Critical data studies reveal environmental impacts of ai and data use
Critical Data Studies in the Anthropocene
Computers and Society
Summary
Data and artificial intelligence are growing quickly, but this growth has hidden environmental effects. The authors argue that researchers studying data should pay more attention to how data systems use resources and who benefits from them. They show examples from Spain and Chile where data infrastructure interacts with social and environmental issues, often ignoring some consequences. The chapter suggests combining ideas from different fields to better understand and address these challenges.
What this means in practice
- •For policy makers: Assess how data infrastructure investments influence social and environmental outcomes to design more equitable and sustainable data policies.
- •For urban planners: Incorporate understanding of data systems' environmental impacts into planning decisions to better manage infrastructure development.
A position paper. It proposes an approach and reports no results.
Authors
Ana Valdivia
Abstract
This chapter introduces the concept of the Anthropocene into critical data studies, a field that has, for the past decade, explored the entanglements between datafication and politics. With the scaling up of contemporary datafication alongside generative computing, it is essential to expand these debates, both theoretically and methodologically, to consider the logics of extraction and exploitation inherent in the politics of artificial intelligence. Critical data scholars are called to interrogate how dominant narratives around the materiality of contemporary datafication either obscure or reveal its environmental impacts, along other key questions such as who benefits from these logics. To illustrate this, this chapter brings two case studies from Spain and Chile and explores how the infrastructure of contemporary datafication intersects with existing power structures, influencing which social and environmental consequences are recognized, addressed, and neglected. Finally, it invites critical data scholars to keep exploring the politics of data, infrastructure, and the Anthropocene by blending discipline boundaries between science and technology studies, media, geography, and political ecology.