(不) 完美的自动化方案:谁更值得信赖,自动化还是人类决策支持?
Tobias Rieger1, Luisa Kugler1, Dietrich Manzey1
1Technische Universität Berlin, Berlin, Germany.
Human factors
|August 26, 2023
概括
人类专家比人工智能 (AI) 或支持角色的新手更能培养更多的信任. 了解代理商的专业知识对于有效的人与代理商的互动和管理信任动态至关重要.
科学领域:
- 人与计算机的互动.
- 认知心理学 认知心理学
- 人工智能的人工智能是人工智能.
背景情况:
- 以前的研究表明,在人与代理互动中,有一个完美的自动化方案.
- 最近的研究提出了关于自动化信任的相互矛盾的证据.
- 这种模糊性需要进一步研究信任动态.
研究的目的:
- 研究人与代理互动中信任态度和行为的动态.
- 检查代理类型 (AI,专家,新手) 和失败经验对信任的影响.
- 澄清关于自动化信任体系的相互矛盾的发现.
主要方法:
- 一个在线实验使用模拟的医疗X射线任务进行.
- 代理人制 (人工智能,专家,新手) 在受试者之间被操纵.
- 失败经验 (完美,不完美,回归完美的支持) 在受试者内部被操纵.
- 信任态度,信任行为和感知到的可靠性被测量为依赖变量.
主要成果:
- 人类专家的信任态度和感知可靠性最高,其次是人工智能,然后是人类新手.
- 观察到的信任形成,解散和恢复的模式在各个代理商之间是一致的.
- 在代理类型之间没有发现失败经验后宽恕的显著差异.
结论:
- 这些发现支持存在一个不完美的自动化方案.
- 代理人的专业知识显著影响信任态度和感知到的可靠性.
- 考虑代理专业知识对于成功的人与代理互动至关重要,特别是当人工智能取代人类专家时.
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