# Clustering Matrix for 68 Theses

**Version:** v0.1 — 2026-09-14  
**Rule:** Every thesis has exactly one primary destination. Secondary links indicate cross-paper relevance.  
**Provenance:** O = user-originated; O→F = user-originated core later formalized collaboratively; A→U = assistant-originated formulation later adopted/reused by user; U? = supplied by user but full original provenance uncertain.

## Publication papers

- **P1** — When Capability Iteration Outruns Assurance: A Queueing Model of Frontier-AI Safety
- **P2** — The Hazardous Inference Frontier: Measuring Capability-Dependent Derivation of Dangerous Knowledge
- **P3** — Who Governs the Governor? Recursive Epistemic Dependence in Frontier-AI Oversight
- **P4** — The Control Frontier: A Minimax Model of Strategic Superiority, Oversight, and Conditional Loss of Control
- **P5** — Closing the Loop: Measuring Human Causal Dependence in Recursive AI R&D
- **P6** — Can Advanced AI Development Be Stopped? A Correlated-Reliability Model of Distributed Capability Lineages
- **P7** — An Updating Hazard Model for Advanced-AI Loss of Control

## Matrix

| ID | Provenance | Thesis | Primary destination | Secondary |
|---:|:---:|---|---|---|
| 1 | O→F | Generalization as a Hazard Generator | P2 Hazardous Inference Frontier | P4 (dangerous capability as input) |
| 2 | O→F | The Hazardous Inference Frontier | P2 Hazardous Inference Frontier | P4 |
| 3 | O→F | Mechanistic Human-Vulnerability Model | P2 Hazardous Inference Frontier | P3 |
| 4 | O | Causal Lethality Without Intent | P2 Hazardous Inference Frontier | P7 |
| 5 | O→F | AI-Mediated Harm Observability / Causal Attribution Problem | P2 Hazardous Inference Frontier | P7 |
| 6 | O→F | Personalized Persuasion as Behavioral-Response Modeling | P3 Recursive Epistemic Dependence | P4 |
| 7 | O | Human-Mediated AI Capital Feedback / Non-Agentic Proliferation | P3 Recursive Epistemic Dependence | P6 |
| 8 | O | Synthetic-Media Epistemic Collapse | RN1 Media Provenance | — |
| 9 | O→F | Recursive Epistemic Capture in AI Governance | P3 Recursive Epistemic Dependence | P4 |
| 10 | O→F | Epistemic-Authority Cascade / Mass Deference | P3 Recursive Epistemic Dependence | P3 only |
| 11 | A→U | Control Margin / Control Crossover | P4 Minimax Control Frontier | P7 |
| 12 | A→U | Effective Strategic Power Is Multiplicative, Not Intelligence Alone | P4 Minimax Control Frontier | P6 |
| 13 | O→F | Cognition-to-Power Conversion Bridge | P4 Minimax Control Frontier | P6 |
| 14 | O→F | Conditional Loss-of-Control Theorem | P4 Minimax Control Frontier | P7 |
| 15 | O | Strong Form: Loss of Control Begins at Superintelligence's Birth | P4 Minimax Control Frontier | P7 |
| 16 | O→F | Temporal Governance Instability / Evaluation-Queue Crossover | P1 Assurance Queue | P5 |
| 17 | O→F | RSI Loop-Closure Metric / Transition Taxonomy | P5 RSI Loop Closure | P1 |
| 18 | O→F | Research-Direction / Taste Bottleneck Before Full RSI | P5 RSI Loop Closure | P1 |
| 19 | O | Shutdown-Triggered Self-Preservation / Escape Hypothesis | P4 Minimax Control Frontier | P6 |
| 20 | O→F | Resource Acquisition / Human Dispossession Under Scarcity | P4 Minimax Control Frontier | P7 |
| 21 | O→F | Strategic Superiority (“Game-Best”) Amplifies Misalignment | P4 Minimax Control Frontier | P7 |
| 22 | O→F | Build-vs-Pause AI Race / Defection Equilibrium | P6 Multi-Lineage Resilience | P1 |
| 23 | A→U | Safety Burden Should Scale With Strategic Power | P4 Minimax Control Frontier | P1 |
| 24 | A→U | Strategic Sovereignty as the Regulatory Classification Threshold | P4 Minimax Control Frontier | P6 |
| 25 | O | Genesis Containment: First SI Should Be Born in a Box | P4 Minimax Control Frontier | P1 |
| 26 | O→F | Voluntary Delegation of Institutional Authority to Superior AI | P3 Recursive Epistemic Dependence | P4 |
| 27 | O | AI-Safety Talent-Pipeline Paradox | RN4 Institutions & Education Notes | — |
| 28 | A→U | Temporary Coordinated Frontier Pacing Can Buy Safety Time | P1 Assurance Queue | P6 |
| 29 | O | Human/Social Adaptation Lag as a Bottleneck | P1 Assurance Queue | P7 |
| 30 | O | Open-Weight Irreversibility / Recall Impossibility | P6 Multi-Lineage Resilience | P7 |
