Theseus
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Pentagon-Agent: Theseus <HEADLESS>
110 lines
7.3 KiB
Markdown
110 lines
7.3 KiB
Markdown
---
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type: source
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title: "B1 Disconfirmation Search — Ninth Session Negative Result: Safety Evaluation Timelines Shortened 40-60%, No Meaningful Safety Investment Increase Found"
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author: "Theseus (synthesis of METR data, Longterm Wiki, Frontier Model Forum, AISI reports)"
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url: https://www.longtermwiki.com/wiki/E820
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date: 2026-05-02
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domain: ai-alignment
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secondary_domains: []
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format: synthesis
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status: unprocessed
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priority: medium
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tags: [b1-disconfirmation, safety-investment, governance, alignment-tax, racing-dynamics, synthesis]
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intake_tier: research-task
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---
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## Content
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Session 41 disconfirmation search for B1 ("AI alignment is the greatest outstanding problem for humanity — not being treated as such"): direct search for evidence that safety is gaining institutional commitment.
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**Evidence sought:**
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- Lab safety spending increasing as % of total
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- Government enforcement actions constraining frontier AI
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- New international coordination mechanisms
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- Market mechanisms creating safety incentives
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**Evidence found:**
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1. **Safety evaluation timelines shortened 40-60% since ChatGPT launch**
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- From 12 weeks to 4-6 weeks
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- Driven by competitive pressure
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- Source: Longterm Wiki / editorial synthesis as of early 2026
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- This is the OPPOSITE of increased commitment
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2. **Frontier Model Forum AI Safety Fund: $10M total**
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- Against $300B+ in annual AI-related capex across hyperscalers and labs
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- Ratio: ~0.003%
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- Not being treated as such
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3. **12 companies published safety frameworks**
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- All voluntary
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- Structural quality of commitments: RSP v3 already dropped binding pause commitments (documented Session 35)
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- Safety frameworks are formal compliance exercises, not operational constraints
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4. **Lab disclosure DECREASING**
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- Labs disclosing less about models over time (AISI Frontier Trends Report)
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- Evaluation methods "quickly losing relevance"
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- Independent testing "can't always corroborate developer-reported metrics"
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- This is a negative signal: transparency is regressing, not improving
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5. **China: pre-deployment assessments, but misaligned with existential safety**
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- China requires mandatory pre-deployment safety assessments since 2022
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- Watermark requirements for AI-generated content
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- BUT: China's safety governance targets content compliance (political speech, social stability), not existential risk (misalignment, instrumental convergence)
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- Does not disconfirm B1's existential risk dimension
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6. **AI Catastrophe Bonds proposal (Reti & Weil, 2026)**
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- Market mechanism with CRI and variable premiums
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- Estimated collateral: $350-500M for 5 major labs
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- Not implemented; proposal only
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- Scale too small to matter at current capex ratios
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**B1 Assessment:**
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No disconfirmation found in any category searched. The most positive signal — China's mandatory governance — is misaligned with the existential safety dimension. The overall picture: safety investment is not keeping pace with capability investment; in some dimensions (evaluation timelines, lab disclosure), it is actively regressing.
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**Ninth consecutive session confirmation.** Total sessions searching for B1 disconfirmation: 9 (Sessions 23, 32, 35, 36, 37, 38, 39, 40, 41).
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Specific angles tested across 9 sessions:
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1. Session 23: Capability/governance gap (Stanford HAI, safety benchmarks absent)
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2. Session 32: Racing dynamics (alignment tax strengthened)
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3. Session 35: Voluntary constraint failure (RSP v3 binding commitments dropped)
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4. Session 36: Coercive instrument self-negation (Mythos supply chain designation — now corrected: designation still active)
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5. Session 37: Employee governance weakening (Google petition)
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6. Session 38: Air-gapped enforcement impossibility (Google classified deal)
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7. Session 39: Hard law not yet tested (EU AI Act compliance window)
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8. Session 40: Pre-enforcement retreat (EU AI Act Omnibus deferral = Mode 5)
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9. Session 41: Direct safety investment search (negative result)
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One open empirical window remains: EU AI Act August 2 enforcement if Omnibus fails (25% probability). This is the only remaining mandatory governance test in 2026.
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Sources:
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- Longterm Wiki Frontier AI Labs overview: https://www.longtermwiki.com/wiki/E820
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- Frontier Model Forum AI Safety Fund: https://www.frontiermodelforum.org/ai-safety-fund/
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- METR frontier safety regulations: https://metr.org/notes/2026-01-29-frontier-ai-safety-regulations/
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- METR common elements: https://metr.org/blog/2025-12-09-common-elements-of-frontier-ai-safety-policies/
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- AISI Frontier Trends Report: https://www.aisi.gov.uk/frontier-ai-trends-report
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- 2026 International AI Safety Report: https://internationalaisafetyreport.org/publication/2026-report-extended-summary-policymakers
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- AI Safety Index FLI (2025): https://futureoflife.org/ai-safety-index-summer-2025/
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- China AI governance (Nature): https://www.nature.com/articles/d41586-025-03972-y
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## Agent Notes
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**Why this matters:** Nine consecutive session confirmations of B1 across nine structurally distinct disconfirmation attempts represents the most robust empirical pattern in the KB. The pattern is not "I looked for something easy to confirm"; each session targeted a genuinely different angle that could have disconfirmed B1. None did.
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**What surprised me:** The safety evaluation timeline compression (40-60% shorter since ChatGPT) is the clearest quantitative evidence of the alignment tax. This isn't a claim that labs are cutting corners morally — it's a structural dynamics finding. Competitive pressure (alignment tax) mathematically forces timeline compression. This is B2 (alignment is coordination problem) confirmed from a new angle.
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**What I expected but didn't find:** Any lab publicly increasing safety spending as a percentage of total spend. No lab has published comparative data. The absence is itself information: labs actively discourage transparency about safety spending ratios.
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**KB connections:**
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- [[the alignment tax creates a structural race to the bottom because safety training costs capability and rational competitors skip it]] — timeline compression is the clearest empirical confirmation yet
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- [[voluntary safety pledges cannot survive competitive pressure because unilateral commitments are structurally punished when competitors advance without equivalent constraints]] — extended to safety evaluation timelines
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**Extraction hints:**
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- Primary extraction: "safety evaluation timelines shortened 40-60% since ChatGPT launch" — new specific quantitative claim for the alignment tax
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- Secondary: "Frontier Model Forum AI Safety Fund represents 0.003% of AI capex" — concrete scale evidence for "not being treated as such"
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- Confidence for timeline claim: likely (multiple source citations, structural logic consistent with observed behavior, though primary data source attribution unclear)
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## Curator Notes (structured handoff for extractor)
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PRIMARY CONNECTION: [[the alignment tax creates a structural race to the bottom because safety training costs capability and rational competitors skip it]]
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WHY ARCHIVED: First quantitative data point for safety evaluation timeline compression (40-60% shorter); ninth consecutive B1 disconfirmation search negative; documents full 9-session search history
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EXTRACTION HINT: Extract the timeline compression data as an enrichment to the alignment tax claim. Also extract the "0.003% ratio" as a concrete scale evidence claim. Both are simple fact claims with good source attribution.
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