Courtesy of John Sohrawardi, Rochester Institute of Technology and Matthew Wright, Rochester Institute of Technology
An investigative journalist receives a video from an anonymous whistleblower. It shows a candidate for president admitting to illegal activity. But is this video real? If so, it would be huge news – the scoop of a lifetime – and could completely turn around the upcoming elections. But the journalist runs the video through a specialized tool, which tells her that the video isn’t what it seems. In fact, it’s a “deepfake,” a video made using artificial intelligence with deep learning.
Journalists all over the world could soon be using a tool like this. In a few years, a tool like this could even be used by everyone to root out fake content in their social media feeds.
As researchers who have been studying deepfake detection and developing a tool for journalists, we see a future for these tools. They won’t solve all our problems, though, and they will be just one part of the arsenal in the broader fight against disinformation.
The problem with deepfakes
Most people know that you can’t believe everything you see. Over the last couple of decades, savvy news consumers have gotten used to seeing images manipulated with photo-editing software. Videos, though, are another story. Hollywood directors can spend millions of dollars on special effects to make up a realistic scene. But using deepfakes, amateurs with a few thousand dollars of computer equipment and a few weeks to spend could make something almost as true to life.
Deepfakes make it possible to put people into movie scenes they were never in – think Tom Cruise playing Iron Man – which makes for entertaining videos. Unfortunately, it also makes it possible to create pornography without the consent of the people depicted.