Entangled Intelligence
AI-Collaborations for More-than-Human-Centred Approaches to Community-Based Climate Adaptation
T. Adriaanssen (TU Delft - Industrial Design Engineering)
D.S. Murray-Rust – Mentor (TU Delft - Human Technology Relations)
R. Bendor – Graduation committee member (TU Delft - Codesigning Social Change)
Bulent Ozel – Graduation committee member (Lucidminds)
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Abstract
Climate change is happening. As mitigation efforts can no longer stop climate change, adaptation is needed to ensure climate resiliency. National regulations and policies often fail to meet the specific contexts of the local scales, and thus, communities need to render themselves capable of adapting through Community-Based Climate Adaptation (CBA) projects. Artificial Intelligence (AI) is seen as a powerful technology with much potential for aiding communities in their adaptation goals, but how this collaboration is to be designed is still unclear. This project uses a More-than-Human-Centred (MtHC) approach, as well as the CreaTures framework and the Augmented Collective Intelligence framework, to explore the collaboration between urban communities and AI technology. This exploration is done to assess how AI systems can enhance the capabilities of communities, and how residents can be motivated to adopt MtHC approaches in their adaptation measures. The process, stakeholders, and challenges of CBA projects, as well as opportunities for AI-based interventions, are explored through literature research, expert interviews and a thematic analysis. Following this, design concepts are explored in collaboration with an expert panel, prototypes of further developed iterations are tested, and a final concept is created. The final concept, called Entangled Intelligence, is tested both with a participant group and the expert panel, in order to retrieve insights on the research questions. The project and its limitations are discussed, and a set of characteristics of AI that support MtHC approaches to CBA is presented.