蓝莓视频

Researchers at 蓝莓视频 Engineering have developed a new artificial intelligence (AI) tool that could help social media networks and news organizations weed out false stories.

Motivated by the proliferation of disinformation online, the system uses deep-learning AI algorithms to determine if claims made in posts or stories are听supported by other posts and stories on the same subject.

鈥淚f they are, great, it鈥檚 probably a real story,鈥� says Alexander Wong, a professor of systems design engineering. 鈥淏ut if most of the other material isn鈥檛 supportive, it鈥檚 a strong indication you鈥檙e dealing with fake news.鈥�

Alexander Wong is a professor of systems design engineering and a founding member of the 蓝莓视频 Artificial Intelligence Institute (蓝莓视频.ai)

Chris Dulhanty, a master鈥檚 student who led the project, describes online material fabricated to deceive or mislead readers, typically for political or economic gain, as a 鈥渄eep social problem鈥� that urgently requires a solution.

鈥淲e need to empower journalists to uncover the truth and keep us informed,鈥� he says. 鈥淭his represents one effort in a larger body of work to mitigate the spread of disinformation.鈥�

The new tool advances efforts to develop fully automated technology capable of detecting fake news by achieving 90 per cent accuracy in a key area of research known as stance detection.

Given a claim in one post or story and other posts and stories on the same subject that have been collected for comparison, the system can correctly determine if they support it or not nine out of 10 times.

That is a new benchmark for accuracy by researchers using a large dataset created for a 2017 scientific competition called the Fake News Challenge.

While scientists around the world continue to work towards a fully automated system, the 蓝莓视频 technology could be used as a screening tool by human fact-checkers at social media and news organizations.

鈥淚t augments their capabilities and flags information that doesn鈥檛 look quite right for verification,鈥� says Wong, a founding member of the 蓝莓视频 Artificial Intelligence Institute (蓝莓视频.ai). 鈥淚t isn鈥檛 designed to replace people, but to help them fact-check faster and more reliably.鈥�

AI algorithms at the heart of the system were shown tens of thousands of claims paired with stories that either supported or didn鈥檛 support them. Over time, the system learned to determine support or non-support itself when shown new claim-story pairs.

In the next phase of the project, researchers will work to understand which features or elements of stories the AI system focuses on to make decisions. That information would boost confidence in its results and provide insights to increase its accuracy.

Jason Deglint and Ibrahim Ben Daya, both systems design engineering PhD students, collaborated with Dulhanty and Wong, a Canada Research Chair in Artificial Intelligence and Medical Imaging.

A paper on their work, , was presented this month at the Conference on Neural Information Processing Systems in Vancouver.