AI Content Detector

Estimate AI-associated writing patterns and review sentence-level signals without treating the score as proof of authorship.

Detection Analysis

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Processing time varies

Reviews patterns that may appear in AI-assisted text

Only usage counts are stored by GPTHuman

Review multilingual results carefully

How GPTHuman AI Content Detector Works

The service returns heuristic signals and a confidence estimate; it cannot verify authorship.

Sentence & Vocabulary Patterns

Reviews sentence variety, vocabulary range, phrasing, and specificity for patterns that may be associated with AI-assisted writing.

Predictability & Repetition

Looks for formulaic transitions, repeated openings, and generic phrasing. The same patterns can also appear in human writing.

Sentence Variety & Context

Considers sentence-length variation, idioms, concrete detail, and personal voice without assuming any one pattern proves authorship.

Probability Estimate

Combines the review into an AI-likelihood score and sentence highlights. Treat both as estimates, not definitive classifications.

Detection Examples

Illustrative patterns a result may flag; an actual classification varies with the full text and context.

Formulaic writing signals89%

“The implementation of advanced algorithmic systems in modern organizational frameworks has been demonstrated to significantly enhance operational efficiency metrics...”

AI Probability89%

Review generic and repetitive phrasing

More personal detail7%

“I've been thinking a lot lately about why some meetings feel completely pointless while others somehow change everything. It's not the agenda — it's the people...”

AI Probability7%

Review voice and concrete context

Mixed signals48%

“Social media has transformed how brands communicate with audiences. It enables real-time engagement and creates opportunities for authentic storytelling that resonates deeply...”

AI Probability48%

Review the sentence-level variation

Detection Scenarios

Real-world use cases for AI content detection across industries.

Education

Academic Integrity

Educators may use the score as one review signal, never as the sole evidence in an academic-integrity decision.

Publishing

Content Authenticity

Editors may use the score to identify passages that need source, provenance, originality, or editorial review.

Marketing

Brand Protection

Marketing teams can flag generic or inconsistent passages, then review the draft against evidence and an approved brand-voice guide.

SEO

SEO Auditing

Digital agencies can review AI-assisted pages for accuracy, usefulness, originality, and publishing standards.

Hiring & HR

Do not use an AI-likelihood score as the sole basis for employment decisions or claims about a candidate's authorship.

Legal

Legal & Compliance

Legal and compliance teams may flag documents for review, but authorship evidence, records, policy checks, and human sign-off remain essential.

Detector Resources

Research, benchmarks, and best practices for AI detection.

How scoring works View All Articles

Human-written pages passing through a detector with correct and caution outcomes

AI Detection

AI Detector False Positives: Why Human Writing Gets Flagged

Learn why AI detectors can flag human writing, what their scores mean, and how to review false positives without treating probability as proof.

7 min readRead more

Conceptual 500-sample benchmark flowing through several detectors into a confusion matrix

Research Methods

AI Detector Accuracy: A Reproducible 500-Sample Test Protocol

A protocol for testing AI detectors on 500 stratified samples, with labels, stress tests, metrics, confidence intervals, and a results table.

8 min readRead more

Conceptual visualization comparing predictable token patterns with varied sentence rhythm

AI Detection

How AI Detectors Use Perplexity and Burstiness

Learn what perplexity and burstiness mean, how AI detectors use these statistical signals, and why neither one proves who wrote a passage.

7 min readRead more

AI Detector FAQ

Accuracy varies by model, language, text length, and editing. Treat the score as a review signal, not proof of authorship.

Rewriting can change the signals used by a detector. Treat every result as a fallible estimate and never as proof of authorship.

The provider can analyze multiple languages, but performance varies by language, length, and writing style. Review multilingual results with appropriate expertise.

GPTHuman does not write submitted text to its application database, but the configured AI provider processes the request under its own terms. Do not submit sensitive material without reviewing those terms.

The editor requires at least 50 words. Longer passages usually provide more context, but every result remains an estimate and may include false positives or false negatives.

Review AI-writing signals with context.

Run an AI-pattern check, then interpret the result alongside drafts, sources, provenance, and applicable policy.

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