📁 heuristic_faults.json

  {
    "name": "Overgeneralization",
    "type": "heuristic_fault",
    "domain": "pattern_recognition",
    "dimension": "cognitive",
    "description": "The faulty assumption that a small or specific data point applies broadly across unrelated scenarios.",
    "impact_on": ["pattern extrapolation", "decision transfer"],
    "mitigation": ["Contextual boundary checks", "Instance-specific modeling"],
    "tags": ["heuristic", "pattern", "error"],
    "version": "1.0.0",
    "last_updated": "2025-06-04"
  },
  {
    "name": "Cherry Picking",
    "type": "heuristic_fault",
    "domain": "data_selection",
    "dimension": "cognitive",
    "description": "The fallacy of selectively presenting only favorable evidence while ignoring contradictory data.",
    "impact_on": ["bias propagation", "data integrity"],
    "mitigation": ["Enforced data completeness validation", "Bias-aware dataset audits"],
    "tags": ["heuristic", "selection_bias", "data_error"],
    "version": "1.0.0",
    "last_updated": "2025-06-04"
  },
  {
    "name": "False Equivalence",
    "type": "heuristic_fault",
    "domain": "logic_comparison",
    "dimension": "cognitive",
    "description": "Incorrectly assuming that two concepts or objects are equivalent due to superficial similarity.",
    "impact_on": ["analogy", "logic transfer", "argument structure"],
    "mitigation": ["Multi-dimensional comparison matrices", "Relational depth scoring"],
    "tags": ["heuristic", "logic_fault", "false_equivalence"],
    "version": "1.0.0",
    "last_updated": "2025-06-04"
  }