How to identify AI-written text 6 working tools

Team TeachWiki

The consequences of using text generated by a neural network are unpredictable. There is a risk of losing positions in search results, reader dissatisfaction, and also the possibility of receiving a complaint about plagiarism.

Artificial intelligence is reaching new heights every day. The AI's abilities are truly amazing. Chat GPT and its analogues have taken over the Internet - with their help they write not only articles, but also diploma and term papers, texts for advertising and greeting cards. Quite successful at the same time.

But this is only one side of the coin. In addition to convenience and saving resources, technology creates many problems. They cause dissatisfaction with authors whose materials the algorithms use as sources. They undermine trust in students, copywriters, and agencies: doubts arise that the texts were written by a person.

Moreover, Google ranks sites with low-quality content worse, and this is precisely what is most often obtained as a result of generation in AI services.

In order to avoid unpleasant consequences and ensure the quality of the work, we offer a set of tools for checking text for writing using a neural network.

  1. GPTZero
  2. A simple but effective application that will help you recognize robot-created material. All you need to do is paste the text into a special window or upload a file in .pdf, .docx or .txt format.

    The service was developed for teachers to check students' homework. Lets you verify that they wrote them themselves.

    GPTZero was trained using human-AI paired text datasets. According to developer statistics, in 99% of cases the text is recognized correctly.

    TechCrunch called the service one of the most accurate AI content detectors. To check small articles up to 5 thousand characters, the free basic version is sufficient.

  3. Content at Scale
  4. The service was created by Justin McGill, an entrepreneur with over 15 years of experience in SEO and content marketing. Thanks to special algorithms and training based on billions of characters of real texts, the tool can accurately predict the most likely variants of words that the AI will use.

    The test result is displayed according to three indicators - predictability, probability and pattern. The right window displays phrases that are supposedly created by the bot. Yellow, orange and red fills indicate the likelihood that the text was written using artificial intelligence tools.

  5. Giant Language Model Test Room
  6. Not the simplest, but quite a detailed tool that allows you to check text against a neural network. The algorithm analyzes the text based on a huge database and identifies words in the text that are among the top 10, top 100 or top 1000 predictable words. The more matches, the higher the likelihood that the text was generated by a robot.

    True, the algorithm was developed for texts of the GPT-2 standard; the tool is not very suitable for checking content in later formats - GPT-3.

  7. GPT-2 Output Detector
  8. The service identifies content written using GPT-2 algorithms. A fairly simple tool that determines the percentage of probability of a text being written by a neural network.

    The algorithm works on the basis of the RoBERTa language model - this is an improved version of BERT, which analyzed 160 GB of text for preliminary training and provides fairly accurate content verification results.

  9. Writer
  10. It is convenient because you can not only add text, but also provide a link to it. The tool reads content from a website page and produces the result of the probability of text being written by a person or a neural network. In the free version you can check up to 1500 characters.

    Larger texts can be processed using API integration. In this case, you can check up to 500,000 words per month.

    The special thing about this AI text checking tool is that it is natively capable of generating content itself. Thus, it uses more in-depth algorithms and constantly improves text analytics.

  11. CrossPlag
  12. To check text for artificial intelligence, a combination of machine learning algorithms and natural language processing methods is used. The tool is trained to learn the patterns and characteristics of different forms of writing and can easily detect them. As a percentage, it shows the probability that the text was generated by a neural network.

Is Artificial Intelligence So Terrible?

On the one hand, AI technologies are our best assistants. They allow you to scale content and save a significant portion of resources. The trend is firmly gaining ground in the modern world and is designed to make our lives and routine processes at work easier.

At the same time, the consequences of using text generated by a neural network are unpredictable. There is a risk of losing positions in search results, reader dissatisfaction, and also the possibility of receiving a complaint about plagiarism.

In our work, we regularly use tools to ensure that the content is unique and truly written by the author himself.