People who use ChatGPT for writing are accurate detectors of AI text (2025)
A recent study reveals that individuals who frequently use ChatGPT for writing tasks are highly effective at detecting AI-generated text. The research involved annotators who analyzed 300 non-fiction articles, achieving a high accuracy rate in distinguishing between human and AI authorship. This finding suggests that experience with language models enhances the ability to identify AI-generated content, even in the face of sophisticated evasion tactics.
- ▪The study involved annotators reading and labeling 300 non-fiction articles as either human-written or AI-generated.
- ▪Annotators who frequently use LLMs misclassified only 1 out of 300 articles, outperforming many commercial detectors.
- ▪The experts relied on lexical clues and also assessed complex text phenomena like formality and clarity.
Hacker News (AI / LLM) files mainly under ai. We currently carry 3,327 of its stories.
Story provenance
Source · retrieval · rights · ranking — open for full record
inspect →
Story provenance
Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.
Record
| Original publisher | arXiv.org |
| Canonical URL | https://arxiv.org/abs/2501.15654 |
| Publication time | Tue, 19 May 2026 02:36:34 +0000 |
| Retrieval time | 2026-05-19T02:44:57.070Z |
| Last seen | 2026-05-19T02:44:57.070Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | RqTXSSR1y6fd |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
Computer Science > Computation and Language arXiv:2501.15654 (cs) [Submitted on 26 Jan 2025 (v1), last revised 19 May 2025 (this version, v2)] Title:People who frequently use ChatGPT for writing tasks are accurate and robust detectors of AI-generated text Authors:Jenna Russell, Marzena Karpinska, Mohit Iyyer View a PDF of the paper titled People who frequently use ChatGPT for writing tasks are accurate and robust detectors of AI-generated text, by Jenna Russell and 2 other authors View PDF HTML (experimental) Abstract:In this paper, we study how well humans can detect text generated by commercial LLMs (GPT-4o, Claude, o1).
…
Excerpt limited to ~120 words for fair-use compliance. The full article is at arXiv.org.
Discussion
0 commentsMore from arXiv.org
