较低级别的人类类型的代理商更值得信赖,在人类自主团队中更少受到指责
Jody Gall1, Christopher J Stanton1
1The MARCS Institute for Brain Behaviour and Development, Western Sydney University, Parramatta, NSW, Australia.
Frontiers in artificial intelligence
|May 14, 2024
概括
设计人工队友需要仔细考虑信任和问责制. 较高的人形化和较低级别的代理人提高了信任和共同责任,导致人类接受更多的失败责任.
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
- 团队合作 动态 团队工作
背景情况:
- 设计有效的人类自主团队 (HAT) 需要了解影响信任和共同问责制的因素.
- 人工智能被整合到人类团队中,引发了关于责任和可靠性的关键问题.
- 之前的研究还没有充分探索代理设计特征和人类对信任和责怪的看法之间的相互作用.
研究的目的:
- 调查人类形象,等级,决策成本和任务难度如何影响对HAT的信任.
- 为了检查当人类和人工智能之间的共同任务失败时,责任是如何分配的.
- 探索个人权力距离导向对信任和责怪归属的影响.
主要方法:
- 一个在主体内部的设计实验,使用模拟的空中交通控制游戏与31名参与者.
- 操纵代理人人形 (人形与机器形) 和军事等级 (上级,同级,下级).
- 行为信任指标 (建议的接受/拒绝) 和一个责任分配尺度,用后勤回归和ANOVA分析.
主要成果:
- 较高水平的代理人形象主义显著增加了对人工队友的信任.
- 人工代理人的较低的感知等级也导致了信任和共同问责制的增加.
- 参与者在与表现出更高的人类形象和较低等级的代理人合作时,对团队失败承担了更多的责任.
结论:
- 代理设计特征,特别是人形和等级,对于培养信任和在HAT.中分享责任至关重要.
- 了解这些设计元素可以优化人与代理之间的协作,提高团队的表现.
- 未来的研究应该继续探索越来越复杂的人类-人工智能伙伴关系中信任和责怪的细微差别.
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