How Do AI Detectors Work

How Do AI Detectors Work? AI Content Detector Tips for 2023

With the rise of AI-generated content, many wonder how these AI detection tools work.

Can you rely on them to catch fake content? In this post, we’ll explore:

  • A TL;DR on how AI detectors spot AI-generated text
  • The inner workings of popular AI detection tools
  • Whether these AI tools can accurately detect fake content
  • Tips to manually identify AI-created text yourself

AI-generated content has exploded in the past year. ChatGPT and tools like it can craft eloquent text in the blink of an eye. But, this AI-created content lacks proper depth and originality.

That’s why AI detection tools have entered the scene. These nifty AI tools aim to sniff out content created by other AI.

TL;DR: AI detectors work by analyzing text for patterns typical of AI writing, like repetition, lack of coherence, and unnatural word choices.

But so far, they aren’t 100% accurate in catching AI-generated content.

The key is understanding how these AI detection tools work under the hood. Knowing their limitations allows you to better utilize them in your content process.

Let’s dive in.

AI Thinking Hard

How do AI detectors Work?

When it comes to these newfangled AI detection tools, how exactly do they work their magic?

What clues are they searching for to separate legit human writing from AI-generated content?

The goal is to know the ins and outs of how these tools analyze text on a deeper level.

They rely on sophisticated natural language processing technology to spot the patterns and quirks that tend to pop up in AI-written text.

AI-generated content contains certain giveaways that reveal it wasn’t crafted by an actual human sitting at a keyboard.

From repetitive phrasing to incoherent logic, bot-produced text tends to lack the flow and coherence of the real McCoy.

These tools sift through the text, attempting to look for signs of life (human-written text). But the technology still has kinks to work out.

The detectors aren’t flawless – yet. Let’s look at the HOW and what these tools do to sniff out “fake” AI text.

AI Thinking Hard

What AI Content Detectors Look For

So, what exactly are these AI detectors searching for when trying to identify AI-generated content? What signals tip them off that a piece of text might have come from an AI model rather than a human writer?

AI detectors rely on various techniques to analyze text on a linguistic level. They look for patterns and anomalies that tend to show up in content produced by AI algorithms. Some of the main signals AI detectors hone in on include:

  • Repetitive phrasing or content
  • Lack of coherence and logical flow
  • Overly complex or simplistic sentence structures
  • Unnatural transitions between topics
  • Odd word choices and combinations

By targeting these linguistic fingerprints, AI detectors aim to reliably determine whether a piece of content was human-written or created by an AI model like ChatGPT. But, the technology remains imperfect, with room for improvement.

Now, let’s explore some of the most common techniques used under the hood of these AI detection tools.

Linguistic Analysis

One of the core techniques used by AI detectors is linguistic analysis.

This requires the tool to do some deep detective work to pick up on patterns of typical “artificial intelligence” content generated by an AI.

These tools typically look over elements such as vocabulary, sentence structure, and logical flow. 

The goal is to detect any anomalies that sound like T-800 model 101 wrote the content.

AI-generated content may use unnecessarily complex sentences or make illogical leaps between ideas.

Linguistic analysis allows detectors to compare text against the patterns and conventions a human writer would likely follow when crafting original content. 

This helps separate the AI-created text from authentic human-written work.


Another technique used by AI detectors is classifiers.

These machine learning models are designed to recognize robotic patterns like “Danger Will Robinson, Danger,” that fail to produce that human-written content feel.

The classifiers are fed large samples of both AI and human writing.

By strategically analyzing various samples, these tools quickly learn to pick up on subtle (and some not-so-subtle) patterns, word choices, and anomalies that tend to appear in AI-created content.

Classifiers allow detectors to take a piece of text and determine the probability that it came from an AI model rather than a human writer.

While not foolproof, they aid in the effort to detect and flag AI-generated content being passed off as legit.


Some AI detectors also use embeddings to identify AI-written text.

Embeddings are vector representations of words produced by language models like BERT.

By passing text through an embedding model, detectors can analyze the spatial relationships between words in a multi-dimensional vector space.

Specific patterns emerge in how words relate to one another in AI-generated text.

Comparing these embeddings against text embedded with a human model allows detectors to pinpoint anomalies.

