Even the Best AI for Spotting Fake News Is Still Terrible
It should be possible to automatically identify dubious news sources — but we’ll need a lot more data
By Karen Hao
When Facebook chief executive Mark Zuckerberg promised Congress that AI would help solve the problem of fake news, he revealed little in the way of how. New research brings us one step closer to figuring that out.
In an extensive study that will be presented at a conference later this month, researchers from MIT, Qatar Computing Research Institute (QCRI), and Sofia University in Bulgaria tested over 900 possible variables for predicting a media outlet’s trustworthiness — probably the largest set ever proposed.
The researchers then trained a machine-learning model on different combinations of the variables to see which would produce the most accurate results. The best model accurately labeled news outlets with “low,” “medium,” or “high” factuality just 65% of the time.
This is far from a smashing success. But the experiments reveal important things about what it would take to outsource our fact-checking to a machine. Preslav Nakov, a senior scientist at QCRI and one of the researchers on the study, says he’s optimistic that sources of fake news can automatically be…
