avoid-ai-writing

1# Avoid AI Writing
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3Find the patterns that make text read as machine-generated, then fix them without sanding off the author's voice.
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5## What a flag proves
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7These patterns are more common in model output, and people produce them too, especially under deadline, in an unfamiliar genre, or in a second language. The evidence on machine detection cuts both ways. A Stanford audit found seven detectors flagged 61% of TOEFL essays by non-native English writers as AI-generated, against roughly 5% of essays by native writers (Liang et al., *Patterns*, 2023). A 2025 audit found open-source detection unsuitable for high-stakes use, with false-positive rates around 30% to 78% depending on the scenario, while the strongest commercial detector it tested approached zero error on medium and long passages (Jabarian and Imas, BFI Working Paper 2025-116). Adversarial paraphrasing still degrades the detectors it targets, averaging an 87.9% drop in true-positive rate at a 1% false-positive threshold, ranging from 64% to 99% by detector (arXiv:2506.07001).
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9Treat every flag here as a writing-quality signal. This skill classifies nothing, and no flag it raises should decide an academic-integrity, hiring, or attribution question.
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11## Modes
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13**rewrite** (default): flag the patterns, return a clean version with every editable AI-ism removed, summarize what changed.
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