This aids in determining if a piece of text was created using AI versus authored by a human writer.

While experimental, embeddings provide another signal to help some of the tools detect ai-generated content being passed off as legit.


Perplexity is another way these tools are able to detect AI content. 

Perplexity measures how predictable or “normal” a piece of text is based on language models trained on human writing.

AI-generated text often contains odd word combinations and transitions that may have high perplexity scores. This suggests the text came from an AI writing tool rather than a human author.

By comparing perplexity scores against benchmark human scores, detectors can assess the likelihood that a given piece of content was AI-created.

High perplexity indicates abnormal, unpredictable text patterns that differ from human writing norms.

Perplexity provides valuable clues to identify AI-produced content parading as the real deal crafted by a flesh-and-blood writer.


Burstiness refers to the rhythm and flow of language produced in the written content. 

AI-generated language often contains irregular bursts of semantic content rather than the steady flow of ideas seen in human writing.

By carefully analyzing the distribution of semantic density, detectors can identify areas of a text with odd bursts of content. 

This bursty rhythm suggests the text was machine-generated rather than crafted organically by a flesh and blood-human person.

Looking at burstiness allows detectors to pinpoint unnatural language patterns that differ from the natural ebb and flow of ideas in text written by an actual person. 

Can You Rely on AI Writing Detection Tools?

With all these fancy detection techniques, you’d think these AI tools can reliably catch any AI-generated content, right? Well, the reality is that it’s not that clear-cut and dry.

The truth is today’s AI detectors still have some kinks to work out. While they leverage some pretty sophisticated language analysis, these tools can still be duped by advanced AI algorithms.

Again, these ” tools ” are here to help but aren’t quite 100% foolproof. They provide hints to identify shady content, but you still need some old-fashioned human judgment.

Rather than blindly trusting the detectors, it’s wise to combine the AI flags with good old manual reviews.

That allows for the most thorough detection work to keep your content squeaky clean of AI influence.

Let’s take a look at some of the top AI detection tools so we can see their strengths as well as some of their drawbacks.

 The more you understand what they can (and can’t) do, the better you can put them to work for you.

AI Content Detection

Best AI Content Detection Tools in 2023

With all this AI-generated content flooding the web these days, which tools actually make the grade when it comes to catching phonies?

Let’s look over some of the top AI detectors making waves in 2023 so you can decide which one works best for you.

Now, look, before we go over these, just not that none of these tools are flawless.

But the following platforms use some pretty slick AI tech to flag content likely created by bots and algorithms. They provide handy signals to identify text that probably didn’t come from a real live human writer.

As AI capabilities get smarter, these detectors must also step up their game. The leading services aim to stay one step ahead of the latest AI content creation tools. 

By combining multiple detection signals, they strive to give content creators solid assists in catching AI-influenced text.

Let’s dive right in!


One detection tool that has gained a lot of popularity is Originality.AI.

This is an awesome tool that uses advanced AI technology to analyze text on a grammatical and semantic level (it’s also on the expensive side). 

It flags content that was likely generated by AI algorithms rather than written by a human author.

Originality.AI compares submitted text against a vast database of content from known AI sources.

The tool uses fancy language analysis to check if your writing makes sense and flows well. By combining these signals, the tool aims to reliably detect text that was not originally authored by a real person.

While not perfect, Originality.AI provides content creators with helpful context on whether the submitted text contains AI influence. 

It offers both free and paid plans to suit different needs. For those concerned about AI-generated content dilution, Originality.AI is worth a look.

This tool does have a limited free plan, and it is a little pricey when you opt for the pro version.

You also get what you pay for.

From all the tools I’ve tested, this is the best one out there as of RIGHT NOW. 

Content At Scale

Another emerging player in AI detection is Content At Scale.

In addition to this amazing tool detecting AI-generated text, it also provides a powerful AI-powered writing assistant.

Content At Scale combines multiple signals to identify content likely written by AI language models rather than a human author.

This includes analyzing things like originality, coherence, vocabulary, and grammar.

Content At Scale allows you to contrast and compare various pieces of text so you can better identify quality human written work compared to artificially produced gibberish.

