OpenAI released its own kryptonite called AI Text Classifier. The ChatGPT detector aims to distinguish AI-generated text from human-written ones after foreshadowing the move in media appearances, like BuzzFeed. The AI Text Classifier has the potential to put a halt to the automated spread of incorrect information, plagiarism, and chatbots pretending to be human. But more progress is needed to reach these objectives. Classification accuracy is low at the moment. It has a 26% success rate, which is not good enough. However, OpenAI believes that it, in combination with other security measures, could help prevent the misuse of AI text generators.
We’ve trained a classifier to distinguish between text written by a human and text written by AIs from a variety of providers. While it is impossible to reliably detect all AI-written text, we believe good classifiers can inform mitigations for false claims that AI-generated text was written by a human: for example, running automated misinformation campaigns, using AI tools for academic dishonesty, and positioning an AI chatbot as a human.
-OpenAI
What is AI Text Classifier? OpenAI’s ChatGPT detector explained
AI Text Classifier from OpenAI is a GPT-3 and ChatGPT detector created for distinguishing between human-written and AI-generated text. According to OpenAI, the ChatGPT detector is a “fine-tuned GPT model that predicts how likely it is that a piece of text was generated by AI from a variety of sources, such as ChatGPT.”
When applied to a corpus of English texts, the technology indicates AI-written material 26% of the time. On the other hand, it misidentified 9% of human-written pieces as being machine-made. OpenAI claims that the technology improves with longer content. Thus it needs at least 1,000 characters to do an analysis. As you can see, OpenAI AI Text Classifier has some limitations, such as:
When applied to brief texts, the classifier performs very poorly (below 1,000 characters), and I t is not rare for the classifier to make a mistake when labeling even longer texts.
- OpenAI’s AI Text Classifier can mistakenly identify human-written content as being produced by artificial intelligence.
- The classifier is best used with English text. It is far less effective in other languages and unreliable in code.
- Extremely predictable text is not reliably identifiable.
- Any text created by an AI can be tweaked to fool a classifier. Although OpenAI’s classifiers can be retrained and updated based on successful attacks, it is still debatable whether the detection has lasting benefits.
- The performance of neural network-based classifiers is notoriously bad when applied to data that isn’t part of the training set. It has been observed that the classifier can be overconfident in its prediction when presented with inputs that are vastly dissimilar to the text in the training set.
OpenAI’s ChatGPT detector was trained using data from 34 different text generators across 5 companies, including OpenAI. This text was coupled with human-written content that was similar but not identical from sources including Wikipedia, websites scraped from Reddit links, and a set of “human demonstrations” collected for an earlier OpenAI text-generating system. (OpenAI acknowledges in a helpful article that it may have mistakenly labeled some AI-written writing as human-written “given the abundance of AI-generated content on the internet.” )
It’s crucial to note that the OpenAI Text Classifier will classify not all texts properly. A minimum of 1,000 characters is required, which is roughly 150-250 words. Since text-generating AI has been found to regurgitate the text on which it was taught, its inability to detect plagiarism is particularly disappointing. Because of its English-forward dataset, OpenAI claims it is more likely to make mistakes when processing text is written by children or in a language other than English.
Despite all its limitations, we can safely say that this tool is still worth a try. Considering that it is out of the hands of the team that developed ChatGPT, it is expected to become more successful in the future.
Do you want to learn how to use ChatGPT effectively and even make money with it? We have some tips and tricks for you! AI prompt engineering is the key to limitless worlds, but you should be careful; when you want to use the AI tool, you can get errors, like ChatGPT is at capacity right now. Yes, it is a really annoying error, but don’t worry; we know how to fix it without switching to ChatGPT Professional.
How to use OpenAI’s AI Text Classifier?
Follow these simple steps to use OpenAI’s AI Text Classifier:
- Go to the AI Text Classifier website and log in.
- Paste the text in the dedicated area.
- The ChatGPT detector has limitations but promising
- Click submit.
We used ChatGPT to write the sample text, and as you can see, we got the result “The classifier considers the text to be likely AI-generated” So, what does “likely” really mean?
OpenAI’s AI Text Classifier estimates how likely it is that the text was produced by artificial intelligence. The outcomes could be anything from:
- Very unlikely
- Unlikely
- Unclear if it is
- Possibly
- Likely
The detector provides a rather ambiguous verdict as to whether or not a certain piece of text was produced by artificial intelligence. It will classify text as “very unlikely” (less than a 10% chance), “unlikely” (10%-45% probability), “unclear if it is” (45%-90%), “possibly” (90%-98%), or “likely” (above 98%) if it has confidence that it was generated by artificial intelligence. So, the ChatGPT detector’s answer is true in this case.
While there are still some debates about artificial intelligence-generated images, people are still looking for the best AI art generators. Will AI replace designers? Keep reading and find out.
What is text classification?
Text classification refers to the process of categorizing and tagging text. It’s a machine-learning miracle that can accurately classify free-form text into rigid categories. Several software systems rely on this method, from sentiment analysis to email filtering.
This endeavor is a supervised learning task because each piece of text is labeled with predetermined categories. Like a veteran scholar, the algorithm must learn from the annotated literature to correctly categorize new text. Text classification has shown to be a game-changer in many fields starting with sentiment analysis, topic labeling, spam identification, and intent detection.
Text classification is a fascinating, well-honed technique that involves just a few key steps. The first step is tokenization, which involves separating the text into individual words and phrases. Then, it uses the elegance of a word embedding technique to transform these tokens into numeric values that provide a glimpse into a higher-dimensional space.
Then it uses these numbers as input for a Machine Learning algorithm, which analyzes the connections between the text and its labels to draw conclusions. Once the algorithm has been trained, it can efficiently categorize untrained text.
There is a fine balance to be struck between the quality of the training data, the method selected, and the parameters used to optimize the model’s accuracy. One way to improve the precision of artistic creation is to tweak its parameters or make use of ensemble techniques.
Welcome to the AI-driven world
Are you new to artificial intelligence? Don’t worry; there’s still time to hop on the AI train. Don’t be scared of AI jargon; we have created a detailed AI glossary for the most commonly used artificial intelligence terms and explain the basics of artificial intelligence as well as the risks and benefits of artificial intelligence.
Do you wonder about the effects of artificial intelligence in everyday life? Almost every day, a new tool, model, or feature pops up and changes our lives, like ChatGPT, and we have already reviewed some of the best ones:
- Text-to-text AI tools
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- Source: https://dataconomy.com/2023/02/openai-ai-text-classifier-chatgpt-detector/
