There’s a revolution afoot, and you will know it by the stripes.

Earlier this year, a group of Berkeley researchers released a pair of videos. In one, a horse trots behind a chain link fence. In the second video, the horse is suddenly sporting a zebra’s black-and-white pattern. The execution isn’t flawless, but the stripes fit the horse so neatly that it throws the equine family tree into chaos.

Turning a horse into a zebra is a nice stunt, but that’s not all it is. It is also a sign of the growing power of machine learning algorithms to rewrite reality. Other tinkerers, for example, have used the zebrafication tool to turn shots of black bears into believable photos of pandas, apples into oranges, and cats into dogs. A Redditor used a different machine learning algorithm to edit porn videos to feature the faces of celebrities. At a new startup called Lyrebird, machine learning experts are synthesizing convincing audio from one-minute samples of a person’s voice. And the engineers developing Adobe’s artificial intelligence platform, called Sensei, are infusing machine learning into a variety of groundbreaking video, photo, and audio editing tools. These projects are wildly different in origin and intent, yet they have one thing in common: They are producing artificial scenes and sounds that look stunningly close to actual footage of the physical world. Unlike earlier experiments with AI-generated media, these look and sound real.

Sandra Upson is Backchannel's executive editor. Sign up to get Backchannel's weekly newsletter, and follow us on Facebook, Twitter, and Instagram.

The technologies underlying this shift will soon push us into new creative realms, amplifying the capabilities of today’s artists and elevating amateurs to the level of seasoned pros. We will search for new definitions of creativity that extend the umbrella to the output of machines. But this boom will have a dark side, too. Some AI-generated content will be used to deceive, kicking off fears of an avalanche of algorithmic fake news. Old debates about whether an image was doctored will give way to new ones about the pedigree of all kinds of content, including text. You’ll find yourself wondering, if you haven’t yet: What role did humans play, if any, in the creation of that album/TV series/clickbait article?

A world awash in AI-generated content is a classic case of a utopia that is also a dystopia. It’s messy, it’s beautiful, and it’s already here.

Currently there are two ways to produce audio or video that resembles the real world. The first is to use cameras and microphones to record a moment in time, such as the original Moon landing. The second is to leverage human talent, often at great expense, to commission a facsimile. So if the Moon descent had been a hoax, a skilled film team would have had to carefully stage Neil Armstrong’s lunar gambol. Machine learning algorithms now offer a third option, by letting anyone with a modicum of technical knowledge algorithmically remix existing content to generate new material.