The paper outlines critical aspects concerning the increasing use of big data in agriculture and farming. In particular, the aim is to shed light on the emerging dominance of the platform economy in the field of agriculture and food production. To analyze those power structures shaping this dynamic, we start with brief observations on the general relationship between digitization and agriculture and explain the platform economy, its general business model, and the proprietary forms of market power emerging from it. Subsequently, (...) we analyze the implications of the involvement of platform-economic companies in the agricultural sector. To do so, we critically examine several key examples that illuminate the strategies and ultimate objectives of those key tech players involved in this transition––particularly, two of the most dominant cloud providers, Alphabet and Amazon. Finally, we identify the main problems that can potentially emerge, and that can already be observed, from Big Tech’s involvement in agriculture and food production: (1) epistemic asymmetry (2) the erosion of privacy (3) potential harms to smaller farms and farmers, and (4) systemic dependencies on a monopolist data infrastructure. As we argue, these four dimensions are not only essential to take into account, but they also ultimately need to be responded to politically. From a policy perspective, to maintain data justice and epistemic symmetry, and to avoid the risks highlighted, we suggest––next to stressing the need for critical scholarship––to establish a democratically governed data trust, rely on open source technology, and fundamentally commit to the principle of collective data sovereignty. -/- Keywords: big tech, data sovereignty, digital farming, digital agriculture, surveillance capitalism, platform economy. (shrink)

This paper will examine the social and ethical impacts of using artificial intelligence (AI) in the agricultural sector. It will identify what are some of the most prevalent challenges and impacts identified in the literature, how this correlates with those discussed in the domain of AI ethics, and are being implemented into AI ethics guidelines. This will be achieved by examining published articles and conference proceedings that focus on societal or ethical impacts of AI in the agri-food sector, through a (...) thematic analysis of the literature. The thematic analysis will be divided based on the classifications outlined through 11 overarching principles, from an established lexicon (transparency, justice and fairness, non-maleficence, responsibility, privacy, beneficence, freedom and autonomy, trust, dignity, sustainability, and solidarity). While research on AI agriculture is still relatively new, this paper aims to map the debate and illustrate what the literature says in the context of social and ethical impacts. It aim is to analyse these impacts, based on these 11 principles. This research will contrast which impacts are not being discussed in agricultural AI and which issues are not being discussed in AI ethics guidelines, but which are discussed in relation to agricultural AI. The aim of this is to identify gaps within the agricultural literature, and gaps in AI ethics guidelines, that may need to be addressed. (shrink)

This book develops an integrated perspective on the practices and politics of making knowledge work in inclusive development and innovation. While debates about development and innovation commonly appeal to the authority of academic researchers, many current approaches emphasize the plurality of actors with relevant expertise for addressing livelihood challenges. Adopting an action-oriented and reflexive approach, this volume explores the variety of ways in which knowledge works, paying particular attention to dilemmas and controversies. The six parts of the book address the (...) complex interplay of knowledge and politics, starting with the need for knowledge integration in the first part and decolonial perspectives on the politics of knowledge integration in the second part. The following three parts focus on the practices of inclusive development and innovation through three major themes of transformative learning, evidence, and digitization. The final part of the book addresses the governance of knowledge and innovation in the light of political struggles about inclusivity. Exploring conceptual and practical themes through case studies from the Global North and South, this book will be of great interest to students, scholars and practitioners researching and working in development studies, epistemology, innovation studies, science and technology studies and sustainability studies more broadly. (shrink)

Metrics have long served as tools for governing at a distance. In the food industry, major manufacturers have embraced metrics as tools to govern the sustainability of the farms producing their commodity raw materials. This metrical turn has been influenced but also complicated by agricultural datafication, that is, the increasing quantities of data generated on and about farms. Despite the sheer abundance of data that companies might use to measure and drive improvement in on-farm sustainability, they have struggled to collect (...) data suitable for such purposes. Attention to the different kinds of distance and diversity across which metrics are supposed to govern suggests reasons why they may fail to do so, even when wielded by otherwise powerful corporations. (shrink)

