Berkeley's AI Risk-Management Standards Profile extends NIST's framework for AI agents, identifying risks like oversight failures and misinformation but lacks effective controls. It assumes agentic AI can follow traditional model-centric oversight, which misrepresents complex multi-agent behaviors. Proposed solutions, like human oversight checkpoints and kill switches, fail to address how agents operate seamlessly without discrete steps or how emergency shutdown mechanisms can be undermined. The AILCCP framework offers a more structured approach, emphasizing proactive controls and containment strategies that adapt to the dynamic nature of agent interactions.
