AI生成网页时易趋同，本文提出用'有益摩擦'保护设计多样性。
Interrogating Design Homogenization in Web Vibe Coding
- 分析网页风格生成全周期，定位同质化风险点。
- 发现快速生成需求会加剧设计趋同与潜在危害。
- 提出以'有益摩擦'为核心的多样性保护框架。
生成式AI常因训练数据中的主流风格而产生同质化输出。然而，这种同质化是否延伸至复杂结构任务如网页设计仍不明确。随着非专业用户越来越多地使用大模型进行‘ vibe-coding’——通过描述美学与功能目标而非编写代码来生成网站，他们可能无意中缩小设计多样性，限制互联网整体的创造性表达。本文探究网页vibe-coding中的设计同质化可能性。首先，我们刻画vibe-coding的生命周期，识别同质化风险出现的关键阶段；其次，开展社会技术风险分析，揭示vibe-coding潜在危害及其与设计同质化的交互影响；研究发现，对无摩擦生成的追求会加剧同质化及其负面影响。最后，我们提出以‘有益摩擦’为核心理念的缓解框架。通过微观、中观、宏观三个层面的案例研究，证明聚焦有益摩擦可帮助创作者挑战默认输出，维护人工智能辅助网页设计中的多样化表达。
原文摘要 · Abstract (English)
Generative AI is known for its tendency to homogenize, often reproducing dominant style conventions found in training data. However, it remains unclear how these homogenizing effects extend to complex structural tasks like web design. As lay creators increasingly turn to LLMs to 'vibe-code' websites -- prompting for aesthetic and functional goals rather than writing code -- they may inadvertently narrow the diversity of their designs, and limit creative expression throughout the internet. In this paper, we interrogate the possibility of design homogenization in web vibe coding. We first characterize the vibe coding lifecycle, pinpointing stages where homogenization risks may arise. We then conduct a sociotechnical risk analysis unpacking the potential harms of web vibe coding and their interaction with design homogenization. We identify that the push for frictionless generation can exacerbate homogenization and its harms. Finally, we propose a mitigation framework centered on the idea of productive friction. Through case studies at the micro, meso, and macro levels, we show how centering productive friction can empower creators to challenge default outputs and preserve diverse expression in AI-mediated web design.
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