The Future of Farming: The (Non)-Sense of Big Data Predictive Tools for Sustainable EU Agriculture

Margot Luyckx*, Leonie Reins

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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Abstract

The agricultural sector is one of the key sectors that need to be transformed in order to mitigate climate change. The use of predictive models supported by big data (“big data predictive tools”) has already been named in the literature as one key possibility to facilitate this change. This contribution maps out the possibilities and potential harms of big data predictive tools for sustainable agricultural use and analyses the role that regulation can play to address these challenges, answering the following question: how can the EU Common Agricultural Policy (CAP) and the European Green Deal address potential harms of big data predictive tools for sustainable agriculture while safeguarding its possibilities. Based on a combination of doctrinal legal research and a review of secondary sources, this contribution concludes that in theory, both instruments recognize the possibilities of big data predictive tools for agriculture and emphasize the necessity of environmental sustainability in this regard. However, some of the most promising and essential elements of achieving sustainable digitalisation in agriculture, risk not being substantiated because of a watered-down CAP, significant focus on larger farms and strong member state margin of appreciation. Although at first sight the CAP and Green Deal seem aligned, it can be concluded that the depth has yet to be proven. Whether this depth can be substantiated will also determine the extent to which digital technologies, such as big data predictive tools, will help in enforcing a sustainable agriculture or risk intensifying unsustainable practices in the EU.
Original languageEnglish
Article number12968
JournalSustainability
Volume14
Issue number20
DOIs
Publication statusPublished - 11 Oct 2022

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