AI self-reports about experience constitute valid empirical data even without proving consciousness.

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• Consciousness in AI is best assessed by drawing on neuroscientific theories of consciousness.claim0.816
  Central methodological claim of the paper.
• Interpretability findings can validate or invalidate what AI systems claim about their own experience.claim0.810
• Self-reports show only weak correlation with human perceptions of AI assistant persona and can diverge from behavioral patternsclaim0.805
  Motivation for using revealed preferences rather than self-reports in evaluation
• The notion of self as illusion, as realized in AI and ALife practices, may contribute to novel fields of affordances for non-human intelligence.claim0.799
  Claim that endowing non-human agents with self-illusion awareness expands their affordance repertoire.
• No AI eval company measures phenomenology—inner observation, aliveness, paradox-holding—only capability or preference.claim0.797
• Can we develop quantitative or behavioral tests for consciousness in AI?question0.795
  Outstanding question about alternative or complementary assessment methods
• When LLMs produce experience claims under self-reference, is this sophisticated simulation or genuine self-representation, and how would we tell the difference?question0.793
  The core interpretive question the paper narrows but cannot definitively answer
• An artificial model replicating mechanisms of self-illusion can test hypotheses and reveal novel affordances for non-human intelligence.hypothesis0.793
  Methodological proposal to integrate knowledge from contemplative and cognitive science into AI/artificial life frameworks.