This provides helpful context when using AI detection across documents.

For those seeking AI writing support along with AI influence checks, Content At Scale aims to offer an all-in-one solution. 

I would give this tool a hard second in its “AI content detection” capabilities. However, if you want a tool that goes beyond just identifying AI-generated text, Content At Scale is an incredible tool for new bloggers.

Just keep in mind it’s on the pricey end. 

If your bank account can swing it, I say go for it!

GPT Zero

Considering it’s completely free, GPT Zero is alright. 

However, this tool falls short of telling you WHERE the AI-written content exists. 

Free 99 is alright, but if you want to know what you need to fix, there are better options than this.

Again, these are tools to help you detect real from fake. 

I wouldn’t 100% rely entirely on any of these tools.

You should always read and review the content to ensure it makes sense and doesn’t give off “robotic” vibes.

AI Detection vs. Plagiarism Detection: What’s The Difference

With both AI detectors and plagiarism checkers on the scene, it’s important to understand how these two tools differ.

While AI content detectors work to identify text generated by AI algorithms, plagiarism detection looks for content copied from other human sources without attribution.

Plagiarism detectors scan text to see if it matches or highly resembles existing content online and in their databases. AI detectors analyze writing to look for patterns indicative of machine generation.

Both tools are 100% necessary for writing content. 

Plagiarism checkers ensure you don’t use others’ content as your own. 

AI detectors help surface text that may have come from a bot rather than original human effort.

The goal is to use BOTH so you are writing not only human-made content but also original content.

How To Detect AI-Generated Text Manually

While AI detectors can help identify potentially AI-generated text, manual detection still plays a role. Here are some tips for spotting questionable content without relying solely on automation:

  • Look for odd transitions and disjointed flow between topics. AI text often lacks a coherent narrative.
  • Watch for passages that seem too generic, stilted, or cookie-cutter without concrete details.
  • Check if phrases and sentences are repeated. AI text contains more repetition.
  • Assess if the text hits on common talking points without going deeper. AI can regurgitate commonly stated ideas without nuance.
  • Consider whether the writing style fits the author. Does it align with their skills and voice?

The goal is to read closely, looking for patterns that suggest the text was crafted using AI without human effort or finesse.

While AI detectors may help flag suspect content, rolling up your sleeves and checking the content yourself is going best way to ensure it wasn’t written by Arnold’s cyborg.

How To Bypass AI Detection?

With AI detectors gaining steam, some may wonder – how can AI-generated content fly under the radar? While bypassing detection has concerning implications, understanding the tactics can help improve tools. Some potential workarounds include:

  • Using multiple AI models to generate content – Detectors train on specific model patterns, so mixing models makes it harder to detect.
  • Employing heavy editing and rewriting – Extensive human editing after AI generation can mask the original source.
  • Generating only partial portions – Using AI for small blurbs within a larger human-written piece is harder to catch.
  • Splitting content across multiple authors – Distributing AI output across authors can evade author-specific patterns.

The goal for ethical content writers and detectors is stopping misuse, not hiding AI-generated text.

As generators grow more advanced, detectors must improve to detect new evasion tactics.

Maintaining integrity as technologies progress remains imperative


The Future of Content Creation 

As AI capabilities expand, what does the future hold for content creation?

While generators like ChatGPT showcase AI’s potential, human creativity and effort remain irreplaceable.

Rather than replacing humans, ethical AI integration is key. Writers can use AI tools as aids while producing original ideas and analysis.

The goal is augmenting, not automating, the creative process.

As generators improve, content creators are responsible for tracking and labeling AI usage.

Transparency around whether the text is human-written or robotically generated text fosters trust.

AI is a tool, not a shortcut. Truly high-quality content requires human effort.

But used judiciously, AI can complement people to make content creation more efficient, not obsolete. 

Final Thoughts on AI Text Detection

Using AI-generated content is what the future holds for us.

As Darwin says, “adapt or die.”

AI-created content is something that is only going to continue to become more mainstream.

Get comfortable with the tools, learn how to use AI-content generation tools, and remember to run them through a good quality detector to identify whether or not AI COMPLETELY wrote it.

Also, always do a manual check because nothing can replace writing or screening from an actual human being.

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