Wires in the branches: The ongoing datafication of the natural world
I work at an organisation where data is our number one topic (it’s literally in our name). We talk about how data can help to address societal problems if used responsibly, or can exacerbate them if we don’t. Rarely, do we stop to consider whether data itself is a good thing, nor what it means to society for people, buildings, cities, trees, animals, weather, electricity to become data points. This piece is a reflection on my personal discomfort regarding the way in which the language of ‘smart’ is spreading from ‘smart cities’ to natural and rural areas.
Data is not just a collection of numbers and symbols, but also a physical and social phenomenon. Data is produced in particular places, and it moves through particular spaces. These places and spaces have a significant impact on the way that data is collected, stored, and used. Think about how often life in cities is mediated through the access and exchange of data; it underpins travel throughout the city, the booking of restaurants, the supply of energy. Smart buildings and smart cities have been pushed by technology companies to local governments and private companies working in the built environment in a bid to sell sensors and equipment. This denotes a concept called ‘datafication’ or the process of converting events and objects into data points. It has become a ‘dominant paradigm’ (Van Dijck, 2014) such that it is assumed that there will be a continued and linear growth in regards to data collection and use.
What’s the significance when organisations are pushing not only for smart cities, but for smart villages, smart forests and smart oceans? What will the consequence be of the uncritical spreading of the theories of urban tech-laden planning to rural areas? Many of these initiatives can be imaginative and critical to the protection of a land, a species, or an industry, but I find it hard not to think about those with a less-than-positive impact.
Even the conceptualisation of rural areas from ‘smart’ projects assume that technology can be transposed from urban areas as ‘rural is just a low-density city’ (Walker et al., 2020)
The complexity of the natural world
How can data ever capture the complexity of a natural world that we are not even close to understanding? Can data predict changing migratory patterns of birds? Or that sea creatures pollinate marine plants and algae? Or that trees protect each other from external threats? Maybe. But in relying on data in conservation and natural stewardship are we missing something? Is there a risk that we prioritise new forms of knowledge production over those that have existed for centuries? Are we ignoring the lived experiences of those working in natural areas or the specific skillsets of researchers, biologists and conservationsists? What context is being missed that a human would spot?
Datafication proponents often assume a self-evident relationship between data and people, subsequently interpreting aggregated data to predict individual behaviour (Van Dijck, 2014). It is an ideology, a ‘widespread belief in the objective quantification and potential tracking of all kinds of human behavior and sociality through online media technologies’ (Van Dijck, 2014). I would argue that under this logic, rural areas are not viewed as having problems that data is equipped to address, but instead as an arena for further capitalism encroachment for extractive ends. Complex technologies, such as AI, are utilised for this logic, being designed to extend and solidify the ability of capital to assetise, extract and enclose (Sadowski 2020). Hence, natural areas become new arenas that, once things have been counted and analysed become easier to be utilised for profit-making purposes — a field with precise yield numbers becomes a more stable investment for an outsider.
In 2021, Tahani Nadim considered the logics and narratives behind natural history collections, and the implications for the digital conversion of specimens and taxonomies that became standard place during a time of colonialism. Nadim wrote how the scale and advancement of technology used for this purpose — from paper and resin to databases and 3D scans, ‘compels a reckoning with the tenacity of natural history’s modes of ordering, especially its naming practices’ (Nadim, 2021). Going deeper, Feinberg shows how humans have a ‘propensity to lose track of the diverse set of interpretive judgments packed into every instance of data collection, and accordingly to diminish the socially situated conditions in which data is created’ (Feinberg, 2023). Quantification, thus, becomes a principle way of ordering the world and much nuance is lost. Furthermore, the ordered systems become places of the counted and uncounted — when this logic is applied in the human world, imbalances in power become apparent — ‘it should be no surprise that the people who can’t be counted are the people who don’t count’ (Bowker and Star, 2001). The same dilemma is facing the natural and non-human world — if a tree is not counted does it exist?
