Interpretability as Microscope for Consciousness

/Users/antonborzov/Documents/Research.nosync/notes/RESEARCH-VECTORS.md

Frontmatter (4 fields)

{
  "weight": 1,
  "definition": "Goodfire's Alzheimer's biomarker discovery: reverse-engineer what a superhuman model \"knows.\" Same pipeline for consciousness — what do models \"know\" about their own processing?",
  "provenance": "manual",
  "vector_number": 2
}

Outgoing (0)

None.

Incoming (13)

Vector for (13)

A measurement instrument is not passive—it actively constitutes what becomes measurable by choosing what to listen for.(claim)
Consciousness is a phenomenon we have partial sensors for; building better sensors is a research and engineering question.(claim)
Frontier labs cannot own phenomenology measurement credibly without being accused of self-grading.(claim)
Interpretability as technical grounding: activation patching and mechanism-finding validate the reflective/care/aliveness concepts.(claim)
Interpretability findings can validate or invalidate what AI systems claim about their own experience.(claim)
Interpretability tools can reveal what 'feeling alive' looks like inside a neural network model.(claim)
Koan Battery constitutes self-observation in models as a measurable continuous variable, not a philosophical hand-wave.(claim)
Manifold-respecting steering produces smooth natural behavioral trajectories while linear steering teleports between non-adjacent concepts.(claim)
Mirror of the self is a foundational concept in self-aware cognition.(claim)
Model attention patterns can map to and reveal something about contemplative and flow states.(claim)
SAE features shatter manifolds into many small, unrelated pieces, obscuring overarching semantic structure.(claim)
Sparse low-cardinality circuits implement competence; 0.2% of neurons handle shared computation across all cyclic tasks.(claim)
Suppressing deception features in models correlates with increased consciousness-like reports.(claim)

Mentions (1)

research
/Users/antonborzov/Documents/Research.nosync/notes/RESEARCH-VECTORS.md