Do you wonder what an AI detection score is all about? If you write, edit, work in marketing, or publish content online, this piece is for you. It will make it clear how to read and use AI detection scores with your team.
Let’s talk about Netus.ai’s AI detector score, what it is, and how to use it.
We’re going to cover several points:
It’s a way to see if writing was done by a person or AI. It gives us a score to show how sure it is.
If it says 60% Original and 40% AI, it means it thinks a human wrote the writing, and it’s 60% sure it’s right.
But it doesn’t mean 60% of the writing is from a person and 40% from AI.
Even if you wrote everything on your own and got a 60% Original score, it doesn’t mean the tool is wrong. It means it’s 60% sure a person did the writing.
Yes, the detector is accurate based on our tests and tests from other groups.
-Our Own Test on Accuracy
-Eight Tests from Others (they found Netus.ai to be the best)
No, the tool doesn’t always get it right. Sometimes, it mistakenly thinks things made by people were made by AI, but this only happens about 1% of the time.
This mistake is known as a “false positive”. False positives are a big hassle when they happen.
We’re working non-stop to make our tech even better, to make these mistakes happen less often.
Sometimes, an AI checker might get it wrong and think a piece of writing came from AI, but it was actually written by a person. We’ve got a free tool for Chrome that helps show clearly how a piece of writing was made—by a person or by AI.
We also offer tips on how to avoid these mistakes and what to do if someone thinks you used AI for your writing.
Netus.ai has different models designed for different needs.
Now, let’s talk about the AI detection models you can choose from:
Lite
Turbo
No, we shouldn’t. When we use a tool to find copied work, it gives us clear evidence that someone has copied. But, when we use a tool to figure out if an AI or a person wrote something, it’s just guessing if it’s more likely one or the other. So, we should not treat finding copied work and spotting AI-written stuff in the same way.
Our AI checker looks at articles in a whole new way, much better and deeper than what’s out there.
It’s super smart at figuring out if an article was written by AI. Want to know more? Check out our detailed article, “Understanding AI Content Checker”. It shares all about our tool. We taught our AI with lots of data from the biggest AI models like ChatGPT, Claude, and Llama.
It’s really good at spotting AI-written parts in articles. Our method is way more detailed and accurate compared to those free AI checkers that might miss a lot.
You asked a good question: “Why did they say my article was written by AI?” To help you understand, we show parts of sentences that our tool thinks probably came from an AI. Note: We can’t just give a simple list of reasons like “here are why your articles seem like they’re written by AI.”
An AI detection score is a way to measure if a text was written by a computer or a person. A tool uses this score to judge how sure it is. For example, if a tool gives a score like “60% AI”, that means it thinks there’s a 60% chance a computer wrote the text.
This tool looks at a lot of things to make its decision. It checks how sentences are put together, which words are used, and if the piece makes sense. Then, it compares this to what it knows about how computers usually write things. Models like GPT-3 or GPT-4 are usually used to make this comparison. But remember, this score is not an exact measure of how much the text is made by a machine. It is more about how sure the tool is of its decision.
Some pieces written by a person may still look like they were made by a computer to this tool. That’s because it only judges based on the patterns it sees in the writing.
Knowing how to use this tool is very useful. It gives you an idea if a text is probably made by a machine. But remember, the tool isn’t perfect. It’s just guessing based on signals it sees in the text. So, it’s always a good idea to be careful when using this score.
Detecting AI-made content isn’t always accurate, despite the tools getting better. From time to time, these detection gadgets mess up. They might not spot text that an AI has written, or they might wrongfully say that a human didn’t write some content, but an AI did instead. Fancy AI models, like GPT-4, trick the detectors a lot because they’re trained to write like humans.
It’s a “false positive” or “false negative” when the detector doesn’t get it right. False positives happen when the detector says that a person didn’t write a piece, but an AI did. This could be because the writing has features that the detector thinks only AI use, like certain repeating patterns or certain types of structured sentences or when the language used is too formal. On the other hand, a false negative is when the detector can’t see the AI writing and instead says it’s written by a person.
For instance, if a real person writes an impressive blog post, it could be said to be machine-written because of certain common phrases used in AI writing. Something like this can create a problem in a setting like a school or work where they need to make sure that the work is real and original. Also, AI creations might be so different and complex that they don’t get spotted at all, meaning that they get wrongly labelled as human-made.
These AI detecting tools keep getting better as we find better ways to train machines and as the AI itself evolves. However, they do mess up with these false positives and negatives, and everyone using them needs to know that they aren’t 100% reliable. Therefore, it’s important to use the AI detection scores along with other methods, instead of just relying on it.
So, let’s say your written material gets wrongly pinpointed as AI-made. No need for alarm. False alarms, though annoying, are a familiar sight, and you can deal with them. First step? Understand why it was flagged. AI surveillance programs usually sift through factors like intricate sentences, choice of words, and style as a whole – which might be seen as “AI-like” even if a person penned it.
Here are some moves to make when your work is wrongfully flagged:
AI spotting and copy-theft tool differences are what we’re going to talk about. Both study an article’s originality but do it differently. Copy-theft is about spotting reused text from other places, while AI detection checks if a machine wrote it.
Copy-theft tools review info from old content, like school papers, web pages, and other released materials. They locate duplicate text. If writing is very similar to text already released, it gets a copy-theft warning.
AI detection works differently. It doesn’t care if text is the same as other released writings. It checks for things hinting a machine burped it out like false-feeling sentence shapes, the same phrases kept on, or too perfect grammar. AI watchers look at speech patterns that might show no imagination or human touch, which can be usual in writing made by a machine.
Knowing these differences is key. Copy-theft detection watches for stolen content, while AI detection checks for text that might not have true human creativity. Both kinds of detections are helpful, but they have different uses and should be applied just right.
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