A Framework for Collaborating a Large Language Model Tool in Brainstorming for Triggering Creative Thoughts
Hung-Fu Chang, Tong Li

TL;DR
This paper introduces the GPS framework that guides the use of Large Language Models like ChatGPT to enhance creativity during brainstorming, demonstrated through a design case study and adapted TTCT assessments.
Contribution
It proposes a novel framework combining goals, prompts, and strategies to systematically improve AI-assisted brainstorming for creative idea generation.
Findings
The framework effectively stimulates creative ideas in brainstorming sessions.
Integration of LLM tools enhances both creativity and usefulness of generated ideas.
The adapted TTCT measures confirm increased creativity in AI-generated ideas.
Abstract
Creativity involves not only generating new ideas from scratch but also redefining existing concepts and synthesizing previous insights. Among various techniques developed to foster creative thinking, brainstorming is widely used. With recent advancements in Large Language Models (LLMs), tools like ChatGPT have significantly impacted various fields by using prompts to facilitate complex tasks. While current research primarily focuses on generating accurate responses, there is a need to explore how prompt engineering can enhance creativity, particularly in brainstorming. Therefore, this study addresses this gap by proposing a framework called GPS, which employs goals, prompts, and strategies to guide designers to systematically work with an LLM tool for improving the creativity of ideas generated during brainstorming. Additionally, we adapted the Torrance Tests of Creative Thinking…
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Taxonomy
TopicsCreativity in Education and Neuroscience
MethodsGreedy Policy Search
