AI-Powered Credibility Labeler for Scientific Misinformation and Disinformation
Jian Wu, assistant professor, computer science, Old Dominion University
Jeremiah Still, assistant professor, psychology, Jian Li, professor, electrical and computer engineering; both Old Dominion University
Fake scientific news has been spreading across the internet for years, but even more so since COVID-19, prompting such fake stories as “mosquitoes spread coronavirus.” It may be easier for people to believe these pieces of news since they seem intuitively correct. Will they change their mind if they see the evidence against these news articles from scientific literature? Do they trust the credibility scores estimated by artificial intelligence algorithms? Will they still pass these news articles to their friends on Facebook? To find some answers, computer scientists will collaborate with psychologists at Old Dominion University. The project consists of three steps. First, a new algorithm will be researched and implemented to estimate how likely a scientific news article reveals the truth. The algorithm will also provide evidence from scientific publications. Then, a website will be built to show users what is found in the first step. Finally, a study will be performed on news consumers to see their reactions when they are shown fake news articles and debunk information on the website we built. The hope is to reveal the effectiveness of using scientific literature as weapons to debunk scientific misinformation and disinformation, eventually curb their spread across society.