What is an AI image detector?
Short answer
An AI image detector is a tool that checks whether an image may have been generated or heavily changed by an AI system.
Some tools look for technical signals inside the file. Some look at pixels. Some look for signed provenance records, such as C2PA Content Credentials. Some use machine learning to compare the image with known AI-generated examples.
The tricky part is that an image can have many histories. It might be fully AI-generated, partly edited with an AI tool, compressed by a social platform, screenshotted, cropped, or created by a real camera and then changed later. A useful check should describe the evidence, not pretend every case is simply real or fake.
Why is AI image detection hard?
Early AI images often had obvious visual mistakes. Today, many do not. At the same time, normal editing and social media uploads can remove the very clues that would help you understand where an image came from.
- New image models fix old visual tells quickly.
- Screenshots create a new file and can wipe origin clues.
- Social platforms often resize and recompress images.
- A real photo can be edited with AI in only one small region.
- A fake caption can mislead even when the image itself is real.
- Metadata can be missing for ordinary reasons.
What should an image checker look at?
A strong review uses layers. One signal may be weak on its own, but several independent signals can give a much clearer picture.
| Evidence layer | What it can tell you | What it cannot prove alone |
|---|---|---|
| Content Credentials | Whether a signed origin or edit history is attached. | Whether the depicted event is true. |
| Metadata | Software, timestamps, device clues, and sometimes generator details. | Authenticity, because metadata can be removed or edited. |
| Pixel forensics | Compression, resizing, splicing, or other editing traces. | The reason the edit happened. |
| AI classifier | Whether the image resembles known AI-generated examples. | Every generator or every future model. |
| Visual review | Odd text, lighting, geometry, or object details. | Proof, because real images can also look strange. |
| Context search | Earlier copies, source account, and external reports. | Technical origin by itself. |
What are C2PA and Content Credentials?
Short answer
C2PA is a standard for attaching signed information about where a digital file came from and how it was edited. Content Credentials are a common way people see that information.
When present and valid, provenance can be very helpful. It may tell you that an image was created by a camera, edited in a particular tool, or generated by software that recorded its role.
But missing credentials do not settle the question. A file may lose its credentials after a screenshot, export, crop, platform upload, or format conversion. So the right conclusion is often origin unknown, not definitely real or definitely fake.
How can you check whether an image is AI-generated?
Start by preserving the best version of the file. Do not work from a tiny screenshot if you can get the original upload, email attachment, or document.
| Step | What to do |
|---|---|
| Get the original | Ask for the highest-quality file, not a screenshot. |
| Check provenance | Look for signed credentials and metadata. |
| Inspect edits | Review compression, cropping, splicing, and export traces. |
| Look at the image | Check text, reflections, anatomy, lighting, and impossible details. |
| Check the story | Search for earlier copies, source accounts, and independent reporting. |
| Write down uncertainty | Say what is known, what is likely, and what remains unresolved. |
How should you read the result?
The safest language is evidence-based. Instead of saying this image is fake, say what the check found: valid AI provenance, missing origin metadata, editing traces, a classifier signal, or no strong signal.
| Finding | Plain-English interpretation |
|---|---|
| Valid AI provenance marker | Strong evidence that the file records AI involvement. |
| No metadata | The origin is unresolved; this is common after upload or export. |
| Classifier signal only | Worth reviewing with other evidence. |
| Editing traces only | The image changed, but the reason may be normal. |
| Clean file and credible source | More confidence, but not mathematical proof. |
| Conflicting signals | Preserve the file and review more carefully. |
What can Stipple inspect?
Stipple can inspect uploaded images and documents for explicit AI-generation markers, C2PA/IPTC-style provenance, generator metadata, editing traces, and other supporting signals.
The goal is not to guess dramatically. The goal is to give you a careful, explainable result that says what the file evidence supports and what it does not.
Frequently asked questions
Can an AI image detector be 100% accurate?
No. AI image generation and editing tools change quickly, and normal file transformations can remove useful clues.
Does missing metadata mean an image is fake?
No. Missing metadata is common. It means one evidence channel is absent, not that the image is fake or real.
Can Stipple check AI-generated images?
Yes. Stipple can inspect uploaded images and documents for provenance, AI markers, editing traces, and related signals.
Sources and further reading
- 01C2PA technical specification
- 02Content Authenticity Initiative
- 03NIST Open Media Forensics Challenge
Educational guidance, not a forensic certification. Detection technologies and standards change; review material decisions against current evidence.