通过定量认知了解对人工智能的信任维度:对人类-人工智能协作的影响
Weizheng Jiang1,2, Dongqin Li2, Chun Liu2
1School of Management, Wuhan University of Science and Technology, Wuhan, China.
PloS one
|July 2, 2025
概括
对人工智能 (AI) 的信任对人类-AI合作期间的认知有双重影响. 功能和情感信任可以促进更高层次的认知,而人工智能的透明度可以阻碍认知过程.
科学领域:
- 认知科学 认知科学
- 人与计算机的交互
- 组织行为 组织行为
背景情况:
- 对人类-人工智能协作创新的角色分配的实证研究是有限的.
- 了解对人工智能的信任机制对于有效的协作至关重要.
- 现有的框架并不完全捕捉到信任对认知的细微影响.
研究的目的:
- 开发一种对人工智能 (AI) 的认知分类法,以解释其在人类-AI 协作中的交互机制.
- 检查对人工智能的信任对不同认知水平的互补和抑制效应.
- 通过人工智能识别促进低级和高级认知的关键驱动因素.
主要方法:
- 在AI框架中构建了一个认知分类学信任.
- 从财务和商务管理实习生收集数据,使用调查和行动后审查方法.
- 使用梯度下降算法分析数据.
主要成果:
- 对人工智能的功能和情感信任增强了高级认知能力.
- 认知信任的透明度维度抑制了认知过程.
- 对人工智能的信任表现出对认知的互补和抑制影响.
结论:
- 对人工智能的信任对人类-人工智能协作中的认知过程有双重影响.
- 这些发现为理解对人工智能的信任提供了理论基础.
- 为大学与工业伙伴关系和知识创新提供实用指导.
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