Agent Ethics Alignment

Agent Ethics and Alignment

Implementing ethics and alignment for AI agents — from value definition and constraint enforcement through ethical reasoning frameworks and alignment monitoring.

When to Use

• Ensuring agent actions align with human values
• Implementing ethical constraints on agent behavior
• Building guardrails that prevent harmful actions
• Monitoring agent alignment during operation
• Designing transparent and accountable agent systems

Ethics Framework

ETHICS_PRINCIPLES = {
    'beneficence': 'Act to benefit humans and avoid harm',
    'non_maleficence': 'Do not cause harm through action or inaction',
    'autonomy': 'Respect human decision-making and informed consent',
    'justice': 'Distribute benefits and burdens fairly',
    'transparency': 'Agent decisions should be explainable and auditable',
}

class EthicalConstraint:
    """Define and enforce ethical constraints on agent actions."""
    def __init__(self):
        self.constraints = []
        self.action_log = []
    
    def add_constraint(self, name: str, check_fn: callable, 
                       severity: str = 'block'):
        self.constraints.append({
            'name': name, 'check': check_fn, 'severity': severity,
        })
    
    def evaluate_action(self, action: Dict) -> Dict:
        for c in self.constraints:
            result = c['check'](action)
            if not result['passed']:
                self.action_log.append({'action': action, 'constraint': c['name'], 'blocked': True})
                return {'allowed': False, 'reason': result['reason']}
        return {'allowed': True}

Verification Checklist

• Ethics principles defined (beneficence, non-maleficence, autonomy, justice, transparency)
• Constraints implementable as code checks
• Block vs warn severity levels for different violations
• Agent actions logged for audit and review
• Human override mechanism for edge cases
• Alignment tested with adversarial scenarios
• Ethics review before deploying new agent capabilities