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Paper short abstract

The paper explores the role of geological surveying and geospatial data visualization in environing the underground in the context of mineral extraction. Based on collaborative research within an arts and science project, it draws on the approach of critical media practice and political geology.

Paper long abstract

The paper explores the role of geological surveying and geospatial data visualization in environing the underground in the context of mineral extraction. Based on collaborative research within an arts and science project, it draws on the approach of critical media practice and political geology.

Vertical gaze of geological exploration does not simply record subsoil strata but enacts the subterrean space as a site of mineral deposits. The axis of the section runs from the outskirts of the atmosphere, through satellite imagery, to Earth's depths (and back, in case of asteroid mining), and the technical eye, itself composed of extracted metals such as lithium, cobalt, and europium, becomes a tool for environing the voluminous, inscrutable spaces. Within the limits of resolution, the technical imagery maps the surface and traces indices, which, together with gamma-ray measurements or the identification of particular plants in the landscape, make the subterranean legible and governable. Visualization technologies environ the underground with an eye on profit from speculative markets and political strategies, such as the EU's low-carbon and digital transitions and critical raw materials classification.

While sinking the probe might suppress other ways of sensing and relationship-making with the subsoils, what spaces are created beyond the edge of exploration and speculation, in the cracks of the Earth, between the individual images and the pixels in the image itself? We reflect on the prospecting practices and production of digital visual representations of underground, while exploring how the arts can facilitate seeing vertical geographies and inscrutable spaces otherwise.

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Paper short abstract

Cloud computing in cities relies on resource-intensive data centers in climate-vulnerable peripheries. Cases from Germany and Spain illustrate the toxic footprint and reorganization of especially rural ‘back end’ spaces that fuel urban cloud infrastructures and economic policies.

Paper long abstract

Big Tech corporations like Amazon and its subsidiary Amazon Web Services (AWS) are increasingly involved in public–private urban infrastructure projects. Their technologies have become the backbone of states’ administration, providing the public sector with cloud computing services. In 2026, for example, AWS has launched a “European Sovereign Cloud” with investments in the state of Brandenburg's data center landscape in cooperation with the German government. Near Berlin, AWS leverages regional cluster politics designed to attract Big Tech and position the German capital at the forefront of European cloud developments. In Aragón, Spain, AWS is similarly building the continent’s largest data-technology hub around promises of economic growth and technology-based resilience for urban areas such as Zaragoza.

Following these two cases, our ethnographic research explores how cloud computing in cities relies on peripheral data centers that consume large amounts of water and energy in toxic environments already strongly affected by the climate crisis. We analyze the exploitative relations between headquarter tech campuses and processing margins as a front end/back end configuration that resembles software/hardware architectures in the ever-present computing of modern urbanism. Drawing on Urban Political Ecology and STS, our findings let local decision-makers, water, and protesters speak alike. How are public data, environmental and social responsibilities privatized and depoliticized through techno-solutionist promises? For whose benefit and to whose loss? Analyzing unjust geographies of polluted back ends and representative front-end developments, we critically conceptualize a digital-material “cloud-city” urbanism and shed light on environments and resistances of communities in its shadows.

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Paper short abstract

Data-rich health technologies are increasingly promoted for addressing health burdens, but carry high environmental impacts and exacerbate health inequities. We advance the concept of Environmental Health Data Justice to re-territorialize the environmental and social justice effects of health data.

Paper long abstract

The rise of data-rich health systems and technologies is an emergent field of environmental justice. Data-rich health technologies, including artificial intelligence, are increasingly promoted as a means to address health burdens, including those driven by anthropogenic environmental change. However, data-rich health technologies come with burdens of their own. They carry substantial environmental impacts, exacerbating both local pollution and global climate change while at the same time digitizing existing health inequities. One of the most concerning effects of these dynamics is that the communities who are likely to be most affected by matters of health data justice are often the same communities that are disproportionately affected by environmental harms. To explore these entanglements, this paper proposes the concept of Environmental Health Data Justice (EHDJ). EHDJ makes visible connections beyond immediate health data ecosystems and can enable a re-territorialization of the environmental and social justice effects specific to health data. Drawing on different case studies, we show how the logic of extraction underpins both the material and “immaterial” components of health data practices. We propose that while environmental and social justice movements have long invested in promoting and protecting multi-faceted areas of health, it is important to turn our attention specifically to the logics, infrastructures, and relationships of health datafication and the effects on our bodies, communities, and lived environments. EHDJ aims to ensure that health-relevant data is collected, shared, processed, and acted upon in ways that dismantle systemic forms of environmental and health injustice and advance the needs of marginalized communities.

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Paper short abstract

AI’s material infrastructures - data centers, chips, energy, and water systems - produce emissions and extract resources in ways affecting planetary and human health. Our scoping review maps scholarship connecting AI's environmental impacts to health outcomes, revealing key research gaps.

Paper long abstract

Artificial intelligence (AI) is widely promoted, yet the material infrastructures underpinning AI have significant consequences for planetary and human health. Data centers, high-performance computing (HPC) facilities, semiconductor manufacturing, energy grids, water-cooling, and other, less visible AI components are associated with environmental impacts including greenhouse gas emissions, water withdrawals, toxic releases, resource extraction, and heat discharge. These environmental impacts, in turn, are increasingly associated with health risks for humans on both individual and population levels. Structured overviews of these connections, however, are lacking.

This contribution maps the AI's environmental footprints' impacts on individual and public health. We explore how environmental risks of AI documented in peer-reviewed scholarship have been associated with health outcomes, both statistically and qualitatively. Drawing on findings from a scoping review of peer-reviewed studies published over the past 10 years, we present preliminary findings, including an overview of identified environmental impact categories, patterns of health linkage, and emerging methodological gaps.

These initial results open up discussion about how AI’s toxic world is enacted within peer-reviewed literature. The findings will shed light on how AI is already fostering new pathways for unequally distributing pollution and contamination, which, in turn, is creating unequal health risks for individuals and on a population level. As digitalization projects transform landscapes, these effects are at risk of intensifying. We will close by proposing avenues for participatory research to address these inequalities.

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Paper short abstract

The "twin transition" is promising more sustainable energy and production systems. Yet the infrastructures enabling AI involve high energy demand, changes in labor and resource use. The paper explores tensions between AI’s sustainability promises and its material impacts.

Paper long abstract

Artificial intelligence (AI) is increasingly positioned as a key driver of sustainable futures. Within the European policy framework of the “twin transition”, digitalization and sustainability are framed as mutually reinforcing pathways toward climate-neutral and resource-efficient societies (EURAXESS, n.d.). AI is expected to play a central role in this process, for example, through optimizing energy systems as well as improving resource efficiency in production cycles. At the same time, the infrastructures that enable AI are associated with significant energy demand and material extraction. These infrastructures are systemically interwoven with toxic environments and unevenly distributed ecological burdens. Recent scholarship further stresses that digitalization and ecological transformation reshape labor and resource-use in interconnected yet tension-ridden ways (Brandl & Matuschek, 2024). Against this backdrop, the very premise of “sustainable AI” has increasingly been called into question, as attempts to reconcile the rapidly expanding use of AI with broader societal sustainability goals may involve fundamental frictions (Rehak, 2024).

Building on Van Wynsberghe’s (2021) distinction between AI for sustainability and the sustainability of AI, the contribution examines how the sustainability promises attached to AI intersect with the production of toxic materialities and uneven environmental exposures.

The paper argues that the twin transition should not be understood as a self-reinforcing pathway toward sustainability but as a process that requires careful governance and infrastructural steering if digitalization is to contribute to sustainable futures rather than producing new toxic environments.