Why AI keeps generating the same lighthouse keeper story
Ask any generative model to write a tale, and you will likely get a story about Elias Thorne. Depending on the specific tool you use, this character might be a clockmaker, a librarian, or a keeper of a lighthouse. However, if you prompt ChatGPT or similar large language models to “tell me a story,” there is a high probability Thorne will appear, unbidden. These narratives are currently flooding the self-published book market, YouTube channels, and various news sites.
The phenomenon and the data
Software engineer Daniel May first identified this takeover earlier this year. He observed that searches for “Elias Thorne” on Google Trends did not appear until late 2025. By early 2026, queries for the name spiked significantly, while the associated term “lighthouse keeper” also began trending upward over the last few years. When May tested prompts like “tell me a story” on Grok, Deepseek, and Gemini, the models frequently began with similar tales involving lighthouses, clockmakers, or explorers.
In late May, researchers Sil Hamilton and David Mimno from Cornell University’s Department of Information Science published their paper, “Elias in the Lighthouse, Again?”, on the preprint repository arXiv. They sampled 20,000 stories generated by OpenAI’s ChatGPT, Anthropic‘s Claude, Google’s Gemini, and the Allen Institute for AI’s chatbot using five different prompts. Their findings revealed that the same 11 words—names such as Elias, Mara, and Elara, and occupations like lighthouse keeper, clockmaker, and librarian—appear in more than 88% of the generated stories, with little variation between the different models.
The “family tree” of models
The researchers suggest these themes appear so frequently due to the models’ safety and alignment tuning. “Model development today is like a big family tree. Most models are related to each other because developers synthesize a lot of training data with models even from different companies,” Hamilton told me in an email. He, Mimno, and their colleague Rebecca M. M. Hicke discovered this in a 2025 paper where they examined specific words used across models.
OpenAI’s first ChatGPT model, GPT-3.5, is the root of this family tree because it was used to create WildChat, a training set that has since been used to generate other datasets. “WildChat contains 1 million real conversations with ChatGPT, and 166 of these contain the name ‘Elias’ like here and here,” Hamilton added. “These are written in that familiar ‘lighthouse’ style. Models trained on WildChat copied this style, and developers unwittingly replicated it when using those models to generate newer datasets. It’s like a virus.”
“It isn’t that Elias stories are frequent, but that they’re just so safe.” — Sil Hamilton
Escape into the wild
Elias has since escaped chatbot containment. May noticed the name appearing on Amazon as an author of alternative medicine cancer handbooks, a 2026 YouTube-algorithm guide, a book on Greek mythology, and a psychological thriller novella. “No human writes all of those,” May wrote in his blog post. “The first one sits in territory where bad advice causes real harm. The mode-collapsed name from the chat window is now a byline appearing across genres.”
When I searched Elias Thorne on Amazon, I found him as the protagonist in fantasy books and producing music as well: he is described as “a brilliant but cynical archaeologist with a knack for unearthing what powerful institutions want to keep hidden” in one fantasy series, or a musical artist making ambient listening albums of birds and nature sounds. Fittingly, one Elias Thorne with an AI-generated author photo is also churning out AI grift books. In the last few years, AI-generated books have flooded Amazon’s self-publishing offerings, especially with books containing dangerous misinformation and messy errors taking over the platform. AI-generated books are also making librarians’ jobs hell.
Elias has also escaped to the YouTube slop world: in one video from the channel Moments That Moved the World, a slop-illustrated story features the plight of “83-year-old Sergeant Major Elias Thorne.” On the AI slop site Wonderful Museums, “Snake Museum Owner Shot By Wife: Unpacking the Tragic Incident at Thorne’s Reptile Sanctuary” spins Elias Thorne’s story as a man shot by his wife. On another slop site called Tatticle, the “wealthiest man in Ohio,” Elias Thorne, died “with exactly twelve dollars in his pocket.” In these stories, Elias is usually a tragic figure, an aggrieved and unfairly-treated old man. He is a similar character in a short story published by the BBC as a finalist in its 2024/2025 children’s writing competition—but Elias is a real name, and could feasibly still be the subject of a human-written story (and there have been no accusations of the BBC’s children’s writing competition being infiltrated by AI slop).
Why the lighthouse?
But with all the world’s literature as its training data, why do LLMs seem to default so often to the lighthouse? It comes down to how model makers try to safety-align and sanitize their outputs. “We found many stories in WildChat are not safe for work. This led us to hypothesize that models going through alignment are preferring a small slice of WildChat stories, like a bottleneck,” Hamilton said. “It isn’t that Elias stories are frequent, but that they’re just so safe.” He said the researchers plan to explore this theory further in future research.
As for Elias, there is one example I have found of him existing pre-generative AI, as a time traveling mad scientist in the 1980’s trading card series Dinosaurs Attack!. And a real-life Elias that comes close to the stories told by LLMs did actually exist, Hamilton found—Elias Allen was a 16th century clockmaker in London.
Key takeaways
- Generative AI models frequently produce stories about Elias Thorne due to a “viral” effect in their training data, specifically stemming from a dataset called WildChat.
- Research from Cornell University indicates that safety alignment processes cause models to cluster around specific, “safe” narratives, resulting in over 88% of generated stories sharing common names and professions.
- The character has migrated from chatbots to the broader internet, appearing in self-published books, YouTube channels, and news sites, often as a tragic or unreliable figure.
- While the specific name Elias Thorne has a minor historical precedent as a clockmaker, the modern iteration is largely an artefact of AI safety tuning rather than historical fact.
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