How to Spot AI Generated Images Before You Share One

An image stops you mid-scroll. Something about it is slightly wrong, and you can’t say what.

Ten seconds later you’ve either shared it or moved on, which is the whole problem.

Learning how to spot AI generated images used to mean counting fingers. Current models fixed hands, teeth and ears, so the reliable tells have moved.

The ones that still work are about text, light and provenance.

Key Takeaways

• Hands and teeth are fixed in current models, so those checks are wasted.
• Text inside a picture is still the most reliable single tell.
• Detector tools report confidence, not proof, and they get both directions wrong.

Most of the Old Advice Stopped Working

The famous tells came from models that are two generations old.

Six-fingered hands, melted ears and mangled teeth were artifacts of how early image models handled small repeated structures. Current tools render them correctly most of the time.

Checking for them now produces false confidence in both directions. A real photograph with an awkwardly cropped hand reads as fake, and a competent generation sails through.

The gap between generations is why this advice ages badly. Current AI image generation software renders hands correctly that the same prompt broke a year ago.

The Tells That Still Work

Three hold up, and they hold up because each one needs the model to understand something rather than reproduce it.

Text Inside the Picture

Read any signage, labels or writing in the frame.

Image models generate letterforms as texture rather than as language, so words drift into shapes that look like writing without being it. The effect is strongest on small or angled text.

Legible, correctly spelled text deep in the background is the strongest single sign of a real photograph.

Light That Doesn’t Agree

Find the light source, then check every shadow against it.

Generated scenes light the main subject correctly and lose track of secondary objects. A shadow falling the wrong way, or a reflection missing from a window, is hard to keep consistent across a whole frame.

Texture That Repeats

Look at crowds, foliage, brickwork and fabric patterns.

Backgrounds are where effort goes last, so repeated elements clone each other and objects at the edge of the frame melt into their neighbors.

Check the File, Not Only the Picture

The picture is one source of evidence, and the file around it is another.

Major generators now embed content credentials, a signed provenance record under the C2PA standard, into the files they produce. Some platforms strip them on upload, so their absence proves nothing while their presence tells you a lot.

A reverse image search answers a different question: whether this picture existed before today, and where.

An image with no history and no credentials isn’t proof of anything. It’s a reason to stop before sharing.

Why Detector Tools Aren’t the Answer

They report a confidence score, and a score is not a verdict.

Detectors are trained on the output of models that already exist. A newer generator produces images the detector has never seen, so the score drifts toward whatever the training set looked like.

The failure that matters is the confident wrong answer. A detector calling a real photograph synthetic does more damage than one that shrugs.

Faces are the hardest case, because AI face swap tools keep a real photograph’s lighting and grain while replacing the part you are looking at.

Real Photographs Get Called Fakes Too

The accusation runs in both directions now, and the false positives have a pattern.

Heavy retouching, a phone’s night mode and aggressive noise reduction all smooth skin and flatten texture the way a generated image does.

Studio product shots draw the same suspicion, because an unbroken background and even lighting are exactly what a model produces when nothing constrains it.

So a picture that looks too clean is not evidence. Ask where it came from before deciding what it is.

Questions People Ask About Spotting AI Images

How can you tell if an image is AI generated?

You check three things: text inside the picture, whether the shadows agree with one light source, and whether the file carries content credentials. Counting fingers no longer works, because current models render hands correctly.

Do AI image detectors work?

They work well enough on older images and poorly on new ones. A detector is trained on models that already exist, so anything newer sits outside what it learned. Treat the score as one input rather than a verdict.

What is the easiest sign of an AI generated image?

The easiest sign is text. Signage, labels and writing in the background come out as letter-shaped texture rather than real words, and the effect gets worse the smaller the text is.

Can AI generated images be detected in metadata?

Sometimes. Major generators embed content credentials under the C2PA standard, which is a signed record of how the file was made. Platforms often strip metadata on upload, so absence proves nothing.

Are AI generated images getting harder to spot?

Yes, and quickly. Each generation fixes the tells the last one was known for, which is why advice from a year ago misleads. The checks that last are the ones about physics and provenance rather than anatomy.

Slow Down Before the Share Button

Next time an image stops you, spend ten seconds on the background rather than on the subject.

Read any text in the frame, find the light source, and check whether the picture existed yesterday.

Those three checks cost less than a correction does, and they’ll keep working after the next model release makes another list of tells useless.