# Do AI detectors flag human writing? 117 of 126 human texts were flagged

Source: https://toolbenchmarks.com/false-positives/  
Tested: 30 October 2026. Publisher: Tool Benchmarks. Data licence: CC BY 4.0.

> Yes, often. We ran seven free AI detectors on 126 human texts that were all published before ChatGPT launched on 30 November 2022. 117 of them (92.9%) were flagged as AI by at least one detector. The most careful detector, Desklib, flagged 6.3%; the worst, TMR, flagged 83.3%.

| Detector | All human text | Academic abstracts | Q&A answers | Encyclopedia articles | Fiction | News reports |
|---|---|---|---|---|---|---|
| Fast-DetectGPT (Qwen2.5-1.5B) | 15.9% | 40.0% | 21.4% | 8.0% | 0.0% | 8.3% |
| Desklib AI text detector | 6.3% | 8.0% | 3.6% | 0.0% | 0.0% | 20.8% |
| Fakespot AI text detector | 34.9% | 12.0% | 39.3% | 40.0% | 12.5% | 70.8% |
| MAGE | 19.0% | 12.0% | 7.1% | 40.0% | 4.2% | 33.3% |
| E5-small LoRA detector | 50.0% | 36.0% | 75.0% | 52.0% | 12.5% | 70.8% |
| OpenAI RoBERTa detector | 4.8% | 0.0% | 10.7% | 4.0% | 4.2% | 4.2% |
| TMR (Target Mining RoBERTa) | 83.3% | 16.0% | 100.0% | 100.0% | 100.0% | 100.0% |

## How we know these texts are human

Every text on this page was published on Wikipedia, Wikinews, Stack Exchange, arXiv or Project Gutenberg before 30 November 2022, the day ChatGPT came out. For Wikipedia and Wikinews we used the article as it stood before that date, and for Stack Exchange we dropped any answer edited after it. AI writing tools existed before ChatGPT, but they were rare in this kind of writing.

## The detectors disagree about which texts look like AI

Only 9 of the 126 human texts passed every detector. Each detector has its own blind spot. Fast-DetectGPT flagged 40.0% of academic abstracts and no fiction. Fakespot and E5-small LoRA flagged most news reports. MAGE flagged 40.0% of encyclopedia articles. Because the false flags fall on different texts, every extra detector you run adds new false positives.

If you check a text with several free tools and treat any "AI" result as a warning, these seven detectors would have flagged 92.9% of genuine human writing.

## Detectors with the most false positives

TMR flagged 83.3% of human texts, including every news report, encyclopedia article, forum answer and fiction passage. E5-small LoRA flagged 50.0%, and Fakespot 34.9%. Each of them catches plenty of AI text too, but a detector that flags this much human writing cannot tell the two apart. The [leaderboard](/ai-detectors/) compares all seven.

## Questions people ask

### Which AI detector has the fewest false positives?

The OpenAI RoBERTa detector flagged the fewest human texts, 4.8%, but it also misses almost all AI text. Among detectors that catch a real share of AI writing, Desklib had the fewest false positives at 6.3%.

### What kind of human writing gets flagged as AI most?

News reports. Fakespot and E5-small LoRA each flagged 70.8% of human news reports, and TMR flagged all of them. Fiction was flagged least by most detectors.

### Can a teacher prove a student used AI with a detector?

Not with these detectors. Even Desklib, the most careful one we tested, flagged 6.3% of human texts, and different detectors flag different texts, so running several makes a false flag more likely, not less.