Critical Data Studies explore the unique cultural, ethical, and critical challenges posed by Big Data. Rather than treat Big Data as only scientifically empirical and therefore largely neutral phenomena, CDS advocates the view that Big Data should be seen as always-already constituted within wider data assemblages. Assemblages is a concept that helps capture the multitude of ways that already-composed data structures inflect and interact with society, its organization and functioning, and the resulting impact on individuals’ daily lives. CDS questions the (...) many assumptions about Big Data that permeate contemporary literature on information and society by locating instances where Big Data may be naively taken to denote objective and transparent informational entities. In this introduction to the Big Data & Society CDS special theme, we briefly describe CDS work, its orientations, and principles. (shrink)

Agricultural innovation happens at different scales and through different streams. In the absence of a common global research agenda, decisions on which innovations are brought to existence, and through which methods, are taken with insufficient view on how innovation affects social relations, the environment, and future food production. Mostly, innovations are considered from the standpoint of economic efficiency, particularly in relationship to creating jobs for technology-exporting countries. Increasingly, however, the realization that innovations cannot be successful on their technical prowess alone (...) calls for a broader investigation. (shrink)

Smart farming has largely been driven by productivity and efficiency aims, but there is an increasing awareness of potential socio-ethical challenges. The responsible research and innovation approach aims to address such challenges but has had limited application in smart farming contexts. Using smart dairying research and development in New Zealand as a case study, we examine the extent to which principles of RRI have been applied in NZ smart dairying development and assess the broader lessons for RRI application in smart (...) farming. We draw on insights from: a review of research on dairy technology use in NZ; interviews with smart dairying stakeholders; and the application of an analytical framework based on RRI dimensions. We conclude that smart dairying R&D and innovation activities have focused on technology development and on-farm use without considering socio-ethical implications and have excluded certain actors such as citizens and consumers. This indicates that readiness to enact RRI in this context is not yet optimal, and future RRI efforts require leadership by government or dairy sector organisations to fully embed RRI principles in the guidelines for large R&D project design. More broadly, enacting RRI in smart farming requires initial identification of RRI readiness in a given sector or country and devising a roadmap and coherent project portfolio to support capacity building for enacting RRI. Additionally, methods for operationalising RRI must be adapted to the context of the national or sectoral innovation system in which smart farming is being developed. (shrink)

Interdisciplinary research needs innovation. As an action-oriented intervention, this Manifesto begins from the authors’ experiences as social scientists working within interdisciplinary science and technology collaborations in agriculture and food. We draw from these experiences to: 1) explain what social scientists contribute to interdisciplinary agri-food tech collaborations; (2) describe barriers to substantive and meaningful collaboration; and (3) propose ways to overcome these barriers. We encourage funding bodies to develop mechanisms that ensure funded projects respect the integrity of social science expertise and (...) incorporate its insights. We also call for the integration of social scientific questions and methods in interdisciplinary projects from the outset, and for a genuine curiosity on the part of STEM and social science researchers alike about the knowledge and skills each of us has to offer. We contend that cultivating such integration and curiosity within interdisciplinary collaborations will make them more enriching for all researchers involved, and more likely to generate socially beneficial outcomes. (shrink)

An emerging discourse about automated agricultural machinery imagines farms as places where farmers and workers do not need to be, but also implicitly frames farms as intolerable places where people do not want to be. Only autonomous machines, this story goes, can relieve farmers and workers of this presumed burden by letting them ‘farm at a distance’. In return for this distanced autonomy, farmers are promised increased control over their work-life balance and greater farm productivity from letting ‘smart’ robots assume (...) control over the operational environment. Drawing upon the ways that these machines are promoted by manufacturers in various media, we trace the nascent contours of what we term a liberatory sociotechnical imaginary for agricultural automation across three cases—automated milking systems, self-driving tractors, and robotic strawberry pickers. We show how promises for new freedoms and autonomy are flexibly deployed to respond to distinct frictions that farmers, workers, and even farm animals experience in different modes of industrial agriculture. However, underlying these promises is the purposefully understated self-interest of manufacturers, who stand to gain further control over farms if automated technologies assume a central role in agriculture. Through the liberatory rhetoric, we contend, the imaginary seeks to enroll farmers into a socio-technical network that creates new relations of dependence upon the companies who design, sell, maintain, and often retain ownership over automated technologies. While potentially powerful, this imaginary may nonetheless fail to coalesce as farmers, workers, and agroecosystems exert their own agency on automated imaginaries and technological futures for agriculture. (shrink)

