Even Google themselves previously offered a no-auth way (just very niche): if you uploaded an image to Google Image search, and went to "About this image", it would show if the image was Google AI-generated. Now it doesn't.
That’s the justification, but the EULA incorporates Google’s regular consumer terms; which means what you upload can also be used for advertising and targeting; and basically any purpose whatsoever by Google.
We need to inform everyone that this technology can encode database identifiers and enough entropy to uniquely identify you as an author (or downloader).
They are not spymarks if they don't encode any personal IDs and are merely used to indicate that an image was AI-generated. I don't think Google or OpenAI use SynthID for that purpose.
Come on man, they're both advertising companies. Would you resist the opportunity to build that social graph and detect a known user anywhere on the internet?
Of course. Privacy is a feature that increases their product value. Moreover, they could get into trouble with the GDPR if they secretly included tracking information in their images.
So the obvious move is that marketing materials sing how it’s super private, while actual steganography encodes everything to uniquely identify you. If someone discovers something wave it away (and crack down on pesky whistleblowers), eat the fines if the worst happens.
True, but haven’t they earned that exact reputation already? They did plenty of unethical/dick moves, they don’t seem to have any product ethics divisions, the meme about “don’t be evil” is there for a reason, so… yes, sadly, cynical but also obvious, no?
- Apple. Least of all, but still fits: PR pushes double on privacy, but their interests are not their end-users, they just happen to align on some points as they’re not in adtech business.
- Microsoft. The classic case for getting slaps on the wrist, Gates said one thing he’d do differently is sending lobbyists earlier, or something to that effect, didn’t he?
- Amazon, Netflix, Uber, Airbnb and many more are still all variants of the same story. It’s not a lie that everyone nowadays expects most megacorps to fuck people over if there’s money in that.
That’s the Order of “Feel for It Again”, with oak leaf clusters already, no? Something’s cursed in this industry, every company that sells software to individual people ends up the same when they become gigantic and endowed by wealth and power, even if they were decent in their early days. They all become those blind heralds of paperclip^W shareholder value(tm) maximizers, and I’m finding myself struggling looking for an exception.
Am I to believe this time it’s going to be any different, to set those - not baseless, I’d say - cynical expectations aside? Any signs there’s a change?
> Moreover, they could get into trouble with the GDPR if they secretly included tracking information in their images.
Do you think that matters to Google? They've been fined repeatedly for violating GDPR already. They don't care about breaking the law if it gets them what they want. They've been found guilty of breaking the law in many countries, including the US. They've easily been able to afford every fine and still come out massively profitable. Google is above the law and they know it.
>I don't think Google or OpenAI use SynthID to include personal data.
Why? I assume by default they are uniquely identifiable, because it just makes sense for them (tracking misuse at the very least), it's trivial to implement and trivial to hide or plausibly deny.
I don't think it's trivial implement. Encoding more bits is harder or more brittle, and not trivial to hide. One could just ask for a completely white image. Any image distortions must then be due to SynthID. If the distortions differ for different accounts, that's strong evidence for varying watermarks.
You can't stop people from using steganography, but when they offer it as a feature to track people you can at least reject their preferred marketing term and call it by a name that reflects what it really is.
I'm confused why no one came up with this terminology for stenographic watermarks before. Now that there's an actual prosocial use for them (helping encourage clear labelling of AI-generated content), suddenly people are coining negatively-loaded terms for it, even though the technology has been in use for nefarious purposes for ages.
It's presumably so they can rate-limit people who are trying to reverse-engineer or otherwise strip it (e.g. iteratively tweaking until it stops getting detected)
How hard can it be to download a set of real images and generated ones in order to train a model to detect and strip the watermark with minimal perceptual difference?
> iteratively tweaking until it stops getting detected
I don't think that dodgy folks have any issue with registering thousands of IDs. I know that I used to regularly get approached by these Chinese companies that were selling good reviews of my free apps. They did this by having thousands of legit AppleID accounts that would download and rate the app.
