Shadow mode, drift alerts and audit logs: Inside the modern audit loop
Summary
The article emphasizes the need for continuous AI compliance through an audit loop, integrating real-time governance into AI development. This approach enhances safety, builds trust, and accelerates innovation by proactively addressing issues rather than relying on traditional, static audits.
Key Insights
What is shadow mode in the context of the modern AI audit loop?
Shadow mode refers to running AI models in a parallel, non-production environment to monitor their performance, detect anomalies, and ensure compliance without impacting live operations, allowing organizations to validate behavior before full deployment.
Sources:
[1]
What are drift alerts and audit logs in AI governance?
Drift alerts notify teams of performance deviations or anomalies in AI models in real-time, while audit logs provide continuous, automated records of AI behavior, data flows, and compliance checks, replacing static audits with proactive oversight.