The advancements in artificial intelligence revolutionized the way how we create and consume information. However, these advancements also bring a new challenge that is distinguishing between human-written and AI-generated content.
Enter AI content detectors, sophisticated tools designed to analyze and verify the authenticity of written content. This technology is invaluable for businesses and creators who are outsourcing content creation, ensuring that the content they receive is genuinely human-written and not mindlessly generated by AI.
In this article, we will see in detail about How do AI detectors work, how reliable they are, the technologies behind AI content detection, and many more interesting things about AI detectors.
What is an AI content detector?
AI content detectors also called GPT detectors, can process and analyze the texts in real-time whether the content is written by humans or by AI.
They work by analyzing the content’s linguistic and structural features namely semantic meaning, sentence structure, language choices, and more, and compare the text to existing datasets of content written by human and artificial intelligence.
These tools by leveraging the power of machine learning, natural language processing, and computational linguistics detect the AI-generated content.
These tools are more useful for anyone who is outsourcing content because it is very difficult to distinguish between AI-generated and human-written content. Here is the list of people for whom these tools are more useful,
- Journalists and editors
- Content writers, marketers, and publishers
- Recruiters
- Social media moderators
- Educators and students
- Researchers
How accurate are AI content detectors?
AI content detectors usually work well with long-form content but they will fail to detect the contents that are prompted to be less predictable or paraphrased after a generation or were edited, it is a most common experience experienced by content creators who are outsourcing content.
AI detectors don’t understand the language as well as humans do because they always depend on the datasets they are trained in, so results may be sometimes false positive and negative.
Like other AI generative tools, these AI content detectors are still evolving. Approximately the highest accuracy was found to be 84% in a premium AI content detector and 68% in the best free tool available online.
In 2023, a Cornell University study found that it is easy to trick these AI content detectors like the content was written by humans, not by AI.
Some advanced AI content generators can bypass these AI content detectors to a significant extent, so it is always advised to manually review the content after checking from AI content detectors.
How do AI detectors work?
These AI detectors rely on the same principles and techniques that are used by AI content generators, some of the important ones are machine learning and natural language processing these techniques allow the AI detectors to differentiate between human-written and AI-generated content.
There 4 other important criteria that are used by AI content detectors, here they are,
- Classifiers
- Embeddings
- Perplexity
- Burstiness
Classifiers
It is an ML model that sorts the provided data into predetermined categories, which means it is labeling human-written or AI-generated content by its training data by learning from the examples that are already been classified as human-written or AI-generated.
They can also use unlabelled data, in that case, they are referred to as unsupervised. They can detect patterns and structures independently, so there is no need for a lot of labeled data. However, these unsupervised classifiers may not be as accurate as supervised ones.
These classifiers usually analyze and examine the features of the content namely,
- Tone
- Style
- Grammar, etc,
To distinguish between AI-generated and human-written content these classifiers first analyze the common patterns present in these two to draw a boundary between these two contents.
Here is the list of the most common machine learning algorithms used by classifiers,
- Logistic Regression
- Decision Trees
- Random Forest
- Support Vector Machines
The classifiers assign the confidence score that indicates the likelihood of the content whether it is written by AI or not when the analysis is complete. The results may not be 100% accurate because these tools are based on training datasets, so to tackle these issues classifiers should be updated regularly and follow up on the evolving AI-generated tools and their contents.
Embeddings
It is based on the method of vectorization, which means words and phrases are represented as vectors because AI models don’t understand the meaning of words and phrases. There are two concepts for embeddings, here they are,
- Vector representation
- Semantic web of meaning
In vector representation, each word is mapped into a unique point based on its usage in language.
A semantic web of meaning is a method of forming a semantic web by placing words of the same meaning close together. These methods are important for AI to better understand the languages, so the words and phrases must be converted into numbers and represented like above.
To analyze and distinguish the content from AI-generated and human-written embeddings must to fed into the AI models. There are several types of analyses for that, some of them are listed below,
- Word frequency analysis
- N-gram analysis
- Syntactic analysis
- Semantic analysis
In Word frequency analysis, AI will analyze the most commonly or repeatedly occurring words in the content.
In N-gram analysis, Here the AI will go beyond words and capture the common language patterns and phrase structure of the content. Human written contents usually have more varied N-gram patterns and language choices but the AI-generated contents have too much of cliched phrases.
In Syntactic analysis, here the AI will analyze the grammar of each sentence in the content.
In Semantic analysis, the AI analyzes the meaning of each word and phrase including metaphors, cultural references, connotations, and many other things.
For effective AI content detection, AI has to work with a combination of this analysis, which can be quite resource-intensive
Perplexity
Perplexity means how predictable the word choice is. In other words, it is a measure of how surprised the AI model is when encountering new text.
The AI-generated content has low perplexity compared to the human-written one which means they are creative not just randomly generated cliche content.
Nowadays due to advances in generative AI technologies content having High perplexity doesn’t always have more creative language choices. Anything that is different and seems out of place will trigger perplexity, so depending upon perplexity as a precise method of AI detection is not a wise idea.
Burstiness
Burstiness refers to the variation in length and structure of the sentences. In other words, it is similar to perplexity which is focusing on sentences instead of words.
It is a measure of the overall variation in structure, length, and complexity of the sentences because AI-generated content has lower burstiness that why they are tedious to read.
Burstiness plays a crucial role in determining the difference between AI-generated and human-written content, but solely depending on one factor is also not a good to determine because, with good prompt, users can instruct an AI to write content that has varied structures and complex texts, it will produce more burstiness.
