{
  "schema": "vedokrok.public-item.v1",
  "release_id": "MHC-RPUB-20260920-75ad787a",
  "url": "/knowledge/test-actual-skill-before-letting-perceived-expertise-override-ai-advice",
  "id": "MHC-D-RESEARCH-0500",
  "version": "0.1.0",
  "title": "Test actual skill before letting perceived expertise override AI advice",
  "summary": "Self-confidence is useful only when it tracks competence.",
  "kind": "protocol",
  "body": "For repeated task classes, compare the person's unaided performance and confidence before using self-perceived expertise as a routing signal. High verified skill can justify more human autonomy; high self-confidence without discrimination should not automatically suppress useful AI checks.",
  "limits": [
    "Expertise can include contextual knowledge that benchmark cases miss; combine performance evidence with domain judgment."
  ],
  "topics": [
    "union-ai-reliance-metacognition"
  ],
  "intents": [],
  "source_ids": [
    "RS-BE3598079F5EB695",
    "RS-3CFE1F643A73D6BC"
  ],
  "evidence": [
    {
      "claim": "A 2026 two-study paper found trust predicted both consultation and adoption of ChatGPT input, while perceived expertise reduced reliance even when perceived expertise did not necessarily equal actual skill.",
      "source_id": "RS-BE3598079F5EB695",
      "role": "supports",
      "note": "The relationship between perceived expertise and true competence is task-specific.",
      "locator": "Abstract highlights"
    },
    {
      "claim": "A 2026 study found metacognitive estimates of one's own confidence shape responses to AI advice and limited metacognitive sensitivity can produce inconsistent advice-taking.",
      "source_id": "RS-3CFE1F643A73D6BC",
      "role": "supports",
      "note": "Detailed boundary conditions should be interpreted from the full study rather than the abstract alone.",
      "locator": "Abstract highlights"
    }
  ],
  "use_when": [
    "A user rejects AI assistance because they feel expert, or accepts it because they feel inexperienced."
  ],
  "avoid_when": [
    "Expertise can include contextual knowledge that benchmark cases miss; combine performance evidence with domain judgment."
  ],
  "example": "A senior analyst who feels expert in a new vendor API should still benchmark unaided accuracy before rejecting all tool support.",
  "check": "The reliance policy responds to demonstrated task competence rather than job title or subjective expertise alone.",
  "steps": [
    "Unaided performance is measured on representative cases.",
    "Self-confidence is recorded separately.",
    "Confidence-accuracy alignment is inspected.",
    "Routing rules distinguish verified skill from self-labels.",
    "Performance is rechecked as the task changes."
  ],
  "sources": [
    {
      "id": "RS-BE3598079F5EB695",
      "title": "Who listens to ChatGPT and when should they? A two-study examination of AI-assisted decision making",
      "url": "https://www.sciencedirect.com/science/article/pii/S2949882126000344"
    },
    {
      "id": "RS-3CFE1F643A73D6BC",
      "title": "AI advice and human metacognition",
      "url": "https://www.sciencedirect.com/science/article/pii/S0167923626001466"
    }
  ],
  "relations": [],
  "collections": [
    {
      "id": "RC-39B535F35706B375",
      "title": "Calibrate when to rely on AI instead of measuring trust as a feeling",
      "url": "/collections/calibrate-when-to-rely-on-ai-instead-of-measuring-trust-as-a-feeling"
    }
  ]
}