Bionote
Anna Massfeller is a doctoral student in Agricultural Economics at the University of Bonn’s Institute for Food and Resource Economics. Her research combines data science methods and behavioral economics to better understand farmers’ decision-making processes. In her research, she often collects primary data through surveys and experiments to explore the factors influencing farmers’ adoption of novel technologies. With a focus on environmental sustainability and practical policy design, Anna examines how farmers respond to various incentives and innovations, including result-based agri-environmental schemes, digital decision support tools, and weeding robots.
Presentation Abstract
Development of Artificial intelligence technologies have the potential to improve farming efficiency globally. Decision support tools are one promising application with the potential to increase farming efficiency. However, for medical and financial applications, there is evidence of users’ reluctance against (potentially superior) AI-based recommendations – a phenomenon known as Algorithm Aversion. This study is the first to investigate Algorithm Aversion in the farming context. Using survey data from a representative sample of 250 German farmers we focus on farmers’ intention to use an AI-DST for wheat fungicide application. For the experimental study we propose and apply a novel Bayesian probabilistic programming workflow. This approach allows jointly analyzing an extended version of the Unified Theory of Acceptance and Use of Technology with a willingness-to-pay experiment. We find that Algorithm Aversion plays an important role in farmers’ decision-making: Adoption intention and willingness-to-pay at a given performance level decrease with increasing AI-Anxiety. For most farmers, an AI-DST would need to perform between 11% and 30% better than a human advisor in order to be perceived as equally valuable. Our results call for a consideration of farmers’ algorithm aversion for technology development and advisory service design.
Co-Authors: Alexa Leyens, Daniel Hermann, Hugo Storm