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Short abstract

We present “perspectival models” and explore the opportunities and challenges of modelling perspectives of preferences in public transportation use, in an attempt to promote public engagement in urban planning.

Long abstract

Can we enliven human perspectives on how cities are experienced using GenAI? How is it possible to create a tool that is both successful at conveying citizens' experiences and ideas, and useful for planning urban environments? We present a case study of the everyday public transportation environment in Winterthur, Switzerland, where users were asked to document their experiences via annotated photos. The study is driven by a methodological ambition to find new ways of giving voice to perspectives that are divergent and often excluded, simplified, or muted in bureaucratic processes. We do so by drawing on recent explorations of bringing perspectives into interaction with AI and the urban environment (Kozlowski & Evans, 2025; Nelson, 2021; Noyman et al., 2025), and introduce what we call "perspectival models", a term borrowed from Underwood (2019), built by combining fine-tuned GenAI and RAG algorithms on multimedia documentation of images, texts, voice notes, and metadata of time and space. By that, we prototype a tool for planning, repurposing digital traces of how the city is experienced by humans in new ways, thus proposing an alternative form of “Soft City Sensing” (Madsen, forthcoming; Madsen et al., 2022; Raban, 1974). Bringing our perspectival models into interaction, we are interested in uncovering common themes and disagreements of citizens’ experiences. We demonstrate these models during the panel and reflect upon in what ways they could succeed in involving citizens’ voices in urban planning. Are they able to convey citizens’ ideas? Or do they merely serve as an elicitation device?