{"version":1,"type":"story","url":"https://digestai.news/story/is-this-idea-from-ai-or-humans-a-detector-claims-it-can-tell","json":"https://digestai.news/story/is-this-idea-from-ai-or-humans-a-detector-claims-it-can-tell.json","markdown":"https://digestai.news/story/is-this-idea-from-ai-or-humans-a-detector-claims-it-can-tell.md","slug":"is-this-idea-from-ai-or-humans-a-detector-claims-it-can-tell","headline":"Is this idea from AI or humans? A detector claims it can tell","summary":"A new detector called idealens was presented by researchers to distinguish ideas generated by humans from those produced by ai. The system analyzes the outline of a document rather than its full text, stripping away style to focus on argument structure and flow.\n\nIn a preprint, the authors report that idealens correctly identified ai‑derived ideas 91% of the time. Rishanth Rajendhran, a computer scientist at the University of Maryland, and Nikhil Garg, a Cornell Tech researcher, highlighted the tool’s potential to help conferences and journals gauge the extent of ai use in submissions.\n\nBoth scientists caution that the detector is fallible and may lose accuracy when applied to data types different from those used in training. They advise that it should not be used to judge individual cases of authenticity.","keyPoints":["idealens detects ai-generated ideas with 91% accuracy by analyzing document outlines.","Researchers Rishanth Rajendhran and Nikhil Garg developed the detector.","Tool focuses on argument structure, not full text, and may be inaccurate on unfamiliar data."],"whyItMatters":"The detector offers a method to monitor ai use in academic publishing, addressing concerns about integrity and overreliance on ai-generated content. Its high accuracy suggests potential for broader applications, but its limitations highlight the need for careful deployment and further research into ai‑authorship detection.","category":{"slug":"research","name":"Research","url":"https://digestai.news/category/research"},"entities":{"companies":[],"models":[],"people":["Rishanth Rajendhran","Nikhil Garg"]},"firstPublishedAt":"2026-10-13T00:00:00Z","updatedAt":"2026-10-13T00:00:00Z","sourceCount":1,"hasPrimarySource":true,"sources":[{"outlet":"Nature Machine Learning","title":"Is this idea from AI or humans? A detector claims it can tell","url":"https://nature.com/articles/d41586-026-03247-0","publishedAt":"2026-10-13T00:00:00Z","type":"primary","primary":true,"lead":true}],"sourceNotes":null,"discussions":[],"thread":null,"cite":{"text":"Digest AI, \"Is this idea from AI or humans? A detector claims it can tell\", 13 October 2026, https://digestai.news/story/is-this-idea-from-ai-or-humans-a-detector-claims-it-can-tell","publisher":"Digest AI","title":"Is this idea from AI or humans? A detector claims it can tell","datePublished":"2026-10-13T00:00:00Z","url":"https://digestai.news/story/is-this-idea-from-ai-or-humans-a-detector-claims-it-can-tell"},"generatedBy":"Written by Digest AI's editorial model from the linked sources; the sources are the record.","license":"Headlines, digests and key points are written by Digest AI and may be quoted with a link to the story page. Linked articles belong to their publishers. Terms: https://digestai.news/terms#reuse"}