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Accepted Contribution:

Data reliability and toxic exposure: anticolonial feminist approaches to the metrics and technologies of mediating air pollution  
Diana Flores Ruíz (University of Washington, Seattle)

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Long abstract:

This paper considers the planetary data infrastructures of air pollution monitoring through an anticolonial, feminist media, science and technology studies approach. I argue that contemporary efforts to (re)calibrate global data infrastructures of air pollution monitoring must take into account the socio-technical historical constructions of data reliability and toxic exposure. This shift also engenders a shift from thinking globally to thinking at a planetary scale. I apply this argument to a political aesthetics analysis of the United Nations Environment Programme’s 2021 air pollution exposure calculator, following Brian Larkin’s assertion that “political aesthetics sutures the material and the figural, showing how both are engaged in a constant reciprocal exchange” (2018).

In analyzing the technologies and metrics of the UNEP data visualization tool, I unpack the sociohistorical contexts that shape two core components of the calculator’s artificial intelligence-enabled live mapping interface: data reliability and toxic exposure. My historical overview of data reliability and toxic exposure fold in concepts from data justice and sovereignty studies, environmental justice, and ecofeminism. This overview encompasses the ways in which social inequities are entangled in processing the raw data of air pollution produced by governments, crowd-sourcing, and satellites, as well as their aggregate data banks.

In considering future avenues for air pollution metrics and technologies, I reflect on speculative measures using historical source material. I conclude by briefly analyzing how the Indigenous art collective Postcommodity accomplishes a perceptual recalibration through Going to Water (2021), their multimedia installation remediating air pollution surveillance video.

Combined Format Open Panel P193
Planetary data infrastructures
  Session 1