Does datafication deepen the ingrain of a land ownership system steeped in historical and present inequalities? Digital mapping of land boundaries for example, can instrumentalise a previously more informal process and help to solidify boundaries that may otherwise remain fluid (see Thiel, 2023). As Webster et al considered, ‘On the level of naming, it is the owners and rulers of land, not the land or its characteristics that is represented in digital maps. Indigenous names are not’ (Webster, Svalastog and Allgaier, 2020). The issue is, once complex, unsettled phenomena such as land boundaries or borders are abstracted into the digital realm they take on a form of objective permanence, and allow digital technologies to become tools of oppression — as the erasure of Palestine on Google Maps demonstrates (Kearns, 2019). Centuries-old contested dynamics are being formalised overnight, with no reference to the actual physical place where the disputes take place. A map, a geography, a land is changed by a digital decision.
A number of studies have been found by (Sarkar and Chapman, 2021) which demonstrate how technologies cause stress in animals; for example, drones have been found to cause physiological stress in birds (Vas et al., 2015). Technologies are hence affecting local ecosystems as well as converting these ecosystems into sensors to benefit humans. Rob Kitchin’s concept of ‘code/space’, is useful here. Kitchin argues that code is increasingly becoming a defining characteristic of space (Kitchin and Dodge, 2011). In other words, the way that we design and use space is increasingly being shaped by code. Let’s take this idea back to the forest — the smart forest — where digital technologies are being used to manage, monitor, enhance, and expand these spaces. As digital devices and data practices proliferate in forest spaces, so too do forests transform into environmental infrastructures and technologies for responding to and mitigating environmental change.
Ideas travelling from urban to rural areas
Even our way of thinking of the rural, in our urban settings, is skewed. Those who live and work in rural settings are automatically assumed to be lacking in access to technology or digital skills — and would benefit immensely from these offerings. The conceptualisation of rural areas within ‘smart’ projects assumes that technology can be transposed from urban areas as ‘rural is just a low-density city’ (Walker et al., 2020). As Walker et al (2020) investigated, data is not a tool that fits naturally into how rural workers traditionally understand their environment, or as one respondent in their study remarked: “There are few fishermen sitting in a boat thinking of a way to use open data”.
Optimisation is always a word to be wary of, an approach to bring the language of economics into complex natural ecosystems.
While the geographic digital divide is a real issue (see Philip et al., 2017), the dynamic is more complex than that. There is often an assumption that rural and natural areas need to utilise the logics and technologies of the urban and not the other way round. The calls for initiatives like ‘big data for agriculture’ come from large organisations centred in major urban centres, and not from the communities themselves. For example, in a survey of Iowa farmers, 30% felt that collection of remotely sensed imagery for monitoring was an invasion of privacy (Arbuckle, 2013). If data and technology is going to be utilised by rural workers, it needs to be the rural workers who desire and benefit from it right?
One 2020 article claimed that the need for data on soil and land use is ‘crucial in order to optimize sustainable management of agricultural, meadow and forest lands’ (Iban and Aksu, 2020). Personally, optimisation is always a word to be wary of, an approach to bring the language of economics into complex natural ecosystems. It is a further logic that sees natural and rural spaces not as places of wonder, or of the primacy of the more-than-human but instead as an ‘investment opportunit[y] to coax the remaining biodiversity to be more productive’ (Tembon, 2019; Sarkar and Chapman, 2021). Thus, as Sarkar and Chapman (2021) proposed, a more critical analysis is required that centres the smart forest within discourse of the ‘neo-liberal stresses of optimization and privatization’ one which decentres human context from an understanding of natural processes.
Further, the use of sensors in rural spaces cannot be separated from the desire to sell these technologies. As with smart cities, private tech companies are adept at spotting opportunities to sell their wares — and what does it give us? What do we get from all this data? Well, when the technological approach was compared to a human-led approach for monitoring vulnerable species, in a 2021 study by Sarkar and Chapman, it was found that the technological approach would be ‘six times more expensive than the labour-intensive tracking station method’ and the assumptions that ‘smart sensors will be more accurate, cost-efficient, and objective are debatable (Sarkar and Chapman, 2021).
Conclusion: when data is not enough
Data always has the potential to help or hinder society. Within this space, rural campaigns are built off the back of data and sensors. Surfers Against Sewage have been monitoring leisure water and the results are, as predicted, not good. The press, public and policymakers are aware of the rampant pollution of our waterways and data is the backbone of these campaigns, and yet the underlying issue is still unresolved. Data cannot be relied upon to solve problems and can only bridge the gap between inaction and action only if the problem is one of a lack of knowledge. Unfortunately, it is apparent that the main causes of inaction over the climate and protection of land and people is not a lack of information, but rather a lack of willpower and morality.
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