Crowdsourcing from a group of 1,128 of users, researchers were able to segment groups as small as 10 individuals online that could accurately determine whether or not an article was false—about as well as professional fact-checkers. Supplemented by algorithms, a system like this could be trained to identify fake news at the speed and scale in which it spreads.
Furthermore, open-sourcing these methods of verification so they are auditable and transparent enough to be easily understood might help ease claims of bias and censorship. An early attempt at this can be seen in Twitter’s Birdwatch, which leverages the community to flag misinformation tweets; the system is new and imperfect, and there are clearly ways that it can be gamed (a problem for any verification system), but it’s an important first attempt.
But Who Determines Truth?
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Source: How to Stop Misinformation’s Spread Before It’s Even Shared | WIRED