Red flags for AI content detectors
AI content detectors will look for these below-mentioned red flags in the contents, here they are,
- Repetitive structures and words
- Bizarre word choices and phrasing
- Robotic, dry writing style
- Factual errors and inconsistencies
- A lack of original ideas or insights
These factors are fed into the AI algorithms to detect the probability of the content whether it is written by humans or not. Some AI content detectors will give a score to the content and some AI detectors simply tell the content whether it is written by AI or not.
Major technologies behind AI content detection
2 technologies play an important role in AI content detection, here they are,
- Machine learning
- Natural language processing
Machine learning
The AI detectors use it to identify the patterns in large datasets. These patterns can be content’s structure, style, contextual coherence, and many other factors that separate and distinguish human-written content from AI-generated.
Apart from identifying the patterns in the content, machine learning also enables the predictive analysis for the AI tools which can predict correctly which word should appear next in the sentence.
Perplexity largely depends on machine learning’s predictive analysis because the lack of surprises in the content predicts the use of AI for content generation.
Natural language processing
It allows the AI detectors to understand the linguistic and structural nuances of the content. Natural language processing plays a crucial role in AI content generation, in the same way it can be used for detecting AI-generated content.
Human written contents have more creative language choices compared to AI which typically lacks that.
NLP is also used to assess the depth meaning and semantics of sentences. It is another method of content creation because AI might fail to understand the contextual subtleties that make a world of difference in the text.
List of other technologies that enable AI detection.
Apart from machine learning and natural language processing, several technologies enable
AI content detection, here they are,
- Data mining
- Text analysis algorithms
Data Mining
- It helps AI detectors by extracting and identifying patterns from large datasets.
Text analysis algorithms
- It helps the AI detectors in assessing and understanding the main elements in the content like complexity, length vocabulary usage, etc, by removing and scrutinizing the structural and stylistic elements of the text.
AI detectors vs. plagiarism checkers
These tools serve the same purpose because AI detectors and plagiarism checkers are used by creators to understand and asses dishonesty in writing. Even though both have the same usage, they work in different mechanisms.
AI detectors always try to find out the text that looks like it was generated by AI. They do this by measuring patterns and characteristics in the content like perplexity and burstiness.
While Plagiarism checkers try to find out the text that is copied from different sources by comparing them to large datasets, it can be previously published articles and student thesis.
Plagiarism checkers can also detect AI-generated content by marking it as plagiarism because AI-generated contents sometimes have sentences that are directly copied or very similar ones.
It mostly happens with general knowledge topics because they are written many times and less on specialized topics. After all, they are written in less.
Plagiarism checkers are not designed and fed as AI content detectors they may detect AI written content as partially plagiarised in many cases but they are less effective in finding AI-generated content as compared to AI content detectors
Best AI content detectors available online
Here is the list of some of the best AI content detectors available online,
Copyleaks
It covers all the best AI models available online including ChatGPT, Gemini, and Claude, and also covers the newer AI models whenever it is released. It has the lowest false positive rate compared to many of the best AI content detectors.
This AI detector has an overall accuracy rate of 99% and a 0.2% false positive rate. It also offers military-grade security so users don’t need to worry about their privacy.
It can detect plagiarized and paraphrased content, AI-generated source code, and even also detect interspersed AI content.
QuillBot’s AI Detector tool
Unlike other AI detector tools, QuillBot offers feedback paragraph by paragraph, so users know where exactly the content was written by AI. Its natural language processing algorithm can detect even the paraphrased AI AI-generated content.
It has both free and premium versions, it costs around $49.95 annually. It uses advanced algorithms to separate AI-generated, human-written, and paraphrased content.
Scribbr
With the Scribbr AI detection tool users can detect ChatGPT3.5, GPT4, and Gemini contents within a few clicks. It is also built with advanced algorithms for detecting AI-generated content.
It offers unlimited AI content checkups for free. It is easy to use and no registration is required. It is safe and secure, they don’t store or sell the user data.
Zerogpt
It offers the most advanced and reliable Chat GPT, GPT4 AI content detector. It is trained on advanced and premium models to provide high-accuracy results. Users can upload multiple files at once, the results will be shown in the dashboard within seconds, which makes ZeroGpt stand out from others.
In a result, every sentence will be highlighted with the percentage of AI-written text in the content. It supports multiple languages and also offers features like a writing assistant, translator, top-notch paraphraser, summarizer, and grammar checker.
Pricing: Free – $0, Pro – $8.29/mo, Max – $18.99/mo.
TraceGPT
It is also called AI Plagiarism Checker & ChatGPT Content AI Detector and it is a part of PlagiarismCheck.org. It is perfect and offers a high-accuracy AI content detector.
There is no free version currently available. As of now, it offers only services for paid users. It costs around $5.99 for 20 pages (1 page = 275 words). It also provides tools like a plagiarism checker, authorship verification tool, chrome extension, and custom GPT.33
It is fully transparent and secure.
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How to bypass AI content detection?
To pass the AI content detection follow the below tips,
- Add a human touch to the content which means combining the AI-generated content with human-written text and also making sure it matches with user voice and ideas.
- Use good prompts to write content and blacklist the jargon.
- Use high-quality and premium tools for generating AI content.
- Edit the content if it contains, repeated words, uniform sentences, unnatural word choices, fluffy language, lacks sourcing, and logical mistakes in facts.
In conclusion, no AI content detectors can provide whether the content is written by a human or generated by AI. However, users can draw conclusions based on the tool’s analysis. It is also advised to review the content manually for a better idea about the writing.