How to Recognise Fake AI-Generated Images
Our face generator with AI technology has a vast number of uses and capacities, creating unique human images that are extremely difficult to distinguish from a real person. NightCafe tools allow you to generate images with a neural network to replicate specific features or as the basis for artwork, and the possibilities are endless.
So, if you want to become an expert at telling real from digital faces apart, we'll share some tips and tricks. Are AI-generated people fake, or are you looking at a real-life person? Let's find out how you can tell.
How to Spot an AI-Generated Human Face
We'd note that AI graphics are highly detailed, and researchers have found that even AI imagery experts don't always get it right. However, some subtle signs might mean a facial representation isn't, in fact, a living, breathing person.
Smudged or Clumpy Hair
AI faces with straight hair often have very straight lines, which look like a person has spent a lot of time finessing their style with a set of straighteners. If you can zoom in close enough, you might spot that a longer strand appears smudged and looks like paint. Individual patches will still look exactly like hair, but it's a discreet detail that AI doesn't always perfect.
Another signal that you're looking at a GAN-generated image is if the hair is clumpy, with random wispy bits around the shoulder line or thick strands that seem out of place. Hairstyles are very variable, but the level of detail can be difficult for a GAN to capture correctly.
Blurry Backgrounds
GANs trained to recognise and synthesise faces aren't as good at forming artificial backgrounds or structures. Because a GAN approaches deep learning with training data in both an original and mirrored version, whereas text is single-orientated, it can get confused with writing, such as on a sign or building.
You might also see a face that doesn't appear to be anything but real with a surreal, blurred background. The training data used by a GAN is centred on the facial image, so it often can't work out how to formulate a believable background–this can be made up of textures rather than a scene you'd expect to see in a photo.
Non-Asymmetrical AI Faces
AI is very smart, but it sometimes doesn't grasp the need for asymmetry in some features but not in others. For example, you might see:
- Mismatched earrings
- Different coloured eyes
- Eyes looking in different directions
- Ears that aren't the same size or height
Of course, any of those might be authentic, and it may be that a photograph subject put on the wrong earrings or has unusual eyes, but this is one indicator that the face could be artificial.
This confusion with repeating patterns also applies to teeth. Data sets will inevitably include images with perfect teeth and slightly misaligned dentistry. The GAN might shrink or expand a tooth unnaturally, which is a common issue with conventional technology that struggles with other repeating patterns, such as brickwork.
Why Is it So Difficult to Differentiate Between Real and AI Faces?
AI deep learning techniques mean that face-generating technology is increasingly smart, filing away millions of data sets to understand what real portrait photos look like, how they vary, and the common characteristics.
The AI replicates those patterns and compares an artificial face to its data, making adjustments where it recognises the difference between its own image and those in its database.