在叙事任务中的GenAI创造力:探索新形式的创造力
Florent Vinchon1, Valentin Gironnay1, Todd Lubart1
1Laboratoire de Psychologie et d'Ergonomie Appliquée (LaPEA), Université Paris Cité and Univ Gustave Eiffel, F-92100 Boulogne-Billancourt, France.
Journal of Intelligence
|December 27, 2024
概括
像ChatGPT一样,生成人工智能 (GenAI) 显示出高内容流性,但平均创造力. 人类指导是独创性的关键,需要新的AI创造力指标.
科学领域:
- 认知科学 认知科学
- 人工智能的人工智能
- 心理学 心理学 心理学
背景情况:
- 生成型人工智能 (GenAIs) 已经迅速发展,像ChatGPT这样的模型变得广泛可用.
- 评估GenAIs的创意能力对于了解它们对各个领域的影响至关重要.
- 传统的创造力指标可能无法充分捕捉人工智能产生的内容的独特性质.
研究的目的:
- 通过使用标准化创造力测试来评估领先的GenAI (ChatGPT) 的创意表现.
- 为了将GenAI的创意产出与人类的表现进行比较.
- 探索人工智能的创造性特征对现有的测量工具的影响.
主要方法:
- 使用标准化创造力评估协议.
- 将ChatGPT与人类参与者的性能进行了比较.
- 分析生成内容的流性和原创性.
主要成果:
- 聊天GPT在生成内容方面表现出了异常的流性.
- 当与人类标准进行比较时,ChatGPT产出的创意质量被发现是平均的.
- 人工智能创造力表现出一定程度的随机性和依赖训练数据.
结论:
- 目前的创造力指标需要重新评估以适应AI能力.
- 人类参与对于将GenAIs引导到新的和原始的输出是必不可少的.
- 未来的研究应该集中在人类-人工智能共同创造和开发可靠的AI创造力评估机制上.
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