Big Tech Meets Big Ag: Diversifying Epistemologies of Data and Power

Abstract

Since 2018, there has been a public backlash against Big Tech – notably against Facebook and Google which have been labeled as ‘ethical miscreants’ that abuse personal data collected from internet use for corporate profit (Solon, 2017; Zuboff, 2019). Less visible both in terms of popular outcry and critical scholarship are some of the largest and longest-standing oligopolistic corporations in North America – big agribusinesses – which increasingly center their business models on the collection and processing of data. For example, every John Deere tractor manufactured today is a piece equipment containing built-in sensors that collect and stream data about soil and crop conditions. Deere & Company has signed 13 legal agreements with seed/chemical corporations, such as Bayer/Monsanto, that allow for data transfer between tractors and other input supply (e.g. chemicals) corporations. As large agribusiness companies become data powerhouses, critical scholarship and activism has not kept up. Compared to critical scholarly attention to big data in other sectors, there is a small, although rapidly growing, cohort of critical scholars working on agricultural big data (see Wolf and Wood, 1997; Driessen and Heutinck, 2015; Carolan 2017; Eastwood et al., 2017; Klerkx et al., 2019; Bronson, 2019). Moreover, the tremendous amount of public activism against big data and algorithms in other sectors has not been applied to agribusinesses – those historically dealing in machinery, seeds and chemicals – whom we can increasingly read as data companies. In this paper, we explore the intersection of Big Tech and big agribusiness. More broadly, we illustrate how an STS lens can be leveraged to broaden and deepen understandings of Big Tech by analyzing and comparing how Big