Technology and social cohesion: deploying artificial intelligence in mediating herder-farmer conflicts in Nigeria

Abstract

This paper argues for the role of technology, such as artificial intelligence, which includes machine learning, in managing conflicts between herders and farmers in Nigeria. Conflicts between itinerant Fulani herders and farmers over the years have resulted in the destruction of lives, properties, and the displacement of many indigenous communities across Nigeria, with devastating social, economic and political consequences. Over time, the conflicts have morphed into ethnic stereotypes, allegations of ethnic cleansing, forceful appropriation and divisive entrenchment of labels that are inimical to national existence. The reality of climate change and increased urbanization suggest that conflicts are likely to exacerbate over shrinking resources in the near future. Finding solutions to the conflicts, therefore requires innovative thinking capable of addressing the limits of past approaches. While mindful of the human and political dimension of the conflicts, I argue using the method of philosophical analysis that technology possesses the capacity for social transformation, and make a case for the modernization of grazing culture and the curbing of crossborder grazing through machine learning (ML) and other forms of artificial intelligence. Machine Learning represents a transformative technology that addresses the security challenges of irregular migration, accommodates the nomadic and subsistent mode of farming associated with the conflicting parties while enabling a gradual but stable transition to full modernization. I conclude that machine learning holds many prospects for minimizing conflicts and attaining social cohesion between herders and farmers when properly complemented by other mechanisms of social cohesion that may be political in nature.