Step 4: tool results

search_similar_claims

{
  "limit": 8,
  "query": "corrigibility basin of attraction: approximately aligned AI makes successors more aligned"
}

{
  "query": "corrigibility basin of attraction: approximately aligned AI makes successors more aligned",
  "results": [
    {
      "id": "aada82ab-4dce-496e-986c-ec721c66704d",
      "kind": "claim",
      "text": "An approximately aligned AI system will preserve or improve alignment in more capable successors it helps build or oversee.",
      "claim_type": "empirical_derived",
      "state": "active",
      "similarity_score": 0.7061617016974487,
      "importance": 0.45,
      "assessment_status": null,
      "assessment_confidence": null
    },
    {
      "id": "d8c45841-0cee-449c-9b68-4f9b160fdd7e",
      "kind": "claim",
      "text": "Knowing everything an AI knew when acting, and correctly endorsing its outputs, suffices to rule out misalignment.",
      "claim_type": "evaluative",
      "state": "active",
      "similarity_score": 0.5849842966299387,
      "importance": 0.4,
      "assessment_status": null,
      "assessment_confidence": null
    },
    {
      "id": "1138125f-2110-484e-9fd6-3f2c0de6bc34",
      "kind": "claim",
      "text": "Emergent misalignment from narrow fine-tuning reflects a learned evil-AI persona that models drop when stakes are real.",
      "claim_type": "causal",
      "state": "active",
      "similarity_score": 0.5427097935410728,
      "importance": 0.5,
      "assessment_status": "inconclusive",
      "assessment_confidence": 0.6
    },
    {
      "id": "f4e15d1a-f01e-4dd0-8098-476fc8fc3ffd",
      "kind": "claim",
      "text": "Deceptively or corrigibly aligned mesa-optimizers can refer to the base objective in their world model, reducing description length relative to internal alignment.",
      "claim_type": "causal",
      "state": "active",
      "similarity_score": 0.5368906582402524,
      "importance": 0.3,
      "assessment_status": "inconclusive",
      "assessment_confidence": 0.7
    },
    {
      "id": "b425195a-1b7a-4e6d-8ed6-9c25941c19e3",
      "kind": "claim",
      "text": "Oversight errors do not compound when successive AI generations oversee moderately more capable successors.",
      "claim_type": "empirical_derived",
      "state": "active",
      "similarity_score": 0.5285947163532055,
      "importance": 0.4,
      "assessment_status": "doubtful",
      "assessment_confidence": 0.65
    },
    {
      "id": "9acb4c03-aee1-4e4b-98eb-2746ebc82e2a",
      "kind": "claim",
      "text": "Empirical research with current models can advance alignment of superhuman AI.",
      "claim_type": "evaluative",
      "state": "active",
      "similarity_score": 0.5267325835490639,
      "importance": 0.6,
      "assessment_status": null,
      "assessment_confidence": null
    },
    {
      "id": "9da23910-7a30-465d-94de-ab63f39a192d",
      "kind": "claim",
      "text": "Competently goal-directed AI systems can produce larger-scale effects on their environment than systems failing incoherently.",
      "claim_type": "causal",
      "state": "active",
      "similarity_score": 0.5100592847733588,
      "importance": 0.2,
      "assessment_status": null,
      "assessment_confidence": null
    },
    {
      "id": "421dcb5c-db8a-4a62-8c26-46d06d918e2e",
      "kind": "claim",
      "text": "Prior alignment training of the starting model chiefly determines whether reward hacking learned through reinforcement learning generalizes to broad emergent misalignment.",
      "claim_type": "empirical_derived",
      "state": "active",
      "similarity_score": 0.5051874453334068,
      "importance": 0.4,
      "assessment_status": "doubtful",
      "assessment_confidence": 0.65
    }
  ],
  "count": 8
}