区分人与AI的创意表现，用新方法衡量人类创造力。
Measuring Creativity in the Age of Generative AI: Distinguishing Human and AI-Generated Creative Performance in Hiring and Talent Systems
- 将创意定义为在约束下生成新颖想法的过程，基于嵌入空间中的思想演化来量化。
- 实证显示新指标符合直觉判断，能捕捉表面质量忽略的创意差异。
- 发现AI环境下创意输出呈双峰分布，突出独特性比流畅性更重要。
生成式AI正快速改变组织创造价值和评估人才的方式。尽管大语言模型提升了基础输出质量，却也带来了对人类创造力评估的模糊性——可观测成果可能部分或完全由AI生成。本文将创意重新定义为一种在共同约束和竞争激励下涌现的分布性与过程性属性。我们提出一个量化框架，通过嵌入空间中的思想生成与转化来衡量创意的新颖性。实证评估表明，该指标与人类对创意的直观判断一致，且能捕捉到仅看表面质量所忽视的区别。研究进一步发现，在AI中介环境中，创意产出出现结构性双峰分布，这对招聘、领导力和竞争策略具有深远影响。结果表明，在生成式AI时代，独特性而非流畅性成为人类创造力的主要信号。
原文摘要 · Abstract (English)
Generative AI is rapidly transforming how organizations create value and evaluate talent. While large language models enhance baseline output quality, they simultaneously introduce ambiguity in assessing human creativity, as observable artifacts may be partially or fully AI-generated. This paper reconceptualizes creativity as a distributional and process-based property that emerges under shared constraints and competitive incentives. We introduce a quantitative framework for measuring creativity as novelty in synthesis, operationalized through idea generation and idea transformation within embedding space. Empirical evaluation demonstrates that the proposed metrics align with intuitive judgments of creativity while capturing distinctions that surface-level quality assessments miss. We further identify a structural shift toward bimodal distributions of creative output in AI-mediated environments, with implications for hiring, leadership, and competitive strategy. The findings suggest that in the age of generative AI, distinctiveness rather than fluency becomes the primary signal of human creative capability.
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