Make bloom and let wither: Biopolitics of precision agriculture at the dawn of surveillance capitalism

Stock, Ryan; Gardezi, Maaz

doi:10.1016/j.geoforum.2021.04.014

Cited by 24 publications

(11 citation statements)

References 59 publications

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“…The infrastructures that make a “smart” or “precision” John Deere tractor make a related point: equipped with sensors that passively gather soil and crop data from fields, such tractors share around-the-clock granular data with other multinational John Deere partners (Clapp and Ruder, 2020), whose subscription data services may then be sold back to farmers, including proprietary decision support systems (DSS) for planting, treating, and harvesting (Bronson and Knezevic, 2019; Stock and Gardezi, 2021). Farmers’ ability to own or control their own data has been shrouded in the “legal murk” of obligatory user agreements (Carbonell, 2016; Carpenter, 2022).…”

Section: Farm Media As Socio-technical Infrastructurementioning

confidence: 99%

“…The high cost of many newer “smart” technologies limits them to large commodity growers: about half of corn and soybean farmers in the United States are estimated to use well established precision agriculture equipment, with fewer adopting the more expensive data-intensive recommendation platforms (Bronson, 2022: 32). Farmers also raise concerns about privacy violations and the competing interests of data brokers whose control over their field data now unduly influences crop insurance companies, chemical manufacturers, investment firms, and other underlying capital infrastructures of food production (Bronson, 2022; Eastwood et al, 2019; Jakku et al, 2019; Miles, 2019; Rasmussen, 2016; Stock and Gardezi, 2021; Wiseman et al, 2019).…”

Section: Farm Media As Socio-technical Infrastructurementioning

confidence: 99%

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Farm media: An introduction

Kish

Peters

2023

New Media & Society

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This essay introduces the first special issue to explore the subject of farm media, which the authors identify as the multiple forms of mediation—representational, infrastructural, and elemental—that reproduce the modern agri-food system. Through this multi-lens framework, media scholars are invited to take the farm seriously as a site of analysis, particularly the recent transformation of agriculture through intensive datafication and its accompanying socio-technical and environmental dimensions. The essay launches these lines of inquiry by reviewing relevant interdisciplinary scholarship, particularly in media studies and critical agrarian studies, and introduces contributor essays exploring the multi-mediation of the farm.

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Section: Farm Media As Socio-technical Infrastructurementioning

confidence: 99%

Section: Farm Media As Socio-technical Infrastructurementioning

confidence: 99%

Farm media: An introduction

Kish

Peters

2023

New Media & Society

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“…The main concerns related to privacy include lack of control over their data, and issues such as what data are collected from farms, how they will be used, and with whom they may be shared (Mark, 2019). Stock et al showed that 78% of farmers are concerned about their data being shared and sold by corporations without their consent or awareness (Stock and Gardezi, 2021). Farm data are highly vulnerable to misuse if they are shared with third parties.…”

Section: Ethical Framework For Assessment Of Artificial Intelligence-...mentioning

confidence: 99%

Recommendations for ethical and responsible use of artificial intelligence in digital agriculture

Dara

Fard

Kaur

2022

Front. Artif. Intell.

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Artificial intelligence (AI) applications are an integral and emerging component of digital agriculture. AI can help ensure sustainable production in agriculture by enhancing agricultural operations and decision-making. Recommendations about soil condition and pesticides or automatic devices for milking and apple picking are examples of AI applications in digital agriculture. Although AI offers many benefits in farming, AI systems may raise ethical issues and risks that should be assessed and proactively managed. Poor design and configuration of intelligent systems may impose harm and unintended consequences on digital agriculture. Invasion of farmers' privacy, damaging animal welfare due to robotic technologies, and lack of accountability for issues resulting from the use of AI tools are only some examples of ethical challenges in digital agriculture. This paper examines the ethical challenges of the use of AI in agriculture in six categories including fairness, transparency, accountability, sustainability, privacy, and robustness. This study further provides recommendations for agriculture technology providers (ATPs) and policymakers on how to proactively mitigate ethical issues that may arise from the use of AI in farming. These recommendations cover a wide range of ethical considerations, such as addressing farmers' privacy concerns, ensuring reliable AI performance, enhancing sustainability in AI systems, and reducing AI bias.

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“…Through this new empiricism critical zonology points the observatory away from the heavens and back down to earth – the observatory and the field combine, and field sites are made permanent through new, interlinked technologies of measurement and surveillance (cf. Stock and Gardezi, 2021). A critical zone, to be known, must be a metrological zone (Barry, 2006).…”

Section: Zoning Sciencementioning

confidence: 99%