Radiant Earth, a nonprofit technology company supporting open machine learning technologies for Earth science, today released a white paper exploring a data ethics framework for farmers to achieve data ownership.
Emerging technologies, such as those combining artificial intelligence and Earth observation satellite data, are essential to “smart farming” innovations. They provide the necessary information to develop agricultural monitoring systems such as cropland and crop type mapping. Still, it also creates a challenge regarding data ownership between farmers and agricultural technology providers (ATPs).
ATPs provide farmers with the technology to collect data from their farm fields and operations to support data-driven decisions leading to improved production. ATPs may also offer analytical services or assist other organizations in deploying smart technologies. The increasing deployment of these technologies creates a data-hungry environment and raises subsequent issues around fairness, ownership, and equitable practice of big data in agriculture.
The debate about smart farming’s data ownership and any consequences that might arise mainly occurs in high-income economies that can deploy the infrastructure readily and where most farmers can advocate for their interests. Smallholder farmers have the most to gain from these smart farming innovations in low- and middle-income countries. However, they often need a data ethics framework that adequately considers their concerns. The white paper addresses the data ownership issue resulting from smart farming. In particular, the white paper examines how high-income countries currently address smart farming’s resulting data ownership issues and identifies ways to preemptively address relevant data ethics issues and policies for low- and middle-income countries.
Radiant Earth completed this white paper through a contract from Enabling Crop Analytics at Scale (ECAAS), an initiative of the Bill & Melinda Gates Foundation managed by Tetra Tech.
Download the white paper for free.