人与LLM创造力:对任务依赖不对称性和语言机制的比较分析
Liping Yang1, Tao Xin2, Yunye Yu3
1Higher Education Supervision and Evaluation Institute, Beijing Institute of Educational Supervision and Evaluation, Beijing 100034, China.
Journal of Intelligence
|February 26, 2026
概括
人类的创造力在新的任务中脱而出,而人工智能提高了写作质量和连贯性. 与有缺陷的AI合作可以阻碍人类的表现,创造一个"协作陷",并冒着同质化的风险.
科学领域:
- 认知心理学 认知心理学
- 人工智能的人工智能
- 人与计算机的交互
背景情况:
- 了解人类和大型语言模型 (LLM) 独特的创作过程在不断变化的AI辅助内容生成领域中至关重要.
- 现有的研究往往侧重于人工智能的能力,不太重视人类和人工智能的创造力背后的独特机制.
研究的目的:
- 为了比较人类和LLM在写作任务中的独特创造力机制.
- 分析仅有人类,仅LLM和LLM辅助写作场景中的性能差异.
- 确定影响人类原创性与LLM有效性的因素,并探索潜在的合作陷.
主要方法:
- 一个两阶段的实验设计,比较人类,LLM-Only和LLM辅助的写作性能.
- 分析命题和创意写作任务,以评估原创性和执行质量.
- 阶层调节回归以揭示不同的语言路径和创造力概况 (理想,安全,适度,普通).
主要成果:
- 人类作者在高要求的创作任务中表现出卓越的独创性.
- 在各种任务和参与者群体中,LLM在执行质量和有效性方面表现出色.
- 观察到一个明显的不对称性:人类的独创性与主观认知投资有关,LLM的有效性与结构连贯性有关.
- 确定了"协作陷"现象,其中低于最佳的LLM协作阻碍了人类的表现,并诱导了认知定.
结论:
- 人类和LLM的创造力通过从根本上不同的机制运作,人类驱动独创性,LLM优化有效性.
- 任务的性质和LLM的质量显著影响合作成果.
- 对"协作陷"的认识对于开发教学方法至关重要,这些教学方法可以保护人类代理,并防止人类-人工智能写作伙伴关系中的创造性同质化.
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