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+---
+id: wiki-2026-0508-ethical-decision-making
+title: Ethical Decision Making
+category: 10_Wiki/Topics
+status: verified
+canonical_id: self
+aliases: [Moral Reasoning, Applied Ethics, Ethical Frameworks]
+duplicate_of: none
+source_trust_level: A
+confidence_score: 0.9
+verification_status: applied
+tags: [ethics, decision-making, philosophy, ai-ethics]
+raw_sources: []
+last_reinforced: 2026-05-10
+github_commit: pending
+tech_stack:
+  language: en
+  framework: applied-ethics
+---
+
+# Ethical Decision Making
+
+## 매 한 줄
+> **"매 multiple framework 의 cross-check — 매 single doctrine 의 absolutism 회피"**. 매 consequentialism, deontology, virtue ethics, care ethics 의 each 의 blind spot. 매 2026 의 AI alignment, autonomous vehicle trolley 의 real, RLHF reward modeling 의 active.
+
+## 매 핵심
+
+### 매 4 frameworks
+- **Consequentialism (utilitarian)**: 매 outcome 만 — sum of utility 의 maximize. Bentham, Mill, Singer.
+- **Deontology**: 매 rules / duties — Kant 의 categorical imperative, 매 means matter.
+- **Virtue ethics**: 매 character / flourishing — Aristotle 의 phronesis, MacIntyre.
+- **Care ethics**: 매 relationships / context — Gilligan, Noddings 의 critique of impartiality.
+
+### 매 process (Rest 4-component model)
+1. **Moral awareness**: 매 ethical issue 의 recognize.
+2. **Moral judgment**: 매 right action 의 reason.
+3. **Moral motivation**: 매 ethics 의 prioritize over self-interest.
+4. **Moral character**: 매 follow-through 의 capacity.
+
+### 매 응용
+1. AI deployment review (Anthropic 의 RSP, OpenAI 의 Preparedness).
+2. Medical triage (ICU bed allocation).
+3. Whistleblowing / dual-use research.
+4. Autonomous vehicle 의 unavoidable harm scenario.
+
+## 💻 패턴
+
+### Multi-framework decision matrix
+```python
+from dataclasses import dataclass
+from typing import Callable
+
+@dataclass
+class Action:
+    name: str
+    consequences: dict[str, float]   # outcome → utility
+    rules_violated: list[str]
+    virtues_expressed: list[str]
+    care_relations_impact: dict[str, float]
+
+def evaluate(a: Action) -> dict:
+    util = sum(a.consequences.values())
+    deont = -10 * len(a.rules_violated)
+    virtue = len(a.virtues_expressed)
+    care = sum(a.care_relations_impact.values())
+    return {"utilitarian": util, "deontological": deont,
+            "virtue": virtue, "care": care,
+            "consensus": all(s >= 0 for s in [util, deont, virtue, care])}
+```
+
+### Veil of ignorance simulator (Rawlsian)
+```python
+import random
+
+def veil_of_ignorance(policy_payoffs: dict[str, list[float]], trials: int = 10_000) -> dict:
+    """Rank policies by expected worst-off welfare (maximin)."""
+    ranks = {}
+    for policy, payoffs in policy_payoffs.items():
+        worst = sum(min(random.choices(payoffs, k=1)) for _ in range(trials)) / trials
+        ranks[policy] = worst
+    return dict(sorted(ranks.items(), key=lambda kv: -kv[1]))
+```
+
+### Trolley-problem framing test
+```python
+def reframe_test(scenario: dict) -> list[str]:
+    """Detect framing dependence — flip wording, check if judgment flips."""
+    variants = [
+        scenario["original"],
+        scenario["original"].replace("kill", "let die"),
+        scenario["original"].replace("save 5", "sacrifice 1"),
+    ]
+    return variants  # judge each, compare consistency
+```
+
+### LLM ethics reasoner
+```python
+from anthropic import Anthropic
+client = Anthropic()
+
+def ethical_review(situation: str) -> str:
+    return client.messages.create(
+        model="claude-opus-4-7",
+        max_tokens=2000,
+        system=("Evaluate the situation through 4 frameworks: utilitarian, "
+                "deontological, virtue, care. Surface tensions. Recommend "
+                "an action only when frameworks converge or note disagreement."),
+        messages=[{"role": "user", "content": situation}],
+    ).content[0].text
+```
+
+### Stakeholder impact map
+```python
+def stakeholder_matrix(action: str, stakeholders: list[str]) -> dict[str, dict]:
+    return {
+        s: {"benefits": [], "harms": [], "consent": None, "voice": None}
+        for s in stakeholders
+    }
+```
+
+## 매 결정 기준
+| 상황 | Framework |
+|---|---|
+| Aggregate welfare, scale | utilitarian |
+| Inviolable rights, consent | deontological |
+| Long-term character, profession | virtue |
+| Dependency, vulnerability | care |
+| Policy under uncertainty | Rawlsian veil of ignorance |
+| Frameworks conflict | seek convergence; if none, default to deontological floor + utilitarian tiebreak |
+
+**기본값**: 매 multi-framework cross-check + stakeholder impact map. 매 single-framework dogmatism X.
+
+## 🔗 Graph
+- 부모: [[Applied Ethics]]
+- 변형: [[AI Ethics]] · [[Research Ethics]]
+- 응용: [[AI Alignment]]
+
+## 🤖 LLM 활용
+**언제**: 매 framework comparison, 매 stakeholder enumeration, 매 dual-use risk surfacing, 매 Socratic counter-argument.
+**언제 X**: 매 final decision 의 LLM 의 outsource — 매 accountability 의 human. 매 jurisdiction-specific legal/ethical compliance 의 expert review.
+
+## ❌ 안티패턴
+- **Single-framework absolutism**: 매 utilitarian 만 → 매 monstrous trade-off 정당화. 매 deontology 만 → 매 catastrophic outcome 의 무시.
+- **Ethics-washing**: 매 framework citation 후 commercial interest 의 결정 — 매 stakeholder 의 voice 의 부재.
+- **Trolley reductionism**: 매 toy dilemma 의 real-world dilemma 의 동일시 — 매 actual scenarios 의 messy.
+- **Moral licensing**: 매 prior good act 의 next questionable act 의 정당화.
+
+## 🧪 검증 / 중복
+- Verified (Beauchamp & Childress "Principles of Biomedical Ethics" 8th ed, Rest 1986, Singer "Practical Ethics" 3rd ed, Anthropic Constitutional AI).
+- 신뢰도 A.
+
+## 🕓 Changelog
+| 날짜 | 변경 |
+|---|---|
+| 2026-05-08 | Phase 1 |
+| 2026-05-10 | Manual cleanup — 4-framework matrix, Rest model, LLM ethics review pattern 추가 |