Recent advances in machine learning have enabled computers to converse with humans meaningfully. In this study, we propose using this technology to facilitate design conversations in large-scale urban development projects by creating chatbot systems that can automate and streamline information exchange between stakeholders and designers. To this end, we developed and evaluated a proof-of-concept chatbot system that can perform design conversations on a specific construction project and convert those conversations into a list of requirements. Next, in an experiment with 56 participants, we compared the chatbot system to a regular online survey, focusing on user satisfaction and the quality and quantity of collected information. The results revealed that, with regard to user satisfaction, the participants preferred the chatbot experience to a regular survey. However, we found that chatbot conversations produced more data than the survey, with a similar rate of novel ideas but fewer themes. Our findings provide robust evidence that chatbots can be effectively used for design discussions in large-scale design projects and offer a user-friendly experience that can help to engage people in the design process. Based on this evidence, by providing a space for meaningful conversations between stakeholders and expanding the reach of design projects, the use of chatbot systems in interactive design systems can potentially improve design processes and their outcomes.

中文翻译：

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评估大语言模型聊天机器人以吸引社区参与大型设计项目

机器学习的最新进展使计算机能够与人类进行有意义的对话。在这项研究中，我们建议使用该技术通过创建聊天机器人系统来促进大型城市开发项目中的设计对话，该系统可以自动化和简化利益相关者和设计师之间的信息交换。为此，我们开发并评估了一个概念验证聊天机器人系统，该系统可以针对特定的施工项目执行设计对话，并将这些对话转换为需求列表。接下来，在 56 名参与者参与的实验中，我们将聊天机器人系统与常规在线调查进行了比较，重点关注用户满意度以及收集信息的质量和数量。结果显示，就用户满意度而言，与定期调查相比，参与者更喜欢聊天机器人体验。然而，我们发现聊天机器人对话产生的数据比调查更多，新颖想法的比例相似，但主题较少。我们的研究结果提供了强有力的证据，表明聊天机器人可以有效地用于大型设计项目中的设计讨论，并提供用户友好的体验，有助于吸引人们参与设计过程。基于这一证据，通过为利益相关者之间提供有意义的对话空间并扩大设计项目的范围，在交互式设计系统中使用聊天机器人系统可以潜在地改善设计流程及其结果。