This fake news detection algorithm outperforms humans

When researchers working on developing a machine learning-based tool for detecting fake news realized there wasn't enough data to train their algorithms, they did the only rational thing: They crowd-sourced hundreds of bullshit news articles and fed them to the machine. The algorithm, which was developed by researchers from the University of Michigan and the University of Amsterdam, uses natural language processing (NLP) to search for specific patterns or linguistic cues that indicate a particular article is fake news. This is different from a fact checking algorithm that cross-references an article with other pieces to see if it contains inconsistent information – this machine learning solution could automate the detection process entirely. No offense to the Michigan/Amsterdam team but building an NLP algorithm to parse sentence structure and hone in on keywords isn't exactly the bleeding edge artificial intelligence work that drops jaws. Getting it to detect fake news better than people, however, is.