Cracking the Code on AI Content

As AI-generated content proliferates, the demand for detectors is on the rise. 

Search engines are becoming especially wary of results pages flooded with AI-generated content that’s largely unoriginal and low-quality. To remedy this, several businesses are implementing AI content detectors into their content editing and publishing strategy.

But how do AI detectors work, and how accurate are they? And is it still possible for AI-generated content to bypass them completely? For writers, academics, and even business professionals, knowing what AI detection is is the first step.

How do AI detectors work?

All AI detectors are trained based on language models used by the tools they aim to detect content from. Essentially, the detector looks for clues to determine whether a human could have authored the content.

The detectors look for two specific aspects: perplexity and burstiness. The lower these two variables are, the more likely it is that the text was generated by AI. Let’s dive into the details and examples.

Perplexity

This is a measure of how likely the text is to confuse the average reader—in other words, how predictable or unpredictable the text is. Human-generated content typically tends to be more complex, with creative language choices and occasional typos. In contrast, an AI generator aims for low perplexity and writes in the least complicated manner. 

Let’s look at an example for the sentence “the cat jumped onto the table…”

Burstiness

This is a measure of how varied the sentence structure is, including length changes. Text with little variation in sentence structure is usually an indicator of low burstiness and is more likely to be AI-generated. Language models generally stay around 10 to 20 words per sentence as they predict the most likely word to come next in the sentence. But humans tend to vary their sentences, making them less predictable.

Other detection techniques

AI content detection also uses these three other approaches.

Classifiers

A classifier is an ML model that categorizes data into predefined groups, often trained on labeled examples of human and AI-written text. It identifies patterns like tone, style, and grammar to sort new content.

Classifiers rely on algorithms like decision trees, logistic regression, random forests, and support vector machines to provide a confidence score indicating whether text is AI-generated. However, the results can be imperfect due to issues like overfitting.

Embeddings

Embeddings represent words or phrases as vectors in a high-dimensional space, positioning similar meanings closer together. This numerical representation allows AI to analyze language through:

• Word frequency analysis that flags repetitive patterns typical in AI content.
• N-gram analysis that examines phrase structures, with human text showing more variety.
• Syntactic analysis that analyzes grammar; AI often uses repetitive patterns.
• Semantic analysis that evaluates nuanced meanings, where human writing excels.

Watermarks

OpenAI, the creator of ChatGPT, is developing a “watermarking” system that marks AI-generated text with an invisible identifier that another system can detect. However, the system is still under development, and it’s unclear how it will work or if the watermark will stay after editing. It is a promising technique, but its effectiveness in AI detection is still unknown.

How reliable are AI detectors?

Now that we have addressed how AI checkers work, let’s understand if their findings are reliable.

AI detectors seem to work fairly well at determining whether text was AI-generated or not, even with longer texts, . However, if the text is edited before being run through a detector, the accuracy of the output can diminish since human input has been added to the equation. 

Human-written text can also be misidentified as AI if it has low perplexity and burstiness. Current accuracy levels for the most popular AI tools on the market range from 65% to 85%.

AI content detectors vs. plagiarism detectors

AI content detectors and plagiarism checkers serve different purposes, although they both analyze written content for authenticity and originality. Here’s how they differ:

AI content detectors identify text generated by AI models like GPT. These tools analyze writing patterns, structure, and style to assess whether the content is artificially generated. Their primary focus is detecting AI-generated content rather than checking for copied material. They look for signs like unnatural phrasing, repetition, and other characteristics typical of AI writing. AI checkers are especially useful in academic and professional environments, where verifying originality is essential.

On the other hand, plagiarism checkers detect instances of copied content. They compare the submitted text against a vast database of previously published works to identify any matches. These tools look for borrowed phrases, sentences, or paragraphs to ensure that the writing is original and free from copyright violations. Plagiarism checker tools are essential for confirming that a piece of content doesn’t infringe on others’ work.

Benefits of AI detectors

Using an AI content detector comes with many benefits, even when using it in a business setting. These include:

• Ensuring originality. Unique content is essential if you’re trying to improve your company’s search engine optimization (SEO) and avoid duplicate content penalties. When you have content that’s created by a human mind, it’s difficult for others to exactly replicate your business’s tone of voice and original thinking.
• Increasing customer trust. When customers know that the business is fully responsible for all of the content it’s creating, trust levels can significantly increase. This could lead to increased sales and customer loyalty over time.
• Minimizing reputational risks. AI-generated content can be unreliable and even include unethical suggestions or plagiarized material. If found out, this information could jeopardize the brand’s reputation and put the business at risk.
• Improving content moderation. Detectors can quickly identify fake reviews, spam, or low-quality content, helping businesses maintain the integrity of a publication.

Human or robot? You decide!

An AI content detector can help you examine any written content before it’s published online or within printed materials. Protect your business’s reputation for original and unique content, even if you’re getting a little help from machine learning upfront.

Learn to manually distinguish between machine and mind and check if something was written by AI.