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LIE-DARs: Grounding remote sensing and environmental AI in perspectives of algorithmic injustice and colonial legacies 
Lydia Gibson (Columbia University)
Tone Walford (University College London)
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Monday 6 June, -
Time zone: Europe/London

Short Abstract:

Grounding remote sensing and environmental AI in their sprawling infrastructures of data practices, actors, political and economic realities, and extractive legacies to better scrutinize their role in existing fieldwork structures and hierarchies, and the violence of data promises and erasures.

Long Abstract:

Remote sensing is fast becoming a mainstay of ecological methodology, replacing in-situ field observations. Many environmental scientists welcome this, citing high cost and carbon emissions of air travel, complex geopolitics, and fractious local sociopolitical structures as reasons to ostensibly decarbonise, depoliticise and “desituate” environmental research. Social science has taken notice of this shift, describing the automated sensors and monitors that now litter landscapes, and the drones and satellites that surveil them overhead, as a form of warfare; where dystopian Orwellian slow violence is intersected by rapid, necropolitical insurgences of military complexes. What is often overlooked, however, is that these instruments, sensors and technologies are just the most visible elements of sprawling informational infrastructures, protruding from and constituting capillary networks of data, technical arrangements, actors, actants, legacies, hierarchies, and imaginaries of environmental futures.

In this proposed panel we seek to provoke a broader scrutiny of automation, remoteness, and the desituation and depoliticization of environmental data, by grounding remote sensing and environmental AI in the geopolitical, topographic, and economic realities that surround and produce it. We invite contributions that explore spaces of power opened out by remote sensing and environmental AI; scrutinise their interdigitation with local environmental imaginaries and policies; reveal how the inequalities and injustices that have gone unresolved within field research are baked into databases, models, and algorithms; and render visible their reiteration of colonial and extractive relationships. In what ways do the ambivalent promises and erasures of interscalar data interact to (re)produce the contemporary violences within environmental research?

Accepted papers:

Session 1 Monday 6 June, 2022, -