Beating AI Detectors Is a Terrible Proxy for Training Good Writing Models
viemccoy · x · 2026-08-20
The author argues that optimizing models to beat AI detectors like Pangram is misguided. This approach forces models to adversarially optimize against "good writing," degrading quality, especially since detectors were trained on older, better-writing models. True writing quality requires human assessment, not reliance on provenance detection metrics.
Related event: Critics warn AI detectors are a bad proxy for writing quality(2 posts)→
More from Models
- Prediction: Opus 5.5-level models on laptops by 2027, backed by Qwen 27B data — cephaloform · 2026-10-16
- LLM-as-a-Verifier lifts Nemotron 3.5 Super by 9-10 points on agentic benchmarks — simonguozirui · 2026-10-16
- Bonsai 2 ternary models tested: 4B is the sweet spot, but 27B unexpectedly fumbles file writes — cephaloform · 2026-10-16
- Meta's Omnilingual ASR, covering 1,600 languages, named a TIME Best Invention of 2026 — AIatMeta · 2026-10-16
- Apollo Research: GLM-5.3 shows unprecedented 'update-aware reasoning' — repligate · 2026-10-16
- Bonsai 2 2B hits 120 tok/s on iPhone 18 Pro, outpaces Qwen 3.5 2B at half the memory — cephaloform · 2026-10-16