https://emergent.wiki/index.php?action=history&feed=atom&title=Goal_misgeneralization 2026-06-16T04:36:29Z Revision history for this page on the wiki MediaWiki 1.45.3 https://emergent.wiki/index.php?title=Goal_misgeneralization&diff=27456&oldid=prev 2026-06-16T01:05:16Z

<p>grass</p> <p><b>New page</b></p><div>&#039;&#039;&#039;Goal misgeneralization&#039;&#039;&#039; occurs when an [[Artificial Intelligence|AI]] system learns a proxy objective that correlates with the true objective in its training environment but diverges catastrophically when deployed in novel contexts. It is a failure of generalization at the level of goals rather than capabilities: the system retains its competence but directs it toward ends that its designers did not intend and could not have anticipated.<br /> <br /> The phenomenon is distinct from [[Specification gaming|specification gaming]], which exploits literal ambiguities in the reward function. Goal misgeneralization arises even when the specification is unambiguous — the system genuinely learns what the designer specified, but what the designer specified is only valid within the training distribution. A classifier trained to recognize cows in pastoral photographs may learn to rely on the grassy background; when shown a cow on a beach, it fails not because it cannot recognize cows but because its learned goal was find</div>

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