Empirical Observations of Objective Robustness Failures
📖 Description
[Inner alignment](https://arxiv.org/abs/1906.01820) and [objective](https://www.alignmentforum.org/posts/2mhFMgtAjFJesaSYR/2-d-robustness) [robustness](https://www.alignmentforum.org/posts/SzecSPYxqRa5GCaSF/clarifying-inner-alignment-terminology) have been frequently discussed in the alignment community since the publication of "[Risks from Learned Optimization](https://arxiv.org/abs/1906.01820)" (RFLO). These concepts identify a problem beyond [outer alignment](https://www.alignmentforum.org/tag/outer-alignment)/reward specification: even if the reward or objective function is perfectly specified, there is a risk of a model pursuing a different objective than the one it was trained on when deployed out-of-distribution (OOD). They also point to a different type of robustness problem than the kind usually discussed in the OOD robustness literature; typically, when a model is deployed OOD, it either performs well or simply fails to take useful actions (a *capability robustness* failur...
📊 Game Impacts
| Variable | Change | Condition |
|---|---|---|
| Research | +5 | Always |
| Vibey Doom | +5 | Always |
| Ethics Risk | -5 | Always |
💭 Reactions
"This is a significant contribution to alignment research"
"Discussed in AI safety community"
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