Data is essential to governing those emerging matters of concern that confront the agrifood every day. But data is no neutral intermediary. It disrupts, exposes, and creates new social, economic, political, and environmental possibilities, whilst simultaneously hiding, excluding, and foreclosing others. Scholars have become attuned to both the constitutive role of data in creating everyday worlds, and the need to develop critical accounts of the materialities, spatialities and multiplicities of data relationships. Whereas this emerging work develops insight to the capacity (...) for data topologies to reterritorialise the spatial performances of everyday life, it has largely reduced the associated temporal dimensions to matters of fact. The effect of these performances has been to naturalize the temporal quality of speed and elide the multiple temporalities required to enact contemporary data worlds. Applying the lenses of infrastructuring, performativity and ferality, this paper explores temporality and data in the everyday worlds produced through the New Zealand kiwifruit industry’s focus on dry matter. The paper argues that temporalities are deeply embedded in the kiwifruit industry’s data relations. We show that while temporal data relations are critical to the industry, we also highlight ways in which those relations introduce new, potentially destabilizing performances into kiwifruit relations. (shrink)

Smart farming has largely been driven by productivity and efficiency aims, but there is an increasing awareness of potential socio-ethical challenges. The responsible research and innovation approach aims to address such challenges but has had limited application in smart farming contexts. Using smart dairying research and development in New Zealand as a case study, we examine the extent to which principles of RRI have been applied in NZ smart dairying development and assess the broader lessons for RRI application in smart (...) farming. We draw on insights from: a review of research on dairy technology use in NZ; interviews with smart dairying stakeholders; and the application of an analytical framework based on RRI dimensions. We conclude that smart dairying R&D and innovation activities have focused on technology development and on-farm use without considering socio-ethical implications and have excluded certain actors such as citizens and consumers. This indicates that readiness to enact RRI in this context is not yet optimal, and future RRI efforts require leadership by government or dairy sector organisations to fully embed RRI principles in the guidelines for large R&D project design. More broadly, enacting RRI in smart farming requires initial identification of RRI readiness in a given sector or country and devising a roadmap and coherent project portfolio to support capacity building for enacting RRI. Additionally, methods for operationalising RRI must be adapted to the context of the national or sectoral innovation system in which smart farming is being developed. (shrink)

Over recent decades, influential agri-food tech actors, institutions, policymakers and others have fostered dominant techno-optimistic, future visions of food and agriculture that are having profound material impacts in present agri-food worlds. Analyzing such realities has become paramount for scholars working across the fields of science and technology studies (STS) and critical agri-food studies, many of whom contribute to STSFAN—the Science and Technology Studies Food and Agriculture Network. This article introduces a Special Issue featuring the scholarship of STSFAN members, which cover (...) a range of case studies and interdisciplinary and transdisciplinary engagements involving such contested agri-food futures. Their contributions are unique in that they emerged from the network’s specific modus operandi: a workshopping practice that supports the constructive, interdisciplinary dialogue necessary for critical research and rigorous analyses of science and technology in agri-food settings. This introduction offers an overview of STS and critical agri-food studies scholarship, including their historical entanglements in respective studies of food scandals, scientific regimes and technological determinism. We illustrate how interdisciplinary engagement across these fields has contributed to the emergent field of what we term agri-food technoscience scholarship, which the contributions of this Special Issue speak to. After a brief discussion of STS concepts, theories and methods shaping agri-food policy, technology design and manufacturing, we present the eleven Special Issue contributions in three thematic clusters: influential actors and their agri-food imaginaries; obfuscated (material) realities in agri-food technologies; and conflictual and constructive engagements in academia and agri-food. The introduction ends with a short reflection on future research trajectories in agri-food technoscience scholarship. (shrink)

