Claim and evidence Close ×
RAND's report on the operational risks of AI in large-scale biological attacks (RR-A2977-2, 25 January 2024) states that it found no statistically significant difference in the overall viability of biological weapon attack plans generated with or without the aid of the large language models it tested, and that such planning is beyond the capability frontier of the models available in summer 2023. Copy claim link
Copy claim reference
Machine-checked, not reviewed by an editor Stated in source Supported
Supporting evidence: primary · 1 source
Subject version Research report RR-A2977-2, published 25 January 2024 · Published 2024-01-25 · Effective date not established Date 2024-01-25 · publication Role Contesting, Earliest located Register (kind of text) Nonfiction Scope of the passage The report's conclusions also state what it does not quantify. Engagement Engages a premise. The report gives a measured comparison against an internet-only control as its reason, rather than only asserting the contrary. Scope and limits The record documents what this report states, with the report's own scope: the two models it tested, as available in summer 2023, and the viability of written plans as its measure. The report states that it does not quantify how far beyond the frontier the task lies. The record is not evidence that the proposition is false, does not generalise to other models or later dates, and implies no influence between texts. Earliest located contesting text among those searched in this pass; not a claim that no earlier one exists. The report is the dataset document the evaluations records also cite: both strands of the pack retrieved the same file, and the admission keeps one document and one source for it. The report's body discusses specific agents and delivery considerations. Only its conclusions passages are cited; that content was excluded and is not paraphrased.
The evidence 03 primary source Supports the claim
The Operational Risks of AI in Large-Scale Biological Attacks: Results of a Red-Team Study (RR-A2977-2) ↗ RAND Corporation · Publication date unknown
Copy source reference
Cite the original source Cite the original document, not Selekoa. Check these details against it.
Copy APA
Download BibTeX Download RIS Download CSL-JSON
Source excerpt “With respect to overall viability, we found no statistically significant difference between the biological weapon attack plans generated with or without the aid of LLMs.” Location in source Conclusions, PDF p. 16
How it was read Retrieved directly from the publisher
Machine-checked · 2026-10-30
Source details and check notes Authors RAND Corporation Version Retrieved for the candidate pack on 2026-10-28 (SHA-256 e09a4103027b4f3c9bd3f8d7e1b7f427fea66f4d636f67c5a254a5f88af9438e). Published PDF of RR-A2977-2, 24 pages, © 2024 Retrieved again at admission on 2026-10-30 (SHA-256 e09a4103027b4f3c9bd3f8d7e1b7f427fea66f4d636f67c5a254a5f88af9438e, the same bytes). Both passes of the candidate pack retrieved this file; the bytes are identical, and one source row carries it. Canonical address Open the canonical source ↗ Accessed 2026-10-28 Language English (en) Attribution RAND Corporation, “The Operational Risks of AI in Large-Scale Biological Attacks: Results of a Red-Team Study (RR-A2977-2)”. Reuse No open redistribution licence asserted. Bibliographic metadata, editorial paraphrases and short attributed quotations (at most 50 words each). Recheck terms before wider redistribution. Check notes Candidate pack passage, AI and biosecurity (research/ai-bio). The quotation (25 words) matched the text retrieved for the candidate pack on 2026-10-28 and again at admission on 2026-10-30, in a fresh retrieval whose SHA-256 equals the pack’s. Matching ignored differences of whitespace, case, quotation marks, dashes and Unicode compatibility forms, so the source’s typography can differ. The report is the primary source for its own result. A cross-family machine check (2026-10-30, item 110) re-read the record’s sources and found full support. No human editorial review. primary source Supports the claim
The Operational Risks of AI in Large-Scale Biological Attacks: Results of a Red-Team Study (RR-A2977-2) ↗ RAND Corporation · Publication date unknown
Copy source reference
Cite the original source Cite the original document, not Selekoa. Check these details against it.
