Artificial intelligence in the agri-food sector: Applications, risks and impacts
Large companies supplying AI software for analysis in agriculture can have an effect on the way agriculture evolves. On the other hand, retailers collect and analyse a massive quantity of data about the preferences and behaviour of their customers. A combination of these elements may create a potential for biased recommendations to farmers, to favour the optimisation of supplies being sent to specific food retailers. New start-ups could take a different view of the data and come up with new applications that may give more independent advice to farmers. European Union legislative initiatives should ensure that this does not lead to a reduction in agrobiodiversity. As algorithms are under continuous construction, and only a limited number of large companies can sustain such efforts, this may also lead to a small base for decision making and may lead to biased decision making.
In this study, sensing and data collection in different agri-food sectors are described, together with how the data can lead to better management and better decision making in crop and animal production.
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project report
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European Parliament / Panel for the Future of Science and Technology (STOA) (STOA)
How artificial intelligence works (STOA)