Episode 54 — Monitor internal changes that require AI risk reassessment (Task 6)
This episode explains which internal changes should trigger AI risk reassessment and why AAISM treats reassessment as a governance-controlled decision, not a vague “review occasionally” idea. You will learn internal triggers such as new data sources, changes in user population, new integrations, altered business objectives, model updates, pipeline refactors, and permission changes that expand access or reduce oversight. We use scenarios like deploying a model to a new customer segment, adding a new plugin, or switching from batch inference to real-time endpoints to show how internal changes alter threat exposure and control needs. Troubleshooting focuses on the most common failure: changes happening through normal engineering work without risk visibility, leading to silent drift between approved risk assumptions and actual production reality. Produced by BareMetalCyber.com, where you’ll find more cyber audio courses, books, and information to strengthen your educational path. Also, if you want to stay up to date with the latest news, visit DailyCyber.News for a newsletter you can use, and a daily podcast you can commute with.
