Indigenous Knowledge Systems (IKS), AI and Climate Change.

Résumé

The accelerated impacts of climate change have significantly worsened forest degradation and land mismanagement. This study aimed to explore how AI could be integrated with IKS to promote climate-resilient land and forest management. A mixed-methods approach was employed. Primary data were collected through semi-structured interviews and focus group discussions, while secondary data were obtained from relevant literature. The population sampling technique used was purposive, and the sample size was 30. The selected participants were 12 Indigenous elders, 10 traditional leaders, and 8 environmental officers. Data were gathered through 15 semi-structured interviews, 3 focus group discussions, and a review of relevant secondary sources. Indigenous indicators, such as phenological patterns and sacred groves, were carefully documented. Findings showed that 85% of environment officers and traditional elders believed that traditional ecological markers could complement AI algorithms. The primary data confirmed the continued effectiveness of Indigenous monitoring methods, while secondary sources supported AI’s potential in recognising patterns. However, 70% expressed concerns over data ownership, cultural sensitivity, and the relevance of AI applications. The study recommended the integration of IKS and AI for climate resilience through Forest and Land Conservation.