A variety of labels have been used for this emergent industry: precision agriculture, e-agriculture, smart agriculture, and digital agriculture, among others. Despite early critical use of precision agriculture, the term tends to be used in the industry to signify a specific suite of production-oriented technologies.However, information technologies are also used to open new markets and new territories for production. For example, digital platforms have become increasingly important for individual producers to bring their goods to market. Figure 1 shows how information technologies are intertwined throughout the cycle of agricultural production and sale.We use digital agriculture for its semantic breadth and increasing currency. In our taxonomy, precision agriculture is a subset of digital tools which improve efficiency through careful management of inputs. Three other types of tools—marketplace and financial platforms, e-extension, and smallholder management—are typically platform-based systems that mediate the social relation between farmers and the outside world. Marketplace and financial technologies help farmers access new credit lines and optimize their market behavior. E-extension is the digitalization of the practice of implementing technological innovations through farmer education, particularly in the international development context. E-extension, like the analog version that preceded it, dutch buckets system is largely reliant on insights produced far from the farm.
Finally, smallholder management platforms allow larger agribusinesses to exert control over smallholder farmers through close management of their inputs, products, and so forth. This may allow major actors to divest themselves of the risk inherent in owning land and instead subcontract smallholders in a relationship analogous to other platforms in the gig economy.For digital agriculture’s boosters, it has the potential to be the much-needed “fourth agricultural revolution” . In particular, it is framed as a climate-friendly way to feed the world and improve the lot of farmers around the world. By making the application of inputs more efficient, digital agriculture can indeed lessen the environmental impact and yield of agriculture. By increasing input efficiency and improving knowledge of market demand, digital agriculture may indeed improve the fortunes of producers. The rhetoric is not dishonest, but it is incomplete.Optimizing inputs enables the continued use of ecologically-harmful chemicals and practices, which would otherwise be abandoned if their effects were not actively mitigated . Digital agriculture’s marketing claims it will improve efficiency, increasing yield and minimizing the use of inputs—many of which are harmful and unsustainable. The externalities produced by using these inputs are the “un- and undervalued costs of industrial capitalist agriculture” .
A team at Cornell, for example, has developed a model that recommends ideal fertilizer application rates for each section of a farmer’s field in order to minimize nitrogen run of into the Gulf of Mexico, which causes algal blooms, depletes oxygen levels in the water, and kills fish and wildlife.While optimization limits the short-term damage of unsustainable practices, it also makes those practices more politically permissible and financially feasible. Thus, by making unsustainable practices appear sustainable, the necessity of adopting more ecologically and socially sustainable and just practices is delayed. By focusing on input management, these technologies advance a limited interpretation of sustainability that still depends on of-farm inputs, rather than a more radical shift to permanently sustainable practices . Just as digital agriculture promises to minimize inputs, it also promises to maximize yield—yet yield is not the problem. In the 1970s Amartya Sen noted that while starvation was increasing globally, food per capital was also increasing —as population grew, food production grew at a greater rate, not only globally but even regionally. While some scholars have taken issue with Sen’s empirical basis, an updated analysis using 2010 statistics found the same results . The direct relationship between hunger and food per capital, when we would expect an inverted one, betrays the simple thesis that hunger is due to a lack of food availability. Instead, Sen attributes hunger to an inability to exchange for food. Davis similarly notes the disconnect between food availability and hunger, finding that famine can occur in areas of grain surplus because it is more attributable to rural food management and exploitation than to production .
The “solution” to hunger, then, lies not in yield. Yield has increased; food per capital has increased; hunger persists. Therefore, stretching yield through digital agriculture is insufficient and does not address the political-economic basis of systemic hunger.The third key claim made by digital agriculture’s boosters is that it will improve farmers’ welfare, in particular their profits. Profits may be found in better decision-making, better yields, and better access to market information . In the Global North, such increased profits may be plausible. However, a primary mode for digital agriculture, the platform service, means that the data produced typically becomes the property of the platform provider. Weersink et al. note that a key challenge for digital agriculture is making this data useful; this, in turn, may favor larger companies with the capacity to process the data. Bronson notes this dynamic and warns that it may reproduce the distributional effects of the Green Revolution—that is, to concentrate wealth and power in the hands of major agribusinesses. In the Global South, digital agriculture presents a different set of problems for farmers’ welfare. Technological innovation that increases a crop’s yield in turn increases supply and undercuts the socially necessary labor time required to produce it. This dynamic lowers the crop’s exchange value at the expense of those at the bottom of global commodity chains, in particular the growers’ compensation per unit of crop. As this price drop is not accompanied by any increase in production for farmers without access to this technological innovation, this drop translates to lower overall compensation and to “exchange entitlement decline” . If they depend on exchange for subsistence, the decreased compensation translates to hunger as well.In reflecting on these mainstream claims, a different theme emerges. Rather than sustainability, nourishment, or farmer welfare, digital agriculture is fundamentally about securing the conditions to generate profit in the food system. Crucially, however, this is not about profit in food production alone, but in the wider capitalist economy for which food is obviously a fundamental input. Therefore, we submit that digital agriculture must be understood as addressing a specific set of crisis tendencies that have emerged at a particular juncture in the social, ecological, and spatial history of capitalism. This juncture is defined by interlocking moments of ecological disaster; enormous advances in information production, gathering, and processing; and “hypertrophic” urbanization . In this section we argue that rather than a solution to the climate crisis, hunger, or farmer welfare, the rise of digital agriculture can better be understood as an attempt to overcome crisis tendencies of “the relentless growth imperatives of an accelerating, increasingly planetary formation of capitalist urbanization” .
