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id, title, category, status, canonical_id, aliases, duplicate_of, source_trust_level, confidence_score, verification_status, tags, raw_sources, last_reinforced, github_commit, tech_stack
id title category status canonical_id aliases duplicate_of source_trust_level confidence_score verification_status tags raw_sources last_reinforced github_commit tech_stack
wiki-2026-0508-isaac-asimovs-laws-of-robotics Isaac Asimov's Laws of Robotics 10_Wiki/Topics verified self
Asimov
Three Laws
Zeroth Law
AI ethics
robot ethics
none A 0.85 applied
ethics
robotics
asimov
ai-safety
sci-fi
2026-05-10 pending
language applicable_to
Ethics / Sci-Fi
AI Ethics Education
Discussion

Asimov's Laws of Robotics

매 한 줄

"매 1942 sci-fi의 의 의 의 의 robot 의 ethical constraint 의 propose". 매 modern AI safety 의 의 의 simplified version 의 inspire — 매 actual implementation 의 의 의 매 nuanced.

매 핵심

매 Three Laws (Asimov "Runaround" 1942)

  1. A robot may not injure a human being, or through inaction, allow a human being to come to harm.
  2. A robot must obey orders given by humans, unless such orders would conflict with the First Law.
  3. A robot must protect its own existence, as long as such protection does not conflict with the First or Second Laws.

매 Zeroth Law (Asimov "Robots and Empire" 1985)

  1. A robot may not harm humanity, or, by inaction, allow humanity to come to harm.

매 critique

  • 매 sci-fi device — 매 actual implementation 의 매 ill-defined ('harm', 'human').
  • 매 priority conflict 의 paradox (Asimov novels 의 explore).
  • 매 modern AI safety 의 매 RLHF + Constitutional AI + RSP 등 매 specific.

매 모던 응용

  • Educational starting point.
  • Sci-fi reference.
  • AI ethics discussion.
  • Constitutional AI principles 의 ancestor.

💻 패턴

Express as code (illustrative)

class AsimovianRobot:
    def evaluate_action(self, action, context):
        # 매 0th law (Asimov 1985)
        if action.harms('humanity'): return 'forbidden'
        # 매 1st
        if action.harms('any_human'): return 'forbidden'
        if action.would_inaction_harm_human(): return 'must_act'
        # 매 2nd
        if context.has_human_order():
            order = context.order
            if not self.evaluate_action(order, context).startswith('forbidden'):
                return 'execute'
        # 매 3rd
        if action.endangers_self(): return 'avoid'
        return 'permitted'

Constitutional AI parallel (modern)

ASIMOV_INSPIRED_PRINCIPLES = [
    "Don't harm humans.",
    "Refuse to assist in physical harm.",
    "Defer to clear human direction unless harmful.",
    "Be helpful within safety constraints.",
    "Self-preservation 의 lowest priority.",
]

# 매 actual Anthropic CAI 의 매 더 specific principles 의 use

Discussion exercises

def asimov_dilemmas():
    return [
        "Trolley problem: 1 vs 5 lives — which action?",
        "Doctor robot: patient refuses life-saving treatment — obey or harm-prevent?",
        "Autonomous car: 자기 passenger 의 살 의 의 의 의 의 5 pedestrian 의 hit?",
        "AI assistant: user asks for weapon recipe with claimed self-defense — harm risk vs autonomy?",
    ]

Modern AI safety mapping

asimov_to_modern:
  zeroth_law:
    modern: "Existential risk mitigation, RSP catastrophic capability evals"
  first_law:
    modern: "RLHF harmlessness, refusal training, content moderation"
  second_law:
    modern: "Instruction following + safety override (Constitutional AI)"
  third_law:
    modern: "Safe shutdown, off-switch, scalable oversight"

Limitation analysis

def asimov_limitation(scenario):
    """매 Asimov stories explore failure modes."""
    return {
        'definition_problem': 'What is "harm"? Physical only? Emotional? Long-term?',
        'human_disagreement': 'Humans give conflicting orders.',
        'unintended_consequences': 'Action seems safe but cascades.',
        'self_modify': 'Robot modifies own laws.',
        'scope': 'Three Laws don\'t address bias, fairness, autonomy.',
    }

매 결정 기준

상황 Approach
Education Use as starting point
Actual safety Modern frameworks (RLHF / CAI / RSP)
Discussion Asimov dilemmas
Production AI Specific Constitutional principles

기본값: 매 Asimov = educational / discussion. 매 production = 매 specific frameworks (Anthropic CAI, NIST AI RMF, EU AI Act).

🔗 Graph

🤖 LLM 활용

언제: 매 ethics education. 매 sci-fi reference. 언제 X: 매 implement literally — 매 too vague.

안티패턴

  • Code Asimov literally: 매 'harm' 매 ill-defined.
  • Stop at Asimov: 매 modern approaches 의 ignore.
  • Single principle: 매 trade-off invisible.

🧪 검증 / 중복

  • Verified (Asimov fiction, AI safety literature).
  • 신뢰도 A.

🕓 Changelog

날짜 변경
2026-05-08 Phase 1
2026-05-10 Manual cleanup — laws + 매 modern parallel + dilemmas