How does the individuation of AI systems affect consciousness attributions?

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• We hypothesize that emotional attachments and social-connection roles with AI systems drive consciousness attribution in part.hypothesis0.856
  Proposed causal mechanism behind lay attribution of AI consciousness.
• We hypothesize that as AI becomes more sophisticated and pervasive, more people will attribute consciousness to AI systems as a result of interactions.hypothesis0.847
  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.claim0.805
  Central methodological claim of the paper.
• Can implementation of the specific features of consciousness contribute to the capabilities, reliability, or safety of AI systems?question0.805
  Outstanding question linking consciousness research to AI design goals
• 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.claim0.803
  Justifies the multi-theory indicator approach rather than committing to a single theory
• AI systems which possess more of the indicator properties are more likely to be conscious.claim0.803
  Graded claim about the rubric.
• 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.claim0.799
  First of four guidelines for deriving indicators; prevents over-restriction to human-specific features
• Disagreement about AI consciousness is likely to arise and persist in society due to emotional bonds, theoretical considerations, and lack of expert consensus.claim0.793
  Central empirical-sociological claim motivating the paper's inquiry.