The Anthropocene is the age marked by the substantial consequences that human activities have caused to the Earth system (the different natural processes and their interactions) [1]. As humans, we are part of the natural world; our digital artifacts are not. With that said, what are some challenges of doing Digital Humanities (DH) in the Anthropocene?

An epistemological challenge is to revise how we think about DH projects. As humanists, we need to include the material part in the project design and consider its environmental impact: the digital infrastructure required to make it possible, including all the different layers of software and hardware you need for your project; those you can see and those you do not see.

An ontological challenge that arises from this is to resituate ourselves: to think about ourselves together with other species within the natural world, rather than as superior or external to nature. This line of thinking also includes seeing the value of all human lives as equal, rather than through the lens of the imaginary hierarchies that societies have invented. The understanding of our belonging to the Earth alongside other species implies a different positionality in the humanities to respect and care for life in general. 

To approach these challenges, we can guide our responses by Paulo Freire’s idea of knowledge as the transformative collective action of human beings over the world, to see that our DH projects are not individual, but part of society. Then, we can think of DH in terms of situated knowledge and explore ideas of a caring society, which also implies a paradigm shift towards an operative perspective for working on reducing the environmental impact of DH projects. I use the term “working” because discussing is not enough, the material consequences of everyday technologies require responses in the realm of action. And here I have no recipe, this is a call for collective action. 

Now, let’s contextualize those challenges beyond any specific DH project. We live in a moment when data is a major commodity that is central to markets. For example, we pay tech companies, who are third parties, to store our files “in the cloud” and/or to process our data (e.g. with smartwatches and other devices). Tech companies also extract information from our everyday digital activities to use it for profit by selling it or applying it to developing new tools, such as training artificial intelligence. This model has been described as data colonialism. 

However, data colonialism requires digital infrastructure. The unhappy metaphor of “the cloud” is a distraction to shade scrutiny. In reality, data centers are industrial complexes [2] spread across the globe, as seen in this Data Center Map. The natural resources needed to operate data storage facilities affect the conditions of the ecosystems around them, for humans and non-humans. One of those resources is massive amounts of water; a report by environmental organizations mentions that “the U.S. Department of Energy estimated that U.S. data centers consumed 1.7 billion liters per day in 2014, or 0.14% of daily U.S. water use” (p.5).

Additionally, creating the hardware for those data centers and the infrastructure that connects us to them has only been possible due to extractivist practices. The history of technological development is linked to the extraction of raw materials (e.g. copper, silver, gold, lithium) mainly from the Global South, disregarding its effects on life on Earth. This implies that some of the most affected communities are those who have been historically dispossessed and happen to be also the most vulnerable to the changes in the Anthropocene. In other words, when someone says that “data is the new oil,” we can think of this comparison not only from the side of the value of its production, but also from the damaging effects of the oil industry profiting without caring for life on Earth. 

To all this, we need to add the recent rise of Artificial Intelligence, which adds a layer of complexity due to the massive amounts of computing power and data centers required to train and interact with the model, leading to even greater consumption of natural resources. We might learn more about the carbon impact of AI to make informed decisions, and, in case we use artificial intelligence in a project, it would be worth adding a note of the environmental impact of our research in the disclosure statement at the end of our work. 

Thinking through these ethical needs and the footprints of our DH projects is a very challenging proposal, but it is especially urgent in the current context. Responding to this challenge might make a difference in the creation of humanistic knowledge that could contribute beyond the humanities.

References that are not available with open access:

[1] Zalasiewicz, Jan, Colin N. Waters, Mark Williams, and Colin P. Summerhayes. (eds). 2019. The Anthropocene as a Geological Time Unit: A Guide to the Scientific Evidence and Current Debate. Cambridge: Cambridge University Press. https://doi.org/10.1017/9781108621359.

[2] Hogan, Mél. 2021. “The Data Center Industrial Complex.” In Melody Jue & Rafico Ruiz (eds.) Saturation: An Elemental Politics. Duke University