TY - GEN
T1 - Addressing challenges to problem complexity
T2 - 33rd International Conference on Design Theory and Methodology, DTM 2021, Held as Part of the ASME 2021 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC-CIE 2021
AU - Song, Binyang
AU - Soria Zurita, Nicolás F.
AU - Nolte, Hannah
AU - Singh, Harshika
AU - Cagan, Jonathan
AU - McComb, Christopher
N1 - Publisher Copyright:
Copyright © 2021 by ASME.
PY - 2021
Y1 - 2021
N2 - As Artificial Intelligence (AI) assistance tools become more ubiquitous in engineering design, it becomes increasingly necessary to understand the influence of AI assistance on the design process and design effectiveness. Previous work has shown the advantages of incorporating AI design agents to assist human designers. However, the influence of AI assistance on the behavior of designers during the design process is still unknown. This study examines the differences in participants' design process and effectiveness with and without AI assistance during a complex drone design task using the HyForm design research platform. Data collected from this study is analyzed to assess the design process and effectiveness using quantitative methods, such as Hidden Markov Models and network analysis. The results indicate that AI assistance is most beneficial when addressing moderately complex objectives but exhibits a reduced advantage in addressing highly complex objectives. During the design process, the individual designers working with AI assistance employ a relatively explorative search strategy, while the individual designers working without AI assistance devote more effort to parameter design.
AB - As Artificial Intelligence (AI) assistance tools become more ubiquitous in engineering design, it becomes increasingly necessary to understand the influence of AI assistance on the design process and design effectiveness. Previous work has shown the advantages of incorporating AI design agents to assist human designers. However, the influence of AI assistance on the behavior of designers during the design process is still unknown. This study examines the differences in participants' design process and effectiveness with and without AI assistance during a complex drone design task using the HyForm design research platform. Data collected from this study is analyzed to assess the design process and effectiveness using quantitative methods, such as Hidden Markov Models and network analysis. The results indicate that AI assistance is most beneficial when addressing moderately complex objectives but exhibits a reduced advantage in addressing highly complex objectives. During the design process, the individual designers working with AI assistance employ a relatively explorative search strategy, while the individual designers working without AI assistance devote more effort to parameter design.
KW - Artificial intelligence
KW - Design behavior
KW - Design exploration
KW - Engineering design
KW - Problem solving
UR - http://www.scopus.com/inward/record.url?scp=85119969728&partnerID=8YFLogxK
U2 - 10.1115/DETC2021-70467
DO - 10.1115/DETC2021-70467
M3 - Contribución a la conferencia
AN - SCOPUS:85119969728
T3 - Proceedings of the ASME Design Engineering Technical Conference
BT - 33rd International Conference on Design Theory and Methodology (DTM)
PB - American Society of Mechanical Engineers (ASME)
Y2 - 17 August 2021 through 19 August 2021
ER -