An interdisciplinary approach to artificial intelligence in agriculture

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.

KEYWORD:

• Artificial intelligence
• ethics
• social-economic
• technological
• interdisciplinarity
• digital agriculture

Acknowledgements

We would like to thank Sjaak Wolfert, the two anonymous reviewers, and the editor of NJAS, for their comments and improvements on our paper.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

¹ Wageningen University and Research.

² This is not to say that other aspects, such as legal, political, and governance are less important. Many of the topics discussed in the literature also have distinct legal and political dimensions (e.g. justice and privacy are ethical issues but also have strong legal implications). However, due to the relatively low level of technological and social readiness level of agricultural AI, the technological, social-economic and ethical aspects are of more importance. Once agricultural AI achieves a higher readiness level, we expect the legal, political and governance disciplines to play a more important role.

³ See: http://www.sweeper-robot.eu; http://trimbot2020.webhosting.rug.nl; and https://www.lely.com/solutions/housing-and-caring/discovery-collector.

⁴ This section does not go into the diversity of ethical frameworks (e.g. utilitarianism, Kantianism, and virtue ethics) that could be applied in such analysis, but will take a more pragmatic approach, providing concerns, impacts, and debates, around ethical topics and themes within the agricultural AI literature. While these frameworks may be useful for providing prescriptions and recommendations, the level of analysis aims at collecting the diversity of viewpoints on ethical issues, rather than limiting to one framework, which may exclude many relevant ethical topics discussed within the debates.

Additional information

Funding

This research received funding from the Management Team at Wageningen Economic Research