人工智能辅助设计合成和工程教育中的人类创造力
Mariza Tsakalerou1, Saltanat Akhmadi1, Aruzhan Balgynbayeva1
1Department of Civil and Environmental Engineering, Nazarbayev University, Astana, Kazakhstan.
Frontiers in artificial intelligence
|February 5, 2026
概括
生成型人工智能加速了创意的产生,但可以限制创造力和功能改进. 只有人类的团队生产了更多的多样化和更高质量的设计,这表明过度依赖人工智能可能会阻碍创造性发展.
科学领域:
- 人与计算机的交互
- 认知科学 认知科学
- 工程教育 工程教育教育
背景情况:
- 人工智能 (AI) 融入教育和专业领域,引发了关于它对人类创造力影响的关键问题.
- 生成型人工智能工具提供快速的创意产生,但它们在促进真正创新的作用仍在争论中.
研究的目的:
- 在工程教育背景下,研究设计任务中人类-人工智能协作的动态.
- 用既定指标评估人工智能协助对创意表现的影响.
主要方法:
- 一项探索性准实验性研究,比较人工智能辅助和只有人类设计团队.
- 在四个方面评估创意表现:解决方案的数量,多样性,独特性和质量.
- 应用创造力指标,包括流性,灵活性,独创性和精确性.
主要成果:
- 人工智能加速了最初的想法产生,但导致过早的融合和狭窄的探索.
- 只有人类的团队展示了更大的代实验,生产具有更高功能质量和思想多样性的设计.
- 自我感知的创造力保持稳定,这表明尽管表现差异,潜在的认知卸载.
结论:
- 人工智能为创意提供了机会,但过度依赖可能会削弱代学习和创造能力.
- 需要道德框架来平衡人工智能增强与创造性解决问题的人类代理.
- 调查结果为关于有效的人类-人工智能协作和创意发展的未来的辩论提供了信息.
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