Abstracts Submission

Recent developments in AI technologies have exacerbated existing concerns about the (un)sustainability of digitalisation and datafication. These concerns are related to the limitations of resources both natural and infrastructure-wise (Dekeyser & Lynch, 2025), to the exhaustion of the latter provoked by the excessive AI-use (Wang & Yorke-Smith, 2025), digital archiving, and mundane data consumption (Vale et al., 2024). This is related to the glut of digital footprints and waste in cities, which has been a problem for both cities and the media for centuries, albeit supercharged in the contemporary moment. What is new is the excessive use and normalisation of an (un)sustainable relationship with digital technology, including the everyday use of tools such as Chat GPT (Hogan, 2024). These tools have severe carbon footprint impacts, using as much water as an average family uses in almost two years for server cooling and electricity generation. For every hundred words generated by the service, an average of three bottles of water are consumed (DeGeurin, 2023).

The smart city and the new digital twins’ tropes—along with prescriptive and acritical perspectives that technologies will be the panacea for any complex issue—are part of the problem (Chiappini, 2020). Discourses around the effectiveness of these types of initiatives and projects often create, semantically and semiotically (Babushkina & Votsis, 2022), a distorted view of digital solutions for fictitious issues, including distortions of key human traits such as knowledge, meaning, and embeddedness into reality. On a smaller scale, the everyday life consumption on search engines, direct messaging, social media addiction, multimedia file exchange, and purchases on big tech logistic platforms pollute not only the environment but the collective consciousness, producing confusion, exhaustion, and fatigue. This constant generation of an amount of information that pollutes the brain becomes what Lovink (2019) defined as “brain-junk.” The number of apps keeps increasing, and so does the data they collect, but users are not always aware and digitally literate about these risks. Hence, both co-dependency on media technologies and a lack of a high degree of digital literacy can be considered societal and spatial issues that might create unevenness. It is unfortunately not possible to control-click emptying the trash from digital waste and material pollution: much of it goes beyond the current understanding and technical capability to take care of. Therefore, there is an urge to overcome the rapid accelerationism of techno-determinism and solutionism and identify tactics and strategies aimed at reducing digital waste.

This thematic issue is concerned with the timely and vital problem of digitalisation and its (un)sustainability, fostering a discussion on the waste and pollution, digital and material, caused by massive datafication and urban platformisation (Cristofari, 2023). The relationship between the geographical scale, socio-political goals, and the technological design of digital infrastructures is of crucial importance to the understanding of the issue of digital waste and its possible reduction (Chiappini & Ferrari, 2024). For instance, data centres account for about two percent of all global energy use, and the raw amount of energy consumed by data centres doubles roughly every four to eight years (International Energy Agency, 2022). Hence, in terms of urban planning, the localisation of data centres has key implications, with direct consequences over the surrounding environment with regard to air pollution and climate change. The thematic issue encompasses inter- and trans-disciplinary perspectives from urban studies and planning, including digital geography, sociology, semiotics, environmental studies, and legal approaches. It aims to engage critically with the normative and prescriptive discourses which favour a techno-determinist view where smart city projects are celebrated. We invite papers that deal with concepts such as waste, noise, and excess in terms of data, materials, time, labour, cultural surplus, chatbots, and AI-powered services, also, but not exclusively, in relation to the uselessness and ineffectiveness of smart city projects and digital twins’ experiments.

References:

-         Babushkina, D., & Votsis, A. (2022). Epistemo-ethical constraints on AI-human decision making for diagnostic purposes. Ethics and Information Technology, 24(2), Article 22.

-         Chiappini, L. (2020). The urban digital platform. Instance from Milan and Amsterdam. Urban Planning, 5(4), 277–288. https://doi.org/10.17645/up.v5i4.3417

-         Chiappini, L., & Ferrari, V. (2024). Digital geographies of power: The scale of digital money infrastructures. First Monday, 29(10). https://doi.org/10.5210/fm.v29i10.13786

-         Cristofari, G. (2023). The politics of platformization: Amsterdam dialogues on platform theory. Institute of Network Cultures. https://networkcultures.org/blog/publication/the-politics-of-platformization-amsterdam-dialogues-on-platform-thoery

-         DeGeurin, M. (2023). 'Thirsty' AI: Training ChatGPT required enough water to fill a nuclear reactor's cooling tower, study finds. Gizmodo. https://gizmodo.com/chatgpt-ai-water-185000-gallons-training-nuclear-1850324249

-         Dekeyser, T., & Lynch, C. R. (2025). Control and resistance in automated shops: Retail transparency, deep learning, and digital refusal. Antipode, 57, 53–74. https://doi.org/10.1111/anti.13093

-         Hogan, M. (2024). AI is a hot mess. Training the Archive, 33–54.

-         International Energy Agency. (2022). World Energy Outlook 2022. https://www.iea.org/reports/world-energy-outlook-2022

-         Lovink, G. (2019). Sad by design. Pluto Press.

-         Vale, M., Ferreira, D., & Rodrigues, N. (Eds.). (2024). Geographies of the platform economy. Springer.

-         Wang, T., & Yorke-Smith, N. (Eds.). (2025). AI for and in Urban Planning [Thematic issue]. Urban Planning, 10. https://doi.org/10.17645/up.i388