Data Farm: On Precision Agriculture and the Political Ecology of Disruption

To read the headlines, American farming is on the edge of a profound and unprecedented revolution: a “big data revolution on the farm” (Wihbey 2015), the “third green revolution” (CEMA 2016), or, simply, “the next great agricultural revolution” (Powell 2017). This revolution, known as “precision agriculture” (PA), is an emerging approach to food production in which farmers leverage the power of digital sensing and big data analytics to manage their crops, livestock, and operations at formerly impossible levels of detail. Proponents assert this more granular information translates to greater control over inputs and costs, in turn shrinking agricultural pollution while increasing productivity.

A closer look at the complicated mix of forces driving PA reveals that its benefits appear more ambiguous, and likely to be less evenly distributed, than current accounts suggest. PA unfolds within an economic and political context likely to reward increases in farm consolidation, automation, and managerial control, conditions that benefit larger farms and landholders, influential agricultural companies, and financiers over smallholder farms, farm laborers, or other species.

Through historical contextualization and comparative study of PA adoption in the Northeast vs. the Great Plains, I show how the development and implementation of PA systems are less a revolutionary, technology-driven break with the past, than an intensification and extension of an already existing socio-economic logic of capitalist accumulation. I argue that while PA may contribute to significant changes in farming, these will neither necessarily nor automatically accrue in the form of greater independence for more farmers, greater food security for more people, or large-scale reductions in pollution and ecological disruption caused by conventional farming. Only by understanding the real social and historical dimensions of precision agriculture can we appreciate how best to avoid its pitfalls, and ensure its potential benefits are as evenly and effectively shared as possible.