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TOWARD HYBRID TEAMS: A PLATFORM TO UNDERSTAND HUMAN-COMPUTER COLLABORATION DURING THE DESIGN OF COMPLEX ENGINEERED SYSTEMS

Part of: Human Behaviour and Design

Published online by Cambridge University Press:  11 June 2020

B. Song ,
N. F. Soria Zurita ,
G. Zhang ,
G. Stump ,
C. Balon ,
S. W. Miller ,
M. Yukish ,
J. Cagan  and
C. McComb
B. Song
Affiliation:
The Pennsylvania State University, United States of America
N. F. Soria Zurita
Affiliation:
The Pennsylvania State University, United States of America Universidad San Francisco de Quito, Ecuador
G. Zhang
Affiliation:
Carnegie Mellon University, United States of America
G. Stump
Affiliation:
The Pennsylvania State University, United States of America
C. Balon
Affiliation:
The Pennsylvania State University, United States of America
S. W. Miller
Affiliation:
The Pennsylvania State University, United States of America
M. Yukish
Affiliation:
The Pennsylvania State University, United States of America
J. Cagan
Affiliation:
Carnegie Mellon University, United States of America
C. McComb*
Affiliation:
The Pennsylvania State University, United States of America
*
*[email protected]

Abstract

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Human-computer hybrid teams can meet challenges in designing complex engineered systems. However, the understanding of interaction in the hybrid teams is lacking. We review the literature and identify four key attributes to construct design research platforms that support multi-phase design, hybrid teams, multiple design scenarios, and data logging. Then, we introduce a platform for unmanned aerial vehicle (UAV) design embodying these attributes. With the platform, experiments can be conducted to study how designers and intelligent computational agents interact, support, and impact each other.

Keywords

collaborative designartificial intelligence (AI)design teamsresearch methodologies and methods
Type
Article
Information
Proceedings of the Design Society: DESIGN Conference , Volume 1 , May 2020 , pp. 1551 - 1560
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2020. Published by Cambridge University Press

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