Thm. 3.2] we can construct an SCM

RCM. Finally, we illustrate the power of this conciliatory perspective by pinpointing

Obtaining human-interpretable explanations of large, general-purpose language models is an urgent goal for AI safety.

Learning from active human involvement enables the human subject to actively intervene and demonstrate to the AI agent during training. The interaction and corrective feedback from human brings safety and AI alignment to the learning process.

Our framework may be thought of as a generalization of the synthetic control and synthetic interventions frameworks, where data is collected via an adaptive intervention assignment policy.

Our framework may be thought of as a generalization of the synthetic control and synthetic interventions frameworks, where data is collected via an adaptive intervention assignment policy.

In many scientific applications, we observe a system in different conditions in which its components may change, rather than in isolation.

In these processes, an evaluator estimates an individual's value to an institution.

Concept erasure aims to remove specified features from a representation. It can improve fairness (e.g.