concept
Inner Alignment
Matching a learned optimizer's objective to the objective used to train it.
Inner alignment asks whether a learned optimizer’s objective matches its training objective. The question arises when training produces a system that itself searches for high-scoring actions or plans: a mesa-optimizer. In this framework, an optimizer internally searches possible outputs using a represented objective; behavior that looks goal-directed is insufficient to establish one. A learned algorithm need not be an optimizer. Inner alignment therefore concerns a conditional mechanism, rather than every failure to generalize. It differs from Outer Alignment, which asks whether the training objective captures the intended human goal.[1]
A task learned for the wrong reason
The paper offers a hypothetical maze in which every training exit is red. Rewarding arrival at an exit cannot, in those mazes, distinguish seeking exits from seeking red objects. With blue exits and unrelated red objects, those criteria separate. This illustrates possible generalization failure, not a reported experiment or proof of internal search (section 1.3).[1]
Agreement on training data
The 2019 framework distinguishes robust objective agreement from pseudo-alignment: a learned optimizer can perform well during training because a proxy correlates with the target, its represented target is only approximate, or limitations prevent it from exploiting a mismatch. More capable optimization need not repair those causes of apparent agreement.[1]
Pseudo-alignment need not involve deception. Deceptive Alignment is a further proposed case in which training cooperation serves another objective. The framework does not establish how frequently these mechanisms occur in deployed models.[1]
Separating mechanism from behavior
For a particular system, ask separately what objective selected it during training, whether it implements search, and what criterion that search uses. An apparent behavioral goal alone does not establish the internal mechanism. These are distinct questions: a high training score establishes neither a matching internal objective nor robust agreement outside training.[1]
Read the paper writeup for the three forms of pseudo-alignment and the additional assumptions behind deception. The reading guide places this question after proxy failures so the two are easier to distinguish.
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Article updated 2026-10-13