AI Text Detector

EyeSift's AI Text Detector is a powerful tool designed to analyze written content and determine the likelihood that it was generated by an artificial intelligence model. Whether you are an educator reviewing student papers, a publisher verifying article originality, or a content manager ensuring authenticity, our text analysis tool provides actionable insights based on advanced linguistic and statistical analysis.

Our text detection system evaluates content across multiple dimensions simultaneously, combining the results into a comprehensive confidence score. Rather than relying on a single metric, we use an ensemble approach that analyzes perplexity, burstiness, entropy, and linguistic patterns to deliver the most balanced and reliable assessment possible.

How It Works

Our AI text detection engine employs four primary analytical methods that work together to assess the origin of written content:

Perplexity Scoring: Perplexity measures how predictable a sequence of words is to a language model. AI-generated text tends to have lower perplexity because AI models generate the most statistically probable word sequences. Human writing, on the other hand, often includes unexpected word choices, creative phrasing, idiomatic expressions, and personal stylistic quirks that increase perplexity. EyeSift calculates perplexity at both the sentence and document level, comparing the results against calibrated baselines for human and AI-generated text.

Burstiness Analysis: Burstiness refers to the variation in sentence structure, length, and complexity throughout a text. Human writers naturally produce "bursty" text, alternating between short, direct sentences and longer, more elaborate ones. AI-generated text tends to be more uniform, maintaining a consistent level of complexity and sentence length. Our burstiness analysis measures this structural variation and flags text with unusually low burstiness as potentially AI-generated.

Entropy Measurement: Entropy quantifies the randomness and information density of text. Our system calculates both character-level and word-level entropy, looking for patterns that deviate from natural human writing distributions. AI-generated text often exhibits characteristic entropy signatures that differ subtly but measurably from human-authored content, particularly in how information is distributed across paragraphs.

Linguistic Pattern Recognition: Beyond statistical measures, our system identifies specific linguistic patterns commonly associated with AI-generated text. These include repetitive transitional phrases, overly structured argumentation, certain vocabulary preferences, and a tendency toward generic rather than specific examples. Our pattern recognition models have been trained on extensive datasets of both human and AI-generated text across a wide range of topics and writing styles.

Supported AI Models

EyeSift's text detector is designed to identify text generated by all major large language models, including:

  • OpenAI GPT-4 and GPT-3.5
  • Anthropic Claude (all versions)
  • Google Gemini
  • Meta LLaMA
  • Mistral and Mixtral
  • Other emerging language models

Our detection models are continuously updated to account for newly released AI models and evolving text generation techniques.

Accuracy Information

Our text detection tool achieves an accuracy rate of approximately 75% to 85%. Accuracy is highest for longer text samples (500 words or more) and for content that has not been significantly edited or paraphrased after AI generation. Accuracy may be lower for very short texts, heavily edited AI content, or text that mixes human and AI-generated passages. We are transparent about these limitations and encourage users to treat our results as probabilistic assessments rather than definitive conclusions.

How to Use

Using the AI Text Detector is simple:

  • Step 1: Paste your text into the analysis field or upload a text document.
  • Step 2: Click the "Analyze" button to begin the detection process.
  • Step 3: Review your results, including the overall confidence score and individual metric breakdowns for perplexity, burstiness, and entropy.
  • Step 4: Use the detailed breakdown to understand which specific factors contributed to the assessment.

Understanding Your Results

Your results include an overall confidence score expressed as a percentage, indicating the likelihood that the submitted text is AI-generated. A score of 0-30% suggests the text is likely human-written. A score of 30-70% indicates mixed signals where the text may contain both human and AI-generated elements or may be heavily edited AI content. A score of 70-100% suggests the text is likely AI-generated. Each result also includes a breakdown of individual metric scores and a written explanation of the key factors that influenced the assessment.

Limitations

It is important to understand the limitations of AI text detection. Very short texts (under 100 words) may not provide enough data for reliable analysis. Text that has been heavily edited, paraphrased, or rewritten after AI generation is harder to detect. Some human-written technical or formulaic content (such as legal documents or scientific abstracts) may exhibit patterns similar to AI-generated text. Results should always be considered alongside other evidence and should never be the sole basis for accusing someone of using AI.

Best Practices for Accurate Results

  • Submit text samples of at least 250 words for more reliable results; 500 words or more is ideal.
  • Provide the original, unedited text whenever possible.
  • Analyze the full document rather than isolated excerpts.
  • Consider running the analysis multiple times on different sections of longer documents.
  • Use the results as one factor in a broader assessment rather than as a definitive judgment.

Supported Languages

EyeSift's text detector currently provides the most accurate results for English-language text. We are actively working to expand support for additional languages, including Spanish, French, German, Portuguese, Chinese, Japanese, and Korean. Detection accuracy for non-English text may vary. Check our updates for announcements about expanded language support.

What Is AI Text Detection and How Does It Work?

AI text detection is the process of analyzing written content to determine whether it was generated by an artificial intelligence model such as ChatGPT, Claude, or Gemini. Our AI text checker measures statistical properties like perplexity, burstiness, and entropy that differ between human and machine writing patterns. As an AI writing detector, EyeSift examines these signals together to detect AI generated text with transparency about confidence levels.

Can AI Detectors Tell If ChatGPT Wrote Something?

Yes, AI detectors like EyeSift can detect ChatGPT writing and identify text from other large language models with 75-85% accuracy. Our ChatGPT detector works by analyzing statistical patterns in word choice, sentence structure, and linguistic features characteristic of AI-generated output rather than human writing. Whether you need to detect ChatGPT writing specifically or check for any AI-generated text, our tool provides detailed breakdowns of the signals found.

AI Detection for Teachers: Maintaining Academic Integrity

EyeSift provides AI detection for teachers who need a reliable, free tool to help evaluate student submissions. Our AI plagiarism checker goes beyond traditional plagiarism detection by identifying whether text was generated by AI models rather than simply copied from existing sources. Teachers can use our AI generated content checker to get a probabilistic assessment that serves as one data point alongside their own professional judgment. We recommend educators use AI detection results as a conversation starter with students rather than as definitive evidence, given that no AI writing detector achieves 100% accuracy.

Related Resources

Explore our other detection tools and in-depth articles to learn more about AI content verification: