Configurations of human-AI work in agriculture

Abstract

Agriculture is making leaps in digitalization and the development of artificial intelligence (AI) systems, e.g., decision support systems, sensors, or autonomous vehicles. However, adoption and widespread use of these technologies remains below expectations with negative consequences for digitally advancing the agricultural industry. Therefore, this study investigates the configurations of human-AI work, in particular, human-AI decision-making. Configurations describe the interactions between workers and intelligent systems, emphasizing the adoption and use of technologies in-situ. This study targets agricultural farms in Germany, collecting qualitative data at small and medium-sized businesses. From this data, the paper examines how configurations of human-AI work emerge and how explanations influence these configurations in the context of agricultural work. Theoretical contributions include a new understanding of how agricultural workers adopt and work with AI to make decisions. Practical contributions include more accessible AI systems, easing transfer into practice, and improving agricultural workers’ interactions with AI.