Tue. Dec 10th, 2024
AIDA and AGRI MEPs discussed the future of agriculture in the digital age on Monday, and how AI could contribute to a more efficient and sustainable agri-food chain.

In this public hearing, the Special Committee on Artificial Intelligence in a Digital Age (AIDA) and the Committee on Agriculture and Rural Development (AGRI) hosted two panels with leading experts on AI’s potential contribution to agricultural practices and how to balance the effects of technological advancements.

You can catch up with the full debate here.

“Artificial intelligence has no purpose in and of itself. Its role, as a sophisticated technology that uses increasingly complex data to make increasingly accurate predictions, projections, and in some cases decisions, is to improve the way our economies and societies function. Using AI in agriculture is ultimately, just like using it in any other domain, a way to improve the well-being of our citizens” said AIDA committee Chair Dragoș Tudorache (Renew, RO).

“AI in agriculture will help us make more efficient use of the land, optimize our resource use, shorten supply chains, and increasing the quality of the agricultural products we consume. But this is not just about a linear increase in efficiency; by researching and deploying AI technology in agriculture and interdependent domains we are also increasing our strategic resilience and reducing our impact on the environment, making good on Europe’s ambition to become a global player and model for the world” he said.

Background

A study requested by the AIDA committee highlights that AI applications in the agricultural sector mainly focus on intensive and industrialised farming systems. The use of unmanned aerial vehicles has allowed scaling up information collection, allowing the development of applications ranging from the identification of water stress, monitoring of crop diseases and weed mapping to crop yield prediction. AI also underwrites the development of robotic applications in agriculture, for example for weeding and harvest.

The most advanced use case of AI in the agricultural sector is precision agriculture, where AI enabled processing of data allows farmers to make temporally and spatially tailored management decisions, leading to a more efficient use of inputs such as fertilisers and pesticides.

The debate took place as EU institutions are working on proposals on the future of the Common Agricultural Policy (CAP), as well as on the Farm to Fork Strategy.

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