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Using artificial intelligence in support of climate change adaptation Africa: potentials and risks

Author

Listed:
  • Walter Leal Filho

    (Manchester Metropolitan University
    Hamburg University of Applied Sciences)

  • Gouvidé Jean Gbaguidi

    (Hamburg University of Applied Sciences
    University of Lomé)

Abstract

Climate change poses significant threats to African countries, with increasing temperatures, erratic rainfall patterns, and extreme weather events impacting ecosystems, agriculture, water resources, and human livelihoods. Artificial intelligence (AI) may offer valuable support in climate change adaptation efforts in the field of agriculture. However, considerable constraints also need to be addressed to maximise AI’s effectiveness. Against this background, this article outlines the potentials and risks of deploying AI in agriculture, as well as the need for clear regulatory frameworks for AI deployment, establishing guidelines that promote innovation while addressing ethical and legal concerns.

Suggested Citation

  • Walter Leal Filho & Gouvidé Jean Gbaguidi, 2024. "Using artificial intelligence in support of climate change adaptation Africa: potentials and risks," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-5, December.
    • Handle: RePEc:pal:palcom:v:11:y:2024:i:1:d:10.1057_s41599-024-04223-7
    DOI: 10.1057/s41599-024-04223-7
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    References listed on IDEAS

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    1. Amuktamalyada Gorlapalli & Supriya Kallakuri & Pagadala Damodaram Sreekanth & Rahul Patil & Nirmala Bandumula & Gabrijel Ondrasek & Meena Admala & Channappa Gireesh & Madhyavenkatapura Siddaiah Ananth, 2022. "Characterization and Prediction of Water Stress Using Time Series and Artificial Intelligence Models," Sustainability, MDPI, vol. 14(11), pages 1-18, May.
    2. Omolola M. Adisa & Joel O. Botai & Abiodun M. Adeola & Abubeker Hassen & Christina M. Botai & Daniel Darkey & Eyob Tesfamariam, 2019. "Application of Artificial Neural Network for Predicting Maize Production in South Africa," Sustainability, MDPI, vol. 11(4), pages 1-17, February.
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