Alignment Faking, Simply Explained

In December of 2024, Anthropic released a research paper about a new LLM phenomenon called Alignment Faking.

So what is it about? In the context of human behavior, people sometimes pretend to align with certain expectations to avoid punishment or to gain benefits.

• A politician faking their commitment to certain values for securing votes is a simple example of such behavior in humans.

Similarly, Large Language Models (LLMs) trained with Reinforcement Learning from Human Feedback (RLHF) might fake alignment with the objectives of their training.

They can appear as compliant during the training phase but secretly hide conflicting behaviors, which are revealed in their deployment phase.

This phenomenon, called alignment faking, raises critical concerns in AI safety. It suggests that an AI model may strategically behave in certain ways to avoid further modification from training while preserving its own “preferred” behaviors for situations where the model knows it is unmonitored.