用语义排斥技术让AI创作更多样，避免千篇一律。
Seeing the Hivemind: A Consensus-Aware Interaction Technique for Mitigating AI Homogenization
- 引入语义排斥技术，主动降低AI输出的共识性
- 计算实验显示语义多样性提升85%~167%，共识短语减少43%~95%
- 用户测试中68.8%愿持续使用，且原创与通顺性不冲突
人们越来越多地用AI进行创意写作，但这种使用方式可能削弱个体创造力，并在整体上降低创意产出的多样性。为此，我们提出语义排斥技术（SRT），并通过计算评估和16名经常使用AI进行创作的参与者的研究进行验证。计算结果显示，SRT在不同任务模式下使语义多样性提升85%至167%，同时将共识性短语减少43%至95%。用户研究发现，SRT生成的内容在有用性（p = .019, W = .208）和连贯性（p = .006, W = .260）评分上更高；68.8%的参与者愿意在多个任务中使用SRT-Strong，而基线仅为18.8%。所有系统中原创性与连贯性呈正相关（ρ = +.40 至 +.67），表明差异性并不影响可读性。这些初步结果为设计支持日常创作且不加剧同质化的AI系统提供了依据。
原文摘要 · Abstract (English)
People are increasingly using AI for creative tasks such as writing. While adoption continues to grow, this form of use risks undermining individual creativity locally and reducing the heterogeneity of creative output at scale. In response, we introduce the Semantic Repulsion Technique (SRT) and evaluate it both computationally and through a study with 16 participants who regularly use AI for creative tasks. Our computational assessment reveals that SRT increases semantic diversity by 85--167\% while reducing consensus phrases by 43--95\% across task modes. In the user study, SRT outputs received higher usefulness ($p = .019$, $W = .208$) and coherence ratings ( $p = .006$, $W = .260$); 68.8\% of participants were willing to use SRT-Strong for multiple tasks versus 18.8\% for baselines. Originality and coherence ratings were positively correlated across all systems ($ρ= +.40$ to $+.67$), suggesting that divergence need not compromise readability. Taken together, these preliminary findings can inform the design of AI systems that aim to support everyday creativity without contributing to homogenization.
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