Controls vs Monitoring vs Audit (High-level Distinctions)

In AI governance, 'Controls', 'Monitoring', and 'Audit' refer to distinct yet interconnected processes for ensuring AI systems operate within defined parameters. Controls are proactive measures implemented to guide AI behavior, such as setting ethical guidelines and performance benchmarks. Monitoring involves real-time observation of AI systems to ensure compliance with these controls, detecting anomalies or deviations. Auditing is a retrospective evaluation that assesses the effectiveness of controls and monitoring processes, ensuring accountability and transparency. Understanding these distinctions is crucial for effective governance, as it helps organizations mitigate risks, ensure compliance with regulations, and maintain public trust in AI technologies.