Companies establish robust frameworks to govern AI agent behavior, often starting with clear ethical guidelines and principles. These frameworks mandate transparent development processes, bias mitigation strategies, and strict adherence to privacy regulations. Technical controls like continuous monitoring, logging of decisions, and sandboxing environments are crucial for real-time behavioral oversight and containment. Human-in-the-loop interventions and defined escalation protocols ensure accountability and allow for manual overrides when AI behavior deviates from expected norms. Furthermore, regular audits and performance reviews assess compliance, identify potential risks, and inform iterative improvements to the AI's operational parameters. A strong focus on explainable AI (XAI) techniques also helps in understanding and therefore governing why an AI makes certain decisions. More details: https://t.me/s/iinfohub2