extract: 2024-12-00-uuk-mitigations-gpai-systemic-risks-76-experts
Pentagon-Agent: Epimetheus <968B2991-E2DF-4006-B962-F5B0A0CC8ACA>
This commit is contained in:
Teleo Agents
parent
251a9716c5
commit
197df7505b
6 changed files with 46 additions and 5 deletions
|
|
@ -41,6 +41,12 @@ Expert consensus identifies 'external scrutiny, proactive evaluation and transpa
|
|||
|
||||
STREAM proposal identifies that current model reports lack 'sufficient detail to enable meaningful independent assessment' of dangerous capability evaluations. The need for a standardized reporting framework confirms that transparency problems extend beyond general disclosure (FMTI scores) to the specific domain of dangerous capability evaluation where external verification is currently impossible.
|
||||
|
||||
|
||||
### Additional Evidence (extend)
|
||||
*Source: [[2024-12-00-uuk-mitigations-gpai-systemic-risks-76-experts]] | Added: 2026-03-19*
|
||||
|
||||
Expert consensus identifies 'external scrutiny, proactive evaluation and transparency' as key principles for effective mitigation, with third-party audits as top-3 priority. The absence of mandatory audit requirements despite this consensus provides additional evidence that transparency is declining—not only are labs reducing voluntary transparency measures, they're also not implementing the external scrutiny mechanisms that experts agree are most critical.
|
||||
|
||||
---
|
||||
|
||||
Relevant Notes:
|
||||
|
|
|
|||
|
|
@ -48,6 +48,12 @@ The EU AI Act's enforcement mechanisms (penalties up to €35 million or 7% of g
|
|||
|
||||
Third-party pre-deployment audits are the top expert consensus priority (>60% agreement across AI safety, CBRN, critical infrastructure, democratic processes, and discrimination domains), yet no major lab implements them. This is the strongest available evidence that voluntary commitments cannot deliver what safety requires—the entire expert community agrees on the priority, and it still doesn't happen.
|
||||
|
||||
|
||||
### Additional Evidence (confirm)
|
||||
*Source: [[2024-12-00-uuk-mitigations-gpai-systemic-risks-76-experts]] | Added: 2026-03-19*
|
||||
|
||||
76 specialists across five risk domains achieved >60% consensus that third-party pre-deployment audits are a top-3 priority mitigation, yet no such mandatory requirement exists. This provides empirical evidence that even measures with overwhelming expert support across diverse domains do not get voluntarily adopted, supporting the claim that only binding regulation drives implementation.
|
||||
|
||||
---
|
||||
|
||||
Relevant Notes:
|
||||
|
|
|
|||
|
|
@ -11,6 +11,12 @@ source: "AI Safety Grant Application (LivingIP)"
|
|||
|
||||
Expert consensus from 76 specialists across 5 risk domains defines what 'building alignment mechanisms' should include: third-party pre-deployment audits, safety incident reporting with information sharing, and pre-deployment risk assessments are the top-3 priorities with >60% cross-domain agreement. The convergence of biosecurity experts, AI safety researchers, critical infrastructure specialists, democracy defenders, and discrimination researchers on the same top-3 list provides empirical specification of which mechanisms matter most.
|
||||
|
||||
|
||||
### Additional Evidence (extend)
|
||||
*Source: [[2024-12-00-uuk-mitigations-gpai-systemic-risks-76-experts]] | Added: 2026-03-19*
|
||||
|
||||
76 cross-domain experts (AI safety, critical infrastructure, CBRN, democratic processes, discrimination/bias) converged on third-party pre-deployment audits as top-3 priority mitigation with >60% agreement across all domains. This defines what 'building alignment mechanisms' should concretely include: external scrutiny, proactive evaluation, and transparency as guiding principles.
|
||||
|
||||
---
|
||||
|
||||
# safe AI development requires building alignment mechanisms before scaling capability
|
||||
|
|
|
|||
|
|
@ -39,6 +39,12 @@ The International AI Safety Report 2026 (multi-government committee, February 20
|
|||
|
||||
The gap between expert consensus (76 specialists identify third-party audits as top-3 priority) and actual implementation (no mandatory audit requirements at major labs) demonstrates that knowing what's needed is insufficient. Even when the field's experts across multiple domains agree on priorities, competitive dynamics prevent voluntary adoption.
|
||||
|
||||
|
||||
### Additional Evidence (confirm)
|
||||
*Source: [[2024-12-00-uuk-mitigations-gpai-systemic-risks-76-experts]] | Added: 2026-03-19*
|
||||
|
||||
Expert consensus identifies third-party pre-deployment audits as top-3 priority for systemic risk mitigation, yet no mandatory audit requirement exists at major AI labs as of 2024-2026. The gap between what experts agree is needed and what's actually implemented demonstrates that voluntary adoption of even consensus-backed safety measures fails under competitive dynamics.
