SOURCE-LINKED INTELLIGENCE

Data Governance for Equitable and Sustainable Digital Food Systems

CORDIS · observation · Publication date unknown

ution."" Data collected from digital sensors implanted into soil, satellites, and mobile phones offer the possibility of gathering unprecedented amounts of data. Combined with predictive analytics of artificial intelligence, this data promises critical insights for governments, food producers, and the private sector to address the challenges of food insecurity and climate change. Yet with these new flows of data also come risks. Unequal capacity to collect and extract value from data can exacerbate structural power asymmetries in food systems, with important implications for human rights. To mitigate these risks, it is essential to establish robust data governance, itself no easy task. Agricultural data defy the legal categories that have guided data protection in other sectors. Moreover, most models of agricultural data governance have been developed in the Global North and may not be fit for the Global South, where smallholders make up the majority of food producers. This project, Data Governance for Equitable and Sustainable Digital Food Systems (DIGIFOOD), examines these emerging

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recordType

award

status

SIGNED

region

EU

value

1998860

unit

EUR