LLM Watermarks

Business owners and marketing team leaders have embraced content marketing since the Internet went public. It's one of the most effective and inexpensive ways to reach targeted audiences with information about a company's products, services, and related topics.

The latest trend in content marketing lies in finding ways to create content with as few resources and in as little time as possible. Unsurprisingly, everyone, from entrepreneurs to freelance writers, has joined the automated content creation bandwagon. Many AI marketing software and tools are on the market, and more pop up regularly.

By now, you've likely heard about and tried various AI mobile and web-based apps like ChapGPT, CopyAI, and Jasper. These tools are designed to generate content based on users' specific prompts or questions. The good news is that Google algorithms now support AI-generated copy. In fact, many business owners who embrace AI are finding their websites moving to the top of SERPs. On the other hand, using generative AI can put a damper on your marketing efforts — one of the biggest issues is LLM watermarks.

What Is LLM?

LLM stands for large language models. Gartner defines large language models as "a specialized type of artificial intelligence (AI) that has been trained on vast amounts of text to understand existing content and generate original content." 

LLMs are part of neural networks that work together to decipher input and generate human-like content from vast datasets. For example, LLMs can generate marketing content, summarize meeting notes, translate languages, classify opinions on social media trends, and use chatbots to address customer questions. The ability of these models to emulate and augment humans has improved creativity and productivity across all industries. However, LLMs have their limitations.

Humans have complex cognitive skills (e.g., reasoning, perception, communication, etc.) and draw experience from their surroundings. On the other hand, LLMs have a narrow scope limited to only the surface form of language. This is why LLMs like ChatGPT, GPT-4, and others sometimes output nonsensical and toxic content. In addition, when in the wrong hands, LLMs have the potential to be used for malicious acts, such as creating fake websites (e.g., fake news), exploiting bots on social media (e.g., election campaign manipulation), or using AI for cheating (e.g., academic writing). Lastly, even when content is 100% human-generated, many AI detectors falsely mark the content as containing a percentage of AI-generated text.

What Are LLM Watermarks

You're probably familiar with watermarks used to indicate copyrights and identify the owner of images. LLM watermarks work similarly. In a study on LLM watermarks, researchers defined them as follows: "A watermark is a hidden pattern in text that is imperceptible to humans, while making the text algorithmically identifiable as synthetic." In simple terms, LLM watermarks can prove ownership as well as the authenticity and integrity of the content.

The study proposes using an efficient watermark to make synthetic text detectable while making false positives unlikely. These LLM watermarks can use open-source algorithms, generate text without retraining, be removed only with significant modification, and be detected accurately. An LLM watermark detection algorithm can be made for public or private use to detect and document LLM-generated text to mitigate potential harm.

The Problem With LLM Watermarks

While watermarking offers a simple, effective, and even inexpensive strategy for mitigating potentially harmful LLM-generated text, another recent study investigated the reliability of LLM watermarks. The researchers posed the following question: "How reliable is watermarking in realistic settings in the wild?"

Watermarked text can be modified to suit a user’s needs or rewritten to avoid detection, so they studied the robustness of watermarked text after being rewritten by humans, paraphrased by non-watermarked LLMs, or mixed into hand-written documents. They found that watermarks are still detectable even after human rewrites and machine paraphrasing. However, the strength of the watermarks was reduced. 

You might think AI-generated text detectors fail because they find AI-generated text and human-generated text similar. In actuality, machine-generated text detectors aren't equipped with a mathematical way to distinguish the difference. The study's most interesting finding was that watermarking's reliability turned out to be a function of content length. Human writers were unable to remove watermarks in content of 1000 words or more.

Scripted Helps You Leverage the Best of Both Worlds

Generative AI is the latest tech advancement that's knocking the socks off everyone, from writers and marketers to startup founders and enterprise CEOs. After all, AI content can be the perfect option for efficiency and speed when appropriate. But, LLM and AI-generated text pose a risk that can only be mitigated with LLM watermarking. Unfortunately, AI-text detectors often give false positives, even with human-written text. However, studies have shown that human-generated text can weaken LLM watermarks. With that in mind, it's essential to tap into the subject matter expertise of human writers for thoughtful, high-quality branded content that stands out from the competition. With Scripted, you get the best of both worlds: AI and human content! Registration is fast and easy, so start your free 30-day trial today.