A relatively new company in New York, Wordflow AI is aiming to improve the odds of consumers finding accurate information on the web by predicting content based on their interests. The company, founded by two PhDs from the University of Michigan, has come up with algorithms to tweak users’ newsfeeds to bring more high-quality news about issues to the spotlight.

Hannah Naranjo, a postdoctoral research fellow in the University of Michigan’s School of Information, and her partner Kevin Shea, an assistant professor in the University of Michigan’s School of Engineering, said they were motivated to create the company when they saw how the over-aggregation of content on social media sites and search engines was pushing headlines and stories toward the top of the lists. With the help of about five brainpower staffers, Wordflow AI created algorithms that can determine the relevance of an article based on user interest.

“If you know what keywords are most likely to send someone to a topic, you can better understand what their interest is,” Naranjo told The New York Times. “The same is true for headlines.”

The algorithms are trying to draw on preexisting knowledge for users by searching hundreds of news articles to see how news is written by other publications.

Once Wordflow AI has created an algorithm that guesses content based on user interest, it would go on to do things like suggest similar articles, feed them to users, and then “aggressively push them into people’s feeds,” according to the Times. Articles that would be unlikely to be found elsewhere on the web would be made popular on social media. The company also has plans to create more job opportunities for writers, editors, and other staff at the company, Naranjo said.

Read the full story at The New York Times.

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