a redirection of international funding from pilot projects to the development of foundational digital infrastructure and localized AI frameworks within Africa. AI
IMPACT Highlights critical infrastructure and data needs for AI adoption in developing regions, impacting global AI research equity.
RANK_REASON The item is a research paper detailing a bibliometric analysis of AI applications in a specific region and domain. [lever_c_demoted from research: ic=1 ai=1.0]
- Africa
- alphaXiv
- Artificial Intelligence
- arXivLabs
- CatalyzeX
- climate change
- Connected Papers
- DagsHub
- Gotit.pub
- Hugging Face
- Litmaps
- ScienceCast
- scite Smart Citations
- Scopus
- VOSviewer
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