Article | Open Access
AI-Supported Participatory Workshops: Middle-Out Engagement for Crisis Events
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Abstract: Considering the lived experience of communities is key when making decisions in complex scenarios, such as preparing for and responding to crisis events. The article reports on three participatory workshops, which assigned community representative roles to workshop participants. Using role-playing as a method, participants were given the task of collaborating on making a decision relating to a speculative crisis scenario. Across the workshops, we collected data about simulating a middle-out engagement approach and the role of artificial intelligence (AI) in enhancing collaboration, supporting decision-making, and representing non-human actors. The article makes three contributions to participatory planning and design in the context of the UN Sustainable Development Goals. First, it presents insights about the use of AI in enhancing collaboration and decision-making in crisis event situations. Second, it discusses approaches for bringing more-than-human considerations into participatory planning and design. Third, it reflects on the value of role-playing as a way to simulate a middle-out engagement process, whereby actors from the top and the bottom collaborate towards making informed decisions in complex scenarios. Drawing on the findings from the workshops, the article critically reflects on challenges and risks associated with using AI in participatory workshops and collaborative decision-making.
Keywords: artificial intelligence; community engagement; conversational agents; middle-out engagement; non-human personas; participatory design; participatory planning
Published:
Issue:
Vol 10 (2025): The Role of Participatory Planning and Design in Addressing the UN Sustainable Development Goals (In Progress)
© Martin Tomitsch, Joel Fredericks, Marius Hoggenmüller, Alexandra Crosby, Adrian Wong, Xinyan Yu, Weidong Huang. This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 license (http://creativecommons.org/licenses/by/4.0), which permits any use, distribution, and reproduction of the work without further permission provided the original author(s) and source are credited.