Using Large Language Models for Idea Generation in Innovation
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摘要
This study tests whether GPT-4 can outperform humans in generating high-quality new-product ideas aimed at college students at a $50 price cap. Across three pools (student ideas, GPT-4 zero-shot, GPT-4 few-shot), AI-generated ideas show higher average purchase intent, with few-shot prompting performing best [page::12]. However, AI ideas are perceived as less novel and more similar to each other, indicating a narrower solution landscape [page::16][page::17][page::15]. Importantly, AI-generated ideas dominate the top decile, being about seven times more likely to appear in the top 10% than human ideas, underscoring substantial value in AI-driven ideation for high-quality outputs [page::3][page::19]. The results imply a productivity premium for AI in ideation and a potential shift toward idea evaluation and AI-human collaboration to maintain diversity and novelty [page::3][page::21].
