Meta made its own AI detection system. It should have just used Google’s

In March, Meta’s Oversight Board called on the company to “meet its public commitments and employ its own tools” to help quell the spread of deceptive generative AI content across platforms. Meta responded in July by introducing Content Seal — an invisible watermarking technology that flags images generated by the company’s new AI model. But it was basically a footnote buried in the company’s announcement for its Muse image and video generation tools.

It’s early days for Content Seal, but the standard isn’t off to a good start. As someone who spends a lot of time scrutinizing AI labeling systems, Content Seal doesn’t fill me with confidence. There are already more established solutions, like C2PA Content Credentials and Google’s SynthID, that Meta could have used instead of launching its own system significantly later.

By Meta’s description, Content Seal works similarly to SynthID. The watermark, invisible to human eyes, provides a “hidden provenance signal” embedded into AI-generated images that can then be scanned and flagged by a detection tool, helping online users to differentiate deepfakes from authentic content. Like SynthID, Meta also says that Content Seal watermarks remain intact and can still be detected if the image is “cropped, compressed, resized, or screenshotted.”

So, if Content Seal functionally does the same thing… why not just adopt SynthID? Meta already operates as a steering committee member of the Coalition for Content Provenance and Authenticity (C2PA) that promotes the separate Content Credentials standard alongside Google. SynthID has also already been adopted by OpenAI, showing Google's willingness to open its technology to rivals.

Content Seal has several limitations in its current state. For now, users can only detect Content Seal watermarks through a dedicated web tool that Meta is testing, meaning Meta hasn’t built those detection capabilities into its Meta AI chatbot like Google has with Gemini. The watermark itself is also only being applied to images generated by Muse, meaning users can’t use it to detect content created by Meta’s older AI models or video.

Meta has also imposed a daily limit on how many times you can check images for Content Seal through its detection tool. On Meta’s own platforms like Facebook and Instagram, unspecified metadata alongside Content Seal watermarking is being used. However, testing shows that images made with Muse cannot be detected when fed into Gemini or C2PA portals.

Meta still isn’t sure about how to pitch itself as both a factory for AI content and the solution for identifying it. Even Instagram head Adam Mosseri expressed conflicting opinions on whether AI content should be filtered or labeled. If Meta wants to stand on its own solutions instead of adopting proven standards like SynthID, it will need much more than a half-baked clone to prove it is serious about AI transparency.