Detecting AI-generated faces

AI can now generate very realistic human faces. Nefarious actors can use these for fake personas (examples: document attributed to a "Martin Aspen" with AI-generated face, or Facebook accounts with AI-generated faces masquerading as Americans) rather than relying on reverse-searchable stock images or random real people.

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Faces generated with Nvidia's StyleGAN (v1, v2) are available conveniently through The convenience and quality mean that almost every AI-generated face you currently see will be from StyleGAN. Below are tips for spotting StyleGAN faces.

Eye/mouth positioning
StyleGAN is trained on the Flickr-Faces-HQ dataset, containing 1024x1024 images of faces that have all been aligned in the same way. If the generated image is uncropped, the face should roughly match this template:

Inconsistent background
StyleGAN has trouble keeping backgrounds continuous between the left and right side of the image. Sometimes the background is at an angle when the subject isn't, or makes no discernible sense.

Asymmetric clothing
The clothing on one shoulder often doesn't match the other - check the collars.

Ringing artifacts
The GAN equivalent of JPEG artifacts. Most easily noticeable on images that haven't been downscaled.

Common place for artifacts, asymmetry, and strange earrings.

Nonsense writing
In places where you'd expect to see writing (usually a hat) there are odd symbols.

The "obvious fails"
Less useful since these images are unlikely to be picked for fake personas, and you'd already easily spot them, but sometimes the GAN mistakes microphones for beards, merges glasses with hair, creates an extra distorted face on the side of the image, or otherwise messes up. Some examples below:
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What about automated detection?
Current most promising method involves making the same generator network recreate a given image and seeing how close it can get - but seems to require technical knowledge and computing power. Looking into this more and may update this post.

For usability, I was able to find the below online tools. Can't completely vouch for them, but they gave reasonable results to the images I fed them:
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And another useful site, if you're now wanting to test your ability to distinguish real from generated:
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