OpenAI reported that an early image classifier correctly identified about 98% of DALL·E 3 images in internal testing. That was not a public, universal detector for AI images: the May 2024 announcement described limited researcher access, and OpenAI said the classifier performed less well on images from other AI models. OpenAI’s current public checker instead looks for provenance signals associated with OpenAI-generated content.
Can OpenAI detect if an image was made with DALL·E 3?
In May 2024, OpenAI announced an early classifier that predicted the likelihood an image was generated by DALL·E 3. The company was opening applications for an initial group of testers, including research labs and research-oriented journalism nonprofits, through its Researcher Access Program—not announcing a general-purpose consumer detector. OpenAI’s May 7, 2024 announcement described the tool’s intended scope as identifying DALL·E 3 images.
OpenAI reported that internal testing of an early version correctly identified approximately 98% of DALL·E 3 images. It also reported that less than approximately 0.5% of non-AI-generated images were incorrectly tagged as DALL·E 3. These are company-reported results, not an independently reproduced benchmark. The announcement does not give the test-set size or composition, confidence intervals, or an independent evaluation protocol.
Does 98% accuracy mean it detects every AI image?
No. The figure concerns DALL·E 3 images, not all images produced by AI systems. OpenAI said the classifier was less effective at distinguishing DALL·E 3 images from images created by other AI models. On its internal dataset, it flagged approximately 5–10% of images from other AI models. That is a different result from the 98% figure and should not be treated as a reliable universal AI-image detection rate.
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OpenAI also said compression, cropping, and saturation changes had minimal impact on the early classifier’s performance, while other modifications could reduce it. The announcement did not specify those other modifications, so the result is not a guarantee for edited or arbitrary images.
How does OpenAI’s current image checker work?
OpenAI’s current Verify OpenAI-generated content page describes a public checker for image or audio files. It looks for supported provenance signals, including C2PA Content Credentials and SynthID, to help identify content generated with ChatGPT, the OpenAI API, or Codex. It does not claim to detect every AI-generated image from every provider.
This is a different approach from the 2024 classifier: provenance checking looks for signals associated with a file’s origin, rather than making a broad judgment that an image looks AI-generated. OpenAI advises checking one image at a time and avoiding cropping or format conversion for the most reliable image check.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What does it mean if OpenAI’s image checker finds no signal?
No signal is inconclusive; it does not establish that a person made the image. A signal may be absent because metadata was removed or tampered with, a watermark degraded, the image came from a legacy generation model, or it was made with another company’s model. Conversely, a detected signal indicates likely origin from OpenAI tools, not whether the image is accurate or shown in the right context. OpenAI’s page explains this limitation in its verification guidance.
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What the 98% figure can—and cannot—tell you
- It can: describe OpenAI’s internal test result for an early classifier intended to identify DALL·E 3 images.
- It cannot: establish that the tool detects all AI images, reliably separates every model’s output, or provides a guarantee for any particular file.
- It does not establish: independent validation of the result. OpenAI’s announcement does not supply sample size, test-set construction, uncertainty bounds, or an external replication.
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