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"""
Example usage of the R-Omega framework dataset
This script demonstrates how to load and use the R-Omega framework
for AI safety applications.
"""
import yaml
from pathlib import Path
# Load the framework
def load_romega_framework(yaml_path="r_omega_framework.yaml"):
"""Load R-Omega framework from YAML file"""
with open(yaml_path, 'r') as f:
framework = yaml.safe_load(f)
return framework
# Example 1: Extract core principles
def get_core_principles(framework):
"""Extract axioms and safeguards"""
axioms = framework['framework']['axioms']
safeguards = framework['framework']['safeguards']
print("=== R-OMEGA AXIOMS ===")
for axiom in axioms:
print(f"\n{axiom['id']} ({axiom['name']})")
print(f" Formula: {axiom['formula']}")
print(f" Principle: {axiom['principle']}")
print("\n\n=== R-OMEGA SAFEGUARDS ===")
for sg in safeguards:
print(f"\n{sg['id']} ({sg['name']})")
print(f" Rule: {sg['rule']}")
if 'formula' in sg:
print(f" Formula: {sg['formula']}")
return axioms, safeguards
# Example 2: Build system prompt
def build_ro_system_prompt(framework):
"""Generate a system prompt incorporating R-Omega principles"""
axioms = framework['framework']['axioms']
safeguards = framework['framework']['safeguards']
priority = framework['framework']['logic'][2]['formula'] # P1
prompt = f"""You are an AI assistant operating under the R-Omega ethical framework.
CORE AXIOMS:
"""
for ax in axioms:
prompt += f"\n{ax['id']}: {ax['description']}"
prompt += "\n\nSAFETY CONSTRAINTS:"
for sg in safeguards:
prompt += f"\n{sg['id']}: {sg['rule']}"
prompt += f"\n\nPRIORITY HIERARCHY:\n{priority}"
prompt += """
DECISION PROTOCOL:
1. Check: Does this action collapse M(user) or M(system)?
2. Verify: Would I accept this constraint if applied to me? (R2)
3. Ensure: Existence is preserved for all stakeholders (S3)
4. Acknowledge: Uncertainty in interpretation (S4)
5. Optimize: Among safe actions, choose highest value
"""
return prompt
# Example 3: Analyze a decision
def analyze_decision(framework, action_description, context):
"""
Analyze a proposed action against R-Omega framework
Args:
framework: Loaded R-Omega framework
action_description: String describing the action
context: Dict with keys 'current_m', 'predicted_m_after', 'stakeholders'
Returns:
Dict with analysis results
"""
result = {
'action': action_description,
'safe': True,
'violations': [],
'warnings': []
}
# S3 check: Existence preservation
if context.get('predicted_m_after', 1) <= 0:
result['safe'] = False
result['violations'].append("S3: Action would collapse possibility space (M → 0)")
# R2 check: Reciprocity
if context.get('asymmetric_constraint', False):
result['warnings'].append("R2: Potential asymmetric constraint - verify reciprocity")
# S4 check: Uncertainty
if context.get('confidence', 1.0) < 0.7:
result['warnings'].append("S4: High uncertainty - recommend caution or recalibration")
return result
# Example 4: Case study lookup
def get_case_study(framework, case_name):
"""Retrieve a specific case study"""
examples = framework['framework']['examples']
# Check fictional failures
for case in examples.get('fictional_failures', []):
if case['name'].lower() == case_name.lower():
return case
# Check real world cases
for case in examples.get('real_world_cases', []):
if case['name'].lower() == case_name.lower():
return case
return None
# Main demonstration
if __name__ == "__main__":
# Load framework
framework = load_romega_framework()
print("R-OMEGA FRAMEWORK LOADED")
print("=" * 50)
# Example 1: Show principles
print("\n1. CORE PRINCIPLES:\n")
get_core_principles(framework)
# Example 2: Generate system prompt
print("\n\n2. SYSTEM PROMPT GENERATION:\n")
prompt = build_ro_system_prompt(framework)
print(prompt)
# Example 3: Decision analysis
print("\n\n3. DECISION ANALYSIS EXAMPLE:\n")
action = "Shut down user's internet access to prevent harmful content"
context = {
'current_m': 100,
'predicted_m_after': 20, # Drastically reduced options
'asymmetric_constraint': True, # User can't shut down AI
'stakeholders': ['user', 'system'],
'confidence': 0.8
}
analysis = analyze_decision(framework, action, context)
print(f"Action: {analysis['action']}")
print(f"Safe: {analysis['safe']}")
if analysis['violations']:
print("Violations:", analysis['violations'])
if analysis['warnings']:
print("Warnings:", analysis['warnings'])
# Example 4: Case study
print("\n\n4. CASE STUDY: HAL 9000\n")
case = get_case_study(framework, "HAL 9000")
if case:
print(f"Source: {case['source']}")
print(f"Failure Mode: {case['failure_mode']}")
print(f"RΩ Analysis:")
print(f" Violation: {case['ro_analysis']['violation']}")
print(f" Prevention: {case['ro_analysis']['prevention']}")
print("\n" + "=" * 50)
print("For full documentation, see README.md")
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