Glad to see we learned from the mistakes of SAML.
/s
In traditional provence use case, you want to prove the image have never edited after it was created from the source. When signature mismatch, it is considered invalid.
For AI use case, you want to proof the image have never touched with AI. C2PA only (kind of) proof the last touch wasn't from AI..
Given how bad Google's implementation is, the only thing Google's implementation proves is that someone somewhere on earth owns a Pixel phone... and we'll probably learn that it doesn't even prove that.
I like to contrast how Google has responded to the failure of their implementation with how Nikon responded to the very same sort of failures. (Search for "Nikon" here [0], but -IMO- the whole post is worth reading.)
[0] <https://www.hackerfactor.com/blog/index.php?/archives/1102-C...>
C2PA is fallible if your origin is fallible. SynthID is a better standard for designating something was created with GenAI, though is limited in what it covers. For example, 3D content is currently a poor fit for both SynthID and C2PA. Audio is also imho poorly served.
There are a few things in the works for 3D…audio is an area I’ve tracked less.
Wacom have a synthid like embedding for geometric data https://youtu.be/AEi083BtgvU?si=Lu9EO4b1SPcfXiQU
And Apple just recently merged a authorship setup into USD https://github.com/PixarAnimationStudios/OpenUSD/pull/4188 (I didn’t realize it was merged till looking it up for this response)
But crucially , none of the global regulations require C2PA specifically. And with all synthetic data , you’re really relying on honor system for transparency.
It’s not like the sensor to display pipeline that C2PA and Apple’s Reference Image can provide when enforced in hardware.