Digital technologies are being developed and adopted across the agro-food system, from farm to fork. Within decision-making spaces, however, little attention is being paid to political factors arising from such technological developments. This review draws from critical social sciences to examine emerging technologies and big data systems in agriculture and assesses some key issues arising in the field. We begin with an introduction and review of the so-called 'digital revolution' and then briefly outline how political economy is effective for understanding major challenges for governing technologies and data systems in agriculture. These challenges include: (1) data ownership and control, (2) the production of technologies and data development, and (3) data security. We then use literature and examples to consider the extent to which the political and economic landscape can be shifted to support greater equity in agriculture, while reflecting on structural challenges and limits. In doing so, we emphasise that while there are significant systemic tensions between digital ag-tech development and agroecological approaches, we do not see them as mutually exclusive per se. This article intends to provide decision-makers, practitioners and scholars from a wide range of disciplines with a timely assessment of agro-food digitalisation that attends to political economic factors. In doing so, this article contributes to policy and decision-making discussions, which, from our perspective, continue to be rather technocentric in nature while paying little attention to how digital technologies can support agroecological systems specifically.
Agriculture stands on the cusp of a digital revolution, and the same technologies that created the Internet and are transforming medicine are now being applied in our farms and on our fields. Overall, this digital agricultural revolution is being driven by the low cost of collecting data on everything from soil conditions to animal health and crop development along with weather station data and data collected by drones and satellites. The promise of these technologies is more food, produced on less land, with fewer inputs and a smaller environmental footprint. At present, however, barriers to realizing this potential include a lack of ability to aggregate and interpret data in such a way that it results in useful decision support tools for farmers and the need to train farmers in how to use new tools. This article reviews the state of the literature on the promise and barriers to realizing the potential for Big Data to revolutionize agriculture.
A systematic global stocktake of evidence on human adaptation to climate changeAssessing global progress on human adaptation to climate change is an urgent priority. Although the literature on adaptation to climate change is rapidly expanding, little is known about the actual extent of implementation. We systematically screened >48,000 articles using machine learning methods and a global network of 126 researchers. Our synthesis of the resulting 1,682 articles presents a systematic and comprehensive global stocktake of implemented human adaptation to climate change. Documented adaptations were largely fragmented, local and incremental, with limited evidence of transformational adaptation and negligible evidence of risk reduction outcomes. We identify eight priorities for global adaptation research: assess the effectiveness of adaptation responses, enhance the understanding of limits to adaptation, enable individuals and civil society to adapt, include missing places, scholars and scholarship, understand private sector responses, improve methods for synthesizing different forms of evidence, assess the adaptation at different temperature thresholds, and improve the inclusion of timescale and the dynamics of responses.
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 (STS) 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.
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