Acting like an algorithm: digital farming platforms and the trajectories they (need not) lock-in
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Acting like an algorithm: digital farming platforms and the trajectories they (need not) lock‑in Michael Carolan1 Accepted: 4 April 2020 © Springer Nature B.V. 2020
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. Keywords Digital agriculture · Precision agriculture · Big data · Dependency · Algorithms · Knowledge · Data cleaning 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
Introduction Smart farming—also known as digital agriculture, e-agriculture, precision agriculture, agriculture 4.0, etc.—is an umbrella term referencing data- and software-intensive platforms widely said to be transforming agriculture (DeClercq et al. 2018; Walter et al. 2017). Farm managers, ranchers, and producers, in conjunction with industry and government * Michael Carolan [email protected] 1
Department of Sociology, Colorado State University, B241 Clark, Fort Collins, CO 80523, USA
actors, are leveraging the capabilities of the Internet of Things (IoT), from sensors to GNSS (Global Navigation Satellite Systems), cloud computing, weather and climate modeling, high-speed internet, historical yield data, and LiDAR (Light Detection and Ranging) systems to usher in what has been described as a digital revolution in agriculture (e.g., Claver 2018; DeBoar 2015). This disruption has been met with a mix of optimism and anxi
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