Chatbots can persuade people to stop believing in conspiracy theories

After each conversation, participants were asked the same rating questions. The researchers followed up with all the participants 10 days after the experiment, and then two months later, to assess whether their views had changed following the conversation with the AI bot. The participants reported a 20% reduction of belief in their chosen conspiracy theory on average, suggesting that talking to the bot had fundamentally changed some people’s minds.

“Even in a lab setting, 20% is a large effect on changing people’s beliefs,” says Zhang. “It might be weaker in the real world, but even 10% or 5% would still be very substantial.”

The authors sought to safeguard against AI models’ tendency to make up information—known as hallucinating—by employing a professional fact-checker to evaluate the accuracy of 128 claims the AI had made. Of these, 99.2% were found to be true, while 0.8% were deemed misleading. None were found to be completely false. 

One explanation for this high degree of accuracy is that a lot has been written about conspiracy theories on the internet, making them very well represented in the model’s training data, says David G. Rand, a professor at MIT Sloan who also worked on the project. The adaptable nature of GPT-4 Turbo means it could easily be connected to different platforms for users to interact with in the future, he adds.

“You could imagine just going to conspiracy forums and inviting people to do their own research by debating the chatbot,” he says. “Similarly, social media could be hooked up to LLMs to post corrective responses to people sharing conspiracy theories, or we could buy Google search ads against conspiracy-related search terms like ‘Deep State.’”

The research upended the authors’ preconceived notions about how receptive people were to solid evidence debunking not only conspiracy theories, but also other beliefs that are not rooted in good-quality information, says Gordon Pennycook, an associate professor at Cornell University who also worked on the project. 

“People were remarkably responsive to evidence. And that’s really important,” he says. “Evidence does matter.”