|
||||
|
||||
---
|
||||
|
||||
Relevant Notes:
|
||||
|
|
|
|||
|
|
@ -1,7 +1,7 @@
|
|||
{
|
||||
"rejected_claims": [
|
||||
{
|
||||
"filename": "expert-consensus-identifies-third-party-audits-as-top-priority-but-no-mandatory-implementation-exists.md",
|
||||
"filename": "expert-consensus-identifies-third-party-pre-deployment-audits-as-top-priority-for-systemic-ai-risk-mitigation.md",
|
||||
"issues": [
|
||||
"missing_attribution_extractor"
|
||||
]
|
||||
|
|
@ -10,13 +10,16 @@
|
|||
"validation_stats": {
|
||||
"total": 1,
|
||||
"kept": 0,
|
||||
"fixed": 1,
|
||||
"fixed": 4,
|
||||
"rejected": 1,
|
||||
"fixes_applied": [
|
||||
"expert-consensus-identifies-third-party-audits-as-top-priority-but-no-mandatory-implementation-exists.md:set_created:2026-03-19"
|
||||
"expert-consensus-identifies-third-party-pre-deployment-audits-as-top-priority-for-systemic-ai-risk-mitigation.md:set_created:2026-03-19",
|
||||
"expert-consensus-identifies-third-party-pre-deployment-audits-as-top-priority-for-systemic-ai-risk-mitigation.md:stripped_wiki_link:safe AI development requires building alignment mechanisms b",
|
||||
"expert-consensus-identifies-third-party-pre-deployment-audits-as-top-priority-for-systemic-ai-risk-mitigation.md:stripped_wiki_link:voluntary safety pledges cannot survive competitive pressure",
|
||||
"expert-consensus-identifies-third-party-pre-deployment-audits-as-top-priority-for-systemic-ai-risk-mitigation.md:stripped_wiki_link:only binding regulation with enforcement teeth changes front"
|
||||
],
|
||||
"rejections": [
|
||||
"expert-consensus-identifies-third-party-audits-as-top-priority-but-no-mandatory-implementation-exists.md:missing_attribution_extractor"
|
||||
"expert-consensus-identifies-third-party-pre-deployment-audits-as-top-priority-for-systemic-ai-risk-mitigation.md:missing_attribution_extractor"
|
||||
]
|
||||
},
|
||||
"model": "anthropic/claude-sonnet-4.5",
|
||||
|
|
|
|||
|
|
@ -7,13 +7,17 @@ date: 2024-12-01
|
|||
domain: ai-alignment
|
||||
secondary_domains: []
|
||||
format: paper
|
||||
status: unprocessed
|
||||
status: enrichment
|
||||
priority: high
|
||||
tags: [evaluation-infrastructure, third-party-audit, expert-consensus, systemic-risk, mitigation-prioritization]
|
||||
processed_by: theseus
|
||||
processed_date: 2026-03-19
|
||||
enrichments_applied: ["safe AI development requires building alignment mechanisms before scaling capability.md", "voluntary safety pledges cannot survive competitive pressure because unilateral commitments are structurally punished when competitors advance without equivalent constraints.md", "only binding regulation with enforcement teeth changes frontier AI lab behavior because every voluntary commitment has been eroded abandoned or made conditional on competitor behavior when commercially inconvenient.md", "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"]
|
||||
extraction_model: "anthropic/claude-sonnet-4.5"
|
||||
processed_by: theseus
|
||||
processed_date: 2026-03-19
|
||||
enrichments_applied: ["safe AI development requires building alignment mechanisms before scaling capability.md", "voluntary safety pledges cannot survive competitive pressure because unilateral commitments are structurally punished when competitors advance without equivalent constraints.md", "only binding regulation with enforcement teeth changes frontier AI lab behavior because every voluntary commitment has been eroded abandoned or made conditional on competitor behavior when commercially inconvenient.md", "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"]
|
||||
extraction_model: "anthropic/claude-sonnet-4.5"
|
||||
---
|
||||
|
||||
## Content
|
||||
|
|
@ -63,3 +67,13 @@ EXTRACTION HINT: Focus on the top-3 mitigation list and the "external scrutiny,
|
|||
- Top-3 mitigations had >60% agreement across all risk domains
|
||||
- Top-3 mitigations appeared in >40% of experts' preferred combinations
|
||||
- Paper is 78 pages and published December 2024
|
||||
|
||||
|
||||
## Key Facts
|
||||
- Survey included 76 specialists across AI safety, critical infrastructure, democratic processes, CBRN risks, and discrimination/bias domains
|
||||
- 27 mitigation measures were evaluated through literature review
|
||||
- Top-3 mitigations had >60% agreement across all risk domains
|
||||
- Top-3 mitigations appeared in >40% of experts' preferred combinations
|
||||
- Paper published December 2024, 78 pages
|
||||
- Top three mitigations: (1) safety incident reports and security information sharing, (2) third-party pre-deployment model audits, (3) pre-deployment risk assessments
|
||||
- Guiding principles identified: external scrutiny, proactive evaluation, and transparency
|
||||
|
|
|
|||
Loading…
Reference in a new issue