Are Farmers Algorithm-Averse? The Case of Decision Support Tools in Crop Management

Anna Massfeller, Daniel Hermann, Alexa Leyens and Hugo Storm
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Anna Massfeller: University of Bonn

No 54khv_v1, SocArXiv from Center for Open Science

Abstract: The advancement of artificial intelligence (AI) technologies has the potential to improve farming efficiency globally, with decision support tools (DSTs) representing a particularly promising application. However, evidence from medical and financial domains reveals a user reluctance to accept AI-based recommendations, even when they outperform human alternatives. This is a phenomenon known as “algorithm aversion” (AA). This study is the first to examine this phenomenon in an agricultural setting. Drawing on survey data from a representative sample of 250 German farmers, we assessed farmers’ intention to use and their willingness-to-pay for DSTs for wheat fungicide application either based on AI or a human advisor. We implemented a novel Bayesian probabilistic programming workflow tailored to experimental studies, enabling a joint analysis that integrates an extended version of the unified theory of acceptance and use of technology with an economic experiment. Our results indicate that AA plays an important role in farmers’ decision-making. For most farmers, an AI-based DST must outperform a human advisor by 11–30% to be considered equally valuable. Similarly, an AI-based DST with equivalent performance must be 21–56% less expensive than the human advisor to be preferred. These findings signify the importance of examining AA as a cognitive bias that may hinder the adoption of promising AI technologies in agriculture.

Date: 2025-12-07
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Persistent link: https://EconPapers.repec.org/RePEc:osf:socarx:54khv_v1

DOI: 10.31219/osf.io/54khv_v1

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