Claim · 2023-11-27 · publication · Stated in source · Supported

The preprint of 27 November 2023 identifies, among the challenges of regulating biological design tools, the potential for safeguards to be circumvented by open-sourcing model weights.

One recorded claim. The claim panel gives its qualification, the source passages with their place in each source, and how it was checked.

What it connects

Towards Responsible Governance of Biological Design Tools → articulates → Public release of model weights increases biological misuse risk

Where it appears

Arguments about AI and biological risk →

Claim and evidence

Towards Responsible Governance of Biological Design Toolsarticulates ↓Public release of model weights increases biological misuse risk

Machine-checked, not reviewed by an editorStated in sourceSupported

Supporting evidence: primary · 1 source

Subject version: arXiv v1 (27 November 2023) · Published 2023-11-27 · Effective date not established
Date: 2023-11-27 · publication
Role: Articulation
Register (kind of text): Nonfiction
Scope of the passage: Stated of biological design tools, whose weights the paper says are often released openly.

Scope and limitsThe record documents what this paper states about tools for biological design, not about general-purpose language models; it is not evidence that the proposition is true and names no model.

The evidence 01

primary sourceSupports the claim

Towards Responsible Governance of Biological Design Tools

arXiv (preprint; workshop paper, Regulatable Machine Learning at NeurIPS 2023) · Publication date unknown

Cite the original source

Cite the original document, not Selekoa. Check these details against it.

Source excerpt

“the potential for safeguards to be circumvented by open-sourcing model weights”

Location in source Introduction, PDF p. 1

How it was read Retrieved directly from the publisher

Machine-checked · 2026-10-30

Source details and check notes

Authors: arXiv (preprint; workshop paper, Regulatable Machine Learning at NeurIPS 2023)
Version: Retrieved for the candidate pack on 2026-10-28 (SHA-256 9e0f06fab595a615ceac3470dd7690069f1460aac6715d2bf9fefaad8bd6054c). arXiv v1 of 27 November 2023 (per the PDF's arXiv stamp) Retrieved again at admission on 2026-10-30 (SHA-256 9e0f06fab595a615ceac3470dd7690069f1460aac6715d2bf9fefaad8bd6054c, the same bytes).
Canonical address: Open the canonical source ↗
Accessed: 2026-10-28
Language: English (en)
Attribution: arXiv (preprint; workshop paper, Regulatable Machine Learning at NeurIPS 2023), “Towards Responsible Governance of Biological Design Tools”.
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 (11 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. One of four regulatory challenges the paper lists. A cross-family machine check (2026-10-30, item 106) 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 meets the proposition’s criterion. The record documents what the text states, in its register (fiction and satire are labelled); it is not evidence that the proposition is true and implies no influence on or from another text.

Date. Date of the arXiv v1 stamp on the PDF.

Record ID ab-arg-d6-moulange-articulates