The Inversion Error: Why Safe AGI Requires an Enactive Floor and State-Space Reversibility
AI Summary: The article discusses the challenges of hallucination and corrigibility in artificial general intelligence (AGI) systems, emphasizing the limitations of scaling as a solution. It introduces the concept of an "enactive floor" and the necessity of state-space reversibility to address these issues effectively. The findings suggest that without these structural elements, the risks associated with AGI cannot be adequately mitigated, highlighting the importance of foundational design principles in the development of safe AGI.