人类什么时候会听从人工智能代理人的建议? 什么时候应该这样做?
Richard E Dunning1, Baruch Fischhoff1, Alex L Davis1
1Carnegie Mellon University, Pittsburgh, PA, USA.
Human factors
|August 8, 2023
概括
人类依赖人工智能 (AI) 建议是有效的人类-AI合作的关键. 使用人工智能代理的用户性能取决于人工智能.
科学领域:
- 人与计算机的互动.
- 人工智能的人工智能是人工智能.
- 认知科学是一种认知科学.
背景情况:
- 人与人工智能之间的协作决策在许多应用中很普遍.
- 人类对人工智能代理的有效依赖对于成功的人类-人工智能合作至关重要.
- 在协作任务中评估人工智能代理的性能需要了解用户交互.
研究的目的:
- 调查人工智能 (AI) 推技能和显示格式对战略游戏中用户表现的影响.
- 根据AI的技能水平,确定用户对AI代理的依赖程度如何变化.
- 评估一种用于评估人类-人工智能协作平台的实验方法.
主要方法:
- 在使用策略游戏 (Connect Four) 进行了2x3对象之间的因数实验.
- 独立变量包括人工智能推格式 (分类与概率) 和人工智能代理人培训水平 (低,中,高).
- 参与者提出了动作,接受了AI建议,然后在10场比赛中进行了最后的动作.
主要成果:
- 使用高技能的人工智能代理提高了用户性能,但导致了不关键的依赖和性能高原.
- 用户表现出对技术较低的人工智能代理的依赖不足.
- 人工智能建议的格式 (分类或概率) 并没有显著影响用户的技能或选择.
结论:
- 人工智能代理人在协作任务中的有效性取决于人工智能的技能水平和用户从其建议中学习的能力.
- 对于实施人工智能决策支持系统的组织来说,了解人类-人工智能团队的行为动态至关重要.
- 该研究提供了一种方法来评估不同的AI设计,并评估它们在人类-AI合作中的表现.
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