Agricultural-technology (ag-tech) and agroecology both promise a better farming future. Ag-tech seeks to improve the food system through the development of high-tech tools such as sensors, digital platforms, and robotic harvesters, with many ag-tech start-ups promising to deliver increased agricultural productivity while also enhancing food system sustainability. Agroecology incorporates diverse cropping systems, low external resource inputs, indigenous and farmer knowledge, and is increasingly associated with political calls for a more just food system. Recently, demand has grown for the potentially groundbreaking (...) benefits of their convergence, with the University of California, Santa Cruz (UCSC) attempting just such a union. Building on its combined expertise in engineering and agroecology, as well as a longstanding reputation as a socially progressive institution, university administrators believe that UCSC could produce a unique, socially just form of ag-tech designed for small, low-resource farmers—a rare contribution given ag-tech’s tendency to cater primarily to large-scale agribusiness. This paper examines the complexities of uniting agroecology and ag-tech through interviews with agroecologists, engineers, and social scientists involved in UCSC’s ag-tech initiative. Within the setting of a historically radical yet neoliberalizing university, I find that significant epistemic and structural barriers exist for agroecology and ag-tech to come together on an even playing field. This case study contributes to broader discussions of the future of food and farming by focusing on the contours and challenges of a widely called-for agricultural collaboration, highlighting its difficulty but also areas of possibility in a particularly rich, contested context. (shrink)

Silicon Valley and its innovation center counterparts have come upon food and agriculture as the next frontier for their unique style of innovation and impact. But what exactly can the tech sector, with expertise in information and communication technologies, bring to a domain in which the biophysical materiality of soil, plants, animals and human bodies have most challenged farmers and food companies? Based on a detailed analysis of all of the companies that have pitched their products at events sponsored by (...) the Silicon Valley-based convener, Foodbytes!, we show that a large proportion of tech-driven solutions are digital technologies transferred from other domains. These technologies at best inform decision-making on the ecological processes of food and farming, but do not provide tools to treat them, and otherwise provide business solutions not even aimed at major challenges in food and farming. Drawing on a small set of interview data, we additionally suggest that tech entrepreneurs migrate to food and agriculture because it seems purposeful, exciting, or lucrative, but sometimes lack a clear understanding of the problems they might solve with their digital technologies. In making our case about the mismatch of problem and solution, we bring into conversation recent critiques of digital solutionism with abiding concerns in agrarian political economy and critical food studies regarding the role of the biological in both challenging food production and spurring technological intervention. (shrink)

This article examines the construction of image recognition algorithms for the classification of plant pathology problems. Rooted in science and technology studies research on the effects of agricultural big data and agricultural algorithms, the study ethnographically examines how algorithms for the recognition of plant pathology are made. To do this, the article looks at the case of a German agtech startup developing image recognition algorithms for an app that aims to help small-scale farmers diagnose plant damages based on digital images (...) of their symptoms. The study posits that the construction of these algorithms can be grasped as a succession of layers, at each of which the startup’s employees carry out different selection practices. It is argued that these practices gradually inscribe a selective recognition of the phenomenon of plant pathology into the algorithms of the app. This selective recognition is reflected in the fact that the emerging algorithms are effective in identifying isolated plant damages on isolated crops, while ignoring most agroecosystem-related actors and relations through which plant damages arise. The article concludes that the app’s selective recognition of plant pathology is likely to perpetuate or even exacerbate the pesticide use of its users. This is because the app’s view of plant pathology as a phenomenon comprised of isolated plant damages on isolated crops is more compatible with the use of chemical pesticides than with approaches to crop protection that strive for a more moderate use of these substances (e.g., integrated pest management, agroecology, organic agriculture). (shrink)

The current research examines the emergent literature of Critical Data Studies, and particularly aligns with Michael and Lupton’s (2016) manifesto calling for researchers to study the Public Understanding of Big Data. The aim of this paper is to explore Irish stakeholders’ narratives on data sharing in agriculture, and the ways in which their attitudes towards different data sharing governance models reflect their understandings of data, the impact that data hold in their lives and in the farming sector, as well as (...) their preferences for how data should be governed within agriculture. Seven focus groups were held in 2019 with Irish stakeholders from a variety of backgrounds, including agri-researchers, those working in SMEs, and farmers of varying ages and sectors. The primary activities carried out during these focus groups centred upon asking participants to discuss four different data sharing governance models, and to work their way through a set of value cards relating to these models. Focus group results are studied using an inductive, data-driven form of thematic analysis (Braun and Clarke 2006). Five primary themes cross-cut these focus groups: 1) Desire for a data intermediary, 2) Reversing the value chain, 3) Categorisation of data, 4) The common good, and 5) Potential danger in data sharing. These themes are explored in the paper through a detailed discussion of the focus group results, in which the authors track the manifestation of these themes across focus groups, and the ways they sometimes morphed or changed depending upon the participating stakeholder group. (shrink)

