One of the primary strategies for managing AI dementia is the implementation of robust rollback mechanisms. These systems should allow for a swift return to a previously stable and verified state. Regular checkpoints and backups of AI models are essential, enabling developers to revert to a functional version if dementia is detected.
So you have rollbacks, but you also have things like automated tests, staged changes, robust observability, logging, and metrics, fine-grained permissions, etc etc