Ceci N'est Pas un Drone: Investigation of the Impact of Design Representation on Design Decision-Making When Considering AI-Generated Designs

Abstract With generative AI-powered design tools, designers and engineers can efficiently generate large numbers of design ideas. However, efficient exploration of these ideas requires engineers and designers to select a smaller group of potential solutions for further development. Therefore, the ability to judge and evaluate designs is critical for the successful use of generative design tools. Different design representation modalities can potentially affect engineering designers' judgments. This work investigates how different design modalities, including visual rendering, numerical performance data, and a combination of both, affect designers' design selections from AI-generated design concepts for Uncrewed Aerial Vehicles. We found that different design modalities do affect participants' choices when presented with AI-generated design solutions. We also found that providing only numerical design performance data can lead to the best ability to select numerically optimal designs in the design problem examined in the study. Additionally, we found that participants prefer visually conventional designs with axis-symmetry when provided visual renderings. The findings of this work provide insights into the interaction between human users and generative engineering design systems.