How “fake news” could get even worse

By H.H.

RICK ASTLEY is rightly famous. His 1987 single, “Never Gonna Give You Up”, has been played more than 330m times on YouTube. But in February last year Mr Astley (pictured) indulged in a rather odd experiment. The singer, looking remarkably similar to his late-’80s self, covered his own hit song, but sang the whole thing in order of pitch. The song, a video of which appears on YouTube, proceeds in a rather unconventional manner. Mr Astley stammers out different lines in a jumble, going from dulcet bass tones to shrill trebles over a tortuous three-and-a-half minutes. The only coherent thing about the apparent stunt is the progression from low to high notes—except then he goes back to low at the end. Did this actually happen?

No. Mr Astley did not rework his song. An artist called Mario Klingemann did, using clever software. The video is a particularly obvious example of generated media, which uses quick and basic techniques. More sophisticated technology is on the verge of being able to generate credible video and audio of anyone saying anything. This is down to progress in an artificial intelligence (AI) technique called machine learning, which allows for the generation of imagery and audio. One particular set-up, known as a generative adversarial network (GAN), works by setting a piece of software (the generative network) to make repeated attempts to create imagesthat look real, while a separate piece of software (the adversarial network) is set up in opposition. The adversary looks at the generated images and judges whether they are “real”, which is measured by similarity to those in the generative software’s training database. In trying to fool the adversary, the generative software learns from its errors. Generated images currently require vast computing power, and only work at low resolution. For now.