How to detect if the text was written by ChatGPT or by a human?
As artificial intelligence (AI) language models become smarter, the ability to distinguish human text from AI-generated text becomes more important than ever. How can we tell if the article we just read or the email we received was written by a human or an AI language model? From detecting fake news and ads to protecting against phishing attacks and verifying business management, you can control whether the text is written by humans or a standard AI language like ChatGPT. There are many practical applications.
But how exactly do we capture AI-generated text? What are the criteria used to distinguish between articles written by humans and articles created by artificial intelligence?
In this article, we explore the answers to these questions. By the end of this article, you will better understand how to determine whether the text was written by a human or an AI language model and why it is more important. So let’s get started!
Understanding artificial intelligence language generation
Using AI software to generate text or speech in natural language is the basis for Natural Language Generation (NLG), a subfield of Natural Language Processing (NLP). NLG includes computational linguistics, natural language understanding (NLU), and natural language processing (NLP).
You can use messages created by chatbots and virtual assistants for customer service and content production. You can use it to create written content such as reports, summaries, and explanations.
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NLG systems use machine learning algorithms to learn from big data to create human text.
Recurrent Neural Networks (RNNs) and Transformers are two examples of deep learning methods that are powerful for some NLG techniques.
Most AI languages are neural network-based models consisting of multiple network layers. Nodes are trained in large databases such as Wikipedia or newspapers to learn patterns and relationships between words and sentences in human language. After training, the AI language model can generate new text by predicting the next word or phrase based on the context of the previous word.
ChatGPT is OpenAI’s native language model based on GPT-4 (now!), is one of the smartest tools. The system is trained on large amounts of data so that it can understand and produce words that resemble human speech. In other words, ChatGPT is a computer used to talk to people, answer their questions, give them information, and create chatbots and virtual assistants.
Discussion The GPT is also smart enough to pass a high school leaving exam, but not very high. The powerful AI chatbot tool recently passed the bar exam and board exam.
Discussion GPT and other AI models have raised concerns about their abuse due to their human-like text generation capabilities. Elon Musk has expressed his displeasure with OpenAI since leaving the OpenAI board of directors in February 2018, resulting in an open letter urging the organization to suspend AI work on powerful machines again. However, despite some concerns, Musk has been an advocate for the development of smart tools like ChatGPT, recognizing their great potential.
Determining whether text was written by a human or a machine is therefore a growing challenge, but it can help prevent the spread of misinformation and malicious content, particularly in journalism, cybersecurity and finance.
Risks of AI-generated text
Researchers have tried various methods to analyze AI-generated text. This is important because NLG models have recently improved the machine’s ability to produce discrete, manageable and quality paper. But the ability to generate unique, manipulable, human text with unprecedented speed and efficiency leads to abuse of the NLG model such as phishing, lack of information, analysis. Counterfeit products, academic dishonesty, and toxic spam are more difficult to detect. To maximize the benefits of NLG technology while minimizing harm, trusted AI needs to address the risk of abuse.
The use of illegal language patterns is common in the real world.
An AI discussion involves an AI researcher creating a computer that can type like a real human on a forum called 4chan. Users of the newspaper cited the program creating multiple messages, including violence, on the board to talk about negative and destructive things, according to the data report. It allows the program to be downloaded and viewed, but many sites are prohibited from using it because it can say something. Many AI leaders – research leaders, CEOs and experts – are considering using this model.
Human Text Detection Techniques
1) Scale AI Detector Content
Scale AI Detector Content was trained using thousands of pages of data. It can scan up to 25,000 characters (approximately 4000 words).
To use this tool, please copy and paste your text into the test before submitting the test. After a few seconds, you’ll see human content (showing how people type text) and the line-by-line transcription of the AI is incredible or obvious.
AI makes predictions by making patterns. AI generators are taught to recognize patterns and produce results that “produce” them. The text corresponding to the pre-existing text will be generated by the AI.
