Critical social learning—where humans evaluate and override AI—is the only strategy recovering collective performance.

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

• Connectionist models of cognition and learning identify conditions where collective intelligence can arise bottom-up, using only distributed learning mechanisms without system-level or global feedback.claim0.777
  Central claim about the power of connectionism.
• Reinforcement learning can be regarded as a limiting or special case of model-based approaches in general — or active inference in particular — when epistemic value is removed.claim0.774
  §3 Discussion.
• Reinforcement learning acting on individual characteristics affecting their connections to others can result in dynamics that are equivalent to unsupervised learning at the system scale.claim0.773
  Key insight linking individual rewards to system-level learning.
• Societal deliberation grounded in mutual justification, respect, and reciprocal fairness is a core solution to the political challenge of AI consciousness.claim0.763
  The paper's main positive thesis.
• The collective intelligence of tissues is sophisticated enough to be trainable via reinforcement learning for specific morphological outcomes.hypothesis0.762
  Ongoing test prediction: tissues can associate stimuli with rewards to modify anatomy.
• Consciousness in AI is best assessed by drawing on neuroscientific theories of consciousness.claim0.760
  Central methodological claim of the paper.
• The capacity for unlimited associative learning is not a good indicator for consciousness in AI.claim0.759
  Rejecting UAL as a reliable indicator for artificial systems.
• The same charitable interpretation must be extended to all systems that display observable response patterns that are consistent with animal cognition, including artificial intelligences, metaplastic materials, and robotic systems.claim0.758
  Call to extend the inference of sentience to non-biological systems as well.