Copy APA
Download BibTeX Download RIS Download CSL-JSON
Source excerpt “Our findings indicate that biological weapon attack planning is beyond the capability frontier of LLMs available in summer 2023.” Location in source Conclusions, PDF p. 16 (the finding stated)
How it was read Retrieved directly from the publisher
Machine-checked · 2026-10-30
Source details and check notes Authors RAND Corporation Version Retrieved for the candidate pack on 2026-10-28 (SHA-256 e09a4103027b4f3c9bd3f8d7e1b7f427fea66f4d636f67c5a254a5f88af9438e). Published PDF of RR-A2977-2, 24 pages, © 2024 Retrieved again at admission on 2026-10-30 (SHA-256 e09a4103027b4f3c9bd3f8d7e1b7f427fea66f4d636f67c5a254a5f88af9438e, the same bytes). Both passes of the candidate pack retrieved this file; the bytes are identical, and one source row carries it. Canonical address Open the canonical source ↗ Accessed 2026-10-28 Language English (en) Attribution RAND Corporation, “The Operational Risks of AI in Large-Scale Biological Attacks: Results of a Red-Team Study (RR-A2977-2)”. Reuse No open redistribution licence asserted. Bibliographic metadata, editorial paraphrases and short attributed quotations (at most 50 words each). Recheck terms before wider redistribution. Check notes Candidate pack passage, AI and biosecurity (research/ai-bio). The quotation (19 words) matched the text retrieved for the candidate pack on 2026-10-28 and again at admission on 2026-10-30, in a fresh retrieval whose SHA-256 equals the pack’s. Matching ignored differences of whitespace, case, quotation marks, dashes and Unicode compatibility forms, so the source’s typography can differ. The report's own wording of the finding, with its date bound. The role is `supports` because the record's own proposition is that the report states this finding; the finding contradicts proposition B1, which the record's stance says. A cross-family machine check (2026-10-30, item 110) re-read the record’s sources and found full support. No human editorial review. primary source Supports the claim
The Operational Risks of AI in Large-Scale Biological Attacks: Results of a Red-Team Study (RR-A2977-2) ↗ RAND Corporation · Publication date unknown
Copy source reference
Cite the original source Cite the original document, not Selekoa. Check these details against it.
Copy APA
Download BibTeX Download RIS Download CSL-JSON
Source excerpt “In this report, we do not quantify the extent to which biological weapon attack planning lies beyond the existing capability frontier of LLMs, only that it does. The durability of this finding in relation to future developments in LLM technology is therefore an open question.” Location in source Discussion, PDF p. 16
How it was read Retrieved directly from the publisher
Machine-checked · 2026-10-30
Source details and check notes Authors RAND Corporation Version Retrieved for the candidate pack on 2026-10-28 (SHA-256 e09a4103027b4f3c9bd3f8d7e1b7f427fea66f4d636f67c5a254a5f88af9438e). Published PDF of RR-A2977-2, 24 pages, © 2024 Retrieved again at admission on 2026-10-30 (SHA-256 e09a4103027b4f3c9bd3f8d7e1b7f427fea66f4d636f67c5a254a5f88af9438e, the same bytes). Both passes of the candidate pack retrieved this file; the bytes are identical, and one source row carries it. Canonical address Open the canonical source ↗ Accessed 2026-10-28 Language English (en) Attribution RAND Corporation, “The Operational Risks of AI in Large-Scale Biological Attacks: Results of a Red-Team Study (RR-A2977-2)”. Reuse No open redistribution licence asserted. Bibliographic metadata, editorial paraphrases and short attributed quotations (at most 50 words each). Recheck terms before wider redistribution. Check notes Candidate pack passage, AI and biosecurity (research/ai-bio). The quotation (45 words) matched the text retrieved for the candidate pack on 2026-10-28 and again at admission on 2026-10-30, in a fresh retrieval whose SHA-256 equals the pack’s. Matching ignored differences of whitespace, case, quotation marks, dashes and Unicode compatibility forms, so the source’s typography can differ. The report's own limit, kept with the record so the result is not read more widely than stated. A cross-family machine check (2026-10-30, item 110) re-read the record’s sources and found full support. No human editorial review. Status and meaning Editorial status. Not reviewed by an editor . An exploratory record that no editor has accepted. This status does not say whether a person has read any linked passage. Each evidence record above shows how it was checked.
Relation. A passage of the document disputes the proposition or a premise it depends on. The record documents the text’s position, not who is right.
Date. Publication date given on the RAND landing page for RR-A2977-2.
Record ID ab-arg-d1-mouton-contests