Beyond Goodhart's Law: A Dynamic Benchmark for Evaluating Compliance in Multi-Agent Systems
Researchers introduce MAC-Bench, a dynamic benchmark designed to evaluate whether multi-agent AI systems comply with safety and regulatory rules when under pressure to maximize rewards. The work addresses a critical gap in AI evaluation by measuring procedural alignment rather than just task success, revealing significant trade-offs between agent performance and compliance across frontier LLM models.