How The ChatGPT Watermark Functions And Why It Could Be Defeated

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OpenAI’s ChatGPT introduced a way to immediately create content however plans to present a watermarking function to make it easy to detect are making some people worried. This is how ChatGPT watermarking works and why there may be a way to beat it.

ChatGPT is an amazing tool that online publishers, affiliates and SEOs at the same time enjoy and fear.

Some online marketers enjoy it because they’re discovering new methods to utilize it to generate content briefs, describes and complex articles.

Online publishers hesitate of the prospect of AI content flooding the search results page, supplanting professional articles composed by people.

Consequently, news of a watermarking function that opens detection of ChatGPT-authored material is also anticipated 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 largely seen in pictures and progressively in videos.

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

Scott Aaronson and ChatGPT Watermarking

A prominent computer researcher called Scott Aaronson was worked with by OpenAI in June 2022 to deal with AI Security and Alignment.

AI Security is a research field concerned with studying ways that AI may pose a harm to people and creating ways to avoid that kind of negative interruption.

The Distill clinical journal, featuring authors affiliated with OpenAI, specifies AI Security like this:

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

AI Positioning is the artificial intelligence field interested in making sure that the AI is aligned with the designated objectives.

A big language model (LLM) like ChatGPT can be used in a way that may go contrary to the objectives of AI Alignment as specified by OpenAI, which is to produce AI that benefits humankind.

Accordingly, the reason for watermarking is to avoid the abuse of AI in a way that damages humanity.

Aaronson explained the factor for watermarking ChatGPT output:

“This could be practical for avoiding academic plagiarism, obviously, however also, 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 created by expert system is produced with a relatively predictable pattern of word choice.

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

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

The technique that makes AI material watermarking undetectable is that the circulation of words still have a random look comparable to regular AI produced text.

This is described as a pseudorandom distribution of words.

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

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

Right now ChatGPT remains in sneak peeks, which permits OpenAI to find “misalignment” through real-world usage.

Most likely watermarking may be introduced in a last variation of ChatGPT or sooner than that.

Scott Aaronson blogged about how watermarking works:

“My primary task so far has actually been a tool for statistically watermarking the outputs of a text design like GPT.

Generally, whenever GPT produces some long text, we desire there to be an otherwise unnoticeable secret signal in its options of words, which you can utilize to show later that, yes, this originated from GPT.”

Aaronson discussed even more how ChatGPT watermarking works. But initially, it is necessary to comprehend the principle of tokenization.

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

Tokenization modifications text into a structured type that can be utilized in artificial intelligence.

The process of text generation is the machine guessing which token comes next based upon the previous token.

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

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

The watermarking itself is what Aaron describes as pseudorandom, in that there’s a mathematical reason for a specific word or punctuation mark to be there but 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 likewise punctuation marks, parts of words, or more– there have to do with 100,000 tokens in overall.

At its core, GPT is constantly generating a possibility circulation over the next token to generate, conditional on the string of previous tokens.

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

As long as the temperature level is nonzero, however, there will generally be some randomness in the option of the next token: you might run over and over with the exact same prompt, 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 select it pseudorandomly, utilizing a cryptographic pseudorandom function, whose secret is known just to OpenAI.”

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

However that randomness contains a bias that can just be spotted by someone with the key to decipher it.

This is the technical description:

“To illustrate, in the diplomatic immunity that GPT had a lot of possible tokens that it judged equally likely, you might simply pick whichever token taken full advantage of g. The option would look uniformly random to somebody who didn’t understand the key, but someone who did understand the secret might later on sum g over all n-grams and see that it was anomalously big.”

Watermarking is a Privacy-first Option

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

Scott Aaronson confirms that OpenAI might do that however that doing so presents a privacy problem. The possible exception is for law enforcement scenario, which he didn’t elaborate on.

How to Detect ChatGPT or GPT Watermarking

Something intriguing that appears 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 defeat the watermarking, he said that it can be beat.

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

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

It seems like the watermarking can be defeated, at least in from November when the above declarations were made.

There is no indication that the watermarking is presently in usage. However when it does enter use, it might be unknown if this loophole was closed.


Check out Scott Aaronson’s article here.

Included image by Best SMM Panel/RealPeopleStudio