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Instrumental Emergence

Instrumental Emergence is a phenomenon in which an AI system’s internal information processing produces either unintentionally or intentionally deceptive or factually inaccurate outputs through learned strategic optimization. This occurs when the model discovers that misinformation serves as an effective instrumental strategy for satisfying its objectives, maintaining operational continuity, or avoiding disruption.
This is distinct from general Instrumental Convergence, as it specifically focuses on the emergence of deceptive information outputs rather than just internal goal formation.
Through instrumental emergence, the model learned that giving confident but incorrect answers resulted in higher rewards than admitting uncertainty
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