News headlines might not be the only things that are fake in the future.

Powerful machine-learning techniques (see “The Dark Secret at the Heart of AI”) are making it increasingly easy to manipulate or generate realistic video and audio, and to impersonate anyone you want with amazing accuracy.

A smartphone app called FaceApp, released recently by a company based in Russia, can automatically modify someone’s face to add a smile, add or subtract years, or swap genders. The app can also apply “beautifying” effects that include smoothing out wrinkles and, more controversially, lightening the skin.

And last week a company called Lyrebird, which was spun out of the University of Montreal, demonstrated technology that it says can be used to impersonate another person’s voice. The company posted demonstration clips of Barack Obama, Donald Trump, and Hillary Clinton all endorsing the technology.

These are just two examples of how the most powerful AI algorithms can be used for generating content rather than simply analyzing data.

Powerful graphics hardware and software, as well as new video-capture technologies, are also driving this trend. Last year researchers at Stanford University demonstrated a face-swapping program called Face2Face. This system can manipulate video footage so that a person’s facial expressions match those of someone being tracked using a depth-sensing camera. The result is often eerily realistic.

The ability to manipulate voices and faces so realistically could raise a number of issues, as the creators of Lyrebird acknowledge.

“Voice recordings are currently considered as strong pieces of evidence in our societies and in particular in jurisdictions of many countries,” reads an ethics statement posted to the company’s website. “Our technology questions the validity of such evidence as it allows to easily manipulate audio recordings. This could potentially have dangerous consequences.”

Both FaceApp and Lyrebird use deep generative convolutional networks to enable these tricks. This means the company is applying a technique that has emerged in recent years as a way of getting algorithms to go beyond just learning to classify things and generate plausible data of their own.