Editorial Guidelines

Last updated: March 2026

Our Commitment to Accuracy

EyeSift is committed to providing accurate, honest, and transparent AI detection services and content. Our stated accuracy range of 75-85% reflects our actual measured performance across standardized test datasets, not a marketing number. We recognize that AI detection carries real consequences: a false positive can unjustly accuse a student or journalist, while a false negative can allow misinformation to pass as authentic.

How We Evaluate Detection Accuracy

We test our detection algorithms against curated benchmark datasets containing verified human-written text and confirmed AI-generated text from multiple models. Benchmarks are conducted using blind testing with stratified sampling across content types, lengths, and complexity levels. We track metrics including true positive rate, false positive rate, F1 score, and AUC-ROC.

Handling False Positives and Negatives

No AI detector is 100% accurate. We address false positives through confidence scoring, per-section analysis, clear disclaimers, and documentation of known false positive patterns. We openly acknowledge limitations including reduced accuracy on paraphrased content, adversarial prompts, and non-native English writing.

Independence and Conflicts of Interest

EyeSift operates with complete editorial independence. We do not accept funding from AI companies, paid reviews, or affiliate commissions from competitors. When our testing shows a competing tool outperforms EyeSift, we report that finding accurately.

Correction and Retraction Policy

Significant errors are corrected with visible correction notices. In the unlikely event an article's conclusions are fundamentally flawed, we issue a retraction notice. We never silently delete articles. Users can report errors via our Contact page.