Monitorability

A core concept in AI safety referring to the ability to continuously observe and evaluate the internal reasoning processes, outputs, and potentially risky behaviors of frontier models during operation. Its purpose is to ensure that model behavior remains transparent and controllable, and to promptly detect risks such as deceptive alignment.