After briefly excavating the informational dynamics latent within the framework of extended and concentrated urbanization, we describe how digital agriculture functions as a “data fix” by allowing the intensification of agricultural industrialization and the extraction and enclosure, for eventual profit, of the data produced by digital agriculture technologies. An early theme in globalization literature was a tendency to embrace the rise of information technologies in a way that dematerialized the now planetary systems of extraction, production, and consumption . Such concepts, however, have largely been absorbed by analyses which show that a deterritorialized “information society” is not displacing traditional modes of production and social relations as much as emerging as a financial-managerial stratum in a “new international division of labor.” Another major theme in globalization studies is the ‘global city network,’ a set of nodes in the global space of flows from which the global economy could be commanded and controlled . In describing such cities as “strategic sites where global processes materialize” , they appear to be material sites floating in a sea of immaterial processes. In this model, cities are simultaneously the result of, yet alienated from, specific material processes— such as agricultural production—taking place beyond their bounds. In both concepts the informational nature of globalization is over-emphasized at the expense of its material effects. In an era of climate crisis, this shortcoming is glaring.One response has been to radically reframe globalization as a material process of urbanization,dutch buckets which unfolds as the product of dialectically-entwined moments of extension and concentration . Concentrated urbanization signifies the moment of agglomeration where the material flows of global capitalism accumulate into cities, megalopolises, and mega-regions. On the flip side, extended urbanization is the moment where remote territories are enclosed and transformed into operational landscapes that funnel energy, materials, and food into areas of accumulation. Both moments cause and are caused by the other: “The urban unfolds into the countryside just as the countryside folds back into the city” . Global capitalist urbanization is a metabolic process of moving and consuming the material world . This involves both fragmentation and homogenization —for example, the simultaneous expansion of monoculture agriculture and of liberal private property regimes. At the same time, enclosure and technological advances deprive peasants of their livelihoods; ‘depeasantization’ is the mirror of urbanization. However, the desire to develop a more materialist model of globalization leads to the black-boxing of information‘s role in facilitating vast networks of production and exchange. To bring information back in requires recognizing that something happens at the moment of concentration which sets the stage for extension. In the present framework, production and the growth imperative drive a search for more raw materials. But extension also depends on informational infrastructure to make a massively decentralized network of global supply chains profitable. Indeed, another way to describe capitalist geography is as “a skein of somewhat longer networks that rather inadequately embrace the world on the basis of points that become centers of calculation” . Information, along with material, is being drawn inwards in the moment of concentration; the processing of raw information—which is “what remains after one abstracts from the material aspects of physical reality” —into actionable knowledge informs extension processes. “Information processing” is computation, and computation at the scale required to make legible the vast amounts of data produced in the contemporary economy involves enormous physical infrastructural investment in data centers, undersea cables, and satellite networks . Such computational capital consists also of intellectual and human capital in the form of models, algorithms, and the expertise to deploy them.
There is a potential for the over accumulation of computational capital, however; as a result, there is a constant drive for firms to find productive outlets. This is what leads firms like Amazon, Microsoft, Google, Oracle, and Cisco—as well as funds invested in and consultancies hired by them—into digital agriculture. By locating, extracting, and enclosing data relevant to another materially productive sector , a firm like Amazon—whose cloud computing infrastructure Jef Bezos has compared to power utilities—can continue to grow. This applies at the worker level, too. Just as a glut of NASA-trained engineers and physicists became quants for hedge funds after the Space Race , a glut of software engineers and data scientists which Silicon Valley cannot absorb find employment outside of the tech sector, including at digital agriculture startups or divisions within larger agribusinesses. Indeed, agribusiness are planning for a future in which they become tech companies themselves: the head of digital agriculture at Bayer Monsanto, for example, has described the future of the conglomerate as a digital platform . The fundamental material crisis that digital agriculture attempts to fix through the manipulation of data is in the sociol-metabolic processes of capitalism and capitalist urbanization. To support social reproduction for a growing non-agrarian population, present-day industrial agriculture destroys its own ecological foundations. As the consequences of climate change become ever more apparent and render growing conditions ever more difficult, a new ecological regime is needed to prolong the production of cheap food and ensure future accumulation in the face of known crises . But not only is fossil fuel-based industrial agricultural production partially responsible for climate change—up to one-fifth of all greenhouse gas emissions—it also exhausts the ecologies within which it is practiced. The search for the fourth agricultural revolution is not a straightforward matter of addressing a Malthusian crisis of natural population growth, but a crisis of capitalism itself. This crisis tendency arises from capitalism’s dependency on the “four cheaps”— labor, food, energy, raw materials—to maintain each cycle of accumulation.