Research addressing the challenges emerging from the development and diffusion of digital technologies has grown rapidly in recent years. However, much of this literature tends to overlook the immersion of these technologies into our everyday lives. This everyday digitalization cannot be reduced to specific technological innovations and is obviously a crucial aspect of the social changes introduced by digital technologies. This themed issue sets out to explore the everyday dimension of digitalization, in the specific context of agri-food systems. We propose (...) a collection of papers that contribute to opening new approaches to digitalization in food and agriculture, by concentrating the attention on the mundane and ordinary aspects of digitalization and exploring their potential contributions to profound transformations in agri-food systems. The various forms of everyday digitalization that are presented in this symposium offer two particular ways of critically engaging with the digitalization of agriculture and food. Firstly, our everyday digitalization looks beyond examining the impacts of digitalization and positioning digital technologies in opposition to farmers, consumers, government, or other actors. Secondly, we shed light on the politics of uncertainty, which enables us to make anticipatory actions and see things beyond success and failure. What we observe is how these imaginaries participate in the co-production of digital realities through their encounter with the complexity of everyday life. Therefore, it remains essential to engage critically with both the imaginary and the everyday dimensions of digitalization in their multiplicity. (shrink)

These last years, the development of AI robots for agriculture, livestock farming and food processing industries is rapidly increasing. These robots are expected to help produce and deliver food more efficiently for a growing human population, but they also raise societal and ethical questions. As the type of questions raised by these AI robots in society have been rarely empirically explored, we engaged in four case studies focussing on four types of AI robots for agri-food ‘in the making’: manure collectors, (...) weeding robots, harvesting robots and food processing robots which select and package fruits, vegetables and meats. Based on qualitative interviews with 33 experts engaged in the development or implementation of these four types of robots, this article provides a broad and varied exploration of the values that play a role in their evaluation and the ethical questions that they raise. Compared to the recently published literature reviews mapping the ethical questions related to AI robots in agri-food, we conclude that stakeholders in our case studies primarily adopt a relational perspective to the value of AI robots and to finding a solution to the ethical questions. Building on our findings we suggest it is best to seek a distribution of tasks between human beings and robots in agri-food, which helps to realize the most acceptable, good or just collaboration between them in food production or processing that contributes to realizing societal goals and help to respond to the 21 century challenges. (shrink)

Recent technological and methodological changes in farming have led to an emerging set of claims about the role of digital technology in food production. Known as precision agriculture, the integration of digital management and surveillance technologies in farming is normatively presented as a revolutionary transformation. Proponents contend that machine learning, Big Data, and automation will create more accurate, efficient, transparent, and environmentally friendly food production, staving off both food insecurity and ecological ruin. This article contributes a critique of these rhetorical (...) and discursive claims to a growing body of critical literature on precision agriculture. It argues precision agriculture is less a revolution than an evolution, an effort to shore up and intensify the conventional farming system responsible for generating many of the social and environmental problems precision agriculture is presented as solving. While precision agriculture advocates portray it as a radical, even democratic epistemological break with the past, this paper locates truth claims surrounding datafication and algorithmic control in farming within deeper historical contexts of the capitalist rationalization of production and efforts to quantify and automate physical and mental labor. Abjuring the growing cultural tendency to treat algorithmic systems as revolutionary in favor of social and historical dimensions of precision agriculture, can help re-frame the discussion about its design and use around real, socially and ecologically oriented change in farming, and so ensure that the possibilities and benefits of precision agriculture are as evenly and effectively shared as possible. (shrink)

