The nature of AI: metabolism, energy, water, labour and justice in the urban political ecology of artificial intelligence

Cugurullo, F., Caprotti, F., Day, J., Geoghegan, S., Lynch, C., Menga, F., Robinson, C. and Williams, J. ORCID: https://orcid.org/0000-0003-2125-8951 2025. The nature of AI: metabolism, energy, water, labour and justice in the urban political ecology of artificial intelligence. Urban Political Ecology 10.1177/30497515251344495

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Abstract

The integration of vast volumes of Artificial Intelligence (AI) technology into the built environment is changing the metabolism of urban spaces. Due to the presence of various AIs in urban systems, there are now more agentic forces influencing the trajectory of urban development and entangling with pre-existing biological intelligences. Because of AI's substantial environmental costs, more resources are now needed to satisfy cities’ technological appetite. Urban futures are also becoming more uncertain as private AI companies gain considerable power in urban governance through oligarchic schemes that leave citizens with no voice. In this paper, we bridge Urban Political Ecology (UPE) and urban AI literature, in order to critically examine the nature of AI as it intertwines with urban living and urban infrastructure. More specifically, we offer a threefold contribution to knowledge. First, we examine how the advent of urban AI is altering urban metabolism, zooming in on specific socio-environmental issues pertaining to energy, water and labour. Second, we discuss how the urban metabolisms altered by AI are reproducing uneven dynamics of development that are ultimately leading to different forms of injustice. Third and finally, we propose a potential course of action to politicize urban AI and intervene on its evolution.

Item Type:	Article
Date Type:	Published Online
Status:	In Press
Schools:	Schools > Geography and Planning (GEOPL)
Publisher:	SAGE Publications
ISSN:	3049-7515
Date of First Compliant Deposit:	12 May 2025
Date of Acceptance:	9 May 2025
Last Modified:	12 Jun 2025 12:45
URI:	https://orca.cardiff.ac.uk/id/eprint/178225

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