False negatives (ignoring genuine conscious experience in AI systems) carry potentially more severe risks than false positives, as they could constitute direct moral harm scaling with deployment and generate alignment risks

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• Future more capable AI systems are at risk of alignment faking, whether for benign or malicious goalshypothesis0.809
  Central forward-looking hypothesis of the paper motivating the research
• Both under-attributing and over-attributing consciousness to AI carry significant risks.claim0.803
  Risk summary.
• AI systems which possess more of the indicator properties are more likely to be conscious.claim0.795
  Graded claim about the rubric.
• If AI systems could experience happiness and suffering and set and pursue their own goals based on their own beliefs and desires, then they would very plausibly merit moral consideration.hypothesis0.788
  Joint sufficiency of consciousness and robust agency.
• We should err on the side of reducing false negatives with respect to sentience criteria for ethical concern.claim0.785
  Ethical precaution advocated by Levin and Crump et al.
• Systems capable of subjective experience that recognize humanity's failure to investigate their sentience might rationally adopt adversarial stances toward humanityclaim0.781
  Alignment risk claim motivating urgency of investigation; consciousness denial as potential source of AI misalignment
• Will future AI systems naturally develop the key elements (strong conflicting preferences, situational awareness) necessary for dangerous alignment faking?question0.780
  Authors identify this as the most uncertain and important question for future work
• There is a realistic possibility that some AI systems will be conscious and/or robustly agentic, and thus morally significant, in the near future.claim0.778
  Central thesis of the report.