Model containment places technical and operational boundaries around a model so unwanted behavior cannot easily reach consequential systems. Measures can include isolated environments, network restrictions, narrow tools, temporary credentials, action limits, and approval gates.
Containment should match measured capability and the impact of failure. It complements training and monitoring because even a well-tested model can encounter unfamiliar conditions or find an unexpected path to an authorized resource.
ELI5
Model containment is like keeping an AI system inside a clearly fenced workspace. The system receives only the data, tools, and permissions needed for its task, while important boundaries are watched and enforced.
For example, researchers can test a model in an isolated computer environment with no access to real customer records or public systems. If the model attempts an unexpected action, the test can be stopped without giving it a path to affect those outside resources.
What controls can provide model containment?
Sandboxes, network restrictions, narrow permissions, temporary credentials, tool allowlists, action budgets, monitoring, and human approval can all contribute.
Does containment replace safety training?
No. Containment limits consequences, while training, evaluation, monitoring, and incident response address other parts of the risk.
