{
  "lesson": "21-fairness-criteria-group-individual-counterfactual",
  "title": "Fairness Criteria - Group, Individual, Counterfactual",
  "questions": [
    {
      "stage": "pre",
      "question": "Which best matches the demographic-parity definition for groups A=a and A=a'?",
      "options": [
        "Equal predictive value across groups",
        "Equal true-positive and false-positive rates across groups",
        "Equal acceptance rates: P(Y=1 | A=a) = P(Y=1 | A=a')",
        "Equal Lipschitz constant across groups"
      ],
      "correct": 2,
      "explanation": ""
    },
    {
      "stage": "check",
      "question": "What does the Chouldechova / Kleinberg-Mullainathan-Raghavan 2017 impossibility result say?",
      "options": [
        "Under unequal base rates, demographic parity, equalized odds, and conditional use accuracy equality cannot all hold simultaneously",
        "Individual fairness implies counterfactual fairness for any DAG",
        "Counterfactual fairness implies demographic parity",
        "Group fairness is always achievable by re-weighting"
      ],
      "correct": 0,
      "explanation": ""
    },
    {
      "stage": "check",
      "question": "Dwork et al. 2012 define individual fairness via:",
      "options": [
        "A causal DAG with a sensitive-attribute intervention",
        "Equal accuracy across protected groups",
        "A Lipschitz condition on the decision map relative to a task-specific similarity metric, so similar individuals get similar decisions",
        "Demographic parity at the individual level"
      ],
      "correct": 2,
      "explanation": ""
    },
    {
      "stage": "check",
      "question": "Counterfactual fairness (Kusner et al. 2017) requires:",
      "options": [
        "Equal Lipschitz constants for all groups",
        "Only group-level statistics",
        "No causal assumptions",
        "A causal DAG; the decision is unchanged when the individual's sensitive attribute is counterfactually altered"
      ],
      "correct": 3,
      "explanation": ""
    },
    {
      "stage": "post",
      "question": "Why do backtracking counterfactuals (arXiv:2401.13935) matter for legal compliance?",
      "options": [
        "They replace embedding-based bias metrics",
        "They eliminate the need for any causal model",
        "They prove the impossibility theorem is wrong",
        "Instead of intervening on a protected attribute (which is legally problematic), they ask which combination of actual features would have produced the counterfactual outcome"
      ],
      "correct": 3,
      "explanation": ""
    },
    {
      "stage": "post",
      "question": "What does the ICLR Blogposts 2024 philosophical reconciliation argue?",
      "options": [
        "With an explicit causal graph, satisfying certain group-fairness measures entails counterfactual fairness, so the apparent opposition between families is partly an artifact of leaving the causal model implicit",
        "Group and counterfactual fairness are unrelated",
        "Only individual fairness is justifiable",
        "The impossibility theorems are resolved by re-weighting"
      ],
      "correct": 0,
      "explanation": ""
    }
  ]
}