By Sarah Marquis
Hackfort, S., Marquis, S., & Bronson, K. (2024). Harvesting value: Corporate strategies of data assetization in agriculture and their socio-ecological implications. Big Data & Society, 11(1).
https://doi.org/10.1177/20539517241234279
In the past decade, much attention has been paid to the ways that Big Tech companies like Google and Facebook leverage personal data to create value, both economic and otherwise. Meanwhile, as digital technologies become more ubiquitous in agriculture, we thought it necessary to interrogate the ways that agricultural big data is being assetized in parallel ways.
In this paper, we ask the following question: how is agricultural data transformed into value by the most powerful agribusinesses and ag-tech firms?
To answer our research question, we read many financial records and annual reports and analyzed earnings calls to see how agricultural data was valued and discussed by multi-national agribusinesses like John Deere, Bayer, BASF and Farmers Edge. We came to several conclusions. The first is that any attempt to systematically examine what agribusinesses do with agricultural data is impaired by legal mechanisms that obfuscate data practices, datasets, and algorithms: copyright, intellectual property law, trade secrecy law, and arbitration agreements all allow for proprietary technologies and a high degree of vagueness and opacity. This is a finding in and of itself; such obfuscation prevents critical analysis and the kind of oversight that the equitable governance of technology requires. Our second, broader argument is that data itself is very likely an asset for agricultural firms, which now uniformly include big data-based services in their portfolios. We outline three strategies that firms use (or are likely to use) to generate value from agricultural data:
Agribusinesses use agricultural big data to secure relationships in which users are dependent upon them.
Agribusinesses gain from practices of price-setting and data sharing.
Agricultural big data is used to develop new products and target marketing materials to users.
The strategies we have identified have socio-ecological implications; they affect social justice, food sovereignty, and sustainability, the latter of which does not always receive due attention in critical data studies (c.f. Gabrys, 2016; Goldstein and Nost, 2022). Our results indicate the reproduction of asymmetrical power relations in the agri-food system favoring corporations and the continuation of long-standing dynamics of inequalities. We can infer that the big data-based predictions agribusinesses sell to farmers are directed toward a productivist model of “surveillance agriculture” (Stone, 2022a) that reinforces existing patterns of unsustainable agro-industrial farming and renders other routes, such as agroecology, peasant farming, and organic farming less legitimate and possible.
