Hany Farid

And now, with generative AI, anybody can create any image of anything, anywhere at the touch of a button.

from four soldiers tied up in a basement to a giraffe trying on a turtleneck sweater.

It's not fun and games, of course, because generative AI is being used to supercharge past threats and create entirely new ones.

The creation of nudes of real women and children used to humiliate or extort them.

Fake videos of doctors promoting bogus cures for serious illnesses.

A Fortune 500 company losing tens of millions of dollars because an AI impersonator of their CEO infiltrated a video call.

Those threats are real, they are here, and we are all vulnerable.

It's useful to understand how generative AI works.

Starting with billions of images with a descriptive caption, each image is degraded until nothing but visual noise is left, a random array of pixels.

And then the AI model learns how to reverse that process by essentially turning that noise back into the original image.

And when this process is done not once, not twice, but billions of times on a diverse set of images, the machine has learned how to convert noise into an image that is semantically consistent with anything you type.

And it's incredible.

But it is decidedly not how a natural photograph is taken, which is the result of converting light that strikes an electronic sensor into a digital representation.

And so one of the first things we like to look at is whether the residual noise in an image looks more like a natural image or an AI-generated image.

Those star-like patterns are a telltale sign of generative AI.

Now, for mathematicians and the physicists in the audience, that is the magnitude of the Fourier transform of the noise residual.

For everybody else, that detail doesn't matter, but you definitely should have taken more math in college.

Professors can't help themselves.

But no forensic technique is perfect.

And so you don't stop after one thing, you keep going.