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?
The adaptation of urbanised areas to climate change is currently one of the key challenges in the domain of urban policy. The diversity of environmental determinants requires the formulation of individual plans dedicated to the most significant local issues. This article serves as a methodic proposition for the stage of retrieving data (with the PESTEL and the Delphi method), systemic diagnosis (evaluation of risk and susceptibility), prognosis (goal trees, goal intensity map) and the formulation of urban adaptation plans. The suggested solution complies with the Polish guidelines for establishing adaptation plans. The proposed methodological approach guarantees the participation of various groups of stakeholders in the process of working on urban adaptation plans, which is in accordance with the current tendencies to strengthen the role of public participation in spatial management. https://doi.org/10.12911/22998993/81658
MULTIFILE
Species responding differently to climate change form ‘transient communities’, communities with constantly changing species composition due to colonization and extinction events. Our goal is to disentangle the mechanisms of response to climate change for terrestrial species in these transient communities and explore the consequences for biodiversity conservation. We review spatial escape and local adaptation of species dealing with climate change from evolutionary and ecological perspectives. From these we derive species vulnerability and management options to mitigate effects of climate change. From the perspective of transient communities, conservation management should scale up static single species approaches and focus on community dynamics and species interdependency, while considering species vulnerability and their importance for the community. Spatially explicit and frequent monitoring is vital for assessing the change in communities and distribution of species. We review management options such as: increasing connectivity and landscape resilience, assisted colonization, and species protection priority in the context of transient communities.
MULTIFILE