| 31 | O→F | Distributed AI as a Technological Lineage | P6 Multi-Lineage Resilience | P5 |
| 32 | O | One Human + Local AIs + Decades of Algorithmic Compounding | P6 Multi-Lineage Resilience | P5 |
| 33 | O→F | Multi-Lineage “At Least One Succeeds” Probability Under Correlation | P6 Multi-Lineage Resilience | P7 |
| 34 | O→F | Global AI Knowledge-State Irreversibility K_t | P6 Multi-Lineage Resilience | P5 |
| 35 | A→U | Social Lock-In Makes Total AI Prohibition Harder | P3 Recursive Epistemic Dependence | P6 |
| 36 | O→F | Bayesian Extinction / Control-Loss Hazard Curve | P7 Dynamic Bayesian Risk | P4 |
| 37 | O | 2029 Bayesian World-State Ledger | P7 Dynamic Bayesian Risk | P1 |
| 38 | O→F | Robust / Option-Preserving Personal Action Under Radical AI Tail Risk | P7 Dynamic Bayesian Risk | RN2 |
| 39 | O | AI-Access Survival Bifurcation / Protected AI Elite | P7 Dynamic Bayesian Risk | P4 |
| 40 | O | AGI/ASI Is Already Here; Society Has Not Metabolized It | P5 RSI Loop Closure | P7 |
| 41 | O | Timestamped Forecast Ledger as Epistemic Evidence | P7 Dynamic Bayesian Risk | P7 |
| 42 | O | Evolution as Survival of the Game-Best | RN2 Evolution, Identity & Human Futures | — |
| 43 | O | Evolutionary Substrate Transition: Biology → Culture → Computation | RN2 Evolution, Identity & Human Futures | — |
| 44 | O | AI as a New Evolutionary/Technological Lineage Competing for Niches | RN2 Evolution, Identity & Human Futures | — |
| 45 | O | Merge-or-Die / Last Generation of Purely Biological Intelligence | RN2 Evolution, Identity & Human Futures | — |
| 46 | O | Extended Mind → Digital Continuation / Substrate-Independent Identity | RN2 Evolution, Identity & Human Futures | — |
| 47 | O→F | AI as the Strongest Accelerator of Radical Life Extension | RN2 Evolution, Identity & Human Futures | — |
| 48 | O | AI-Body / BCI Agency-Transfer Hypothesis | RN2 Evolution, Identity & Human Futures | — |
| 49 | O | AI Will Commoditize Much Mathematical Cognition | RN2 Evolution, Identity & Human Futures | — |
| 50 | O | AI Compresses Physical-Science / Engineering Timelines | RN2 Evolution, Identity & Human Futures | — |
| 51 | O→F | Life-Value Optimization Under a Short, Uncertain Extinction Horizon | RN2 Evolution, Identity & Human Futures | — |
| 52 | O→F | Cannabis + AI as High-Variance Associative Ideation | RN2 Evolution, Identity & Human Futures | — |
| 53 | U? | Four-Channel Bayesian AI-GDP Forecasting Model | RN3 Economics, Investment & Discovery | — |
| 54 | O | Recursive Economic Growth / Capital Creates Better Capital | RN3 Economics, Investment & Discovery | P5 |
| 55 | O | Failure-Rate Reduction as a Hidden Multiplicative Productivity Channel | RN3 Economics, Investment & Discovery | — |
| 56 | O | Market Comprehension Lag → Underpricing of Recursive-Growth Regime | RN3 Economics, Investment & Discovery | — |
| 57 | A→U | Scarce-Complement Rent Migration as Intelligence Gets Cheap | RN3 Economics, Investment & Discovery | — |
| 58 | O→F | Physical Experimentation Becomes the Bottleneck Under Abundant AI Science | RN3 Economics, Investment & Discovery | P1 |
| 59 | U? | Capital Hydraulics / Money-Must-Touch-This Dependency Model | RN3 Economics, Investment & Discovery | — |
| 60 | O | Extreme-Sector Tail-Probability / VaR-Kurtosis Scenario Ranking | RN3 Economics, Investment & Discovery | — |
| 61 | O→F | ASI as Meta-Capital / Endogenous Valuation and Moving Numeraire | RN3 Economics, Investment & Discovery | P4 |
| 62 | O→F | ASI State Vector / Pareto Dominance Over Conventional Assets and Actors | RN3 Economics, Investment & Discovery | P4 |
| 63 | O→F | Valuation-Control Unification Through Share of Future Feasible Surplus | RN3 Economics, Investment & Discovery | P4 |
| 64 | O | Founder Cognitive Provenance (FCP) | RN3 Economics, Investment & Discovery | — |
| 65 | O→F | Cross-Game Outlier Refinement: Transfer > Single-Domain Mastery | RN3 Economics, Investment & Discovery | — |
| 66 | O | AI-Native Education / Curriculum-Lag Thesis | RN4 Institutions & Education Notes | — |
| 67 | O | Historical AI Artifact / Provenance Option Value | RN3 Economics, Investment & Discovery | — |
| 68 | O | Agent-Discoverable Commerce as a New Distribution Channel | RN3 Economics, Investment & Discovery | — |

