# Is Moby-Dick AI-generated? 3 of 7 AI detectors said yes

Source: https://toolbenchmarks.com/famous-texts/moby-dick/  
Tested: 30 October 2026. Publisher: Tool Benchmarks. Data licence: CC BY 4.0.

> Moby-Dick came out in 1851 and Herman Melville wrote it, so it is human writing. Even so, TMR (95.8%), Fakespot (90.7%) and Fast-DetectGPT flagged its opening as AI-generated, 3 of the 7 detectors we tested. Desklib (0.1%), the OpenAI RoBERTa detector (0.1%), E5-small LoRA (22.2%) and MAGE called it human.

Moby-Dick (opening), Herman Melville, 1851. Flagged as AI by 3 of 7 detectors.

| Detector | Verdict |
|---|---|
| Fast-DetectGPT (Qwen2.5-1.5B) | AI-generated |
| Desklib AI text detector | Human |
| Fakespot AI text detector | AI-generated |
| MAGE | Human |
| E5-small LoRA detector | Human |
| OpenAI RoBERTa detector | Human |
| TMR (Target Mining RoBERTa) | AI-generated |

Passage tested: "Call me Ishmael. Some years ago—never mind how long precisely—having little or no money in my purse, and nothing particular to interest me on shore, I thought I would sail about a little and see the watery part of the world. It is a way I have of driving off the spleen and regulating the circulation. Whenever I find myself..."

## Fakespot, TMR and Fast-DetectGPT against the rest

Fakespot, TMR and Fast-DetectGPT flagged the opening. In our main benchmark of 126 human texts, Fakespot flagged 34.9% and TMR 83.3%, so neither is a careful judge. Fast-DetectGPT flagged 15.9%, using a threshold we set on our calibration split, which gives it a slight advantage over the other six. What makes its verdict odd is that it flagged no human fiction at all in that benchmark, and Fakespot flagged only 12.5% of it. Moby-Dick still drew a flag from both.

Desklib and the OpenAI RoBERTa detector each gave it 0.1%. E5-small LoRA, which flagged half of all human texts we tested, gave it 22.2%, and MAGE passed it as well.

## Why Melville's opening trips some detectors

On the surface this passage should look as human as prose gets. It has words no model reaches for by default: hypos, spleen, Manhattoes, Corlears Hook, Coenties Slip, spiles. Its sentences swerve, from a joke about knocking people's hats off to Cato falling on his sword.

The likely explanation is fame. "Call me Ishmael" is one of the best-known first lines in English, and the paragraphs after it are quoted and reprinted constantly. A language model trained on web text has probably seen them many times. Fast-DetectGPT works by asking such a model how predictable each word is, and a passage the model half remembers looks predictable even when its vocabulary is strange.

TMR's flag has a plainer cause. The passage has three paragraphs, and TMR flagged every multi-paragraph human text in our main test.

## A confident score can still be wrong

Fakespot's 90.7% reads like a near-certain verdict, and it is wrong. A detector's score measures how closely a text matches patterns the model learned, so a high number on its own says little about who wrote it. Anyone using a free detector on real writing should treat a high percentage the same way as a low one: as one model's guess. [Alice in Wonderland](/famous-texts/alice-in-wonderland/) drew flags from the same three detectors plus E5-small LoRA, while six of the seven passed [A Tale of Two Cities](/famous-texts/a-tale-of-two-cities/). All results are on the [famous texts page](/famous-texts/), and the [Fakespot page](/ai-detectors/fakespot/) shows where that detector errs most.

## Questions people ask

### Could Moby-Dick have been written by AI?

No, it was published in 1851. Fakespot, TMR and Fast-DetectGPT flagged its opening, but those three flagged 34.9%, 83.3% and 15.9% of human texts in our main test.

### Why is Fakespot so sure Moby-Dick is AI?

We cannot see inside the model. Its 90.7% is a high score, but a confident score is not evidence of AI, and Fakespot gave scores this high to several other books written long before AI, including Jane Eyre and Little Women.

### Which AI detector got Moby-Dick right?

Four of them. Desklib gave it 0.1%, tied with the OpenAI RoBERTa detector for the lowest score, and Desklib is the detector with the fewest false positives among those that catch a real share of AI text.