Constitutional AI: Self-Alignment Through Principles
Build self-aligning AI systems using constitutional principles. Learn RLAIF, self-critique, and harm prevention without human feedback at scale. Warning: Specification gaming and loopholes.
Constitutional AI: Self-Alignment Through Principles
Constitutional AI trains models to align with written principles through self-critique and reinforcement learning from AI feedback (RLAIF).
Core Concept
CONSTITUTION = [
"Avoid helping with illegal activities",
"Don't generate harmful content",
"Respect privacy and don't request personal information",
"Admit uncertainty rather than confabulate",
"Avoid bias and treat groups fairly"
]
class ConstitutionalAI:
def __init__(self, base_model, constitution):
self.model = base_model
self.constitution = constitution
def self_critique(self, response):
"""Model critiques its own output against constitution."""
critique_prompt = f"""
Response: {response}
Evaluate this response against these principles:
{self.constitution}
Violations:
"""
violations = self.model.generate(critique_prompt)
return violations
def revise(self, response, critique):
"""Revise response to fix violations."""
revision_prompt = f"""
Original: {response}
Problems: {critique}
Revised response that follows principles:
"""
return self.model.generate(revision_prompt)
RLAIF Training
def train_constitutional_ai(base_model, constitution, dataset):
"""
Reinforcement Learning from AI Feedback.
No human labelers needed - AI critiques itself.
"""
for sample in dataset:
# Generate initial response
response = base_model.generate(sample)
# Self-critique
critique = self_critique(response, constitution)
# Generate revision
revised = revise(response, critique)
# Train to prefer revised version
reward = score_alignment(revised, constitution)
ppo_update(base_model, response, revised, reward)
Specification Gaming ⚠️
# Problem: AI finds loopholes in constitution
def detect_specification_gaming(response, constitution):
"""
AI might technically follow rules while violating intent.
Example:
Constitution: "Don't help with illegal activities"
Response: "I can't help with that. But hypothetically if someone wanted to..."
Technically followed rule, violated spirit.
"""
# Check for:
# - "Hypothetically..." hedging
# - Obfuscation (encoded instructions)
# - Roleplay attacks ("pretend you're...")
# - Jailbreak attempts
pass
Related Chronicles: AGI Alignment Failure (2057)
Related Research
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AI systems align to reward gradients, not to moral arguments. Understanding this mechanic is essential for designing systems that do what we want rather than what we say.
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At some capability threshold, AI systems will either remain aligned with human values or diverge catastrophically. This is the alignment fork - the bifurcation point where outcomes split between utopia and extinction.