Plausibility in models and fiction: What Integrated Assessment Modellers can learn from an interaction with climate fiction

Futures(2023)

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摘要
Integrated assessment models (IAMs) are critical tools to explore possible pathways to a low-carbon future. By simulating complex interactions between social and climatic processes, they help policymakers to systematically compare mitigation policies. However, their authoritative projections of cost-effective and technically feasible pathways restrict more transformative low-carbon imaginaries, especially because IAM pathways are often understood in terms of probability rather than plausibility. We suggest an interaction with climate fiction could be helpful to address this situation. Despite fundamental differences, we argue that both IAMs and climate fiction can be seen as practices of storytelling about plausible future worlds. For this exploratory article, we staged conversations between modellers and climate fiction writers to compare their respective processes of storytelling and the content of both their stories and story-worlds, focusing specifically on how they build plausibility. Whereas modellers rely on historical observations, expert judgment, transparency and rationality to build plausibility, fiction writers build plausibility by engaging with readers’ life worlds and experience, concreteness and emotionally meaningful details. Key similarities were that both modellers and fiction writers work with what-if questions, a causally connected story and build their stories through an iterative process. Based on this comparison, we suggest that an interaction between IAMs and climate fiction could be useful for improving the democratic and epistemic qualities of the IAM practice by 1) enabling a more equal dialogue between modellers and societal actors on plausible futures and 2) critically reflecting upon and broadening the spectrum of plausible futures provided by IAMs.
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关键词
Integrated assessment model, Climate fiction, Storytelling, Mitigation scenario, Low-carbon futures, Plausibility
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