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No visual test can reliably prove that an image was made with AI. Start with the original file and look for verifiable provenance or a supported watermark; treat detector scores and visual clues only as leads. A missing signal does not prove the image is camera-made, and evidence of how a file was created does not establish that its caption or depicted event is true.
Check provenance before judging pixels
When available and verifiable, a file’s provenance is stronger evidence of its recorded history than a guess based on how it looks. C2PA Content Credentials can carry information about a file’s origin and recorded edits. They are metadata attached to the file, so a platform upload, conversion, or other export may remove them. Adoption is not universal, either. A file without credentials is therefore inconclusive, not proof of a camera origin. The U.S. Office of Research Integrity explains these limits.
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Credentials are not exclusive to AI images: they can also record media from cameras, news organizations, and other workflows. A valid record can support claims about a file’s stated history, but it does not establish that the scene is real, that the caption is accurate, or that the image is being shown in context. Nor does a record that an edit occurred explain why it was made.
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1Repair Windows errors before they cause bigger problems2Scan for outdated or missing drivers - takes under a minute3Clear out junk files and repair common Windows errorsA practical workflow for checking an image
- Keep the best copy. Ask for the original file, or obtain the version from the source that first published it. Save a copy before editing or converting it; those steps and social platforms can strip metadata.
- Inspect Content Credentials. Open the original in a compatible viewer and check whether it has a valid signed provenance record. Read what the record says about origin and edits rather than treating the mere presence of credentials as an AI label.
- Check for a supported watermark. Use a verifier that names the signal and generators it supports. For example, OpenAI’s verifier checks supported OpenAI C2PA and SynthID signals; it is not a universal AI-image detector. Google’s SynthID verification information likewise concerns supported models and media.
- Use general detectors only as a prompt. A detector may return a classification or score, but its results depend on the systems and conditions it was tested against. Do not treat a confidence number as proof.
- Investigate the source and the claim. Look for the earliest available posting, a photographer or publisher statement, independent images of the same event, and corroboration from reliable sources. Ask both whether the image may be synthetic and whether the specific claim attached to it is supported.
- Report uncertainty honestly. If there is no usable provenance signal and the image cannot be independently checked, call it unverified rather than declaring it authentic or AI-generated.
What each checking method can and cannot tell you
| Method | What it can tell you | Main limitation | Best use |
|---|---|---|---|
| C2PA Content Credentials | A verifiable record of file origin and recorded edits, when present and supported | Metadata may be stripped; adoption is incomplete; a record does not explain why an edit occurred | Inspect the original file’s recorded history |
| Supported watermark checker, such as a SynthID verifier | Whether the checker finds a signal associated with a generator it supports | Coverage is limited by tool, model, export route, file type, and date; no result cannot exclude unsupported or degraded signals | Check for a known provider’s supported signal |
| General AI-image detector | A model’s estimate or classification for the submitted image | Performance may not generalize across generators or transformations; a score is not proof | Prompt further investigation |
| Visual inspection | Visible inconsistencies that may suggest questions to investigate | No validated visual cue establishes origin from pixels alone | Generate leads, never a standalone verdict |
| Context and source checking | Whether the image and caption fit independently verifiable evidence | Original sources may be unavailable | Assess the claim being made about the image |
Interpret watermark and detector results narrowly
Watermarks and provenance records answer different questions. SynthID embeds a signal in supported generated media; C2PA credentials carry provenance information in metadata. Whether either is available depends on the creation tool, model, export route, file type, and date.
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A positive result from a supported verifier is scoped evidence. OpenAI says its verifier checks supported OpenAI C2PA and SynthID signals, and a detected signal indicates likely origin from its tools; it does not establish later modification, accuracy, or context. Its help page says: “If no signal is detected, it means the tool did not find supported signals in the uploaded file.” That is not the same as proving no AI was involved. Before uploading a sensitive image, review the verifier’s current file-handling and privacy terms; OpenAI’s stated terms are service-specific and may change. See OpenAI’s current verifier documentation.
Detector evaluations also do not justify a universal accuracy claim. NIST’s 2024 overview surveys approaches including provenance, watermarking, and detection. Its 2025 pilot evaluation plan for image discriminators describes comparison against known human and AI-generated images using multiple performance measures. The practical implication is to judge a detector in the context of its tested systems and conditions, not to treat one output as a universal verdict.
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Keep image origin separate from image truth
Even a valid provenance record does not prove the depicted event happened as presented. An image can be authentic yet misleadingly captioned or stripped of context; an edit record documents an edit but not its purpose. Verify the underlying claim independently, and describe what the evidence supports rather than making a stronger claim about origin or truth.
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