This article asks how the application of digital technologies is changing the organization of the agri-food system in the context of the third food regime. The academic debate on digitalization and food largely focuses on the input and farm level. Yet, based on the analysis of 280 digital services and products, we show that digital technologies are now being used along the entire food commodity chain. We argue that digital technologies in the third food regime serve on the one hand (...) as a continuation of established information and communication technologies, thus deepening certain features of the existing food regime such as the retail sector’s control over global commodity chains. On the other hand, digital technologies also introduce new forms of control and value extraction based on the use of data and pave the way for large tech companies to take over market shares in the agri-food sector. Finally, we find that multinational agri-food companies are starting to take on the business models of leading digital tech companies, for instance by developing digital platforms throughout the agri-food system. We argue that this shows that the broader economic restructuring of neoliberal capitalism towards digital capitalism is also making its way into the agri-food system. (shrink)

Digital farming technologies promise to help farmers make well-informed decisions that improve the quality and quantity of their production, with less labour and less impact on the environment. This future, however, can only become a reality if farmers are willing to share their data with agribusinesses that develop digital technologies. To foster trust in data sharing, in Europe the EU Code of Conduct for agricultural data sharing by contractual agreement was launched in 2018 which encourages transparency about data use. This (...) article looks at the EU Code through the lens of literature on trust and contract agreements. We agree with the makers of the EU Code that a contract can make an important contribution to trust relationships as it is needed to mitigate the detrimental effects of power relationships between experts and non-experts. Building on Onora O’Neills perspective to trust, however, we argued that a contract can only be successful in fostering trust when information is comprehended by the more vulnerable party in this relationship who has to sign the contract, the more powerful partner takes responsibility to provide that information, and information is tailored to the information needs of the party signing the contract, even when data are re-used over a longer period. In addition, we think that differences between trust relationships and relationships of accountability, give reason to add to informed consent other more substantive ethical components in a more encompassing code of conduct. (shrink)

Despite increasing attention to the sensors, drones, robots, and apps permeating agri-food systems, little attention has been paid to social media, perhaps the most ubiquitous digital technology in rural areas globally. This article draws on analysis of farming groups on Myanmar Facebook to posit social media as appropriated agritech: a generic technology incorporated into existing circuits of economic and social exchange that becomes a site of agrarian innovation. Through analysis of an original archive of popular posts collected from Myanmar-language Facebook (...) pages and groups related to agriculture, I explore the ways that farmers, traders, agronomists and agricultural companies use social media to further agrarian commerce and knowledge. These activities evidence that farmers use Facebook not only to exchange market or planting information, but also to interact in ways structured by existing social, political and economic relations. More broadly, my analysis builds on insights from STS and postcolonial computing to disrupt assumptions about the totalizing power of digital technologies and affirm the relevance of social media to agriculture, while inviting new research into the surprising, ambiguous relationships between small farmers and big tech. (shrink)

We describe how the set of tools, practices, and social relations known as “precision agriculture” is defined, promoted, and debated. To do so, we perform a critical discourse analysis of popular and trade press websites. Promoters of precision agriculture champion how big data analytics, automated equipment, and decision-support software will optimize yields in the face of narrow margins and public concern about farming’s environmental impacts. At its core, however, the idea of farmers leveraging digital infrastructure in their operations is not (...) new, as agronomic research in this vein has existed for over 30 years. Contemporary discourse in precision ag tends to favour emerging digital technologies themselves over their embeddedness in longstanding precision management approaches. Following several strands of science and technology studies research, we explore what rhetorical emphasis on technical innovation achieves, and argue that this discourse of novelty is a reinvention of precision agriculture in the context of the growing “smart” agricultural economy. We overview six tensions that remain unresolved in this promotional rhetoric, concerning the definitions, history, goals, adoption, uses, and impacts of precision agriculture. We then synthesize these in a discussion of the extent to which digital tools are believed to displace farmer decision-making and whether digital agriculture addresses the biophysical heterogeneity of farm landscapes or land itself has become an “experimental technology”—a way to advance the general development of artificial intelligence. This discussion ultimately helps us name a larger dilemma: that the smart agricultural economy is perhaps less about supporting land and its stewards than promising future tech and profits. (shrink)