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Machine learning algorithms significantly outperform human judgment in detecting lying during high-stakes strategic interactions, according to new research from the University of California San Diego's Rady School of Management.

The study can have major implications for the spread of misinformation, as machine learning could be used to bolster efforts to reduce fictitious content on major platforms like YouTube, Tik-Tok and Instagram.

The study, to be published in Management Science and available as a working paper, focused on participants' ability to detect lying on the popular British TV show "Golden Balls," which aired from 2007 to 2010. It finds that while humans struggle to predict contestants' deception behavior, algorithms perform much better.

"We find that there are certain 'tells' when a person is being deceptive," said Marta Serra-Garcia, lead author of the study and associate professor of behavioral economics at the UC San Diego Rady School of Management.

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