Author(s)

Kaiwei Zhu, Yawei Wang

Corresponding Author

Kaiwei Zhu

Abstract

Based on the perspective of design cognition theory, this paper deeply studies the internal mechanism and effectiveness of AI-assisted creative generation. Integrating core principles of design cognitive theory, assessing the current status of AI technology in creative generation, and exploring the collaborative dynamics between AI and human designers in the creative process. It builds an effectiveness evaluation system that includes efficiency, quality, user experience, and business value, and combines empirical analysis with multi-field case studies. Research has found that AI can significantly improve the efficiency of idea generation and optimize the design process. However, human designers still need to lead in creative depth and emotional expression. This study provides a theoretical basis for analyzing the role of AI in creative design. Additionally, it provides a reference for promoting the practice of human-machine collaborative innovation in the design industry. Research has confirmed that AI is an "efficiency extension tool" for design cognition rather than a substitute. Its core value lies in liberating repetitive labor and expanding the boundaries of data processing. Humans still play a crucial role in the emotional depth of creativity, cultural narratives, and value judgments. In the design industry, it is essential to broaden the use of AI for large-scale tasks while also enhancing the leadership of designers in areas like artistic creation. Future research needs to pay further attention to AI ethics, cross-domain collaborative differences, and designers' technical literacy to promote the evolution of creative design towards an innovative ecosystem.

Keywords

Design Cognitive Theory; AI-Assisted Creative Generation; Human-Computer Collaboration; Creative Effectiveness; Design Cognition Mechanism; User Experience; Creative Quality; Design Innovation