AI and Global Climate Change: The political economy of data and energy in geographic perspective

Abstract

Artificial Intelligence (AI) and Global Climate Change are two developments that will come to define the twenty-first century. As such, examining their intersections is crucial and can yield important insights. Geography is well positioned to study these intersections through its diverse conceptual and methodological toolkit, which bridges the physical and environmental science, the social sciences and the humanities, as well as the human and more-than-human worlds. A first step in deploying a geographic analysis can be to ground the links between AI and Global Climate Change in concrete geographic contexts. I illustrate this exercise in the paragraphs that follow and identify its productive potential. Specifically, this text deploys a geographic perspective grounded in political economy to connect concerns about the data and energy inequalities embedded in various AI applications while showing how such inequalities are intertwined both with the monitoring of Global Climate Change and with its material impacts.