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arXiv 提交日期: 2026-02-10
📄 Abstract - Beyond Input-Output: Rethinking Creativity through Design-by-Analogy in Human-AI Collaboration

While the proliferation of foundation models has significantly boosted individual productivity, it also introduces a potential challenge: the homogenization of creative content. In response, we revisit Design-by-Analogy (DbA), a cognitively grounded approach that fosters novel solutions by mapping inspiration across domains. However, prevailing perspectives often restrict DbA to early ideation or specific data modalities, while reducing AI-driven design to simplified input-output pipelines. Such conceptual limitations inadvertently foster widespread design fixation. To address this, we expand the understanding of DbA by embedding it into the entire creative process, thereby demonstrating its capacity to mitigate such fixation. Through a systematic review of 85 studies, we identify six forms of representation and classify techniques across seven stages of the creative process. We further discuss three major application domains: creative industries, intelligent manufacturing, and education and services, demonstrating DbA's practical relevance. Building on this synthesis, we frame DbA as a mediating technology for human-AI collaboration and outline the potential opportunities and inherent risks for advancing creativity support in HCI and design research.

顶级标签: agents systems theory
详细标签: design-by-analogy human-ai collaboration creativity support design fixation foundation models 或 搜索:

超越输入-输出:通过人机协作中的类比设计重新思考创造力 / Beyond Input-Output: Rethinking Creativity through Design-by-Analogy in Human-AI Collaboration


1️⃣ 一句话总结

这篇论文提出,将一种基于认知的‘类比设计’方法融入人机协作的整个创意过程,可以有效对抗当前AI工具可能导致的创意同质化问题,并为不同领域的创新应用提供框架。

源自 arXiv: 2602.09423