How The ChatGPT Watermark Works And Why It Could Be Defeated

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OpenAI’s ChatGPT introduced a way to automatically develop material however plans to present a watermarking function to make it simple to discover are making some individuals worried. This is how ChatGPT watermarking works and why there may be a method to beat it.

ChatGPT is an amazing tool that online publishers, affiliates and SEOs all at once love and dread.

Some online marketers love it because they’re finding new ways to use it to produce material briefs, outlines and complex posts.

Online publishers hesitate of the possibility of AI material flooding the search results, supplanting expert short articles composed by people.

As a result, 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 or text) that is embedded onto an image. The watermark signals who is the original author of the work.

It’s mainly seen in photos and progressively in videos.

Watermarking text in ChatGPT includes cryptography in the form of embedding a pattern of words, letters and punctiation in the form of a secret code.

Scott Aaronson and ChatGPT Watermarking

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

AI Security is a research field interested in studying manner ins which AI may present a damage to humans and creating methods to avoid that type of unfavorable disturbance.

The Distill scientific journal, including authors connected with OpenAI, specifies AI Security like this:

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

AI Positioning is the expert system field concerned with ensuring that the AI is aligned with the intended goals.

A big language design (LLM) like ChatGPT can be utilized in a way that may go contrary to the objectives of AI Positioning as defined by OpenAI, which is to produce AI that benefits humanity.

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

Aaronson described the factor for watermarking ChatGPT output:

“This could be useful for avoiding scholastic plagiarism, clearly, however also, for example, mass generation of propaganda …”

How Does ChatGPT Watermarking Work?

ChatGPT watermarking is a system that embeds a statistical pattern, a code, into the options of words and even punctuation marks.

Material developed by artificial intelligence is generated with a fairly foreseeable pattern of word option.

The words composed by human beings and AI follow an analytical pattern.

Changing the pattern of the words used in produced content is a way to “watermark” the text to make it simple for a system to detect if it was the product of an AI text generator.

The trick that makes AI content watermarking undetectable is that the circulation of words still have a random look comparable to regular AI created text.

This is described as a pseudorandom circulation of words.

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

ChatGPT watermarking is not currently in use. However Scott Aaronson at OpenAI is on record mentioning that it is prepared.

Today ChatGPT is in previews, which enables OpenAI to discover “misalignment” through real-world use.

Most likely watermarking might be presented in a last version of ChatGPT or faster than that.

Scott Aaronson discussed how watermarking works:

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

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

Aaronson explained even more how ChatGPT watermarking works. However initially, it is essential to comprehend the principle of tokenization.

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

Tokenization modifications text into a structured type that can be used in machine learning.

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

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

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 but it is still statistically random.

Here is the technical description of GPT watermarking:

“For GPT, every input and output is a string of tokens, which could be words however likewise punctuation marks, parts of words, or more– there have to do with 100,000 tokens in total.

At its core, GPT is constantly producing a probability circulation over the next token to create, conditional on the string of previous tokens.

After the neural net produces the circulation, the OpenAI server then in fact samples a token according to that circulation– or some modified version of the distribution, depending upon a criterion called ‘temperature.’

As long as the temperature is nonzero, though, 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 completion (i.e., string of output tokens) each time.

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

The watermark looks totally natural to those checking out the text due to the fact that the choice of words is imitating the randomness of all the other words.

However that randomness consists of a predisposition that can just be found by somebody with the secret to decode it.

This is the technical explanation:

“To highlight, in the diplomatic immunity that GPT had a lot of possible tokens that it evaluated similarly probable, you might merely pick whichever token optimized g. The choice would look evenly random to someone who didn’t know the key, but somebody who did understand the secret could later on sum g over all n-grams and see that it was anomalously large.”

Watermarking is a Privacy-first Service

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

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

How to Detect ChatGPT or GPT Watermarking

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

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

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

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

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

There is no indicator that the watermarking is currently in use. But when it does enter use, it might be unidentified if this loophole was closed.


Check out Scott Aaronson’s blog post here.

Included image by Best SMM Panel/RealPeopleStudio