Meta AI image detector fails to identify some of its own cropped AI images, Reuters analysis finds

A new AI detection tool from Meta which the tech company previewed this week alongside the launch of its image-generation model, Muse ‌Image, failed to identify some of its own AI-generated images once they were cropped, according to a Reuters analysis.

In an analysis of 40 images generated using Muse Image, Reuters found the detection tool verified all of the original AI-generated images but failed to verify 55% of ⁠the same images after they were cropped to approximately one-third to one-half of their original size.

When asked about the results of the Reuters analysis of the detection tool, Meta noted that the tool was a preview. The company said the watermark is designed to remain intact after common edits, but that the signal may be lost if an image is heavily cropped.

Rival tech companies Google and OpenAI have cautioned that their own detection ‌tools ⁠are not foolproof against image-alteration techniques.

https://www.reuters.com/business/meta-ai-image-detector-fails-identify-some-its-own-cropped-ai-images-reuters-2026-07-10/Open link View original on sh.itjust.works

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lyralycan

sh.itjust.works

Last year I generated 8 images during a day of experimenting with Google's Gemini Image model. Running this same test on my own images:

5/8 were verified using Google's own embedded SynthID;
After running the failures through once again, one verified, making the successful total 6/8. Two remained ambiguous according to the AI.

Of these images:

5 were generated with just a prompt (4*/5), including the image that was not recognised at first
2 were generated using personal images alongside a prompt (1/2), the recognised one of a human, the other of a rabbit
1 was generated using sourced imagery alongside a prompt (0/1)

Conclusion: Hilariously, it seems the in-house watermark method is absolutely not accurate.

Zarobi

Cache miss

Just use one of these.