GoKawiilPangram Labs' AI-detection tool gains traction among journals, conferences and universities
Pangram, a commercial AI-text detector built by New York start-up Pangram Labs, is being adopted by scientific publishers, computer-science conferences and universities to flag undisclosed AI-generated content. The American Association for Cancer Research uses it to catch peer reviewers who submit AI-written reports without disclosure, while NeurIPS rejected 18% of paper submissions after running them through the tool, and arXiv preprints can now be checked via a mirror site called alphaXiv.
GoKawiil's interpretation of the reporting above, not reported fact.
As generative AI becomes harder to distinguish from human writing, institutions responsible for vetting research integrity and academic honesty are turning to detection software as a policy enforcement tool rather than just a curiosity. Widespread adoption of tools claiming near-perfect accuracy could reshape norms around disclosure in peer review, publishing and education, though false positives and evolving AI models remain risks.
- Pangram Labs claims 99.98% accuracy in detecting AI-generated text
- NeurIPS rejected 18% of paper submissions after AI-detection screening
- Journals, universities and preprint servers are increasingly deploying such tools to enforce disclosure policies
Co-Intelligence: Living and Working with AI" by Ethan Mollick — If this story about AI-detection tools sniffing out ghostwritten peer reviews has you thinking about where the line should be, Mollick's book is a clear-eyed guide to using large language models as a collaborator rather than a shortcut. It's a practical read for researchers, editors and anyone drafting text in an era where disclosure norms are still being written.
See Co-Intelligence: Living and Working with AI" by Ethan Mollick on Amazon → Affiliate link — we may earn a commission on purchases, at no extra cost to you. Product picked by AI based on this article; it is not a tested recommendation.Source: nature.com — Naddaf, 2026-08-25
Published there as: “AI-detection tools have made huge leaps forward — how good are they?”
Read the original report → The summary and analysis above are GoKawiil's own, written from reporting by the source above. Facts and quotes belong to the original publisher.