Step 3: assistant

thinking

Calls record_claim_instance

{
  "url": "https://ai-alignment.com/corrigibility-3039e668638",
  "title": "Corrigibility",
  "stance": "affirms",
  "context": "Christiano argues informally that an agent which approximately wants to help its overseer will want to become more corrigible, so small errors are corrected rather than compounded; he notes the argument is a simplification.",
  "speaker": "Paul Christiano",
  "claim_id": "aa5205cb-3287-477e-9e11-8fec1abc78c7",
  "confidence": 0.85,
  "publication": "AI Alignment (Medium)",
  "source_kind": "blog_post",
  "verbatim_text": "A sufficiently corrigible agent will tend to become more corrigible and benign over time. Corrigibility marks out a broad basin of attraction towards acceptable outcomes."
}

Calls set_claim_importance

{
  "claim_id": "aa5205cb-3287-477e-9e11-8fec1abc78c7",
  "reasoning": "The basin-of-attraction thesis is a named, recurring premise in debates over whether approximate alignment suffices for iterated AI development; disputed between the Christiano/Anthropic-adjacent and MIRI traditions, but unsettleable with current evidence and narrower than the central AI-risk claims.",
  "importance": 0.45,
  "contestation": 0.6
}