混合人工智能团队的敏捷新研究框架:信任、透明度和可转移性

IF 4.3 3区 材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC ACS Applied Electronic Materials Pub Date : 2022-07-26 DOI:https://dl.acm.org/doi/10.1145/3514257
Sabrina Caldwell, Penny Sweetser, Nicholas O’Donnell, Matthew J. Knight, Matthew Aitchison, Tom Gedeon, Daniel Johnson, Margot Brereton, Marcus Gallagher, David Conroy
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引用次数: 0

摘要

我们提出了一个新的研究框架,通过该框架,可以在实验环境中探索人类-人工智能团队的新兴学科,为转移到现实环境做准备。我们通过敏捷方法的视角来研究现有的文献和未解决的研究问题,以构建我们提出的框架。我们的框架旨在为理解这一研究领域的宏观特征提供一个结构,支持对人类团队成员和人工智能团队成员的可接受性进行整体研究。该框架有可能提高人类-人工智能混合团队的决策和绩效。此外,我们的框架建议将敏捷方法应用于研究管理和知识发现。我们提出了一种混合团队的可转移性途径,首先在安全的环境中进行测试,例如实时战略视频游戏,其中的经验教训元素可以转移到现实世界的情况中。
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An Agile New Research Framework for Hybrid Human-AI Teaming: Trust, Transparency, and Transferability

We propose a new research framework by which the nascent discipline of human-AI teaming can be explored within experimental environments in preparation for transferal to real-world contexts. We examine the existing literature and unanswered research questions through the lens of an Agile approach to construct our proposed framework. Our framework aims to provide a structure for understanding the macro features of this research landscape, supporting holistic research into the acceptability of human-AI teaming to human team members and the affordances of AI team members. The framework has the potential to enhance decision-making and performance of hybrid human-AI teams. Further, our framework proposes the application of Agile methodology for research management and knowledge discovery. We propose a transferability pathway for hybrid teaming to be initially tested in a safe environment, such as a real-time strategy video game, with elements of lessons learned that can be transferred to real-world situations.

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CiteScore
7.20
自引率
4.30%
发文量
567
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