Researchers at the University of Chicago are experimenting with artificial intelligence (AI)-based techniques for automatically generating convincing online reviews, such as bogus Yelp restaurant critiques.
"We have validated the danger of someone using AI to create fake accounts that are good enough to fool current countermeasures," says University of Chicago professor Ben Zhao.
The team employed a deep-learning artificial neural network to extract letter and word patterns used in millions of existing reviews, and used them produce its own reviews.
Testing showed Yelp's filtering software, which also relies on machine-learning algorithms, had problems distinguishing real from fake critiques. In addition, many human evaluators also were fooled by the automated posts.
Zhao's team is building algorithms designed to serve as countermeasures to identify phony reviews, and they also are considering further research into fake news detection.
The researchers will present their research in November at the ACM Conference on Computer and Communications Security (CCS 2017) in Dallas, TX.
From Scientific American
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