Current debates in science and technology studies emphasize that the bio-economy—or, the articulation of capitalism and biotechnology—is built on notions of commodity production, commodification, and materiality, emphasizing that it is possible to derive value from body parts, molecular and cellular tissues, biological processes, and so on. What is missing from these perspectives, however, is consideration of the political-economic actors, knowledges, and practices involved in the creation and management of value. As part of a rethinking of value in the bio-economy, this (...) article analyzes three key political-economic processes: financialization, capitalization, and assetization. In doing so, it argues that value is managed as part of a series of valuation practices, it is not inherent in biological materialities. (shrink)

Farming is undergoing a digital revolution. Our existing review of current Big Data applications in the agri-food sector has revealed several collection and analytics tools that may have implications for relationships of power between players in the food system. For example, Who retains ownership of the data generated by applications like Monsanto Corproation's Weed I.D. “app”? Are there privacy implications with the data gathered by John Deere's precision agricultural equipment? Systematically tracing the digital revolution in agriculture, and charting the affordances (...) as well as the limitations of Big Data applied to food and agriculture, should be a broad research goal for Big Data scholarship. Such a goal brings data scholarship into conversation with food studies and it allows for a focus on the material consequences of big data in society. (shrink)

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. (shrink)

Gene editing techniques, such as CRISPR, are being heralded as powerful new tools for delivering agricultural products and foods with a variety of beneficial traits quickly, easily, and cheaply. Proponents are concerned, however, about whether the public will accept the new technology and that excessive regulatory oversight could limit the technology’s potential. In this paper, we draw on the sociotechnical imaginaries literature to examine how proponents are imagining the potential benefits and risks of gene editing technologies within agriculture. We derive (...) our data from a content analysis of public comments submitted to the Food and Drug Administration’s 2017 docket titled “Genome Editing in New Plant Varieties Used for Food.” Our sample frame consists of 26 comments representing 30 agriculture and biotech companies, organizations, and trade associations. Our findings reveal three key sociotechnical imaginaries, including that gene editing technologies in agriculture: are not GMO but instead equivalent to traditional plant breeding; have the potential to usher in a new Green Revolution; and could facilitate the democratization of agricultural biotechnologies. We argue that forming and projecting these collective interpretations of the potential of gene editing technologies for crops and foods plays an important role in efforts by proponents to influence regulatory oversight, modes of governance, and build public acceptance. This research contributes to calls by science and technology studies scholars to investigate emergent concerns and imaginaries for novel technoscientific advances to help inform upstream models of public engagement and governance decisions. (shrink)

Adoption of technology in agriculture can significantly reorganize production and relationships amongst humans, animals, technology, and the natural environment. However, the adoption of agricultural technology is not homogenous, and diversity in integration leads to a diversity of outcomes and impacts. In this study, we examine the adoption of automated milking systems in small and midsize dairy farms in the US Midwest, the Netherlands, and Denmark. In contrast to technological determinism, we find significant variation amongst adopters in the implementation of AMS (...) and corresponding variation in outcomes. Adopters have significant discretion in determining the use of AMS, which leads to a diversity of possible outcomes for family and non-family labor, human–cow relationships, animal welfare, the environment, and financial resiliency. Adoption and implementation are shaped by both structural factors, such as debt load and labor market variation, and by farmers’ individual personality traits and values, such as a willingness to release control to technology. Rather than uniform adoption and impacts of technology, we highlight the importance of context, the co-constitution of technology and users, and the diversity of technology adoption and its associated impacts. (shrink)

Within the framework of a general reflection on technical change, this paper is aimed at opposing an approach that assigns a primary role to the progress of biological knowledge in the evolution of the agro-food system. Instead, the importance of the complex and heterogeneous nature of the transformation under way is highlighted. Biotechnological research risks falling into a reductionist rut when it ignores the structural and organizational changes in the agro-food industry and the contribution of other technical innovations, especially in (...) the field of computers and in product innovation. If one really wants to speak of a biotechnology revolution, one must specify that it is essentially a scientific revolution: at the production level the contribution of the biotechnologies is still potential, while the agro-food sector is going through a period of profound change. (shrink)

The increasing availability of digital data reflecting economic and human development, and in particular the availability of data emitted as a by-product of people’s use of technological devices and services, has both political and practical implications for the way people are seen and treated by the state and by the private sector. Yet the data revolution is so far primarily a technical one: the power of data to sort, categorise and intervene has not yet been explicitly connected to a social (...) justice agenda by the agencies and authorities involved. Meanwhile, although data-driven discrimination is advancing at a similar pace to data processing technologies, awareness and mechanisms for combating it are not. This paper posits that just as an idea of justice is needed in order to establish the rule of law, an idea of data justice – fairness in the way people are made visible, represented and treated as a result of their production of digital data – is necessary to determine ethical paths through a datafying world. Bringing together the emerging scholarly perspectives on this topic, I propose three pillars as the basis of a notion of international data justice: visibility, engagement with technology and antidiscrimination. These pillars integrate positive with negative rights and freedoms, and by doing so challenge both the basis of current data protection regulations and the growing assumption that being visible through the data we emit is part of the contemporary social contract. (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)

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)

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 draws on the concept of “performance” to argue for greater recognition of preexisting practices in the configuration of users. Through an Australian case study of a computer-based dairy decision-support system introduced via a two-day workshop to participating farmers, the article examines the assembling of imputed farmer users in the design of the software. It then explores how the designer and trainers attempt, through the decision-support system, to mobilize their network and align the imputed user with farmers' preexisting performances. (...) The case study highlights that attempts to make workable on-farm the “new” performances of users inscribed in the software are highly contingent on farmers' preexisting knowledge practices. These “old” performances problematize the designer's and trainers' version of imputed users and contribute to partial translation of the decision-support system. A focus on performance is argued to provide a useful starting point in mapping the effects of preexisting knowledge practices on attempts to enroll users in technosocial programs. (shrink)