Artificial intelligence in farming: Challenges and opportunities for building trust

Maaz Gardezi*, Bhavna Joshi, Donna M. Rizzo, Mark Ryan, Edward Prutzer, Skye Brugler, Ali Dadkhah

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

7 Citations (Scopus)

Abstract

Artificial intelligence (AI) represents technologies with human-like cognitive abilities to learn, perform, and make decisions. AI in precision agriculture (PA) enables farmers and farm managers to deploy highly targeted and precise farming practices based on site-specific agroclimatic field measurements. The foundational and applied development of AI has matured considerably over the last 30 years. The time is now right to engage seriously with the ethics and responsible practice of AI for the well-being of farmers and farm managers. In this paper, we identify and discuss both challenges and opportunities for improving farmers’ trust in those providing AI solutions for PA. We highlight that farmers’ trust can be moderated by how the benefits and risks of AI are perceived, shared, and distributed. We propose four recommendations for improving farmers’ trust. First, AI developers should improve model transparency and explainability. Second, clear responsibility and accountability should be assigned to AI decisions. Third, concerns about the fairness of AI need to be overcome to improve human-machine partnerships in agriculture. Finally, regulation and voluntary compliance of data ownership, privacy, and security are needed, if AI systems are to become accepted and used by farmers.

Original languageEnglish
Pages (from-to)1217-1228
JournalAgronomy Journal
Volume116
Issue number3
Early online date5 Apr 2023
DOIs
Publication statusPublished - 2024

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