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OpenAI reported that an early classifier correctly identified about 98% of DALL·E 3 images in the company’s internal testing. That was not a claim of 98% accuracy for detecting every kind of AI image, nor evidence of a generally available detector. OpenAI’s current public checker works differently: it looks for provenance signals associated with OpenAI content, and a missing signal does not prove an image was made by a person.
What OpenAI’s 98% figure measured
On May 7, 2024, OpenAI announced applications for an initial group of testers—including research labs and research-oriented journalism nonprofits—to access an image-detection classifier through its Researcher Access Program. OpenAI described it as a tool that predicted the likelihood an image was generated by DALL·E 3, rather than a universal detector available to everyone. OpenAI’s announcement reported results from internal testing of an early version.
- OpenAI said the classifier correctly identified approximately 98% of DALL·E 3 images.
- It incorrectly tagged less than approximately 0.5% of non-AI-generated images as DALL·E 3.
Those figures are company-reported, not an independently reproduced benchmark. The announcement does not give the relevant sample size, test-set composition, confidence intervals, or an independent evaluation protocol in the cited discussion. The rates therefore should not be treated as a guarantee for arbitrary images.
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OpenAI said its 2024 classifier was intended to estimate whether an image came from DALL·E 3. Its performance was lower when distinguishing DALL·E 3 images from images made by other AI models: OpenAI reported that it flagged approximately 5–10% of other-model images on its internal dataset. This means the tool was not simply identifying “AI-made” versus “human-made” images. Its reported results were strongest for the particular generator it targeted.
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OpenAI also said compression, cropping, and saturation changes had minimal impact on that early classifier’s performance, while other modifications could reduce it. The announcement did not specify those other modifications.
What OpenAI’s current image checker does
OpenAI’s current verification page describes a public file-upload checker for images or audio. It looks for supported provenance signals, including C2PA Content Credentials and SynthID, to help identify content generated with ChatGPT, the OpenAI API, or Codex. That is a provenance check for supported OpenAI content, not a promise to recognize all AI-generated images from all providers.
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For an image check, OpenAI advises uploading one image at a time and avoiding cropping or format conversion for the most reliable result. This is practical guidance for the current signal-checking workflow; it should not be confused with the separate robustness statement OpenAI made about its early 2024 classifier.
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What a positive result—or no signal—means
If a signal is detected
OpenAI says, “A detected signal indicates that the content likely originated from OpenAI tools.” It speaks to likely origin, not whether the image is accurate, authentic in its context, or used honestly.
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If no signal is detected
No signal is inconclusive. The image may still have been AI-generated: metadata could have been removed or altered, a watermark may have degraded, the image could come from a legacy generation model, or it may have been made with another provider’s model. An absent signal is not proof of human authorship.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Why this distinction matters for image checks
A classifier, a watermark, and signed metadata are different kinds of evidence. The 2024 classifier estimated whether an image resembled the DALL·E 3 images it was trained and evaluated on. The current checker looks for provenance signals embedded in supported content. Either approach has a limited scope: a classifier’s result depends on its target and evaluation, while a provenance check can fail to find a signal that is missing or degraded. OpenAI’s published figures do not establish a comparable, independently evaluated accuracy rate for the current public checker.
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DALL·E 3 itself is a text-to-image system: a text prompt is used to generate an image, as described in OpenAI’s DALL·E 3 system card. Whether an image looks painterly or photographic cannot substitute for provenance evidence, and neither a positive nor a negative checker result alone establishes the image’s truth or authorship.
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