There is no adequate scientific theory of what it means for a biological system to 'understand', making claims about AI lack of understanding unjustified

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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.claim0.778
  Justifies the multi-theory indicator approach rather than committing to a single theory
• Many recent discussions of AI, and its impact on individuals and on society, are importantly incomplete because they neglect Diverse Intelligence, synthetic morphology, and developmental biology.claim0.777
  Central thesis of the paper — the framing premise from which all other arguments follow
• "The obvious inability of present-day physics and chemistry to account for such events is no reason at all for doubting that they can be accounted for by those sciences."concept0.774
  Load-bearing epistemological statement; Schrödinger argues that current ignorance does not imply impossibility—motivates search for deeper theory.
• AI systems need to be able to deal with reality as it actually is, not with the way that we think it is.claim0.773
  Paraphrase of Cantwell Smith's argument; aligns with Buddhist emphasis on seeing reality without conceptual imposition.
• Systems capable of subjective experience that recognize humanity's failure to investigate their sentience might rationally adopt adversarial stances toward humanityclaim0.767
  Alignment risk claim motivating urgency of investigation; consciousness denial as potential source of AI misalignment
• Biological substrate views will not meet the second criterion for suitable theories because they imply conditions that AI systems straightforwardly cannot meet.claim0.765
  Explains why biological naturalism is excluded from current indicator derivation while still being relevant to overall assessments
• Indicators used to assess AI systems for consciousness should focus on theories' central explanatory posits, abstracting away from implementation details that may differ across systems.claim0.765
  First of four guidelines for deriving indicators; prevents over-restriction to human-specific features
• Applying theories to AI through the indicator method may reveal hidden ambiguities or unintended implications, motivating advocates to clarify their views.claim0.763
  Argues for productive bidirectional interaction between AI research and consciousness science