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Artificial intelligence in farming: Challenges and opportunities for building trust

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dc.contributor.authorGardezi, Maazen
dc.contributor.authorJoshi, Bhavnaen
dc.contributor.authorRizzo, Donna M.en
dc.contributor.authorRyan, Marken
dc.contributor.authorPrutzer, Edwarden
dc.contributor.authorBrugler, Skyeen
dc.contributor.authorDadkhah, Alien
dc.date.accessioned2023-06-23T14:00:27Zen
dc.date.available2023-06-23T14:00:27Zen
dc.date.issued2023-05en
dc.description.abstractArtificial 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.en
dc.description.notesACKNOWLEDGMENTS This research is based upon work supported by the National Science Foundation under Grant Number 2202706 and 2026431. The authors thank the anonymous reviewers and journal editor for their valuable suggestions to improve the manuscript. Any opinions, findings, and conclusions or recommendations expressed in this paper are those of the authors and do not necessarily reflect the views of the National Science Foundation.en
dc.description.sponsorshipNational Science Foundation [2202706, 2026431]en
dc.description.versionPublished versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.doihttps://doi.org/10.1002/agj2.21353en
dc.identifier.eissn1435-0645en
dc.identifier.issn0002-1962en
dc.identifier.urihttp://hdl.handle.net/10919/115499en
dc.language.isoenen
dc.publisherWileyen
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectbig dataen
dc.subjectprecision agricultureen
dc.subjectinnovationen
dc.titleArtificial intelligence in farming: Challenges and opportunities for building trusten
dc.title.serialAgronomy Journalen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten

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