Faculty of
Engineering, Architecture and Information Technology

19 September 2019

Figuring out fake news

The ability to determine what’s real and what’s fake online could soon become a little easier thanks to artificial intelligence systems and research developed at The University of Queensland.

Data scientist Associate Professor Dr Gianluca Demartini said the aim of the project was to establish an online safety benchmark for the identification of fake news.

“News can be misleading, incomplete and sometimes just plain fabricated,” Dr Demartini said. 

“Being exposed to such content influences our way of thinking and our decision-making processes, which can create risks to our safety online, both as individuals and as a society.

“While benchmarks to evaluate AI systems that can detect fake news already exist, we wanted to create something different, where instead of just experts or journalists assessing the credibility of news, we are able to give regular people the power and tools to evaluate it for themselves.”

UQ researchers have collected a range of online data over a number of years to determine how people perceive online content and how their biases and stereotypes might play a role in their perception.

“These judgements will allow us to train and evaluate machine-learning models to automatically detect fake news,” Dr Demartini said.

“In my opinion, this is key for the future of news on social media.

”Rather than having the artificial intelligence making decisions for us on what is fake or not, we should teach the users of social media platforms how to identify such items themselves.

“This project really is about responsible data science, where researchers can adapt their research and algorithms for the benefit of the public.”

Dr Demartini was awarded a $60,000 grant from Facebook Research to carry out the project.

Media: School of Information Technology and Electrical Engineering, Dr Gianluca Demartini, 0412 522 985, g.demartini@uq.edu.au; EAIT communications, Paige Ashby, p.ashby@uq.edu.au, 0430 511 615.