How The ChatGPT Watermark Works And Why It Might Be Defeated

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OpenAI’s ChatGPT presented a way to immediately create material but plans to introduce a watermarking function to make it simple to discover are making some individuals anxious. This is how ChatGPT watermarking works and why there might be a method to beat it.

ChatGPT is an extraordinary tool that online publishers, affiliates and SEOs simultaneously love and fear.

Some online marketers enjoy it because they’re discovering brand-new methods to utilize it to generate material briefs, outlines and intricate short articles.

Online publishers are afraid of the prospect of AI material flooding the search engine result, supplanting specialist posts written by people.

As a result, news of a watermarking function that opens detection of ChatGPT-authored content is likewise expected with anxiety and hope.

Cryptographic Watermark

A watermark is a semi-transparent mark (a logo design or text) that is ingrained onto an image. The watermark signals who is the initial author of the work.

It’s mainly seen in pictures and significantly in videos.

Watermarking text in ChatGPT involves cryptography in the kind of embedding a pattern of words, letters and punctiation in the type of a secret code.

Scott Aaronson and ChatGPT Watermarking

An influential computer system scientist called Scott Aaronson was worked with by OpenAI in June 2022 to work on AI Safety and Positioning.

AI Safety is a research field interested in studying manner ins which AI might pose a damage to people and developing methods to prevent that type of negative disturbance.

The Distill scientific journal, including authors associated with OpenAI, defines AI Safety like this:

“The objective of long-lasting artificial intelligence (AI) safety is to make sure that advanced AI systems are reliably lined up with human worths– that they reliably do things that individuals desire them to do.”

AI Alignment is the artificial intelligence field concerned with making sure that the AI is lined up with the designated objectives.

A large language model (LLM) like ChatGPT can be used in a way that might go contrary to the goals of AI Alignment as defined by OpenAI, which is to create AI that benefits humanity.

Accordingly, the factor for watermarking is to prevent the abuse of AI in such a way that hurts humanity.

Aaronson described the reason for watermarking ChatGPT output:

“This could be practical for avoiding scholastic plagiarism, undoubtedly, but likewise, for instance, mass generation of propaganda …”

How Does ChatGPT Watermarking Work?

ChatGPT watermarking is a system that embeds an analytical pattern, a code, into the choices of words and even punctuation marks.

Material produced by artificial intelligence is generated with a relatively foreseeable pattern of word option.

The words written by humans and AI follow an analytical pattern.

Changing the pattern of the words utilized in created material is a way to “watermark” the text to make it easy for a system to find if it was the item of an AI text generator.

The trick that makes AI material watermarking undetected is that the circulation of words still have a random appearance similar to typical AI created text.

This is described as a pseudorandom distribution of words.

Pseudorandomness is a statistically random series of words or numbers that are not actually random.

ChatGPT watermarking is not presently in usage. Nevertheless Scott Aaronson at OpenAI is on record specifying that it is planned.

Right now ChatGPT remains in previews, which allows OpenAI to discover “misalignment” through real-world use.

Probably watermarking may be presented in a final version of ChatGPT or earlier than that.

Scott Aaronson blogged about how watermarking works:

“My primary project so far has been a tool for statistically watermarking the outputs of a text model like GPT.

Basically, whenever GPT generates some long text, we want there to be an otherwise undetectable secret signal in its choices of words, which you can use to show later on that, yes, this came from GPT.”

Aaronson explained further how ChatGPT watermarking works. However first, it is necessary to comprehend the principle of tokenization.

Tokenization is an action that occurs in natural language processing where the maker takes the words in a document and breaks them down into semantic units like words and sentences.

Tokenization changes text into a structured type that can be used in artificial intelligence.

The procedure of text generation is the maker guessing which token follows based on the previous token.

This is finished with a mathematical function that determines the possibility of what the next token will be, what’s called a likelihood circulation.

What word is next is forecasted but it’s random.

The watermarking itself is what Aaron refers to as pseudorandom, in that there’s a mathematical factor for a specific word or punctuation mark to be there however it is still statistically random.

Here is the technical explanation of GPT watermarking:

“For GPT, every input and output is a string of tokens, which might be words but also punctuation marks, parts of words, or more– there have to do with 100,000 tokens in overall.

At its core, GPT is constantly creating a likelihood distribution over the next token to produce, conditional on the string of previous tokens.

After the neural net generates the circulation, the OpenAI server then in fact samples a token according to that circulation– or some customized variation of the distribution, depending on a criterion called ‘temperature.’

As long as the temperature level is nonzero, though, there will usually be some randomness in the choice of the next token: you might run over and over with the exact same timely, and get a various conclusion (i.e., string of output tokens) each time.

So then to watermark, rather of choosing the next token arbitrarily, the idea will be to choose it pseudorandomly, using a cryptographic pseudorandom function, whose secret is known only to OpenAI.”

The watermark looks completely natural to those checking out the text since the option of words is imitating the randomness of all the other words.

However that randomness includes a predisposition that can just be spotted by someone with the secret to decode it.

This is the technical description:

“To highlight, in the diplomatic immunity that GPT had a lot of possible tokens that it judged equally probable, you might just select whichever token made the most of g. The choice would look uniformly random to somebody who didn’t understand the secret, but somebody who did know the key might later on sum g over all n-grams and see that it was anomalously large.”

Watermarking is a Privacy-first Option

I have actually seen discussions on social media where some people recommended that OpenAI could keep a record of every output it creates and utilize that for detection.

Scott Aaronson validates that OpenAI might do that however that doing so poses a personal privacy issue. The possible exception is for law enforcement circumstance, which he didn’t elaborate on.

How to Discover ChatGPT or GPT Watermarking

Something interesting that seems to not be well known yet is that Scott Aaronson noted that there is a way to beat the watermarking.

He didn’t state it’s possible to beat the watermarking, he said that it can be defeated.

“Now, this can all be defeated with enough effort.

For instance, if you used another AI to paraphrase GPT’s output– well okay, we’re not going to be able to spot that.”

It looks like the watermarking can be beat, at least in from November when the above statements were made.

There is no sign that the watermarking is currently in usage. But when it does enter into usage, it may be unknown if this loophole was closed.


Check out Scott Aaronson’s article here.

Featured image by Best SMM Panel/RealPeopleStudio