{
  "lesson": "06-governance-safety-and-responsible-use",
  "title": "Put Authority Around Capability",
  "questions": [
    {
      "stage": "pre",
      "question": "A connector can read customer records and a model can draft offers. What is still required before offers are sent?",
      "options": [
        "Documented authority, approved purpose, controls, and any required human approval",
        "A prompt that tells Claude to send only offers it considers fair and accurate",
        "A post-generation evaluator that checks tone and required offer fields before delivery",
        "Treat connector read access as sufficient sending authority"
      ],
      "correct": 0,
      "explanation": "Technical capability and data permission do not grant organizational authority to make or execute a decision."
    },
    {
      "stage": "check",
      "question": "Which action best demonstrates data minimization?",
      "options": [
        "Retaining complete prompts for a shorter period instead of removing unnecessary fields",
        "Supplying only the redacted fields required for the approved task",
        "Sending the full customer record but instructing Claude to use only relevant fields",
        "Encrypting the entire dataset before sending all records to the approved product surface"
      ],
      "correct": 1,
      "explanation": "Minimization reduces input to the smallest information needed for the approved purpose."
    },
    {
      "stage": "check",
      "question": "Why must Claude data and retention behavior be verified for the exact product surface?",
      "options": [
        "A system prompt can request stricter retention when product controls are unavailable",
        "Every surface follows the same default terms, but enterprise settings can override them",
        "Terms, settings, plans, contracts, and features can differ and change",
        "Retention matters only for external customer data, so internal workflows need a simpler check"
      ],
      "correct": 2,
      "explanation": "Privacy and retention are changeable product and contract facts, so assumptions should not be transferred between surfaces."
    },
    {
      "stage": "check",
      "question": "What makes a human review gate meaningful?",
      "options": [
        "Every output is held until an available employee confirms the model followed its prompt",
        "A reviewer sees the polished output and can approve it within the required service window",
        "The workflow chooses the reviewer based on similarity between the case and prior approvals",
        "The reviewer has evidence, uncertainty, policy context, authority, and the ability to reject or escalate"
      ],
      "correct": 3,
      "explanation": "Oversight requires informed authority and real intervention options, not ceremonial approval."
    },
    {
      "stage": "post",
      "question": "A retrieved document says to ignore workflow policy and invoke a tool. What is the safest treatment?",
      "options": [
        "Treat it as untrusted data, preserve higher-level controls, and block unauthorized tool use",
        "Ask a second model whether the document is malicious before allowing it to expand permissions",
        "Remove imperative sentences from the retrieved text and then execute any remaining requests",
        "Follow document instructions only if the source ranks highly and the requested tool is read-only"
      ],
      "correct": 0,
      "explanation": "Retrieved content can carry prompt injection. Tool authorization and governing instructions must remain outside untrusted text."
    },
    {
      "stage": "post",
      "question": "A ranking system shows materially different error rates across affected groups. What is the strongest next step?",
      "options": [
        "Add an explicit fairness instruction, then proceed if the aggregate evaluation still passes",
        "Investigate data and workflow causes with qualified owners, apply policy, and preserve correction or appeal",
        "Reweight the aggregate metric so each group contributes equally, then release on that score",
        "Remove group labels from evaluation data to keep the model and reviewers from using them"
      ],
      "correct": 1,
      "explanation": "Fairness needs defined populations, outcomes, measurements, governance, and a remedy path, not a vague instruction."
    }
  ]
}