Our world today has progressed so far and has become so digitalized. The new world is tilting towards AI and robotics, hence why this question might be floating in your head. It’s 2024, and AI-generated content is everywhere. You will find AI tests everywhere, from blogging sites to global news sites.
AI detectors (AI writing detectors or AI content detectors) are tools designed to detect when a text was partially or entirely generated by artificial intelligence (AI) tools such as ChatGPT.
AI detection software is beneficial, for example, to educators who want to check that their students are doing their writing or moderators trying to remove fake product reviews and other spam content.
However, these tools are quite new and experimental, and they’re generally considered somewhat unreliable for now. Below, we explain how they work, how reliable they are, and how they’re being used.
Does AI Detection Software Work? A Clear Explanation On How They Work
AI detectors utilize two types of technology to detect AI-generated content:
- machine learning
- natural language processors.
Both of these allow the AI detector to identify predictable language patterns, syntax, and complexity levels. If the detector recognizes enough of these patterns, it provides a likelihood that the text was generated by AI.
But what do AI detectors compare their findings to? Most AI detectors have been trained on thousands, if not millions, of datasets. This helps the detector identify and compare the text example to pieces of AI-generated content that it has already learned.
So, not only does the detector find patterns in the writing that are indicative of AI generation, but it also compares this to thousands of examples of AI text.
While you might think this is an added layer of security, we must always keep in mind that AI detectors are determining the likelihood that the text was created by AI. A detector can never say with 100% precision that a text has been created by AI or a human.
AI detectors are usually based on language models similar to those used in the AI writing tools they’re trying to detect. The language model essentially looks at the input and asks, “Is this the sort of thing that I would have written?” If the answer is “yes,” it concludes that the text is probably AI-generated.
Specifically, the models look for two things in a text: perplexity and burstiness. The lower these two variables are, the more likely the text is to be AI-generated. These seem like less technical terms, so you might be wondering what these unusual terms mean.
- Perplexity
Perplexity refers to how confusing or complex the text might be for a reader. Literally, what are the chances this will leave the reader perplexed (that is, make no sense to the reader)? Why is this important? Because AI-generated content usually oversimplifies the text and has a low perplexity level.
AI detectors measure perplexity because low perplexity scores indicate that an automated solution wrote a piece of text, whereas a high perplexity score suggests that it’s been written by a human user with more inconsistencies in language choice.
In summary, perplexity is a measure of how unpredictable a text is.
- AI language models aim to produce texts with low perplexity, which are more likely to make sense and read smoothly but are also more predictable.
- Human writing tends to have higher perplexity: more creative language choices, but also more typos.
Language models work by predicting what word would naturally come next in a sentence and inserting it.
- Burstiness
Burstiness has to do with the flow of the sentences and the structure in which they are written. If you’ve ever read AI content, you’ll know that the sentence length and structures do not vary much.
This is what gives it that mechanical and robotic feel when you read it. Human writers tend to use varying sentence lengths. On the other hand, burstiness is used to assess the variance in sentence structure and length, something like perplexity, but on the level of sentences rather than words.
Texts with limited variation in sentence structure and length are referred to as having low burstiness, while texts with more variation between those two variables have high burstiness.
AI-generated text has less burstiness, producing sentences of an average length with a more consistent structure. In comparison, human writers will use sentences of different lengths with less overall consistency.
AI text tends to be less “bursty” than human text. Because language models predict the most likely word to come next, they tend to produce sentences of average length (say, 10–20 words) and with conventional structures. This is why AI writing can sometimes seem monotonous. Low burstiness indicates that a text is likely to be AI-generated.
The Credibility Of AI Detection Software
It is not just all about having AI detection software; the major question and difficulty is whether it is reliable; this lies in the question asked genuinely by individuals, “Does AI detection software work?”. Over the years, this has been a source of battle between those who believe it works and those who doubt the reliability of AI detection software. If an AI detection tool isn’t reliable, what is the point of even using one?
In our experience, AI detectors normally work well, especially with longer texts, but can easily fail if the AI output is prompted to be less predictable or was edited or paraphrased after being generated. Detectors can easily misidentify human-written text as AI-generated if it happens to match the criteria (low perplexity and burstiness). In simple terms, an AI detector will lean towards text being AI-created unless there are imperfections like spelling or grammatical errors. This means that more often than not, false positives also tend to occur on a fairly frequent basis if the human writer has a predictable and consistent style.
Recent research into the best AI detectors indicates that no tool can provide complete accuracy; the highest accuracy that was found was 84% in a premium tool or 68% in the best free tool.
These tools give a useful indication of how likely it is that a text was AI-generated, but it is advised against treating them as evidence on their own. As language models continue to develop, it’s likely that detection tools will always have to race to keep up with them.
Sites like Google have much more powerful AI detectors that can flag when a website or blog has AI-generated content and is trying to earn ad revenue from it.
Unless you put in the time and effort to humanize the work, it is fairly easy for detectors to spot AI text. You should also note that these days people have different tactics to make AI writing less detectable, which in turn will make the text look highly suspicious or inappropriate for the purpose it was intended for.
Common Problems Encountered With Most AI Checkers
Most AI checkers are limited to their datasets, which can lead to varying results when scanning content. These datasets also need to be constantly updated to stay relevant.
Language models are always evolving, and if AI detectors do not update their datasets, they can be using old logic and fail to identify better AI-generated content.
Yet again, AI detectors are not good at identifying AI content that has been altered by humans. This means that if a writer were to use AI text and change it to improve the perplexity or burstiness, the AI detector wouldn’t be able to flag it as AI content.
Now, you might say that if a writer takes the time to edit and alter the content, then it shouldn’t be flagged as AI text. However you might feel about it, the bottom line is that AI detectors can be easily fooled by human writers.
The Importance Of AI Detection Software
Here’s an answer if you have this question at heart: “Why do people bother if a text is AI-generated?” Yes, AI detectors are important for enterprises, academic institutions, and other entities that need to verify that a piece of text is human-written. It discourages laziness and encourages individuals to think and use their smart brains.
For example, academics can use these tools to help check that students are writing their essays; they want to make sure they are original. For marketers, it can be used to ensure that paid-for content has been written from scratch, and recruiters can deploy them to check that candidates’ applications and letters are genuine. For publishers, they want to ensure that they only publish human-written content. Web content writers who want to publish AI-generated content but are concerned that it may rank lower in search engines if it is identified as AI writing.
Conclusion
By now, you must have come to terms with how AI detectors work. The AI detection software consists of tools that rely on large datasets and predictable patterns found within AI-generated content.
While the accuracy of these AI writing detectors is debatable, we must always remember that they only provide the likelihood that AI created the content.