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The paper explores the impact of Large Language Models (LLMs) on human creativity through two large pre-registered parallel experiments involving 1,100 participants. The study compares the effects of two forms of LLM assistance—a standard LLM providing direct answers and a coach-like LLM offering guidance—with a control group receiving no AI assistance. The focus is on how these forms of assistance affect unassisted human creativity in tasks targeting divergent and convergent thinking. The findings suggest that while LLM assistance can provide short-term boosts in creativity during assisted tasks, it may inadvertently hinder independent creative performance when users work without assistance, raising concerns about the long-term impact on human creativity and cognition.
Impact of LLMs on Creativity
The study investigates how LLMs influence divergent and convergent thinking, two core components of creativity. Divergent thinking involves generating multiple, unique ideas, while convergent thinking focuses on refining these ideas to select the most effective solutions.
Experimental Design
The experiments compare the effects of standard LLM assistance, coach-like LLM guidance, and no assistance on participants' creative performance. Participants engaged in a series of exposure rounds with different forms of LLM assistance, followed by a final unassisted test round to measure the impact on independent creative performance.
Findings
- Divergent Thinking: LLM assistance did not enhance participants' originality or fluency in subsequent unassisted tasks. In some cases, it led to decreased originality and reduced diversity of ideas, suggesting a potential homogenization effect.
- Convergent Thinking: While LLM assistance improved performance during assisted tasks, it did not translate into better performance in subsequent unassisted tasks. Participants who received guidance from LLMs performed worse in the unassisted test rounds compared to those with no prior LLM exposure.
Implications
The study provides empirical evidence that LLM assistance boosts performance during assisted tasks but may hinder independent creative performance in unassisted tasks. It highlights the differential impacts of LLMs on divergent and convergent thinking, with users showing skepticism toward LLM assistance in divergent tasks and beneficial effects in convergent tasks. The findings also reveal persistent homogenization effects due to LLM-generated strategies, posing challenges for designing effective LLM coaching systems.
Design Implications
The paper offers design implications for developing LLM-based tools that enhance human creativity without undermining independent creative abilities. It emphasizes the need for careful consideration of the long-term impact of LLM use on human creativity and cognition.
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