The Dismal Harvest: The Uneven Landscapes of AI in Agriculture

Abstract

In this intervention, I examine artificial intelligence (AI) in agriculture through a political ecology lens, analysing how promises of productivity, efficiency, and sustainability take shape across uneven postcolonial landscapes. Building on feminist and critical agrarian perspectives, I focus on the material relations of farming to show that AI in agriculture, often portrayed as immaterial, relies on deeply material infrastructures—sensors, data centres, energy systems, and extractive supply chains. Tracing how AI-driven digital agriculture and smart agriculture reconfigure relations between farmers, land, and technology, I argue that care for agroecosystems is increasingly displaced by care for digital infrastructures, with dire consequences for the social and ecological relations that sustain rural labour, land, and livelihoods. Focusing on emergent applications of AI in agriculture in the Global South, I show how these technologies consolidate corporate power, erode agrarian knowledges, and reproduce postcolonial inequalities under neoliberal capitalism. I conceptualise AI as a socioecological fix, stressing the need to re-spatialise and historicise technological change in the context of agrarian change, by attending to its infrastructural and ecological entanglements. I situate this analysis within debates on economies of repair, arguing that understanding AI in agriculture requires attention not only to breakdown and failure but also to the everyday practices of repair—technical, ecological, and social—that sustain digital infrastructures and reveal the uneven burdens of maintaining them across agrarian worlds. This intervention contributes to the Themed Intervention, 'Geographies of Responsibility, Care and Repair in Digital Worlds of AI'.