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Paper short abstract

Over-reliance on the promises of digital twins blunts our ability to flexibly react to a changing environment. This research investigates how large-scale digital twins of the Earth actively reconfigure the future; ultimately making us less resilient by narrowing the scope of climate interventions.

Paper long abstract

Digital twin (DT) technologies emerged out of manufacturing and engineering industries, designed to link an object, product, or system – the ‘physical twin’ – with a virtual ‘digital twin’ – an identical, mutually-affecting representation that updates in real time. In environmental contexts, they are increasingly applied as a technological innovation that promises to solve the interlinked crises of biodiversity loss, climate change, and pollution by allowing us to observe (and, in theory, avoid) undesirable potential futures. Through creating AI-enabled, multi-scale, continually-updating models, digital twins of Earth system processes aim to improve resilience; informing governmental decision-making processes, forecasting future climate events, and helping with resource allocation. Whilst they have the potential to be impactful at local scales, large-scale digital twins of the Earth actively reconfigure how we envisage and engage with the future by changing our approach to planning and prediction. They only forecast what we already know to model, creating a form of narrow resilience. ‘Informed’ becomes ‘outsourced’ in decision-making, with interventions targeted to solve specific ‘what-if’ scenarios, turning attention away from supporting adaptability to cope with both expected and unforeseen situations. In this, they act as ‘blinkered oracles’; revered actors that offer the myth of a certain future. This research draws on findings from a multi-sited ethnography, combined with literature from science and technology studies, responsible innovation, and risk and disaster reduction, to consider how digital twins of the Earth create potential futures that we privilege over the very real present.