I haven't been approached by one of these in a long time. I guess Apple figured out how to put the kibosh on them.
OpenAI's tool is worse though because it doesn't detect SynthID from non-OpenAI models. I just tried it with various images created by Imagen / Nano Banana.
Given that it's an ad company, they want something to connect what you're doing to the rest of their data, and they couldn't possibly keep the old image search results there if they want people to use this.
I worry we’ll have to approach this the other way around: verify that photos came from a camera, using hardware support like Apple’s Reference Image, rather than try to detect every AI generated one.
In many situations, photos are evidence. AI tools make convincing fakes, such as images of defect product.
There are ways to watermark text generated by an LLM, but i am curious about if and how they are doing it to STT services.
If i say "The cat is on the mat", and the STT writes that down, the text is still technically transcribed by an ai. Is "transcribed" included in the wide definition covered by "generated"? well it seems it depends who you ask to. IANAL so i can't tell.
That paper explicitly states that the implementation is proprietary and the paper is not intended to describe the implementation itself. The paper focuses on the design considerations, technical challenges, and lessons learned from developing and deploying SynthID at scale. It explicitly omits critical implementation details such as the neural network architecture, training process and the loss functions used. The paper is really focused on deployment, not on SynthID's actual implementation.
It's a real shame Google isn't more transparent about how it actually works, and doesn't provide any mechanism for classifying images in bulk or offline.
They don't want you to know, because they're the baddies. Imagine how much money they can get from advertisers if they're able to identify every single piece of code, reddit thread, email, GitHub readme that you've ever written based on your secret ID. They're creaming themselves just thinking about it.
"Excellent work acquiring that outlook data Anat, now let's cross check the defunct company emails against YouTube videos edited with Google PrivateEditAI™ to figure out what the social security number of this YouTube account is."
So your theory is that i'm going to generate code with google AI, but google will secretly embed my watermark into it, then scrape the internet looking for text with my watermark in it, then put it all together to form a profile of me? Wouldn't it be easier to form a profile of me based on my conversation history in google AI apps?
Ah but that's the genius of the scheme. Every single one of those providers will detect your secret ID and refuse the request. And sneak their own one in for good measure.
Finally, the previous implementations were very silly! OpenAI had a nice tool, but it only detected their own watermarks, and Google's process was "upload the image to Gemini and ask if it's AI generated", which seemed like a perplexing waste of tokens and breath.
(While a sibling comment points out putting the image through Google Image Search as an alternative, I don't remember this being signposted in the support article I've read, so I unfortunately didn't know about it)
The “ask Gemini” thing was so bad, because it made people think that worked with other chatbots. I know some smart, well-informed people who have been under the impression that they can ask Claude if something is AI-generated and get an accurate answer!
If I go directly to the URL it wants me to agree to some stuff before I even know what the service is. I had to come to these comments to figure that out (without agreeing to anything first).
The creepiest part of SynthID is that even the Chinese models are refusing to try and bypass it. Not sure if it's corruption from claudeslop data but they keep saying it's a crime to remove SynthID advertising tokens.
>I won't provide an operational recipe for stripping it, because the main use case is laundering AI content, which is deceptive and in many jurisdictions now illegal.
Is there an open standard or something for people generating images to encode them or is the standard private and only shared with frontier model builders? That's a shame if latter. But pretty cool standardizing technology.
I tested about 8 pictures. All 8 were made with OpenAI and Google. 2 were altered by and had text and picture overlays. The 6 didn't and SynthID caught them. The 2 altered passed. Interesting!
I hate that Google don't have an API or open library to detect gemini images, unless you're enterprise. Create a problem then charge API access to get the solution.
