Digital agriculture refers to a suite of disruptive technologies that leverage big data in order to better monitor, assess, and manage farm-level production.
The hallmark of these technologies is the flow of intensive farm-level data to external entities that seek to make production more precise and more profitable. Proponents claim that by creating a suite of feedback systems that integrate production and consumer data, digital agriculture will enable farmers to make better informed and more timely decisions around how best to manage their plots. This much-heralded transformation in decision-making has significant implications for smallholder farming systems—family-run, subsistence farmers.
In 2021, I launched a SSHRC-funded research project that aims to examine how and if digital agriculture can be implemented successfully in low-input smallholder farming systems. This project has two broad aims: First, we will narrow in on the actors promoting digital agriculture and reveal how their aims and interests are translated into predictive algorithms designed to modify farmer behaviour. Second, we will analyze the interactions between these digital technologies and smallholder farmers. This research will allow us to assess how the introduction of digital agriculture will impact farmer behavioural change in terms of both decision-making and social relations.