A new Canadian study, comparing more than 100,000 people with today’s most advanced AI systems, delivers a surprising result: generative AI can now beat the average human on certain creativity tests.
Models like GPT-4 showed strong performance on tasks designed to measure original thinking and idea generation, sometimes outperforming typical human responses.
Before people begin worrying too much about an AI takeover, there remains a clear ceiling. The most creative humans — especially the top 10% — still leave AI well behind, particularly on richer creative work like poetry and storytelling.
Scientists from the University of Montreal contend that generative AI systems have now reached a level where they can outperform the average human on certain creativity measures.
At the same time, the most creative people still show a clear and consistent advantage over even the strongest AI models.
To derive at these findings researchers evaluated several leading large language models, including ChatGPT, Claude, Gemini, and others, and compared their performance with results from more than 100,000 human participants.
Methods
To evaluate creativity fairly across humans and machines, the research team used multiple methods. The primary tool was the Divergent Association Task (DAT), a widely used psychological test that measures divergent creativity, or the ability to generate diverse and original ideas from a single prompt.
Research findings highlight a clear turning point
Some AI systems, including GPT-4, exceeded average human scores on tasks designed to measure divergent linguistic creativity.
“Our study shows that some AI systems based on large language models can now outperform average human creativity on well-defined tasks,” explains Professor Karim Jerbi in a research brief. “This result may be surprising — even unsettling — but our study also highlights an equally important observation: even the best AI systems still fall short of the levels reached by the most creative humans.”
Further analysis revealed a striking pattern. While some AI models now outperform the average person, peak creativity remains firmly human.
Moreover, when researchers examined the most creative half of participants, their average scores surpassed those of every AI model tested. The gap grew even larger among the top 10 percent of the most creative individuals.
Interpretation
The researchers then explored whether AI success on this simple word association task could extend to more complex and realistic creative activities. To test this, they compared AI systems and human participants on creative writing challenges such as composing haiku (a short three-line poetic form), writing movie plot summaries, and producing short stories.
The results followed a familiar pattern. While AI systems sometimes exceeded the performance of average humans, the most skilled human creators consistently delivered stronger and more original work.
What next for AI?
These findings raise an important question. Is AI creativity fixed, or can it be shaped? The study shows that creativity in AI can be adjusted by changing technical settings, particularly the model’s temperature. This parameter controls how predictable or adventurous the generated responses are.
At lower temperature settings, AI produces safer and more conventional outputs. At higher temperatures, responses become more varied, less predictable, and more exploratory, allowing the system to move beyond familiar ideas.
It was also demonstrated that creativity is strongly influenced by how instructions are written. For example, prompts that encourage models to think about word origins and structure using etymology lead to more unexpected associations and higher creativity scores.
These results emphasise that AI creativity depends heavily on human guidance, making interaction and prompting a central part of the creative process.
The research appears in the journal Scientific Reports, titled “Divergent creativity in humans and large language models.”
