15,325
AI content detection
2023-01-31
AI Text Classifier
23
Classifies human vs machine text.
Overview
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The OpenAI AI Text Classifier is a tool designed to distinguish between text written by humans and text written by AI systems. It is based on a language model fine-tuned on a dataset of pairs of human-written text and AI-written text on the same topic.
The classifier is relatively reliable on longer texts, but is known to be unreliable on short texts, code, and language other than English. It is also vulnerable to editing that could evade the classifier and it is not designed to be a primary decision-making tool.
The classifier should be used as a complement to other methods of determining the source of a piece of text. OpenAI is engaging with educators, journalists, and other affected communities to better understand the limitations and impacts of using the AI Text Classifier.
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AI Text Classifier was manually vetted by our editorial team and was first featured on February 1st 2023.
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Pros and Cons
Pros
Works on longer texts
Engages with user communities
Updated model for reliability
Publicly available for feedback
Adjusted confidence for accuracy
Informative for educators, journalists
Continual improvement on detection
Fine-tuned on varied dataset
Potential reveal of false claims
False positive rate regulated
API for web integration
ChatGPT resource for educators
Feedback solicited for improvements
Impact studies on multiple groups
Tuned with different language models
Cons
Unreliable on short texts
Limited to English text
Poor performance on code
vulnerable to text editing
Poor calibration outside training data
Cannot identify predictable texts
Not designed as primary tool
Q&A
What is the principle behind the OpenAI AI Text Classifier?
The principle behind the OpenAI AI Text Classifier is that it is a language model that has been fine-tuned on a dataset of pairs of human-written text and AI-written text on the same topic.
Does the OpenAI AI Text Classifier distinguish between human and AI-written text?
Yes, the OpenAI AI Text Classifier is designed to distinguish between human-written and AI-written text.
Can the OpenAI AI Text Classifier reliably detect short texts?
No, the OpenAI AI Text Classifier is known to be unreliable when it comes to detecting short texts, especially texts below 1,000 characters.
Why is the OpenAI AI Text Classifier considered unreliable for non-English texts?
The OpenAI AI Text Classifier is considered unreliable for non-English texts because it has been trained predominantly on English language texts. It's performance significantly degrades when working with other languages.
Can the OpenAI AI Text Classifier be fooled by editing?
Yes, the OpenAI AI Text Classifier can be fooled by edited AI-written text. This is because any edits can make the AI-generated text appear more human-like, thereby tricking the classifier.
What other methods complement the OpenAI AI Text Classifier?
The OpenAI AI Text Classifier should be used as a complement to other methods of determining the source of a piece of text. It does not mention what these specific other methods are.
Why is the OpenAI AI Text Classifier not a primary decision-making tool?
The OpenAI AI Text Classifier is not a primary decision-making tool because it has various limitations. These include unreliability with short texts, non-English texts, and very predictable texts. Further, it can be tricked by edited AI-text and may confidently label some human-written texts as AI-written.
Who are the potential users of the OpenAI AI Text Classifier?
The potential users of the OpenAI AI Text Classifier include educators, journalists, misinformation researchers, and other affected communities.
How can the OpenAI AI Text Classifier improve mitigations for false claims?
The OpenAI AI Text Classifier could improve mitigations for false claims by distinguishing between human and AI-written text. It can thus raise a flag when AI-generated text is falsely claimed to have been written by a human.
What is the OpenAI AI Text Classifier's accuracy on a challenge set of English texts?
On a challenge set of English texts, the OpenAI AI Text Classifier correctly identifies 26% of AI-written text as 'likely AI-written', and incorrectly labels human-written text as AI-written 9% of the time.
How does the OpenAI AI Text Classifier perform on predicting very predictable text?
The OpenAI AI Text Classifier cannot reliably identify very predictable text. For example, a list of the first 1,000 prime numbers could have been written by either a human or an AI since the answer is always the same.
Can the OpenAI AI Text Classifier be updated and retrained based on successful attacks?
Yes, classifiers like the OpenAI AI Text Classifier can be updated and retrained based on successful attempts to evade the classifier.
What is the training process of the OpenAI AI Text Classifier?
The OpenAI AI Text Classifier is trained by fine-tuning a language model on a dataset of pairs of human and AI-written text on the same topic. Texts are divided into a prompt and a response, with responses generated from different language models.
How does the OpenAI AI Text Classifier perform on different languages?
The OpenAI AI Text Classifier performs significantly worse on languages other than English and is unreliable on code.
Does the OpenAI AI Text Classifier helps in identifying AI-generated misinformation campaigns?
Yes, the OpenAI AI Text Classifier could potentially be used to identify AI-generated misinformation campaigns by distinguishing between human and AI-written text.
Do output predictions differ a lot for texts significantly different from the training data?
Yes, for inputs that are very different from text in the training dataset, the OpenAI AI Text Classifier can sometimes be extremely confident in a wrong prediction.
How does the length of input text affect the classifier's reliability?
The reliability of the OpenAI AI Text Classifier typically improves as the length of the input text increases. This is because longer texts provide more contextual information for the classifier.
What is the intended impact of the OpenAI AI Text Classifier on educators and journalists?
The intended impact of the OpenAI AI Text Classifier on educators and journalists is to enable them to better identify AI-written text, while also recognizing the limitations and impacts of such classifiers.
How is OpenAI gathering feedback and understanding the limitations of the AI Text Classifier?
OpenAI is engaging with educators, journalists, and other affected communities to gather feedback and better understand the limitations of the AI Text Classifier. They have also made a feedback form available for those directly impacted by these issues.
Is there a direct way to interact with or use the OpenAI AI Text Classifier?
Yes, there's a web app where everyone can try the OpenAI AI Text Classifier and see how it labels text.
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