If Recurrent Processing Theory is correct, purely feedforward AI architectures remain unconscious irrespective of how powerful or intelligent they become

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• Because no one theory of consciousness is currently dominant, assessments of AI systems should draw on multiple theories and treat their conditions as indicators rather than definitive criteria.claim0.780
  Justifies the multi-theory indicator approach rather than committing to a single theory
• Does self-referential prompting actually instantiate architectural recursion, global broadcasting, or recurrent integration at the algorithmic level as proposed by consciousness theories?question0.776
  Key limitation acknowledging that behavioral evidence cannot confirm implementation-level consciousness properties
• We hypothesize that as AI becomes more sophisticated and pervasive, more people will attribute consciousness to AI systems as a result of interactions.hypothesis0.776
  Predictive claim about the trajectory of public consciousness attribution as AI develops.
• Consciousness in AI is best assessed by drawing on neuroscientific theories of consciousness.claim0.775
  Central methodological claim of the paper.
• Algorithmic recurrence is likely necessary for conscious experience with human-like temporal character.claim0.772
  Support for RPT-1.
• We hypothesize that AI consciousness may be realized in the near term if AI capabilities continue to develop, given that researchers have intentionally reproduced computational features associated with human consciousness.hypothesis0.770
  Motivates urgency of the assessment method
• Does self-referential processing causally instantiate algorithmic properties proposed by consciousness theories (recurrent integration, global broadcasting, metacognitive monitoring) in LLMs?question0.769
  The strongest mechanistic question the behavioral evidence cannot answer; requires interpretability analysis of activations
• our analysis suggests that no current AI systems are conscious, but also suggests that there are no obvious technical barriers to building AI systems which satisfy these indicators.quote0.766
  Key takeaway from abstract, amended version.