从人类团队到混合情报团队:识别,描述和评估基本的质量属性
Davide Dell'Anna1, Pradeep K Murukannaiah2, Mireia Yurrita1
1Utrecht University, Utrecht, The Netherlands.
Autonomous agents and multi-agent systems
|February 23, 2026
概括
混合智能 (HI) 系统需要一个高质量的模型来建立有效的人类-AI团队. 本研究确定了设计和评估HI的关键人力团队属性,为其开发提供了新的框架.
科学领域:
- 计算机科学 计算机科学
- 人与计算机的交互
- 人工智能的人工智能
背景情况:
- 混合智能 (HI) 集成人工智能 (AI) 来增强人类的能力.
- 现有的文献缺乏用于HI系统设计和评估的系统模型.
- 当前的讨论往往忽略了人类-人工智能组合,主要关注技术.
研究的目的:
- 从人类-人工智能团队的角度开发一个质量模型来描述和评估HI系统.
- 研究人类团队属性的适用于HI系统的可用性.
- 为HI的整体设计和评估提供框架.
主要方法:
- 对50名HI研究人员进行了一项研究,以评估人类团队特性对HI的相关性.
- 开发了HI团队的质量模型,其中包括七个高级别和16个特定的质量属性.
- 通过竞赛进行了第二次经验调查,参与者将质量模型应用于HI场景.
主要成果:
- 人类团队的属性,如局限性,相互依赖性,能力,有目的性,主动性,规范性和有效性对于HI系统很重要.
- 开发的质量模型包括七个高级别和16个特定属性,经经验评估证实了其相关性.
- 对48个HI使用场景的分析强调了在系统设计过程中应用质量模型所获得的见解.
结论:
- 为混合智能团队建立了一个新的质量模型,以人类团队属性为基础.
- 该模型为设计和评估HI系统提供了一个结构化的方法,强调了人类-AI协作.
- 这些发现为研究人员和设计人员提供了实际指导,旨在创建有效的HI系统.
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