<p>Artificial intelligence (AI) is rapidly expanding within agricultural systems, yet public attitudes toward its use remain poorly understood. We analyse single-word responses from public surveys in the United Kingdom (<i>N</i> = 1054) and the United States (<i>N</i> = 998) to quantify both sentiment polarity and emotional responses to agricultural AI. Using lexicon-based methods, we find that sentiment is relatively more negative in the United States, although the overall emotional structure is similar across both countries. Fear and anticipation emerge as the dominant emotions, indicating persistent ambivalence toward AI in agriculture. Cross-country differences are evident, with statistically significant higher levels of anger in the United States compared to the United Kingdom. Regression and marginal effect estimates show that attitudes toward science and technology are the most consistent predictors of both sentiment and emotional responses, significantly reducing negative emotions while increasing positive ones. Demographic factors play a secondary role, although age accounts for systematic variation, particularly in the United Kingdom. These findings suggest that public sentiments toward agricultural AI are primarily shaped by underlying orientations toward science and technology rather than socioeconomic characteristics. Understanding these dynamics in affective association is critical for designing governance and communication strategies that foster trust and support the responsible adoption of AI in agricultural systems.</p>

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

Public sentiments toward artificial intelligence in agriculture across the United States and United Kingdom

  • Bryony Sharp,
  • Albert Boaitey,
  • Carmen Hubbard

摘要

Artificial intelligence (AI) is rapidly expanding within agricultural systems, yet public attitudes toward its use remain poorly understood. We analyse single-word responses from public surveys in the United Kingdom (N = 1054) and the United States (N = 998) to quantify both sentiment polarity and emotional responses to agricultural AI. Using lexicon-based methods, we find that sentiment is relatively more negative in the United States, although the overall emotional structure is similar across both countries. Fear and anticipation emerge as the dominant emotions, indicating persistent ambivalence toward AI in agriculture. Cross-country differences are evident, with statistically significant higher levels of anger in the United States compared to the United Kingdom. Regression and marginal effect estimates show that attitudes toward science and technology are the most consistent predictors of both sentiment and emotional responses, significantly reducing negative emotions while increasing positive ones. Demographic factors play a secondary role, although age accounts for systematic variation, particularly in the United Kingdom. These findings suggest that public sentiments toward agricultural AI are primarily shaped by underlying orientations toward science and technology rather than socioeconomic characteristics. Understanding these dynamics in affective association is critical for designing governance and communication strategies that foster trust and support the responsible adoption of AI in agricultural systems.