The intelligence of check for ai writing

The core of detecting the intelligence of check for ai writing lies in identifying subtle differences in statistical features and language patterns between it and human creations. The current mainstream detection methods are mainly based on the following technical principles:
check for ai writing based on statistical features
Construct a classifier by analyzing statistical measures such as lexical diversity, word frequency distribution, and syntactic complexity of the text. Human writing typically presents richer "noise" and irregularity, while AI generated text exhibits higher "smoothness" and consistency in vocabulary selection and sentence length. For example, the sentence structure of AI text is too neat, the word distribution is abnormal, and the structure template is obvious.
check for ai writing based on end-to-end detection using neural networks
This is currently the most mainstream method, which directly determines the source of text by training binary classification neural network models (such as BERT, RoBERTa). This type of model can capture more abstract and deeper semantic and stylistic features, with an accuracy rate of over 95% on specific test sets. For example, Turnitin's AI detection module is based on this type of technology.
check for ai writing based on watermark or specific prompts
Embedding imperceptible "watermark" patterns in the generated word element probability distribution through specific algorithms, or inputting specific "detection prompts" to observe whether their response patterns conform to typical AI behavior. This method can provide reliable traceability signals.
check for ai writing based on factual and logical consistency verification
Utilize external knowledge bases or logical reasoning models to verify whether the facts stated in the text are accurate and whether the logical chain is self consistent. This method focuses on "content" rather than "style".
Comparison of mainstream detection tools for detecting check for ai writing
GPTZero: Based on the "perplexity" and "suddenness" indicators, the detection rate of ChatGPT generated text exceeds 98%.
Originality. AI: With an accuracy rate of 96%, it is suitable for the fields of SEO and content marketing.
Pen AIGC detection: can analyze the AI generation probability of each text segment and calculate the proportion of the entire text.
Tianmu Intelligent Recognition System: With an accuracy rate of 93%, it supports long text detection and PDF report generation.