Measure the difference between AI output and human writing through prediction, probability, and model scores. Human writing is unpredictable because it does not follow a pattern.
People’s values are different and more creative. AI typing, on the other hand, only recognizes patterns.
2) Originality.ai
The only illegal AI content detection that works with ChatGPT and GPT 3.5 is Originality (the most professional language tool). It is the best content checker for originality, intellectual property and plagiarism detection. The tool uses GPT-3 and other language models learned from big data to predict content.
To use originality, put the content in the scanner and scan it.
Authenticity saves scans to your account clipboard as opposed to large content. This is great for returning multiple items.
AI looks for a score, not a percentage, to indicate the probability that the chosen spell is AI.
Research Score
According to Originality CEO, normal content below 10% is safe!
You should consider the content as outdated only when 40-50% of the content has AI.
The larger the sample size, the higher the detection accuracy, but accuracy does not mean trust! The more authors you read, the better you can tell if this is true.
Pay attention to missing and imperfections. It would be more accurate to evaluate the author/service over the article rather than the article.
3) AI Content Detector at Writer.com
While the index of undetected AI content is more specific, Writer.com offers a free and straightforward AI content detector. You can scan the text from the URL or enter the text directly on their device to run the scan.
Capture contains 1500 words of AI content that can be viewed at any time for free.
It does a good job of analyzing the text generated by ChatGPT.
4) OpenAI Classifier (by OpenAI)
OpenAI unleashes its language to determine if something is written in artificial intelligence (especially ChatGPT). When in doubt, the company claims you can use its tools to determine if something has been written with artificial intelligence. Although the tool was developed by the same company as Chat GPT, OpenAI claims that only 26% of AI grammar has been determined to be “as if written by AI”.
In this case you can use a classifier. It should contain at least 1000 characters and work better with capital letters.
Texts that are always predictable cannot be reliably verified. This includes music and math, because every answer is always the same. With the launch of the splitter, here are some helpful tips for teachers to try to digest the latest ChatGPT excitement.
5) DetectGPT
The DetectGPT method is based on calculating the (logarithmic) probability of the text. If the LLM is processing text, each token has a different probability depending on which tokens are displayed first. Combine all such events to get the result of the whole text.
Next, the DetectGPT process messed up the text. If the probability of the new text is less than the probability of the old text, the old text is generated by artificial intelligence.
Otherwise, it’s almost done by humans.
6) GPTZero
GPTZero is a simple linear regression model for predicting complex text.
Confusion about the log result of the DetectGPT script mentioned above. The exponent of negative log probability is used to calculate the surprise. The broad language structure learns to increase the ability of the text to reduce negative consequences and reduce anxiety. Therefore, the less complex the text, the less random it will be.
GPTZero then uses the idea that easier-to-understand sentences will be generated by artificial intelligence. GPTZero also shows what it calls the “explosion” of the text, which is another way of showing how bad the text is. Burstability is a measure of the difficulty of understanding each sentence.
Limitations of Detecting AI-Generated Text
While there are methods for detecting AI-generated text, they have limitations, for example:
AI text detectors can be unreliable for short words. Therefore, please make sure that the text is at least 1000 characters.
Sometimes AI text detectors need to be more secure and claim that the text was created by AI, even if it was written by a human.
AI text captures are currently only available in English, although some language models can produce text in multiple languages.
text detectors can detect text created in other languages, but they work best with ChatGPT text.
If people change it later, they won’t be able to capture the AI-generated text.
A good enough AI language model is indistinguishable from human handwriting if the language model has access to lots of data to learn.
Additionally, some AI language models are specifically designed to mimic human behavior and intentionally produce text that is indistinguishable from human handwriting. These are called “enemy” patterns and are very difficult to detect.
Conclusion
In summary, being able to tell whether the text was written by a human or an artificial intelligence language model is important for promoting responsible and ethical use of technology and information. As AI trends evolve, recognition of AI-generated texts will become important in many fields and industries, including journalism, finance, and cybersecurity.
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