Developer Builds Bilingual AI Detector After English-Only Tools Misread Persian Text

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A developer discovered a critical flaw in mainstream AI content detectors after a pre-ChatGPT Persian blog post was flagged 87% AI-generated by a leading tool. Most detectors rely on statistical signals like perplexity and burstiness that were trained and calibrated almost entirely on English text, making them unreliable for other languages. Non-English writing structures, such as Persian verb patterns and word order, do not match the predictability baselines these tools were built on, leading to systematic false positives. This bias has real consequences in education, journalism, and content moderation, where wrongful AI-authorship accusations can harm real people. In response, the developer built OriginLens AI, a hybrid detector designed to treat Persian and English as equally supported languages.

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