When Faced With Increasing Complexity: The Effectiveness of Artificial Intelligence Assistance for Drone Design
Abstract
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 are 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.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Sep 09, 2021
- Source ID
- 10.1115/1.4051871
Entities
People
- Binyang Song
- Christopher McComb
- Hannah Nolte
- Harshika Singh
- Jonathan Cagan
- Nicolás F. Soria Zurita
Organizations
- Carnegie Mellon University
- Defense Advanced Research Projects Agency
- Pennsylvania State University
- Polytechnic University of Milan
- University of San Francisco