Comparing AIGC and traditional idea generation methods: Evaluating their impact on creativity in the product design ideation phase

Abstract

In the early stages of product design, generating creative ideas is crucial for designers as it lays the groundwork for innovative products. This study explores how different idea generation methods, including modern artificial intelligence-generated content (AIGC) and traditional approaches, affect designers' creativity. Using a mixed-methods approach, we conducted a detailed experiment with 38 s-year university students majoring in product design, comparing four methods: traditional brainstorming (with and without images) and AIGC (using DCGANs and PGGANs). Our findings indicate that while AIGC offers benefits, it does not consistently surpass traditional techniques in fostering creativity. The quality of AIGC-generated images significantly impacts creativity, with higher-quality images proving more inspirational. Additionally, gender differences were observed: male designers preferred traditional methods, while female designers favored AIGC for creative enhancement. Male designers generated more creative ideas when working with low-quality images, whereas female designers were more productive with high-quality stimuli. This study suggests that to optimize creativity in product design, it is essential to balance the benefits of both AIGC and traditional methods, choosing the approach that best fits the project's unique needs rather than focusing solely on the latest or most advanced methods. Moreover, maintaining a good balance between AIGC and traditional idea generation methods throughout the process should be considered.