使用GPT-4的无监督方法评估创意想法的新性,可行性和价值
Felix B Kern1, Chien-Te Wu1, Zenas C Chao1
1International Research Center for Neurointelligence (WPI-IRCN), UTIAS, The University of Tokyo, Tokyo, Japan.
British journal of psychology (London, England : 1953)
|July 22, 2024
概括
本研究引入了一种新的方法,使用GPT-4来评估创造力,评估日本替代用途测试 (AUT) 的新性,可行性和价值. 这是一个很棒的节目,这是一个很棒的节目.
科学领域:
- 认知心理学 认知心理学
- 人工智能的人工智能
- 心理测量 心理测量 心理测量
背景情况:
- 创造力评估传统上优先考虑新性,往往忽视可行性和价值,限制现实世界的适用性.
- 现有的创造力测试可能无法完全捕捉到创造性思维的多面性质.
研究的目的:
- 开发和验证基于大型语言模型 (LLM) 的方法来评估创造力的三个关键维度:新性,可行性和价值.
- 评估在日语语言替代用途测试 (AUT) 的背景下,对LLM不同的提示设计的有效性.
主要方法:
- 利用GPT-4,一个复杂的LLM,来评估日本AUT的创造性反应.
- 采用众包评估方法,收集30个问题项的实地真相数据.
- 测试并比较了各种GPT提示设计,重点是"先解释,然后评估"策略,每个提示有多个响应.
主要成果:
- "首先解释,然后评估"提示设计,每次提示有多个响应,证明了成本效益和准确性 (r = .62, .59, .33对于新性,可行性,价值).
- 基于LLM的方法实现了与现有的新性评估方法相比的准确性,而不需要培训数据.
- 不同LLM (GPT-4 Turbo,GPT-4 Omni,Claude 3.5 Sonnet) 的一致性能表明,开发的提示设计具有普遍适用性.
结论:
- 使用LLMs.已经建立了一个直接和准确的平台,用于即时的AUT评估.
- 这项研究为未来的创造力评估方法研究提供了有价值的基础真相数据.
- 这些发现突出了LLM的潜力,可以全面评估多方面的创造力,而不仅仅是新奇.
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