Worldwide, rivers face challenges due to human and climatic pressures. Floods, droughts, pollution, damming and hydropeaking are only a few examples of these pressures, and influence the way rivers flow. Climate change adaptation projects increase the incentive to domesticate rivers, often legitimised through expert views on (future) vulnerability and risk. This emerging river imaginary dominates current debates in many rivers in our world. River imaginaries reflect spatially bound hydrosocial territories in which multiple actors on multiple scales from multiples sectors operate to reach varying objectives. They include water flows, ecological systems, climate conditions, hydraulic infrastructure, financial means, institutional arrangements, legal frameworks and information/knowledge hubs. In the context of climate change adaptation, river imaginaries are strongly dependent on the extent to which climate change is expected to influence rivers through a mixture of probable, possible, desirable or preferable versions of a (future) river. As such, knowledge-structures of future making are scrutinised in this research by emphasising on the role of change, the role of futures and the role of experts. This presentation aims to elucidate how river imaginaries have influenced river management under climate change adaptation that resulted in large infrastructural projects. Through a study of the Meuse river, a concrete case of a imaginary came into being in the Dutch-Belgian Border-Meuse trajectory. Moreover, preliminary result from adaptation projects in the marshlands of the lower Magdalena in Colombia strengthen the dominate imaginary of technocratic and ecocentric approaches to climate change adaptation where an expert view on local knowledge dominates.
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Oratie over het commercialiseringsproces op sportgebied, uitgesproken op 18 oktober 2006 bij de openbare aanvaarding van het ambt van bijzonder hoogleraar op het vakgebied van de Sportontwikkeling aan de Universiteit Utrecht in de faculteit Rechtsgeleerdheid, Economie, Bestuur en Organisatie, departement Bestuurs- en organisatiewetenschappen.
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This paper introduces and contextualises Climate Futures, an experiment in which AI was repurposed as a ‘co-author’ of climate stories and a co-designer of climate-related images that facilitate reflections on present and future(s) of living with climate change. It converses with histories of writing and computation, including surrealistic ‘algorithmic writing’, recombinatory poems and ‘electronic literature’. At the core lies a reflection about how machine learning’s associative, predictive and regenerative capacities can be employed in playful, critical and contemplative goals. Our goal is not automating writing (as in product-oriented applications of AI). Instead, as poet Charles Hartman argues, ‘the question isn’t exactly whether a poet or a computer writes the poem, but what kinds of collaboration might be interesting’ (1996, p. 5). STS scholars critique labs as future-making sites and machine learning modelling practices and, for example, describe them also as fictions. Building on these critiques and in line with ‘critical technical practice’ (Agre, 1997), we embed our critique of ‘making the future’ in how we employ machine learning to design a tool for looking ahead and telling stories on life with climate change. This has involved engaging with climate narratives and machine learning from the critical and practical perspectives of artistic research. We trained machine learning algorithms (i.e. GPT-2 and AttnGAN) using climate fiction novels (as a dataset of cultural imaginaries of the future). We prompted them to produce new climate fiction stories and images, which we edited to create a tarot-like deck and a story-book, thus also playfully engaging with machine learning’s predictive associations. The tarot deck is designed to facilitate conversations about climate change. How to imagine the future beyond scenarios of resilience and the dystopian? How to aid our transition into different ways of caring for the planet and each other?
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