When design workshops meet chatbots: Meaningful participation at scale?

Stephen Yang, Jonathan Dortheimer, Aaron Sprecher, Qian Yang

Research output: Contribution to journalArticlepeer-review

Abstract

This paper explores the potential of chatbots, powered by large language models, as a tool for fostering community participation in architectural and urban design. By taking a hybrid approach to community participation in a real-world mixed-use building project, in which we integrated remote chatbot engagements with face-to-face workshops, we explored the potential for a hybrid approach to scaling up the reach of participation while ensuring that such participation is meaningful, genuine, and empowering. Our findings suggest that a hybrid approach amplified the strengths and mitigated the shortcomings of the two methods. The chatbot was effective in sustaining the length of participation, broadening the reach of participation, and creating a personalized environment for introspection. Meanwhile, the face-to-face workshops still played a crucial role in bolstering community ties and trust. This research contributes to understanding chatbots’ strengths and weaknesses in participatory processes, both within spatial design and beyond. In addition, it informs future explorations of participatory processes that span different spatial-temporal configurations.

Original languageEnglish
Pages (from-to)216-237
Number of pages22
JournalInternational Journal of Architectural Computing
Volume22
Issue number2
DOIs
StatePublished - Jun 2024

Keywords

  • Artificial intelligence
  • chatbot
  • community participation
  • large language models
  • natural language processing
  • participatory design

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