人类-人工智能金融咨询中的信任形成,错误影响和修复:动态行为分析
1Research Institute of Human Ecology, Seoul National University, Seoul 08826, Republic of Korea.
Behavioral sciences (Basel, Switzerland)
|October 29, 2025
概括
人工智能 (AI) 的信任在可预测的阶段演变:最初的欣赏,错误后的急剧下降,以及带有解释的恢复. 财务素养影响了这些信任动态.
科学领域:
- 人与计算机的交互
- 人工智能伦理学 人工智能伦理学
- 认知心理学 认知心理学
背景情况:
- 了解对人工智能 (AI) 信任的时间演变对于AI的采用至关重要.
- 现有的研究主要集中在最初的AI接受上,忽视了随着时间的推移的信任动态.
- 人工智能信任动态需要一个框架,包括形成,错误影响和修复.
研究的目的:
- 开发和测试人工智能的时间信任动态框架.
- 调查人工智能信任的各个阶段:形成,错误冲击和后错误修复.
- 检查解释和财务素养在人工智能信任恢复中的作用.
主要方法:
- 在金融咨询环境中进行了两项实验.
- 第1项研究 (N=189) 对人类与算法顾问的信任进行了比较.
- 第二项研究 (N=294) 在三个交互回合中操纵了准确性和后错误解释.
主要成果:
- 参与者最初表现出"算法欣赏",偏爱人工智能顾问.
- 单个人工智能错误导致信任大幅下降,表明对故障的高度敏感性.
- 错误后的解释有助于恢复信任,有时超过初始水平.
- 金融素养缓解了信任的下降和复苏,更高的专业知识导致了更明显的变化.
结论:
- 人工智能信任表现出明显的时间模式,与人际信任不同.
- 人工智能信任对错误非常敏感,但可以通过有效的解释来修复.
- 结果为设计人工智能系统提供了实际指导,以培养和保持用户信任.
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