Indicators are merely intended to be credence-shifting; we do not need to be certain that a theory is correct for it to provide useful indicators.

Entities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.

• Indicators should avoid ambiguous terms and contested concepts, but without prematurely committing to precise specifications that anticipate all uncertainties.claim0.836
  Fourth guideline for deriving indicators; illustrated by algorithmic vs implementation-level recurrence distinction
• Applying theories to AI through the indicator method may reveal hidden ambiguities or unintended implications, motivating advocates to clarify their views.claim0.819
  Argues for productive bidirectional interaction between AI research and consciousness science
• Indicators based on potential background conditions for consciousness should be included to mitigate the narrow focus of theories on distinguishing conscious from unconscious states in humans.claim0.791
  Third guideline for deriving indicators; justifies PP-1 and AE-1/AE-2
• "[W]e must confess that perception, and what depends upon it, is inexplicable in terms of mechanical reasons... when inspecting its interior, we will find only parts that push one another, and we will never find anything to explain a perception."quote0.784
  Canonical illustration of the Hard Problem intuition that any functional/mechanical explanation faces an explanatory gap for perception
• GWT advocates should clarify whether the system built to implement all four GWT indicators is conscious, given that the indicator method implies a positive assessment.claim0.780
  Concrete example of how indicator method can prompt theoretical clarification from theory advocates
• Many of the indicator properties can be implemented in AI systems using current techniques.claim0.779
  Feasibility demonstrated in Section 3.1.
• 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.claim0.777
  First of four guidelines for deriving indicators; prevents over-restriction to human-specific features
• This theory doesn't have to correspond exactly to human behavior or social customs; we only need analogs useful for program correctness.claim0.774
  The speech act theory for programming can be simpler than human models.