Can AI Come Up With Better Ideas Than People? Sort Of, Science Says.

Need a great idea? Ask the masses. “Crowdsourcing” has become a popular way for companies to gather insights — because when you bring together people with diverse knowledge and approaches, you can find unexpected genius. But crowdsourcing is time-consuming and expensive. Could generative AI help? Researchers at Harvard Business School and the University of Washington’s Foster School of Business decided to find out.

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The research

The study set up a crowdsourcing challenge. The question was: “Who has ideas for how companies can implement the circular economy into their business to make them more climate-friendly?”

First, the researchers invited real people to submit their suggestions and ended up with 125 ideas. Next, the researchers prompted ChatGPT’s GPT-4 with the same question and slight variations, which produced 730 solutions.

All the ideas were reviewed by 300 human judges, who evaluated them based on novelty, value, and quality.

The results

The human-generated solutions were more novel, but in many ways, the AI-prompted concepts were better — higher quality, more strategically viable, with greater financial and environmental value.

As for the economics of the project, they were stark: To produce those 125 human submissions required a combined 2,520 hours of work — and $2,555 to cover expenses. But to get the 730 solutions from AI, it took just 5.5 hours and cost only $27.01.

Related: How Crowdsourcing Is Shaping the Future of Everything

What we’ve learned

Generative AI is great at generating ideas — but it can’t do it all on its own. To succeed, you need to give the tool very clear, thoughtful prompts, says study investigator Léonard Boussioux, an assistant professor at the University of Washington’s Foster School of Business who’s also affiliated with Harvard Business School.

In their experiment, he and his colleagues tried two distinct strategies. In the first, along with the challenge question, they asked GPT-4 to assume 100 different personas (executive, manager, entrepreneur) to replicate the variety of humans who might reply to a crowdsource request. In the second approach, they prompted the AI with the same question and got a first answer — and then followed it up by asking, “Make sure to tackle a different problem than the previous ones and propose a different solution.” They repeated this 100 times, with a different persona each time, as if it were one person pushed to give various perspectives.

The result: The second approach led to more novel, viable, and quality ideas.

How to use this

Let’s say your company is considering a pivot. “The quality of your questioning and critical thinking is what matters most,” Boussioux says. “But AI can help you find good starting questions. Describe your company, the stakeholders, your goals. Include as much data as you can — a blog post about what you do, financial spreadsheets, a white paper. Then ask something like, ‘I’m looking maybe to pivot. Can you suggest a direction to investigate?'” This can get you going.

Try iterative prompting, but don’t do it 100 times like the study did. “We found that if you keep asking for too long, the final ideas are potentially more creative, but they’re also not as feasible or valuable,” Boussioux says. The sweet spot? Two to four times.

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