Error-Sensitive Model of Overlapping Consensus

Entities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.

• Overlapping Consensusconcept0.829
  Agreement on policies endorsed by different worldviews for different reasons; drawn from Rawls and applied to AI consciousness.
• Mutual-Benefit Model of Overlapping Consensusconcept0.814
  One of two models for overlapping consensus: seeks actions justifiable by both AI and human welfare interests.
• Overlapping consensus on AI-consciousness-related policies is achievable even under persistent disagreement about AI consciousness itself.claim0.748
  Key positive claim about the tractability of the political challenge via deliberation.
• Acknowledgment of possible error about AI consciousness, combined with recognition of error costs, can motivate overlapping consensus on precautionary policies.claim0.747
  The error-sensitive model of overlapping consensus.
• Interpretability features converge across different model architectures, revealing structural similarities.claim0.736
• Different models cannot converge to the same representation if they have access to fundamentally different information; convergence is capped by mutual information between input signalsclaim0.734
  Key limitation of the PRH for non-bijective observations
• Diffusion-Aggregation Modelconcept0.733
  Computational models of crystal growth that produce rough overall symmetry but fail to explain the detailed identical sub-symmetries on snowflake arms
• Cross-Model Semantic Convergenceconcept0.731
  The tighter clustering of experience-report embeddings across independently trained model families under self-referential processing