Lu et al. 2026 warn that autonomous systems could tax review systems and add noise to the literature; Baker et al. 2026 ("Verifiable Agentic Science on Public Infrastructure") measure a concrete mechanism, showing that 30 unguided local agents given the same dataset splinter into 18 incompatible pipelines—an irreproducibility arising from unrecorded improvisation rather than from fabrication.
E1 supports Lu et al.'s warning about taxing review systems and adding noise, and E23 supports the 30-agents-splintering-into-18-pipelines finding from unrecorded improvisation, but neither cited text mentions fabrication, so the contrast 'rather than from fabrication' is added.
Written by Kimi K3 via Ollama Cloud · checked by GLM-5.3 via Ollama Cloud · 2 Nov, 04:36
Source chain
AEvery quote below was checked, without a model, to appear verbatim in its source.
- 01
“there could be important risks, including taxing overwhelmed review systems and adding noise to the scientific literature.”
Full-text passage · no page number · evidence E1
We evaluate The AI Scientist in two settings: a focused mode using human-provided code templates as an initial scaffold for conducting research on a specific topic and a template-free, open-ended mode that leverages agentic search for wider scientific exploration6,7. Both settings produce diverse ideas and automatically test, report on and evaluate them. This achievement demonstrates the growing capacity of AI for making scientific contributions and signifies a potential paradigm shift in how research is conducted. As with any impactful new technology, there could be important risks, including taxing overwhelmed review systems and adding noise to the scientific literature. However, if developed responsibly, such autonomous systems could greatly accelerate scientific discovery. Main AI has long been used to aid scientific discovery, an ambition with deep roots in the history of the field1,8–11. Before the rise of large language models (LLMs), AI was limited to helping with specific, narrow tasks, such as discovering chemical structures2, finding mathematical proofs1, discovering new materials12–14 and predicting the three-dimensional shape of proteins15,16.
Passage read from www.ebi.ac.uk, which may be a preprint rather than the published version.
- 02
“30 unguided local agents splinter into 18 incompatible pipelines on the same dataset”
Abstract · no page number · evidence E23