It is frequently argued that false and misleading claims, spread primarily on social media, are a serious problem in need of urgent response. Current strategies to address the problem – relying on fact-checks, source labeling, limits on the visibility of certain claims, and, ultimately, content removals – face two serious shortcomings: they are ineffective and biased. Consequently, it is reasonable to want to seek alternatives. This paper provides one: to address the problems with misinformation, social media platforms should abandon third-party (...) fact-checks and rely instead on user-driven prediction markets. This solution is likely less biased and more effective than currently implemented alternatives and, therefore, constitutes a superior way of tackling misinformation. (shrink)

It is frequently argued that false and misleading claims, spread primarily on social media, are a serious problem in need of urgent response. Current strategies to address the problem – relying on fact-checks, source labeling, limits on the visibility of certain claims, and, ultimately, content removals – face two serious shortcomings: they are ineffective and biased. Consequently, it is reasonable to want to seek alternatives. This paper provides one: to address the problems with misinformation, social media platforms should abandon third-party (...) fact-checks and rely instead on user-driven prediction markets. This solution is likely less biased and more effective than currently implemented alternatives and, therefore, constitutes a superior way of tackling misinformation. (shrink)