Abstract

While design is turning to more-than-human (MTH) approaches, integrating posthumanist theory into design practices remains challenging. We argue that making MTH thinking “actionable” demands moving beyond the idea that there is a gap to bridge. Instead, we propose that the space between theory and practice could offer an interesting starting point for experimentation. Exploring that liminal space, we designed two generative AI tools – Oblique and MoTH. Using ChatGPT-4, these tools create design strategies based on diverse MTH texts. Reflecting on the process of making and using these tools, we offer two contributions: First, we explain how designers can use the tools (and create their own variants) to walk through design concepts from multiple perspectives. Then, we provide a critical discussion on the opportunities and limitations of using AI for MTH design, including how to situate MTH knowledge(s) and avoid extractivist relations.

Keywords

more-than-human design; large language models; generative ai; posthuman design

Creative Commons License

Creative Commons Attribution-NonCommercial 4.0 International License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

Conference Track

Research Paper

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Jun 23rd, 9:00 AM Jun 28th, 5:00 PM

More-than-human Design and AI: Exploring the Space between Theory and Practice

While design is turning to more-than-human (MTH) approaches, integrating posthumanist theory into design practices remains challenging. We argue that making MTH thinking “actionable” demands moving beyond the idea that there is a gap to bridge. Instead, we propose that the space between theory and practice could offer an interesting starting point for experimentation. Exploring that liminal space, we designed two generative AI tools – Oblique and MoTH. Using ChatGPT-4, these tools create design strategies based on diverse MTH texts. Reflecting on the process of making and using these tools, we offer two contributions: First, we explain how designers can use the tools (and create their own variants) to walk through design concepts from multiple perspectives. Then, we provide a critical discussion on the opportunities and limitations of using AI for MTH design, including how to situate MTH knowledge(s) and avoid extractivist relations.

 

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