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After launch ChatGPT, Pandora’s box opened. We are currently observing a technological shift in the way we work. People are building websites, apps, and even writing novels using ChatGPT.
With all the hype and the introduction of generative AI tools, we’ve seen the rise of bad actors. If you follow the latest news, you must have heard that ChatGPT passed the Wharton MBA exam. There is a whole list of exams passed by ChatGPT from medical to law degree – List: Here are the tests that ChatGPT has passed so far.
In addition to exams, students use it for assignments, writers submit generative content, and researchers create high-quality articles just by writing prompts.
To counter generative content abuse, I present to you 5 free AI content detection tools. You can use them to check content validity and improve your SEO ranking.
GPZero is designed by Princeton senior Edward Tian to detect typing generated by ChatGPT. The creator saw that students were using this technology to cheat on assignments, so he came up with protection.
Image from GPTZero
The web application is quite simple. You can either paste your text or load pdf, docx and txt files. You can find the summary, average confusion and burstity scores with one click of the “GET RESULTS” button. In addition, it will highlight text that is likely to be written by the AI.
Image from GPTZero
Note: for purely AI-written content, you won’t see highlighted text.
You can also try Streamlit demo applications.
OpenAI GPT2 output detector is developed by OpenAI and hosted on HuggingFace so that users can freely check the validity of the content. It can detect text generated by ChatGPT, GPT3 and GPT2. The application uses Output detector GPT-2 model based on Transformers.
Image from OpenAI GPT2 output detector
To check content validity, just copy and paste the text and it will automatically show you the true/false percentage.
I’ve been using it for a few days and I think it’s fairly accurate at detecting all kinds of AI text generation.
Hello-SimpleAI ChatGPT Detector consists of three versions to detect text generated by ChatGPT.
- QA version: requires both questions and answers to check if it was generated by ChatGPT. It uses a PLM based classifier on the backend.
- Single text version: Long text is required to detect text generated by ChatGPT using PLM-based classifiers.
- Linguistic version: detects ChatGPT based on language features.
Image from Hello-SimpleAI
In my opinion, the Linguistic version is the most accurate. To see the results, you need to enter the text and click on the Predict button. The application displays results from two different models GLTR and PPL. You can read more about it at chatgpt-comparison-detection project.
Contentatscale AI Content Detector is a tool I often use to assess quality. It is fast, simple and accurate. AI content detector allows users to receive Human content score by inserting text.
Image from Contentatscale
Note: For accurate results, try to enter a small piece of text (150-200 words).
Writers AI Content Detector is similar to Contentatscale. Either the URL of the page or the text is required to calculate the Human Generated Content score. It is fast and relatively accurate.
Image from Writers AI Content Detector
Note: you are limited to 1500 characters so try pasting a small piece of text to generate a score.
With the advent of generative AI tools, we have seen the rise of AI detection tools. At this stage, they are not accurate in detecting code snippets and mixed text (Human + AI), but in the future you will see many companies using detection tools to improve quality and increase productivity.
In this post, we have learned about the 5 best AI generative text discovery tools. These tools are fast, reliable and simple. Just enter the text to get the results.
If you are interested in learning more about AI, Machine Learning, MLOps and Data Science, follow my social networks. Well thank you.
Abid Ali Awan (@1abidaliawan) is a certified data scientist who loves building machine learning models. He currently focuses 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 telecommunications engineering. His vision is to build an AI product using a graph neural network for students struggling with mental illness.
