Abstract
This paper contributes to our understanding of farm data value chains with assistance from 54 semi-structured interviews and field notes from participant observations. Methodologically, it includes individuals, such as farmers, who hold well-known positionalities within digital agriculture spaces—platforms that include precision farming techniques, farm equipment built on machine learning architecture and algorithms, and robotics—while also including less visible elements and practices. The actors interviewed and materialities and performances observed thus came from spaces and places inhabited by, for example, farmers, crop scientists, statisticians, programmers, and senior leadership in firms located in the U.S. and Canada. The stability of “the” artifacts followed for this project proved challenging, which led to me rethinking how to approach the subject conceptually. The paper is animated by a posthumanist commitment, drawing heavily from assemblage thinking and critical data scholarship coming out of Science and Technology Studies. The argument’s understanding of “chains” therefore lies on an alternative conceptual plane relative to most commodity chain scholarship. To speak of a data value chain is to foreground an orchestrating set of relations among humans, non-humans, products, spaces, places, and practices. The paper’s principle contribution involves interrogating lock-in tendencies at different “points” along the digital farm platform assemblage while pushing for a varied understanding of governance depending on the roles of the actors and actants involved.
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Notes
“Yellow No. 2” field corn is a USDA (United State Department of Agriculture) grade designation with a minimum test weight of 54 lb per bushel at 15.5 percent moisture. It has a maximum limit of percent broken kernels and foreign material and cannot exceed 5 percent total damaged kernels (Extension 2009). It is also often used to speak generally of conventional corn seed.
I cannot take credit for this neologism, as I heard it from Michael Bell some twenty years ago.
Abbreviations
- AI:
-
Artificial Intelligence
- GNSS:
-
Global Navigation Satellite Systems
- IoT:
-
Internet of Things
- LiDAR:
-
Light Detection and Ranging
- STS:
-
Science and Technologies Studies
- USDA:
-
United States Department of Agriculture
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Acknowledgements
This research was supported in part by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2016S1A3A2924243), the National Institute of Food and Agriculture (NIFA-COL00725), and the Office for the Vice President for Research, College of Liberal Arts, and Office of Engagement at Colorado State University.
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Carolan, M. Acting like an algorithm: digital farming platforms and the trajectories they (need not) lock-in. Agric Hum Values 37, 1041–1053 (2020). https://doi.org/10.1007/s10460-020-10032-w
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DOI: https://doi.org/10.1007/s10460-020-10032-w