Ideas are Dimes a Dozen: Large Language Models for Idea Generation in Innovation

Abstract

Large language models (LLMs) such as OpenAI's GPT series have shown remarkable capabilities in generating fluent and coherent text in various domains. We compare the ideation capabilities of ChatGPT-4, a chatbot based on a state-of-the-art LLM, with those of students at an elite university. ChatGPT-4 can generate ideas much faster and cheaper than students, the ideas are on average of higher quality (as measured by purchase-intent surveys) and exhibit higher variance in quality. More important, the vast majority of the best ideas in the pooled sample are generated by ChatGPT and not by the students. Providing ChatGPT with a few examples of highly-rated ideas further increases its performance. We discuss the implications of these findings for the management of innovation.

Keywords: innovation, idea generation, creativity, creative problem solving, LLM, large-scale language models, AI, artificial intelligence, ChatGPT