AI-Assisted Bioinspired Design: Evaluating the Effectiveness of Directed Intuition in LLM Outputs

Bio-inspired design is a well-established approach for generating creative ideas, and recent advances in large language models (LLMs) offer new opportunities for exploring such designs. Many studies have developed complex frameworks to integrate LLMs with bio-inspired design. One of the simplest methods a designer may use when first exploring bio-inspired design is through the directed intuitive approach, which instructs the designer to consider how nature might solve a given problem. While prior research has studied the impact of the directed intuitive method on human solutions, its effect on LLM-generated solutions remains unclear. This study investigates whether the directed intuitive method can lead to more effective LLM-generated solutions and whether the solutions are comparable to human created solutions. A 2 × 2 × 2 factorial experiment was conducted, combining LLM and human responses with directed intuitive instructions. Results show that directing LLMs to “consider nature” increases the novelty and variety of generated solutions, though LLMs still produced fewer novel ideas than humans. No significant differences were observed between human and LLM solutions in terms of variety and quality.