Tech giants like Meta, Google, and X are investing heavily in AI tools designed to detect fake news. It sounds reassuring, but according to a new study from the Université de Montréal, these tools have some serious drawbacks hiding behind impressive-sounding accuracy numbers.
Doctoral researcher Dorsaf Sallami examined AI fake news detection systems and found that they don’t actually fact-check anything. They calculate probabilities based on their training data. Think of it less like a journalist verifying a story and more like a mirror reflecting whatever it is shown, including the same biases and blind spots.
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According to Dorsaf Sallami, a system that scores 95% accuracy in a lab setting can still fail in the real world, and that gap is a serious problem.
The bias problem nobody is talking about
Beyond accuracy, Sallami found that many of these systems carry embedded biases that largely
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