{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,11]],"date-time":"2026-01-11T15:34:43Z","timestamp":1768145683790,"version":"3.49.0"},"reference-count":0,"publisher":"Koozakar LLC","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JEPSD"],"abstract":"<jats:p>Climate change has been found to disproportionately affect rural communities across \nAfrica, which, as a result, deepens existing socio-economic and environmental \ninequalities. As global efforts shift towards Artificial Intelligence (AI)-driven solutions \nto enhance climate resilience and adaptation, recent scholarship highlights their \npotential, such as predictive modeling, resource management, and disaster response. \nHowever, applying these solutions in African rural contexts, characterized by limited \naccess to technology, infrastructure, and resources, remains a challenge. This challenge \nbecomes more alarming when considering the human and social dimensions of climate \nvulnerability, where current AI-driven approaches often fail to engage with the lived \nrealities, traditional knowledge systems, and unique challenges of rural populations.To \naddress these gaps, this paper adopts a Complementary Framework that views AI and \nIndigenous Knowledge Systems not as opposing forces, but rather, as mutual which \ncould coexist for productive outcomes. It does these shortcomings by critically \nevaluating the integration of AI-driven solutions into rural African settings. It \nemphasises the need for inclusivity and the recognition of indigenous knowledge and \napproaches through the use of machine learning. Hence, by identifying systemic \nbarriers; technological, social, and cultural, that hinder effective implementation, the \npaper calls for a shift away from a purely techno-centric paradigm, arguing for a more \ninclusive and participatory model that considers the voices, needs, expertise, and \noverall reality of Africa\u2019s vulnerable rural communities.<\/jats:p>","DOI":"10.69798\/84663696","type":"journal-article","created":{"date-parts":[[2025,8,10]],"date-time":"2025-08-10T12:41:41Z","timestamp":1754829701000},"page":"59-70","source":"Crossref","is-referenced-by-count":0,"title":["Towards Inclusive Climate Solutions: Merging Indigenous African Knowledge and Artificial Intelligence in Rural Communities"],"prefix":"10.69798","volume":"1","author":[{"name":"Lagos State University, Ojo. Nigeria","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1647-7025","authenticated-orcid":false,"given":"Damilola","family":"Olatade","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-2093-2971","authenticated-orcid":false,"given":"Ridwan","family":"Mogaji","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"name":"Lagos State University, Ojo. Nigeria","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"50185","published-online":{"date-parts":[[2025,7,1]]},"container-title":["Journal of Ecopolitics, Peace, and Sustainable Development"],"original-title":[],"deposited":{"date-parts":[[2026,1,11]],"date-time":"2026-01-11T13:04:42Z","timestamp":1768136682000},"score":1,"resource":{"primary":{"URL":"https:\/\/koozakar.com\/journals\/article\/KJ-36882968"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7,1]]},"references-count":0,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,7,1]]}},"URL":"https:\/\/doi.org\/10.69798\/84663696","relation":{},"subject":[],"published":{"date-parts":[[2025,7,1]]}}}