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extract: 2025-08-00-mccaslin-stream-chembio-evaluation-reporting

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6
domains/ai-alignment/AI lowers the expertise barrier for engineering biological weapons from PhD-level to amateur which makes bioterrorism the most proximate AI-enabled existential risk.md
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@ -27,6 +27,12 @@ The structural point is about threat proximity. AI takeover requires autonomy, r
The International AI Safety Report 2026 (multi-government committee, February 2026) confirms that 'biological/chemical weapons information accessible through AI systems' is a documented malicious use risk. While the report does not specify the expertise level required (PhD vs amateur), it categorizes bio/chem weapons information access alongside AI-generated persuasion and cyberattack capabilities as confirmed malicious use risks, giving institutional multi-government validation to the bioterrorism concern.
### Additional Evidence (extend)
*Source: [[2025-08-00-mccaslin-stream-chembio-evaluation-reporting]] | Added: 2026-03-19*
STREAM framework specifically targets ChemBio dangerous capability evaluation reporting as its initial focus domain, indicating that expert consensus identifies biological and chemical risks as the priority area requiring standardized transparent evaluation disclosure. The multi-stakeholder process (including government experts) signals regulatory interest in making ChemBio capability assessments independently verifiable.
---
Relevant Notes:

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domains/ai-alignment/AI transparency is declining not improving because Stanford FMTI scores dropped 17 points in one year while frontier labs dissolved safety teams and removed safety language from mission statements.md
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@ -35,6 +35,12 @@ The alignment implication: transparency is a prerequisite for external oversight
Expert consensus identifies 'external scrutiny, proactive evaluation and transparency' as the key principles for mitigating AI systemic risks, with third-party audits as the top-3 implementation priority. The transparency decline documented by Stanford FMTI is moving in the opposite direction from what 76 cross-domain experts identify as necessary.
### Additional Evidence (extend)
*Source: [[2025-08-00-mccaslin-stream-chembio-evaluation-reporting]] | Added: 2026-03-19*
STREAM framework proposal (August 2025) provides specific evidence of the transparency gap: a 23-expert multi-stakeholder group found that current AI model reports lack sufficient standardized disclosure detail for dangerous capability evaluations, particularly in ChemBio domains. The need for a 3-page standardized reporting template with 'gold standard examples' demonstrates that existing transparency practices are inadequate for independent assessment of evaluation rigor.
---
Relevant Notes:

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inbox/queue/.extraction-debug/2025-08-00-mccaslin-stream-chembio-evaluation-reporting.json Normal file
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@ -0,0 +1,24 @@
{
"rejected_claims": [
{
"filename": "ai-model-reports-lack-standardized-dangerous-capability-evaluation-disclosure-preventing-independent-assessment.md",
"issues": [
"missing_attribution_extractor"
]
}
],
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"total": 1,
"kept": 0,
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"rejected": 1,
"fixes_applied": [
"ai-model-reports-lack-standardized-dangerous-capability-evaluation-disclosure-preventing-independent-assessment.md:set_created:2026-03-19"
],
"rejections": [
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"model": "anthropic/claude-sonnet-4.5",
"date": "2026-03-19"
}

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inbox/queue/2025-08-00-mccaslin-stream-chembio-evaluation-reporting.md
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@ -7,9 +7,13 @@ date: 2025-08-01
domain: ai-alignment
secondary_domains: []
format: paper
status: unprocessed
status: enrichment
priority: medium
tags: [evaluation-infrastructure, dangerous-capabilities, standardized-reporting, ChemBio, transparency, STREAM]
processed_by: theseus
processed_date: 2026-03-19
enrichments_applied: ["AI transparency is declining not improving because Stanford FMTI scores dropped 17 points in one year while frontier labs dissolved safety teams and removed safety language from mission statements.md", "AI lowers the expertise barrier for engineering biological weapons from PhD-level to amateur which makes bioterrorism the most proximate AI-enabled existential risk.md"]
extraction_model: "anthropic/claude-sonnet-4.5"
---
## Content
@ -53,3 +57,11 @@ PRIMARY CONNECTION: [[AI lowers the expertise barrier for engineering biological
WHY ARCHIVED: Provides evidence of emerging standardization for dangerous capability evaluation reporting. The multi-stakeholder process (government, academia, AI companies) signals potential for eventual adoption.
EXTRACTION HINT: Focus on the disclosure gap: labs currently report their own dangerous capability evaluations without standardized format, preventing independent assessment of rigor.
## Key Facts
- STREAM (Standard for Transparently Reporting Evaluations in AI Model Reports) proposed August 2025
- STREAM developed through consensus of 23 experts from government, civil society, academia, and frontier AI companies
- STREAM provides a 3-page reporting template and gold standard examples for dangerous capability evaluation disclosure
- STREAM's initial focus is chemical and biological (ChemBio) dangerous capability evaluations
- STREAM has two stated purposes: practical guidance for AI developers and enabling third-party assessment of evaluation rigor