AI 中文总结
该研究构建受对抗性设计理论启发的AI智能体，通过45名设计学生的实验发现，该智能体实施的建设性冲突可提升新手交互设计师的重新考量能力，推动设计改进与创意拓展。
AI 中文摘要
生成式AI智能体正越来越多地被用于交互设计中，以辅助创意构思并提供反馈，这类智能体通常遵循自身的内部推理逻辑，这类交互往往会增加设计创意并拓展设计空间。本研究探索设计智能体的对抗性角色，促使设计师应对利益相关者的矛盾。我们构建了一个受对抗性设计理论启发的AI智能体，该智能体可构建建设性冲突。我们采用被试间实验考察该智能体的影响，共有45名设计专业学生参与实验，分为三个条件组：自我反思组（对设计方案进行无辅助的评审）、逐步指导组（通过书面提示引导设计师完成建设性冲突框架）、互动参与组（通过AI智能体交互式实施建设性冲突框架，综合利益相关者的反对意见）。后两个条件组共享同一框架，但区别在于框架是自行实施还是由智能体实施。结果显示，与自我反思组相比，逐步指导组和互动参与组均报告了显著更高的自我重新考量程度，并对设计方案做出了更多改进；与逐步指导组相比，对抗性智能体引入了更多冲突性视角，互动参与组的参与者生成并舍弃了更多创意。这些发现表明，由智能体实施的建设性冲突可将重新考量转化为具体的设计行动，并加深对不同利益相关者视角的参与度。
英文摘要
Generative AI agents are increasingly used in interaction design to facilitate ideation and offer critique, often following their own internal reasoning. These interactions tend to add design ideas and expand the design space. Our work explores an antagonistic role for design agents, prompting designers to engage with stakeholder tension. We built an AI agent inspired by adversarial design theory that enacts constructive conflict. We examine the agent's influence in a between-subjects experiment with 45 design students across three conditions: Self Reflection (unsupported review of the design proposal), Stepwise Guidance (written prompts that walk designers through a constructive-conflict framework), and Interactive Engagement (an AI agent that enacts the constructive-conflict framework interactively by synthesizing stakeholder pushback). The latter two conditions share the framework but differ in whether it is self-enacted or agent-enacted. Results show that, compared with Self Reflection, both the Stepwise Guidance and Interactive Engagement groups reported significantly higher self-reconsideration and made more improvements to their design proposals. Compared with Stepwise Guidance, the antagonistic agent introduced more conflictual perspectives, and participants in the Interactive Engagement condition generated and discarded more ideas. These findings suggest that agent-enacted constructive conflict can turn reconsideration into concrete design actions and deepen engagement with divergent stakeholder perspectives.
Comments8 pages, 4 figures, conditionally accepted to Human-Agent Interaction 2026
