Machine learning can't flag false news, new studies show

In one study, Schuster and team showed that machine learning-taught fact-checking systems struggled to handle negative statements ("Greg never said his car wasn't blue") even when they would know the positive statement was true ("Greg says his car is blue"). The problem, say the researchers, is that the database is filled with human bias. The people who created FEVER tended to write their false entries as negative statements and their true statements as positive statements -- so the computers learned to rate sentences with negative statements as false. That means the systems were solving a much easier problem than detecting fake news. "If you create for yourself an easy target, you can win at that target," said MIT professor Regina Barzilay.