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June 7, 20242 citationsOpen Access

Environmental peacebuilding and AI: the case for decomputing

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DMDan McQuillan

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Abstract

In this paper I address the relationship between environmental peacebuilding and AI. That this question should come up is no surprise. Environmental peacebuilding, as the set of multiple ways in which the management of environmental issues can be integrated into conflict prevention, resolution and recovery, is no stranger to the use of technologies such as remote sensing and data analysis. Given the claims made about AI as a form of generalised problem solving with uncanny powers of prediction and interpretation, it seems only natural to ask how it might be adopted for such worthy ends. Indeed, this is in line with the reception of AI in society as a whole; that it is inevitable, and that the actual questions that arise about AI are utilitarian ones of maximising benefits and minimising harms. However, the argument I will put forward is that the nature of contemporary AI makes it profoundly problematic for environmental peacebuilding because it is deeply entangled with destroying environments and driving conflicts on multiple levels. The paper will make the case that the adoption of AI by the emergent field of environmental peacebuilding will intensify its own internal inconsistencies and amplify those tendencies that some have called environmental peacebuilding’s ‘dark side’.However, taking a critical stance towards AI for environmental peacebuilding is not simply to argue in the negative. In this paper I will also make the case for an alternative to AI as we know it, in the form of a prefigurative technopolitics of environmental peacebuilding. That is, it will try to articulate an approach to technology which is indivisible from the desired social and environmental ends, and which in its day-to-day operations acts to bring those goals into being. In the context of advanced computation and its relationship to environmental peacebuilding, the approach proposed in the paper is one of ‘decomputing’. Decomputing is a departure from AI’s commitments to extractivism and scale. It invokes care for the environment through a commitment to low-power infrastructure, salvage and repair, and to deconfliction by replacing modes of computation that sediment the status quo with those drawing on principles of relationality, inclusion and respect for life.

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Dan McQuillan (2024) studied this question.

synapsesocial.com/papers/68e65baeb6db6435875ea1d1https://doi.org/10.31235/osf.io/gs5bn
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