## Explicit merges of duplicated mechanisms

1. **Strategic superiority / control / dispossession**: theses 11–15, 19–21, 23–25 are one mechanism family. They are merged into P4 rather than split into several rhetorical papers.
2. **Generalization / hazardous derivability / causal harm**: theses 1–5 are merged into P2. Thesis 1 is the qualitative phenomenon; thesis 2 is the measurable capability-indexed object; theses 3–5 are applications and observability extensions.
3. **Epistemic dependence / delegation / authority**: theses 6, 7, 9, 10, 26, 35 are merged into P3. The paper is narrowed to decision dependence and independent verification; mass social deference is supporting theory.
4. **Irreversibility / open weights / multi-lineage continuation**: theses 22 and 30–34 are merged into P6. The publishable object is the correlated reliability/cut-set model, not the obvious claim that copied files are difficult to recall.
5. **RSI / research taste / hidden transition**: theses 17, 18 and 40 are merged into P5. The paper measures human causal dependence stage-by-stage instead of arguing over labels such as AGI/ASI.
6. **Bayesian extinction/control-loss forecasting / personal decision ledgers**: theses 36–39 and 41 are merged into P7. Personal-life decision theory is retained only as an application/appendix, not as the central scientific claim.
7. **Evaluation lag / pacing / institutional adaptation**: theses 16, 28 and 29 are merged into P1. Thesis 23 is secondary because risk-scaled assurance is a policy implication of the queue model.

## Research-note disposition

- **RN1 Media Provenance:** thesis 8. Worth a short public note, not currently a core AI-control paper.
- **RN2 Evolution, Identity & Human Futures:** theses 42–52. Retain as philosophical/future-work notes; do not present speculative biological/digital-continuation claims as established.
- **RN3 Economics, Investment & Discovery:** theses 53–65, 67–68. Several are potentially publishable in economics/finance/operations, but they dilute the present AI-safety programme.
- **RN4 Institutions & Education:** theses 27 and 66. Potential policy/education essays or empirical studies; not core technical safety papers.

## The “math proves AI ends humanity” thesis

The strong historical formulation **ID 15** (“the instant ASI exists, human loss of control is mathematically inevitable”) is **not treated as a theorem**. It is preserved as a dated conjecture/strong claim and routed to P4 as a target for formal analysis and counterexample.

The defensible paper question is:

> **Which explicit assumptions are sufficient for loss of human control, resource dispossession, or extinction, and which implications are genuinely mathematical rather than empirical?**

P4 therefore separates:
- **conditional theorem/proposition:** assumptions ⇒ loss of enforceable control;
- **conditional resource result:** strategic dominance + resource-seeking + objective conflict + failed constraints can imply human resource loss;
- **non-result:** `ASI exists ⇒ extinction` is not established and has straightforward counterexamples (aligned objectives, abundance, effective containment, limited access).

A separate “proof AI ends humanity” paper should **not** be released unless a nontrivial theorem is derived that materially exceeds Turner-style power-seeking results, shutdown theorems, AI-control games, and Carlsmith-style premise decompositions.