Decoding the agility of artificial intelligence- assisted human design teams

被引:21
|
作者
Song, Binyang [1 ]
Gyory, Joshua T.
Zhang, Guanglu
Zurita, Nicolas F. Soria [1 ]
Stump, Gary [3 ]
Martin, Jay [3 ]
Miller, Simon [3 ]
Balon, Corey [3 ]
Yukish, Michael [3 ]
McComb, Christopher [2 ]
Cagan, Jonathan [2 ]
机构
[1] Penn State Univ, Sch Engn Design Technol, Profess Programs, Pennsylvania, PA 16802 USA
[2] Carnegie Mellon Univ, Dept Mech Engn, Pittsburgh, PA 15213 USA
[3] Penn State Univ, Appl Res Lab, Pennsylvania, PA 16802 USA
关键词
artificial intelligence; collaborative design; engineering design; hu-manecomputer interaction; complex problem solving; ORGANIZATIONAL AGILITY; FUTURE; COMMUNICATION; TECHNOLOGIES; PERFORMANCE; ENTERPRISE; COMPLEXITY; AL;
D O I
10.1016/j.destud.2022.101094
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Although necessary for complex problem solving, such as engineering design, team agility is often difficult to achieve in practice. The evolution of Artificial Intelligence (AI) affords unique opportunities for supporting team problem solving. While integrating assistive AI agents into human teams has at times improved team performance, it is still unclear if, how, and why AI affects team agility. A large-scale human experiment answers these questions, revealing that, with appropriately interfaced AIs, AI-assisted human teams enjoy improved coordination and communications, leading to better performance and adaptations to team disruptions, while devoting more effort to information handling and exploring the solution space more broadly. In sum, working with AI enables human team members to think more and act less. (c) 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-ncnd/4.0/).
引用
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页数:33
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