Divergent Creativity in Humans and Large Language Models

Understand

The recent surge of Large Language Models (LLMs) has led to claims that they are approaching a level of creativity akin to human capabilities.

• This idea has sparked a blend of excitement and apprehension.
• However, a critical piece that has been missing in this discourse is a systematic evaluation of LLMs' semantic diversity, particularly in comparison to human divergent thinking.
• To bridge this gap, we leverage recent advances in computational creativity to analyze semantic divergence in both state-of-the-art LLMs and a substantial dataset of 100,000 humans.