In this research paper we explore the role of Generative Large Language Models (Gen-LLMs) in supporting the product design process, moving beyond their conventional application as mere brainstorming assistants. Through an automated review of 15,355 design-related scientific articles, we identify and classify language-based tasks Gen-LLMs can enhance across various stages of product design. Employing a novel methodological approach that combines Named Entity Recognition with qualitative task classification, we classify these tasks into three primary functions: generation, evaluation, and description, subsequently mapping them to the corresponding phases of the design process: Problem Definition, Conceptual Design, Embodiment Design, and Detailed Design. Our findings reveal that while the generative capabilities of Gen-LLMs have been the primary focus, their potential to augment evaluative and descriptive tasks is significant and underexplored. By highlighting the diverse applications of Gen-LLMs, this study challenges the existing research and practice paradigm, advocating for a broader exploration of Gen-LLMs' capabilities. It underscores the necessity of balancing automation with human-centric design values and proposes a research agenda for further integrating Gen-LLMs into design practices, thus enriching both the theoretical and practical aspects.

How can Generative LLMs support Designers? Escaping the “Brainstorming Assistant” Fixation

filippo chiarello
;
vito giordano
2024-01-01

Abstract

In this research paper we explore the role of Generative Large Language Models (Gen-LLMs) in supporting the product design process, moving beyond their conventional application as mere brainstorming assistants. Through an automated review of 15,355 design-related scientific articles, we identify and classify language-based tasks Gen-LLMs can enhance across various stages of product design. Employing a novel methodological approach that combines Named Entity Recognition with qualitative task classification, we classify these tasks into three primary functions: generation, evaluation, and description, subsequently mapping them to the corresponding phases of the design process: Problem Definition, Conceptual Design, Embodiment Design, and Detailed Design. Our findings reveal that while the generative capabilities of Gen-LLMs have been the primary focus, their potential to augment evaluative and descriptive tasks is significant and underexplored. By highlighting the diverse applications of Gen-LLMs, this study challenges the existing research and practice paradigm, advocating for a broader exploration of Gen-LLMs' capabilities. It underscores the necessity of balancing automation with human-centric design values and proposes a research agenda for further integrating Gen-LLMs into design practices, thus enriching both the theoretical and practical aspects.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/1282527
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