82 comments
[ 34.4 ms ] story [ 242 ms ] threadEven Google themselves previously offered a no-auth way (just very niche): if you uploaded an image to Google Image search, and went to "About this image", it would show if the image was Google AI-generated. Now it doesn't.
https://brand.io/article/spymarks/
We need to inform everyone that this technology can encode database identifiers and enough entropy to uniquely identify you as an author (or downloader).
This extends to other forms of media as well.
- Google. The canonical “don’t be evil” meme origin.
- Meta. Adjacent “they trust me, dumb fucks” meme origin.
- Apple. Least of all, but still fits: PR pushes double on privacy, but their interests are not their end-users, they just happen to align on some points as they’re not in adtech business.
- Microsoft. The classic case for getting slaps on the wrist, Gates said one thing he’d do differently is sending lobbyists earlier, or something to that effect, didn’t he?
- Amazon, Netflix, Uber, Airbnb and many more are still all variants of the same story. It’s not a lie that everyone nowadays expects most megacorps to fuck people over if there’s money in that.
That’s the Order of “Feel for It Again”, with oak leaf clusters already, no? Something’s cursed in this industry, every company that sells software to individual people ends up the same when they become gigantic and endowed by wealth and power, even if they were decent in their early days. They all become those blind heralds of paperclip^W shareholder value(tm) maximizers, and I’m finding myself struggling looking for an exception.
Am I to believe this time it’s going to be any different, to set those - not baseless, I’d say - cynical expectations aside? Any signs there’s a change?
Do you think that matters to Google? They've been fined repeatedly for violating GDPR already. They don't care about breaking the law if it gets them what they want. They've been found guilty of breaking the law in many countries, including the US. They've easily been able to afford every fine and still come out massively profitable. Google is above the law and they know it.
Why? I assume by default they are uniquely identifiable, because it just makes sense for them (tracking misuse at the very least), it's trivial to implement and trivial to hide or plausibly deny.
How hard can it be to download a set of real images and generated ones in order to train a model to detect and strip the watermark with minimal perceptual difference?
I don't think that dodgy folks have any issue with registering thousands of IDs. I know that I used to regularly get approached by these Chinese companies that were selling good reviews of my free apps. They did this by having thousands of legit AppleID accounts that would download and rate the app.
I haven't been approached by one of these in a long time. I guess Apple figured out how to put the kibosh on them.
Given that it's an ad company, they want something to connect what you're doing to the rest of their data, and they couldn't possibly keep the old image search results there if they want people to use this.
More detail at https://deepmind.google/models/synthid/
For those who, like me, were hoping it was a vision model to identify synthesizer models from photos of concerts and music studios!
In many situations, photos are evidence. AI tools make convincing fakes, such as images of defect product.
how is "abc" different from "abc" generated by LLM
https://www.youtube.com/watch?v=kVXp6UNVPTo
This is the best SynthID write-up I've found so far: https://fyx.me/articles/attempting-model-extraction-of-googl...
It covers how it actually works (probably), and how to train your own classifier for it, with some seemingly decent results.
"Excellent work acquiring that outlook data Anat, now let's cross check the defunct company emails against YouTube videos edited with Google PrivateEditAI™ to figure out what the social security number of this YouTube account is."
> classifying images in bulk or offline
You've described exactly the elements spammers and fraudsters need to be able to defeat this mechanism.
Hey Gemini, find a synonym for every second adjective. Replace in text.
Hey Grok, find a synonym for every third proper noun. Replace in text.
Hey …
Too short for watermarking but point taken of course.
Probably more like
https://deepwalker.xyz/blog/evaluating-synthid-watermark-rob...
https://help.openai.com/en/articles/8912793-provenance-signa...
There is rate limit though
(While a sibling comment points out putting the image through Google Image Search as an alternative, I don't remember this being signposted in the support article I've read, so I unfortunately didn't know about it)
https://www.vals.ai/blogs/ai-detection-benchmark
>I won't provide an operational recipe for stripping it, because the main use case is laundering AI content, which is deceptive and in many jurisdictions now illegal.