Public Acceptance of Robots and Autonomous Crop Farming – A Cluster Analysis of German Citizens’ Attitudes and Concerns
DOI:
https://doi.org/10.52825/gjae.v74i.2283Keywords:
Autonomous Crop Farming, Responsible Research and Innovation, Public Acceptance, PAM ClusteringAbstract
Public acceptance is essential for technology innovation in agriculture. Due to the recent advances in artificial intelligence, robotics and autonomous systems (RAS) could soon revolutionize crop farming landscapes. What is society's view on crops being produced with the help of autonomous machines and how do different groups accept the technologies? A sample of 567 German citizens was segmented into clusters using an unsupervised machine-learning technique. The analysis elaborated on heterogeneity in public attitudes concerning challenges and advances of RAS and investigated political attitudes in relation to RAS attitudes. A majority of the participants are in favor of the use of RAS. While 41% of the participants positioned themselves as positive (Proponents), about 19% even showed a strong positive attitude towards RAS use (Enthusiasts). The ease of farm work and environmental benefits drive RAS acceptance among Proponents and Enthusiasts. Nevertheless, 29% support RAS use overall but raise concerns regarding socio-economic impacts (Skeptical Proponents), and 11% (Skeptics) take a skeptical stance. Skeptical Proponents and Skeptics fear negative consequences for family farms and are doubtful about potential positive environmental contributions. A higher share of right-wing and non-voter participants is detected among the more skeptical clusters, while green (environmental) party voters are among the more positive participants. Potential concerns should be recognized and addressed by the farming sector on the development path to more automated agriculture. Food production is a sensitive topic affecting everyone, which should be considered in communication efforts. The advantages of RAS technologies need to be articulated through targeted scientific communication.
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Copyright (c) 2025 Hendrik Hilmar Zeddies, Gesa Busch
This work is licensed under a Creative Commons Attribution 4.0 International License.
Accepted 2025-02-07
Published 2025-03-31
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Deutsche Forschungsgemeinschaft
Grant numbers EXC 2070–390732324-PhenoRob