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在人类-人工智能合作中促进集体智能:为COHUMAININ奠定基础
Pranav Gupta1, Thuy Ngoc Nguyen2, Cleotilde Gonzalez2
1Gies College of Business, University of Illinois, Urbana-Champaign.
Topics in cognitive science
|June 29, 2023
概括
这项研究提出了集体人机智能 (COHUMAIN) 来理解复杂的人机智能系统如何实现集体智能. 它呼吁跨学科的研究来设计社会技术系统,以加强人机协作.
科学领域:
- 社会技术系统 社会技术系统
- 人工智能的人工智能
- 集体情报是一种集体情报.
背景情况:
- 人机交互越来越多地由人工智能调解,但理解这些复杂系统中的集体智能仍然是一个挑战.
- 现有的研究是孤立的,低估了社会或技术方面的方面.
- 弥合学科差距对于推进人类-人工智能协作研究至关重要.
研究的目的:
- 倡导建立集体人机智能 (COHUMAIN) 作为一个跨学科的研究领域.
- 概述一个研究议程,为设计社会技术系统采取整体方法.
- 提出社会认知架构,以理解和增强人类人工智能系统中的集体智能.
主要方法:
- 开发一种社会认知架构,即交易系统模型,以表达集体智能的过程.
- 将交易系统模型扩展到人-人工智能系统.
- 整合基于实例的学习理论来设计与人类合作的AI代理.
主要成果:
- 交易系统模型为理解人类-人工智能系统中的集体智能提供了一个框架.
- 基于实例的学习理论为AI代理设计提供了一个兼容的认知架构.
- 最近的工作证明了这些模型在人类-人工智能协作中的应用.
结论:
- 建立COHUMAIN对于释放人类机器智能的全部潜力至关重要.
- 需要一个整体的,跨学科的方法来设计有效的社会技术系统.
- 鼓励进一步开发社会认知架构,以推进该领域的研究.
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