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contributor authorXu, Zeda
contributor authorHong, Chloe Soohwa
contributor authorSoria Zurita, Nicolás F.
contributor authorGyory, Joshua T.
contributor authorStump, Gary
contributor authorNolte, Hannah
contributor authorCagan, Jonathan
contributor authorMcComb, Christopher
date accessioned2024-04-24T22:41:54Z
date available2024-04-24T22:41:54Z
date copyright2/1/2024 12:00:00 AM
date issued2024
identifier issn1050-0472
identifier othermd_146_8_081401.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4295704
description abstractExploring the opportunities for incorporating Artificial Intelligence (AI) to support team problem-solving has been the focus of intensive ongoing research. However, while the incorporation of such AI tools into human team problem-solving can improve team performance, it is still unclear what modality of AI integration will lead to a genuine human–AI partnership capable of mimicking the dynamic adaptability of humans. This work unites human designers with AI Partners as fellow team members who can both reactively and proactively collaborate in real-time toward solving a complex and evolving engineering problem. Team performance and problem-solving behaviors are examined using the HyForm collaborative research platform, which uses an online collaborative design environment that simulates a complex interdisciplinary design problem. The problem constraints are unexpectedly changed midway through problem-solving to simulate the nature of dynamically evolving engineering problems. This work shows that after the unexpected design constraints change, or shock, is introduced, human–AI hybrid teams perform similarly to human teams, demonstrating the capability of AI Partners to adapt to unexpected events. Nonetheless, hybrid teams do struggle more with coordination and communication after the shock is introduced. Overall, this work demonstrates that these AI design partners can participate as active partners within human teams during a large, complex task, showing promise for future integration in practice.
publisherThe American Society of Mechanical Engineers (ASME)
titleAdaptation Through Communication: Assessing Human–Artificial Intelligence Partnership for the Design of Complex Engineering Systems
typeJournal Paper
journal volume146
journal issue8
journal titleJournal of Mechanical Design
identifier doi10.1115/1.4064490
journal fristpage81401-1
journal lastpage81401-16
page16
treeJournal of Mechanical Design:;2024:;volume( 146 ):;issue: 008
contenttypeFulltext


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