An interdisciplinary approach to artificial intelligence in agriculture

M Ryan, G Isakhanyan… - NJAS: Impact in …, 2023 - Taylor & Francis
NJAS: Impact in Agricultural and Life Sciences, 2023Taylor & Francis
Innovations in digital technologies, especially in artificial intelligence (AI), promise
substantial benefits to the agricultural sector. Agriculture is increasingly expected to ensure
food security and food safety while at the same time considering the environmental aspects.
AI in the agricultural sector offers the potential to feed a continuously growing global
population and still contribute to achieving the UN's Sustainable Development Goals
(SDGs). Despite its promises, the use of AI in agriculture is still limited. We argue that the …
Abstract
Innovations in digital technologies, especially in artificial intelligence (AI), promise substantial benefits to the agricultural sector. Agriculture is increasingly expected to ensure food security and food safety while at the same time considering the environmental aspects. AI in the agricultural sector offers the potential to feed a continuously growing global population and still contribute to achieving the UN’s Sustainable Development Goals (SDGs). Despite its promises, the use of AI in agriculture is still limited. We argue that the slow uptake is due to the diverse ways in which AI impacts the agri-food industry, due to the diversity of foods, supply chains, climates, and land in the agricultural sector. We propose that this is also exacerbated by ethical concerns arising from AI use, the varying degrees of technological development and skills, and the economic impacts of agricultural AI. A literature review of multiple disciplines in agricultural AI (economic, environmental, social, ethical, and technological) and a focus group of experts. AI-powered systems in agriculture raise various sets of concerns in multiple disciplines that need to be aligned to provide sustainable AI solutions for the agriculture domain. Our research proposes that it is important to adopt an interdisciplinary approach when developing AI in agriculture. AI in agriculture should be developed by interdisciplinary collaboration because it has a greater chance to be robust, economically-valuable and socially desirable, which may lead to greater acceptance and trust among farmers when using it.
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