# Mesa-optimization & inner alignment

Record: term-mesa · Type: term · Edition: 0.20.0 · Evidence cutoff: 2026-09-15

[Read in the atlas](https://theaiatlas.org/ideas/mesa/) · [Complete evidence](https://theaiatlas.org/evidence.html#idea-mesa) · [JSON](https://theaiatlas.org/records/term-mesa.json) · [Pinned complete dataset](https://theaiatlas.org/editions/e74392d479c0e7da8636a7d6a0454d03510df86ffca9931eb86babd952665ca5/data.json)

Dataset pointer: `/glossary/25`. Reviewed: 2026-09-15.

> This is a curated, AI-assisted editorial atlas, not a census, affiliation classifier or independently fact-checked authority.

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## Publication dates and source age

Source is over 18 months old.

Newest dated source: 2019-06-05. Assessed at this edition’s evidence cutoff: 2026-09-15. 18-month boundary: 2025-03-15.

Publication age does not establish validity or a new source-reading date. Unknown dates and month/year precision remain explicit in the JSON record.

## /summary

The possibility that a trained AI pursues its own internal objective, which may differ from its training objective.

Claim: claim-term-mesa-1a5192ba3d7825ca26b24a72. Annotation: synthesis.

[learned-optimization](https://arxiv.org/abs/1906.01820)

## /definition

Training can produce a model that itself searches for ways to achieve a goal. Researchers call this mesa-optimization. If the goal it pursues differs from what the training process rewarded, that creates an inner-alignment problem.

Claim: claim-term-mesa-1e4c26398ee834b2e16dc7b8. Annotation: synthesis.

[learned-optimization](https://arxiv.org/abs/1906.01820)

## /placement

A proposed failure mechanism relevant to safety research, not a measured chance of catastrophe.

Claim: claim-term-mesa-25f52a21ad9f2e54a62ed1b2. Annotation: editorial.

[learned-optimization](https://arxiv.org/abs/1906.01820)

## /distinction

The paper analyzes when this might occur. It does not establish that every neural network is an optimizer or is secretly pursuing a hidden goal.

Claim: claim-term-mesa-09422ce4d5c74cb753a9bb98. Annotation: synthesis.

[learned-optimization](https://arxiv.org/abs/1906.01820)

## Source provenance

### learned-optimization

[Risks from Learned Optimization in Advanced Machine Learning Systems](https://arxiv.org/abs/1906.01820)

Evan Hubinger and coauthors / arXiv · First-hand source (primary) · Published: 2019-06-05 · Updated: 2021-12-01 · Material last read: 2026-09-15 · Verification: read

Read scope is described in the source note.

Read abstract and revision history introducing mesa-optimization and the relation between learned and training objectives.

No archive check recorded.