avoid-ai-writing

# Avoid AI Writing

Find the patterns that make text read as machine-generated, then fix them without sanding off the author's voice.

## What a flag proves

These 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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