Research co-authored by Wharton professors Gideon Nave and Christian Terwiesch finds that while ChatGPT improves the quality of individual ideas, it also leads groups to generate more similar ideas.
2 min. read
As more companies look to tools like ChatGPT to supercharge creativity, a recent study out of the Wharton School offers a word of caution: Generative AI may boost the quality of individual ideas but often times hurts the novelty and diversity of the ideas generated. When considered one at a time, the AI generated ideas are good and often great. But when considering a pool of ideas created by AI, the ideas fall short in originality and are too similar to each other.
Christian Terwiesch, co-director of Wharton’s Mack Institute,explains, “That points to a trade-off to be aware of: If you rely on ChatGPT as your only creative advisor, you’ll soon run out of ideas, because they’re too similar to each other.”
The study extends earlier experiments that found that participants using ChatGPT during creative tasks produced more original and useful ideas, outperforming both unaided individuals and those using search engines.
When Terwiesch and co-authors Wharton professor Gideon Nave and Mack Institute research fellow Lennart Meincke reanalyzed the data from these experiments, however, they found that participants using the chatbot were more likely to produce overlapping responses, often using strikingly similar language.
By contrast, the human-only group generated entirely unique ideas. In fact, just 6% of the AI-generated ideas were considered unique, compared with 100% in the human group.
These findings have important implications for businesses. In functions like product development, marketing, and strategy, success often depends on generating a wide range of strong ideas to tackle problems from different angles.
“Diversity is often overlooked,” says Terwiesch. “If you don’t solve for it explicitly, you won’t get it.”
One technique the researchers highlight is “chain-of-thought prompting,” a method that breaks a task into smaller, structured steps. This can increase the diversity of ideas and reduce repetition, says Terwiesch.
Meincke adds that starting with customer needs and pain points identified in human ideas may help teams move in different directions before introducing AI. He also suggests using multiple AI models to inject greater variety into the brainstorming process.
The paper arrives as generative AI moves deeper into business workflows, not just for writing and coding but also for creative tasks like ideation, product naming, and brand development.
Still, the researchers caution against mistaking fluency for originality. The best ideas may still be born from disagreement, divergence, and a bit of creative mess.
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