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After the launch of ChatGPT, the Pandora box opened. We are now observing a technological shift in the ways we do work. People are creating websites, apps, and even writing novels using ChatGPT.
With all the hype and introduction of AI generative tools, we have seen a rise in bad actors. If you are following the latest news, you must have heard that ChatGPT has passed the Wharton MBA exam. There is a whole list of exams passed by ChatGPT, from medical to a law degree – List: Here Are the Exams ChatGPT Has Passed so Far.
Apart from exams, students are using it to submit assignments, writers are submitting generative content, and researchers are producing high-quality papers just by typing prompts.
To counter the abuse of generative content, I am introducing you to 5 free AI content detector tools. You can use them to check the validity of the content and improve your SEO ranking.
GPTZero is designed by Edward Tian, a Princeton senior, to detect writing generated by ChatGPT. The creator has seen that the technology was used by students to cheat on assignments, so he came up with the safeguard.
Image from GPTZero
The web-based app is quite simple. You can either paste your text or load the pdf, docx, and txt files. With a single click on the “GET RESULTS” button, you can find the summary, average Perplexity, and Burstiness score. Furthermore, it will highlight the text that is likely to be written by AI.
Image from GPTZero
Note: in case of content written entirely by AI, you won’t see highlight text.
You can also try Streamlit demo of the app.
OpenAI GPT2 Output Detector is developed by OpenAI and hosted on HuggingFace for users to freely check the content validity. It can detect text generated by ChatGPT, GPT3, and GPT2. The application is using the GPT-2 output detector model based on the Transformers.
Image from OpenAI GPT2 Output Detector
To check the content validity, just copy and paste the text, and it will automatically show you the Real/Fake percentage.
I have been using it for a few days, and I think it is fairly accurate in detecting all kinds of AI text generation.
Hello-SimpleAI ChatGPT Detector consists of three versions to detect text generated with ChatGPT.
- QA version: requires both questions and answers to check if it was generated by ChatGPT. On the backend, it is using a PLM-based classifier.
- Sinlge-text version: required long text to detect text generated by ChatGPT by using PLM-based classifiers.
- Linguistic version: detects ChatGPT based on linguistic features.
Image from Hello-SimpleAI
In my opinion, the most accurate is the Linguistic version. You need to provide the text and click on the predict button to see the results. The application will show results from two different models GLTR and PPL. You can read more about it on the chatgpt-comparison-detection project.
Contentatscale AI Content Detector is the tool that I frequently use for quality assessment. It is fast, simple, and accurate. The AI Content Detector allows users to receive the Human Content score by pasting the text.
Image from Contentatscale
Note: to get accurate results try to paste a small chunk of the text (150-200 words).
Writers AI Content Detector is similar to Contentatscale. It requires either the URL of the page or text to calculate the “Human-Generated Content” score. It is fast and fairly accurate.
Image from Writers AI Content Detector
Note: you have a limitation of 1500 characters, so try to paste a small chunk of text to generate the score.
With the rise of AI generative tools, we have seen the rise of AI detector tools. At this stage, they are not accurate in detection code snippets and mixed text (Human +AI), but in the future, you will see a lot of companies adopting detection tools to increase quality and improve productivity.
In this post, we have learned about the 5 best tools for detecting AI generative text. These tools are fast, reliable, and simple. You just have to paste the text to receive the results.
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Abid Ali Awan (@1abidaliawan) is a certified data scientist professional who loves building machine learning models. Currently, he is focusing on content creation and writing technical blogs on machine learning and data science technologies. Abid holds a Master’s degree in Technology Management and a bachelor’s degree in Telecommunication Engineering. His vision is to build an AI product using a graph neural network for students struggling with mental illness.